novoenzyme_manual.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!pip install git+https://github.com/facebookresearch/esm.git -q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import torch\n",
    "# import esm\n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm.notebook import tqdm; tqdm.pandas()\n",
    "import gc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install -Uqq fastbook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastbook import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('df_combine.csv')\n",
    "test_df = pd.read_csv('test_combine.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Seed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def seed_everything(seed=42):\n",
    "    random.seed(seed)\n",
    "    os.environ['PYTHONHASHSEED'] = str(seed)\n",
    "    np.random.seed(seed)\n",
    "    torch.manual_seed(seed)\n",
    "    torch.cuda.manual_seed(seed)\n",
    "    torch.backends.cudnn.deterministic = True\n",
    "    \n",
    "seed_everything(seed=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Get esm feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading: \"https://dl.fbaipublicfiles.com/fair-esm/models/esm2_t33_650M_UR50D.pt\" to /root/.cache/torch/hub/checkpoints/esm2_t33_650M_UR50D.pt\n",
      "Downloading: \"https://dl.fbaipublicfiles.com/fair-esm/regression/esm2_t33_650M_UR50D-contact-regression.pt\" to /root/.cache/torch/hub/checkpoints/esm2_t33_650M_UR50D-contact-regression.pt\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "ESM2(\n",
       "  (embed_tokens): Embedding(33, 1280, padding_idx=1)\n",
       "  (layers): ModuleList(\n",
       "    (0): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (1): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (2): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (3): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (4): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (5): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (6): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (7): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (8): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (9): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (10): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (11): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (12): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (13): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (14): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (15): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (16): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (17): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (18): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (19): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (20): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (21): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (22): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (23): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (24): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (25): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (26): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (27): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (28): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (29): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (30): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (31): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "    (32): TransformerLayer(\n",
       "      (self_attn): MultiheadAttention(\n",
       "        (k_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (v_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (q_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (out_proj): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "        (rot_emb): RotaryEmbedding()\n",
       "      )\n",
       "      (self_attn_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "      (fc1): Linear(in_features=1280, out_features=5120, bias=True)\n",
       "      (fc2): Linear(in_features=5120, out_features=1280, bias=True)\n",
       "      (final_layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "    )\n",
       "  )\n",
       "  (contact_head): ContactPredictionHead(\n",
       "    (regression): Linear(in_features=660, out_features=1, bias=True)\n",
       "    (activation): Sigmoid()\n",
       "  )\n",
       "  (emb_layer_norm_after): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "  (lm_head): RobertaLMHead(\n",
       "    (dense): Linear(in_features=1280, out_features=1280, bias=True)\n",
       "    (layer_norm): LayerNorm((1280,), eps=1e-05, elementwise_affine=True)\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load ESM-2 model\n",
    "model, alphabet = esm.pretrained.esm2_t33_650M_UR50D()\n",
    "batch_converter = alphabet.get_batch_converter()\n",
    "model.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transferred model to GPU\n"
     ]
    }
   ],
   "source": [
    "if torch.cuda.is_available():\n",
    "    model = model.cuda()\n",
    "    print(\"Transferred model to GPU\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_feature(r,colname):\n",
    "    data = [('protein',r[colname])]\n",
    "    labels, strs, tokens = batch_converter(data)\n",
    "    with torch.no_grad(): \n",
    "        results = model(tokens.cuda(), repr_layers=[33], return_contacts=True)\n",
    "    rpr = results[\"representations\"][33].squeeze()\n",
    "    rpr=rpr[1 : len(r[colname]) + 1].mean(0).detach().cpu().numpy()\n",
    "    \n",
    "    del results, labels, strs, tokens, data #especially need to delete those on cuda: tokens, results\n",
    "\n",
    "    return rpr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_feature_df(df,colname):\n",
    "    series = df.progress_apply(lambda r: get_feature(r,colname), axis=1)\n",
    "    df_feature = pd.DataFrame(series.tolist())\n",
    "    return df_feature"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### In order to process esm, delete long sequence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['len'] = df.mut_seq.apply(len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.query('len < 1000').len.plot.hist(bins=200);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.query('len < 800')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "75586a6dc9d046528c46fe3b0299d0e1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/5139 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fedecc8049ea4587be36f8cbf410bc2f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/5139 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mut_feature = get_feature_df(df,'mut_seq')\n",
    "wt_feature = get_feature_df(df,'wt_seq')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = pd.read_csv('test_sub.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7dfb431f842e4a53af65789c009b2d65",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/2413 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "89f506b6fa124573ac01c3e06b1adfa8",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/2413 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_mut = get_feature_df(test,'mut_seq')\n",
    "test_wt = get_feature_df(test,'wt_seq')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       221\n",
       "1       221\n",
       "2       220\n",
       "3       221\n",
       "4       221\n",
       "       ... \n",
       "2408    221\n",
       "2409    221\n",
       "2410    221\n",
       "2411    221\n",
       "2412    221\n",
       "Name: mut_seq, Length: 2413, dtype: int64"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_combine.mut_seq.transform(len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_feature = test_wt - test_mut\n",
    "test_combine = pd.concat([test, test_feature],axis=1)\n",
    "test_combine['len'] = test_combine.mut_seq.transform(len)\n",
    "test_combine.to_csv('test_combine.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_combine.rename(columns={'pH':'pH2'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_df=test_combine.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_df.to_csv('test_combine.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'pd' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [1]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m test_df \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtest_combine.csv\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
     ]
    }
   ],
   "source": [
    "test_df = pd.read_csv('test_combine.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get feature differences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "diff_feature = wt_feature - mut_feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.reset_index(inplace=True) #make sure the index of two concat dfs are same\n",
    "df_combine = pd.concat([df, diff_feature], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine = pd.read_csv('with_esm_feature.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## Filter out data with dTm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine = df_combine.dropna(subset = 'Tm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Fill pH NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.mode.chained_assignment = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine['pH2'] = df_combine.groupby('group').pH.transform(lambda x: x.fillna(x.mean()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### for those groups that don't have pH or pH.mean() at all, fill with 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine.pH2.fillna(8, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_combine.pH2.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## Normalize Targets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine['y_max'] = df_combine.groupby('group').Tm.transform(lambda x: x/x.max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine['y_normalize'] = df_combine.groupby('group').Tm.transform(lambda x: (x-x.mean())/x.std() )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 52)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_combine.y_max.isna().sum(),df_combine.y_normalize.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_combine.y_max.plot.hist(bins=50);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_combine.y_normalize.plot.hist(bins=50);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interestingly, there are some groups with same Tm all the time (std=0), so filter out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([37, 66, 68, 69])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_combine[df_combine.groupby('group').Tm.transform(lambda x: x.std()==0)].group.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([37, 66, 68, 69])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_combine[df_combine.y_normalize.isna()].group.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine = df_combine.dropna(subset='y_normalize')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "37 in df_combine.group.to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4108, 1292)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_combine.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df.group!=33]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Check how many per group; remove group count < 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXkAAAEJCAYAAABxIVf8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAAc4klEQVR4nO3de5hdVZnn8e9Lwh0lIZQhJtHQEkF7bC6WiA8qjGlsLo6hG6XFHsnwxE7PTFRAezTd0xeldQYdm1vbw0yaiAkKCvTYiULbxBjaS5uYIglJICQpAiEpElJckgCBQOI7f6z3WDuHU3V2nXOqKrXy+zzPeWrvtddeZ+3bu9deZ+9d5u6IiEieDhnqCoiIyMBRkBcRyZiCvIhIxhTkRUQypiAvIpIxBXkRkYyNHOoKABx//PE+adKkoa6GiMiw8sADDzzt7m195TkggvykSZPo6OgY6mqIiAwrZrapXh5114iIZExBXkQkYwryIiIZU5AXEcmYgryISMYU5EVEMqYgLyKSsbpB3sxONrOVhc8uM7vKzI4zs4VmtiH+jo78ZmY3mVmnma0yszMGfjFERKSWug9Dufs64DQAMxsBdAHfB2YBi9z9WjObFeNfAC4AJsfn3cDN8bdPk2bd85vhx6+9qJ+LISIitfS3u2YK8Ki7bwKmAnMjfS5wcQxPBeZ5sgQYZWbjWlFZERHpn/4G+Y8Bd8TwWHffGsPbgLExPB7YXJhnS6Ttx8xmmFmHmXV0d3f3sxoiIlJG6SBvZocBHwbuqp7m6R/F9uufxbr7bHdvd/f2trY+368jIiIN6k9L/gJgubs/FeNPVbph4u/2SO8CJhbmmxBpIiIyyPoT5C+jp6sGYAEwLYanAfML6ZfHXTZnATsL3ToiIjKISr1q2MyOBs4D/qSQfC1wp5lNBzYBl0b6vcCFQCewG7iiZbUVEZF+KRXk3f1FYExV2jOku22q8zowsyW1ExGRpuiJVxGRjCnIi4hkTEFeRCRjCvIiIhlTkBcRyZiCvIhIxhTkRUQypiAvIpIxBXkRkYwpyIuIZExBXkQkYwryIiIZU5AXEcmYgryISMYU5EVEMqYgLyKSMQV5EZGMKciLiGRMQV5EJGMK8iIiGSsV5M1slJndbWaPmNlaM3uPmR1nZgvNbEP8HR15zcxuMrNOM1tlZmcM7CKIiEhvyrbkbwR+5O6nAKcCa4FZwCJ3nwwsinGAC4DJ8ZkB3NzSGouISGl1g7yZHQu8H5gD4O6vuPsOYCowN7LNBS6O4anAPE+WAKPMbFyL6y0iIiWUacmfCHQDt5rZCjO7xcyOBsa6+9bIsw0YG8Pjgc2F+bdEmoiIDLIyQX4kcAZws7ufDrxIT9cMAO7ugPfni81shpl1mFlHd3d3f2YVEZGSygT5LcAWd18a43eTgv5TlW6Y+Ls9pncBEwvzT4i0/bj7bHdvd/f2tra2RusvIiJ9qBvk3X0bsNnMTo6kKcDDwAJgWqRNA+bH8ALg8rjL5ixgZ6FbR0REBtHIkvk+DXzHzA4DNgJXkE4Qd5rZdGATcGnkvRe4EOgEdkdeEREZAqWCvLuvBNprTJpSI68DM5urloiItIKeeBURyZiCvIhIxhTkRUQypiAvIpIxBXkRkYwpyIuIZExBXkQkYwryIiIZU5AXEcmYgryISMYU5EVEMqYgLyKSMQV5EZGMKciLiGRMQV5EJGMK8iIiGVOQFxHJmIK8iEjGFORFRDKmIC8ikrFSQd7MHjez1Wa20sw6Iu04M1toZhvi7+hINzO7ycw6zWyVmZ0xkAsgIiK9609L/t+7+2nu3h7js4BF7j4ZWBTjABcAk+MzA7i5VZUVEZH+aaa7ZiowN4bnAhcX0ud5sgQYZWbjmvgeERFpUNkg78B9ZvaAmc2ItLHuvjWGtwFjY3g8sLkw75ZIExGRQTayZL73unuXmb0BWGhmjxQnurubmffni+NkMQPgTW96E9afmUVEpJRSLXl374q/24HvA2cCT1W6YeLv9sjeBUwszD4h0qrLnO3u7e7e3tbW1vgSiIhIr+oGeTM72sxeVxkGPgisARYA0yLbNGB+DC8ALo+7bM4Cdha6dUREZBCV6a4ZC3zfzCr5b3f3H5nZMuBOM5sObAIujfz3AhcCncBu4IqW11pEREqpG+TdfSNwao30Z4ApNdIdmNmS2omISFP0xKuISMYU5EVEMqYgLyKSMQV5EZGMKciLiGRMQV5EJGMK8iIiGVOQFxHJmIK8iEjGFORFRDKmIC8ikjEFeRGRjCnIi4hkTEFeRCRjCvIiIhlTkBcRyZiCvIhIxhTkRUQypiAvIpIxBXkRkYwpyIuIZKx0kDezEWa2wsx+GOMnmtlSM+s0s++Z2WGRfniMd8b0SQNUdxERqaM/LfkrgbWF8a8C17v7ScBzwPRInw48F+nXRz4RERkCpYK8mU0ALgJuiXEDPgDcHVnmAhfH8NQYJ6ZPifwiIjLIyrbkbwA+D/w6xscAO9x9b4xvAcbH8HhgM0BM3xn592NmM8ysw8w6uru7G6u9iIj0qW6QN7MPAdvd/YFWfrG7z3b3dndvb2tra2XRIiISRpbIczbwYTO7EDgCeD1wIzDKzEZGa30C0BX5u4CJwBYzGwkcCzzT8pqLiEhddVvy7v5n7j7B3ScBHwN+4u5/BCwGPhLZpgHzY3hBjBPTf+Lu3tJai4hIKc3cJ/8F4LNm1knqc58T6XOAMZH+WWBWc1UUEZFGlemu+Q13vx+4P4Y3AmfWyPMy8NEW1E1ERJqkJ15FRDKmIC8ikjEFeRGRjCnIi4hkTEFeRCRjCvIiIhlTkBcRyZiCvIhIxhTkRUQypiAvIpIxBXkRkYwpyIuIZExBXkQkYwryIiIZU5AXEcmYgryISMYU5EVEMqYgLyKSMQV5EZGMKciLiGSsbpA3syPM7Fdm9qCZPWRmX4r0E81sqZl1mtn3zOywSD88xjtj+qQBXgYREelFmZb8HuAD7n4qcBpwvpmdBXwVuN7dTwKeA6ZH/unAc5F+feQTEZEhUDfIe/JCjB4aHwc+ANwd6XOBi2N4aowT06eYmbWqwiIiUl6pPnkzG2FmK4HtwELgUWCHu++NLFuA8TE8HtgMENN3AmNqlDnDzDrMrKO7u7uphRARkdpKBXl33+fupwETgDOBU5r9Ynef7e7t7t7e1tbWbHEiIlJDv+6ucfcdwGLgPcAoMxsZkyYAXTHcBUwEiOnHAs+0orIiItI/Ze6uaTOzUTF8JHAesJYU7D8S2aYB82N4QYwT03/i7t7COouISEkj62dhHDDXzEaQTgp3uvsPzexh4Ltm9mVgBTAn8s8BbjOzTuBZ4GMDUG8RESmhbpB391XA6TXSN5L656vTXwY+2pLaiYhIU/TEq4hIxhTkRUQydkAH+Umz7mHSrHuGuhoiIsPWAR3kRUSkOQryIiIZU5AXEcmYgryISMYU5EVEMqYgLyKSMQV5EZGMKciLiGRMQV5EJGMK8iIiGVOQFxHJmIK8iEjGFORFRDKmIC8ikjEFeRGRjCnIi4hkTEFeRCRjdYO8mU00s8Vm9rCZPWRmV0b6cWa20Mw2xN/RkW5mdpOZdZrZKjM7o5UV1n+LEhEpr0xLfi/wOXd/O3AWMNPM3g7MAha5+2RgUYwDXABMjs8M4OaW11pEREqpG+Tdfau7L4/h54G1wHhgKjA3ss0FLo7hqcA8T5YAo8xsXKsrLiIi9fWrT97MJgGnA0uBse6+NSZtA8bG8Hhgc2G2LZEmIiKDrHSQN7NjgH8ErnL3XcVp7u6A9+eLzWyGmXWYWUd3d3d/ZhURkZJGlslkZoeSAvx33P3/RfJTZjbO3bdGd8z2SO8CJhZmnxBp+3H32cBsgPb2dn+6wQUo/gj7+LUXNViKiEieytxdY8AcYK27X1eYtACYFsPTgPmF9MvjLpuzgJ2Fbh0RERlEZVryZwOfAFab2cpI+3PgWuBOM5sObAIujWn3AhcCncBu4IpWVlhERMqrG+Td/eeA9TJ5So38Dsxssl4iItICWT7xqgemRESSLIO8iIgkCvIiIhlTkBcRyZiCvIhIxhTkRUQypiAvIpIxBXkRkYwpyIuIZOygCfJ6QEpEDkYHTZAXETkYHdRBXq17EcndQR3kRURypyAvIpIxBXkRkYyV+vd/Bwv9K0ERyY1a8nXox1kRGc4U5BugwC8iw4WCvIhIxhTkRUQyVjfIm9k3zWy7ma0ppB1nZgvNbEP8HR3pZmY3mVmnma0yszMGsvIiItK3Mi35bwHnV6XNAha5+2RgUYwDXABMjs8M4ObWVFNERBpRN8i7+0+BZ6uSpwJzY3gucHEhfZ4nS4BRZjauRXUVEZF+arRPfqy7b43hbcDYGB4PbC7k2xJpIiIyBJr+4dXdHfD+zmdmM8ysw8w6uru7m62GiIjU0GiQf6rSDRN/t0d6FzCxkG9CpL2Gu89293Z3b29ra2uwGiIi0pdGg/wCYFoMTwPmF9Ivj7tszgJ2Frp1RERkkNV9d42Z3QGcCxxvZluAvwauBe40s+nAJuDSyH4vcCHQCewGrhiAOouISEl1g7y7X9bLpCk18jows9lKDTd6sZmIHKj0xKuISMYU5AdIrZeYlU0TEWkVBXkRkYzpn4YcYNS/LyKtpJb8MKAuHRFplIK8iEjG1F0zTFVa9pUuHXXziEgtaslnTHfziIha8lLqqqA6j4gMDwry0rBGTw46YYgMHnXXyAFB3UgiA0MteTkg6YdkkdZQS16GDbX2RfpPQV5EJGPqrpFhTc8LiPRNQV6yp7t+5GCmIC/SC50cJAcK8iIt1tfJoZgmMhgU5EWGSJmrAj19LM1SkBfJQH9ODrXSdMLIl4K8iOxHVxN5GZAgb2bnAzcCI4Bb3P3agfgeETlwtPJqolXvRWplHYarlgd5MxsB/D1wHrAFWGZmC9z94VZ/l4jIYBmuJ5qBaMmfCXS6+0YAM/suMBVQkBcRaUIjd2mZu7e0Emb2EeB8d/9kjH8CeLe7f6oq3wxgRoyeDKwDjgeeriqy0bTBnk91UB1Uh+FTVi51eLO7t9EXd2/pB/gIqR++Mv4J4Bsl5+1oVdpgz6c6qA6qw/ApK7c69PUZiBeUdQETC+MTIk1ERAbZQAT5ZcBkMzvRzA4DPgYsGIDvERGROlr+w6u77zWzTwH/QrqF8pvu/lDJ2We3MG2w51MdVAfVYfiUlVsdetXyH15FROTAoX8aIiKSMQV5EZGMKciLiGRsSF9QZmankJ6GHR9JXcACd19bI994YKm7v2BmZwIOjAGeAM4HHnH3ewvzzHP3ywvjMyL/A8DPgFnAJcBPgT9z952Rr3JH0JPu/mMz+3iUf0zU71VgPXC7u+9q5frIgZm9wd23l8g3xt2fGYw6ydAZ7vtD2foPZNlNr5uyN9S3+gN8AVhJCrb/MT6zKmmFfJ8hPQ27HHgcuB1YAnQA24CfAI8AzwBrSbdr/gDYF8MLgD8GXgK+BPwCWArcALwA7CI9OfZfgTbgO8D3oozbgAeB1fH920nv5fkK6TUN5w7g+nlDiTxjGij3WODaWGfPFtbbtcCoQr7XA/+TdGL7eKSdANwc62MM8NVYD/8EvC3SngJGA8fFd82J9faPwFigHdgIvAzsAC6LstuBxcC3Sc9ZLAR2xvc/GsPdse2/BfwIWBWffwb+M3BolDUC+JPYZmdH2lHA52O+I4D/FPvG14BjIs/jheU/FPiLKP/6mP8kUqNgVyzT/yWd/P+B9J6mrbE+lsc+9LcDVM/fAdZX1XMrMB9oKyzDbwHfBL7cRz2/C1xEnX2CA3d/WAbc04K6f7Gq7seRjv3ngNOB4/o4ftYBv4x1+fFC2X8fy1ur7LLrZk98RxdwTkOxZAiD/HpiZ69KPwzYUBhfHTvoE8AkYDdwFelg2BcbcDlwR2z8c4BzSS3uc+KzjJ6D4mjgpRheQeqyejRWcDfwPDANGBUbYTXpYLQYvj/m/e2YPhA710dJJ7TRwJt72fiNHhivxLq8srCOzyO9NfSXwBnxWQTcGsu2IL77X4BPR3mrgF9HWc8ALwKPka6wHov63UIKMI8AV8cyLgbeFXnmkHbiXwGbgD8CLgM2k56cnk8KHA8AnwX+knTyXUcK9BOAfwd8kBTMvh/r7zbg7lg3DwDXAXeSgm53LNsrUec9pH3l+aj786Qg/rfxHY+Rgvw8UjD5fVKgvy620Zqo/3Wkbb0ZuIbU+NgS5TRTz2+Q9vk9UefnSfv9vhjeE/XsJh1Te6KM3yddsf4XUuOpt3qeF9tvPnBC7A9n8Np94kDdH34W4zc2WfcvRP2LdX811vNe0rF2NXB/5D2hcPz8MJZjRZS/LfLOIjUua5Vddt10AV8Hnox5rwbeOFyC/COk9y4U01aRAuXL9LR+XiYFxD2R50FSK+c6YHekHRIL/zxwWqTtIQXJMaRW/13AFTHtGVJAXA68FVhWaBVtIrXCno7yHgYOJ7Wq1hGPE8dOso3mD4xaO0Al8DxGCjitPDCeBiYDc4H/EXXfRwpKu6PsxbHsi+k5If530pXPmFhvTwCfi23xDmBlZb0XtmclbS2pa3AlsCTSlhdO4u8jBalt8Z3PVLZ15WQcf5eRAtkhpO65St030nNQVtbfY6SgOJJ0T/GO2I4r4ntuIgXuscCqWnUn7Q/rSCf4VfTsJysK++sTlfkLDYclUc/DgbVN1tMKdX248B2PVdVzReRdQ3qVyL3xPbeSTi4161locK0tTKvsD4vp2ScO1P1hHa/dH/pd90iv1L9S1vLCen4f8L9JAX8xMKPGcq2Lv0+SegzGAK/UKrvsuqmsl5j2aNRhW3UdDtQgfz7QSbqEnR2fPbGzXE5qwb45VtaFpD5ySF0tryPt9PsK5R0bO8hdpNbPXnoOqo2kYP6tGH6RdADsAf4VOLVQztWR5wlSV9F6UgB+Nna8yomiE/hpswdGiZ2r1QfGTlJ3wAmF71tL6g74cWF51pIOns2FtCeAh0gnky9H2oRY592xXfaSTiafi/VopJPafbGTfpF0IlxP6j67Lcr5JWmf+Eqso4uBfwM+RTpJf5h0glxCutKpHFAbSPvJH5J+s6GwXMW6byXtSxtID+gBvDO2WVcs66vAH5B+q6kE56+Q9pu1wJ+TriJXk1ppPyedNNcCbyF156wntfQr9Xy42XoW6vo8aZ/cGNu5WM/lxe1dOAH8FSkY1qxn5LuPdFU6NsbXAGeRGiA/PsD3h/tI+3Nns3Uv1H8HqRH5ILCxKm7dR2p131FIWx/7Q+X7HiR1sz0E7Oil7LLrZjupN6K4bkbEurn1gA7yUdlDYoNcEp8FwPur8kwgBaTbY/zwwrSzC8PHA++I4YuIVmqN7xwLXEA6aN7TS543EpdEpG6bq2IjnlK1sT9PCw6MwnLujB2gi3RiGYgDYxGpZf8I6cT0LKlb4R+Ifsco62vA7wIXF9KuiTI3VK2vk0iBaQkpEP114dMWef6A1L2xghQknyS9hbTSP30q6aD9Z+CUWL5dpBPmLlJAPZnUZfdP8T3rScHpWdLV14lR1rdjPXy6UMdbgJnAqzXq/ijpsn83qeVb+VS27ZWxbSpXd4/T0xf7XlJQf5V00D4FvLtQz91Rz+1N1vMtsQ4+E99RrOvYqMMJwKLCPFOijmt7qedZhXWwlLRPPBfL+ChpPzluiPaH06i/P7yVdLV+UyxPq+p+N+lYeRrYVjV9ND3Hz3P0dNV+t/B915C6mM9n/67nYtll180O0lXZb9ZNv+PsUAb54fyp2tjPVu1co5vcuTZX7QD1DoyRMb1MoHxrTLsE+NPC959COpEd05+0GJ8Sy3Qkqe+50bLeVimrkOdtNeZ7NynYjQHOjuW8Mqa9ndQ6ugp4V5206yPNSFdCf0W6kutrvt8mnXyvrkr7uxp1uDDGx8Tn21XbfF6N/arXNHqeUB9HXKk1UNYP2f/H2Vp53hfL+MEYf28szwcLeeqmRTl/UWK+/b6vj7Jq5bmhsr+QfqebQ7oq/irp5HcN6QR+Pelq/8he0r5UlXYU6TeTxVVlrSF1mRxbqMdngIm9jfeS50jSbyP18r2mrP5+9FqDAWBmV7j7rb2N10szsyOBt7j7mmbLqlH2Z0gtxUrrbjqpG2EmaUfeQWq5vol0BdBX2kLg/VHWBcClvcxXpvyFpAP5kUJZbybd9XRCYb7TYvo7SC24PyT1SY8idXPtI/2g9S7Sie020kmhOq16vr2xqop5ziyZVqus8aS7tbaTul7OZP/3gi+L5aiM/4p0simTVl3Wr0hdmo3M9wFS6/5n7v5hM/sk6aT5NVJf/jbSVcTxpKvPH5BarjNrpN1QNd9vxTqo5HmatM2Pr0qbWZWvP2W9MdbvDyLPJaTG0LmkLpP5pNu055H2madJjZ4yabXK+iTpN7RXSD/83kVq3L0Yf+8g3XzxQmH8LlL3bjHPnTXmq853O+kEs19Z7t5NfzRzhtCn9ofoa+9tvJm0Zucj7laK4S5SN86TpMvLFaRuhrJpu4H/FmU9NIhljSD1N++KvCNId6tU7rZaTbqLanXkqZXW6Hxly6q+42sD6U6LK0mts3NJwfW+SDunH2mNllVrvq2Rfk6s+2XA6hg+OrZLW2yDyjIv6yWt0fmaKWttIW05+/+AXLkxo/K7xUp6fruom9ZLWSt47R15u0gngamR9irpauJ/kU4atfKUTatV1o9IdwC+rkw8GtKHoYYzM1tVlTS5MHx4TJ9cNU7JtEbLKjPfZODfzMxILaqTSQf6NaTugMfN7NySaZuAKWY2jrQzlp2vmbKeJO3wkA403H0f8KyZ7XH3XWa2191fNLN9wKO10hqdrx9ltZOC6YdI/fknkw7QD5FOZivNbDOpa+1DwL+WTWu0rF7me4kURFeZ2RjSFcCvzWw08US8u3eb2SGk25s9tsdr0hqdr8my1pCu+vaSfvCcaGZXkH4TeDG2wxozmxX71Zqyab2U5aSu1WfdfbqZHUq6+vw94Hfdvc3MTid16VxG6q59Y408teYrW9YFMf510omub0PZ4h3OH9IPPafRcxdQd6z8s2NaJe3CwnjZtEbLKjPfLyLPJHruWFpMPEBWWL66aaQ7U95J4U6nQShrKemBtX2kALCU1H96LD0tsqWkLp7lwCG10hqdr2xZke9Y9r/j6wl67j75Bj1XVw2ltWo+0u88xTvRNsffx0l3oI2L4cdifGMvaY3O10xZx5J+wN4T26HyzMNLse4rt6tuizKX9jOtuqxad+StiL9HFcdrpVXGy6bVKqu38V5j1VAHy+H6IV1KvbfWOD13As0h9XvfXp2vr7RGyyozH3G3UlWeyh1MxbuV6qZVlXX2IJV1eFWeynjx7qrDi+O10hqdr2xZNcre746v6vFm0lo5X1X+o4g7gWqNl01rdL5+lvUO0o0H7yT9zvP64njkayitavw1d+QBb+1rvJm0Wnn6+9EPryIiGTtkqCsgIiIDR0FeRCRjCvIiIhlTkBcpMDPdVixZUZCXg4qZ/aWZrTOzn5vZHWb2p2Z2v5ndYGYdwJVmNsXMVpjZajP7ppkdHvM+bmbHx3C7md0fw180s9vM7JdmtsHM/njollBkf2q1yEHDzN5FelT9VNJrCJaTXsEMcJi7t5vZEaQnQKe4+3ozm0d6J/sNdYr/HdIL6o4GVpjZPe7+5AAshki/qCUvB5Ozgfnu/rK7P0960Krie/H3ZNJrntfH+FzS+3nqme/uL7n706SHuM6sN4PIYFCQF0leLJFnLz3HzBFV06ofONEDKHJAUJCXg8kvgP9gZkeY2TGkd7hUWwdMMrOTYvwTpMfYIT1W/84YvqRqvqlR7hjSe3eWtbLiIo1SkJeDhrsvI/1jmlWkF3etJr08rJjnZeAK4C4zW016rez/iclfAm6MH2j3VRW/itRNswT4G/XHy4FCrzWQg4qZHePuL5jZUaT/lDTD3Zc3WeYXgRfc/eutqKNIK+nuGjnYzDazt5P61Oc2G+BFDnRqyYuIZEx98iIiGVOQFxHJmIK8iEjGFORFRDKmIC8ikjEFeRGRjP1/NGBdPEabm7AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_combine.groupby('group').mut_seq.count().plot.bar();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine = df_combine[df_combine.groupby('group').mut_seq.transform(lambda x: x.count()>=20)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### check the distribution of y_normalize after filter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_combine.y_normalize.plot.hist(bins=50);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Redefine group number using ngroup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['group'] = df.groupby(['group']).ngroup()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('df_combine.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('df_combine.csv')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Get groups with constant pH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "group  pH2 \n",
       "0      1.99    False\n",
       "       2.00     True\n",
       "       2.02    False\n",
       "       2.03    False\n",
       "       2.10    False\n",
       "               ...  \n",
       "36     8.00    False\n",
       "37     7.00     True\n",
       "38     6.00     True\n",
       "39     6.00    False\n",
       "       7.00    False\n",
       "Name: mut_seq, Length: 246, dtype: bool"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['group','pH2']).mut_seq.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['group_pH'] = df.groupby(['group','pH2']).ngroup()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.group_pH.sort_values().unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### remove groups with count <20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAD4CAYAAAAD6PrjAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAAR+0lEQVR4nO3dfaxkdX3H8fdHwGdaoaxbumAvmq12rRW3K5L4UK2pwlpd6APFtEoNdU0KiaY2cdGm8g+JbapWGyVCJIL1CavItmArEKPxD8CFIo9SVoHCurLrQwQfAoLf/jHnHiZ479259865Z+6d9yuZ3HN+55yZ72/OzHzueZgzqSokSQJ4XN8FSJImh6EgSWoZCpKklqEgSWoZCpKk1sF9F7AcRxxxRM3MzPRdhiStKtddd933qmrdXNNWdSjMzMywa9euvsuQpFUlyd3zTets91GSo5N8OcmtSW5J8tam/ewke5Lc0Ny2Di1zVpLdSW5P8uquapMkza3LLYWHgbdX1fVJDgWuS3JFM+39VfXPwzMn2QScCjwX+A3gyiS/VVWPdFijJGlIZ1sKVbW3qq5vhh8AbgM2LLDINuDTVfVgVd0J7AaO66o+SdIvW5Gzj5LMAC8ArmmazkxyY5ILkhzWtG0A7hla7F7mCJEk25PsSrJr//79XZYtSVOn81BI8lTgc8Dbqup+4FzgWcCxwF7gvYu5v6o6r6q2VNWWdevmPHguSVqiTkMhySEMAuETVfV5gKq6r6oeqapfAOfz6C6iPcDRQ4sf1bRJklZIl2cfBfgocFtVvW+o/cih2U4Gbm6GdwKnJnlCkmOAjcC1XdUnSfplXZ599GLgDcBNSW5o2t4JvD7JsUABdwFvAaiqW5JcDNzK4MylMzzzSJJWVmehUFVfAzLHpMsXWOYc4JyuapIkLcxrH2ksZnZc1ncJksbAUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLLUFAnZnZc1ncJkpbAUJAktQwFSVLLUJAktQwFSVLLUJAktToLhSRHJ/lykluT3JLkrU374UmuSHJH8/ewpj1JPphkd5Ibk2zuqjZJ0ty63FJ4GHh7VW0CjgfOSLIJ2AFcVVUbgauacYATgY3NbTtwboe1SZLm0FkoVNXeqrq+GX4AuA3YAGwDLmxmuxA4qRneBlxUA1cDT0tyZFf1SZJ+2YocU0gyA7wAuAZYX1V7m0nfBdY3wxuAe4YWu7dpe+x9bU+yK8mu/fv3d1e0JE2hzkMhyVOBzwFvq6r7h6dVVQG1mPurqvOqaktVbVm3bt0YK5UkdRoKSQ5hEAifqKrPN833ze4Wav7ua9r3AEcPLX5U0yZJWiFdnn0U4KPAbVX1vqFJO4HTmuHTgEuH2t/YnIV0PPCjod1MkqQVcHCH9/1i4A3ATUluaNreCbwHuDjJ6cDdwCnNtMuBrcBu4KfAmzqsTZI0h85Coaq+BmSeya+cY/4CzuiqHknSgfmNZklSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlSa6RQSPK8rguRJPVv1C2FDye5NsnfJPnVURZIckGSfUluHmo7O8meJDc0t61D085KsjvJ7Ulevch+SJLGYKRQqKqXAn8BHA1cl+STSf7wAIt9DDhhjvb3V9Wxze1ygCSbgFOB5zbLfDjJQSP2QZI0JiMfU6iqO4C/B94B/D7wwSTfTPLH88z/VeAHI979NuDTVfVgVd0J7AaOG7U2adbMjsv6LkFa1UY9pvC7Sd4P3Ab8AfDaqvrtZvj9i3zMM5Pc2OxeOqxp2wDcMzTPvU3bXLVsT7Irya79+/cv8qElSQsZdUvhX4HrgedX1RlVdT1AVX2HwdbDqM4FngUcC+wF3ruIZWke87yq2lJVW9atW7fYxSVJCzh4xPleA/ysqh4BSPI44IlV9dOq+vioD1ZV980OJzkf+M9mdA+D4xWzjmraJEkraNQthSuBJw2NP7lpW5QkRw6NngzMnpm0Ezg1yROSHANsBK5d7P1LkpZn1C2FJ1bVj2dHqurHSZ680AJJPgW8HDgiyb3Au4GXJzkWKOAu4C3N/d2S5GLgVuBh4IzZrRJJ0soZNRR+kmTz7LGEJL8H/GyhBarq9XM0f3SB+c8BzhmxHmleMzsu4673vKbvMqRVadRQeBvw2STfAQL8OvDnXRUlSerHSKFQVV9P8hzg2U3T7VX18+7KkiT1YdQtBYAXAjPNMpuTUFUXdVKVJKkXI4VCko8z+H7BDcDsAeACDAVJWkNG3VLYAmyqquqyGElSv0b9nsLNDA4uS5LWsFG3FI4Abk1yLfDgbGNVva6TqiRJvRg1FM7usghJ0mQY9fcUvsLgG8iHNMNfZ3CBvKnmZZolrTWjXjr7zcC/Ax9pmjYAX+ioJklST0Y90HwG8GLgfmh/cOfpXRUlSerHqKHwYFU9NDuS5GAG31OQJpK79qSlGTUUvpLkncCTmt9m/izwH92VJUnqw6ihsAPYD9zE4HLXl7O4X1yTJK0Co14Q7xfA+c1NkrRGjXrtozuZ4xhCVT1z7BVJknqzmGsfzXoi8GfA4eMvR5LUp1G/vPb9odueqvoXwJ+2kqQ1ZtTdR5uHRh/HYMthMb/FIElaBUb9YH/v0PDDDC55ccrYq5Ek9WrUs49e0XUhkqT+jbr76G8Xml5V7xtPOZKkPi3m7KMXAjub8dcC1wJ3dFGUJKkfo4bCUcDmqnoAIMnZwGVV9ZddFSZJWnmjXuZiPfDQ0PhDTZskaQ0ZdUvhIuDaJJc04ycBF3ZSkSSpN6OefXROki8CL22a3lRV/9NdWZKkPoy6+wjgycD9VfUB4N4kx3RUkySpJ6P+HOe7gXcAZzVNhwD/1lVRkqR+jLqlcDLwOuAnAFX1HeDQroqSJPVj1FB4qKqK5vLZSZ7SXUk6EH9qUlJXRg2Fi5N8BHhakjcDV+IP7kjSmnPAs4+SBPgM8BzgfuDZwD9U1RUd1yZJWmEHDIWqqiSXV9XzgJGDIMkFwB8B+6rqd5q2wxkEzAzNlVar6odN8HwA2Ar8FPirqrp+kX2RJC3TqLuPrk/ywkXe98eAEx7TtgO4qqo2Alc14wAnAhub23bg3EU+liRpDEYNhRcBVyf5VpIbk9yU5MaFFqiqrwI/eEzzNh79JvSFDL4ZPdt+UQ1czeDYxZEj1iZJGpMFdx8leUZV/R/w6jE93vqq2tsMf5dHr5+0AbhnaL57m7a9SJJWzIGOKXyBwdVR707yuar6k3E9cHOsoha7XJLtDHYx8YxnPGNc5UiSOPDuowwNP3MMj3ff7G6h5u++pn0PcPTQfEc1bb+kqs6rqi1VtWXdunVjKEmSNOtAoVDzDC/VTuC0Zvg04NKh9jdm4HjgR0O7mSRJK+RAu4+en+R+BlsMT2qGacarqn5lvgWTfAp4OXBEknuBdwPvYfBFuNOBu4FTmtkvZ3A66m4Gp6S+aWndkSQtx4KhUFUHLfWOq+r180x65RzzFnDGUh9LkjQei7l0tiRpjTMUJEktQ0GS1DIUJEktQ0GS1DIUpIY/XiQZCpKkIYaCJKllKEhj5C4orXaGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIklqGgiSpZShIq4jfmFbXDAVpzPzg1mpmKEiSWoaCJKllKEiSWoaCJKllKEiSWoaCJKllKEiSWobCGuc585IWw1CQJLUMBUlSy1CQJLUMBUlSy1CQJLUMBUlS6+A+HjTJXcADwCPAw1W1JcnhwGeAGeAu4JSq+mEf9UnStOpzS+EVVXVsVW1pxncAV1XVRuCqZlyStIImaffRNuDCZvhC4KT+SpGk6dRXKBTwpSTXJdnetK2vqr3N8HeB9XMtmGR7kl1Jdu3fv38lapWkqdHLMQXgJVW1J8nTgSuSfHN4YlVVkpprwao6DzgPYMuWLXPOI0laml62FKpqT/N3H3AJcBxwX5IjAZq/+/qoTdLyeL2t1W3FQyHJU5IcOjsMvAq4GdgJnNbMdhpw6UrXJml+fthPhz52H60HLkky+/ifrKr/SvJ14OIkpwN3A6f0UJskTbUVD4Wq+jbw/Dnavw+8cqXrkSQ9apJOSZUk9cxQkCS1DAVJUstQkCS1DAVJUstQkLTq+R2K8TEUJEktQ0GS1DIUJEktQ0GSxmCtHNcwFCRphU1ygBgKkqSWoSBNiEn+71HTw1CQtGYYrMtnKEjSMq2lMDIUNPHW0htO02e1vX4NBUkTY7V9gK5FhsIa4ZtJ0jgYCpKklqEgSWoZCpKklqEwBTzeIE2Ocbwfu3xPGwqS1jz/MRqdoSBJahkKkibOavjPfik1HmiZSei3oSBNuUn4IFqLVuvzaiiskNX6ApE0XQyFBUziB/lyaprE/qyELvrtc7m6H2MSzdfvlX4+DIUDWA0v0NVQo6TVwVCQJLUMBa1abiFpnHw9DRgK8s2gZVvoNTSz4zJfY6uIodCztfxm6eI87knSda3Lvf/V9FxOksc+b9P2PBoKYzTqi2elXmST/mKe7z/IxdZ9oP9SF3Mf46jnQMv1uV6m/QNv1jhfY2vNxIVCkhOS3J5kd5IdK/W4k7aJOwn/ZU/S8zFOk9avSXvtdWUcgTQJ74u1bqJCIclBwIeAE4FNwOuTbOrisbr6AF3qC7+P/yoX+jAatX0lP9BWY+gt94NwKethXB+ca/07CYvt8/C0Pl+LXT9nExUKwHHA7qr6dlU9BHwa2NZzTcv+IFzq9U76esPM92YZ5xfnuvpwXO79zTffKPN3tb6W8tx1+ZpdqJ6u/pMfZVfjJAbbajwulKpa8QedT5I/BU6oqr9uxt8AvKiqzhyaZzuwvRl9NnD7Eh/uCOB7yyh3NZvWvtvv6WK/5/ebVbVurgkHj7+eblXVecB5y72fJLuqassYSlp1prXv9nu62O+lmbTdR3uAo4fGj2raJEkrYNJC4evAxiTHJHk8cCqws+eaJGlqTNTuo6p6OMmZwH8DBwEXVNUtHT3csndBrWLT2nf7PV3s9xJM1IFmSVK/Jm33kSSpR4aCJKk1laHQ16U0+pDkriQ3Jbkhya6m7fAkVyS5o/l7WN91LleSC5LsS3LzUNuc/czAB5v1f2OSzf1Vvjzz9PvsJHuadX5Dkq1D085q+n17klf3U/XyJTk6yZeT3JrkliRvbdrX9DpfoN/jW+dVNVU3BgewvwU8E3g88A1gU991ddjfu4AjHtP2T8COZngH8I991zmGfr4M2AzcfKB+AluBLwIBjgeu6bv+Mff7bODv5ph3U/N6fwJwTPM+OKjvPiyx30cCm5vhQ4H/bfq3ptf5Av0e2zqfxi2FibyUxgrbBlzYDF8InNRfKeNRVV8FfvCY5vn6uQ24qAauBp6W5MgVKXTM5un3fLYBn66qB6vqTmA3g/fDqlNVe6vq+mb4AeA2YANrfJ0v0O/5LHqdT2MobADuGRq/l4Wf1NWugC8lua65RAjA+qra2wx/F1jfT2mdm6+f0/AaOLPZTXLB0O7BNdnvJDPAC4BrmKJ1/ph+w5jW+TSGwrR5SVVtZnDl2TOSvGx4Yg22Mdf8ecnT0s/GucCzgGOBvcB7e62mQ0meCnwOeFtV3T88bS2v8zn6PbZ1Po2hMFWX0qiqPc3ffcAlDDYd75vddG7+7uuvwk7N1881/Rqoqvuq6pGq+gVwPo/uLlhT/U5yCIMPxk9U1eeb5jW/zufq9zjX+TSGwtRcSiPJU5IcOjsMvAq4mUF/T2tmOw24tJ8KOzdfP3cCb2zOSDke+NHQLodV7zH7yk9msM5h0O9TkzwhyTHARuDala5vHJIE+ChwW1W9b2jSml7n8/V7rOu876PpPR3B38rgqP23gHf1XU+H/XwmgzMPvgHcMttX4NeAq4A7gCuBw/uudQx9/RSDzeafM9hvevp8/WRwBsqHmvV/E7Cl7/rH3O+PN/26sflQOHJo/nc1/b4dOLHv+pfR75cw2DV0I3BDc9u61tf5Av0e2zr3MheSpNY07j6SJM3DUJAktQwFSVLLUJAktQwFSVLLUJAktQwFSVLr/wHH/CRhP8cV4gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.group_pH.plot.hist(bins=500);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.groupby('group_pH').mut_seq.transform(lambda x: x.count()>=20)].group_pH.plot.hist(bins=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df.groupby('group_pH').mut_seq.transform(lambda x: x.count()>=20)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('df_combine2.csv',index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define feature columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "esm_feature = [str(i) for i in range(1280)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "others = ['pH2','len']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = esm_feature + others"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Make Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data import Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MyDataset(Dataset):\n",
    "    def __init__(self,df, features,target,group,train=True):\n",
    "        self.df = df\n",
    "        self.features = features\n",
    "        self.target = target\n",
    "        self.train=train\n",
    "        self.group=group\n",
    "    def __len__(self): return len(self.df[self.group].unique())\n",
    "    def __getitem__(self, idx): # add shuffle and random choice\n",
    "        df_frac = self.df[self.df[self.group]==idx].sample(n=20) if self.train else self.df[self.df[self.group]==idx]#randomly pick 20\n",
    "        \n",
    "        feature = torch.as_tensor(df_frac.loc[:,self.features].values*1000,dtype=torch.float32)\n",
    "        label = torch.as_tensor(df_frac.loc[:,self.target].values,dtype=torch.float32)\n",
    "        return feature,label"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = MyDataset(df,features,'y_normalize','group_pH',train=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "42"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "x,y=dataset[41]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TestDataset(Dataset):\n",
    "    def __init__(self,df, features):\n",
    "        self.df = df\n",
    "        self.x = df.loc[:,features].values*1000\n",
    "        # self.y = df.loc[:,target].values\n",
    "    def __len__(self): return len(self.df)\n",
    "    def __getitem__(self, idx):\n",
    "        feature = torch.as_tensor(self.x[idx],dtype=torch.float32)\n",
    "        # label = torch.as_tensor(self.y[idx],dtype=torch.float32)\n",
    "        return feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [],
   "source": [
    "x,y=dataset[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([20, 1282])"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(708, 1293)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.group==0].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DataLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "dl = DataLoader(dataset,bs=8,shuffle=True,num_workers=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y = dl.one_batch()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/lazy.py:178: UserWarning: Lazy modules are a new feature under heavy development so changes to the API or functionality can happen at any moment.\n",
      "  warnings.warn('Lazy modules are a new feature under heavy development '\n"
     ]
    }
   ],
   "source": [
    "model1 = nn.Sequential(nn.LazyLinear(500),\n",
    "                      nn.LazyBatchNorm1d(),\n",
    "                      nn.LazyLinear(200),\n",
    "                      nn.LazyBatchNorm1d(), \n",
    "                      nn.LazyLinear(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Model2(Module):\n",
    "    def __init__(self, num_features, num_targets, hidden_size):\n",
    "        cha_1 = 256\n",
    "        cha_2 = 512\n",
    "        cha_3 = 512\n",
    "\n",
    "        cha_1_reshape = int(hidden_size/cha_1)\n",
    "        cha_po_1 = int(hidden_size/cha_1/2)\n",
    "        cha_po_2 = int(hidden_size/cha_1/2/2) * cha_3\n",
    "\n",
    "        self.cha_1 = cha_1\n",
    "        self.cha_2 = cha_2\n",
    "        self.cha_3 = cha_3\n",
    "        self.cha_1_reshape = cha_1_reshape\n",
    "        self.cha_po_1 = cha_po_1\n",
    "        self.cha_po_2 = cha_po_2\n",
    "\n",
    "        self.batch_norm1 = nn.BatchNorm1d(num_features)\n",
    "        self.dropout1 = nn.Dropout(0.1)\n",
    "        self.dense1 = nn.utils.weight_norm(nn.Linear(num_features, hidden_size))\n",
    "\n",
    "        self.batch_norm_c1 = nn.BatchNorm1d(cha_1)\n",
    "        self.dropout_c1 = nn.Dropout(0.1)\n",
    "        self.conv1 = nn.utils.weight_norm(nn.Conv1d(cha_1,cha_2, kernel_size = 5, stride = 1, padding=2,  bias=False),dim=None)\n",
    "\n",
    "        self.ave_po_c1 = nn.AdaptiveAvgPool1d(output_size = cha_po_1)\n",
    "\n",
    "        self.batch_norm_c2 = nn.BatchNorm1d(cha_2)\n",
    "        self.dropout_c2 = nn.Dropout(0.1)\n",
    "        self.conv2 = nn.utils.weight_norm(nn.Conv1d(cha_2,cha_2, kernel_size = 3, stride = 1, padding=1, bias=True),dim=None)\n",
    "\n",
    "        self.batch_norm_c2_1 = nn.BatchNorm1d(cha_2)\n",
    "        self.dropout_c2_1 = nn.Dropout(0.3)\n",
    "        self.conv2_1 = nn.utils.weight_norm(nn.Conv1d(cha_2,cha_2, kernel_size = 3, stride = 1, padding=1, bias=True),dim=None)\n",
    "\n",
    "        self.batch_norm_c2_2 = nn.BatchNorm1d(cha_2)\n",
    "        self.dropout_c2_2 = nn.Dropout(0.2)\n",
    "        self.conv2_2 = nn.utils.weight_norm(nn.Conv1d(cha_2,cha_3, kernel_size = 5, stride = 1, padding=2, bias=True),dim=None)\n",
    "\n",
    "        self.max_po_c2 = nn.MaxPool1d(kernel_size=4, stride=2, padding=1)\n",
    "\n",
    "        self.flt = nn.Flatten()\n",
    "\n",
    "        self.batch_norm3 = nn.BatchNorm1d(cha_po_2)\n",
    "        self.dropout3 = nn.Dropout(0.2)\n",
    "        self.dense3 = nn.utils.weight_norm(nn.Linear(cha_po_2, num_targets))\n",
    "\n",
    "    def forward(self, x):\n",
    "\n",
    "        x = self.batch_norm1(x)\n",
    "        x = self.dropout1(x)\n",
    "        x = F.celu(self.dense1(x), alpha=0.06)\n",
    "\n",
    "        x = x.reshape(x.shape[0],self.cha_1,\n",
    "                      self.cha_1_reshape)\n",
    "\n",
    "        x = self.batch_norm_c1(x)\n",
    "        x = self.dropout_c1(x)\n",
    "        x = F.relu(self.conv1(x))\n",
    "\n",
    "        x = self.ave_po_c1(x)\n",
    "\n",
    "        x = self.batch_norm_c2(x)\n",
    "        x = self.dropout_c2(x)\n",
    "        x = F.relu(self.conv2(x))\n",
    "        x_s = x\n",
    "\n",
    "        x = self.batch_norm_c2_1(x)\n",
    "        x = self.dropout_c2_1(x)\n",
    "        x = F.relu(self.conv2_1(x))\n",
    "\n",
    "        x = self.batch_norm_c2_2(x)\n",
    "        x = self.dropout_c2_2(x)\n",
    "        x = F.relu(self.conv2_2(x))\n",
    "        x =  x * x_s\n",
    "\n",
    "        x = self.max_po_c2(x)\n",
    "\n",
    "        x = self.flt(x)\n",
    "\n",
    "        x = self.batch_norm3(x)\n",
    "        x = self.dropout3(x)\n",
    "        x = self.dense3(x)\n",
    "\n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_features = x.shape[1]\n",
    "num_targets=1\n",
    "hidden_size=4096"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = x.to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Model2(num_features,num_targets,hidden_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = model.to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = model(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[ 1.2487],\n",
       "        [ 0.4335],\n",
       "        [-0.3007],\n",
       "        [ 0.2190],\n",
       "        [-0.9422],\n",
       "        [ 0.9492],\n",
       "        [-0.4454],\n",
       "        [-0.5357],\n",
       "        [ 0.8943],\n",
       "        [-0.5422],\n",
       "        [ 0.0483],\n",
       "        [ 0.2749],\n",
       "        [ 1.5215],\n",
       "        [-0.2835],\n",
       "        [-1.4190],\n",
       "        [-0.3366],\n",
       "        [-0.6745],\n",
       "        [-0.1032],\n",
       "        [-0.3456],\n",
       "        [-0.1123]], device='cuda:0', grad_fn=<AddmmBackward0>)"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting torchsort\n",
      "  Downloading torchsort-0.1.9.tar.gz (12 kB)\n",
      "  Preparing metadata (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25hRequirement already satisfied: torch in /usr/local/lib/python3.9/dist-packages (from torchsort) (1.12.0+cu116)\n",
      "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.9/dist-packages (from torch->torchsort) (4.3.0)\n",
      "Building wheels for collected packages: torchsort\n",
      "  Building wheel for torchsort (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25h  Created wheel for torchsort: filename=torchsort-0.1.9-cp39-cp39-linux_x86_64.whl size=3037929 sha256=35e7018204e47ab66754a8ce5f68e624bcc352b3670564131231a6277f69ab3a\n",
      "  Stored in directory: /root/.cache/pip/wheels/72/ec/75/5ef2081c0df220afc613a01260f3034f3f6a8f90f605c2b6ab\n",
      "Successfully built torchsort\n",
      "Installing collected packages: torchsort\n",
      "Successfully installed torchsort-0.1.9\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!pip install torchsort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torchsort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "def spearman_loss(pred, target):\n",
    "\n",
    "    x = 1e-3\n",
    "    mse = MSELossFlat()(pred,target)\n",
    "    pred = torchsort.soft_rank(pred.reshape(1,-1),regularization_strength=x)\n",
    "    target = torchsort.soft_rank(target.reshape(1,-1),regularization_strength=x)\n",
    "    pred = pred - pred.mean()\n",
    "    pred = pred / pred.norm()\n",
    "    target = target - target.mean()\n",
    "    target = target / target.norm()\n",
    "    ret = 1- (pred * target).sum()\n",
    "    \n",
    "    return mse + ret"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "def only_spearman_loss(pred, target):\n",
    "\n",
    "    x = 1e-3\n",
    "    # mse = MSELossFlat()(pred,target)\n",
    "    pred = torchsort.soft_rank(pred.reshape(1,-1),regularization_strength=x)\n",
    "    target = torchsort.soft_rank(target.reshape(1,-1),regularization_strength=x)\n",
    "    pred = pred - pred.mean()\n",
    "    pred = pred / pred.norm()\n",
    "    target = target - target.mean()\n",
    "    target = target / target.norm()\n",
    "    ret = 1- (pred * target).sum()\n",
    "    \n",
    "    return ret"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TensorBase(1.3226, device='cuda:0')"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spearman_loss(pred,y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# learn = Learner(dl,model,loss_func=MSELossFlat())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = model2.cuda()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optimizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "optimizer = torch.optim.Adam(model.parameters(), lr=1e-3, weight_decay=1e-5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scheduler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.optim.lr_scheduler import OneCycleLR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scheduler = OneCycleLR(optimizer, max_lr=1e-2,steps_per_epoch=len(dataset),div_factor=1e3, epochs=25,pct_start=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training OLOS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_fn(dataset,train_idx, model,loss_fn,optimizer,scheduler):\n",
    "    \n",
    "    model.train()\n",
    "    final_loss=0\n",
    "\n",
    "    for idx in train_idx:\n",
    "        x,y=dataset[idx]\n",
    "        x,y=x.to(device),y.to(device)\n",
    "\n",
    "        pred=model(x)\n",
    "        loss = loss_fn(pred,y)\n",
    "\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        scheduler.step()\n",
    "\n",
    "        final_loss +=loss.item()\n",
    "\n",
    "    final_loss/=len(train_idx)\n",
    "\n",
    "    return final_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = MyDataset(df,features,'y_normalize','group_pH',train=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "valid_idx = [20,30]\n",
    "model.eval()\n",
    "final_loss = 0\n",
    "spearmans = 0\n",
    "preds = []\n",
    "ys = []\n",
    "with torch.no_grad():\n",
    "    for idx in valid_idx:\n",
    "        x, y = dataset[idx]\n",
    "        x, y = x.to(device), y.to(device)\n",
    "        pred = model(x)\n",
    "        loss = loss_fn(pred, y)\n",
    "\n",
    "        final_loss += loss.item()\n",
    "        spearman = stats.spearmanr(pred.squeeze().cpu().numpy(), y.squeeze().cpu().numpy())\n",
    "        # print(f'spearman loss for group {idx} is {spearman}')\n",
    "        spearmans +=spearman.correlation\n",
    "        preds.append(pred.detach().cpu().numpy())\n",
    "        ys.append(y.detach().cpu().numpy())\n",
    "\n",
    "final_loss /= len(valid_idx)\n",
    "spearmans /= len(valid_idx)\n",
    "ys,preds = np.concatenate(ys),np.concatenate(preds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.07503795589740603"
      ]
     },
     "execution_count": 267,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spearman.correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SpearmanrResult(correlation=1.0, pvalue=0.0)"
      ]
     },
     "execution_count": 264,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.spearmanr(pred.,pred.squeeze().cpu().numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "def valid_fn(dataset,valid_idx,model,loss_fn):\n",
    "\n",
    "    model.eval()\n",
    "    final_loss = 0\n",
    "    spearmans = 0\n",
    "    preds = []\n",
    "    ys = []\n",
    "    with torch.no_grad():\n",
    "        for idx in valid_idx:\n",
    "            x, y = dataset[idx]\n",
    "            x, y = x.to(device), y.to(device)\n",
    "            pred = model(x)\n",
    "            loss = loss_fn(pred, y)\n",
    "\n",
    "            final_loss += loss.item()\n",
    "            spearman = stats.spearmanr(pred.squeeze().cpu().numpy(), y.squeeze().cpu().numpy())\n",
    "            # print(f'spearman loss for group {idx} is {spearman}')\n",
    "            spearmans +=spearman.correlation\n",
    "            preds.append(pred.detach().cpu().numpy())\n",
    "            ys.append(y.detach().cpu().numpy())\n",
    "\n",
    "    final_loss /= len(valid_idx)\n",
    "    spearmans /= len(valid_idx)\n",
    "    ys,preds = np.concatenate(ys),np.concatenate(preds)\n",
    "    \n",
    "    return final_loss, preds,ys,spearmans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "def test_fn(dl,model):\n",
    "    model.eval()\n",
    "    preds = []\n",
    "    with torch.no_grad():\n",
    "        for x in dl:\n",
    "            x = x.to(device)\n",
    "            pred = model(x)\n",
    "            preds.append(pred.detach().cpu().numpy())\n",
    "        \n",
    "    preds = np.concatenate(preds)\n",
    "    \n",
    "    return preds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### GroupKFold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold\n",
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install -Uqq wandb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33msky1ove\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n"
     ]
    }
   ],
   "source": [
    "!wandb login"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "import wandb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 0---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_221703-22yxrmam</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/22yxrmam\" target=\"_blank\">fold_0</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 1---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Finishing last run (ID:22yxrmam) before initializing another..."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▅▅▄▅█▂▄▃▃▅▆▁▄▅▅▆▄▄▆▅▆▆▄▁██▆▆█▇████████▇▇</td></tr><tr><td>train loss</td><td>█▆▅▇▃▅▁▂▅▇▃▃▃▅▄▄▇▅▄▃▃▄▂█▅▄▄▃▅▃▂▁▂▃▁▂▁▁▄▃</td></tr><tr><td>valid loss</td><td>          ▃█▅▄▄▃▅▅▃▄▃▃▅█▁▁▃▃▁▂▁▁▁▁▁▁▁▁▂▂</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.15912</td></tr><tr><td>train loss</td><td>0.84342</td></tr><tr><td>valid loss</td><td>0.84088</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">fold_0</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/22yxrmam\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/22yxrmam</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_221703-22yxrmam/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Successfully finished last run (ID:22yxrmam). Initializing new run:<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_221741-pgglqm0n</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/pgglqm0n\" target=\"_blank\">fold_1</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 2---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Finishing last run (ID:pgglqm0n) before initializing another..."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f84f63ee273e4b5a8fcac2d93bd4a649",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value='0.002 MB of 0.002 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▆▅▁▄▂▃▂▇█▄█▁▄▄▄▃▄▄▅▅▆▇▅▅▄▅▆▆▆▆▆▆▆▅▅▅▅▅▆▇</td></tr><tr><td>train loss</td><td>▅▅▆▁▅██▃▂▅▄▅▅▃▂▅▆▅▆▅▅▃▅▃▁▃▄▁▂▃▆▄▅▂▃▃▃▄▄▃</td></tr><tr><td>valid loss</td><td>          ▁█▅▆▅▇▅▅▅▄▃▂▄▄▅▄▄▃▃▃▃▄▃▄▄▄▄▄▃▃</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.12865</td></tr><tr><td>train loss</td><td>0.88799</td></tr><tr><td>valid loss</td><td>0.87135</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">fold_1</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/pgglqm0n\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/pgglqm0n</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_221741-pgglqm0n/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Successfully finished last run (ID:pgglqm0n). Initializing new run:<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e374bf9702cc43ba8c426dffd9cbd37e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value='Waiting for wandb.init()...\\r'), FloatProgress(value=0.01667032006662339, max=1.0)…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_221824-3ujomuxu</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/3ujomuxu\" target=\"_blank\">fold_2</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 3---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Finishing last run (ID:3ujomuxu) before initializing another..."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d23d3cfdeccd458d9be8dec9ac828782",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value='0.002 MB of 0.002 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▆▅▅▆▆▆▅▇▅▅▅▆▄▃▃▅▅▂▁▁▁▁▁▃▅▅▅▆▆█▄█▇▇▆▆▆▆▇▇</td></tr><tr><td>train loss</td><td>▅▃▁▁▁▂▇▅▆▂▂▂▅▆▆▄▄▅█▆▆▇▇▇▄▄▅▄▅▄▄▃▂▁▃▄▂▃▂▂</td></tr><tr><td>valid loss</td><td>          ▄▃▅▆▆▄▄▇█████▆▄▄▄▃▃▁▅▁▂▂▃▃▃▃▂▂</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.21086</td></tr><tr><td>train loss</td><td>0.8812</td></tr><tr><td>valid loss</td><td>0.78932</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">fold_2</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/3ujomuxu\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/3ujomuxu</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_221824-3ujomuxu/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Successfully finished last run (ID:3ujomuxu). Initializing new run:<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "68b720502d704e92b1fd4aacbb3c7137",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value='Waiting for wandb.init()...\\r'), FloatProgress(value=0.0166692254676794, max=1.0))…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_221906-p76f62kt</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/p76f62kt\" target=\"_blank\">fold_3</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 4---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Finishing last run (ID:p76f62kt) before initializing another..."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▂▅▃▄▅▃▃▄▄▂▁▆▃▄▄▄▁█▇▇▇▅▄▄▁▁▁▃▅▂▅▄▃▃▃▃▃▂▃▂</td></tr><tr><td>train loss</td><td>▆▂▃▂▄▃▆▆█▄▆▄▅▆▆▆▅▄▃▂▁▃▂▃▃▄▃▂▄▃▂▃▄▃▃▅▅▄▅▇</td></tr><tr><td>valid loss</td><td>          █▃▆▅▅▅█▁▂▂▂▄▅▅███▆▄▇▄▅▆▆▆▆▆▇▆▇</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>-0.02634</td></tr><tr><td>train loss</td><td>1.04261</td></tr><tr><td>valid loss</td><td>1.02623</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">fold_3</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/p76f62kt\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/p76f62kt</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_221906-p76f62kt/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Successfully finished last run (ID:p76f62kt). Initializing new run:<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_221947-fu5vmqa0</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/fu5vmqa0\" target=\"_blank\">fold_4</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "232626e5fc1547f5a1d78b3e357fd8c9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value='0.002 MB of 0.002 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▄▄▄▄▆▃▁▂▂▁▅▅▅▃▄▂▄▄▆▇█▇█▅▃▅▅▃▂▃▂▂▁▁▁▁▂▂▃▃</td></tr><tr><td>train loss</td><td>▆▂▄▃▄▅▆█▇█▇▆▄▆▇▇▄▃▄▆▃▄▁▃▄▆▄▄▇▅▅▆▆▆▅▆▄▅▅▅</td></tr><tr><td>valid loss</td><td>        ▇█▄▄▄▆▅▇▅▅▃▂▁▂▁▄▆▄▄▆▇▆▇▇████▇▇▆▆</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>-0.08207</td></tr><tr><td>train loss</td><td>0.93287</td></tr><tr><td>valid loss</td><td>1.08206</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">fold_4</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/fu5vmqa0\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_only_spearmanLoss/runs/fu5vmqa0</a><br/>Synced 4 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_221947-fu5vmqa0/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "EPOCHS=100\n",
    "for fold, (train_idx, valid_idx) in enumerate(KFold(5,shuffle=True).split(df.group.unique())):\n",
    "    print(f\"-------Fold {fold}---------------\")\n",
    "    wandb.init(project=\"novoenzyme_only_spearmanLoss\",name=f\"fold_{fold}\")\n",
    "    \n",
    "    train_ds = MyDataset(df,features,'y_normalize','group_pH',train=True)\n",
    "    valid_ds = MyDataset(df,features,'y_normalize','group_pH',train=False)\n",
    "    \n",
    "    model = Model2(num_features,num_targets,hidden_size).cuda()\n",
    "    loss_fn = only_spearman_loss\n",
    "    optimizer = torch.optim.Adam(model.parameters(), lr=1e-3, weight_decay=1e-5)\n",
    "    scheduler = OneCycleLR(optimizer, max_lr=1e-2,steps_per_epoch=len(train_ds),div_factor=1e3, epochs=EPOCHS,pct_start=0.1)\n",
    "    \n",
    "    # oof = np.zeros((len(df), 1))\n",
    "    best_spearman = 0\n",
    "    \n",
    "    for epoch in range(EPOCHS):\n",
    "        train_loss = train_fn(train_ds,train_idx,model,loss_fn, optimizer,scheduler)\n",
    "        valid_loss,valid_preds,valid_ys,spearmans = valid_fn(valid_ds,valid_idx, model,loss_fn)\n",
    "        wandb.log({\"train loss\": train_loss, \"valid loss\": valid_loss, \"spearman\":spearmans})\n",
    "\n",
    "        if spearmans > best_spearman:\n",
    "            best_spearman = spearmans\n",
    "            # oof[valid_idx] = valid_preds\n",
    "            torch.save(model.state_dict(),f'my_model/fold{fold}.pth')\n",
    "\n",
    "    wandb.finish()\n",
    "    \n",
    "    test_ds = TestDataset(test_df,features)\n",
    "    test_dl = DataLoader(test_ds,bs=20,shuffle=False,num_workers=4)\n",
    "\n",
    "    model = Model2(num_features,num_targets,hidden_size)\n",
    "    model.load_state_dict(torch.load(f'my_model/fold{fold}.pth'))\n",
    "    model.to(device)\n",
    "\n",
    "    # oofs+=oof/2\n",
    "    test_preds += test_fn(test_dl,model)/2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8554554958647924"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_fn(train_dl,model,loss_fn, optimizer,scheduler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.],\n",
       "       [0.],\n",
       "       [0.],\n",
       "       ...,\n",
       "       [0.],\n",
       "       [0.],\n",
       "       [0.]])"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "def run_kfold(Nfolds=5, seed=0, EPOCHS=100,loss_fn=MSELossFlat()):\n",
    "    seed_everything(seed)\n",
    "    test_preds = np.zeros((len(test_df), 1))\n",
    "    \n",
    "    for fold, (train_idx, valid_idx) in enumerate(KFold(Nfolds,shuffle=True).split(df.group.unique())):\n",
    "        print(f\"-------Fold {fold}---------------\")\n",
    "        wandb.init(project=\"novoenzyme_MSELoss\",name=f\"seed{seed}_fold{fold}\")\n",
    "\n",
    "        train_ds = MyDataset(df,features,'y_normalize','group_pH',train=True)\n",
    "        valid_ds = MyDataset(df,features,'y_normalize','group_pH',train=False)\n",
    "\n",
    "        model = Model2(num_features,num_targets,hidden_size).cuda()\n",
    "        # loss_fn = MSELossFlat()\n",
    "        optimizer = torch.optim.Adam(model.parameters(), lr=1e-3, weight_decay=1e-5)\n",
    "        scheduler = OneCycleLR(optimizer, max_lr=1e-2,steps_per_epoch=len(train_ds),div_factor=1e3, epochs=EPOCHS,pct_start=0.1)\n",
    "\n",
    "        # oof = np.zeros((len(df), 1))\n",
    "        best_spearman = 0\n",
    "\n",
    "        for epoch in range(EPOCHS):\n",
    "            train_loss = train_fn(train_ds,train_idx,model,loss_fn, optimizer,scheduler)\n",
    "            valid_loss,valid_preds,valid_ys,spearmans = valid_fn(valid_ds,valid_idx, model,loss_fn)\n",
    "            wandb.log({\"train loss\": train_loss, \"valid loss\": valid_loss, \"spearman\":spearmans})\n",
    "\n",
    "            if spearmans > best_spearman:\n",
    "                best_spearman = spearmans\n",
    "                # oof[valid_idx] = valid_preds\n",
    "                torch.save(model.state_dict(),f'my_model/fold{fold}.pth')\n",
    "                print(f'fold{fold} saving model at epoch{epoch} when spearman is {best_spearman}')\n",
    "\n",
    "        wandb.finish()\n",
    "\n",
    "        test_ds = TestDataset(test_df,features)\n",
    "        test_dl = DataLoader(test_ds,bs=20,shuffle=False,num_workers=4)\n",
    "\n",
    "        model = Model2(num_features,num_targets,hidden_size)\n",
    "        model.load_state_dict(torch.load(f'my_model/fold{fold}.pth'))\n",
    "        model.to(device)\n",
    "\n",
    "        # oofs+=oof/2\n",
    "        test_preds += test_fn(test_dl,model)/Nfolds\n",
    "\n",
    "    return test_preds\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 0---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232205-11iq10k4</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/11iq10k4\" target=\"_blank\">seed0_fold0</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold0 saving model when spearman is 0.12738196906781693\n",
      "fold0 saving model when spearman is 0.2991361981447643\n",
      "fold0 saving model when spearman is 0.37763960904194677\n",
      "fold0 saving model when spearman is 0.4174345323526554\n",
      "fold0 saving model when spearman is 0.4363874463675074\n",
      "fold0 saving model when spearman is 0.4582810370244391\n",
      "fold0 saving model when spearman is 0.48148205143999206\n",
      "fold0 saving model when spearman is 0.48636402924488686\n",
      "fold0 saving model when spearman is 0.4933084763701525\n",
      "fold0 saving model when spearman is 0.5315828463564977\n",
      "fold0 saving model when spearman is 0.5471742612870879\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d9fabf11450f48faad55b5fb01397350",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value='0.002 MB of 0.002 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▃▃▃▁▃▅▄▆▆▆▇▆▇▇▇▇▇█▇▇▇▇▇▇▇▇▇█▇█▇███▇▇▇▇▇▇</td></tr><tr><td>train loss</td><td>▇█▅▄▃▂▂▂▃▂▂▂▂▂▂▂▁▁▁▂▁▁▁▁▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>valid loss</td><td>▁█▂▄▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.46712</td></tr><tr><td>train loss</td><td>0.43814</td></tr><tr><td>valid loss</td><td>0.91424</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed0_fold0</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/11iq10k4\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/11iq10k4</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232205-11iq10k4/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 1---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232251-23xbx9nk</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/23xbx9nk\" target=\"_blank\">seed0_fold1</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold1 saving model when spearman is 0.10192793697862022\n",
      "fold1 saving model when spearman is 0.1084406194329781\n",
      "fold1 saving model when spearman is 0.1582910795805306\n",
      "fold1 saving model when spearman is 0.19329348727424772\n",
      "fold1 saving model when spearman is 0.212035871745973\n",
      "fold1 saving model when spearman is 0.29614667796683986\n",
      "fold1 saving model when spearman is 0.3619391879410187\n",
      "fold1 saving model when spearman is 0.3620346803754149\n",
      "fold1 saving model when spearman is 0.377397471364805\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▃▁▃▁▃▃▃▅█▇▇▇█▅▅▄▆▇▆▆▇▆▅▆▆▆▅▅▆▇▆▇▆▇▆▆▆▆▆▅</td></tr><tr><td>train loss</td><td>██▆▄▄▄▃▃▃▃▂▂▂▂▂▂▃▂▂▂▂▂▁▂▂▁▂▂▁▁▂▂▁▁▁▁▁▂▁▁</td></tr><tr><td>valid loss</td><td>▁██▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.21158</td></tr><tr><td>train loss</td><td>0.39323</td></tr><tr><td>valid loss</td><td>0.72557</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed0_fold1</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/23xbx9nk\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/23xbx9nk</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232251-23xbx9nk/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 2---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232337-2hhdurof</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/2hhdurof\" target=\"_blank\">seed0_fold2</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold2 saving model when spearman is 0.08740147306007896\n",
      "fold2 saving model when spearman is 0.12783567805418666\n",
      "fold2 saving model when spearman is 0.1568714899824754\n",
      "fold2 saving model when spearman is 0.2417613284512498\n",
      "fold2 saving model when spearman is 0.27272922505876646\n",
      "fold2 saving model when spearman is 0.29553605722394044\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▁▄▁▄▅▅▆▆▆▇▆█▇▆█▆▇▆▅▇▇▇▆▆▆█▇▇▆█▆█▆▆▆▆▆▆▇▇</td></tr><tr><td>train loss</td><td>▇█▄▅▃▄▃▂▃▃▂▂▂▂▂▂▂▁▂▂▂▂▂▂▂▂▂▁▂▁▂▂▁▂▁▂▁▁▁▂</td></tr><tr><td>valid loss</td><td>▁▁█▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.21946</td></tr><tr><td>train loss</td><td>0.43507</td></tr><tr><td>valid loss</td><td>0.79523</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed0_fold2</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/2hhdurof\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/2hhdurof</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232337-2hhdurof/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 3---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232422-189hffr4</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/189hffr4\" target=\"_blank\">seed0_fold3</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold3 saving model when spearman is 0.09103415913531299\n",
      "fold3 saving model when spearman is 0.1095775057696705\n",
      "fold3 saving model when spearman is 0.3266170128807259\n",
      "fold3 saving model when spearman is 0.33666973364025615\n",
      "fold3 saving model when spearman is 0.37151274916295723\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▄▃▁▃▃▄▁▃▇▆▇█▇▇▇▇▇▇▇▆▇█▇▆▇▇██▇▇██▇▇▇█▆█▇▇</td></tr><tr><td>train loss</td><td>▇█▅▄▃▃▃▃▂▂▂▂▂▁▂▂▂▂▂▂▂▁▂▂▁▂▁▁▁▁▁▁▁▁▂▁▁▁▁▁</td></tr><tr><td>valid loss</td><td>▁▁█▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.2732</td></tr><tr><td>train loss</td><td>0.39631</td></tr><tr><td>valid loss</td><td>0.8611</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed0_fold3</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/189hffr4\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/189hffr4</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232422-189hffr4/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 4---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232505-ect9nol9</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/ect9nol9\" target=\"_blank\">seed0_fold4</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold4 saving model when spearman is 0.01747873080287878\n",
      "fold4 saving model when spearman is 0.11060210345877326\n",
      "fold4 saving model when spearman is 0.1855316503622975\n",
      "fold4 saving model when spearman is 0.19016239904241983\n",
      "fold4 saving model when spearman is 0.19584101832781084\n",
      "fold4 saving model when spearman is 0.36260207555458934\n",
      "fold4 saving model when spearman is 0.3792575842075483\n",
      "fold4 saving model when spearman is 0.38837314566623116\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▃▁▃▄▂▅▂▅▇▇▆▇▇▅▆▆▅▆▇█▇▇▇▇▇█▇▇█▇█▇▇█▇▇▇█▇▇</td></tr><tr><td>train loss</td><td>███▆▄▄▃▃▃▂▃▂▂▂▂▂▂▂▂▃▂▂▂▂▂▂▁▁▂▂▂▂▁▁▁▁▁▁▁▂</td></tr><tr><td>valid loss</td><td>▁▁█▃▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.3109</td></tr><tr><td>train loss</td><td>0.4193</td></tr><tr><td>valid loss</td><td>0.98898</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed0_fold4</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/ect9nol9\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/ect9nol9</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232505-ect9nol9/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 0---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232551-38ohxgd5</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/38ohxgd5\" target=\"_blank\">seed1_fold0</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold0 saving model when spearman is 0.13328582314558693\n",
      "fold0 saving model when spearman is 0.15828110676834137\n",
      "fold0 saving model when spearman is 0.24559103827471038\n",
      "fold0 saving model when spearman is 0.2911479672808695\n",
      "fold0 saving model when spearman is 0.3131323538319924\n",
      "fold0 saving model when spearman is 0.3137738270154146\n",
      "fold0 saving model when spearman is 0.3173966225843878\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "948a197600c342e589960c7104a76a2c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value='0.002 MB of 0.002 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▅▄▄▄▃▄▃▆▁▅▅▅▆█▆██▇█▆▇▇▇▇▇▇█▇▇▇▇▇▇▇█▇▇▆▇▇</td></tr><tr><td>train loss</td><td>▇█▅▄▃▃▂▂▃▃▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▂▁▂▁▁▁▁▁▂▁▁</td></tr><tr><td>valid loss</td><td>▁█▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.27356</td></tr><tr><td>train loss</td><td>0.44642</td></tr><tr><td>valid loss</td><td>0.68597</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed1_fold0</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/38ohxgd5\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/38ohxgd5</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232551-38ohxgd5/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 1---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232635-2hmwkgtc</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/2hmwkgtc\" target=\"_blank\">seed1_fold1</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold1 saving model when spearman is 0.00021840192115881889\n",
      "fold1 saving model when spearman is 0.08161963229198935\n",
      "fold1 saving model when spearman is 0.2071427289932323\n",
      "fold1 saving model when spearman is 0.23122421636078475\n",
      "fold1 saving model when spearman is 0.2777722126218359\n",
      "fold1 saving model when spearman is 0.36258738221507014\n",
      "fold1 saving model when spearman is 0.3691523120018732\n",
      "fold1 saving model when spearman is 0.4289322437729431\n",
      "fold1 saving model when spearman is 0.4473981755845603\n",
      "fold1 saving model when spearman is 0.4857915902723953\n",
      "fold1 saving model when spearman is 0.4938448154046392\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▃▂▃▃▁▄▄▆▇▆▇▇▇▇▇▇▇█▆█▇▇▇▇██▇▇█▇▇▇▇▇▇█▇▇▇▇</td></tr><tr><td>train loss</td><td>██▆▄▃▃▃▃▃▂▃▂▃▂▂▂▂▂▂▂▂▂▂▂▂▂▂▂▁▁▁▂▁▁▁▁▁▁▁▁</td></tr><tr><td>valid loss</td><td>▁▁█▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.39467</td></tr><tr><td>train loss</td><td>0.4094</td></tr><tr><td>valid loss</td><td>0.71691</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed1_fold1</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/2hmwkgtc\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/2hmwkgtc</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232635-2hmwkgtc/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 2---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232721-1ff23yzi</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/1ff23yzi\" target=\"_blank\">seed1_fold2</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold2 saving model when spearman is 0.054073585325082406\n",
      "fold2 saving model when spearman is 0.08149592743043534\n",
      "fold2 saving model when spearman is 0.11295173843624354\n",
      "fold2 saving model when spearman is 0.13439464841508206\n",
      "fold2 saving model when spearman is 0.25265380846413743\n",
      "fold2 saving model when spearman is 0.26196259077818457\n",
      "fold2 saving model when spearman is 0.3189440152324097\n",
      "fold2 saving model when spearman is 0.32991190424035816\n",
      "fold2 saving model when spearman is 0.36643994143744124\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▂▁▂▃▂▆▅▇█▅▅▅▆█▆▆▆▇▇▆▅▆▆▅▅▅▅▄▅▄▅▅▅▅▆▆▅▆▄▆</td></tr><tr><td>train loss</td><td>▇█▆▄▄▃▂▃▂▃▃▂▂▂▂▂▁▁▂▂▁▁▂▂▂▂▁▁▁▂▁▂▁▁▂▁▁▁▁▁</td></tr><tr><td>valid loss</td><td>▁▁█▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.24386</td></tr><tr><td>train loss</td><td>0.44937</td></tr><tr><td>valid loss</td><td>0.66574</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed1_fold2</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/1ff23yzi\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/1ff23yzi</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232721-1ff23yzi/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 3---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232808-330fbo1r</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/330fbo1r\" target=\"_blank\">seed1_fold3</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold3 saving model when spearman is 0.11855599420798367\n",
      "fold3 saving model when spearman is 0.21292380912114472\n",
      "fold3 saving model when spearman is 0.35221962773543025\n",
      "fold3 saving model when spearman is 0.3920834603877464\n",
      "fold3 saving model when spearman is 0.394250349832284\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▄▁▃▂▁▅▂▄█▇▅▆█▇▆▆▇▆▆▆▆▆▆▇▆▆▆▆▆▇▇▆▇▆▅▆▆▇▆▇</td></tr><tr><td>train loss</td><td>▇█▇▅▃▃▂▂▂▂▂▃▃▂▂▂▂▂▂▂▂▂▂▂▁▁▂▂▁▁▂▁▁▁▁▂▁▁▁▁</td></tr><tr><td>valid loss</td><td>▁▁█▂▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.30223</td></tr><tr><td>train loss</td><td>0.38347</td></tr><tr><td>valid loss</td><td>1.01068</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed1_fold3</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/330fbo1r\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/330fbo1r</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232808-330fbo1r/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------Fold 4---------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Tracking run with wandb version 0.13.7"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Run data is saved locally in <code>/notebooks/wandb/run-20221231_232855-2ioghu0l</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Syncing run <strong><a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/2ioghu0l\" target=\"_blank\">seed1_fold4</a></strong> to <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://wandb.me/run\" target=\"_blank\">docs</a>)<br/>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fold4 saving model when spearman is 0.026803682579226062\n",
      "fold4 saving model when spearman is 0.13770107957567299\n",
      "fold4 saving model when spearman is 0.13849952973661192\n",
      "fold4 saving model when spearman is 0.23219930190855176\n",
      "fold4 saving model when spearman is 0.29663109635683615\n",
      "fold4 saving model when spearman is 0.430198108988795\n",
      "fold4 saving model when spearman is 0.46568781616892263\n",
      "fold4 saving model when spearman is 0.47406357951874795\n",
      "fold4 saving model when spearman is 0.4745566537192076\n",
      "fold4 saving model when spearman is 0.4768900959706271\n",
      "fold4 saving model when spearman is 0.49110030632389073\n",
      "fold4 saving model when spearman is 0.49500958036118314\n",
      "fold4 saving model when spearman is 0.5056962818566605\n",
      "fold4 saving model when spearman is 0.5090154214152811\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cc234eb6ee9a4cefbd93b696242edd48",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value='0.002 MB of 0.002 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, max…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
       "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
       "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
       "    </style>\n",
       "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>▂▃▂▂▁▁▅▄▄▄▄▆▇▇▇▇█▆▇█▇▇▇▇▇▇▆█▇▆▇█████████</td></tr><tr><td>train loss</td><td>██▅▄▃▃▂▃▂▂▂▂▂▂▂▂▁▂▂▂▂▂▁▁▂▁▁▂▂▁▁▂▁▂▁▁▁▁▁▁</td></tr><tr><td>valid loss</td><td>▁▄█▃▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>spearman</td><td>0.49122</td></tr><tr><td>train loss</td><td>0.38719</td></tr><tr><td>valid loss</td><td>1.00592</td></tr></table><br/></div></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Synced <strong style=\"color:#cdcd00\">seed1_fold4</strong>: <a href=\"https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/2ioghu0l\" target=\"_blank\">https://wandb.ai/sky1ove/novoenzyme_MSELoss/runs/2ioghu0l</a><br/>Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "Find logs at: <code>./wandb/run-20221231_232855-2ioghu0l/logs</code>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "SEED = [0,1]\n",
    "\n",
    "# oof = np.zeros((len(df), 1))\n",
    "predictions = np.zeros((len(test_df), 1))\n",
    "\n",
    "for seed in SEED:\n",
    "    \n",
    "    predict= run_kfold(seed=seed)\n",
    "    predictions+=predict/len(SEED)\n",
    "    # oof+=oof_/len(SEED)\n",
    "    \n",
    "# df['oof'] = oof\n",
    "test_df['preds'] = predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>seq_id</th>\n",
       "      <th>mut_seq</th>\n",
       "      <th>pH2</th>\n",
       "      <th>wt_seq</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "      <th>23</th>\n",
       "      <th>24</th>\n",
       "      <th>25</th>\n",
       "      <th>26</th>\n",
       "      <th>27</th>\n",
       "      <th>28</th>\n",
       "      <th>29</th>\n",
       "      <th>30</th>\n",
       "      <th>31</th>\n",
       "      <th>32</th>\n",
       "      <th>33</th>\n",
       "      <th>34</th>\n",
       "      <th>35</th>\n",
       "      <th>36</th>\n",
       "      <th>37</th>\n",
       "      <th>38</th>\n",
       "      <th>39</th>\n",
       "      <th>40</th>\n",
       "      <th>41</th>\n",
       "      <th>42</th>\n",
       "      <th>43</th>\n",
       "      <th>44</th>\n",
       "      <th>45</th>\n",
       "      <th>46</th>\n",
       "      <th>47</th>\n",
       "      <th>48</th>\n",
       "      <th>49</th>\n",
       "      <th>50</th>\n",
       "      <th>51</th>\n",
       "      <th>52</th>\n",
       "      <th>53</th>\n",
       "      <th>54</th>\n",
       "      <th>55</th>\n",
       "      <th>56</th>\n",
       "      <th>57</th>\n",
       "      <th>58</th>\n",
       "      <th>59</th>\n",
       "      <th>60</th>\n",
       "      <th>61</th>\n",
       "      <th>62</th>\n",
       "      <th>63</th>\n",
       "      <th>64</th>\n",
       "      <th>65</th>\n",
       "      <th>66</th>\n",
       "      <th>67</th>\n",
       "      <th>68</th>\n",
       "      <th>69</th>\n",
       "      <th>70</th>\n",
       "      <th>71</th>\n",
       "      <th>72</th>\n",
       "      <th>73</th>\n",
       "      <th>74</th>\n",
       "      <th>75</th>\n",
       "      <th>76</th>\n",
       "      <th>77</th>\n",
       "      <th>78</th>\n",
       "      <th>79</th>\n",
       "      <th>80</th>\n",
       "      <th>81</th>\n",
       "      <th>82</th>\n",
       "      <th>83</th>\n",
       "      <th>84</th>\n",
       "      <th>85</th>\n",
       "      <th>86</th>\n",
       "      <th>87</th>\n",
       "      <th>88</th>\n",
       "      <th>89</th>\n",
       "      <th>90</th>\n",
       "      <th>91</th>\n",
       "      <th>92</th>\n",
       "      <th>93</th>\n",
       "      <th>94</th>\n",
       "      <th>95</th>\n",
       "      <th>96</th>\n",
       "      <th>97</th>\n",
       "      <th>98</th>\n",
       "      <th>99</th>\n",
       "      <th>100</th>\n",
       "      <th>101</th>\n",
       "      <th>102</th>\n",
       "      <th>103</th>\n",
       "      <th>104</th>\n",
       "      <th>105</th>\n",
       "      <th>106</th>\n",
       "      <th>107</th>\n",
       "      <th>108</th>\n",
       "      <th>109</th>\n",
       "      <th>110</th>\n",
       "      <th>111</th>\n",
       "      <th>112</th>\n",
       "      <th>113</th>\n",
       "      <th>114</th>\n",
       "      <th>115</th>\n",
       "      <th>116</th>\n",
       "      <th>117</th>\n",
       "      <th>118</th>\n",
       "      <th>119</th>\n",
       "      <th>120</th>\n",
       "      <th>121</th>\n",
       "      <th>122</th>\n",
       "      <th>123</th>\n",
       "      <th>124</th>\n",
       "      <th>125</th>\n",
       "      <th>126</th>\n",
       "      <th>127</th>\n",
       "      <th>128</th>\n",
       "      <th>129</th>\n",
       "      <th>130</th>\n",
       "      <th>131</th>\n",
       "      <th>132</th>\n",
       "      <th>133</th>\n",
       "      <th>134</th>\n",
       "      <th>135</th>\n",
       "      <th>136</th>\n",
       "      <th>137</th>\n",
       "      <th>138</th>\n",
       "      <th>139</th>\n",
       "      <th>140</th>\n",
       "      <th>141</th>\n",
       "      <th>142</th>\n",
       "      <th>143</th>\n",
       "      <th>144</th>\n",
       "      <th>145</th>\n",
       "      <th>146</th>\n",
       "      <th>147</th>\n",
       "      <th>148</th>\n",
       "      <th>149</th>\n",
       "      <th>150</th>\n",
       "      <th>151</th>\n",
       "      <th>152</th>\n",
       "      <th>153</th>\n",
       "      <th>154</th>\n",
       "      <th>155</th>\n",
       "      <th>156</th>\n",
       "      <th>157</th>\n",
       "      <th>158</th>\n",
       "      <th>159</th>\n",
       "      <th>160</th>\n",
       "      <th>161</th>\n",
       "      <th>162</th>\n",
       "      <th>163</th>\n",
       "      <th>164</th>\n",
       "      <th>165</th>\n",
       "      <th>166</th>\n",
       "      <th>167</th>\n",
       "      <th>168</th>\n",
       "      <th>169</th>\n",
       "      <th>170</th>\n",
       "      <th>171</th>\n",
       "      <th>172</th>\n",
       "      <th>173</th>\n",
       "      <th>174</th>\n",
       "      <th>175</th>\n",
       "      <th>176</th>\n",
       "      <th>177</th>\n",
       "      <th>178</th>\n",
       "      <th>179</th>\n",
       "      <th>180</th>\n",
       "      <th>181</th>\n",
       "      <th>182</th>\n",
       "      <th>183</th>\n",
       "      <th>184</th>\n",
       "      <th>185</th>\n",
       "      <th>186</th>\n",
       "      <th>187</th>\n",
       "      <th>188</th>\n",
       "      <th>189</th>\n",
       "      <th>190</th>\n",
       "      <th>191</th>\n",
       "      <th>192</th>\n",
       "      <th>193</th>\n",
       "      <th>194</th>\n",
       "      <th>195</th>\n",
       "      <th>196</th>\n",
       "      <th>197</th>\n",
       "      <th>198</th>\n",
       "      <th>199</th>\n",
       "      <th>200</th>\n",
       "      <th>201</th>\n",
       "      <th>202</th>\n",
       "      <th>203</th>\n",
       "      <th>204</th>\n",
       "      <th>205</th>\n",
       "      <th>206</th>\n",
       "      <th>207</th>\n",
       "      <th>208</th>\n",
       "      <th>209</th>\n",
       "      <th>210</th>\n",
       "      <th>211</th>\n",
       "      <th>212</th>\n",
       "      <th>213</th>\n",
       "      <th>214</th>\n",
       "      <th>215</th>\n",
       "      <th>216</th>\n",
       "      <th>217</th>\n",
       "      <th>218</th>\n",
       "      <th>219</th>\n",
       "      <th>220</th>\n",
       "      <th>221</th>\n",
       "      <th>222</th>\n",
       "      <th>223</th>\n",
       "      <th>224</th>\n",
       "      <th>225</th>\n",
       "      <th>226</th>\n",
       "      <th>227</th>\n",
       "      <th>228</th>\n",
       "      <th>229</th>\n",
       "      <th>230</th>\n",
       "      <th>231</th>\n",
       "      <th>232</th>\n",
       "      <th>233</th>\n",
       "      <th>234</th>\n",
       "      <th>235</th>\n",
       "      <th>236</th>\n",
       "      <th>237</th>\n",
       "      <th>238</th>\n",
       "      <th>239</th>\n",
       "      <th>240</th>\n",
       "      <th>241</th>\n",
       "      <th>242</th>\n",
       "      <th>243</th>\n",
       "      <th>244</th>\n",
       "      <th>245</th>\n",
       "      <th>246</th>\n",
       "      <th>247</th>\n",
       "      <th>248</th>\n",
       "      <th>249</th>\n",
       "      <th>250</th>\n",
       "      <th>251</th>\n",
       "      <th>252</th>\n",
       "      <th>253</th>\n",
       "      <th>254</th>\n",
       "      <th>255</th>\n",
       "      <th>256</th>\n",
       "      <th>257</th>\n",
       "      <th>258</th>\n",
       "      <th>259</th>\n",
       "      <th>260</th>\n",
       "      <th>261</th>\n",
       "      <th>262</th>\n",
       "      <th>263</th>\n",
       "      <th>264</th>\n",
       "      <th>265</th>\n",
       "      <th>266</th>\n",
       "      <th>267</th>\n",
       "      <th>268</th>\n",
       "      <th>269</th>\n",
       "      <th>270</th>\n",
       "      <th>271</th>\n",
       "      <th>272</th>\n",
       "      <th>273</th>\n",
       "      <th>274</th>\n",
       "      <th>275</th>\n",
       "      <th>276</th>\n",
       "      <th>277</th>\n",
       "      <th>278</th>\n",
       "      <th>279</th>\n",
       "      <th>280</th>\n",
       "      <th>281</th>\n",
       "      <th>282</th>\n",
       "      <th>283</th>\n",
       "      <th>284</th>\n",
       "      <th>285</th>\n",
       "      <th>286</th>\n",
       "      <th>287</th>\n",
       "      <th>288</th>\n",
       "      <th>289</th>\n",
       "      <th>290</th>\n",
       "      <th>291</th>\n",
       "      <th>292</th>\n",
       "      <th>293</th>\n",
       "      <th>294</th>\n",
       "      <th>295</th>\n",
       "      <th>296</th>\n",
       "      <th>297</th>\n",
       "      <th>298</th>\n",
       "      <th>299</th>\n",
       "      <th>300</th>\n",
       "      <th>301</th>\n",
       "      <th>302</th>\n",
       "      <th>303</th>\n",
       "      <th>304</th>\n",
       "      <th>305</th>\n",
       "      <th>306</th>\n",
       "      <th>307</th>\n",
       "      <th>308</th>\n",
       "      <th>309</th>\n",
       "      <th>310</th>\n",
       "      <th>311</th>\n",
       "      <th>312</th>\n",
       "      <th>313</th>\n",
       "      <th>314</th>\n",
       "      <th>315</th>\n",
       "      <th>316</th>\n",
       "      <th>317</th>\n",
       "      <th>318</th>\n",
       "      <th>319</th>\n",
       "      <th>320</th>\n",
       "      <th>321</th>\n",
       "      <th>322</th>\n",
       "      <th>323</th>\n",
       "      <th>324</th>\n",
       "      <th>325</th>\n",
       "      <th>326</th>\n",
       "      <th>327</th>\n",
       "      <th>328</th>\n",
       "      <th>329</th>\n",
       "      <th>330</th>\n",
       "      <th>331</th>\n",
       "      <th>332</th>\n",
       "      <th>333</th>\n",
       "      <th>334</th>\n",
       "      <th>335</th>\n",
       "      <th>336</th>\n",
       "      <th>337</th>\n",
       "      <th>338</th>\n",
       "      <th>339</th>\n",
       "      <th>340</th>\n",
       "      <th>341</th>\n",
       "      <th>342</th>\n",
       "      <th>343</th>\n",
       "      <th>344</th>\n",
       "      <th>345</th>\n",
       "      <th>346</th>\n",
       "      <th>347</th>\n",
       "      <th>348</th>\n",
       "      <th>349</th>\n",
       "      <th>350</th>\n",
       "      <th>351</th>\n",
       "      <th>352</th>\n",
       "      <th>353</th>\n",
       "      <th>354</th>\n",
       "      <th>355</th>\n",
       "      <th>356</th>\n",
       "      <th>357</th>\n",
       "      <th>358</th>\n",
       "      <th>359</th>\n",
       "      <th>360</th>\n",
       "      <th>361</th>\n",
       "      <th>362</th>\n",
       "      <th>363</th>\n",
       "      <th>364</th>\n",
       "      <th>365</th>\n",
       "      <th>366</th>\n",
       "      <th>367</th>\n",
       "      <th>368</th>\n",
       "      <th>369</th>\n",
       "      <th>370</th>\n",
       "      <th>371</th>\n",
       "      <th>372</th>\n",
       "      <th>373</th>\n",
       "      <th>374</th>\n",
       "      <th>375</th>\n",
       "      <th>376</th>\n",
       "      <th>377</th>\n",
       "      <th>378</th>\n",
       "      <th>379</th>\n",
       "      <th>380</th>\n",
       "      <th>381</th>\n",
       "      <th>382</th>\n",
       "      <th>383</th>\n",
       "      <th>384</th>\n",
       "      <th>385</th>\n",
       "      <th>386</th>\n",
       "      <th>387</th>\n",
       "      <th>388</th>\n",
       "      <th>389</th>\n",
       "      <th>390</th>\n",
       "      <th>391</th>\n",
       "      <th>392</th>\n",
       "      <th>393</th>\n",
       "      <th>394</th>\n",
       "      <th>395</th>\n",
       "      <th>396</th>\n",
       "      <th>397</th>\n",
       "      <th>398</th>\n",
       "      <th>399</th>\n",
       "      <th>400</th>\n",
       "      <th>401</th>\n",
       "      <th>402</th>\n",
       "      <th>403</th>\n",
       "      <th>404</th>\n",
       "      <th>405</th>\n",
       "      <th>406</th>\n",
       "      <th>407</th>\n",
       "      <th>408</th>\n",
       "      <th>409</th>\n",
       "      <th>410</th>\n",
       "      <th>411</th>\n",
       "      <th>412</th>\n",
       "      <th>413</th>\n",
       "      <th>414</th>\n",
       "      <th>415</th>\n",
       "      <th>416</th>\n",
       "      <th>417</th>\n",
       "      <th>418</th>\n",
       "      <th>419</th>\n",
       "      <th>420</th>\n",
       "      <th>421</th>\n",
       "      <th>422</th>\n",
       "      <th>423</th>\n",
       "      <th>424</th>\n",
       "      <th>425</th>\n",
       "      <th>426</th>\n",
       "      <th>427</th>\n",
       "      <th>428</th>\n",
       "      <th>429</th>\n",
       "      <th>430</th>\n",
       "      <th>431</th>\n",
       "      <th>432</th>\n",
       "      <th>433</th>\n",
       "      <th>434</th>\n",
       "      <th>435</th>\n",
       "      <th>436</th>\n",
       "      <th>437</th>\n",
       "      <th>438</th>\n",
       "      <th>439</th>\n",
       "      <th>440</th>\n",
       "      <th>441</th>\n",
       "      <th>442</th>\n",
       "      <th>443</th>\n",
       "      <th>444</th>\n",
       "      <th>445</th>\n",
       "      <th>446</th>\n",
       "      <th>447</th>\n",
       "      <th>448</th>\n",
       "      <th>449</th>\n",
       "      <th>450</th>\n",
       "      <th>451</th>\n",
       "      <th>452</th>\n",
       "      <th>453</th>\n",
       "      <th>454</th>\n",
       "      <th>455</th>\n",
       "      <th>456</th>\n",
       "      <th>457</th>\n",
       "      <th>458</th>\n",
       "      <th>459</th>\n",
       "      <th>460</th>\n",
       "      <th>461</th>\n",
       "      <th>462</th>\n",
       "      <th>463</th>\n",
       "      <th>464</th>\n",
       "      <th>465</th>\n",
       "      <th>466</th>\n",
       "      <th>467</th>\n",
       "      <th>468</th>\n",
       "      <th>469</th>\n",
       "      <th>470</th>\n",
       "      <th>471</th>\n",
       "      <th>472</th>\n",
       "      <th>473</th>\n",
       "      <th>474</th>\n",
       "      <th>475</th>\n",
       "      <th>476</th>\n",
       "      <th>477</th>\n",
       "      <th>478</th>\n",
       "      <th>479</th>\n",
       "      <th>480</th>\n",
       "      <th>481</th>\n",
       "      <th>482</th>\n",
       "      <th>483</th>\n",
       "      <th>484</th>\n",
       "      <th>485</th>\n",
       "      <th>486</th>\n",
       "      <th>487</th>\n",
       "      <th>488</th>\n",
       "      <th>489</th>\n",
       "      <th>490</th>\n",
       "      <th>491</th>\n",
       "      <th>492</th>\n",
       "      <th>493</th>\n",
       "      <th>494</th>\n",
       "      <th>...</th>\n",
       "      <th>783</th>\n",
       "      <th>784</th>\n",
       "      <th>785</th>\n",
       "      <th>786</th>\n",
       "      <th>787</th>\n",
       "      <th>788</th>\n",
       "      <th>789</th>\n",
       "      <th>790</th>\n",
       "      <th>791</th>\n",
       "      <th>792</th>\n",
       "      <th>793</th>\n",
       "      <th>794</th>\n",
       "      <th>795</th>\n",
       "      <th>796</th>\n",
       "      <th>797</th>\n",
       "      <th>798</th>\n",
       "      <th>799</th>\n",
       "      <th>800</th>\n",
       "      <th>801</th>\n",
       "      <th>802</th>\n",
       "      <th>803</th>\n",
       "      <th>804</th>\n",
       "      <th>805</th>\n",
       "      <th>806</th>\n",
       "      <th>807</th>\n",
       "      <th>808</th>\n",
       "      <th>809</th>\n",
       "      <th>810</th>\n",
       "      <th>811</th>\n",
       "      <th>812</th>\n",
       "      <th>813</th>\n",
       "      <th>814</th>\n",
       "      <th>815</th>\n",
       "      <th>816</th>\n",
       "      <th>817</th>\n",
       "      <th>818</th>\n",
       "      <th>819</th>\n",
       "      <th>820</th>\n",
       "      <th>821</th>\n",
       "      <th>822</th>\n",
       "      <th>823</th>\n",
       "      <th>824</th>\n",
       "      <th>825</th>\n",
       "      <th>826</th>\n",
       "      <th>827</th>\n",
       "      <th>828</th>\n",
       "      <th>829</th>\n",
       "      <th>830</th>\n",
       "      <th>831</th>\n",
       "      <th>832</th>\n",
       "      <th>833</th>\n",
       "      <th>834</th>\n",
       "      <th>835</th>\n",
       "      <th>836</th>\n",
       "      <th>837</th>\n",
       "      <th>838</th>\n",
       "      <th>839</th>\n",
       "      <th>840</th>\n",
       "      <th>841</th>\n",
       "      <th>842</th>\n",
       "      <th>843</th>\n",
       "      <th>844</th>\n",
       "      <th>845</th>\n",
       "      <th>846</th>\n",
       "      <th>847</th>\n",
       "      <th>848</th>\n",
       "      <th>849</th>\n",
       "      <th>850</th>\n",
       "      <th>851</th>\n",
       "      <th>852</th>\n",
       "      <th>853</th>\n",
       "      <th>854</th>\n",
       "      <th>855</th>\n",
       "      <th>856</th>\n",
       "      <th>857</th>\n",
       "      <th>858</th>\n",
       "      <th>859</th>\n",
       "      <th>860</th>\n",
       "      <th>861</th>\n",
       "      <th>862</th>\n",
       "      <th>863</th>\n",
       "      <th>864</th>\n",
       "      <th>865</th>\n",
       "      <th>866</th>\n",
       "      <th>867</th>\n",
       "      <th>868</th>\n",
       "      <th>869</th>\n",
       "      <th>870</th>\n",
       "      <th>871</th>\n",
       "      <th>872</th>\n",
       "      <th>873</th>\n",
       "      <th>874</th>\n",
       "      <th>875</th>\n",
       "      <th>876</th>\n",
       "      <th>877</th>\n",
       "      <th>878</th>\n",
       "      <th>879</th>\n",
       "      <th>880</th>\n",
       "      <th>881</th>\n",
       "      <th>882</th>\n",
       "      <th>883</th>\n",
       "      <th>884</th>\n",
       "      <th>885</th>\n",
       "      <th>886</th>\n",
       "      <th>887</th>\n",
       "      <th>888</th>\n",
       "      <th>889</th>\n",
       "      <th>890</th>\n",
       "      <th>891</th>\n",
       "      <th>892</th>\n",
       "      <th>893</th>\n",
       "      <th>894</th>\n",
       "      <th>895</th>\n",
       "      <th>896</th>\n",
       "      <th>897</th>\n",
       "      <th>898</th>\n",
       "      <th>899</th>\n",
       "      <th>900</th>\n",
       "      <th>901</th>\n",
       "      <th>902</th>\n",
       "      <th>903</th>\n",
       "      <th>904</th>\n",
       "      <th>905</th>\n",
       "      <th>906</th>\n",
       "      <th>907</th>\n",
       "      <th>908</th>\n",
       "      <th>909</th>\n",
       "      <th>910</th>\n",
       "      <th>911</th>\n",
       "      <th>912</th>\n",
       "      <th>913</th>\n",
       "      <th>914</th>\n",
       "      <th>915</th>\n",
       "      <th>916</th>\n",
       "      <th>917</th>\n",
       "      <th>918</th>\n",
       "      <th>919</th>\n",
       "      <th>920</th>\n",
       "      <th>921</th>\n",
       "      <th>922</th>\n",
       "      <th>923</th>\n",
       "      <th>924</th>\n",
       "      <th>925</th>\n",
       "      <th>926</th>\n",
       "      <th>927</th>\n",
       "      <th>928</th>\n",
       "      <th>929</th>\n",
       "      <th>930</th>\n",
       "      <th>931</th>\n",
       "      <th>932</th>\n",
       "      <th>933</th>\n",
       "      <th>934</th>\n",
       "      <th>935</th>\n",
       "      <th>936</th>\n",
       "      <th>937</th>\n",
       "      <th>938</th>\n",
       "      <th>939</th>\n",
       "      <th>940</th>\n",
       "      <th>941</th>\n",
       "      <th>942</th>\n",
       "      <th>943</th>\n",
       "      <th>944</th>\n",
       "      <th>945</th>\n",
       "      <th>946</th>\n",
       "      <th>947</th>\n",
       "      <th>948</th>\n",
       "      <th>949</th>\n",
       "      <th>950</th>\n",
       "      <th>951</th>\n",
       "      <th>952</th>\n",
       "      <th>953</th>\n",
       "      <th>954</th>\n",
       "      <th>955</th>\n",
       "      <th>956</th>\n",
       "      <th>957</th>\n",
       "      <th>958</th>\n",
       "      <th>959</th>\n",
       "      <th>960</th>\n",
       "      <th>961</th>\n",
       "      <th>962</th>\n",
       "      <th>963</th>\n",
       "      <th>964</th>\n",
       "      <th>965</th>\n",
       "      <th>966</th>\n",
       "      <th>967</th>\n",
       "      <th>968</th>\n",
       "      <th>969</th>\n",
       "      <th>970</th>\n",
       "      <th>971</th>\n",
       "      <th>972</th>\n",
       "      <th>973</th>\n",
       "      <th>974</th>\n",
       "      <th>975</th>\n",
       "      <th>976</th>\n",
       "      <th>977</th>\n",
       "      <th>978</th>\n",
       "      <th>979</th>\n",
       "      <th>980</th>\n",
       "      <th>981</th>\n",
       "      <th>982</th>\n",
       "      <th>983</th>\n",
       "      <th>984</th>\n",
       "      <th>985</th>\n",
       "      <th>986</th>\n",
       "      <th>987</th>\n",
       "      <th>988</th>\n",
       "      <th>989</th>\n",
       "      <th>990</th>\n",
       "      <th>991</th>\n",
       "      <th>992</th>\n",
       "      <th>993</th>\n",
       "      <th>994</th>\n",
       "      <th>995</th>\n",
       "      <th>996</th>\n",
       "      <th>997</th>\n",
       "      <th>998</th>\n",
       "      <th>999</th>\n",
       "      <th>1000</th>\n",
       "      <th>1001</th>\n",
       "      <th>1002</th>\n",
       "      <th>1003</th>\n",
       "      <th>1004</th>\n",
       "      <th>1005</th>\n",
       "      <th>1006</th>\n",
       "      <th>1007</th>\n",
       "      <th>1008</th>\n",
       "      <th>1009</th>\n",
       "      <th>1010</th>\n",
       "      <th>1011</th>\n",
       "      <th>1012</th>\n",
       "      <th>1013</th>\n",
       "      <th>1014</th>\n",
       "      <th>1015</th>\n",
       "      <th>1016</th>\n",
       "      <th>1017</th>\n",
       "      <th>1018</th>\n",
       "      <th>1019</th>\n",
       "      <th>1020</th>\n",
       "      <th>1021</th>\n",
       "      <th>1022</th>\n",
       "      <th>1023</th>\n",
       "      <th>1024</th>\n",
       "      <th>1025</th>\n",
       "      <th>1026</th>\n",
       "      <th>1027</th>\n",
       "      <th>1028</th>\n",
       "      <th>1029</th>\n",
       "      <th>1030</th>\n",
       "      <th>1031</th>\n",
       "      <th>1032</th>\n",
       "      <th>1033</th>\n",
       "      <th>1034</th>\n",
       "      <th>1035</th>\n",
       "      <th>1036</th>\n",
       "      <th>1037</th>\n",
       "      <th>1038</th>\n",
       "      <th>1039</th>\n",
       "      <th>1040</th>\n",
       "      <th>1041</th>\n",
       "      <th>1042</th>\n",
       "      <th>1043</th>\n",
       "      <th>1044</th>\n",
       "      <th>1045</th>\n",
       "      <th>1046</th>\n",
       "      <th>1047</th>\n",
       "      <th>1048</th>\n",
       "      <th>1049</th>\n",
       "      <th>1050</th>\n",
       "      <th>1051</th>\n",
       "      <th>1052</th>\n",
       "      <th>1053</th>\n",
       "      <th>1054</th>\n",
       "      <th>1055</th>\n",
       "      <th>1056</th>\n",
       "      <th>1057</th>\n",
       "      <th>1058</th>\n",
       "      <th>1059</th>\n",
       "      <th>1060</th>\n",
       "      <th>1061</th>\n",
       "      <th>1062</th>\n",
       "      <th>1063</th>\n",
       "      <th>1064</th>\n",
       "      <th>1065</th>\n",
       "      <th>1066</th>\n",
       "      <th>1067</th>\n",
       "      <th>1068</th>\n",
       "      <th>1069</th>\n",
       "      <th>1070</th>\n",
       "      <th>1071</th>\n",
       "      <th>1072</th>\n",
       "      <th>1073</th>\n",
       "      <th>1074</th>\n",
       "      <th>1075</th>\n",
       "      <th>1076</th>\n",
       "      <th>1077</th>\n",
       "      <th>1078</th>\n",
       "      <th>1079</th>\n",
       "      <th>1080</th>\n",
       "      <th>1081</th>\n",
       "      <th>1082</th>\n",
       "      <th>1083</th>\n",
       "      <th>1084</th>\n",
       "      <th>1085</th>\n",
       "      <th>1086</th>\n",
       "      <th>1087</th>\n",
       "      <th>1088</th>\n",
       "      <th>1089</th>\n",
       "      <th>1090</th>\n",
       "      <th>1091</th>\n",
       "      <th>1092</th>\n",
       "      <th>1093</th>\n",
       "      <th>1094</th>\n",
       "      <th>1095</th>\n",
       "      <th>1096</th>\n",
       "      <th>1097</th>\n",
       "      <th>1098</th>\n",
       "      <th>1099</th>\n",
       "      <th>1100</th>\n",
       "      <th>1101</th>\n",
       "      <th>1102</th>\n",
       "      <th>1103</th>\n",
       "      <th>1104</th>\n",
       "      <th>1105</th>\n",
       "      <th>1106</th>\n",
       "      <th>1107</th>\n",
       "      <th>1108</th>\n",
       "      <th>1109</th>\n",
       "      <th>1110</th>\n",
       "      <th>1111</th>\n",
       "      <th>1112</th>\n",
       "      <th>1113</th>\n",
       "      <th>1114</th>\n",
       "      <th>1115</th>\n",
       "      <th>1116</th>\n",
       "      <th>1117</th>\n",
       "      <th>1118</th>\n",
       "      <th>1119</th>\n",
       "      <th>1120</th>\n",
       "      <th>1121</th>\n",
       "      <th>1122</th>\n",
       "      <th>1123</th>\n",
       "      <th>1124</th>\n",
       "      <th>1125</th>\n",
       "      <th>1126</th>\n",
       "      <th>1127</th>\n",
       "      <th>1128</th>\n",
       "      <th>1129</th>\n",
       "      <th>1130</th>\n",
       "      <th>1131</th>\n",
       "      <th>1132</th>\n",
       "      <th>1133</th>\n",
       "      <th>1134</th>\n",
       "      <th>1135</th>\n",
       "      <th>1136</th>\n",
       "      <th>1137</th>\n",
       "      <th>1138</th>\n",
       "      <th>1139</th>\n",
       "      <th>1140</th>\n",
       "      <th>1141</th>\n",
       "      <th>1142</th>\n",
       "      <th>1143</th>\n",
       "      <th>1144</th>\n",
       "      <th>1145</th>\n",
       "      <th>1146</th>\n",
       "      <th>1147</th>\n",
       "      <th>1148</th>\n",
       "      <th>1149</th>\n",
       "      <th>1150</th>\n",
       "      <th>1151</th>\n",
       "      <th>1152</th>\n",
       "      <th>1153</th>\n",
       "      <th>1154</th>\n",
       "      <th>1155</th>\n",
       "      <th>1156</th>\n",
       "      <th>1157</th>\n",
       "      <th>1158</th>\n",
       "      <th>1159</th>\n",
       "      <th>1160</th>\n",
       "      <th>1161</th>\n",
       "      <th>1162</th>\n",
       "      <th>1163</th>\n",
       "      <th>1164</th>\n",
       "      <th>1165</th>\n",
       "      <th>1166</th>\n",
       "      <th>1167</th>\n",
       "      <th>1168</th>\n",
       "      <th>1169</th>\n",
       "      <th>1170</th>\n",
       "      <th>1171</th>\n",
       "      <th>1172</th>\n",
       "      <th>1173</th>\n",
       "      <th>1174</th>\n",
       "      <th>1175</th>\n",
       "      <th>1176</th>\n",
       "      <th>1177</th>\n",
       "      <th>1178</th>\n",
       "      <th>1179</th>\n",
       "      <th>1180</th>\n",
       "      <th>1181</th>\n",
       "      <th>1182</th>\n",
       "      <th>1183</th>\n",
       "      <th>1184</th>\n",
       "      <th>1185</th>\n",
       "      <th>1186</th>\n",
       "      <th>1187</th>\n",
       "      <th>1188</th>\n",
       "      <th>1189</th>\n",
       "      <th>1190</th>\n",
       "      <th>1191</th>\n",
       "      <th>1192</th>\n",
       "      <th>1193</th>\n",
       "      <th>1194</th>\n",
       "      <th>1195</th>\n",
       "      <th>1196</th>\n",
       "      <th>1197</th>\n",
       "      <th>1198</th>\n",
       "      <th>1199</th>\n",
       "      <th>1200</th>\n",
       "      <th>1201</th>\n",
       "      <th>1202</th>\n",
       "      <th>1203</th>\n",
       "      <th>1204</th>\n",
       "      <th>1205</th>\n",
       "      <th>1206</th>\n",
       "      <th>1207</th>\n",
       "      <th>1208</th>\n",
       "      <th>1209</th>\n",
       "      <th>1210</th>\n",
       "      <th>1211</th>\n",
       "      <th>1212</th>\n",
       "      <th>1213</th>\n",
       "      <th>1214</th>\n",
       "      <th>1215</th>\n",
       "      <th>1216</th>\n",
       "      <th>1217</th>\n",
       "      <th>1218</th>\n",
       "      <th>1219</th>\n",
       "      <th>1220</th>\n",
       "      <th>1221</th>\n",
       "      <th>1222</th>\n",
       "      <th>1223</th>\n",
       "      <th>1224</th>\n",
       "      <th>1225</th>\n",
       "      <th>1226</th>\n",
       "      <th>1227</th>\n",
       "      <th>1228</th>\n",
       "      <th>1229</th>\n",
       "      <th>1230</th>\n",
       "      <th>1231</th>\n",
       "      <th>1232</th>\n",
       "      <th>1233</th>\n",
       "      <th>1234</th>\n",
       "      <th>1235</th>\n",
       "      <th>1236</th>\n",
       "      <th>1237</th>\n",
       "      <th>1238</th>\n",
       "      <th>1239</th>\n",
       "      <th>1240</th>\n",
       "      <th>1241</th>\n",
       "      <th>1242</th>\n",
       "      <th>1243</th>\n",
       "      <th>1244</th>\n",
       "      <th>1245</th>\n",
       "      <th>1246</th>\n",
       "      <th>1247</th>\n",
       "      <th>1248</th>\n",
       "      <th>1249</th>\n",
       "      <th>1250</th>\n",
       "      <th>1251</th>\n",
       "      <th>1252</th>\n",
       "      <th>1253</th>\n",
       "      <th>1254</th>\n",
       "      <th>1255</th>\n",
       "      <th>1256</th>\n",
       "      <th>1257</th>\n",
       "      <th>1258</th>\n",
       "      <th>1259</th>\n",
       "      <th>1260</th>\n",
       "      <th>1261</th>\n",
       "      <th>1262</th>\n",
       "      <th>1263</th>\n",
       "      <th>1264</th>\n",
       "      <th>1265</th>\n",
       "      <th>1266</th>\n",
       "      <th>1267</th>\n",
       "      <th>1268</th>\n",
       "      <th>1269</th>\n",
       "      <th>1270</th>\n",
       "      <th>1271</th>\n",
       "      <th>1272</th>\n",
       "      <th>1273</th>\n",
       "      <th>1274</th>\n",
       "      <th>1275</th>\n",
       "      <th>1276</th>\n",
       "      <th>1277</th>\n",
       "      <th>1278</th>\n",
       "      <th>1279</th>\n",
       "      <th>len</th>\n",
       "      <th>preds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>31390</td>\n",
       "      <td>VPVNPEPDATSVENVAEKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>8</td>\n",
       "      <td>VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>-0.000880</td>\n",
       "      <td>0.005861</td>\n",
       "      <td>-0.001142</td>\n",
       "      <td>0.001560</td>\n",
       "      <td>-0.001140</td>\n",
       "      <td>0.003098</td>\n",
       "      <td>-0.000677</td>\n",
       "      <td>0.009220</td>\n",
       "      <td>0.006545</td>\n",
       "      <td>0.005213</td>\n",
       "      <td>0.001721</td>\n",
       "      <td>0.001665</td>\n",
       "      <td>0.002427</td>\n",
       "      <td>0.001326</td>\n",
       "      <td>0.000078</td>\n",
       "      <td>-0.000716</td>\n",
       "      <td>-0.005735</td>\n",
       "      <td>-0.003838</td>\n",
       "      <td>-0.002226</td>\n",
       "      <td>0.000062</td>\n",
       "      <td>0.007706</td>\n",
       "      <td>0.001523</td>\n",
       "      <td>0.000442</td>\n",
       "      <td>-0.004630</td>\n",
       "      <td>0.004695</td>\n",
       "      <td>0.006622</td>\n",
       "      <td>0.000703</td>\n",
       "      <td>-0.004250</td>\n",
       "      <td>-0.000168</td>\n",
       "      <td>-0.008219</td>\n",
       "      <td>-0.011683</td>\n",
       "      <td>0.006361</td>\n",
       "      <td>0.006471</td>\n",
       "      <td>-0.007541</td>\n",
       "      <td>-0.003363</td>\n",
       "      <td>-0.004653</td>\n",
       "      <td>-0.004417</td>\n",
       "      <td>-0.001235</td>\n",
       "      <td>0.008840</td>\n",
       "      <td>0.000694</td>\n",
       "      <td>0.000850</td>\n",
       "      <td>0.006141</td>\n",
       "      <td>-0.003925</td>\n",
       "      <td>-0.001583</td>\n",
       "      <td>-0.009671</td>\n",
       "      <td>-0.001748</td>\n",
       "      <td>-0.003297</td>\n",
       "      <td>0.000377</td>\n",
       "      <td>0.004377</td>\n",
       "      <td>-0.004123</td>\n",
       "      <td>-0.005825</td>\n",
       "      <td>0.014136</td>\n",
       "      <td>-0.003595</td>\n",
       "      <td>-0.003714</td>\n",
       "      <td>-0.006888</td>\n",
       "      <td>0.002039</td>\n",
       "      <td>-0.005702</td>\n",
       "      <td>-0.003207</td>\n",
       "      <td>0.004504</td>\n",
       "      <td>-0.000632</td>\n",
       "      <td>0.005922</td>\n",
       "      <td>-0.000584</td>\n",
       "      <td>-0.007453</td>\n",
       "      <td>-0.000234</td>\n",
       "      <td>-0.003078</td>\n",
       "      <td>0.000713</td>\n",
       "      <td>0.000698</td>\n",
       "      <td>-0.005901</td>\n",
       "      <td>-0.004494</td>\n",
       "      <td>0.001243</td>\n",
       "      <td>0.000557</td>\n",
       "      <td>-0.004787</td>\n",
       "      <td>-0.006329</td>\n",
       "      <td>0.004250</td>\n",
       "      <td>0.003193</td>\n",
       "      <td>0.000611</td>\n",
       "      <td>0.004937</td>\n",
       "      <td>-0.002435</td>\n",
       "      <td>-0.010002</td>\n",
       "      <td>0.005202</td>\n",
       "      <td>-0.004449</td>\n",
       "      <td>0.001022</td>\n",
       "      <td>-0.001900</td>\n",
       "      <td>-0.005596</td>\n",
       "      <td>-0.000590</td>\n",
       "      <td>-0.000775</td>\n",
       "      <td>0.000065</td>\n",
       "      <td>0.001447</td>\n",
       "      <td>-0.009103</td>\n",
       "      <td>-0.007289</td>\n",
       "      <td>-0.003843</td>\n",
       "      <td>-0.002246</td>\n",
       "      <td>-0.000216</td>\n",
       "      <td>0.001120</td>\n",
       "      <td>-0.001694</td>\n",
       "      <td>-0.001785</td>\n",
       "      <td>-0.004490</td>\n",
       "      <td>-0.004186</td>\n",
       "      <td>0.003316</td>\n",
       "      <td>-0.006126</td>\n",
       "      <td>0.004397</td>\n",
       "      <td>0.000563</td>\n",
       "      <td>0.003522</td>\n",
       "      <td>-0.002592</td>\n",
       "      <td>-0.000511</td>\n",
       "      <td>-0.002908</td>\n",
       "      <td>-0.003775</td>\n",
       "      <td>-0.000803</td>\n",
       "      <td>0.003068</td>\n",
       "      <td>0.003710</td>\n",
       "      <td>-0.003042</td>\n",
       "      <td>-0.005348</td>\n",
       "      <td>0.005032</td>\n",
       "      <td>0.004530</td>\n",
       "      <td>-0.006334</td>\n",
       "      <td>0.001030</td>\n",
       "      <td>-0.002692</td>\n",
       "      <td>-0.001035</td>\n",
       "      <td>-0.000708</td>\n",
       "      <td>0.013762</td>\n",
       "      <td>0.004706</td>\n",
       "      <td>-0.004970</td>\n",
       "      <td>-0.001227</td>\n",
       "      <td>-0.002073</td>\n",
       "      <td>-0.004395</td>\n",
       "      <td>-0.003007</td>\n",
       "      <td>-0.001933</td>\n",
       "      <td>0.002220</td>\n",
       "      <td>-0.005801</td>\n",
       "      <td>0.000941</td>\n",
       "      <td>-0.004171</td>\n",
       "      <td>0.003066</td>\n",
       "      <td>0.003047</td>\n",
       "      <td>0.006733</td>\n",
       "      <td>-0.001738</td>\n",
       "      <td>0.006408</td>\n",
       "      <td>-0.004232</td>\n",
       "      <td>-0.001138</td>\n",
       "      <td>0.007493</td>\n",
       "      <td>0.003127</td>\n",
       "      <td>-0.005692</td>\n",
       "      <td>0.006050</td>\n",
       "      <td>-0.003088</td>\n",
       "      <td>0.003156</td>\n",
       "      <td>-0.005429</td>\n",
       "      <td>0.006658</td>\n",
       "      <td>0.004450</td>\n",
       "      <td>0.002410</td>\n",
       "      <td>0.002481</td>\n",
       "      <td>0.013582</td>\n",
       "      <td>0.001654</td>\n",
       "      <td>-0.000327</td>\n",
       "      <td>-0.002682</td>\n",
       "      <td>-0.002992</td>\n",
       "      <td>0.007328</td>\n",
       "      <td>0.012059</td>\n",
       "      <td>-0.002122</td>\n",
       "      <td>-0.000760</td>\n",
       "      <td>0.007938</td>\n",
       "      <td>0.004236</td>\n",
       "      <td>-0.007783</td>\n",
       "      <td>-0.001685</td>\n",
       "      <td>-0.002012</td>\n",
       "      <td>-0.003006</td>\n",
       "      <td>-0.000200</td>\n",
       "      <td>-0.002088</td>\n",
       "      <td>0.001345</td>\n",
       "      <td>-0.000170</td>\n",
       "      <td>-0.002235</td>\n",
       "      <td>0.006566</td>\n",
       "      <td>-0.002846</td>\n",
       "      <td>0.004572</td>\n",
       "      <td>0.006810</td>\n",
       "      <td>-0.004250</td>\n",
       "      <td>0.007363</td>\n",
       "      <td>-0.002255</td>\n",
       "      <td>0.003187</td>\n",
       "      <td>-0.008666</td>\n",
       "      <td>0.008766</td>\n",
       "      <td>-0.012510</td>\n",
       "      <td>0.002735</td>\n",
       "      <td>-0.002226</td>\n",
       "      <td>-0.004583</td>\n",
       "      <td>-0.000017</td>\n",
       "      <td>0.000594</td>\n",
       "      <td>0.007394</td>\n",
       "      <td>0.007216</td>\n",
       "      <td>-0.009349</td>\n",
       "      <td>0.006109</td>\n",
       "      <td>-0.003539</td>\n",
       "      <td>-0.001058</td>\n",
       "      <td>0.006410</td>\n",
       "      <td>-0.003968</td>\n",
       "      <td>-0.003418</td>\n",
       "      <td>-0.005987</td>\n",
       "      <td>-0.000349</td>\n",
       "      <td>-0.003589</td>\n",
       "      <td>-0.004120</td>\n",
       "      <td>-0.003990</td>\n",
       "      <td>0.006590</td>\n",
       "      <td>-0.004517</td>\n",
       "      <td>-0.007955</td>\n",
       "      <td>-0.005222</td>\n",
       "      <td>0.002230</td>\n",
       "      <td>0.005574</td>\n",
       "      <td>0.000754</td>\n",
       "      <td>0.008606</td>\n",
       "      <td>0.002115</td>\n",
       "      <td>0.002924</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>0.003336</td>\n",
       "      <td>0.003689</td>\n",
       "      <td>-0.000887</td>\n",
       "      <td>-0.000204</td>\n",
       "      <td>0.000128</td>\n",
       "      <td>-0.003729</td>\n",
       "      <td>-0.002760</td>\n",
       "      <td>-0.005721</td>\n",
       "      <td>0.004585</td>\n",
       "      <td>0.002891</td>\n",
       "      <td>-0.003355</td>\n",
       "      <td>0.005476</td>\n",
       "      <td>-0.002326</td>\n",
       "      <td>-0.001338</td>\n",
       "      <td>0.004515</td>\n",
       "      <td>-0.006109</td>\n",
       "      <td>-0.004300</td>\n",
       "      <td>0.006142</td>\n",
       "      <td>-0.008638</td>\n",
       "      <td>-0.001841</td>\n",
       "      <td>-0.003307</td>\n",
       "      <td>-0.007982</td>\n",
       "      <td>-0.000609</td>\n",
       "      <td>-0.007637</td>\n",
       "      <td>-0.009760</td>\n",
       "      <td>0.000834</td>\n",
       "      <td>-0.004194</td>\n",
       "      <td>0.001217</td>\n",
       "      <td>0.004657</td>\n",
       "      <td>-0.002367</td>\n",
       "      <td>-0.003185</td>\n",
       "      <td>0.002436</td>\n",
       "      <td>0.004250</td>\n",
       "      <td>-0.000503</td>\n",
       "      <td>0.001145</td>\n",
       "      <td>0.001158</td>\n",
       "      <td>0.001879</td>\n",
       "      <td>-0.001357</td>\n",
       "      <td>-0.000628</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>-0.007244</td>\n",
       "      <td>-0.007605</td>\n",
       "      <td>-0.003452</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.001796</td>\n",
       "      <td>-0.000046</td>\n",
       "      <td>-0.002339</td>\n",
       "      <td>-0.000479</td>\n",
       "      <td>0.007232</td>\n",
       "      <td>-0.010644</td>\n",
       "      <td>0.005247</td>\n",
       "      <td>-0.005556</td>\n",
       "      <td>0.002255</td>\n",
       "      <td>-0.003174</td>\n",
       "      <td>0.010494</td>\n",
       "      <td>0.005637</td>\n",
       "      <td>-0.001970</td>\n",
       "      <td>-0.000483</td>\n",
       "      <td>-0.008590</td>\n",
       "      <td>0.002272</td>\n",
       "      <td>0.003792</td>\n",
       "      <td>-0.004972</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>-0.000027</td>\n",
       "      <td>-0.002423</td>\n",
       "      <td>0.000693</td>\n",
       "      <td>-0.003254</td>\n",
       "      <td>-0.007957</td>\n",
       "      <td>-0.001948</td>\n",
       "      <td>0.006308</td>\n",
       "      <td>-0.001018</td>\n",
       "      <td>-0.005609</td>\n",
       "      <td>0.000670</td>\n",
       "      <td>0.004219</td>\n",
       "      <td>-0.008333</td>\n",
       "      <td>-0.003207</td>\n",
       "      <td>0.005300</td>\n",
       "      <td>0.002946</td>\n",
       "      <td>-0.011096</td>\n",
       "      <td>-0.005440</td>\n",
       "      <td>-0.006602</td>\n",
       "      <td>0.001100</td>\n",
       "      <td>-0.001819</td>\n",
       "      <td>-0.004929</td>\n",
       "      <td>0.004408</td>\n",
       "      <td>-0.002294</td>\n",
       "      <td>-0.001896</td>\n",
       "      <td>-0.011765</td>\n",
       "      <td>0.011569</td>\n",
       "      <td>-0.009669</td>\n",
       "      <td>-0.000850</td>\n",
       "      <td>-0.001947</td>\n",
       "      <td>-0.003291</td>\n",
       "      <td>-0.002720</td>\n",
       "      <td>0.004024</td>\n",
       "      <td>-0.003592</td>\n",
       "      <td>0.006291</td>\n",
       "      <td>0.009176</td>\n",
       "      <td>-0.000684</td>\n",
       "      <td>0.002185</td>\n",
       "      <td>-0.008286</td>\n",
       "      <td>0.005002</td>\n",
       "      <td>-0.003498</td>\n",
       "      <td>0.002933</td>\n",
       "      <td>0.007788</td>\n",
       "      <td>0.000454</td>\n",
       "      <td>-0.004595</td>\n",
       "      <td>-0.000274</td>\n",
       "      <td>-0.003731</td>\n",
       "      <td>0.004325</td>\n",
       "      <td>0.000980</td>\n",
       "      <td>0.003137</td>\n",
       "      <td>-0.008290</td>\n",
       "      <td>-0.000637</td>\n",
       "      <td>-0.003388</td>\n",
       "      <td>0.002274</td>\n",
       "      <td>0.002616</td>\n",
       "      <td>-0.001681</td>\n",
       "      <td>0.007493</td>\n",
       "      <td>-0.001374</td>\n",
       "      <td>0.001922</td>\n",
       "      <td>0.000747</td>\n",
       "      <td>0.005497</td>\n",
       "      <td>-0.004544</td>\n",
       "      <td>-0.005103</td>\n",
       "      <td>0.001857</td>\n",
       "      <td>0.006852</td>\n",
       "      <td>-0.003110</td>\n",
       "      <td>-0.003492</td>\n",
       "      <td>0.011977</td>\n",
       "      <td>-0.001746</td>\n",
       "      <td>-0.006554</td>\n",
       "      <td>-0.004790</td>\n",
       "      <td>0.003478</td>\n",
       "      <td>0.004946</td>\n",
       "      <td>0.004604</td>\n",
       "      <td>-0.012539</td>\n",
       "      <td>-0.001268</td>\n",
       "      <td>-0.001721</td>\n",
       "      <td>-0.000085</td>\n",
       "      <td>0.002606</td>\n",
       "      <td>-0.003262</td>\n",
       "      <td>0.008400</td>\n",
       "      <td>-0.006088</td>\n",
       "      <td>-0.006039</td>\n",
       "      <td>-0.001080</td>\n",
       "      <td>0.004411</td>\n",
       "      <td>0.002365</td>\n",
       "      <td>-0.004801</td>\n",
       "      <td>-0.006958</td>\n",
       "      <td>-0.000641</td>\n",
       "      <td>0.002824</td>\n",
       "      <td>0.006942</td>\n",
       "      <td>-0.005025</td>\n",
       "      <td>0.002441</td>\n",
       "      <td>0.001353</td>\n",
       "      <td>-0.000082</td>\n",
       "      <td>-0.004659</td>\n",
       "      <td>0.001985</td>\n",
       "      <td>0.001751</td>\n",
       "      <td>0.007858</td>\n",
       "      <td>0.001790</td>\n",
       "      <td>0.000919</td>\n",
       "      <td>-0.000298</td>\n",
       "      <td>-0.002244</td>\n",
       "      <td>0.004237</td>\n",
       "      <td>0.000828</td>\n",
       "      <td>-0.006844</td>\n",
       "      <td>0.008459</td>\n",
       "      <td>0.005118</td>\n",
       "      <td>-0.000023</td>\n",
       "      <td>-0.013254</td>\n",
       "      <td>-0.000635</td>\n",
       "      <td>0.001363</td>\n",
       "      <td>-0.001795</td>\n",
       "      <td>-0.002976</td>\n",
       "      <td>-0.002670</td>\n",
       "      <td>-0.004095</td>\n",
       "      <td>-0.004342</td>\n",
       "      <td>0.002858</td>\n",
       "      <td>-0.010473</td>\n",
       "      <td>-0.003198</td>\n",
       "      <td>-0.002863</td>\n",
       "      <td>-0.000459</td>\n",
       "      <td>0.004597</td>\n",
       "      <td>0.004563</td>\n",
       "      <td>0.001963</td>\n",
       "      <td>-0.001478</td>\n",
       "      <td>-0.003395</td>\n",
       "      <td>-0.009020</td>\n",
       "      <td>0.004000</td>\n",
       "      <td>-0.001206</td>\n",
       "      <td>-0.002643</td>\n",
       "      <td>-0.002629</td>\n",
       "      <td>-0.002933</td>\n",
       "      <td>-0.002904</td>\n",
       "      <td>-0.003276</td>\n",
       "      <td>0.008862</td>\n",
       "      <td>-0.001322</td>\n",
       "      <td>0.000425</td>\n",
       "      <td>-0.008587</td>\n",
       "      <td>-0.002175</td>\n",
       "      <td>0.005011</td>\n",
       "      <td>0.002639</td>\n",
       "      <td>0.001981</td>\n",
       "      <td>0.001597</td>\n",
       "      <td>0.003285</td>\n",
       "      <td>0.006081</td>\n",
       "      <td>0.009656</td>\n",
       "      <td>-0.000778</td>\n",
       "      <td>-0.000198</td>\n",
       "      <td>-0.000004</td>\n",
       "      <td>0.004717</td>\n",
       "      <td>0.008202</td>\n",
       "      <td>-0.005843</td>\n",
       "      <td>0.003433</td>\n",
       "      <td>0.002622</td>\n",
       "      <td>-0.007305</td>\n",
       "      <td>-0.001266</td>\n",
       "      <td>0.003037</td>\n",
       "      <td>0.000979</td>\n",
       "      <td>0.003750</td>\n",
       "      <td>0.000326</td>\n",
       "      <td>-0.004067</td>\n",
       "      <td>-0.003417</td>\n",
       "      <td>-0.001478</td>\n",
       "      <td>0.002335</td>\n",
       "      <td>-0.002801</td>\n",
       "      <td>0.006955</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.005252</td>\n",
       "      <td>-0.005993</td>\n",
       "      <td>-0.001634</td>\n",
       "      <td>-0.004723</td>\n",
       "      <td>0.002039</td>\n",
       "      <td>0.002762</td>\n",
       "      <td>-0.000594</td>\n",
       "      <td>-0.002401</td>\n",
       "      <td>-0.002338</td>\n",
       "      <td>0.004323</td>\n",
       "      <td>-0.003520</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>0.003160</td>\n",
       "      <td>-0.002437</td>\n",
       "      <td>0.003282</td>\n",
       "      <td>0.002997</td>\n",
       "      <td>-0.001690</td>\n",
       "      <td>0.005104</td>\n",
       "      <td>0.003124</td>\n",
       "      <td>0.021138</td>\n",
       "      <td>-0.008735</td>\n",
       "      <td>-0.001766</td>\n",
       "      <td>-0.007534</td>\n",
       "      <td>0.006001</td>\n",
       "      <td>0.005115</td>\n",
       "      <td>-0.005641</td>\n",
       "      <td>0.006440</td>\n",
       "      <td>0.000479</td>\n",
       "      <td>-0.005883</td>\n",
       "      <td>0.005565</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>-0.005525</td>\n",
       "      <td>0.002366</td>\n",
       "      <td>0.001094</td>\n",
       "      <td>-0.004438</td>\n",
       "      <td>-0.003804</td>\n",
       "      <td>0.000252</td>\n",
       "      <td>-0.004086</td>\n",
       "      <td>0.007175</td>\n",
       "      <td>0.002231</td>\n",
       "      <td>0.002621</td>\n",
       "      <td>-0.000050</td>\n",
       "      <td>0.003858</td>\n",
       "      <td>0.009224</td>\n",
       "      <td>0.006117</td>\n",
       "      <td>0.004712</td>\n",
       "      <td>0.007446</td>\n",
       "      <td>0.003142</td>\n",
       "      <td>0.005351</td>\n",
       "      <td>0.001471</td>\n",
       "      <td>-0.004765</td>\n",
       "      <td>-0.000367</td>\n",
       "      <td>-0.006590</td>\n",
       "      <td>-0.001904</td>\n",
       "      <td>-0.003761</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001853</td>\n",
       "      <td>-0.004825</td>\n",
       "      <td>-0.004105</td>\n",
       "      <td>0.005022</td>\n",
       "      <td>0.003571</td>\n",
       "      <td>-0.001795</td>\n",
       "      <td>-0.001572</td>\n",
       "      <td>0.006370</td>\n",
       "      <td>-0.001410</td>\n",
       "      <td>-0.004103</td>\n",
       "      <td>-0.002774</td>\n",
       "      <td>-0.003145</td>\n",
       "      <td>-0.003326</td>\n",
       "      <td>0.000314</td>\n",
       "      <td>-0.000896</td>\n",
       "      <td>0.004464</td>\n",
       "      <td>0.006698</td>\n",
       "      <td>0.010924</td>\n",
       "      <td>-0.001516</td>\n",
       "      <td>0.003525</td>\n",
       "      <td>-0.005164</td>\n",
       "      <td>-0.000705</td>\n",
       "      <td>0.003306</td>\n",
       "      <td>-0.000277</td>\n",
       "      <td>0.004697</td>\n",
       "      <td>-0.007911</td>\n",
       "      <td>0.003834</td>\n",
       "      <td>-0.003547</td>\n",
       "      <td>-0.005056</td>\n",
       "      <td>0.000232</td>\n",
       "      <td>-0.002777</td>\n",
       "      <td>-0.002308</td>\n",
       "      <td>0.001011</td>\n",
       "      <td>0.003399</td>\n",
       "      <td>-0.011207</td>\n",
       "      <td>-0.005757</td>\n",
       "      <td>-0.005707</td>\n",
       "      <td>0.006208</td>\n",
       "      <td>0.006205</td>\n",
       "      <td>-0.004009</td>\n",
       "      <td>-0.006675</td>\n",
       "      <td>-0.004794</td>\n",
       "      <td>0.001098</td>\n",
       "      <td>0.001365</td>\n",
       "      <td>0.011387</td>\n",
       "      <td>-0.001293</td>\n",
       "      <td>0.010500</td>\n",
       "      <td>0.000524</td>\n",
       "      <td>0.002752</td>\n",
       "      <td>-0.002868</td>\n",
       "      <td>0.000371</td>\n",
       "      <td>-0.000415</td>\n",
       "      <td>0.004123</td>\n",
       "      <td>-0.001168</td>\n",
       "      <td>-0.003838</td>\n",
       "      <td>0.000399</td>\n",
       "      <td>0.006600</td>\n",
       "      <td>0.004980</td>\n",
       "      <td>-0.010759</td>\n",
       "      <td>0.000608</td>\n",
       "      <td>0.000529</td>\n",
       "      <td>0.001002</td>\n",
       "      <td>-0.005758</td>\n",
       "      <td>-0.003974</td>\n",
       "      <td>0.007797</td>\n",
       "      <td>-0.009725</td>\n",
       "      <td>0.005865</td>\n",
       "      <td>-0.003664</td>\n",
       "      <td>0.008944</td>\n",
       "      <td>0.009346</td>\n",
       "      <td>0.000797</td>\n",
       "      <td>0.000887</td>\n",
       "      <td>0.002772</td>\n",
       "      <td>-0.003367</td>\n",
       "      <td>0.003296</td>\n",
       "      <td>0.001201</td>\n",
       "      <td>-0.000482</td>\n",
       "      <td>0.005248</td>\n",
       "      <td>0.005021</td>\n",
       "      <td>0.001763</td>\n",
       "      <td>0.003390</td>\n",
       "      <td>-0.005972</td>\n",
       "      <td>-0.004258</td>\n",
       "      <td>-0.000625</td>\n",
       "      <td>0.004447</td>\n",
       "      <td>-0.002024</td>\n",
       "      <td>0.000723</td>\n",
       "      <td>0.003046</td>\n",
       "      <td>-0.006266</td>\n",
       "      <td>0.004699</td>\n",
       "      <td>-0.001824</td>\n",
       "      <td>0.004019</td>\n",
       "      <td>-0.003601</td>\n",
       "      <td>-0.028502</td>\n",
       "      <td>-0.000853</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.004616</td>\n",
       "      <td>0.005497</td>\n",
       "      <td>0.001255</td>\n",
       "      <td>0.001495</td>\n",
       "      <td>-0.012231</td>\n",
       "      <td>-0.009861</td>\n",
       "      <td>0.005232</td>\n",
       "      <td>-0.008915</td>\n",
       "      <td>0.005231</td>\n",
       "      <td>-0.002353</td>\n",
       "      <td>-0.004961</td>\n",
       "      <td>0.006445</td>\n",
       "      <td>0.003820</td>\n",
       "      <td>-0.004297</td>\n",
       "      <td>0.007125</td>\n",
       "      <td>0.003156</td>\n",
       "      <td>0.007652</td>\n",
       "      <td>-0.002011</td>\n",
       "      <td>-0.003582</td>\n",
       "      <td>-0.001509</td>\n",
       "      <td>0.000779</td>\n",
       "      <td>0.002303</td>\n",
       "      <td>-0.003520</td>\n",
       "      <td>0.005689</td>\n",
       "      <td>0.010472</td>\n",
       "      <td>0.005543</td>\n",
       "      <td>-0.003652</td>\n",
       "      <td>0.004436</td>\n",
       "      <td>-0.004752</td>\n",
       "      <td>0.004456</td>\n",
       "      <td>0.003100</td>\n",
       "      <td>0.008039</td>\n",
       "      <td>-0.002783</td>\n",
       "      <td>-0.004633</td>\n",
       "      <td>-0.002108</td>\n",
       "      <td>-0.010201</td>\n",
       "      <td>0.001383</td>\n",
       "      <td>0.002102</td>\n",
       "      <td>0.006877</td>\n",
       "      <td>-0.011129</td>\n",
       "      <td>0.001141</td>\n",
       "      <td>0.006317</td>\n",
       "      <td>-0.008450</td>\n",
       "      <td>0.001704</td>\n",
       "      <td>-0.000311</td>\n",
       "      <td>0.011933</td>\n",
       "      <td>0.004289</td>\n",
       "      <td>-0.005513</td>\n",
       "      <td>-0.000602</td>\n",
       "      <td>0.003280</td>\n",
       "      <td>0.007059</td>\n",
       "      <td>0.004133</td>\n",
       "      <td>-0.003220</td>\n",
       "      <td>-0.002597</td>\n",
       "      <td>0.007762</td>\n",
       "      <td>-0.005168</td>\n",
       "      <td>0.005155</td>\n",
       "      <td>-0.001474</td>\n",
       "      <td>0.008265</td>\n",
       "      <td>-0.007314</td>\n",
       "      <td>0.002857</td>\n",
       "      <td>-0.000681</td>\n",
       "      <td>-0.002008</td>\n",
       "      <td>-0.003248</td>\n",
       "      <td>0.001069</td>\n",
       "      <td>0.003655</td>\n",
       "      <td>0.001974</td>\n",
       "      <td>0.009681</td>\n",
       "      <td>-0.008204</td>\n",
       "      <td>0.003589</td>\n",
       "      <td>0.002943</td>\n",
       "      <td>0.005035</td>\n",
       "      <td>0.000491</td>\n",
       "      <td>-0.001282</td>\n",
       "      <td>-0.000248</td>\n",
       "      <td>0.002212</td>\n",
       "      <td>0.002148</td>\n",
       "      <td>0.003609</td>\n",
       "      <td>0.008287</td>\n",
       "      <td>-0.004587</td>\n",
       "      <td>-0.008573</td>\n",
       "      <td>0.000723</td>\n",
       "      <td>0.001434</td>\n",
       "      <td>-0.003390</td>\n",
       "      <td>-0.002041</td>\n",
       "      <td>0.007911</td>\n",
       "      <td>0.006009</td>\n",
       "      <td>-0.002130</td>\n",
       "      <td>0.005947</td>\n",
       "      <td>-0.004412</td>\n",
       "      <td>-0.006648</td>\n",
       "      <td>0.010594</td>\n",
       "      <td>-0.003362</td>\n",
       "      <td>0.002635</td>\n",
       "      <td>-0.009418</td>\n",
       "      <td>-0.001327</td>\n",
       "      <td>-0.005974</td>\n",
       "      <td>-0.005435</td>\n",
       "      <td>0.001865</td>\n",
       "      <td>0.000867</td>\n",
       "      <td>-0.005751</td>\n",
       "      <td>0.005233</td>\n",
       "      <td>-0.002514</td>\n",
       "      <td>-0.004314</td>\n",
       "      <td>0.001509</td>\n",
       "      <td>0.006846</td>\n",
       "      <td>0.006396</td>\n",
       "      <td>0.003910</td>\n",
       "      <td>0.000732</td>\n",
       "      <td>0.007434</td>\n",
       "      <td>0.002479</td>\n",
       "      <td>-0.000767</td>\n",
       "      <td>0.003164</td>\n",
       "      <td>0.001642</td>\n",
       "      <td>0.006758</td>\n",
       "      <td>-0.009542</td>\n",
       "      <td>-0.007527</td>\n",
       "      <td>0.002650</td>\n",
       "      <td>0.004797</td>\n",
       "      <td>0.009927</td>\n",
       "      <td>0.007912</td>\n",
       "      <td>-0.002413</td>\n",
       "      <td>-0.002616</td>\n",
       "      <td>0.000845</td>\n",
       "      <td>0.002013</td>\n",
       "      <td>-0.000816</td>\n",
       "      <td>-0.000949</td>\n",
       "      <td>-0.005307</td>\n",
       "      <td>-0.001706</td>\n",
       "      <td>0.004884</td>\n",
       "      <td>0.002780</td>\n",
       "      <td>-0.000456</td>\n",
       "      <td>-0.003082</td>\n",
       "      <td>0.010725</td>\n",
       "      <td>0.006711</td>\n",
       "      <td>0.005910</td>\n",
       "      <td>0.000381</td>\n",
       "      <td>0.003895</td>\n",
       "      <td>0.007585</td>\n",
       "      <td>0.004521</td>\n",
       "      <td>0.007398</td>\n",
       "      <td>-0.003492</td>\n",
       "      <td>-0.000129</td>\n",
       "      <td>-0.003768</td>\n",
       "      <td>-0.002924</td>\n",
       "      <td>-0.001704</td>\n",
       "      <td>0.004513</td>\n",
       "      <td>0.004837</td>\n",
       "      <td>-0.001674</td>\n",
       "      <td>-0.007842</td>\n",
       "      <td>-0.002553</td>\n",
       "      <td>0.004770</td>\n",
       "      <td>0.004965</td>\n",
       "      <td>-0.003042</td>\n",
       "      <td>0.000574</td>\n",
       "      <td>-0.001793</td>\n",
       "      <td>-0.000634</td>\n",
       "      <td>0.011419</td>\n",
       "      <td>-0.012274</td>\n",
       "      <td>0.007318</td>\n",
       "      <td>0.005310</td>\n",
       "      <td>-0.002118</td>\n",
       "      <td>-0.004183</td>\n",
       "      <td>-0.005952</td>\n",
       "      <td>-0.005874</td>\n",
       "      <td>-0.002159</td>\n",
       "      <td>0.005735</td>\n",
       "      <td>0.000972</td>\n",
       "      <td>0.001641</td>\n",
       "      <td>0.004541</td>\n",
       "      <td>-0.003215</td>\n",
       "      <td>0.002098</td>\n",
       "      <td>0.001160</td>\n",
       "      <td>-0.004673</td>\n",
       "      <td>0.007593</td>\n",
       "      <td>-0.004132</td>\n",
       "      <td>-0.004235</td>\n",
       "      <td>0.009154</td>\n",
       "      <td>0.007042</td>\n",
       "      <td>0.002043</td>\n",
       "      <td>-0.005049</td>\n",
       "      <td>-0.006457</td>\n",
       "      <td>0.004323</td>\n",
       "      <td>-0.003796</td>\n",
       "      <td>-0.000677</td>\n",
       "      <td>0.001260</td>\n",
       "      <td>-0.004335</td>\n",
       "      <td>0.000987</td>\n",
       "      <td>-0.000387</td>\n",
       "      <td>-0.010761</td>\n",
       "      <td>0.006239</td>\n",
       "      <td>0.001163</td>\n",
       "      <td>0.002810</td>\n",
       "      <td>0.002129</td>\n",
       "      <td>0.008587</td>\n",
       "      <td>0.000520</td>\n",
       "      <td>0.002393</td>\n",
       "      <td>-0.001776</td>\n",
       "      <td>-0.004646</td>\n",
       "      <td>-0.001924</td>\n",
       "      <td>-0.001987</td>\n",
       "      <td>-0.002959</td>\n",
       "      <td>-0.006058</td>\n",
       "      <td>-0.004105</td>\n",
       "      <td>0.003657</td>\n",
       "      <td>0.004626</td>\n",
       "      <td>0.004524</td>\n",
       "      <td>-0.000461</td>\n",
       "      <td>0.012908</td>\n",
       "      <td>-0.004787</td>\n",
       "      <td>-0.001794</td>\n",
       "      <td>0.003498</td>\n",
       "      <td>0.001557</td>\n",
       "      <td>0.000731</td>\n",
       "      <td>-0.000431</td>\n",
       "      <td>0.002069</td>\n",
       "      <td>0.001653</td>\n",
       "      <td>0.002036</td>\n",
       "      <td>0.003535</td>\n",
       "      <td>-0.001400</td>\n",
       "      <td>0.002427</td>\n",
       "      <td>0.000632</td>\n",
       "      <td>-0.000073</td>\n",
       "      <td>0.003720</td>\n",
       "      <td>-0.004585</td>\n",
       "      <td>0.010733</td>\n",
       "      <td>0.002584</td>\n",
       "      <td>0.008741</td>\n",
       "      <td>-0.011122</td>\n",
       "      <td>-0.001453</td>\n",
       "      <td>-0.003604</td>\n",
       "      <td>-0.000493</td>\n",
       "      <td>0.003991</td>\n",
       "      <td>0.000632</td>\n",
       "      <td>0.000292</td>\n",
       "      <td>0.001253</td>\n",
       "      <td>0.006234</td>\n",
       "      <td>-0.001079</td>\n",
       "      <td>0.003224</td>\n",
       "      <td>-0.003889</td>\n",
       "      <td>0.003642</td>\n",
       "      <td>0.005208</td>\n",
       "      <td>-0.006301</td>\n",
       "      <td>-0.004531</td>\n",
       "      <td>0.003383</td>\n",
       "      <td>-0.003216</td>\n",
       "      <td>-0.001922</td>\n",
       "      <td>0.008373</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.006317</td>\n",
       "      <td>0.001862</td>\n",
       "      <td>-0.002463</td>\n",
       "      <td>-0.000178</td>\n",
       "      <td>0.000207</td>\n",
       "      <td>0.002494</td>\n",
       "      <td>-0.004085</td>\n",
       "      <td>-0.000317</td>\n",
       "      <td>-0.004050</td>\n",
       "      <td>-0.002591</td>\n",
       "      <td>-0.000578</td>\n",
       "      <td>-0.007256</td>\n",
       "      <td>-0.000095</td>\n",
       "      <td>0.000828</td>\n",
       "      <td>-0.001294</td>\n",
       "      <td>0.001070</td>\n",
       "      <td>-0.003755</td>\n",
       "      <td>-0.003444</td>\n",
       "      <td>0.003891</td>\n",
       "      <td>-0.000255</td>\n",
       "      <td>0.013864</td>\n",
       "      <td>-0.001735</td>\n",
       "      <td>-0.002377</td>\n",
       "      <td>-0.009057</td>\n",
       "      <td>0.001671</td>\n",
       "      <td>0.001164</td>\n",
       "      <td>0.002980</td>\n",
       "      <td>-0.009550</td>\n",
       "      <td>-0.008745</td>\n",
       "      <td>0.002028</td>\n",
       "      <td>0.005308</td>\n",
       "      <td>-0.000641</td>\n",
       "      <td>0.033912</td>\n",
       "      <td>0.002231</td>\n",
       "      <td>-0.002407</td>\n",
       "      <td>0.001768</td>\n",
       "      <td>-0.001168</td>\n",
       "      <td>-0.004282</td>\n",
       "      <td>-0.003597</td>\n",
       "      <td>-0.003565</td>\n",
       "      <td>-0.003218</td>\n",
       "      <td>0.001302</td>\n",
       "      <td>-0.002086</td>\n",
       "      <td>-0.008752</td>\n",
       "      <td>0.001775</td>\n",
       "      <td>0.002813</td>\n",
       "      <td>0.002518</td>\n",
       "      <td>0.006637</td>\n",
       "      <td>-0.006155</td>\n",
       "      <td>0.003113</td>\n",
       "      <td>-0.003088</td>\n",
       "      <td>0.003588</td>\n",
       "      <td>0.000525</td>\n",
       "      <td>-0.008758</td>\n",
       "      <td>0.002451</td>\n",
       "      <td>0.001703</td>\n",
       "      <td>-0.004010</td>\n",
       "      <td>0.001648</td>\n",
       "      <td>0.002025</td>\n",
       "      <td>-0.004000</td>\n",
       "      <td>0.000372</td>\n",
       "      <td>-0.012531</td>\n",
       "      <td>-0.001429</td>\n",
       "      <td>-0.007036</td>\n",
       "      <td>-0.001672</td>\n",
       "      <td>0.001931</td>\n",
       "      <td>-0.000335</td>\n",
       "      <td>0.004489</td>\n",
       "      <td>0.001426</td>\n",
       "      <td>0.002925</td>\n",
       "      <td>-0.005068</td>\n",
       "      <td>0.000946</td>\n",
       "      <td>0.001076</td>\n",
       "      <td>0.000817</td>\n",
       "      <td>-0.006266</td>\n",
       "      <td>-0.006568</td>\n",
       "      <td>0.002272</td>\n",
       "      <td>0.002776</td>\n",
       "      <td>0.002689</td>\n",
       "      <td>0.001243</td>\n",
       "      <td>0.010112</td>\n",
       "      <td>-0.004836</td>\n",
       "      <td>0.002611</td>\n",
       "      <td>0.003935</td>\n",
       "      <td>0.003538</td>\n",
       "      <td>0.006074</td>\n",
       "      <td>-0.001749</td>\n",
       "      <td>-0.003450</td>\n",
       "      <td>-0.003461</td>\n",
       "      <td>0.000416</td>\n",
       "      <td>-0.004331</td>\n",
       "      <td>-0.000705</td>\n",
       "      <td>-0.003025</td>\n",
       "      <td>0.004187</td>\n",
       "      <td>-0.008011</td>\n",
       "      <td>-0.002535</td>\n",
       "      <td>0.001290</td>\n",
       "      <td>0.003631</td>\n",
       "      <td>-0.004148</td>\n",
       "      <td>-0.007724</td>\n",
       "      <td>-0.004900</td>\n",
       "      <td>0.001873</td>\n",
       "      <td>0.002570</td>\n",
       "      <td>0.002026</td>\n",
       "      <td>-0.002774</td>\n",
       "      <td>-0.002987</td>\n",
       "      <td>0.002104</td>\n",
       "      <td>0.001275</td>\n",
       "      <td>0.000386</td>\n",
       "      <td>0.000118</td>\n",
       "      <td>0.001486</td>\n",
       "      <td>0.001503</td>\n",
       "      <td>0.003058</td>\n",
       "      <td>0.004697</td>\n",
       "      <td>-0.002407</td>\n",
       "      <td>-0.005566</td>\n",
       "      <td>-0.003793</td>\n",
       "      <td>-0.000626</td>\n",
       "      <td>-0.000390</td>\n",
       "      <td>0.001811</td>\n",
       "      <td>0.004139</td>\n",
       "      <td>0.009623</td>\n",
       "      <td>-0.002554</td>\n",
       "      <td>0.001318</td>\n",
       "      <td>0.006217</td>\n",
       "      <td>0.001786</td>\n",
       "      <td>-0.004694</td>\n",
       "      <td>-0.000620</td>\n",
       "      <td>-0.000839</td>\n",
       "      <td>0.000981</td>\n",
       "      <td>-0.000774</td>\n",
       "      <td>0.000527</td>\n",
       "      <td>-0.000049</td>\n",
       "      <td>0.000246</td>\n",
       "      <td>-0.006903</td>\n",
       "      <td>-0.007978</td>\n",
       "      <td>-0.004754</td>\n",
       "      <td>0.002166</td>\n",
       "      <td>-0.004440</td>\n",
       "      <td>-0.002391</td>\n",
       "      <td>-0.000643</td>\n",
       "      <td>-0.000126</td>\n",
       "      <td>-0.006577</td>\n",
       "      <td>0.008047</td>\n",
       "      <td>0.004099</td>\n",
       "      <td>0.003754</td>\n",
       "      <td>0.002841</td>\n",
       "      <td>0.008031</td>\n",
       "      <td>0.001052</td>\n",
       "      <td>0.005231</td>\n",
       "      <td>-0.004897</td>\n",
       "      <td>-0.000695</td>\n",
       "      <td>221</td>\n",
       "      <td>-10884.404301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31391</td>\n",
       "      <td>VPVNPEPDATSVENVAKKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>8</td>\n",
       "      <td>VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>-0.000514</td>\n",
       "      <td>0.002023</td>\n",
       "      <td>0.006529</td>\n",
       "      <td>-0.004647</td>\n",
       "      <td>0.002037</td>\n",
       "      <td>-0.000266</td>\n",
       "      <td>-0.000165</td>\n",
       "      <td>0.006555</td>\n",
       "      <td>0.002120</td>\n",
       "      <td>-0.001398</td>\n",
       "      <td>0.000498</td>\n",
       "      <td>-0.000698</td>\n",
       "      <td>0.000558</td>\n",
       "      <td>0.000592</td>\n",
       "      <td>-0.001641</td>\n",
       "      <td>-0.001401</td>\n",
       "      <td>0.005935</td>\n",
       "      <td>0.002921</td>\n",
       "      <td>0.002210</td>\n",
       "      <td>0.001295</td>\n",
       "      <td>0.004519</td>\n",
       "      <td>-0.005045</td>\n",
       "      <td>-0.000317</td>\n",
       "      <td>0.002797</td>\n",
       "      <td>-0.003759</td>\n",
       "      <td>-0.001041</td>\n",
       "      <td>-0.010086</td>\n",
       "      <td>0.001043</td>\n",
       "      <td>-0.000399</td>\n",
       "      <td>-0.002663</td>\n",
       "      <td>-0.001998</td>\n",
       "      <td>-0.004853</td>\n",
       "      <td>0.005246</td>\n",
       "      <td>-0.001988</td>\n",
       "      <td>0.000656</td>\n",
       "      <td>-0.002520</td>\n",
       "      <td>-0.002869</td>\n",
       "      <td>-0.001722</td>\n",
       "      <td>0.005738</td>\n",
       "      <td>0.003100</td>\n",
       "      <td>0.001821</td>\n",
       "      <td>-0.003688</td>\n",
       "      <td>-0.002210</td>\n",
       "      <td>0.000293</td>\n",
       "      <td>0.000813</td>\n",
       "      <td>-0.000995</td>\n",
       "      <td>0.003731</td>\n",
       "      <td>0.001136</td>\n",
       "      <td>-0.001639</td>\n",
       "      <td>0.001343</td>\n",
       "      <td>0.004689</td>\n",
       "      <td>0.004922</td>\n",
       "      <td>-0.003203</td>\n",
       "      <td>-0.002617</td>\n",
       "      <td>-0.002726</td>\n",
       "      <td>-0.000338</td>\n",
       "      <td>-0.003506</td>\n",
       "      <td>0.004604</td>\n",
       "      <td>-0.000120</td>\n",
       "      <td>-0.002236</td>\n",
       "      <td>0.000848</td>\n",
       "      <td>0.004217</td>\n",
       "      <td>-0.001167</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.001542</td>\n",
       "      <td>-0.002504</td>\n",
       "      <td>0.002913</td>\n",
       "      <td>-0.003450</td>\n",
       "      <td>-0.001690</td>\n",
       "      <td>-0.001140</td>\n",
       "      <td>-0.000813</td>\n",
       "      <td>0.000382</td>\n",
       "      <td>-0.000938</td>\n",
       "      <td>0.005969</td>\n",
       "      <td>0.000759</td>\n",
       "      <td>0.000437</td>\n",
       "      <td>0.004642</td>\n",
       "      <td>-0.001402</td>\n",
       "      <td>-0.005463</td>\n",
       "      <td>-0.000447</td>\n",
       "      <td>-0.000400</td>\n",
       "      <td>-0.007205</td>\n",
       "      <td>0.001617</td>\n",
       "      <td>0.000552</td>\n",
       "      <td>0.001775</td>\n",
       "      <td>0.001884</td>\n",
       "      <td>0.001239</td>\n",
       "      <td>0.009410</td>\n",
       "      <td>-0.001185</td>\n",
       "      <td>-0.005192</td>\n",
       "      <td>-0.000956</td>\n",
       "      <td>-0.005783</td>\n",
       "      <td>-0.000927</td>\n",
       "      <td>-0.002372</td>\n",
       "      <td>0.000240</td>\n",
       "      <td>-0.002697</td>\n",
       "      <td>-0.004125</td>\n",
       "      <td>0.001755</td>\n",
       "      <td>0.003197</td>\n",
       "      <td>-0.000605</td>\n",
       "      <td>0.001321</td>\n",
       "      <td>-0.001208</td>\n",
       "      <td>0.001953</td>\n",
       "      <td>0.001707</td>\n",
       "      <td>0.004823</td>\n",
       "      <td>-0.001778</td>\n",
       "      <td>0.000046</td>\n",
       "      <td>-0.005588</td>\n",
       "      <td>-0.003833</td>\n",
       "      <td>0.005903</td>\n",
       "      <td>-0.002701</td>\n",
       "      <td>-0.000305</td>\n",
       "      <td>0.002246</td>\n",
       "      <td>-0.000370</td>\n",
       "      <td>-0.000592</td>\n",
       "      <td>0.000329</td>\n",
       "      <td>0.002070</td>\n",
       "      <td>0.000347</td>\n",
       "      <td>0.001702</td>\n",
       "      <td>-0.000166</td>\n",
       "      <td>-0.000069</td>\n",
       "      <td>0.007289</td>\n",
       "      <td>0.003029</td>\n",
       "      <td>0.000956</td>\n",
       "      <td>0.006247</td>\n",
       "      <td>0.003030</td>\n",
       "      <td>0.000124</td>\n",
       "      <td>-0.000641</td>\n",
       "      <td>-0.002563</td>\n",
       "      <td>0.003606</td>\n",
       "      <td>-0.001970</td>\n",
       "      <td>0.007326</td>\n",
       "      <td>0.001987</td>\n",
       "      <td>0.006974</td>\n",
       "      <td>-0.000799</td>\n",
       "      <td>0.008079</td>\n",
       "      <td>-0.004831</td>\n",
       "      <td>0.002992</td>\n",
       "      <td>-0.003861</td>\n",
       "      <td>0.004352</td>\n",
       "      <td>-0.000036</td>\n",
       "      <td>0.005177</td>\n",
       "      <td>-0.006541</td>\n",
       "      <td>0.000609</td>\n",
       "      <td>0.000208</td>\n",
       "      <td>0.000929</td>\n",
       "      <td>-0.000266</td>\n",
       "      <td>-0.000165</td>\n",
       "      <td>0.003226</td>\n",
       "      <td>0.000780</td>\n",
       "      <td>-0.004527</td>\n",
       "      <td>-0.000945</td>\n",
       "      <td>0.004098</td>\n",
       "      <td>-0.002132</td>\n",
       "      <td>0.003744</td>\n",
       "      <td>0.003986</td>\n",
       "      <td>0.001495</td>\n",
       "      <td>-0.001935</td>\n",
       "      <td>0.005328</td>\n",
       "      <td>-0.003285</td>\n",
       "      <td>0.006778</td>\n",
       "      <td>0.001431</td>\n",
       "      <td>-0.002886</td>\n",
       "      <td>0.001198</td>\n",
       "      <td>0.001040</td>\n",
       "      <td>-0.001998</td>\n",
       "      <td>0.005288</td>\n",
       "      <td>-0.004095</td>\n",
       "      <td>-0.000515</td>\n",
       "      <td>-0.000732</td>\n",
       "      <td>0.000986</td>\n",
       "      <td>0.003424</td>\n",
       "      <td>0.001906</td>\n",
       "      <td>-0.001599</td>\n",
       "      <td>0.005547</td>\n",
       "      <td>-0.000558</td>\n",
       "      <td>0.000861</td>\n",
       "      <td>0.003443</td>\n",
       "      <td>0.001305</td>\n",
       "      <td>-0.003596</td>\n",
       "      <td>-0.000309</td>\n",
       "      <td>0.000136</td>\n",
       "      <td>0.002129</td>\n",
       "      <td>0.003715</td>\n",
       "      <td>0.000656</td>\n",
       "      <td>-0.001256</td>\n",
       "      <td>0.004192</td>\n",
       "      <td>-0.004908</td>\n",
       "      <td>0.001253</td>\n",
       "      <td>-0.000100</td>\n",
       "      <td>-0.004676</td>\n",
       "      <td>0.005369</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.001301</td>\n",
       "      <td>-0.000130</td>\n",
       "      <td>-0.001653</td>\n",
       "      <td>0.002840</td>\n",
       "      <td>0.001271</td>\n",
       "      <td>0.008204</td>\n",
       "      <td>-0.000202</td>\n",
       "      <td>-0.000863</td>\n",
       "      <td>-0.002364</td>\n",
       "      <td>0.001609</td>\n",
       "      <td>0.001860</td>\n",
       "      <td>-0.000888</td>\n",
       "      <td>0.001947</td>\n",
       "      <td>0.006667</td>\n",
       "      <td>0.000171</td>\n",
       "      <td>-0.000011</td>\n",
       "      <td>-0.001766</td>\n",
       "      <td>-0.002764</td>\n",
       "      <td>0.000967</td>\n",
       "      <td>0.003783</td>\n",
       "      <td>0.001290</td>\n",
       "      <td>-0.001496</td>\n",
       "      <td>-0.001686</td>\n",
       "      <td>0.003631</td>\n",
       "      <td>0.000797</td>\n",
       "      <td>-0.004414</td>\n",
       "      <td>0.002109</td>\n",
       "      <td>-0.000737</td>\n",
       "      <td>-0.000792</td>\n",
       "      <td>-0.003543</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>0.002837</td>\n",
       "      <td>-0.001237</td>\n",
       "      <td>-0.002298</td>\n",
       "      <td>0.002736</td>\n",
       "      <td>-0.000320</td>\n",
       "      <td>0.002414</td>\n",
       "      <td>0.000393</td>\n",
       "      <td>-0.001212</td>\n",
       "      <td>-0.003941</td>\n",
       "      <td>-0.001039</td>\n",
       "      <td>-0.009250</td>\n",
       "      <td>-0.002265</td>\n",
       "      <td>-0.004860</td>\n",
       "      <td>0.002201</td>\n",
       "      <td>0.000801</td>\n",
       "      <td>-0.002248</td>\n",
       "      <td>-0.003733</td>\n",
       "      <td>0.001498</td>\n",
       "      <td>-0.003929</td>\n",
       "      <td>-0.000850</td>\n",
       "      <td>0.001544</td>\n",
       "      <td>-0.006092</td>\n",
       "      <td>0.000473</td>\n",
       "      <td>-0.000624</td>\n",
       "      <td>0.002165</td>\n",
       "      <td>0.000542</td>\n",
       "      <td>-0.000222</td>\n",
       "      <td>-0.002133</td>\n",
       "      <td>-0.004275</td>\n",
       "      <td>-0.000211</td>\n",
       "      <td>-0.000457</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>-0.007201</td>\n",
       "      <td>-0.000491</td>\n",
       "      <td>-0.001883</td>\n",
       "      <td>-0.005460</td>\n",
       "      <td>0.006911</td>\n",
       "      <td>-0.004933</td>\n",
       "      <td>0.002711</td>\n",
       "      <td>0.005454</td>\n",
       "      <td>-0.003249</td>\n",
       "      <td>0.005815</td>\n",
       "      <td>0.002572</td>\n",
       "      <td>-0.000396</td>\n",
       "      <td>-0.000483</td>\n",
       "      <td>0.001023</td>\n",
       "      <td>-0.000357</td>\n",
       "      <td>-0.002375</td>\n",
       "      <td>-0.002288</td>\n",
       "      <td>-0.002635</td>\n",
       "      <td>-0.000637</td>\n",
       "      <td>0.002361</td>\n",
       "      <td>0.001522</td>\n",
       "      <td>-0.001509</td>\n",
       "      <td>-0.002052</td>\n",
       "      <td>-0.004516</td>\n",
       "      <td>-0.002954</td>\n",
       "      <td>-0.001485</td>\n",
       "      <td>0.003971</td>\n",
       "      <td>0.002128</td>\n",
       "      <td>-0.002856</td>\n",
       "      <td>-0.002071</td>\n",
       "      <td>0.000398</td>\n",
       "      <td>-0.000610</td>\n",
       "      <td>-0.000013</td>\n",
       "      <td>0.000588</td>\n",
       "      <td>-0.002250</td>\n",
       "      <td>0.001266</td>\n",
       "      <td>-0.000885</td>\n",
       "      <td>-0.001328</td>\n",
       "      <td>0.002051</td>\n",
       "      <td>-0.001935</td>\n",
       "      <td>-0.003351</td>\n",
       "      <td>-0.001675</td>\n",
       "      <td>0.004258</td>\n",
       "      <td>-0.002545</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>-0.000308</td>\n",
       "      <td>0.001822</td>\n",
       "      <td>-0.005645</td>\n",
       "      <td>-0.000234</td>\n",
       "      <td>-0.004319</td>\n",
       "      <td>0.002719</td>\n",
       "      <td>0.001973</td>\n",
       "      <td>0.002813</td>\n",
       "      <td>0.002325</td>\n",
       "      <td>0.001256</td>\n",
       "      <td>-0.003249</td>\n",
       "      <td>0.006546</td>\n",
       "      <td>-0.001979</td>\n",
       "      <td>-0.001485</td>\n",
       "      <td>0.003807</td>\n",
       "      <td>-0.000088</td>\n",
       "      <td>-0.005765</td>\n",
       "      <td>-0.002113</td>\n",
       "      <td>0.000726</td>\n",
       "      <td>-0.000228</td>\n",
       "      <td>0.001708</td>\n",
       "      <td>-0.003648</td>\n",
       "      <td>-0.003335</td>\n",
       "      <td>0.001433</td>\n",
       "      <td>0.000495</td>\n",
       "      <td>-0.002904</td>\n",
       "      <td>-0.001140</td>\n",
       "      <td>0.001934</td>\n",
       "      <td>-0.001544</td>\n",
       "      <td>0.006937</td>\n",
       "      <td>0.003114</td>\n",
       "      <td>0.003723</td>\n",
       "      <td>-0.003374</td>\n",
       "      <td>0.000598</td>\n",
       "      <td>0.003127</td>\n",
       "      <td>0.001971</td>\n",
       "      <td>-0.003489</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>0.002011</td>\n",
       "      <td>0.001543</td>\n",
       "      <td>0.000571</td>\n",
       "      <td>0.002954</td>\n",
       "      <td>-0.004249</td>\n",
       "      <td>-0.000031</td>\n",
       "      <td>-0.002090</td>\n",
       "      <td>-0.006160</td>\n",
       "      <td>-0.001220</td>\n",
       "      <td>0.002064</td>\n",
       "      <td>-0.000844</td>\n",
       "      <td>0.005637</td>\n",
       "      <td>0.002212</td>\n",
       "      <td>0.002191</td>\n",
       "      <td>-0.004165</td>\n",
       "      <td>0.006326</td>\n",
       "      <td>0.000222</td>\n",
       "      <td>-0.001233</td>\n",
       "      <td>0.004685</td>\n",
       "      <td>-0.002974</td>\n",
       "      <td>0.000532</td>\n",
       "      <td>-0.008781</td>\n",
       "      <td>0.000585</td>\n",
       "      <td>-0.000520</td>\n",
       "      <td>-0.003381</td>\n",
       "      <td>-0.000096</td>\n",
       "      <td>0.004933</td>\n",
       "      <td>-0.001777</td>\n",
       "      <td>0.000204</td>\n",
       "      <td>0.002057</td>\n",
       "      <td>-0.000291</td>\n",
       "      <td>-0.006100</td>\n",
       "      <td>0.005486</td>\n",
       "      <td>0.000856</td>\n",
       "      <td>0.005285</td>\n",
       "      <td>-0.000910</td>\n",
       "      <td>-0.007412</td>\n",
       "      <td>-0.001051</td>\n",
       "      <td>0.000210</td>\n",
       "      <td>-0.000926</td>\n",
       "      <td>-0.000028</td>\n",
       "      <td>0.000468</td>\n",
       "      <td>-0.002332</td>\n",
       "      <td>-0.002915</td>\n",
       "      <td>-0.001808</td>\n",
       "      <td>-0.003136</td>\n",
       "      <td>0.000648</td>\n",
       "      <td>0.001136</td>\n",
       "      <td>-0.003341</td>\n",
       "      <td>-0.001253</td>\n",
       "      <td>0.005500</td>\n",
       "      <td>-0.003532</td>\n",
       "      <td>-0.000047</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.004065</td>\n",
       "      <td>-0.003817</td>\n",
       "      <td>0.006483</td>\n",
       "      <td>-0.002586</td>\n",
       "      <td>-0.000813</td>\n",
       "      <td>-0.008039</td>\n",
       "      <td>-0.004399</td>\n",
       "      <td>0.000164</td>\n",
       "      <td>0.001488</td>\n",
       "      <td>0.002707</td>\n",
       "      <td>0.000867</td>\n",
       "      <td>-0.001973</td>\n",
       "      <td>0.002025</td>\n",
       "      <td>-0.000853</td>\n",
       "      <td>0.003696</td>\n",
       "      <td>-0.001473</td>\n",
       "      <td>-0.000225</td>\n",
       "      <td>0.003349</td>\n",
       "      <td>0.001429</td>\n",
       "      <td>0.003255</td>\n",
       "      <td>-0.005715</td>\n",
       "      <td>0.003484</td>\n",
       "      <td>-0.000862</td>\n",
       "      <td>-0.002179</td>\n",
       "      <td>0.001604</td>\n",
       "      <td>-0.002499</td>\n",
       "      <td>-0.002114</td>\n",
       "      <td>-0.006316</td>\n",
       "      <td>0.000491</td>\n",
       "      <td>-0.003621</td>\n",
       "      <td>0.000323</td>\n",
       "      <td>-0.000413</td>\n",
       "      <td>0.001487</td>\n",
       "      <td>0.001529</td>\n",
       "      <td>0.000567</td>\n",
       "      <td>-0.007458</td>\n",
       "      <td>0.000960</td>\n",
       "      <td>0.001414</td>\n",
       "      <td>0.002622</td>\n",
       "      <td>-0.001311</td>\n",
       "      <td>-0.001550</td>\n",
       "      <td>-0.000834</td>\n",
       "      <td>-0.003316</td>\n",
       "      <td>-0.001409</td>\n",
       "      <td>0.004381</td>\n",
       "      <td>0.001285</td>\n",
       "      <td>-0.000183</td>\n",
       "      <td>0.001479</td>\n",
       "      <td>-0.002749</td>\n",
       "      <td>-0.004522</td>\n",
       "      <td>-0.003197</td>\n",
       "      <td>-0.002027</td>\n",
       "      <td>-0.000521</td>\n",
       "      <td>-0.000284</td>\n",
       "      <td>-0.001985</td>\n",
       "      <td>-0.002740</td>\n",
       "      <td>-0.002361</td>\n",
       "      <td>0.001156</td>\n",
       "      <td>-0.000268</td>\n",
       "      <td>0.000690</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>0.003523</td>\n",
       "      <td>-0.003181</td>\n",
       "      <td>-0.003115</td>\n",
       "      <td>-0.002571</td>\n",
       "      <td>0.003337</td>\n",
       "      <td>0.000541</td>\n",
       "      <td>-0.004239</td>\n",
       "      <td>-0.000300</td>\n",
       "      <td>-0.001187</td>\n",
       "      <td>-0.004446</td>\n",
       "      <td>0.002863</td>\n",
       "      <td>-0.000953</td>\n",
       "      <td>0.002714</td>\n",
       "      <td>-0.001473</td>\n",
       "      <td>0.000342</td>\n",
       "      <td>-0.000817</td>\n",
       "      <td>0.003521</td>\n",
       "      <td>-0.004910</td>\n",
       "      <td>-0.001112</td>\n",
       "      <td>-0.000411</td>\n",
       "      <td>0.001621</td>\n",
       "      <td>0.000500</td>\n",
       "      <td>0.002201</td>\n",
       "      <td>-0.006457</td>\n",
       "      <td>0.004645</td>\n",
       "      <td>0.001603</td>\n",
       "      <td>-0.001066</td>\n",
       "      <td>-0.004928</td>\n",
       "      <td>-0.000288</td>\n",
       "      <td>0.007518</td>\n",
       "      <td>0.003553</td>\n",
       "      <td>0.002274</td>\n",
       "      <td>-0.000873</td>\n",
       "      <td>0.001896</td>\n",
       "      <td>0.002269</td>\n",
       "      <td>0.002745</td>\n",
       "      <td>0.003929</td>\n",
       "      <td>0.002371</td>\n",
       "      <td>0.000128</td>\n",
       "      <td>0.005033</td>\n",
       "      <td>-0.001226</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002494</td>\n",
       "      <td>0.000747</td>\n",
       "      <td>-0.001385</td>\n",
       "      <td>0.009638</td>\n",
       "      <td>0.003521</td>\n",
       "      <td>-0.000522</td>\n",
       "      <td>0.000561</td>\n",
       "      <td>-0.000192</td>\n",
       "      <td>0.001406</td>\n",
       "      <td>-0.001567</td>\n",
       "      <td>0.001872</td>\n",
       "      <td>-0.001337</td>\n",
       "      <td>-0.006624</td>\n",
       "      <td>0.003946</td>\n",
       "      <td>-0.002637</td>\n",
       "      <td>0.002448</td>\n",
       "      <td>0.000594</td>\n",
       "      <td>-0.000353</td>\n",
       "      <td>-0.002710</td>\n",
       "      <td>0.001619</td>\n",
       "      <td>-0.003120</td>\n",
       "      <td>0.003322</td>\n",
       "      <td>0.003156</td>\n",
       "      <td>-0.001034</td>\n",
       "      <td>0.000347</td>\n",
       "      <td>-0.000194</td>\n",
       "      <td>-0.000791</td>\n",
       "      <td>0.001370</td>\n",
       "      <td>-0.000717</td>\n",
       "      <td>-0.001479</td>\n",
       "      <td>0.002841</td>\n",
       "      <td>-0.001648</td>\n",
       "      <td>0.002490</td>\n",
       "      <td>0.000622</td>\n",
       "      <td>0.001481</td>\n",
       "      <td>-0.004538</td>\n",
       "      <td>-0.002973</td>\n",
       "      <td>-0.004161</td>\n",
       "      <td>-0.002375</td>\n",
       "      <td>-0.002207</td>\n",
       "      <td>-0.001935</td>\n",
       "      <td>-0.000621</td>\n",
       "      <td>0.006917</td>\n",
       "      <td>-0.000483</td>\n",
       "      <td>0.004052</td>\n",
       "      <td>0.000223</td>\n",
       "      <td>0.000122</td>\n",
       "      <td>-0.000655</td>\n",
       "      <td>-0.002002</td>\n",
       "      <td>-0.000417</td>\n",
       "      <td>-0.003626</td>\n",
       "      <td>-0.003995</td>\n",
       "      <td>0.000151</td>\n",
       "      <td>0.004092</td>\n",
       "      <td>-0.002145</td>\n",
       "      <td>-0.000563</td>\n",
       "      <td>-0.000019</td>\n",
       "      <td>-0.000545</td>\n",
       "      <td>-0.004100</td>\n",
       "      <td>0.001835</td>\n",
       "      <td>0.001928</td>\n",
       "      <td>-0.004750</td>\n",
       "      <td>0.001604</td>\n",
       "      <td>0.000758</td>\n",
       "      <td>-0.005482</td>\n",
       "      <td>-0.004904</td>\n",
       "      <td>-0.004869</td>\n",
       "      <td>-0.003482</td>\n",
       "      <td>-0.001946</td>\n",
       "      <td>0.001213</td>\n",
       "      <td>0.001538</td>\n",
       "      <td>0.000325</td>\n",
       "      <td>0.000696</td>\n",
       "      <td>-0.005030</td>\n",
       "      <td>-0.000800</td>\n",
       "      <td>0.002104</td>\n",
       "      <td>0.000886</td>\n",
       "      <td>-0.002643</td>\n",
       "      <td>0.002751</td>\n",
       "      <td>-0.001919</td>\n",
       "      <td>-0.005029</td>\n",
       "      <td>-0.003694</td>\n",
       "      <td>-0.001568</td>\n",
       "      <td>0.004757</td>\n",
       "      <td>0.002956</td>\n",
       "      <td>-0.000047</td>\n",
       "      <td>-0.000024</td>\n",
       "      <td>0.003003</td>\n",
       "      <td>-0.002677</td>\n",
       "      <td>0.003872</td>\n",
       "      <td>0.000547</td>\n",
       "      <td>0.002726</td>\n",
       "      <td>-0.000146</td>\n",
       "      <td>0.011734</td>\n",
       "      <td>0.000455</td>\n",
       "      <td>0.000752</td>\n",
       "      <td>-0.001889</td>\n",
       "      <td>0.003672</td>\n",
       "      <td>-0.000692</td>\n",
       "      <td>0.002164</td>\n",
       "      <td>0.002887</td>\n",
       "      <td>-0.001416</td>\n",
       "      <td>0.002405</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>0.001953</td>\n",
       "      <td>-0.002931</td>\n",
       "      <td>0.003204</td>\n",
       "      <td>-0.003072</td>\n",
       "      <td>-0.000341</td>\n",
       "      <td>0.005361</td>\n",
       "      <td>-0.001850</td>\n",
       "      <td>-0.001096</td>\n",
       "      <td>-0.000558</td>\n",
       "      <td>-0.000967</td>\n",
       "      <td>-0.003816</td>\n",
       "      <td>-0.003976</td>\n",
       "      <td>-0.000630</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.003379</td>\n",
       "      <td>-0.002186</td>\n",
       "      <td>0.001462</td>\n",
       "      <td>0.005445</td>\n",
       "      <td>-0.005174</td>\n",
       "      <td>0.003430</td>\n",
       "      <td>0.000904</td>\n",
       "      <td>0.004320</td>\n",
       "      <td>0.001745</td>\n",
       "      <td>-0.000899</td>\n",
       "      <td>-0.003137</td>\n",
       "      <td>-0.004041</td>\n",
       "      <td>-0.000435</td>\n",
       "      <td>-0.003659</td>\n",
       "      <td>0.001378</td>\n",
       "      <td>-0.001996</td>\n",
       "      <td>0.002496</td>\n",
       "      <td>-0.000900</td>\n",
       "      <td>0.001333</td>\n",
       "      <td>-0.002189</td>\n",
       "      <td>-0.002776</td>\n",
       "      <td>0.001087</td>\n",
       "      <td>0.002395</td>\n",
       "      <td>-0.000890</td>\n",
       "      <td>0.004375</td>\n",
       "      <td>-0.001467</td>\n",
       "      <td>-0.000606</td>\n",
       "      <td>0.001189</td>\n",
       "      <td>0.004796</td>\n",
       "      <td>-0.007712</td>\n",
       "      <td>-0.000275</td>\n",
       "      <td>-0.001116</td>\n",
       "      <td>-0.000139</td>\n",
       "      <td>-0.002867</td>\n",
       "      <td>0.003639</td>\n",
       "      <td>0.003427</td>\n",
       "      <td>0.001717</td>\n",
       "      <td>-0.004914</td>\n",
       "      <td>-0.002428</td>\n",
       "      <td>-0.001729</td>\n",
       "      <td>0.000485</td>\n",
       "      <td>-0.001695</td>\n",
       "      <td>-0.002192</td>\n",
       "      <td>0.000638</td>\n",
       "      <td>0.001852</td>\n",
       "      <td>0.001845</td>\n",
       "      <td>-0.000111</td>\n",
       "      <td>0.000407</td>\n",
       "      <td>-0.002436</td>\n",
       "      <td>-0.001365</td>\n",
       "      <td>0.002021</td>\n",
       "      <td>0.001851</td>\n",
       "      <td>0.002180</td>\n",
       "      <td>-0.001217</td>\n",
       "      <td>0.000679</td>\n",
       "      <td>-0.003685</td>\n",
       "      <td>-0.003890</td>\n",
       "      <td>-0.001024</td>\n",
       "      <td>0.001088</td>\n",
       "      <td>0.002543</td>\n",
       "      <td>0.005739</td>\n",
       "      <td>-0.002018</td>\n",
       "      <td>0.000495</td>\n",
       "      <td>0.000955</td>\n",
       "      <td>-0.001939</td>\n",
       "      <td>0.005252</td>\n",
       "      <td>0.001891</td>\n",
       "      <td>0.000566</td>\n",
       "      <td>-0.004282</td>\n",
       "      <td>0.007317</td>\n",
       "      <td>-0.000687</td>\n",
       "      <td>0.003051</td>\n",
       "      <td>-0.000897</td>\n",
       "      <td>-0.004686</td>\n",
       "      <td>0.000562</td>\n",
       "      <td>0.003005</td>\n",
       "      <td>0.000522</td>\n",
       "      <td>-0.000916</td>\n",
       "      <td>0.000446</td>\n",
       "      <td>0.003708</td>\n",
       "      <td>0.000044</td>\n",
       "      <td>-0.000352</td>\n",
       "      <td>0.004183</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>0.004579</td>\n",
       "      <td>-0.000387</td>\n",
       "      <td>0.001955</td>\n",
       "      <td>0.006274</td>\n",
       "      <td>-0.000868</td>\n",
       "      <td>0.003246</td>\n",
       "      <td>0.004949</td>\n",
       "      <td>0.000960</td>\n",
       "      <td>0.001794</td>\n",
       "      <td>-0.005426</td>\n",
       "      <td>0.001095</td>\n",
       "      <td>-0.002318</td>\n",
       "      <td>-0.001666</td>\n",
       "      <td>0.009929</td>\n",
       "      <td>-0.001606</td>\n",
       "      <td>0.001832</td>\n",
       "      <td>-0.002037</td>\n",
       "      <td>-0.001793</td>\n",
       "      <td>0.000806</td>\n",
       "      <td>0.000860</td>\n",
       "      <td>0.001025</td>\n",
       "      <td>-0.004991</td>\n",
       "      <td>-0.000144</td>\n",
       "      <td>0.002480</td>\n",
       "      <td>-0.003896</td>\n",
       "      <td>0.000367</td>\n",
       "      <td>0.000829</td>\n",
       "      <td>0.003670</td>\n",
       "      <td>0.003671</td>\n",
       "      <td>0.004156</td>\n",
       "      <td>-0.001881</td>\n",
       "      <td>0.000812</td>\n",
       "      <td>0.000850</td>\n",
       "      <td>0.003391</td>\n",
       "      <td>0.001766</td>\n",
       "      <td>0.001131</td>\n",
       "      <td>-0.000713</td>\n",
       "      <td>-0.004386</td>\n",
       "      <td>0.002673</td>\n",
       "      <td>-0.002020</td>\n",
       "      <td>0.002296</td>\n",
       "      <td>0.002220</td>\n",
       "      <td>0.001291</td>\n",
       "      <td>-0.001561</td>\n",
       "      <td>0.003964</td>\n",
       "      <td>-0.002158</td>\n",
       "      <td>0.002620</td>\n",
       "      <td>0.003389</td>\n",
       "      <td>0.001761</td>\n",
       "      <td>-0.000022</td>\n",
       "      <td>-0.001588</td>\n",
       "      <td>0.004331</td>\n",
       "      <td>-0.007911</td>\n",
       "      <td>0.004321</td>\n",
       "      <td>0.001742</td>\n",
       "      <td>0.004874</td>\n",
       "      <td>0.001602</td>\n",
       "      <td>-0.001650</td>\n",
       "      <td>-0.001933</td>\n",
       "      <td>-0.002093</td>\n",
       "      <td>0.001448</td>\n",
       "      <td>-0.003245</td>\n",
       "      <td>0.002422</td>\n",
       "      <td>0.002507</td>\n",
       "      <td>-0.002441</td>\n",
       "      <td>-0.004023</td>\n",
       "      <td>0.001685</td>\n",
       "      <td>0.000815</td>\n",
       "      <td>0.003674</td>\n",
       "      <td>0.002426</td>\n",
       "      <td>0.001362</td>\n",
       "      <td>-0.000356</td>\n",
       "      <td>-0.000395</td>\n",
       "      <td>-0.000506</td>\n",
       "      <td>-0.004125</td>\n",
       "      <td>-0.002061</td>\n",
       "      <td>0.000086</td>\n",
       "      <td>-0.001102</td>\n",
       "      <td>-0.003258</td>\n",
       "      <td>0.005661</td>\n",
       "      <td>0.003965</td>\n",
       "      <td>0.000133</td>\n",
       "      <td>-0.004082</td>\n",
       "      <td>-0.000135</td>\n",
       "      <td>-0.001579</td>\n",
       "      <td>0.005034</td>\n",
       "      <td>0.003602</td>\n",
       "      <td>0.000775</td>\n",
       "      <td>0.000414</td>\n",
       "      <td>-0.002283</td>\n",
       "      <td>0.000509</td>\n",
       "      <td>0.000184</td>\n",
       "      <td>-0.004333</td>\n",
       "      <td>0.002305</td>\n",
       "      <td>0.000936</td>\n",
       "      <td>0.000402</td>\n",
       "      <td>-0.000009</td>\n",
       "      <td>-0.005472</td>\n",
       "      <td>-0.000710</td>\n",
       "      <td>0.000585</td>\n",
       "      <td>-0.003682</td>\n",
       "      <td>-0.003001</td>\n",
       "      <td>-0.002656</td>\n",
       "      <td>-0.001364</td>\n",
       "      <td>0.001641</td>\n",
       "      <td>0.000397</td>\n",
       "      <td>0.000929</td>\n",
       "      <td>0.001161</td>\n",
       "      <td>-0.000427</td>\n",
       "      <td>0.000508</td>\n",
       "      <td>0.001497</td>\n",
       "      <td>0.000118</td>\n",
       "      <td>-0.002483</td>\n",
       "      <td>0.000346</td>\n",
       "      <td>-0.000778</td>\n",
       "      <td>-0.002458</td>\n",
       "      <td>-0.001003</td>\n",
       "      <td>-0.001132</td>\n",
       "      <td>-0.003157</td>\n",
       "      <td>0.003487</td>\n",
       "      <td>0.003784</td>\n",
       "      <td>0.004643</td>\n",
       "      <td>-0.005611</td>\n",
       "      <td>0.000625</td>\n",
       "      <td>-0.001392</td>\n",
       "      <td>-0.001760</td>\n",
       "      <td>0.002323</td>\n",
       "      <td>0.001822</td>\n",
       "      <td>-0.003009</td>\n",
       "      <td>-0.004915</td>\n",
       "      <td>-0.000982</td>\n",
       "      <td>-0.004607</td>\n",
       "      <td>-0.001477</td>\n",
       "      <td>0.002869</td>\n",
       "      <td>0.007182</td>\n",
       "      <td>-0.000507</td>\n",
       "      <td>-0.001543</td>\n",
       "      <td>0.004684</td>\n",
       "      <td>-0.000522</td>\n",
       "      <td>-0.002789</td>\n",
       "      <td>0.003759</td>\n",
       "      <td>-0.002150</td>\n",
       "      <td>-0.000672</td>\n",
       "      <td>0.000430</td>\n",
       "      <td>0.000777</td>\n",
       "      <td>0.002088</td>\n",
       "      <td>0.002297</td>\n",
       "      <td>0.000165</td>\n",
       "      <td>-0.004206</td>\n",
       "      <td>0.001031</td>\n",
       "      <td>-0.001919</td>\n",
       "      <td>-0.000946</td>\n",
       "      <td>0.005356</td>\n",
       "      <td>-0.002754</td>\n",
       "      <td>0.001922</td>\n",
       "      <td>-0.000066</td>\n",
       "      <td>0.002864</td>\n",
       "      <td>0.003399</td>\n",
       "      <td>-0.001069</td>\n",
       "      <td>-0.002727</td>\n",
       "      <td>-0.001410</td>\n",
       "      <td>-0.004574</td>\n",
       "      <td>-0.003438</td>\n",
       "      <td>0.001970</td>\n",
       "      <td>0.001062</td>\n",
       "      <td>-0.003287</td>\n",
       "      <td>-0.001799</td>\n",
       "      <td>-0.000047</td>\n",
       "      <td>0.000368</td>\n",
       "      <td>-0.004688</td>\n",
       "      <td>-0.002218</td>\n",
       "      <td>-0.003762</td>\n",
       "      <td>-0.005283</td>\n",
       "      <td>-0.003763</td>\n",
       "      <td>-0.003124</td>\n",
       "      <td>-0.001896</td>\n",
       "      <td>-0.001691</td>\n",
       "      <td>0.008579</td>\n",
       "      <td>0.007583</td>\n",
       "      <td>0.003213</td>\n",
       "      <td>-0.000449</td>\n",
       "      <td>0.003214</td>\n",
       "      <td>-0.000219</td>\n",
       "      <td>-0.000517</td>\n",
       "      <td>0.002234</td>\n",
       "      <td>-0.000257</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>-0.000741</td>\n",
       "      <td>-0.000982</td>\n",
       "      <td>0.000183</td>\n",
       "      <td>0.003615</td>\n",
       "      <td>-0.005491</td>\n",
       "      <td>0.000358</td>\n",
       "      <td>-0.003905</td>\n",
       "      <td>-0.000435</td>\n",
       "      <td>-0.003215</td>\n",
       "      <td>-0.003982</td>\n",
       "      <td>0.003442</td>\n",
       "      <td>0.000444</td>\n",
       "      <td>-0.002314</td>\n",
       "      <td>0.004182</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>-0.001429</td>\n",
       "      <td>-0.002954</td>\n",
       "      <td>0.001522</td>\n",
       "      <td>0.001930</td>\n",
       "      <td>0.003185</td>\n",
       "      <td>-0.003132</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>-0.000184</td>\n",
       "      <td>0.002173</td>\n",
       "      <td>0.001814</td>\n",
       "      <td>-0.006247</td>\n",
       "      <td>0.003999</td>\n",
       "      <td>-0.000282</td>\n",
       "      <td>0.000965</td>\n",
       "      <td>-0.000213</td>\n",
       "      <td>0.005772</td>\n",
       "      <td>-0.002476</td>\n",
       "      <td>-0.002544</td>\n",
       "      <td>-0.000967</td>\n",
       "      <td>0.001775</td>\n",
       "      <td>-0.001085</td>\n",
       "      <td>0.002551</td>\n",
       "      <td>-0.002846</td>\n",
       "      <td>0.000493</td>\n",
       "      <td>0.002565</td>\n",
       "      <td>-0.000049</td>\n",
       "      <td>0.003042</td>\n",
       "      <td>0.002458</td>\n",
       "      <td>0.001157</td>\n",
       "      <td>-0.003079</td>\n",
       "      <td>0.003549</td>\n",
       "      <td>-0.002870</td>\n",
       "      <td>-0.001641</td>\n",
       "      <td>0.000906</td>\n",
       "      <td>-0.002574</td>\n",
       "      <td>0.003358</td>\n",
       "      <td>0.000392</td>\n",
       "      <td>-0.006646</td>\n",
       "      <td>-0.001252</td>\n",
       "      <td>0.002143</td>\n",
       "      <td>0.003294</td>\n",
       "      <td>-0.001132</td>\n",
       "      <td>-0.000098</td>\n",
       "      <td>0.003329</td>\n",
       "      <td>0.000252</td>\n",
       "      <td>0.002045</td>\n",
       "      <td>-0.001054</td>\n",
       "      <td>-0.000043</td>\n",
       "      <td>0.000951</td>\n",
       "      <td>0.000570</td>\n",
       "      <td>0.001261</td>\n",
       "      <td>0.000425</td>\n",
       "      <td>-0.005690</td>\n",
       "      <td>-0.003137</td>\n",
       "      <td>-0.000632</td>\n",
       "      <td>0.000790</td>\n",
       "      <td>0.000191</td>\n",
       "      <td>-0.001748</td>\n",
       "      <td>0.000250</td>\n",
       "      <td>0.000128</td>\n",
       "      <td>-0.001355</td>\n",
       "      <td>0.002444</td>\n",
       "      <td>0.002274</td>\n",
       "      <td>-0.004300</td>\n",
       "      <td>0.001348</td>\n",
       "      <td>0.000502</td>\n",
       "      <td>-0.001999</td>\n",
       "      <td>0.001594</td>\n",
       "      <td>0.000865</td>\n",
       "      <td>0.004196</td>\n",
       "      <td>0.002273</td>\n",
       "      <td>-0.002218</td>\n",
       "      <td>0.000885</td>\n",
       "      <td>0.007369</td>\n",
       "      <td>-0.002596</td>\n",
       "      <td>-0.001608</td>\n",
       "      <td>0.001013</td>\n",
       "      <td>0.003873</td>\n",
       "      <td>-0.004223</td>\n",
       "      <td>-0.000815</td>\n",
       "      <td>0.007243</td>\n",
       "      <td>-0.003368</td>\n",
       "      <td>0.002374</td>\n",
       "      <td>0.000447</td>\n",
       "      <td>0.002127</td>\n",
       "      <td>-0.000243</td>\n",
       "      <td>-0.000179</td>\n",
       "      <td>-0.001908</td>\n",
       "      <td>-0.000759</td>\n",
       "      <td>0.000466</td>\n",
       "      <td>-0.001078</td>\n",
       "      <td>-0.003322</td>\n",
       "      <td>0.000893</td>\n",
       "      <td>221</td>\n",
       "      <td>-10884.868028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>31392</td>\n",
       "      <td>VPVNPEPDATSVENVAKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>8</td>\n",
       "      <td>VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>0.001554</td>\n",
       "      <td>0.003795</td>\n",
       "      <td>0.001174</td>\n",
       "      <td>-0.002076</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.000875</td>\n",
       "      <td>-0.000238</td>\n",
       "      <td>0.007113</td>\n",
       "      <td>0.001629</td>\n",
       "      <td>0.000464</td>\n",
       "      <td>0.002051</td>\n",
       "      <td>0.003605</td>\n",
       "      <td>0.000605</td>\n",
       "      <td>-0.000747</td>\n",
       "      <td>-0.001254</td>\n",
       "      <td>-0.000672</td>\n",
       "      <td>-0.000192</td>\n",
       "      <td>0.001116</td>\n",
       "      <td>0.000719</td>\n",
       "      <td>-0.000765</td>\n",
       "      <td>0.006963</td>\n",
       "      <td>-0.002990</td>\n",
       "      <td>0.000630</td>\n",
       "      <td>-0.001651</td>\n",
       "      <td>-0.000062</td>\n",
       "      <td>0.002690</td>\n",
       "      <td>-0.003319</td>\n",
       "      <td>-0.003158</td>\n",
       "      <td>-0.001309</td>\n",
       "      <td>-0.007168</td>\n",
       "      <td>-0.005191</td>\n",
       "      <td>-0.000979</td>\n",
       "      <td>0.001867</td>\n",
       "      <td>-0.001046</td>\n",
       "      <td>-0.001662</td>\n",
       "      <td>-0.001426</td>\n",
       "      <td>-0.003246</td>\n",
       "      <td>0.000179</td>\n",
       "      <td>0.006521</td>\n",
       "      <td>-0.002055</td>\n",
       "      <td>-0.000768</td>\n",
       "      <td>0.001603</td>\n",
       "      <td>-0.001208</td>\n",
       "      <td>-0.002187</td>\n",
       "      <td>-0.001787</td>\n",
       "      <td>-0.000757</td>\n",
       "      <td>0.000202</td>\n",
       "      <td>0.000316</td>\n",
       "      <td>-0.000098</td>\n",
       "      <td>-0.002026</td>\n",
       "      <td>-0.000020</td>\n",
       "      <td>0.011114</td>\n",
       "      <td>-0.002907</td>\n",
       "      <td>-0.003117</td>\n",
       "      <td>-0.005397</td>\n",
       "      <td>0.000437</td>\n",
       "      <td>-0.006327</td>\n",
       "      <td>0.000198</td>\n",
       "      <td>0.002078</td>\n",
       "      <td>-0.000832</td>\n",
       "      <td>0.001532</td>\n",
       "      <td>0.002228</td>\n",
       "      <td>-0.003896</td>\n",
       "      <td>-0.002793</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>-0.000430</td>\n",
       "      <td>0.000177</td>\n",
       "      <td>-0.003434</td>\n",
       "      <td>-0.003956</td>\n",
       "      <td>0.001073</td>\n",
       "      <td>0.000306</td>\n",
       "      <td>-0.002091</td>\n",
       "      <td>-0.000257</td>\n",
       "      <td>0.003190</td>\n",
       "      <td>0.002147</td>\n",
       "      <td>0.000233</td>\n",
       "      <td>0.004014</td>\n",
       "      <td>-0.001664</td>\n",
       "      <td>-0.007914</td>\n",
       "      <td>0.002709</td>\n",
       "      <td>-0.001607</td>\n",
       "      <td>0.000984</td>\n",
       "      <td>-0.002138</td>\n",
       "      <td>-0.000419</td>\n",
       "      <td>-0.000547</td>\n",
       "      <td>-0.000228</td>\n",
       "      <td>0.000371</td>\n",
       "      <td>0.003289</td>\n",
       "      <td>-0.004728</td>\n",
       "      <td>-0.004577</td>\n",
       "      <td>-0.001594</td>\n",
       "      <td>-0.002785</td>\n",
       "      <td>0.000521</td>\n",
       "      <td>0.000157</td>\n",
       "      <td>-0.000761</td>\n",
       "      <td>-0.002925</td>\n",
       "      <td>-0.002729</td>\n",
       "      <td>-0.002870</td>\n",
       "      <td>0.002260</td>\n",
       "      <td>-0.002608</td>\n",
       "      <td>0.002268</td>\n",
       "      <td>-0.000610</td>\n",
       "      <td>0.002469</td>\n",
       "      <td>0.001055</td>\n",
       "      <td>0.002409</td>\n",
       "      <td>0.000757</td>\n",
       "      <td>-0.001179</td>\n",
       "      <td>-0.000726</td>\n",
       "      <td>-0.000192</td>\n",
       "      <td>0.001947</td>\n",
       "      <td>-0.002876</td>\n",
       "      <td>-0.004225</td>\n",
       "      <td>0.005035</td>\n",
       "      <td>0.001253</td>\n",
       "      <td>-0.002786</td>\n",
       "      <td>0.000839</td>\n",
       "      <td>-0.000108</td>\n",
       "      <td>-0.000820</td>\n",
       "      <td>0.000550</td>\n",
       "      <td>0.004553</td>\n",
       "      <td>0.003569</td>\n",
       "      <td>0.001601</td>\n",
       "      <td>0.002888</td>\n",
       "      <td>0.001402</td>\n",
       "      <td>-0.000123</td>\n",
       "      <td>-0.000276</td>\n",
       "      <td>-0.001046</td>\n",
       "      <td>-0.001028</td>\n",
       "      <td>-0.002321</td>\n",
       "      <td>0.002351</td>\n",
       "      <td>-0.000303</td>\n",
       "      <td>0.004724</td>\n",
       "      <td>0.003057</td>\n",
       "      <td>0.005729</td>\n",
       "      <td>-0.000481</td>\n",
       "      <td>0.006912</td>\n",
       "      <td>-0.009170</td>\n",
       "      <td>0.000180</td>\n",
       "      <td>0.001107</td>\n",
       "      <td>0.004029</td>\n",
       "      <td>-0.000955</td>\n",
       "      <td>0.004163</td>\n",
       "      <td>-0.003214</td>\n",
       "      <td>-0.000769</td>\n",
       "      <td>-0.000028</td>\n",
       "      <td>0.003590</td>\n",
       "      <td>0.002487</td>\n",
       "      <td>0.001093</td>\n",
       "      <td>0.001905</td>\n",
       "      <td>0.004828</td>\n",
       "      <td>-0.003208</td>\n",
       "      <td>0.000137</td>\n",
       "      <td>0.001139</td>\n",
       "      <td>-0.004476</td>\n",
       "      <td>0.007098</td>\n",
       "      <td>0.007679</td>\n",
       "      <td>0.000384</td>\n",
       "      <td>-0.001003</td>\n",
       "      <td>0.005451</td>\n",
       "      <td>0.001259</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>-0.001340</td>\n",
       "      <td>-0.004397</td>\n",
       "      <td>-0.001096</td>\n",
       "      <td>-0.001432</td>\n",
       "      <td>-0.003001</td>\n",
       "      <td>0.001238</td>\n",
       "      <td>-0.003678</td>\n",
       "      <td>0.001909</td>\n",
       "      <td>0.002520</td>\n",
       "      <td>-0.001713</td>\n",
       "      <td>0.002993</td>\n",
       "      <td>0.005520</td>\n",
       "      <td>-0.002514</td>\n",
       "      <td>0.007303</td>\n",
       "      <td>-0.000097</td>\n",
       "      <td>0.001314</td>\n",
       "      <td>-0.004341</td>\n",
       "      <td>0.002481</td>\n",
       "      <td>-0.005829</td>\n",
       "      <td>-0.000837</td>\n",
       "      <td>-0.003805</td>\n",
       "      <td>-0.001569</td>\n",
       "      <td>0.001925</td>\n",
       "      <td>0.000775</td>\n",
       "      <td>0.005764</td>\n",
       "      <td>0.004770</td>\n",
       "      <td>-0.008731</td>\n",
       "      <td>0.005299</td>\n",
       "      <td>0.001163</td>\n",
       "      <td>-0.001003</td>\n",
       "      <td>0.005146</td>\n",
       "      <td>-0.000789</td>\n",
       "      <td>0.000106</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>-0.000705</td>\n",
       "      <td>-0.000341</td>\n",
       "      <td>-0.001598</td>\n",
       "      <td>0.000705</td>\n",
       "      <td>0.004404</td>\n",
       "      <td>-0.004549</td>\n",
       "      <td>-0.003406</td>\n",
       "      <td>-0.003281</td>\n",
       "      <td>-0.000364</td>\n",
       "      <td>0.002250</td>\n",
       "      <td>0.001073</td>\n",
       "      <td>0.006508</td>\n",
       "      <td>0.002890</td>\n",
       "      <td>0.002586</td>\n",
       "      <td>0.000848</td>\n",
       "      <td>0.000808</td>\n",
       "      <td>0.002934</td>\n",
       "      <td>0.003297</td>\n",
       "      <td>-0.001448</td>\n",
       "      <td>-0.001157</td>\n",
       "      <td>-0.003505</td>\n",
       "      <td>0.000309</td>\n",
       "      <td>-0.003576</td>\n",
       "      <td>-0.000585</td>\n",
       "      <td>0.002916</td>\n",
       "      <td>0.001352</td>\n",
       "      <td>0.004237</td>\n",
       "      <td>-0.001896</td>\n",
       "      <td>-0.002816</td>\n",
       "      <td>0.005161</td>\n",
       "      <td>-0.002018</td>\n",
       "      <td>-0.000868</td>\n",
       "      <td>0.002030</td>\n",
       "      <td>-0.004721</td>\n",
       "      <td>0.000240</td>\n",
       "      <td>-0.002177</td>\n",
       "      <td>-0.004127</td>\n",
       "      <td>-0.003459</td>\n",
       "      <td>-0.000872</td>\n",
       "      <td>-0.008947</td>\n",
       "      <td>-0.001082</td>\n",
       "      <td>-0.004031</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>0.002541</td>\n",
       "      <td>-0.001883</td>\n",
       "      <td>-0.001830</td>\n",
       "      <td>0.002173</td>\n",
       "      <td>0.001758</td>\n",
       "      <td>-0.001697</td>\n",
       "      <td>0.000698</td>\n",
       "      <td>-0.002726</td>\n",
       "      <td>0.000632</td>\n",
       "      <td>-0.002519</td>\n",
       "      <td>-0.000642</td>\n",
       "      <td>-0.000692</td>\n",
       "      <td>-0.001570</td>\n",
       "      <td>-0.004926</td>\n",
       "      <td>-0.002861</td>\n",
       "      <td>0.000273</td>\n",
       "      <td>0.001232</td>\n",
       "      <td>-0.000184</td>\n",
       "      <td>-0.001697</td>\n",
       "      <td>0.001505</td>\n",
       "      <td>0.004525</td>\n",
       "      <td>-0.005389</td>\n",
       "      <td>0.003022</td>\n",
       "      <td>-0.005925</td>\n",
       "      <td>0.003244</td>\n",
       "      <td>0.000031</td>\n",
       "      <td>0.005136</td>\n",
       "      <td>0.005386</td>\n",
       "      <td>-0.000755</td>\n",
       "      <td>0.001083</td>\n",
       "      <td>-0.002872</td>\n",
       "      <td>-0.001028</td>\n",
       "      <td>0.002323</td>\n",
       "      <td>-0.004696</td>\n",
       "      <td>-0.002553</td>\n",
       "      <td>-0.001303</td>\n",
       "      <td>0.000376</td>\n",
       "      <td>0.001295</td>\n",
       "      <td>-0.001650</td>\n",
       "      <td>-0.004442</td>\n",
       "      <td>-0.003426</td>\n",
       "      <td>0.001465</td>\n",
       "      <td>-0.001749</td>\n",
       "      <td>-0.003955</td>\n",
       "      <td>0.002847</td>\n",
       "      <td>0.002384</td>\n",
       "      <td>-0.003867</td>\n",
       "      <td>-0.001955</td>\n",
       "      <td>0.003560</td>\n",
       "      <td>0.001139</td>\n",
       "      <td>-0.005800</td>\n",
       "      <td>-0.002149</td>\n",
       "      <td>-0.004418</td>\n",
       "      <td>0.000187</td>\n",
       "      <td>-0.001101</td>\n",
       "      <td>-0.003003</td>\n",
       "      <td>0.001395</td>\n",
       "      <td>-0.000196</td>\n",
       "      <td>-0.000687</td>\n",
       "      <td>-0.005953</td>\n",
       "      <td>0.003645</td>\n",
       "      <td>-0.004994</td>\n",
       "      <td>-0.001695</td>\n",
       "      <td>-0.000765</td>\n",
       "      <td>0.001946</td>\n",
       "      <td>-0.004481</td>\n",
       "      <td>0.001759</td>\n",
       "      <td>-0.001376</td>\n",
       "      <td>0.002192</td>\n",
       "      <td>0.004857</td>\n",
       "      <td>-0.001622</td>\n",
       "      <td>0.001589</td>\n",
       "      <td>-0.002263</td>\n",
       "      <td>0.000567</td>\n",
       "      <td>-0.000549</td>\n",
       "      <td>-0.001327</td>\n",
       "      <td>0.005732</td>\n",
       "      <td>0.000796</td>\n",
       "      <td>-0.002129</td>\n",
       "      <td>-0.004202</td>\n",
       "      <td>-0.000435</td>\n",
       "      <td>0.000758</td>\n",
       "      <td>0.001282</td>\n",
       "      <td>0.001354</td>\n",
       "      <td>-0.003045</td>\n",
       "      <td>-0.003108</td>\n",
       "      <td>-0.000797</td>\n",
       "      <td>0.003943</td>\n",
       "      <td>0.001388</td>\n",
       "      <td>-0.001349</td>\n",
       "      <td>0.003555</td>\n",
       "      <td>-0.001258</td>\n",
       "      <td>0.004531</td>\n",
       "      <td>0.002402</td>\n",
       "      <td>0.002919</td>\n",
       "      <td>-0.003306</td>\n",
       "      <td>-0.001708</td>\n",
       "      <td>0.002203</td>\n",
       "      <td>0.002471</td>\n",
       "      <td>-0.002637</td>\n",
       "      <td>-0.000214</td>\n",
       "      <td>0.003513</td>\n",
       "      <td>-0.000983</td>\n",
       "      <td>-0.004609</td>\n",
       "      <td>-0.002597</td>\n",
       "      <td>0.000676</td>\n",
       "      <td>0.001903</td>\n",
       "      <td>0.001754</td>\n",
       "      <td>-0.006350</td>\n",
       "      <td>-0.000185</td>\n",
       "      <td>0.000572</td>\n",
       "      <td>0.000867</td>\n",
       "      <td>0.001571</td>\n",
       "      <td>-0.000751</td>\n",
       "      <td>0.004707</td>\n",
       "      <td>-0.004768</td>\n",
       "      <td>-0.000309</td>\n",
       "      <td>-0.003802</td>\n",
       "      <td>0.001033</td>\n",
       "      <td>0.002071</td>\n",
       "      <td>-0.003668</td>\n",
       "      <td>-0.004895</td>\n",
       "      <td>-0.006001</td>\n",
       "      <td>0.000758</td>\n",
       "      <td>0.004973</td>\n",
       "      <td>-0.007410</td>\n",
       "      <td>0.001144</td>\n",
       "      <td>0.003964</td>\n",
       "      <td>-0.000051</td>\n",
       "      <td>-0.000279</td>\n",
       "      <td>0.000758</td>\n",
       "      <td>0.001544</td>\n",
       "      <td>-0.001437</td>\n",
       "      <td>0.002331</td>\n",
       "      <td>-0.000014</td>\n",
       "      <td>0.001253</td>\n",
       "      <td>-0.000283</td>\n",
       "      <td>-0.002273</td>\n",
       "      <td>0.001916</td>\n",
       "      <td>-0.003672</td>\n",
       "      <td>-0.000143</td>\n",
       "      <td>0.001645</td>\n",
       "      <td>0.002330</td>\n",
       "      <td>-0.010662</td>\n",
       "      <td>0.001321</td>\n",
       "      <td>-0.000864</td>\n",
       "      <td>-0.002499</td>\n",
       "      <td>-0.001460</td>\n",
       "      <td>-0.000200</td>\n",
       "      <td>-0.002046</td>\n",
       "      <td>-0.002664</td>\n",
       "      <td>0.006770</td>\n",
       "      <td>-0.005767</td>\n",
       "      <td>-0.000921</td>\n",
       "      <td>-0.001066</td>\n",
       "      <td>0.002041</td>\n",
       "      <td>0.001461</td>\n",
       "      <td>0.005656</td>\n",
       "      <td>-0.001666</td>\n",
       "      <td>-0.001130</td>\n",
       "      <td>-0.003461</td>\n",
       "      <td>-0.005652</td>\n",
       "      <td>0.000897</td>\n",
       "      <td>-0.000950</td>\n",
       "      <td>0.000699</td>\n",
       "      <td>-0.002795</td>\n",
       "      <td>-0.002364</td>\n",
       "      <td>-0.001244</td>\n",
       "      <td>-0.004487</td>\n",
       "      <td>0.004600</td>\n",
       "      <td>-0.002025</td>\n",
       "      <td>-0.000370</td>\n",
       "      <td>-0.002842</td>\n",
       "      <td>-0.002636</td>\n",
       "      <td>0.003808</td>\n",
       "      <td>-0.000494</td>\n",
       "      <td>0.002871</td>\n",
       "      <td>-0.000364</td>\n",
       "      <td>0.000790</td>\n",
       "      <td>0.003250</td>\n",
       "      <td>0.002966</td>\n",
       "      <td>-0.000429</td>\n",
       "      <td>-0.003006</td>\n",
       "      <td>-0.000956</td>\n",
       "      <td>-0.000765</td>\n",
       "      <td>0.003959</td>\n",
       "      <td>-0.001882</td>\n",
       "      <td>0.002661</td>\n",
       "      <td>0.000686</td>\n",
       "      <td>-0.002113</td>\n",
       "      <td>-0.001376</td>\n",
       "      <td>0.000169</td>\n",
       "      <td>0.001094</td>\n",
       "      <td>0.004328</td>\n",
       "      <td>-0.001399</td>\n",
       "      <td>-0.000251</td>\n",
       "      <td>0.000794</td>\n",
       "      <td>0.001056</td>\n",
       "      <td>0.001543</td>\n",
       "      <td>0.000200</td>\n",
       "      <td>0.003106</td>\n",
       "      <td>0.000123</td>\n",
       "      <td>0.003024</td>\n",
       "      <td>-0.002709</td>\n",
       "      <td>-0.001892</td>\n",
       "      <td>-0.004055</td>\n",
       "      <td>-0.000025</td>\n",
       "      <td>0.003034</td>\n",
       "      <td>0.001007</td>\n",
       "      <td>-0.005975</td>\n",
       "      <td>-0.002149</td>\n",
       "      <td>0.002412</td>\n",
       "      <td>-0.003539</td>\n",
       "      <td>0.000337</td>\n",
       "      <td>0.001650</td>\n",
       "      <td>-0.001221</td>\n",
       "      <td>0.004999</td>\n",
       "      <td>-0.000844</td>\n",
       "      <td>-0.000573</td>\n",
       "      <td>0.000180</td>\n",
       "      <td>0.001845</td>\n",
       "      <td>0.009868</td>\n",
       "      <td>-0.006403</td>\n",
       "      <td>-0.000967</td>\n",
       "      <td>-0.006023</td>\n",
       "      <td>-0.001569</td>\n",
       "      <td>0.003088</td>\n",
       "      <td>-0.001335</td>\n",
       "      <td>0.001644</td>\n",
       "      <td>0.001898</td>\n",
       "      <td>-0.003921</td>\n",
       "      <td>0.002789</td>\n",
       "      <td>0.002971</td>\n",
       "      <td>-0.005832</td>\n",
       "      <td>-0.000669</td>\n",
       "      <td>0.000396</td>\n",
       "      <td>-0.001430</td>\n",
       "      <td>-0.001625</td>\n",
       "      <td>0.001568</td>\n",
       "      <td>-0.004271</td>\n",
       "      <td>0.004049</td>\n",
       "      <td>0.002908</td>\n",
       "      <td>-0.001834</td>\n",
       "      <td>-0.003282</td>\n",
       "      <td>0.002760</td>\n",
       "      <td>0.006411</td>\n",
       "      <td>0.003782</td>\n",
       "      <td>0.003147</td>\n",
       "      <td>0.002358</td>\n",
       "      <td>0.002040</td>\n",
       "      <td>0.002744</td>\n",
       "      <td>0.000921</td>\n",
       "      <td>-0.001223</td>\n",
       "      <td>0.001132</td>\n",
       "      <td>-0.001797</td>\n",
       "      <td>0.000665</td>\n",
       "      <td>-0.002556</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000433</td>\n",
       "      <td>-0.001007</td>\n",
       "      <td>-0.003479</td>\n",
       "      <td>0.005989</td>\n",
       "      <td>0.002503</td>\n",
       "      <td>0.000435</td>\n",
       "      <td>0.000992</td>\n",
       "      <td>0.002852</td>\n",
       "      <td>0.000655</td>\n",
       "      <td>-0.002492</td>\n",
       "      <td>0.000261</td>\n",
       "      <td>-0.002169</td>\n",
       "      <td>-0.000887</td>\n",
       "      <td>0.003594</td>\n",
       "      <td>-0.001009</td>\n",
       "      <td>0.001598</td>\n",
       "      <td>0.003293</td>\n",
       "      <td>0.002903</td>\n",
       "      <td>-0.000700</td>\n",
       "      <td>0.003077</td>\n",
       "      <td>-0.005147</td>\n",
       "      <td>0.001776</td>\n",
       "      <td>0.002632</td>\n",
       "      <td>-0.001892</td>\n",
       "      <td>0.001713</td>\n",
       "      <td>-0.001691</td>\n",
       "      <td>0.000848</td>\n",
       "      <td>0.000766</td>\n",
       "      <td>-0.003730</td>\n",
       "      <td>0.000932</td>\n",
       "      <td>0.001728</td>\n",
       "      <td>-0.004056</td>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.003931</td>\n",
       "      <td>-0.004466</td>\n",
       "      <td>-0.004109</td>\n",
       "      <td>-0.004257</td>\n",
       "      <td>0.001282</td>\n",
       "      <td>0.001845</td>\n",
       "      <td>-0.001606</td>\n",
       "      <td>-0.002569</td>\n",
       "      <td>-0.003462</td>\n",
       "      <td>0.004505</td>\n",
       "      <td>0.000581</td>\n",
       "      <td>0.006636</td>\n",
       "      <td>-0.000550</td>\n",
       "      <td>0.003573</td>\n",
       "      <td>-0.002108</td>\n",
       "      <td>0.002484</td>\n",
       "      <td>-0.002274</td>\n",
       "      <td>0.000615</td>\n",
       "      <td>-0.001032</td>\n",
       "      <td>0.001960</td>\n",
       "      <td>0.002325</td>\n",
       "      <td>-0.001879</td>\n",
       "      <td>-0.000156</td>\n",
       "      <td>-0.000166</td>\n",
       "      <td>0.001412</td>\n",
       "      <td>-0.006539</td>\n",
       "      <td>0.000359</td>\n",
       "      <td>-0.000113</td>\n",
       "      <td>0.000285</td>\n",
       "      <td>-0.003895</td>\n",
       "      <td>-0.001474</td>\n",
       "      <td>0.002026</td>\n",
       "      <td>-0.004296</td>\n",
       "      <td>-0.001474</td>\n",
       "      <td>-0.001252</td>\n",
       "      <td>0.003544</td>\n",
       "      <td>0.003752</td>\n",
       "      <td>0.001999</td>\n",
       "      <td>0.000215</td>\n",
       "      <td>-0.000308</td>\n",
       "      <td>-0.002747</td>\n",
       "      <td>0.000604</td>\n",
       "      <td>-0.000867</td>\n",
       "      <td>-0.000699</td>\n",
       "      <td>0.000951</td>\n",
       "      <td>0.003611</td>\n",
       "      <td>0.001004</td>\n",
       "      <td>-0.000646</td>\n",
       "      <td>-0.002978</td>\n",
       "      <td>-0.003646</td>\n",
       "      <td>0.002683</td>\n",
       "      <td>0.002488</td>\n",
       "      <td>-0.000338</td>\n",
       "      <td>0.002324</td>\n",
       "      <td>0.002267</td>\n",
       "      <td>-0.004413</td>\n",
       "      <td>0.003299</td>\n",
       "      <td>-0.002138</td>\n",
       "      <td>0.004568</td>\n",
       "      <td>0.000583</td>\n",
       "      <td>-0.010170</td>\n",
       "      <td>0.000810</td>\n",
       "      <td>0.001265</td>\n",
       "      <td>0.000947</td>\n",
       "      <td>0.006531</td>\n",
       "      <td>0.002066</td>\n",
       "      <td>-0.000972</td>\n",
       "      <td>-0.003245</td>\n",
       "      <td>-0.000239</td>\n",
       "      <td>0.001623</td>\n",
       "      <td>-0.003105</td>\n",
       "      <td>0.002114</td>\n",
       "      <td>-0.001234</td>\n",
       "      <td>-0.000855</td>\n",
       "      <td>0.003455</td>\n",
       "      <td>0.002724</td>\n",
       "      <td>0.001943</td>\n",
       "      <td>0.003262</td>\n",
       "      <td>0.000809</td>\n",
       "      <td>0.005380</td>\n",
       "      <td>-0.000384</td>\n",
       "      <td>-0.003195</td>\n",
       "      <td>-0.002797</td>\n",
       "      <td>0.001275</td>\n",
       "      <td>0.000339</td>\n",
       "      <td>0.001141</td>\n",
       "      <td>0.001686</td>\n",
       "      <td>0.003658</td>\n",
       "      <td>0.004915</td>\n",
       "      <td>-0.004764</td>\n",
       "      <td>0.001600</td>\n",
       "      <td>-0.002305</td>\n",
       "      <td>0.003290</td>\n",
       "      <td>0.002297</td>\n",
       "      <td>-0.000738</td>\n",
       "      <td>-0.002228</td>\n",
       "      <td>-0.003098</td>\n",
       "      <td>0.000897</td>\n",
       "      <td>-0.006696</td>\n",
       "      <td>0.001484</td>\n",
       "      <td>-0.000039</td>\n",
       "      <td>0.003103</td>\n",
       "      <td>-0.003043</td>\n",
       "      <td>0.000854</td>\n",
       "      <td>0.000210</td>\n",
       "      <td>-0.004403</td>\n",
       "      <td>0.003371</td>\n",
       "      <td>0.001631</td>\n",
       "      <td>0.008503</td>\n",
       "      <td>0.004136</td>\n",
       "      <td>-0.002198</td>\n",
       "      <td>0.001331</td>\n",
       "      <td>0.000127</td>\n",
       "      <td>0.005136</td>\n",
       "      <td>-0.003257</td>\n",
       "      <td>-0.001834</td>\n",
       "      <td>-0.000589</td>\n",
       "      <td>0.004771</td>\n",
       "      <td>-0.001900</td>\n",
       "      <td>0.003834</td>\n",
       "      <td>0.002597</td>\n",
       "      <td>0.003465</td>\n",
       "      <td>-0.005570</td>\n",
       "      <td>-0.002061</td>\n",
       "      <td>-0.000266</td>\n",
       "      <td>0.002084</td>\n",
       "      <td>-0.002867</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.002323</td>\n",
       "      <td>-0.000034</td>\n",
       "      <td>0.004767</td>\n",
       "      <td>-0.005834</td>\n",
       "      <td>0.001657</td>\n",
       "      <td>0.000658</td>\n",
       "      <td>0.001024</td>\n",
       "      <td>0.001304</td>\n",
       "      <td>-0.001445</td>\n",
       "      <td>-0.000115</td>\n",
       "      <td>0.001606</td>\n",
       "      <td>0.003634</td>\n",
       "      <td>-0.002547</td>\n",
       "      <td>0.000907</td>\n",
       "      <td>-0.001185</td>\n",
       "      <td>-0.004377</td>\n",
       "      <td>0.004333</td>\n",
       "      <td>0.000962</td>\n",
       "      <td>-0.002190</td>\n",
       "      <td>-0.000114</td>\n",
       "      <td>0.002327</td>\n",
       "      <td>0.002658</td>\n",
       "      <td>0.000926</td>\n",
       "      <td>0.005232</td>\n",
       "      <td>-0.000648</td>\n",
       "      <td>-0.005277</td>\n",
       "      <td>0.007134</td>\n",
       "      <td>-0.000677</td>\n",
       "      <td>0.001168</td>\n",
       "      <td>-0.005339</td>\n",
       "      <td>-0.003922</td>\n",
       "      <td>-0.001905</td>\n",
       "      <td>-0.000304</td>\n",
       "      <td>0.000742</td>\n",
       "      <td>-0.001232</td>\n",
       "      <td>-0.000536</td>\n",
       "      <td>0.006279</td>\n",
       "      <td>-0.000840</td>\n",
       "      <td>-0.000034</td>\n",
       "      <td>0.002845</td>\n",
       "      <td>0.003053</td>\n",
       "      <td>0.005551</td>\n",
       "      <td>0.001298</td>\n",
       "      <td>-0.000123</td>\n",
       "      <td>0.005662</td>\n",
       "      <td>0.000809</td>\n",
       "      <td>0.000482</td>\n",
       "      <td>0.005148</td>\n",
       "      <td>-0.000664</td>\n",
       "      <td>0.004202</td>\n",
       "      <td>-0.006927</td>\n",
       "      <td>-0.000422</td>\n",
       "      <td>0.001865</td>\n",
       "      <td>0.004531</td>\n",
       "      <td>0.008443</td>\n",
       "      <td>0.003474</td>\n",
       "      <td>0.000647</td>\n",
       "      <td>-0.001987</td>\n",
       "      <td>-0.001830</td>\n",
       "      <td>-0.001166</td>\n",
       "      <td>0.002247</td>\n",
       "      <td>0.000942</td>\n",
       "      <td>-0.002277</td>\n",
       "      <td>-0.001117</td>\n",
       "      <td>0.003283</td>\n",
       "      <td>0.001231</td>\n",
       "      <td>-0.000141</td>\n",
       "      <td>0.001368</td>\n",
       "      <td>0.005194</td>\n",
       "      <td>0.002548</td>\n",
       "      <td>0.002964</td>\n",
       "      <td>0.001227</td>\n",
       "      <td>0.001356</td>\n",
       "      <td>0.001781</td>\n",
       "      <td>0.003912</td>\n",
       "      <td>0.002740</td>\n",
       "      <td>0.001812</td>\n",
       "      <td>-0.000197</td>\n",
       "      <td>-0.001587</td>\n",
       "      <td>-0.000933</td>\n",
       "      <td>-0.000626</td>\n",
       "      <td>0.002844</td>\n",
       "      <td>0.002911</td>\n",
       "      <td>0.000564</td>\n",
       "      <td>-0.003354</td>\n",
       "      <td>0.000811</td>\n",
       "      <td>0.001608</td>\n",
       "      <td>0.003075</td>\n",
       "      <td>-0.000030</td>\n",
       "      <td>0.000915</td>\n",
       "      <td>-0.000362</td>\n",
       "      <td>-0.001756</td>\n",
       "      <td>0.007517</td>\n",
       "      <td>-0.009313</td>\n",
       "      <td>0.005702</td>\n",
       "      <td>0.001698</td>\n",
       "      <td>-0.000440</td>\n",
       "      <td>0.000160</td>\n",
       "      <td>-0.002866</td>\n",
       "      <td>-0.003232</td>\n",
       "      <td>-0.002612</td>\n",
       "      <td>0.002072</td>\n",
       "      <td>0.000222</td>\n",
       "      <td>0.001083</td>\n",
       "      <td>0.001696</td>\n",
       "      <td>-0.002966</td>\n",
       "      <td>-0.000709</td>\n",
       "      <td>-0.000048</td>\n",
       "      <td>-0.001926</td>\n",
       "      <td>0.004157</td>\n",
       "      <td>-0.000919</td>\n",
       "      <td>-0.001277</td>\n",
       "      <td>0.003237</td>\n",
       "      <td>0.001963</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>-0.005614</td>\n",
       "      <td>-0.003715</td>\n",
       "      <td>0.001582</td>\n",
       "      <td>-0.003014</td>\n",
       "      <td>-0.001688</td>\n",
       "      <td>0.002360</td>\n",
       "      <td>0.002443</td>\n",
       "      <td>0.000940</td>\n",
       "      <td>-0.001468</td>\n",
       "      <td>-0.005785</td>\n",
       "      <td>0.001494</td>\n",
       "      <td>0.001355</td>\n",
       "      <td>0.000702</td>\n",
       "      <td>-0.000106</td>\n",
       "      <td>0.003197</td>\n",
       "      <td>0.000730</td>\n",
       "      <td>0.000893</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>-0.004399</td>\n",
       "      <td>0.001022</td>\n",
       "      <td>0.000061</td>\n",
       "      <td>0.000407</td>\n",
       "      <td>0.000426</td>\n",
       "      <td>-0.002261</td>\n",
       "      <td>0.000616</td>\n",
       "      <td>0.002420</td>\n",
       "      <td>0.001075</td>\n",
       "      <td>-0.001422</td>\n",
       "      <td>0.002973</td>\n",
       "      <td>-0.003820</td>\n",
       "      <td>-0.002766</td>\n",
       "      <td>0.000611</td>\n",
       "      <td>0.001048</td>\n",
       "      <td>-0.001471</td>\n",
       "      <td>-0.000651</td>\n",
       "      <td>-0.000778</td>\n",
       "      <td>-0.001062</td>\n",
       "      <td>-0.000853</td>\n",
       "      <td>0.000886</td>\n",
       "      <td>0.000324</td>\n",
       "      <td>0.000289</td>\n",
       "      <td>0.000870</td>\n",
       "      <td>-0.001526</td>\n",
       "      <td>0.000933</td>\n",
       "      <td>-0.003803</td>\n",
       "      <td>0.005082</td>\n",
       "      <td>0.004858</td>\n",
       "      <td>0.004316</td>\n",
       "      <td>-0.004715</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>0.000076</td>\n",
       "      <td>-0.003433</td>\n",
       "      <td>0.004414</td>\n",
       "      <td>0.001262</td>\n",
       "      <td>-0.000826</td>\n",
       "      <td>-0.001564</td>\n",
       "      <td>0.003783</td>\n",
       "      <td>-0.003299</td>\n",
       "      <td>-0.001664</td>\n",
       "      <td>-0.000692</td>\n",
       "      <td>0.003720</td>\n",
       "      <td>0.000567</td>\n",
       "      <td>-0.004693</td>\n",
       "      <td>-0.000204</td>\n",
       "      <td>0.002204</td>\n",
       "      <td>-0.004405</td>\n",
       "      <td>0.001580</td>\n",
       "      <td>0.001316</td>\n",
       "      <td>-0.001586</td>\n",
       "      <td>0.000363</td>\n",
       "      <td>0.003229</td>\n",
       "      <td>0.000530</td>\n",
       "      <td>0.001888</td>\n",
       "      <td>0.000988</td>\n",
       "      <td>-0.001594</td>\n",
       "      <td>-0.001511</td>\n",
       "      <td>-0.000620</td>\n",
       "      <td>-0.003069</td>\n",
       "      <td>0.000079</td>\n",
       "      <td>0.000335</td>\n",
       "      <td>-0.000861</td>\n",
       "      <td>-0.001490</td>\n",
       "      <td>0.002620</td>\n",
       "      <td>0.001336</td>\n",
       "      <td>0.002098</td>\n",
       "      <td>-0.001556</td>\n",
       "      <td>-0.004735</td>\n",
       "      <td>-0.000642</td>\n",
       "      <td>-0.001379</td>\n",
       "      <td>0.007653</td>\n",
       "      <td>-0.000416</td>\n",
       "      <td>-0.001686</td>\n",
       "      <td>-0.003135</td>\n",
       "      <td>0.001527</td>\n",
       "      <td>0.001953</td>\n",
       "      <td>-0.000403</td>\n",
       "      <td>-0.005697</td>\n",
       "      <td>-0.003899</td>\n",
       "      <td>-0.000030</td>\n",
       "      <td>0.000595</td>\n",
       "      <td>-0.004442</td>\n",
       "      <td>0.003507</td>\n",
       "      <td>0.001786</td>\n",
       "      <td>0.001744</td>\n",
       "      <td>0.005222</td>\n",
       "      <td>0.002536</td>\n",
       "      <td>-0.004478</td>\n",
       "      <td>-0.000007</td>\n",
       "      <td>-0.004313</td>\n",
       "      <td>-0.000970</td>\n",
       "      <td>0.003568</td>\n",
       "      <td>-0.000307</td>\n",
       "      <td>-0.000105</td>\n",
       "      <td>-0.003397</td>\n",
       "      <td>0.001009</td>\n",
       "      <td>0.000454</td>\n",
       "      <td>0.005946</td>\n",
       "      <td>-0.007346</td>\n",
       "      <td>0.003109</td>\n",
       "      <td>-0.003658</td>\n",
       "      <td>0.001517</td>\n",
       "      <td>-0.003145</td>\n",
       "      <td>-0.006120</td>\n",
       "      <td>0.002802</td>\n",
       "      <td>-0.001303</td>\n",
       "      <td>-0.002125</td>\n",
       "      <td>0.003493</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>-0.005149</td>\n",
       "      <td>-0.004391</td>\n",
       "      <td>-0.007192</td>\n",
       "      <td>0.001592</td>\n",
       "      <td>-0.000869</td>\n",
       "      <td>-0.000918</td>\n",
       "      <td>-0.000899</td>\n",
       "      <td>-0.000842</td>\n",
       "      <td>0.003269</td>\n",
       "      <td>0.003082</td>\n",
       "      <td>-0.001193</td>\n",
       "      <td>-0.000758</td>\n",
       "      <td>0.001173</td>\n",
       "      <td>-0.000831</td>\n",
       "      <td>0.000899</td>\n",
       "      <td>0.001563</td>\n",
       "      <td>-0.003624</td>\n",
       "      <td>-0.000650</td>\n",
       "      <td>-0.002048</td>\n",
       "      <td>0.001292</td>\n",
       "      <td>0.002027</td>\n",
       "      <td>0.004819</td>\n",
       "      <td>-0.001560</td>\n",
       "      <td>0.001423</td>\n",
       "      <td>0.003461</td>\n",
       "      <td>0.001985</td>\n",
       "      <td>0.005454</td>\n",
       "      <td>-0.000235</td>\n",
       "      <td>-0.000876</td>\n",
       "      <td>-0.002509</td>\n",
       "      <td>0.002964</td>\n",
       "      <td>-0.004921</td>\n",
       "      <td>-0.002823</td>\n",
       "      <td>0.000685</td>\n",
       "      <td>0.000392</td>\n",
       "      <td>-0.003351</td>\n",
       "      <td>-0.000157</td>\n",
       "      <td>-0.003875</td>\n",
       "      <td>0.001611</td>\n",
       "      <td>0.000193</td>\n",
       "      <td>-0.002321</td>\n",
       "      <td>-0.003488</td>\n",
       "      <td>0.002336</td>\n",
       "      <td>0.002921</td>\n",
       "      <td>0.001887</td>\n",
       "      <td>-0.001929</td>\n",
       "      <td>0.001034</td>\n",
       "      <td>0.000725</td>\n",
       "      <td>0.001609</td>\n",
       "      <td>0.000630</td>\n",
       "      <td>0.000811</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>0.000612</td>\n",
       "      <td>-0.002673</td>\n",
       "      <td>0.001426</td>\n",
       "      <td>0.001154</td>\n",
       "      <td>-0.001617</td>\n",
       "      <td>-0.005566</td>\n",
       "      <td>0.001887</td>\n",
       "      <td>-0.002332</td>\n",
       "      <td>-0.001287</td>\n",
       "      <td>0.003442</td>\n",
       "      <td>0.005313</td>\n",
       "      <td>-0.002194</td>\n",
       "      <td>-0.002129</td>\n",
       "      <td>0.000546</td>\n",
       "      <td>-0.001055</td>\n",
       "      <td>-0.001138</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.000449</td>\n",
       "      <td>0.002954</td>\n",
       "      <td>-0.003886</td>\n",
       "      <td>-0.001415</td>\n",
       "      <td>0.003804</td>\n",
       "      <td>-0.001086</td>\n",
       "      <td>-0.004927</td>\n",
       "      <td>-0.005850</td>\n",
       "      <td>-0.002068</td>\n",
       "      <td>-0.000393</td>\n",
       "      <td>-0.003590</td>\n",
       "      <td>0.001722</td>\n",
       "      <td>-0.002203</td>\n",
       "      <td>0.000800</td>\n",
       "      <td>-0.002868</td>\n",
       "      <td>0.003846</td>\n",
       "      <td>-0.001309</td>\n",
       "      <td>0.002737</td>\n",
       "      <td>0.000492</td>\n",
       "      <td>0.001449</td>\n",
       "      <td>0.001184</td>\n",
       "      <td>0.004764</td>\n",
       "      <td>-0.005017</td>\n",
       "      <td>0.000357</td>\n",
       "      <td>220</td>\n",
       "      <td>-10317.575149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>31393</td>\n",
       "      <td>VPVNPEPDATSVENVALCTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>8</td>\n",
       "      <td>VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>0.001673</td>\n",
       "      <td>-0.007426</td>\n",
       "      <td>-0.003333</td>\n",
       "      <td>-0.004354</td>\n",
       "      <td>0.005721</td>\n",
       "      <td>-0.009422</td>\n",
       "      <td>-0.003682</td>\n",
       "      <td>0.004291</td>\n",
       "      <td>-0.001897</td>\n",
       "      <td>-0.006636</td>\n",
       "      <td>-0.002854</td>\n",
       "      <td>0.001780</td>\n",
       "      <td>-0.004251</td>\n",
       "      <td>0.003884</td>\n",
       "      <td>-0.010242</td>\n",
       "      <td>0.002416</td>\n",
       "      <td>0.010369</td>\n",
       "      <td>-0.007417</td>\n",
       "      <td>0.007271</td>\n",
       "      <td>-0.001903</td>\n",
       "      <td>-0.002313</td>\n",
       "      <td>0.008311</td>\n",
       "      <td>-0.009734</td>\n",
       "      <td>-0.000912</td>\n",
       "      <td>-0.001225</td>\n",
       "      <td>-0.003375</td>\n",
       "      <td>0.003810</td>\n",
       "      <td>0.003486</td>\n",
       "      <td>0.000332</td>\n",
       "      <td>0.003990</td>\n",
       "      <td>0.006250</td>\n",
       "      <td>-0.009031</td>\n",
       "      <td>-0.010551</td>\n",
       "      <td>0.008982</td>\n",
       "      <td>-0.002483</td>\n",
       "      <td>-0.013694</td>\n",
       "      <td>0.009374</td>\n",
       "      <td>-0.002693</td>\n",
       "      <td>-0.004071</td>\n",
       "      <td>-0.007455</td>\n",
       "      <td>-0.004270</td>\n",
       "      <td>-0.002642</td>\n",
       "      <td>0.006446</td>\n",
       "      <td>-0.002435</td>\n",
       "      <td>0.000963</td>\n",
       "      <td>0.003526</td>\n",
       "      <td>0.006891</td>\n",
       "      <td>-0.008458</td>\n",
       "      <td>-0.001821</td>\n",
       "      <td>-0.002957</td>\n",
       "      <td>0.006351</td>\n",
       "      <td>-0.005931</td>\n",
       "      <td>0.000800</td>\n",
       "      <td>-0.000811</td>\n",
       "      <td>0.009732</td>\n",
       "      <td>-0.004468</td>\n",
       "      <td>-0.002034</td>\n",
       "      <td>-0.011356</td>\n",
       "      <td>0.001027</td>\n",
       "      <td>-0.002575</td>\n",
       "      <td>0.000713</td>\n",
       "      <td>-0.002021</td>\n",
       "      <td>-0.001503</td>\n",
       "      <td>-0.005751</td>\n",
       "      <td>0.002910</td>\n",
       "      <td>-0.007079</td>\n",
       "      <td>0.001843</td>\n",
       "      <td>-0.001481</td>\n",
       "      <td>0.008085</td>\n",
       "      <td>-0.005315</td>\n",
       "      <td>-0.000860</td>\n",
       "      <td>-0.004668</td>\n",
       "      <td>0.003940</td>\n",
       "      <td>-0.003935</td>\n",
       "      <td>0.005237</td>\n",
       "      <td>0.000577</td>\n",
       "      <td>-0.000392</td>\n",
       "      <td>-0.002009</td>\n",
       "      <td>0.004976</td>\n",
       "      <td>-0.001360</td>\n",
       "      <td>-0.006399</td>\n",
       "      <td>-0.003731</td>\n",
       "      <td>0.002678</td>\n",
       "      <td>0.012482</td>\n",
       "      <td>-0.005712</td>\n",
       "      <td>-0.009157</td>\n",
       "      <td>0.010385</td>\n",
       "      <td>-0.008893</td>\n",
       "      <td>0.005757</td>\n",
       "      <td>0.005256</td>\n",
       "      <td>0.002315</td>\n",
       "      <td>0.012063</td>\n",
       "      <td>0.004146</td>\n",
       "      <td>-0.006066</td>\n",
       "      <td>-0.011616</td>\n",
       "      <td>-0.002152</td>\n",
       "      <td>0.007147</td>\n",
       "      <td>-0.001056</td>\n",
       "      <td>0.010263</td>\n",
       "      <td>0.012072</td>\n",
       "      <td>0.004924</td>\n",
       "      <td>0.000888</td>\n",
       "      <td>-0.005017</td>\n",
       "      <td>0.008709</td>\n",
       "      <td>0.013407</td>\n",
       "      <td>0.014180</td>\n",
       "      <td>0.001005</td>\n",
       "      <td>-0.001245</td>\n",
       "      <td>-0.006040</td>\n",
       "      <td>-0.009866</td>\n",
       "      <td>0.006024</td>\n",
       "      <td>-0.002855</td>\n",
       "      <td>0.000935</td>\n",
       "      <td>-0.002676</td>\n",
       "      <td>-0.004958</td>\n",
       "      <td>0.002334</td>\n",
       "      <td>0.003284</td>\n",
       "      <td>0.002368</td>\n",
       "      <td>-0.006183</td>\n",
       "      <td>-0.006321</td>\n",
       "      <td>0.005545</td>\n",
       "      <td>-0.000311</td>\n",
       "      <td>0.009847</td>\n",
       "      <td>0.000701</td>\n",
       "      <td>0.008558</td>\n",
       "      <td>-0.001030</td>\n",
       "      <td>0.007608</td>\n",
       "      <td>0.014061</td>\n",
       "      <td>0.006539</td>\n",
       "      <td>0.004115</td>\n",
       "      <td>0.009240</td>\n",
       "      <td>-0.004986</td>\n",
       "      <td>-0.006364</td>\n",
       "      <td>-0.000488</td>\n",
       "      <td>0.008148</td>\n",
       "      <td>-0.006098</td>\n",
       "      <td>-0.009313</td>\n",
       "      <td>0.012192</td>\n",
       "      <td>-0.001144</td>\n",
       "      <td>-0.005071</td>\n",
       "      <td>0.007572</td>\n",
       "      <td>-0.013070</td>\n",
       "      <td>0.001043</td>\n",
       "      <td>-0.005575</td>\n",
       "      <td>-0.003519</td>\n",
       "      <td>-0.005993</td>\n",
       "      <td>-0.008636</td>\n",
       "      <td>-0.000650</td>\n",
       "      <td>-0.006986</td>\n",
       "      <td>-0.009121</td>\n",
       "      <td>0.000755</td>\n",
       "      <td>0.013079</td>\n",
       "      <td>0.002076</td>\n",
       "      <td>-0.017425</td>\n",
       "      <td>-0.004296</td>\n",
       "      <td>-0.006133</td>\n",
       "      <td>0.004651</td>\n",
       "      <td>0.000255</td>\n",
       "      <td>0.004990</td>\n",
       "      <td>0.008767</td>\n",
       "      <td>-0.001047</td>\n",
       "      <td>-0.015396</td>\n",
       "      <td>-0.003428</td>\n",
       "      <td>-0.006049</td>\n",
       "      <td>-0.000710</td>\n",
       "      <td>-0.001615</td>\n",
       "      <td>-0.003120</td>\n",
       "      <td>-0.005523</td>\n",
       "      <td>0.014698</td>\n",
       "      <td>-0.007283</td>\n",
       "      <td>-0.003173</td>\n",
       "      <td>0.005119</td>\n",
       "      <td>0.010412</td>\n",
       "      <td>-0.001594</td>\n",
       "      <td>-0.004649</td>\n",
       "      <td>0.008439</td>\n",
       "      <td>0.002742</td>\n",
       "      <td>-0.000370</td>\n",
       "      <td>-0.008229</td>\n",
       "      <td>-0.002384</td>\n",
       "      <td>-0.005679</td>\n",
       "      <td>-0.000082</td>\n",
       "      <td>-0.002076</td>\n",
       "      <td>-0.000279</td>\n",
       "      <td>0.004088</td>\n",
       "      <td>0.000220</td>\n",
       "      <td>-0.010480</td>\n",
       "      <td>-0.010460</td>\n",
       "      <td>-0.005780</td>\n",
       "      <td>0.008082</td>\n",
       "      <td>-0.010512</td>\n",
       "      <td>0.004513</td>\n",
       "      <td>0.018501</td>\n",
       "      <td>-0.004291</td>\n",
       "      <td>0.008247</td>\n",
       "      <td>-0.005214</td>\n",
       "      <td>-0.005151</td>\n",
       "      <td>0.000537</td>\n",
       "      <td>0.008533</td>\n",
       "      <td>0.009378</td>\n",
       "      <td>0.002591</td>\n",
       "      <td>0.007559</td>\n",
       "      <td>-0.000021</td>\n",
       "      <td>0.006741</td>\n",
       "      <td>0.003786</td>\n",
       "      <td>0.017479</td>\n",
       "      <td>0.001933</td>\n",
       "      <td>-0.012492</td>\n",
       "      <td>-0.003135</td>\n",
       "      <td>0.005879</td>\n",
       "      <td>-0.009476</td>\n",
       "      <td>-0.002311</td>\n",
       "      <td>0.015933</td>\n",
       "      <td>0.003649</td>\n",
       "      <td>-0.006620</td>\n",
       "      <td>0.006657</td>\n",
       "      <td>0.007641</td>\n",
       "      <td>0.001674</td>\n",
       "      <td>0.004870</td>\n",
       "      <td>-0.001685</td>\n",
       "      <td>-0.005412</td>\n",
       "      <td>0.002810</td>\n",
       "      <td>0.001780</td>\n",
       "      <td>-0.007029</td>\n",
       "      <td>-0.000757</td>\n",
       "      <td>0.001910</td>\n",
       "      <td>0.006433</td>\n",
       "      <td>0.002402</td>\n",
       "      <td>0.005347</td>\n",
       "      <td>0.003398</td>\n",
       "      <td>0.010057</td>\n",
       "      <td>-0.004514</td>\n",
       "      <td>-0.002222</td>\n",
       "      <td>0.009211</td>\n",
       "      <td>-0.020441</td>\n",
       "      <td>0.005050</td>\n",
       "      <td>-0.003008</td>\n",
       "      <td>-0.008313</td>\n",
       "      <td>-0.001006</td>\n",
       "      <td>0.023590</td>\n",
       "      <td>0.006906</td>\n",
       "      <td>0.002240</td>\n",
       "      <td>0.009629</td>\n",
       "      <td>0.001271</td>\n",
       "      <td>-0.008618</td>\n",
       "      <td>-0.003097</td>\n",
       "      <td>-0.006483</td>\n",
       "      <td>0.005114</td>\n",
       "      <td>-0.006242</td>\n",
       "      <td>-0.001768</td>\n",
       "      <td>0.006093</td>\n",
       "      <td>0.001273</td>\n",
       "      <td>-0.017759</td>\n",
       "      <td>-0.009203</td>\n",
       "      <td>-0.000190</td>\n",
       "      <td>0.014746</td>\n",
       "      <td>-0.001711</td>\n",
       "      <td>0.007193</td>\n",
       "      <td>0.003628</td>\n",
       "      <td>0.003185</td>\n",
       "      <td>0.001933</td>\n",
       "      <td>-0.003136</td>\n",
       "      <td>0.005200</td>\n",
       "      <td>0.006725</td>\n",
       "      <td>-0.003274</td>\n",
       "      <td>0.001943</td>\n",
       "      <td>-0.003050</td>\n",
       "      <td>0.012695</td>\n",
       "      <td>0.001109</td>\n",
       "      <td>-0.001442</td>\n",
       "      <td>-0.002274</td>\n",
       "      <td>0.002177</td>\n",
       "      <td>-0.004069</td>\n",
       "      <td>-0.008495</td>\n",
       "      <td>0.004030</td>\n",
       "      <td>-0.000771</td>\n",
       "      <td>0.003308</td>\n",
       "      <td>0.006749</td>\n",
       "      <td>-0.003146</td>\n",
       "      <td>-0.003374</td>\n",
       "      <td>-0.002810</td>\n",
       "      <td>0.001246</td>\n",
       "      <td>0.003597</td>\n",
       "      <td>0.000382</td>\n",
       "      <td>0.011801</td>\n",
       "      <td>-0.007923</td>\n",
       "      <td>0.004439</td>\n",
       "      <td>-0.007229</td>\n",
       "      <td>0.000260</td>\n",
       "      <td>-0.008417</td>\n",
       "      <td>0.002179</td>\n",
       "      <td>0.004321</td>\n",
       "      <td>-0.002208</td>\n",
       "      <td>0.003642</td>\n",
       "      <td>-0.014688</td>\n",
       "      <td>0.000962</td>\n",
       "      <td>0.010715</td>\n",
       "      <td>0.001356</td>\n",
       "      <td>-0.006549</td>\n",
       "      <td>-0.013929</td>\n",
       "      <td>-0.001882</td>\n",
       "      <td>-0.004407</td>\n",
       "      <td>0.005251</td>\n",
       "      <td>-0.008241</td>\n",
       "      <td>-0.006877</td>\n",
       "      <td>-0.000031</td>\n",
       "      <td>-0.010575</td>\n",
       "      <td>0.006132</td>\n",
       "      <td>-0.003762</td>\n",
       "      <td>-0.010743</td>\n",
       "      <td>0.007790</td>\n",
       "      <td>0.014735</td>\n",
       "      <td>-0.005917</td>\n",
       "      <td>0.000351</td>\n",
       "      <td>0.015528</td>\n",
       "      <td>0.004538</td>\n",
       "      <td>0.005205</td>\n",
       "      <td>-0.003109</td>\n",
       "      <td>-0.003651</td>\n",
       "      <td>0.005203</td>\n",
       "      <td>-0.000431</td>\n",
       "      <td>-0.011314</td>\n",
       "      <td>-0.002118</td>\n",
       "      <td>-0.006106</td>\n",
       "      <td>-0.000441</td>\n",
       "      <td>-0.006619</td>\n",
       "      <td>-0.010588</td>\n",
       "      <td>-0.003119</td>\n",
       "      <td>-0.002094</td>\n",
       "      <td>0.009821</td>\n",
       "      <td>-0.000921</td>\n",
       "      <td>-0.004853</td>\n",
       "      <td>-0.004941</td>\n",
       "      <td>0.001802</td>\n",
       "      <td>0.003003</td>\n",
       "      <td>-0.003869</td>\n",
       "      <td>-0.005943</td>\n",
       "      <td>-0.006190</td>\n",
       "      <td>0.003126</td>\n",
       "      <td>-0.001738</td>\n",
       "      <td>0.008161</td>\n",
       "      <td>-0.005443</td>\n",
       "      <td>0.000175</td>\n",
       "      <td>-0.007528</td>\n",
       "      <td>0.007868</td>\n",
       "      <td>0.005668</td>\n",
       "      <td>0.011491</td>\n",
       "      <td>0.004316</td>\n",
       "      <td>0.009442</td>\n",
       "      <td>-0.007122</td>\n",
       "      <td>0.001432</td>\n",
       "      <td>-0.000035</td>\n",
       "      <td>0.003566</td>\n",
       "      <td>-0.006418</td>\n",
       "      <td>0.006594</td>\n",
       "      <td>-0.008582</td>\n",
       "      <td>0.005260</td>\n",
       "      <td>0.002441</td>\n",
       "      <td>0.002633</td>\n",
       "      <td>0.000655</td>\n",
       "      <td>-0.009667</td>\n",
       "      <td>0.005820</td>\n",
       "      <td>-0.003021</td>\n",
       "      <td>0.007652</td>\n",
       "      <td>0.010012</td>\n",
       "      <td>-0.001932</td>\n",
       "      <td>-0.002825</td>\n",
       "      <td>-0.000553</td>\n",
       "      <td>-0.002318</td>\n",
       "      <td>0.000619</td>\n",
       "      <td>-0.005500</td>\n",
       "      <td>0.001682</td>\n",
       "      <td>-0.006809</td>\n",
       "      <td>0.004185</td>\n",
       "      <td>0.003385</td>\n",
       "      <td>0.000322</td>\n",
       "      <td>-0.002018</td>\n",
       "      <td>0.004385</td>\n",
       "      <td>-0.011242</td>\n",
       "      <td>-0.008273</td>\n",
       "      <td>0.004208</td>\n",
       "      <td>0.001734</td>\n",
       "      <td>-0.004746</td>\n",
       "      <td>-0.006230</td>\n",
       "      <td>-0.002114</td>\n",
       "      <td>0.000901</td>\n",
       "      <td>-0.002506</td>\n",
       "      <td>0.003958</td>\n",
       "      <td>0.007301</td>\n",
       "      <td>0.015434</td>\n",
       "      <td>0.008088</td>\n",
       "      <td>-0.003450</td>\n",
       "      <td>0.004394</td>\n",
       "      <td>-0.003394</td>\n",
       "      <td>0.000268</td>\n",
       "      <td>-0.000212</td>\n",
       "      <td>0.001074</td>\n",
       "      <td>0.014988</td>\n",
       "      <td>-0.008361</td>\n",
       "      <td>0.010381</td>\n",
       "      <td>-0.006635</td>\n",
       "      <td>0.003316</td>\n",
       "      <td>-0.002516</td>\n",
       "      <td>-0.000403</td>\n",
       "      <td>0.002445</td>\n",
       "      <td>-0.006312</td>\n",
       "      <td>-0.008796</td>\n",
       "      <td>-0.000116</td>\n",
       "      <td>0.001852</td>\n",
       "      <td>-0.004929</td>\n",
       "      <td>0.008533</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>-0.004769</td>\n",
       "      <td>0.008146</td>\n",
       "      <td>-0.007155</td>\n",
       "      <td>-0.003321</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>-0.001060</td>\n",
       "      <td>0.001441</td>\n",
       "      <td>0.000053</td>\n",
       "      <td>-0.002304</td>\n",
       "      <td>-0.001602</td>\n",
       "      <td>-0.007708</td>\n",
       "      <td>0.003524</td>\n",
       "      <td>0.014231</td>\n",
       "      <td>0.002595</td>\n",
       "      <td>-0.004719</td>\n",
       "      <td>0.012870</td>\n",
       "      <td>-0.002978</td>\n",
       "      <td>-0.013729</td>\n",
       "      <td>0.000558</td>\n",
       "      <td>0.014707</td>\n",
       "      <td>0.007637</td>\n",
       "      <td>0.005685</td>\n",
       "      <td>0.001102</td>\n",
       "      <td>-0.000620</td>\n",
       "      <td>-0.004628</td>\n",
       "      <td>-0.001868</td>\n",
       "      <td>0.003153</td>\n",
       "      <td>-0.007812</td>\n",
       "      <td>0.004223</td>\n",
       "      <td>0.006406</td>\n",
       "      <td>0.001885</td>\n",
       "      <td>-0.007560</td>\n",
       "      <td>0.006905</td>\n",
       "      <td>-0.004586</td>\n",
       "      <td>0.008165</td>\n",
       "      <td>-0.012605</td>\n",
       "      <td>0.001803</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>-0.004281</td>\n",
       "      <td>-0.000286</td>\n",
       "      <td>0.001895</td>\n",
       "      <td>-0.006753</td>\n",
       "      <td>-0.003258</td>\n",
       "      <td>-0.003839</td>\n",
       "      <td>0.005622</td>\n",
       "      <td>-0.009538</td>\n",
       "      <td>0.004394</td>\n",
       "      <td>-0.002947</td>\n",
       "      <td>-0.006281</td>\n",
       "      <td>-0.005271</td>\n",
       "      <td>-0.011118</td>\n",
       "      <td>-0.015571</td>\n",
       "      <td>-0.010631</td>\n",
       "      <td>-0.004490</td>\n",
       "      <td>-0.009815</td>\n",
       "      <td>0.000306</td>\n",
       "      <td>0.012209</td>\n",
       "      <td>0.006021</td>\n",
       "      <td>0.006984</td>\n",
       "      <td>0.004114</td>\n",
       "      <td>-0.005553</td>\n",
       "      <td>-0.003706</td>\n",
       "      <td>-0.000458</td>\n",
       "      <td>-0.003128</td>\n",
       "      <td>0.000801</td>\n",
       "      <td>-0.002175</td>\n",
       "      <td>-0.006965</td>\n",
       "      <td>-0.002316</td>\n",
       "      <td>-0.010232</td>\n",
       "      <td>-0.002298</td>\n",
       "      <td>0.006447</td>\n",
       "      <td>-0.004175</td>\n",
       "      <td>-0.007377</td>\n",
       "      <td>-0.009964</td>\n",
       "      <td>0.004610</td>\n",
       "      <td>0.002130</td>\n",
       "      <td>-0.007100</td>\n",
       "      <td>0.011058</td>\n",
       "      <td>0.008136</td>\n",
       "      <td>0.002592</td>\n",
       "      <td>-0.010724</td>\n",
       "      <td>-0.007064</td>\n",
       "      <td>-0.004359</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002789</td>\n",
       "      <td>0.004718</td>\n",
       "      <td>-0.003479</td>\n",
       "      <td>-0.000263</td>\n",
       "      <td>0.003572</td>\n",
       "      <td>0.004727</td>\n",
       "      <td>0.000771</td>\n",
       "      <td>0.002442</td>\n",
       "      <td>0.006991</td>\n",
       "      <td>-0.005417</td>\n",
       "      <td>0.006208</td>\n",
       "      <td>0.004296</td>\n",
       "      <td>0.010111</td>\n",
       "      <td>0.002681</td>\n",
       "      <td>-0.001555</td>\n",
       "      <td>-0.009507</td>\n",
       "      <td>0.000257</td>\n",
       "      <td>-0.003381</td>\n",
       "      <td>-0.010428</td>\n",
       "      <td>-0.004871</td>\n",
       "      <td>0.004610</td>\n",
       "      <td>-0.008839</td>\n",
       "      <td>0.000388</td>\n",
       "      <td>0.006411</td>\n",
       "      <td>-0.002544</td>\n",
       "      <td>-0.001637</td>\n",
       "      <td>-0.001551</td>\n",
       "      <td>0.009239</td>\n",
       "      <td>0.001057</td>\n",
       "      <td>-0.000726</td>\n",
       "      <td>0.013650</td>\n",
       "      <td>-0.000676</td>\n",
       "      <td>0.005630</td>\n",
       "      <td>0.003068</td>\n",
       "      <td>0.009164</td>\n",
       "      <td>-0.005227</td>\n",
       "      <td>0.005770</td>\n",
       "      <td>0.000063</td>\n",
       "      <td>-0.006457</td>\n",
       "      <td>-0.001392</td>\n",
       "      <td>0.002213</td>\n",
       "      <td>-0.004814</td>\n",
       "      <td>0.014181</td>\n",
       "      <td>-0.006488</td>\n",
       "      <td>-0.008543</td>\n",
       "      <td>-0.004331</td>\n",
       "      <td>-0.000550</td>\n",
       "      <td>-0.002211</td>\n",
       "      <td>-0.004660</td>\n",
       "      <td>-0.010791</td>\n",
       "      <td>-0.006687</td>\n",
       "      <td>0.007169</td>\n",
       "      <td>0.006782</td>\n",
       "      <td>0.005833</td>\n",
       "      <td>-0.005731</td>\n",
       "      <td>-0.004347</td>\n",
       "      <td>0.000218</td>\n",
       "      <td>-0.006834</td>\n",
       "      <td>-0.000546</td>\n",
       "      <td>-0.007544</td>\n",
       "      <td>-0.006154</td>\n",
       "      <td>0.004892</td>\n",
       "      <td>-0.014094</td>\n",
       "      <td>-0.002611</td>\n",
       "      <td>-0.004265</td>\n",
       "      <td>0.007592</td>\n",
       "      <td>0.003699</td>\n",
       "      <td>0.005374</td>\n",
       "      <td>0.002248</td>\n",
       "      <td>-0.003863</td>\n",
       "      <td>0.000038</td>\n",
       "      <td>0.000098</td>\n",
       "      <td>-0.002378</td>\n",
       "      <td>0.004232</td>\n",
       "      <td>-0.011772</td>\n",
       "      <td>-0.002318</td>\n",
       "      <td>-0.002896</td>\n",
       "      <td>-0.012400</td>\n",
       "      <td>-0.012538</td>\n",
       "      <td>0.009027</td>\n",
       "      <td>0.004523</td>\n",
       "      <td>0.006960</td>\n",
       "      <td>-0.003576</td>\n",
       "      <td>0.002492</td>\n",
       "      <td>0.000723</td>\n",
       "      <td>0.002521</td>\n",
       "      <td>0.005172</td>\n",
       "      <td>0.005398</td>\n",
       "      <td>0.000399</td>\n",
       "      <td>0.003636</td>\n",
       "      <td>-0.000958</td>\n",
       "      <td>-0.004564</td>\n",
       "      <td>-0.002525</td>\n",
       "      <td>-0.006415</td>\n",
       "      <td>-0.002690</td>\n",
       "      <td>-0.007712</td>\n",
       "      <td>-0.019142</td>\n",
       "      <td>0.001955</td>\n",
       "      <td>-0.001671</td>\n",
       "      <td>0.002396</td>\n",
       "      <td>0.012967</td>\n",
       "      <td>-0.000634</td>\n",
       "      <td>-0.002383</td>\n",
       "      <td>-0.001253</td>\n",
       "      <td>-0.012169</td>\n",
       "      <td>-0.008524</td>\n",
       "      <td>-0.000142</td>\n",
       "      <td>-0.004119</td>\n",
       "      <td>-0.000909</td>\n",
       "      <td>-0.000283</td>\n",
       "      <td>0.010044</td>\n",
       "      <td>-0.002188</td>\n",
       "      <td>-0.006571</td>\n",
       "      <td>-0.002219</td>\n",
       "      <td>-0.000708</td>\n",
       "      <td>-0.003496</td>\n",
       "      <td>0.005212</td>\n",
       "      <td>-0.008632</td>\n",
       "      <td>0.012524</td>\n",
       "      <td>0.000226</td>\n",
       "      <td>-0.001055</td>\n",
       "      <td>0.003622</td>\n",
       "      <td>0.001682</td>\n",
       "      <td>-0.009452</td>\n",
       "      <td>-0.011821</td>\n",
       "      <td>-0.006998</td>\n",
       "      <td>-0.003859</td>\n",
       "      <td>-0.016605</td>\n",
       "      <td>-0.009689</td>\n",
       "      <td>-0.003057</td>\n",
       "      <td>-0.003918</td>\n",
       "      <td>0.004505</td>\n",
       "      <td>0.012329</td>\n",
       "      <td>0.005905</td>\n",
       "      <td>0.000423</td>\n",
       "      <td>0.001961</td>\n",
       "      <td>-0.009720</td>\n",
       "      <td>0.006879</td>\n",
       "      <td>-0.000380</td>\n",
       "      <td>0.003894</td>\n",
       "      <td>0.006366</td>\n",
       "      <td>0.000451</td>\n",
       "      <td>-0.002149</td>\n",
       "      <td>0.005586</td>\n",
       "      <td>0.008883</td>\n",
       "      <td>-0.005197</td>\n",
       "      <td>0.003697</td>\n",
       "      <td>-0.024970</td>\n",
       "      <td>0.001268</td>\n",
       "      <td>0.003824</td>\n",
       "      <td>0.001234</td>\n",
       "      <td>0.007010</td>\n",
       "      <td>-0.009388</td>\n",
       "      <td>0.001050</td>\n",
       "      <td>0.011935</td>\n",
       "      <td>0.005011</td>\n",
       "      <td>-0.006414</td>\n",
       "      <td>0.009406</td>\n",
       "      <td>0.006568</td>\n",
       "      <td>-0.001005</td>\n",
       "      <td>0.009956</td>\n",
       "      <td>-0.001823</td>\n",
       "      <td>-0.001707</td>\n",
       "      <td>-0.009748</td>\n",
       "      <td>0.004161</td>\n",
       "      <td>0.003833</td>\n",
       "      <td>-0.002299</td>\n",
       "      <td>-0.001462</td>\n",
       "      <td>-0.003109</td>\n",
       "      <td>-0.014126</td>\n",
       "      <td>-0.003046</td>\n",
       "      <td>-0.011102</td>\n",
       "      <td>-0.002238</td>\n",
       "      <td>0.008416</td>\n",
       "      <td>-0.007870</td>\n",
       "      <td>0.006612</td>\n",
       "      <td>-0.009689</td>\n",
       "      <td>0.005125</td>\n",
       "      <td>-0.008288</td>\n",
       "      <td>0.003471</td>\n",
       "      <td>-0.007264</td>\n",
       "      <td>-0.010433</td>\n",
       "      <td>0.003808</td>\n",
       "      <td>-0.004035</td>\n",
       "      <td>-0.000027</td>\n",
       "      <td>0.010557</td>\n",
       "      <td>0.001609</td>\n",
       "      <td>0.003614</td>\n",
       "      <td>-0.000886</td>\n",
       "      <td>-0.004510</td>\n",
       "      <td>0.005688</td>\n",
       "      <td>0.002767</td>\n",
       "      <td>-0.006711</td>\n",
       "      <td>-0.003819</td>\n",
       "      <td>-0.027639</td>\n",
       "      <td>-0.001664</td>\n",
       "      <td>0.003189</td>\n",
       "      <td>-0.013366</td>\n",
       "      <td>0.002838</td>\n",
       "      <td>0.001337</td>\n",
       "      <td>-0.007892</td>\n",
       "      <td>0.004753</td>\n",
       "      <td>-0.003217</td>\n",
       "      <td>-0.005543</td>\n",
       "      <td>-0.003545</td>\n",
       "      <td>0.001269</td>\n",
       "      <td>-0.006059</td>\n",
       "      <td>0.006750</td>\n",
       "      <td>0.009795</td>\n",
       "      <td>-0.010899</td>\n",
       "      <td>-0.010615</td>\n",
       "      <td>0.005228</td>\n",
       "      <td>0.009636</td>\n",
       "      <td>0.000486</td>\n",
       "      <td>-0.001129</td>\n",
       "      <td>-0.009402</td>\n",
       "      <td>0.008821</td>\n",
       "      <td>0.006143</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>-0.000341</td>\n",
       "      <td>-0.003522</td>\n",
       "      <td>-0.002881</td>\n",
       "      <td>0.003854</td>\n",
       "      <td>0.000789</td>\n",
       "      <td>0.005915</td>\n",
       "      <td>-0.010355</td>\n",
       "      <td>-0.004280</td>\n",
       "      <td>-0.003020</td>\n",
       "      <td>-0.001607</td>\n",
       "      <td>-0.006273</td>\n",
       "      <td>-0.004918</td>\n",
       "      <td>-0.014880</td>\n",
       "      <td>0.008853</td>\n",
       "      <td>0.003023</td>\n",
       "      <td>-0.003390</td>\n",
       "      <td>0.000519</td>\n",
       "      <td>-0.000332</td>\n",
       "      <td>0.012038</td>\n",
       "      <td>0.001560</td>\n",
       "      <td>0.002485</td>\n",
       "      <td>-0.000056</td>\n",
       "      <td>-0.000745</td>\n",
       "      <td>0.005487</td>\n",
       "      <td>-0.008767</td>\n",
       "      <td>0.001178</td>\n",
       "      <td>0.001327</td>\n",
       "      <td>-0.005863</td>\n",
       "      <td>0.006762</td>\n",
       "      <td>-0.003472</td>\n",
       "      <td>0.006037</td>\n",
       "      <td>-0.001943</td>\n",
       "      <td>0.002984</td>\n",
       "      <td>-0.006977</td>\n",
       "      <td>0.001240</td>\n",
       "      <td>-0.001522</td>\n",
       "      <td>-0.004316</td>\n",
       "      <td>0.009255</td>\n",
       "      <td>-0.000403</td>\n",
       "      <td>0.014436</td>\n",
       "      <td>0.001368</td>\n",
       "      <td>0.006142</td>\n",
       "      <td>0.001537</td>\n",
       "      <td>-0.002476</td>\n",
       "      <td>0.001323</td>\n",
       "      <td>0.000437</td>\n",
       "      <td>0.000573</td>\n",
       "      <td>0.011829</td>\n",
       "      <td>0.007153</td>\n",
       "      <td>0.000742</td>\n",
       "      <td>-0.001113</td>\n",
       "      <td>0.005721</td>\n",
       "      <td>0.006887</td>\n",
       "      <td>-0.004399</td>\n",
       "      <td>-0.006866</td>\n",
       "      <td>0.003969</td>\n",
       "      <td>0.012598</td>\n",
       "      <td>0.001537</td>\n",
       "      <td>0.007366</td>\n",
       "      <td>0.007686</td>\n",
       "      <td>-0.000895</td>\n",
       "      <td>0.003221</td>\n",
       "      <td>-0.005785</td>\n",
       "      <td>0.008888</td>\n",
       "      <td>-0.003175</td>\n",
       "      <td>0.007031</td>\n",
       "      <td>0.003802</td>\n",
       "      <td>0.008191</td>\n",
       "      <td>-0.007958</td>\n",
       "      <td>-0.003317</td>\n",
       "      <td>0.007669</td>\n",
       "      <td>0.005389</td>\n",
       "      <td>0.011699</td>\n",
       "      <td>-0.005045</td>\n",
       "      <td>-0.004139</td>\n",
       "      <td>0.002811</td>\n",
       "      <td>0.003813</td>\n",
       "      <td>0.001670</td>\n",
       "      <td>-0.008682</td>\n",
       "      <td>0.009680</td>\n",
       "      <td>0.004962</td>\n",
       "      <td>0.000851</td>\n",
       "      <td>0.010386</td>\n",
       "      <td>-0.003440</td>\n",
       "      <td>0.001460</td>\n",
       "      <td>0.002038</td>\n",
       "      <td>0.007297</td>\n",
       "      <td>0.001546</td>\n",
       "      <td>-0.012513</td>\n",
       "      <td>0.003570</td>\n",
       "      <td>-0.004566</td>\n",
       "      <td>-0.000986</td>\n",
       "      <td>-0.005267</td>\n",
       "      <td>-0.009787</td>\n",
       "      <td>-0.005350</td>\n",
       "      <td>-0.004647</td>\n",
       "      <td>0.002005</td>\n",
       "      <td>-0.009381</td>\n",
       "      <td>0.007997</td>\n",
       "      <td>0.005250</td>\n",
       "      <td>-0.014698</td>\n",
       "      <td>-0.000505</td>\n",
       "      <td>-0.017321</td>\n",
       "      <td>0.010749</td>\n",
       "      <td>0.004073</td>\n",
       "      <td>-0.004085</td>\n",
       "      <td>0.003723</td>\n",
       "      <td>0.001736</td>\n",
       "      <td>-0.007749</td>\n",
       "      <td>-0.000832</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>-0.000140</td>\n",
       "      <td>-0.008526</td>\n",
       "      <td>0.005793</td>\n",
       "      <td>0.004406</td>\n",
       "      <td>-0.007187</td>\n",
       "      <td>-0.002408</td>\n",
       "      <td>-0.006218</td>\n",
       "      <td>0.008370</td>\n",
       "      <td>0.005194</td>\n",
       "      <td>0.007689</td>\n",
       "      <td>-0.005904</td>\n",
       "      <td>0.005939</td>\n",
       "      <td>0.004482</td>\n",
       "      <td>-0.005056</td>\n",
       "      <td>0.003243</td>\n",
       "      <td>-0.009869</td>\n",
       "      <td>-0.007245</td>\n",
       "      <td>0.006185</td>\n",
       "      <td>-0.006239</td>\n",
       "      <td>-0.011484</td>\n",
       "      <td>-0.008518</td>\n",
       "      <td>-0.007950</td>\n",
       "      <td>-0.004320</td>\n",
       "      <td>-0.004224</td>\n",
       "      <td>0.003527</td>\n",
       "      <td>-0.001120</td>\n",
       "      <td>0.005529</td>\n",
       "      <td>0.001387</td>\n",
       "      <td>0.004295</td>\n",
       "      <td>0.003376</td>\n",
       "      <td>0.003163</td>\n",
       "      <td>0.012282</td>\n",
       "      <td>-0.002306</td>\n",
       "      <td>-0.002013</td>\n",
       "      <td>0.001356</td>\n",
       "      <td>-0.004786</td>\n",
       "      <td>0.011900</td>\n",
       "      <td>0.000919</td>\n",
       "      <td>0.007332</td>\n",
       "      <td>0.002184</td>\n",
       "      <td>0.002864</td>\n",
       "      <td>-0.018468</td>\n",
       "      <td>0.010034</td>\n",
       "      <td>0.000553</td>\n",
       "      <td>0.006191</td>\n",
       "      <td>-0.009226</td>\n",
       "      <td>0.008989</td>\n",
       "      <td>-0.004457</td>\n",
       "      <td>-0.000800</td>\n",
       "      <td>-0.000518</td>\n",
       "      <td>-0.001062</td>\n",
       "      <td>0.008006</td>\n",
       "      <td>-0.010530</td>\n",
       "      <td>0.003928</td>\n",
       "      <td>-0.003129</td>\n",
       "      <td>0.004882</td>\n",
       "      <td>0.000328</td>\n",
       "      <td>0.008715</td>\n",
       "      <td>0.009887</td>\n",
       "      <td>-0.001589</td>\n",
       "      <td>-0.001407</td>\n",
       "      <td>-0.004055</td>\n",
       "      <td>0.001394</td>\n",
       "      <td>-0.008486</td>\n",
       "      <td>0.004310</td>\n",
       "      <td>-0.005357</td>\n",
       "      <td>0.004375</td>\n",
       "      <td>0.002478</td>\n",
       "      <td>0.002729</td>\n",
       "      <td>0.003002</td>\n",
       "      <td>-0.011194</td>\n",
       "      <td>0.007009</td>\n",
       "      <td>0.000714</td>\n",
       "      <td>0.014408</td>\n",
       "      <td>0.006603</td>\n",
       "      <td>-0.004174</td>\n",
       "      <td>0.011914</td>\n",
       "      <td>0.009980</td>\n",
       "      <td>0.012751</td>\n",
       "      <td>-0.005883</td>\n",
       "      <td>-0.009657</td>\n",
       "      <td>-0.001705</td>\n",
       "      <td>0.007608</td>\n",
       "      <td>0.004737</td>\n",
       "      <td>-0.008167</td>\n",
       "      <td>0.009936</td>\n",
       "      <td>-0.001411</td>\n",
       "      <td>-0.014298</td>\n",
       "      <td>-0.002624</td>\n",
       "      <td>0.007873</td>\n",
       "      <td>0.005376</td>\n",
       "      <td>-0.000106</td>\n",
       "      <td>-0.006798</td>\n",
       "      <td>-0.000324</td>\n",
       "      <td>0.000126</td>\n",
       "      <td>-0.004922</td>\n",
       "      <td>0.020413</td>\n",
       "      <td>-0.000375</td>\n",
       "      <td>-0.001113</td>\n",
       "      <td>-0.016149</td>\n",
       "      <td>-0.000477</td>\n",
       "      <td>-0.000023</td>\n",
       "      <td>-0.013357</td>\n",
       "      <td>0.005865</td>\n",
       "      <td>0.000101</td>\n",
       "      <td>0.007961</td>\n",
       "      <td>-0.003085</td>\n",
       "      <td>0.009965</td>\n",
       "      <td>-0.007398</td>\n",
       "      <td>0.006291</td>\n",
       "      <td>0.003187</td>\n",
       "      <td>0.007088</td>\n",
       "      <td>-0.001882</td>\n",
       "      <td>0.008161</td>\n",
       "      <td>0.009741</td>\n",
       "      <td>-0.000460</td>\n",
       "      <td>-0.001436</td>\n",
       "      <td>-0.007137</td>\n",
       "      <td>-0.007437</td>\n",
       "      <td>0.003878</td>\n",
       "      <td>0.006034</td>\n",
       "      <td>-0.009194</td>\n",
       "      <td>0.000843</td>\n",
       "      <td>0.008307</td>\n",
       "      <td>0.005829</td>\n",
       "      <td>-0.003962</td>\n",
       "      <td>-0.003075</td>\n",
       "      <td>-0.007779</td>\n",
       "      <td>0.001405</td>\n",
       "      <td>-0.003967</td>\n",
       "      <td>0.008015</td>\n",
       "      <td>-0.001405</td>\n",
       "      <td>0.008397</td>\n",
       "      <td>0.002877</td>\n",
       "      <td>0.008065</td>\n",
       "      <td>0.001060</td>\n",
       "      <td>0.000964</td>\n",
       "      <td>0.009822</td>\n",
       "      <td>0.013424</td>\n",
       "      <td>-0.003469</td>\n",
       "      <td>0.001062</td>\n",
       "      <td>-0.005695</td>\n",
       "      <td>-0.001510</td>\n",
       "      <td>0.005355</td>\n",
       "      <td>-0.007122</td>\n",
       "      <td>-0.012169</td>\n",
       "      <td>-0.007502</td>\n",
       "      <td>0.004943</td>\n",
       "      <td>-0.003612</td>\n",
       "      <td>-0.000596</td>\n",
       "      <td>-0.005103</td>\n",
       "      <td>-0.001728</td>\n",
       "      <td>-0.004516</td>\n",
       "      <td>-0.012891</td>\n",
       "      <td>-0.002525</td>\n",
       "      <td>0.000833</td>\n",
       "      <td>-0.000366</td>\n",
       "      <td>0.003219</td>\n",
       "      <td>-0.005892</td>\n",
       "      <td>-0.003820</td>\n",
       "      <td>0.000123</td>\n",
       "      <td>0.002821</td>\n",
       "      <td>-0.005008</td>\n",
       "      <td>0.004118</td>\n",
       "      <td>-0.001402</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>-0.001173</td>\n",
       "      <td>221</td>\n",
       "      <td>-10908.172922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>31394</td>\n",
       "      <td>VPVNPEPDATSVENVALFTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>8</td>\n",
       "      <td>VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK</td>\n",
       "      <td>-0.001855</td>\n",
       "      <td>-0.006140</td>\n",
       "      <td>-0.004859</td>\n",
       "      <td>-0.000936</td>\n",
       "      <td>0.000460</td>\n",
       "      <td>-0.005054</td>\n",
       "      <td>0.003511</td>\n",
       "      <td>-0.005133</td>\n",
       "      <td>-0.004164</td>\n",
       "      <td>-0.002212</td>\n",
       "      <td>-0.002171</td>\n",
       "      <td>-0.002070</td>\n",
       "      <td>-0.001750</td>\n",
       "      <td>-0.005559</td>\n",
       "      <td>0.001148</td>\n",
       "      <td>0.004328</td>\n",
       "      <td>0.007116</td>\n",
       "      <td>-0.003240</td>\n",
       "      <td>0.009528</td>\n",
       "      <td>0.002678</td>\n",
       "      <td>-0.005606</td>\n",
       "      <td>0.004446</td>\n",
       "      <td>-0.002386</td>\n",
       "      <td>0.004925</td>\n",
       "      <td>0.006682</td>\n",
       "      <td>-0.002475</td>\n",
       "      <td>0.003435</td>\n",
       "      <td>0.006496</td>\n",
       "      <td>0.001737</td>\n",
       "      <td>0.016198</td>\n",
       "      <td>0.011326</td>\n",
       "      <td>-0.000562</td>\n",
       "      <td>-0.006750</td>\n",
       "      <td>-0.001145</td>\n",
       "      <td>-0.002046</td>\n",
       "      <td>-0.000886</td>\n",
       "      <td>0.008971</td>\n",
       "      <td>0.001017</td>\n",
       "      <td>-0.005870</td>\n",
       "      <td>-0.006281</td>\n",
       "      <td>-0.004514</td>\n",
       "      <td>-0.005496</td>\n",
       "      <td>0.005690</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>-0.003079</td>\n",
       "      <td>-0.001153</td>\n",
       "      <td>0.002925</td>\n",
       "      <td>-0.003554</td>\n",
       "      <td>0.000972</td>\n",
       "      <td>-0.000210</td>\n",
       "      <td>0.003546</td>\n",
       "      <td>-0.009387</td>\n",
       "      <td>0.004236</td>\n",
       "      <td>0.002710</td>\n",
       "      <td>0.006324</td>\n",
       "      <td>-0.005759</td>\n",
       "      <td>0.003699</td>\n",
       "      <td>-0.007567</td>\n",
       "      <td>0.001543</td>\n",
       "      <td>-0.003559</td>\n",
       "      <td>0.000202</td>\n",
       "      <td>-0.003010</td>\n",
       "      <td>0.002440</td>\n",
       "      <td>-0.001609</td>\n",
       "      <td>-0.001678</td>\n",
       "      <td>0.002916</td>\n",
       "      <td>-0.001426</td>\n",
       "      <td>0.003689</td>\n",
       "      <td>0.011065</td>\n",
       "      <td>0.002640</td>\n",
       "      <td>-0.001981</td>\n",
       "      <td>-0.004056</td>\n",
       "      <td>-0.001877</td>\n",
       "      <td>-0.008256</td>\n",
       "      <td>0.001612</td>\n",
       "      <td>0.000357</td>\n",
       "      <td>-0.001008</td>\n",
       "      <td>0.004687</td>\n",
       "      <td>0.010047</td>\n",
       "      <td>0.001832</td>\n",
       "      <td>-0.004028</td>\n",
       "      <td>0.000487</td>\n",
       "      <td>-0.000776</td>\n",
       "      <td>0.002337</td>\n",
       "      <td>-0.003395</td>\n",
       "      <td>-0.005316</td>\n",
       "      <td>0.005361</td>\n",
       "      <td>-0.004850</td>\n",
       "      <td>0.004968</td>\n",
       "      <td>0.007549</td>\n",
       "      <td>0.001049</td>\n",
       "      <td>0.003923</td>\n",
       "      <td>0.000946</td>\n",
       "      <td>-0.001707</td>\n",
       "      <td>-0.001963</td>\n",
       "      <td>-0.003033</td>\n",
       "      <td>0.004753</td>\n",
       "      <td>-0.001833</td>\n",
       "      <td>0.004170</td>\n",
       "      <td>0.004961</td>\n",
       "      <td>0.001475</td>\n",
       "      <td>-0.001672</td>\n",
       "      <td>-0.001031</td>\n",
       "      <td>0.002833</td>\n",
       "      <td>0.006131</td>\n",
       "      <td>0.007077</td>\n",
       "      <td>0.000970</td>\n",
       "      <td>0.004488</td>\n",
       "      <td>0.002911</td>\n",
       "      <td>-0.003593</td>\n",
       "      <td>0.006264</td>\n",
       "      <td>0.001957</td>\n",
       "      <td>-0.004054</td>\n",
       "      <td>-0.001472</td>\n",
       "      <td>-0.001309</td>\n",
       "      <td>-0.002096</td>\n",
       "      <td>0.006297</td>\n",
       "      <td>-0.001055</td>\n",
       "      <td>-0.007202</td>\n",
       "      <td>-0.002022</td>\n",
       "      <td>-0.003977</td>\n",
       "      <td>-0.002993</td>\n",
       "      <td>0.000866</td>\n",
       "      <td>0.000710</td>\n",
       "      <td>0.003248</td>\n",
       "      <td>-0.000821</td>\n",
       "      <td>0.004893</td>\n",
       "      <td>0.001801</td>\n",
       "      <td>0.000730</td>\n",
       "      <td>0.006553</td>\n",
       "      <td>0.001875</td>\n",
       "      <td>-0.007934</td>\n",
       "      <td>0.001897</td>\n",
       "      <td>-0.001260</td>\n",
       "      <td>0.007142</td>\n",
       "      <td>-0.007956</td>\n",
       "      <td>0.000240</td>\n",
       "      <td>0.005228</td>\n",
       "      <td>-0.001265</td>\n",
       "      <td>-0.000952</td>\n",
       "      <td>0.007961</td>\n",
       "      <td>-0.009255</td>\n",
       "      <td>0.005105</td>\n",
       "      <td>-0.004063</td>\n",
       "      <td>-0.004220</td>\n",
       "      <td>0.003465</td>\n",
       "      <td>-0.006518</td>\n",
       "      <td>0.003743</td>\n",
       "      <td>-0.004951</td>\n",
       "      <td>-0.007556</td>\n",
       "      <td>-0.003309</td>\n",
       "      <td>0.005537</td>\n",
       "      <td>-0.001746</td>\n",
       "      <td>0.002538</td>\n",
       "      <td>-0.010434</td>\n",
       "      <td>-0.007014</td>\n",
       "      <td>0.005587</td>\n",
       "      <td>-0.001107</td>\n",
       "      <td>-0.004208</td>\n",
       "      <td>0.001295</td>\n",
       "      <td>0.004583</td>\n",
       "      <td>-0.014078</td>\n",
       "      <td>-0.005283</td>\n",
       "      <td>-0.001156</td>\n",
       "      <td>0.000435</td>\n",
       "      <td>-0.001728</td>\n",
       "      <td>-0.001805</td>\n",
       "      <td>-0.000829</td>\n",
       "      <td>0.003978</td>\n",
       "      <td>-0.009634</td>\n",
       "      <td>-0.000968</td>\n",
       "      <td>-0.001138</td>\n",
       "      <td>-0.000695</td>\n",
       "      <td>0.003354</td>\n",
       "      <td>-0.007953</td>\n",
       "      <td>0.001724</td>\n",
       "      <td>0.003112</td>\n",
       "      <td>0.003967</td>\n",
       "      <td>-0.012626</td>\n",
       "      <td>0.000502</td>\n",
       "      <td>-0.000972</td>\n",
       "      <td>0.005894</td>\n",
       "      <td>0.004535</td>\n",
       "      <td>-0.006220</td>\n",
       "      <td>-0.005194</td>\n",
       "      <td>-0.001993</td>\n",
       "      <td>-0.007887</td>\n",
       "      <td>0.005381</td>\n",
       "      <td>-0.004237</td>\n",
       "      <td>0.003526</td>\n",
       "      <td>0.006868</td>\n",
       "      <td>-0.006208</td>\n",
       "      <td>0.001183</td>\n",
       "      <td>0.001384</td>\n",
       "      <td>0.000843</td>\n",
       "      <td>-0.000538</td>\n",
       "      <td>0.000202</td>\n",
       "      <td>0.000670</td>\n",
       "      <td>0.003393</td>\n",
       "      <td>0.001102</td>\n",
       "      <td>0.003865</td>\n",
       "      <td>0.003482</td>\n",
       "      <td>0.002313</td>\n",
       "      <td>-0.000524</td>\n",
       "      <td>0.001610</td>\n",
       "      <td>0.001718</td>\n",
       "      <td>-0.005350</td>\n",
       "      <td>-0.005895</td>\n",
       "      <td>0.000245</td>\n",
       "      <td>0.004085</td>\n",
       "      <td>-0.000278</td>\n",
       "      <td>-0.003854</td>\n",
       "      <td>0.005218</td>\n",
       "      <td>0.003397</td>\n",
       "      <td>0.000351</td>\n",
       "      <td>0.003043</td>\n",
       "      <td>0.000638</td>\n",
       "      <td>0.008459</td>\n",
       "      <td>0.000960</td>\n",
       "      <td>-0.006805</td>\n",
       "      <td>-0.004955</td>\n",
       "      <td>-0.002235</td>\n",
       "      <td>0.002537</td>\n",
       "      <td>0.005220</td>\n",
       "      <td>-0.004952</td>\n",
       "      <td>-0.000010</td>\n",
       "      <td>-0.000095</td>\n",
       "      <td>0.001680</td>\n",
       "      <td>0.009218</td>\n",
       "      <td>0.001509</td>\n",
       "      <td>0.000557</td>\n",
       "      <td>0.000467</td>\n",
       "      <td>0.005892</td>\n",
       "      <td>0.010072</td>\n",
       "      <td>-0.010771</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>0.000473</td>\n",
       "      <td>-0.004464</td>\n",
       "      <td>-0.004146</td>\n",
       "      <td>0.015695</td>\n",
       "      <td>0.009529</td>\n",
       "      <td>0.004614</td>\n",
       "      <td>0.000116</td>\n",
       "      <td>-0.002080</td>\n",
       "      <td>-0.007691</td>\n",
       "      <td>-0.003694</td>\n",
       "      <td>0.000585</td>\n",
       "      <td>-0.000227</td>\n",
       "      <td>-0.004657</td>\n",
       "      <td>-0.006214</td>\n",
       "      <td>0.003972</td>\n",
       "      <td>0.005916</td>\n",
       "      <td>-0.000871</td>\n",
       "      <td>-0.007495</td>\n",
       "      <td>-0.003989</td>\n",
       "      <td>0.004245</td>\n",
       "      <td>0.002578</td>\n",
       "      <td>0.001107</td>\n",
       "      <td>-0.001407</td>\n",
       "      <td>0.007706</td>\n",
       "      <td>-0.007211</td>\n",
       "      <td>0.001114</td>\n",
       "      <td>-0.005189</td>\n",
       "      <td>0.004984</td>\n",
       "      <td>-0.001748</td>\n",
       "      <td>-0.003523</td>\n",
       "      <td>-0.001577</td>\n",
       "      <td>0.000142</td>\n",
       "      <td>0.009031</td>\n",
       "      <td>-0.005275</td>\n",
       "      <td>-0.001430</td>\n",
       "      <td>0.004567</td>\n",
       "      <td>-0.000633</td>\n",
       "      <td>-0.004632</td>\n",
       "      <td>0.000414</td>\n",
       "      <td>-0.003252</td>\n",
       "      <td>-0.000523</td>\n",
       "      <td>0.009145</td>\n",
       "      <td>-0.002628</td>\n",
       "      <td>-0.008933</td>\n",
       "      <td>0.000825</td>\n",
       "      <td>0.009408</td>\n",
       "      <td>0.004169</td>\n",
       "      <td>-0.003717</td>\n",
       "      <td>0.003821</td>\n",
       "      <td>0.003737</td>\n",
       "      <td>-0.003645</td>\n",
       "      <td>-0.005211</td>\n",
       "      <td>0.005278</td>\n",
       "      <td>0.002469</td>\n",
       "      <td>0.006803</td>\n",
       "      <td>0.000478</td>\n",
       "      <td>0.003211</td>\n",
       "      <td>0.005997</td>\n",
       "      <td>-0.004050</td>\n",
       "      <td>-0.006022</td>\n",
       "      <td>0.004303</td>\n",
       "      <td>0.005620</td>\n",
       "      <td>-0.009924</td>\n",
       "      <td>-0.002434</td>\n",
       "      <td>-0.002266</td>\n",
       "      <td>-0.006177</td>\n",
       "      <td>0.002716</td>\n",
       "      <td>0.006249</td>\n",
       "      <td>-0.005892</td>\n",
       "      <td>0.005215</td>\n",
       "      <td>-0.003852</td>\n",
       "      <td>-0.000609</td>\n",
       "      <td>0.005044</td>\n",
       "      <td>-0.012586</td>\n",
       "      <td>0.001935</td>\n",
       "      <td>0.004926</td>\n",
       "      <td>-0.001774</td>\n",
       "      <td>0.001821</td>\n",
       "      <td>0.005828</td>\n",
       "      <td>0.002018</td>\n",
       "      <td>0.006045</td>\n",
       "      <td>-0.000734</td>\n",
       "      <td>0.003343</td>\n",
       "      <td>-0.004489</td>\n",
       "      <td>0.000532</td>\n",
       "      <td>-0.005981</td>\n",
       "      <td>0.003153</td>\n",
       "      <td>0.000289</td>\n",
       "      <td>0.001391</td>\n",
       "      <td>-0.004562</td>\n",
       "      <td>-0.004278</td>\n",
       "      <td>0.003065</td>\n",
       "      <td>-0.010981</td>\n",
       "      <td>0.002848</td>\n",
       "      <td>-0.002906</td>\n",
       "      <td>-0.002266</td>\n",
       "      <td>-0.008011</td>\n",
       "      <td>0.001619</td>\n",
       "      <td>0.000897</td>\n",
       "      <td>0.000320</td>\n",
       "      <td>-0.004550</td>\n",
       "      <td>-0.001730</td>\n",
       "      <td>0.000913</td>\n",
       "      <td>-0.002610</td>\n",
       "      <td>-0.002464</td>\n",
       "      <td>-0.000137</td>\n",
       "      <td>0.002739</td>\n",
       "      <td>-0.003543</td>\n",
       "      <td>-0.002181</td>\n",
       "      <td>0.001272</td>\n",
       "      <td>0.007591</td>\n",
       "      <td>0.001683</td>\n",
       "      <td>0.002744</td>\n",
       "      <td>-0.004292</td>\n",
       "      <td>0.002358</td>\n",
       "      <td>-0.004141</td>\n",
       "      <td>-0.005304</td>\n",
       "      <td>0.001516</td>\n",
       "      <td>-0.000224</td>\n",
       "      <td>0.001790</td>\n",
       "      <td>0.008032</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>-0.001383</td>\n",
       "      <td>0.000406</td>\n",
       "      <td>0.004917</td>\n",
       "      <td>-0.000847</td>\n",
       "      <td>-0.004276</td>\n",
       "      <td>0.007006</td>\n",
       "      <td>-0.003003</td>\n",
       "      <td>-0.001622</td>\n",
       "      <td>0.001375</td>\n",
       "      <td>0.004074</td>\n",
       "      <td>-0.001774</td>\n",
       "      <td>-0.003822</td>\n",
       "      <td>-0.005093</td>\n",
       "      <td>0.001612</td>\n",
       "      <td>0.001097</td>\n",
       "      <td>-0.004537</td>\n",
       "      <td>0.002555</td>\n",
       "      <td>-0.000288</td>\n",
       "      <td>-0.007979</td>\n",
       "      <td>0.005640</td>\n",
       "      <td>0.006600</td>\n",
       "      <td>-0.004001</td>\n",
       "      <td>-0.001309</td>\n",
       "      <td>0.008440</td>\n",
       "      <td>-0.000717</td>\n",
       "      <td>-0.007569</td>\n",
       "      <td>-0.002529</td>\n",
       "      <td>0.004958</td>\n",
       "      <td>0.000790</td>\n",
       "      <td>0.006025</td>\n",
       "      <td>0.007009</td>\n",
       "      <td>-0.004792</td>\n",
       "      <td>0.002331</td>\n",
       "      <td>-0.005401</td>\n",
       "      <td>0.000707</td>\n",
       "      <td>-0.007436</td>\n",
       "      <td>-0.006361</td>\n",
       "      <td>-0.004932</td>\n",
       "      <td>0.000383</td>\n",
       "      <td>-0.000114</td>\n",
       "      <td>-0.003236</td>\n",
       "      <td>0.013075</td>\n",
       "      <td>-0.002431</td>\n",
       "      <td>0.000638</td>\n",
       "      <td>-0.000726</td>\n",
       "      <td>0.000708</td>\n",
       "      <td>0.000391</td>\n",
       "      <td>-0.000539</td>\n",
       "      <td>0.000512</td>\n",
       "      <td>0.001225</td>\n",
       "      <td>0.004515</td>\n",
       "      <td>-0.007087</td>\n",
       "      <td>0.005318</td>\n",
       "      <td>-0.002076</td>\n",
       "      <td>0.003204</td>\n",
       "      <td>0.001008</td>\n",
       "      <td>-0.003370</td>\n",
       "      <td>-0.001116</td>\n",
       "      <td>0.001061</td>\n",
       "      <td>-0.006357</td>\n",
       "      <td>0.000351</td>\n",
       "      <td>0.008104</td>\n",
       "      <td>0.003967</td>\n",
       "      <td>0.003960</td>\n",
       "      <td>-0.000475</td>\n",
       "      <td>-0.002753</td>\n",
       "      <td>0.002951</td>\n",
       "      <td>-0.000413</td>\n",
       "      <td>0.000598</td>\n",
       "      <td>0.010207</td>\n",
       "      <td>-0.001567</td>\n",
       "      <td>-0.005640</td>\n",
       "      <td>-0.005142</td>\n",
       "      <td>0.002730</td>\n",
       "      <td>0.003111</td>\n",
       "      <td>0.001751</td>\n",
       "      <td>-0.001908</td>\n",
       "      <td>0.003468</td>\n",
       "      <td>-0.005181</td>\n",
       "      <td>0.001222</td>\n",
       "      <td>-0.000392</td>\n",
       "      <td>-0.009367</td>\n",
       "      <td>0.000565</td>\n",
       "      <td>0.006181</td>\n",
       "      <td>0.002171</td>\n",
       "      <td>-0.003833</td>\n",
       "      <td>-0.002744</td>\n",
       "      <td>-0.004780</td>\n",
       "      <td>-0.002748</td>\n",
       "      <td>-0.001617</td>\n",
       "      <td>0.001901</td>\n",
       "      <td>-0.001115</td>\n",
       "      <td>-0.000330</td>\n",
       "      <td>0.000460</td>\n",
       "      <td>-0.002645</td>\n",
       "      <td>-0.007317</td>\n",
       "      <td>0.002992</td>\n",
       "      <td>0.002923</td>\n",
       "      <td>0.000848</td>\n",
       "      <td>-0.005538</td>\n",
       "      <td>-0.003953</td>\n",
       "      <td>-0.008905</td>\n",
       "      <td>0.000331</td>\n",
       "      <td>-0.000291</td>\n",
       "      <td>-0.000121</td>\n",
       "      <td>-0.008729</td>\n",
       "      <td>-0.005692</td>\n",
       "      <td>0.001733</td>\n",
       "      <td>-0.006690</td>\n",
       "      <td>-0.000877</td>\n",
       "      <td>0.008125</td>\n",
       "      <td>0.005272</td>\n",
       "      <td>-0.003766</td>\n",
       "      <td>0.001985</td>\n",
       "      <td>-0.001519</td>\n",
       "      <td>0.000517</td>\n",
       "      <td>0.000013</td>\n",
       "      <td>0.000965</td>\n",
       "      <td>0.004496</td>\n",
       "      <td>0.001580</td>\n",
       "      <td>-0.007750</td>\n",
       "      <td>-0.005869</td>\n",
       "      <td>-0.007786</td>\n",
       "      <td>0.001544</td>\n",
       "      <td>-0.000680</td>\n",
       "      <td>-0.003887</td>\n",
       "      <td>-0.007272</td>\n",
       "      <td>-0.009140</td>\n",
       "      <td>-0.000963</td>\n",
       "      <td>-0.002012</td>\n",
       "      <td>-0.010825</td>\n",
       "      <td>0.004503</td>\n",
       "      <td>0.002203</td>\n",
       "      <td>-0.001153</td>\n",
       "      <td>-0.004419</td>\n",
       "      <td>-0.002674</td>\n",
       "      <td>-0.003784</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002440</td>\n",
       "      <td>0.003578</td>\n",
       "      <td>0.000496</td>\n",
       "      <td>-0.005749</td>\n",
       "      <td>-0.001555</td>\n",
       "      <td>0.000727</td>\n",
       "      <td>0.004111</td>\n",
       "      <td>-0.002372</td>\n",
       "      <td>-0.001511</td>\n",
       "      <td>0.001224</td>\n",
       "      <td>0.003049</td>\n",
       "      <td>0.001377</td>\n",
       "      <td>0.000223</td>\n",
       "      <td>-0.004406</td>\n",
       "      <td>0.003568</td>\n",
       "      <td>-0.004115</td>\n",
       "      <td>-0.002926</td>\n",
       "      <td>-0.005698</td>\n",
       "      <td>0.001095</td>\n",
       "      <td>-0.003753</td>\n",
       "      <td>0.000078</td>\n",
       "      <td>-0.007364</td>\n",
       "      <td>-0.001632</td>\n",
       "      <td>-0.003815</td>\n",
       "      <td>-0.000898</td>\n",
       "      <td>0.004058</td>\n",
       "      <td>-0.000930</td>\n",
       "      <td>0.002614</td>\n",
       "      <td>0.001044</td>\n",
       "      <td>0.001816</td>\n",
       "      <td>0.006050</td>\n",
       "      <td>0.001786</td>\n",
       "      <td>0.000512</td>\n",
       "      <td>-0.004546</td>\n",
       "      <td>0.005492</td>\n",
       "      <td>0.000930</td>\n",
       "      <td>0.004144</td>\n",
       "      <td>-0.002696</td>\n",
       "      <td>-0.002503</td>\n",
       "      <td>0.005134</td>\n",
       "      <td>0.002485</td>\n",
       "      <td>0.000257</td>\n",
       "      <td>0.004762</td>\n",
       "      <td>-0.000612</td>\n",
       "      <td>-0.004920</td>\n",
       "      <td>-0.000470</td>\n",
       "      <td>-0.004702</td>\n",
       "      <td>-0.003881</td>\n",
       "      <td>0.002894</td>\n",
       "      <td>0.000904</td>\n",
       "      <td>0.001864</td>\n",
       "      <td>0.006960</td>\n",
       "      <td>0.001752</td>\n",
       "      <td>-0.001262</td>\n",
       "      <td>-0.001182</td>\n",
       "      <td>-0.008065</td>\n",
       "      <td>-0.000019</td>\n",
       "      <td>-0.001122</td>\n",
       "      <td>0.003914</td>\n",
       "      <td>-0.005908</td>\n",
       "      <td>-0.000939</td>\n",
       "      <td>0.005159</td>\n",
       "      <td>0.001858</td>\n",
       "      <td>0.000722</td>\n",
       "      <td>-0.005833</td>\n",
       "      <td>0.001347</td>\n",
       "      <td>0.001139</td>\n",
       "      <td>0.001493</td>\n",
       "      <td>0.006612</td>\n",
       "      <td>-0.002556</td>\n",
       "      <td>-0.003409</td>\n",
       "      <td>0.001042</td>\n",
       "      <td>-0.004241</td>\n",
       "      <td>0.001463</td>\n",
       "      <td>-0.003543</td>\n",
       "      <td>-0.001175</td>\n",
       "      <td>-0.000636</td>\n",
       "      <td>-0.006529</td>\n",
       "      <td>-0.006263</td>\n",
       "      <td>0.006715</td>\n",
       "      <td>0.005717</td>\n",
       "      <td>0.006899</td>\n",
       "      <td>0.000988</td>\n",
       "      <td>-0.005719</td>\n",
       "      <td>-0.004945</td>\n",
       "      <td>0.001491</td>\n",
       "      <td>0.000852</td>\n",
       "      <td>-0.003704</td>\n",
       "      <td>0.006189</td>\n",
       "      <td>0.004543</td>\n",
       "      <td>-0.000086</td>\n",
       "      <td>-0.001014</td>\n",
       "      <td>-0.001267</td>\n",
       "      <td>-0.004788</td>\n",
       "      <td>0.000200</td>\n",
       "      <td>0.002416</td>\n",
       "      <td>-0.003725</td>\n",
       "      <td>-0.004215</td>\n",
       "      <td>0.000523</td>\n",
       "      <td>0.001659</td>\n",
       "      <td>0.003605</td>\n",
       "      <td>0.002989</td>\n",
       "      <td>-0.000029</td>\n",
       "      <td>0.002694</td>\n",
       "      <td>-0.007722</td>\n",
       "      <td>-0.002443</td>\n",
       "      <td>0.003299</td>\n",
       "      <td>-0.004109</td>\n",
       "      <td>0.000633</td>\n",
       "      <td>-0.003849</td>\n",
       "      <td>0.005786</td>\n",
       "      <td>-0.002362</td>\n",
       "      <td>-0.006972</td>\n",
       "      <td>-0.002625</td>\n",
       "      <td>0.007393</td>\n",
       "      <td>0.009215</td>\n",
       "      <td>-0.001103</td>\n",
       "      <td>-0.005710</td>\n",
       "      <td>0.003802</td>\n",
       "      <td>-0.001138</td>\n",
       "      <td>-0.005780</td>\n",
       "      <td>-0.004400</td>\n",
       "      <td>-0.003323</td>\n",
       "      <td>-0.002462</td>\n",
       "      <td>-0.001829</td>\n",
       "      <td>-0.006636</td>\n",
       "      <td>-0.004310</td>\n",
       "      <td>-0.009812</td>\n",
       "      <td>-0.003027</td>\n",
       "      <td>0.000720</td>\n",
       "      <td>-0.006053</td>\n",
       "      <td>0.004773</td>\n",
       "      <td>0.004995</td>\n",
       "      <td>0.002276</td>\n",
       "      <td>-0.002932</td>\n",
       "      <td>0.004482</td>\n",
       "      <td>-0.002625</td>\n",
       "      <td>0.001419</td>\n",
       "      <td>0.000633</td>\n",
       "      <td>-0.000740</td>\n",
       "      <td>0.000977</td>\n",
       "      <td>-0.003378</td>\n",
       "      <td>-0.007951</td>\n",
       "      <td>0.007089</td>\n",
       "      <td>0.001211</td>\n",
       "      <td>0.003707</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>-0.006759</td>\n",
       "      <td>-0.001843</td>\n",
       "      <td>0.005588</td>\n",
       "      <td>0.000461</td>\n",
       "      <td>0.009947</td>\n",
       "      <td>-0.000429</td>\n",
       "      <td>-0.003201</td>\n",
       "      <td>0.002961</td>\n",
       "      <td>0.003578</td>\n",
       "      <td>0.004429</td>\n",
       "      <td>0.007892</td>\n",
       "      <td>0.004225</td>\n",
       "      <td>0.002567</td>\n",
       "      <td>0.000637</td>\n",
       "      <td>0.000865</td>\n",
       "      <td>-0.000494</td>\n",
       "      <td>-0.005048</td>\n",
       "      <td>0.003975</td>\n",
       "      <td>-0.003921</td>\n",
       "      <td>0.000092</td>\n",
       "      <td>-0.001471</td>\n",
       "      <td>-0.004624</td>\n",
       "      <td>0.003038</td>\n",
       "      <td>-0.002907</td>\n",
       "      <td>-0.003765</td>\n",
       "      <td>0.000646</td>\n",
       "      <td>0.006916</td>\n",
       "      <td>-0.003745</td>\n",
       "      <td>0.007293</td>\n",
       "      <td>0.005219</td>\n",
       "      <td>-0.000962</td>\n",
       "      <td>-0.000175</td>\n",
       "      <td>0.004902</td>\n",
       "      <td>0.002143</td>\n",
       "      <td>-0.003517</td>\n",
       "      <td>-0.000975</td>\n",
       "      <td>-0.004573</td>\n",
       "      <td>-0.008031</td>\n",
       "      <td>0.002911</td>\n",
       "      <td>0.001631</td>\n",
       "      <td>-0.007392</td>\n",
       "      <td>-0.001785</td>\n",
       "      <td>-0.002386</td>\n",
       "      <td>0.005854</td>\n",
       "      <td>0.001024</td>\n",
       "      <td>-0.001811</td>\n",
       "      <td>0.001193</td>\n",
       "      <td>-0.012547</td>\n",
       "      <td>-0.003798</td>\n",
       "      <td>-0.002171</td>\n",
       "      <td>-0.005774</td>\n",
       "      <td>-0.000603</td>\n",
       "      <td>0.001878</td>\n",
       "      <td>-0.005006</td>\n",
       "      <td>-0.000121</td>\n",
       "      <td>-0.003011</td>\n",
       "      <td>-0.004765</td>\n",
       "      <td>-0.002176</td>\n",
       "      <td>-0.007227</td>\n",
       "      <td>-0.001165</td>\n",
       "      <td>0.002824</td>\n",
       "      <td>-0.003718</td>\n",
       "      <td>-0.003393</td>\n",
       "      <td>-0.003780</td>\n",
       "      <td>0.007759</td>\n",
       "      <td>0.005468</td>\n",
       "      <td>-0.003689</td>\n",
       "      <td>-0.002886</td>\n",
       "      <td>-0.012854</td>\n",
       "      <td>0.001604</td>\n",
       "      <td>0.009180</td>\n",
       "      <td>0.004220</td>\n",
       "      <td>0.002954</td>\n",
       "      <td>-0.001210</td>\n",
       "      <td>-0.003428</td>\n",
       "      <td>-0.002271</td>\n",
       "      <td>0.001851</td>\n",
       "      <td>0.003840</td>\n",
       "      <td>-0.007585</td>\n",
       "      <td>-0.001564</td>\n",
       "      <td>0.000789</td>\n",
       "      <td>0.000328</td>\n",
       "      <td>-0.005998</td>\n",
       "      <td>-0.004830</td>\n",
       "      <td>-0.009269</td>\n",
       "      <td>0.003636</td>\n",
       "      <td>-0.002792</td>\n",
       "      <td>-0.001797</td>\n",
       "      <td>-0.001252</td>\n",
       "      <td>-0.004151</td>\n",
       "      <td>0.002248</td>\n",
       "      <td>0.003810</td>\n",
       "      <td>0.002370</td>\n",
       "      <td>0.001541</td>\n",
       "      <td>0.003043</td>\n",
       "      <td>-0.004578</td>\n",
       "      <td>-0.005639</td>\n",
       "      <td>0.002382</td>\n",
       "      <td>0.003181</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.000735</td>\n",
       "      <td>-0.000612</td>\n",
       "      <td>0.002972</td>\n",
       "      <td>-0.000486</td>\n",
       "      <td>0.000183</td>\n",
       "      <td>-0.002488</td>\n",
       "      <td>-0.006943</td>\n",
       "      <td>0.006430</td>\n",
       "      <td>-0.008495</td>\n",
       "      <td>0.001057</td>\n",
       "      <td>0.003234</td>\n",
       "      <td>0.004276</td>\n",
       "      <td>0.005450</td>\n",
       "      <td>0.001425</td>\n",
       "      <td>0.001308</td>\n",
       "      <td>-0.002968</td>\n",
       "      <td>0.005625</td>\n",
       "      <td>-0.001577</td>\n",
       "      <td>-0.006387</td>\n",
       "      <td>0.007392</td>\n",
       "      <td>0.002295</td>\n",
       "      <td>-0.003306</td>\n",
       "      <td>0.002022</td>\n",
       "      <td>-0.004258</td>\n",
       "      <td>0.007435</td>\n",
       "      <td>-0.001989</td>\n",
       "      <td>-0.007882</td>\n",
       "      <td>0.002799</td>\n",
       "      <td>0.004047</td>\n",
       "      <td>0.001144</td>\n",
       "      <td>0.003983</td>\n",
       "      <td>0.002129</td>\n",
       "      <td>0.003350</td>\n",
       "      <td>0.002134</td>\n",
       "      <td>-0.005590</td>\n",
       "      <td>0.000710</td>\n",
       "      <td>-0.007778</td>\n",
       "      <td>-0.001891</td>\n",
       "      <td>0.003862</td>\n",
       "      <td>0.003214</td>\n",
       "      <td>-0.005978</td>\n",
       "      <td>0.000474</td>\n",
       "      <td>0.005371</td>\n",
       "      <td>0.002037</td>\n",
       "      <td>0.006995</td>\n",
       "      <td>-0.005063</td>\n",
       "      <td>0.002264</td>\n",
       "      <td>0.005753</td>\n",
       "      <td>-0.002165</td>\n",
       "      <td>-0.006393</td>\n",
       "      <td>-0.003897</td>\n",
       "      <td>0.005493</td>\n",
       "      <td>0.005321</td>\n",
       "      <td>-0.002703</td>\n",
       "      <td>-0.002980</td>\n",
       "      <td>-0.002505</td>\n",
       "      <td>0.002743</td>\n",
       "      <td>-0.005221</td>\n",
       "      <td>0.005093</td>\n",
       "      <td>0.002640</td>\n",
       "      <td>-0.003089</td>\n",
       "      <td>0.005345</td>\n",
       "      <td>0.000383</td>\n",
       "      <td>-0.001643</td>\n",
       "      <td>-0.001629</td>\n",
       "      <td>-0.003849</td>\n",
       "      <td>0.000733</td>\n",
       "      <td>0.000826</td>\n",
       "      <td>-0.004458</td>\n",
       "      <td>-0.003010</td>\n",
       "      <td>0.003331</td>\n",
       "      <td>0.003342</td>\n",
       "      <td>-0.006916</td>\n",
       "      <td>0.000815</td>\n",
       "      <td>-0.013179</td>\n",
       "      <td>0.001554</td>\n",
       "      <td>-0.003302</td>\n",
       "      <td>0.003517</td>\n",
       "      <td>0.002687</td>\n",
       "      <td>-0.001022</td>\n",
       "      <td>0.010075</td>\n",
       "      <td>-0.002407</td>\n",
       "      <td>-0.002101</td>\n",
       "      <td>0.003718</td>\n",
       "      <td>-0.007985</td>\n",
       "      <td>-0.003279</td>\n",
       "      <td>0.003045</td>\n",
       "      <td>-0.005396</td>\n",
       "      <td>0.003376</td>\n",
       "      <td>-0.004243</td>\n",
       "      <td>-0.000980</td>\n",
       "      <td>0.012561</td>\n",
       "      <td>0.001858</td>\n",
       "      <td>-0.002216</td>\n",
       "      <td>0.002927</td>\n",
       "      <td>0.000277</td>\n",
       "      <td>-0.006694</td>\n",
       "      <td>-0.001347</td>\n",
       "      <td>-0.006589</td>\n",
       "      <td>0.000164</td>\n",
       "      <td>0.001895</td>\n",
       "      <td>-0.005986</td>\n",
       "      <td>-0.007113</td>\n",
       "      <td>0.000191</td>\n",
       "      <td>0.004452</td>\n",
       "      <td>-0.003357</td>\n",
       "      <td>0.001659</td>\n",
       "      <td>0.000060</td>\n",
       "      <td>0.000911</td>\n",
       "      <td>0.001960</td>\n",
       "      <td>-0.003563</td>\n",
       "      <td>0.001039</td>\n",
       "      <td>0.001211</td>\n",
       "      <td>0.001736</td>\n",
       "      <td>-0.000745</td>\n",
       "      <td>0.003839</td>\n",
       "      <td>-0.007487</td>\n",
       "      <td>0.001948</td>\n",
       "      <td>-0.009391</td>\n",
       "      <td>0.003020</td>\n",
       "      <td>0.000959</td>\n",
       "      <td>0.008670</td>\n",
       "      <td>-0.001196</td>\n",
       "      <td>0.003210</td>\n",
       "      <td>-0.001581</td>\n",
       "      <td>0.006536</td>\n",
       "      <td>0.004418</td>\n",
       "      <td>0.005121</td>\n",
       "      <td>-0.009717</td>\n",
       "      <td>0.004144</td>\n",
       "      <td>-0.008547</td>\n",
       "      <td>0.000554</td>\n",
       "      <td>0.001406</td>\n",
       "      <td>-0.006212</td>\n",
       "      <td>0.003426</td>\n",
       "      <td>-0.003931</td>\n",
       "      <td>0.002286</td>\n",
       "      <td>0.002905</td>\n",
       "      <td>0.001368</td>\n",
       "      <td>-0.002835</td>\n",
       "      <td>0.006987</td>\n",
       "      <td>0.003766</td>\n",
       "      <td>-0.001711</td>\n",
       "      <td>-0.002004</td>\n",
       "      <td>-0.006303</td>\n",
       "      <td>-0.007697</td>\n",
       "      <td>-0.000948</td>\n",
       "      <td>-0.004791</td>\n",
       "      <td>-0.004272</td>\n",
       "      <td>-0.001037</td>\n",
       "      <td>-0.000489</td>\n",
       "      <td>0.005916</td>\n",
       "      <td>-0.001943</td>\n",
       "      <td>-0.004365</td>\n",
       "      <td>0.006818</td>\n",
       "      <td>-0.003776</td>\n",
       "      <td>0.001974</td>\n",
       "      <td>0.011620</td>\n",
       "      <td>-0.000924</td>\n",
       "      <td>0.003449</td>\n",
       "      <td>0.007249</td>\n",
       "      <td>0.003084</td>\n",
       "      <td>-0.003317</td>\n",
       "      <td>-0.003446</td>\n",
       "      <td>-0.003963</td>\n",
       "      <td>-0.003640</td>\n",
       "      <td>-0.001127</td>\n",
       "      <td>-0.001690</td>\n",
       "      <td>0.002598</td>\n",
       "      <td>-0.001005</td>\n",
       "      <td>-0.005238</td>\n",
       "      <td>-0.000333</td>\n",
       "      <td>-0.000551</td>\n",
       "      <td>-0.001576</td>\n",
       "      <td>-0.001935</td>\n",
       "      <td>0.003699</td>\n",
       "      <td>-0.001511</td>\n",
       "      <td>-0.001963</td>\n",
       "      <td>-0.008522</td>\n",
       "      <td>0.011874</td>\n",
       "      <td>0.004201</td>\n",
       "      <td>-0.000671</td>\n",
       "      <td>-0.004653</td>\n",
       "      <td>-0.006324</td>\n",
       "      <td>0.000169</td>\n",
       "      <td>-0.008368</td>\n",
       "      <td>0.002840</td>\n",
       "      <td>0.000280</td>\n",
       "      <td>0.003849</td>\n",
       "      <td>-0.001673</td>\n",
       "      <td>-0.002002</td>\n",
       "      <td>-0.002434</td>\n",
       "      <td>0.002833</td>\n",
       "      <td>0.002729</td>\n",
       "      <td>0.004236</td>\n",
       "      <td>-0.004682</td>\n",
       "      <td>0.004260</td>\n",
       "      <td>0.003642</td>\n",
       "      <td>0.008232</td>\n",
       "      <td>-0.005737</td>\n",
       "      <td>-0.000487</td>\n",
       "      <td>-0.005699</td>\n",
       "      <td>0.004266</td>\n",
       "      <td>0.003859</td>\n",
       "      <td>-0.006486</td>\n",
       "      <td>-0.001472</td>\n",
       "      <td>-0.002495</td>\n",
       "      <td>0.004884</td>\n",
       "      <td>-0.001086</td>\n",
       "      <td>-0.000399</td>\n",
       "      <td>-0.002601</td>\n",
       "      <td>-0.004319</td>\n",
       "      <td>-0.001082</td>\n",
       "      <td>0.002546</td>\n",
       "      <td>0.005598</td>\n",
       "      <td>0.005924</td>\n",
       "      <td>-0.002384</td>\n",
       "      <td>0.006545</td>\n",
       "      <td>-0.002430</td>\n",
       "      <td>-0.006307</td>\n",
       "      <td>0.002711</td>\n",
       "      <td>0.005242</td>\n",
       "      <td>-0.005628</td>\n",
       "      <td>0.000864</td>\n",
       "      <td>0.001913</td>\n",
       "      <td>-0.007391</td>\n",
       "      <td>0.005219</td>\n",
       "      <td>0.003791</td>\n",
       "      <td>0.001190</td>\n",
       "      <td>-0.004289</td>\n",
       "      <td>-0.002755</td>\n",
       "      <td>-0.007370</td>\n",
       "      <td>0.000787</td>\n",
       "      <td>0.001424</td>\n",
       "      <td>-0.004954</td>\n",
       "      <td>0.000784</td>\n",
       "      <td>-0.003405</td>\n",
       "      <td>0.001943</td>\n",
       "      <td>0.004562</td>\n",
       "      <td>-0.000358</td>\n",
       "      <td>0.001799</td>\n",
       "      <td>-0.007718</td>\n",
       "      <td>-0.001927</td>\n",
       "      <td>-0.004853</td>\n",
       "      <td>0.001723</td>\n",
       "      <td>-0.003374</td>\n",
       "      <td>0.000668</td>\n",
       "      <td>-0.009545</td>\n",
       "      <td>0.003395</td>\n",
       "      <td>-0.007194</td>\n",
       "      <td>221</td>\n",
       "      <td>-10903.710743</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 1286 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   seq_id  \\\n",
       "0   31390   \n",
       "1   31391   \n",
       "2   31392   \n",
       "3   31393   \n",
       "4   31394   \n",
       "\n",
       "                                                                                                                                                                                                                         mut_seq  \\\n",
       "0  VPVNPEPDATSVENVAEKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "1  VPVNPEPDATSVENVAKKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "2   VPVNPEPDATSVENVAKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "3  VPVNPEPDATSVENVALCTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "4  VPVNPEPDATSVENVALFTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "\n",
       "   pH2  \\\n",
       "0    8   \n",
       "1    8   \n",
       "2    8   \n",
       "3    8   \n",
       "4    8   \n",
       "\n",
       "                                                                                                                                                                                                                          wt_seq  \\\n",
       "0  VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "1  VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "2  VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "3  VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "4  VPVNPEPDATSVENVALKTGSGDSQSDPIKADLEVKGQSALPFDVDCWAILCKGAPNVLQRVNEKTKNSNRDRSGANKGPFKDPQKWGIKALPPKNPSWSAQDFKSPEEYAFASSLQGGTNAILAPVNLASQNSQGGVLNGFYSANKVAQFDPSKPQQTKGTWFQITKFTGAAGPYCKALGSNDKSVCDKNKNIAGDWGFDPAKWAYQYDEKNNKFNYVGK   \n",
       "\n",
       "          0         1         2         3         4         5         6  \\\n",
       "0 -0.000880  0.005861 -0.001142  0.001560 -0.001140  0.003098 -0.000677   \n",
       "1 -0.000514  0.002023  0.006529 -0.004647  0.002037 -0.000266 -0.000165   \n",
       "2  0.001554  0.003795  0.001174 -0.002076  0.000028  0.000875 -0.000238   \n",
       "3  0.001673 -0.007426 -0.003333 -0.004354  0.005721 -0.009422 -0.003682   \n",
       "4 -0.001855 -0.006140 -0.004859 -0.000936  0.000460 -0.005054  0.003511   \n",
       "\n",
       "          7         8         9        10        11        12        13  \\\n",
       "0  0.009220  0.006545  0.005213  0.001721  0.001665  0.002427  0.001326   \n",
       "1  0.006555  0.002120 -0.001398  0.000498 -0.000698  0.000558  0.000592   \n",
       "2  0.007113  0.001629  0.000464  0.002051  0.003605  0.000605 -0.000747   \n",
       "3  0.004291 -0.001897 -0.006636 -0.002854  0.001780 -0.004251  0.003884   \n",
       "4 -0.005133 -0.004164 -0.002212 -0.002171 -0.002070 -0.001750 -0.005559   \n",
       "\n",
       "         14        15        16        17        18        19        20  \\\n",
       "0  0.000078 -0.000716 -0.005735 -0.003838 -0.002226  0.000062  0.007706   \n",
       "1 -0.001641 -0.001401  0.005935  0.002921  0.002210  0.001295  0.004519   \n",
       "2 -0.001254 -0.000672 -0.000192  0.001116  0.000719 -0.000765  0.006963   \n",
       "3 -0.010242  0.002416  0.010369 -0.007417  0.007271 -0.001903 -0.002313   \n",
       "4  0.001148  0.004328  0.007116 -0.003240  0.009528  0.002678 -0.005606   \n",
       "\n",
       "         21        22        23        24        25        26        27  \\\n",
       "0  0.001523  0.000442 -0.004630  0.004695  0.006622  0.000703 -0.004250   \n",
       "1 -0.005045 -0.000317  0.002797 -0.003759 -0.001041 -0.010086  0.001043   \n",
       "2 -0.002990  0.000630 -0.001651 -0.000062  0.002690 -0.003319 -0.003158   \n",
       "3  0.008311 -0.009734 -0.000912 -0.001225 -0.003375  0.003810  0.003486   \n",
       "4  0.004446 -0.002386  0.004925  0.006682 -0.002475  0.003435  0.006496   \n",
       "\n",
       "         28        29        30        31        32        33        34  \\\n",
       "0 -0.000168 -0.008219 -0.011683  0.006361  0.006471 -0.007541 -0.003363   \n",
       "1 -0.000399 -0.002663 -0.001998 -0.004853  0.005246 -0.001988  0.000656   \n",
       "2 -0.001309 -0.007168 -0.005191 -0.000979  0.001867 -0.001046 -0.001662   \n",
       "3  0.000332  0.003990  0.006250 -0.009031 -0.010551  0.008982 -0.002483   \n",
       "4  0.001737  0.016198  0.011326 -0.000562 -0.006750 -0.001145 -0.002046   \n",
       "\n",
       "         35        36        37        38        39        40        41  \\\n",
       "0 -0.004653 -0.004417 -0.001235  0.008840  0.000694  0.000850  0.006141   \n",
       "1 -0.002520 -0.002869 -0.001722  0.005738  0.003100  0.001821 -0.003688   \n",
       "2 -0.001426 -0.003246  0.000179  0.006521 -0.002055 -0.000768  0.001603   \n",
       "3 -0.013694  0.009374 -0.002693 -0.004071 -0.007455 -0.004270 -0.002642   \n",
       "4 -0.000886  0.008971  0.001017 -0.005870 -0.006281 -0.004514 -0.005496   \n",
       "\n",
       "         42        43        44        45        46        47        48  \\\n",
       "0 -0.003925 -0.001583 -0.009671 -0.001748 -0.003297  0.000377  0.004377   \n",
       "1 -0.002210  0.000293  0.000813 -0.000995  0.003731  0.001136 -0.001639   \n",
       "2 -0.001208 -0.002187 -0.001787 -0.000757  0.000202  0.000316 -0.000098   \n",
       "3  0.006446 -0.002435  0.000963  0.003526  0.006891 -0.008458 -0.001821   \n",
       "4  0.005690  0.000021 -0.003079 -0.001153  0.002925 -0.003554  0.000972   \n",
       "\n",
       "         49        50        51        52        53        54        55  \\\n",
       "0 -0.004123 -0.005825  0.014136 -0.003595 -0.003714 -0.006888  0.002039   \n",
       "1  0.001343  0.004689  0.004922 -0.003203 -0.002617 -0.002726 -0.000338   \n",
       "2 -0.002026 -0.000020  0.011114 -0.002907 -0.003117 -0.005397  0.000437   \n",
       "3 -0.002957  0.006351 -0.005931  0.000800 -0.000811  0.009732 -0.004468   \n",
       "4 -0.000210  0.003546 -0.009387  0.004236  0.002710  0.006324 -0.005759   \n",
       "\n",
       "         56        57        58        59        60        61        62  \\\n",
       "0 -0.005702 -0.003207  0.004504 -0.000632  0.005922 -0.000584 -0.007453   \n",
       "1 -0.003506  0.004604 -0.000120 -0.002236  0.000848  0.004217 -0.001167   \n",
       "2 -0.006327  0.000198  0.002078 -0.000832  0.001532  0.002228 -0.003896   \n",
       "3 -0.002034 -0.011356  0.001027 -0.002575  0.000713 -0.002021 -0.001503   \n",
       "4  0.003699 -0.007567  0.001543 -0.003559  0.000202 -0.003010  0.002440   \n",
       "\n",
       "         63        64        65        66        67        68        69  \\\n",
       "0 -0.000234 -0.003078  0.000713  0.000698 -0.005901 -0.004494  0.001243   \n",
       "1  0.001142  0.001542 -0.002504  0.002913 -0.003450 -0.001690 -0.001140   \n",
       "2 -0.002793  0.000907 -0.000430  0.000177 -0.003434 -0.003956  0.001073   \n",
       "3 -0.005751  0.002910 -0.007079  0.001843 -0.001481  0.008085 -0.005315   \n",
       "4 -0.001609 -0.001678  0.002916 -0.001426  0.003689  0.011065  0.002640   \n",
       "\n",
       "         70        71        72        73        74        75        76  \\\n",
       "0  0.000557 -0.004787 -0.006329  0.004250  0.003193  0.000611  0.004937   \n",
       "1 -0.000813  0.000382 -0.000938  0.005969  0.000759  0.000437  0.004642   \n",
       "2  0.000306 -0.002091 -0.000257  0.003190  0.002147  0.000233  0.004014   \n",
       "3 -0.000860 -0.004668  0.003940 -0.003935  0.005237  0.000577 -0.000392   \n",
       "4 -0.001981 -0.004056 -0.001877 -0.008256  0.001612  0.000357 -0.001008   \n",
       "\n",
       "         77        78        79        80        81        82        83  \\\n",
       "0 -0.002435 -0.010002  0.005202 -0.004449  0.001022 -0.001900 -0.005596   \n",
       "1 -0.001402 -0.005463 -0.000447 -0.000400 -0.007205  0.001617  0.000552   \n",
       "2 -0.001664 -0.007914  0.002709 -0.001607  0.000984 -0.002138 -0.000419   \n",
       "3 -0.002009  0.004976 -0.001360 -0.006399 -0.003731  0.002678  0.012482   \n",
       "4  0.004687  0.010047  0.001832 -0.004028  0.000487 -0.000776  0.002337   \n",
       "\n",
       "         84        85        86        87        88        89        90  \\\n",
       "0 -0.000590 -0.000775  0.000065  0.001447 -0.009103 -0.007289 -0.003843   \n",
       "1  0.001775  0.001884  0.001239  0.009410 -0.001185 -0.005192 -0.000956   \n",
       "2 -0.000547 -0.000228  0.000371  0.003289 -0.004728 -0.004577 -0.001594   \n",
       "3 -0.005712 -0.009157  0.010385 -0.008893  0.005757  0.005256  0.002315   \n",
       "4 -0.003395 -0.005316  0.005361 -0.004850  0.004968  0.007549  0.001049   \n",
       "\n",
       "         91        92        93        94        95        96        97  \\\n",
       "0 -0.002246 -0.000216  0.001120 -0.001694 -0.001785 -0.004490 -0.004186   \n",
       "1 -0.005783 -0.000927 -0.002372  0.000240 -0.002697 -0.004125  0.001755   \n",
       "2 -0.002785  0.000521  0.000157 -0.000761 -0.002925 -0.002729 -0.002870   \n",
       "3  0.012063  0.004146 -0.006066 -0.011616 -0.002152  0.007147 -0.001056   \n",
       "4  0.003923  0.000946 -0.001707 -0.001963 -0.003033  0.004753 -0.001833   \n",
       "\n",
       "         98        99       100       101       102       103       104  \\\n",
       "0  0.003316 -0.006126  0.004397  0.000563  0.003522 -0.002592 -0.000511   \n",
       "1  0.003197 -0.000605  0.001321 -0.001208  0.001953  0.001707  0.004823   \n",
       "2  0.002260 -0.002608  0.002268 -0.000610  0.002469  0.001055  0.002409   \n",
       "3  0.010263  0.012072  0.004924  0.000888 -0.005017  0.008709  0.013407   \n",
       "4  0.004170  0.004961  0.001475 -0.001672 -0.001031  0.002833  0.006131   \n",
       "\n",
       "        105       106       107       108       109       110       111  \\\n",
       "0 -0.002908 -0.003775 -0.000803  0.003068  0.003710 -0.003042 -0.005348   \n",
       "1 -0.001778  0.000046 -0.005588 -0.003833  0.005903 -0.002701 -0.000305   \n",
       "2  0.000757 -0.001179 -0.000726 -0.000192  0.001947 -0.002876 -0.004225   \n",
       "3  0.014180  0.001005 -0.001245 -0.006040 -0.009866  0.006024 -0.002855   \n",
       "4  0.007077  0.000970  0.004488  0.002911 -0.003593  0.006264  0.001957   \n",
       "\n",
       "        112       113       114       115       116       117       118  \\\n",
       "0  0.005032  0.004530 -0.006334  0.001030 -0.002692 -0.001035 -0.000708   \n",
       "1  0.002246 -0.000370 -0.000592  0.000329  0.002070  0.000347  0.001702   \n",
       "2  0.005035  0.001253 -0.002786  0.000839 -0.000108 -0.000820  0.000550   \n",
       "3  0.000935 -0.002676 -0.004958  0.002334  0.003284  0.002368 -0.006183   \n",
       "4 -0.004054 -0.001472 -0.001309 -0.002096  0.006297 -0.001055 -0.007202   \n",
       "\n",
       "        119       120       121       122       123       124       125  \\\n",
       "0  0.013762  0.004706 -0.004970 -0.001227 -0.002073 -0.004395 -0.003007   \n",
       "1 -0.000166 -0.000069  0.007289  0.003029  0.000956  0.006247  0.003030   \n",
       "2  0.004553  0.003569  0.001601  0.002888  0.001402 -0.000123 -0.000276   \n",
       "3 -0.006321  0.005545 -0.000311  0.009847  0.000701  0.008558 -0.001030   \n",
       "4 -0.002022 -0.003977 -0.002993  0.000866  0.000710  0.003248 -0.000821   \n",
       "\n",
       "        126       127       128       129       130       131       132  \\\n",
       "0 -0.001933  0.002220 -0.005801  0.000941 -0.004171  0.003066  0.003047   \n",
       "1  0.000124 -0.000641 -0.002563  0.003606 -0.001970  0.007326  0.001987   \n",
       "2 -0.001046 -0.001028 -0.002321  0.002351 -0.000303  0.004724  0.003057   \n",
       "3  0.007608  0.014061  0.006539  0.004115  0.009240 -0.004986 -0.006364   \n",
       "4  0.004893  0.001801  0.000730  0.006553  0.001875 -0.007934  0.001897   \n",
       "\n",
       "        133       134       135       136       137       138       139  \\\n",
       "0  0.006733 -0.001738  0.006408 -0.004232 -0.001138  0.007493  0.003127   \n",
       "1  0.006974 -0.000799  0.008079 -0.004831  0.002992 -0.003861  0.004352   \n",
       "2  0.005729 -0.000481  0.006912 -0.009170  0.000180  0.001107  0.004029   \n",
       "3 -0.000488  0.008148 -0.006098 -0.009313  0.012192 -0.001144 -0.005071   \n",
       "4 -0.001260  0.007142 -0.007956  0.000240  0.005228 -0.001265 -0.000952   \n",
       "\n",
       "        140       141       142       143       144       145       146  \\\n",
       "0 -0.005692  0.006050 -0.003088  0.003156 -0.005429  0.006658  0.004450   \n",
       "1 -0.000036  0.005177 -0.006541  0.000609  0.000208  0.000929 -0.000266   \n",
       "2 -0.000955  0.004163 -0.003214 -0.000769 -0.000028  0.003590  0.002487   \n",
       "3  0.007572 -0.013070  0.001043 -0.005575 -0.003519 -0.005993 -0.008636   \n",
       "4  0.007961 -0.009255  0.005105 -0.004063 -0.004220  0.003465 -0.006518   \n",
       "\n",
       "        147       148       149       150       151       152       153  \\\n",
       "0  0.002410  0.002481  0.013582  0.001654 -0.000327 -0.002682 -0.002992   \n",
       "1 -0.000165  0.003226  0.000780 -0.004527 -0.000945  0.004098 -0.002132   \n",
       "2  0.001093  0.001905  0.004828 -0.003208  0.000137  0.001139 -0.004476   \n",
       "3 -0.000650 -0.006986 -0.009121  0.000755  0.013079  0.002076 -0.017425   \n",
       "4  0.003743 -0.004951 -0.007556 -0.003309  0.005537 -0.001746  0.002538   \n",
       "\n",
       "        154       155       156       157       158       159       160  \\\n",
       "0  0.007328  0.012059 -0.002122 -0.000760  0.007938  0.004236 -0.007783   \n",
       "1  0.003744  0.003986  0.001495 -0.001935  0.005328 -0.003285  0.006778   \n",
       "2  0.007098  0.007679  0.000384 -0.001003  0.005451  0.001259  0.000196   \n",
       "3 -0.004296 -0.006133  0.004651  0.000255  0.004990  0.008767 -0.001047   \n",
       "4 -0.010434 -0.007014  0.005587 -0.001107 -0.004208  0.001295  0.004583   \n",
       "\n",
       "        161       162       163       164       165       166       167  \\\n",
       "0 -0.001685 -0.002012 -0.003006 -0.000200 -0.002088  0.001345 -0.000170   \n",
       "1  0.001431 -0.002886  0.001198  0.001040 -0.001998  0.005288 -0.004095   \n",
       "2 -0.001340 -0.004397 -0.001096 -0.001432 -0.003001  0.001238 -0.003678   \n",
       "3 -0.015396 -0.003428 -0.006049 -0.000710 -0.001615 -0.003120 -0.005523   \n",
       "4 -0.014078 -0.005283 -0.001156  0.000435 -0.001728 -0.001805 -0.000829   \n",
       "\n",
       "        168       169       170       171       172       173       174  \\\n",
       "0 -0.002235  0.006566 -0.002846  0.004572  0.006810 -0.004250  0.007363   \n",
       "1 -0.000515 -0.000732  0.000986  0.003424  0.001906 -0.001599  0.005547   \n",
       "2  0.001909  0.002520 -0.001713  0.002993  0.005520 -0.002514  0.007303   \n",
       "3  0.014698 -0.007283 -0.003173  0.005119  0.010412 -0.001594 -0.004649   \n",
       "4  0.003978 -0.009634 -0.000968 -0.001138 -0.000695  0.003354 -0.007953   \n",
       "\n",
       "        175       176       177       178       179       180       181  \\\n",
       "0 -0.002255  0.003187 -0.008666  0.008766 -0.012510  0.002735 -0.002226   \n",
       "1 -0.000558  0.000861  0.003443  0.001305 -0.003596 -0.000309  0.000136   \n",
       "2 -0.000097  0.001314 -0.004341  0.002481 -0.005829 -0.000837 -0.003805   \n",
       "3  0.008439  0.002742 -0.000370 -0.008229 -0.002384 -0.005679 -0.000082   \n",
       "4  0.001724  0.003112  0.003967 -0.012626  0.000502 -0.000972  0.005894   \n",
       "\n",
       "        182       183       184       185       186       187       188  \\\n",
       "0 -0.004583 -0.000017  0.000594  0.007394  0.007216 -0.009349  0.006109   \n",
       "1  0.002129  0.003715  0.000656 -0.001256  0.004192 -0.004908  0.001253   \n",
       "2 -0.001569  0.001925  0.000775  0.005764  0.004770 -0.008731  0.005299   \n",
       "3 -0.002076 -0.000279  0.004088  0.000220 -0.010480 -0.010460 -0.005780   \n",
       "4  0.004535 -0.006220 -0.005194 -0.001993 -0.007887  0.005381 -0.004237   \n",
       "\n",
       "        189       190       191       192       193       194       195  \\\n",
       "0 -0.003539 -0.001058  0.006410 -0.003968 -0.003418 -0.005987 -0.000349   \n",
       "1 -0.000100 -0.004676  0.005369  0.000029  0.001301 -0.000130 -0.001653   \n",
       "2  0.001163 -0.001003  0.005146 -0.000789  0.000106  0.000231 -0.000705   \n",
       "3  0.008082 -0.010512  0.004513  0.018501 -0.004291  0.008247 -0.005214   \n",
       "4  0.003526  0.006868 -0.006208  0.001183  0.001384  0.000843 -0.000538   \n",
       "\n",
       "        196       197       198       199       200       201       202  \\\n",
       "0 -0.003589 -0.004120 -0.003990  0.006590 -0.004517 -0.007955 -0.005222   \n",
       "1  0.002840  0.001271  0.008204 -0.000202 -0.000863 -0.002364  0.001609   \n",
       "2 -0.000341 -0.001598  0.000705  0.004404 -0.004549 -0.003406 -0.003281   \n",
       "3 -0.005151  0.000537  0.008533  0.009378  0.002591  0.007559 -0.000021   \n",
       "4  0.000202  0.000670  0.003393  0.001102  0.003865  0.003482  0.002313   \n",
       "\n",
       "        203       204       205       206       207       208       209  \\\n",
       "0  0.002230  0.005574  0.000754  0.008606  0.002115  0.002924  0.000645   \n",
       "1  0.001860 -0.000888  0.001947  0.006667  0.000171 -0.000011 -0.001766   \n",
       "2 -0.000364  0.002250  0.001073  0.006508  0.002890  0.002586  0.000848   \n",
       "3  0.006741  0.003786  0.017479  0.001933 -0.012492 -0.003135  0.005879   \n",
       "4 -0.000524  0.001610  0.001718 -0.005350 -0.005895  0.000245  0.004085   \n",
       "\n",
       "        210       211       212       213       214       215       216  \\\n",
       "0  0.003336  0.003689 -0.000887 -0.000204  0.000128 -0.003729 -0.002760   \n",
       "1 -0.002764  0.000967  0.003783  0.001290 -0.001496 -0.001686  0.003631   \n",
       "2  0.000808  0.002934  0.003297 -0.001448 -0.001157 -0.003505  0.000309   \n",
       "3 -0.009476 -0.002311  0.015933  0.003649 -0.006620  0.006657  0.007641   \n",
       "4 -0.000278 -0.003854  0.005218  0.003397  0.000351  0.003043  0.000638   \n",
       "\n",
       "        217       218       219       220       221       222       223  \\\n",
       "0 -0.005721  0.004585  0.002891 -0.003355  0.005476 -0.002326 -0.001338   \n",
       "1  0.000797 -0.004414  0.002109 -0.000737 -0.000792 -0.003543  0.000040   \n",
       "2 -0.003576 -0.000585  0.002916  0.001352  0.004237 -0.001896 -0.002816   \n",
       "3  0.001674  0.004870 -0.001685 -0.005412  0.002810  0.001780 -0.007029   \n",
       "4  0.008459  0.000960 -0.006805 -0.004955 -0.002235  0.002537  0.005220   \n",
       "\n",
       "        224       225       226       227       228       229       230  \\\n",
       "0  0.004515 -0.006109 -0.004300  0.006142 -0.008638 -0.001841 -0.003307   \n",
       "1  0.002837 -0.001237 -0.002298  0.002736 -0.000320  0.002414  0.000393   \n",
       "2  0.005161 -0.002018 -0.000868  0.002030 -0.004721  0.000240 -0.002177   \n",
       "3 -0.000757  0.001910  0.006433  0.002402  0.005347  0.003398  0.010057   \n",
       "4 -0.004952 -0.000010 -0.000095  0.001680  0.009218  0.001509  0.000557   \n",
       "\n",
       "        231       232       233       234       235       236       237  \\\n",
       "0 -0.007982 -0.000609 -0.007637 -0.009760  0.000834 -0.004194  0.001217   \n",
       "1 -0.001212 -0.003941 -0.001039 -0.009250 -0.002265 -0.004860  0.002201   \n",
       "2 -0.004127 -0.003459 -0.000872 -0.008947 -0.001082 -0.004031  0.000032   \n",
       "3 -0.004514 -0.002222  0.009211 -0.020441  0.005050 -0.003008 -0.008313   \n",
       "4  0.000467  0.005892  0.010072 -0.010771  0.000307  0.000473 -0.004464   \n",
       "\n",
       "        238       239       240       241       242       243       244  \\\n",
       "0  0.004657 -0.002367 -0.003185  0.002436  0.004250 -0.000503  0.001145   \n",
       "1  0.000801 -0.002248 -0.003733  0.001498 -0.003929 -0.000850  0.001544   \n",
       "2  0.002541 -0.001883 -0.001830  0.002173  0.001758 -0.001697  0.000698   \n",
       "3 -0.001006  0.023590  0.006906  0.002240  0.009629  0.001271 -0.008618   \n",
       "4 -0.004146  0.015695  0.009529  0.004614  0.000116 -0.002080 -0.007691   \n",
       "\n",
       "        245       246       247       248       249       250       251  \\\n",
       "0  0.001158  0.001879 -0.001357 -0.000628  0.000163 -0.007244 -0.007605   \n",
       "1 -0.006092  0.000473 -0.000624  0.002165  0.000542 -0.000222 -0.002133   \n",
       "2 -0.002726  0.000632 -0.002519 -0.000642 -0.000692 -0.001570 -0.004926   \n",
       "3 -0.003097 -0.006483  0.005114 -0.006242 -0.001768  0.006093  0.001273   \n",
       "4 -0.003694  0.000585 -0.000227 -0.004657 -0.006214  0.003972  0.005916   \n",
       "\n",
       "        252       253       254       255       256       257       258  \\\n",
       "0 -0.003452  0.000018  0.001796 -0.000046 -0.002339 -0.000479  0.007232   \n",
       "1 -0.004275 -0.000211 -0.000457  0.000163 -0.007201 -0.000491 -0.001883   \n",
       "2 -0.002861  0.000273  0.001232 -0.000184 -0.001697  0.001505  0.004525   \n",
       "3 -0.017759 -0.009203 -0.000190  0.014746 -0.001711  0.007193  0.003628   \n",
       "4 -0.000871 -0.007495 -0.003989  0.004245  0.002578  0.001107 -0.001407   \n",
       "\n",
       "        259       260       261       262       263       264       265  \\\n",
       "0 -0.010644  0.005247 -0.005556  0.002255 -0.003174  0.010494  0.005637   \n",
       "1 -0.005460  0.006911 -0.004933  0.002711  0.005454 -0.003249  0.005815   \n",
       "2 -0.005389  0.003022 -0.005925  0.003244  0.000031  0.005136  0.005386   \n",
       "3  0.003185  0.001933 -0.003136  0.005200  0.006725 -0.003274  0.001943   \n",
       "4  0.007706 -0.007211  0.001114 -0.005189  0.004984 -0.001748 -0.003523   \n",
       "\n",
       "        266       267       268       269       270       271       272  \\\n",
       "0 -0.001970 -0.000483 -0.008590  0.002272  0.003792 -0.004972  0.000034   \n",
       "1  0.002572 -0.000396 -0.000483  0.001023 -0.000357 -0.002375 -0.002288   \n",
       "2 -0.000755  0.001083 -0.002872 -0.001028  0.002323 -0.004696 -0.002553   \n",
       "3 -0.003050  0.012695  0.001109 -0.001442 -0.002274  0.002177 -0.004069   \n",
       "4 -0.001577  0.000142  0.009031 -0.005275 -0.001430  0.004567 -0.000633   \n",
       "\n",
       "        273       274       275       276       277       278       279  \\\n",
       "0 -0.000027 -0.002423  0.000693 -0.003254 -0.007957 -0.001948  0.006308   \n",
       "1 -0.002635 -0.000637  0.002361  0.001522 -0.001509 -0.002052 -0.004516   \n",
       "2 -0.001303  0.000376  0.001295 -0.001650 -0.004442 -0.003426  0.001465   \n",
       "3 -0.008495  0.004030 -0.000771  0.003308  0.006749 -0.003146 -0.003374   \n",
       "4 -0.004632  0.000414 -0.003252 -0.000523  0.009145 -0.002628 -0.008933   \n",
       "\n",
       "        280       281       282       283       284       285       286  \\\n",
       "0 -0.001018 -0.005609  0.000670  0.004219 -0.008333 -0.003207  0.005300   \n",
       "1 -0.002954 -0.001485  0.003971  0.002128 -0.002856 -0.002071  0.000398   \n",
       "2 -0.001749 -0.003955  0.002847  0.002384 -0.003867 -0.001955  0.003560   \n",
       "3 -0.002810  0.001246  0.003597  0.000382  0.011801 -0.007923  0.004439   \n",
       "4  0.000825  0.009408  0.004169 -0.003717  0.003821  0.003737 -0.003645   \n",
       "\n",
       "        287       288       289       290       291       292       293  \\\n",
       "0  0.002946 -0.011096 -0.005440 -0.006602  0.001100 -0.001819 -0.004929   \n",
       "1 -0.000610 -0.000013  0.000588 -0.002250  0.001266 -0.000885 -0.001328   \n",
       "2  0.001139 -0.005800 -0.002149 -0.004418  0.000187 -0.001101 -0.003003   \n",
       "3 -0.007229  0.000260 -0.008417  0.002179  0.004321 -0.002208  0.003642   \n",
       "4 -0.005211  0.005278  0.002469  0.006803  0.000478  0.003211  0.005997   \n",
       "\n",
       "        294       295       296       297       298       299       300  \\\n",
       "0  0.004408 -0.002294 -0.001896 -0.011765  0.011569 -0.009669 -0.000850   \n",
       "1  0.002051 -0.001935 -0.003351 -0.001675  0.004258 -0.002545  0.000032   \n",
       "2  0.001395 -0.000196 -0.000687 -0.005953  0.003645 -0.004994 -0.001695   \n",
       "3 -0.014688  0.000962  0.010715  0.001356 -0.006549 -0.013929 -0.001882   \n",
       "4 -0.004050 -0.006022  0.004303  0.005620 -0.009924 -0.002434 -0.002266   \n",
       "\n",
       "        301       302       303       304       305       306       307  \\\n",
       "0 -0.001947 -0.003291 -0.002720  0.004024 -0.003592  0.006291  0.009176   \n",
       "1 -0.000308  0.001822 -0.005645 -0.000234 -0.004319  0.002719  0.001973   \n",
       "2 -0.000765  0.001946 -0.004481  0.001759 -0.001376  0.002192  0.004857   \n",
       "3 -0.004407  0.005251 -0.008241 -0.006877 -0.000031 -0.010575  0.006132   \n",
       "4 -0.006177  0.002716  0.006249 -0.005892  0.005215 -0.003852 -0.000609   \n",
       "\n",
       "        308       309       310       311       312       313       314  \\\n",
       "0 -0.000684  0.002185 -0.008286  0.005002 -0.003498  0.002933  0.007788   \n",
       "1  0.002813  0.002325  0.001256 -0.003249  0.006546 -0.001979 -0.001485   \n",
       "2 -0.001622  0.001589 -0.002263  0.000567 -0.000549 -0.001327  0.005732   \n",
       "3 -0.003762 -0.010743  0.007790  0.014735 -0.005917  0.000351  0.015528   \n",
       "4  0.005044 -0.012586  0.001935  0.004926 -0.001774  0.001821  0.005828   \n",
       "\n",
       "        315       316       317       318       319       320       321  \\\n",
       "0  0.000454 -0.004595 -0.000274 -0.003731  0.004325  0.000980  0.003137   \n",
       "1  0.003807 -0.000088 -0.005765 -0.002113  0.000726 -0.000228  0.001708   \n",
       "2  0.000796 -0.002129 -0.004202 -0.000435  0.000758  0.001282  0.001354   \n",
       "3  0.004538  0.005205 -0.003109 -0.003651  0.005203 -0.000431 -0.011314   \n",
       "4  0.002018  0.006045 -0.000734  0.003343 -0.004489  0.000532 -0.005981   \n",
       "\n",
       "        322       323       324       325       326       327       328  \\\n",
       "0 -0.008290 -0.000637 -0.003388  0.002274  0.002616 -0.001681  0.007493   \n",
       "1 -0.003648 -0.003335  0.001433  0.000495 -0.002904 -0.001140  0.001934   \n",
       "2 -0.003045 -0.003108 -0.000797  0.003943  0.001388 -0.001349  0.003555   \n",
       "3 -0.002118 -0.006106 -0.000441 -0.006619 -0.010588 -0.003119 -0.002094   \n",
       "4  0.003153  0.000289  0.001391 -0.004562 -0.004278  0.003065 -0.010981   \n",
       "\n",
       "        329       330       331       332       333       334       335  \\\n",
       "0 -0.001374  0.001922  0.000747  0.005497 -0.004544 -0.005103  0.001857   \n",
       "1 -0.001544  0.006937  0.003114  0.003723 -0.003374  0.000598  0.003127   \n",
       "2 -0.001258  0.004531  0.002402  0.002919 -0.003306 -0.001708  0.002203   \n",
       "3  0.009821 -0.000921 -0.004853 -0.004941  0.001802  0.003003 -0.003869   \n",
       "4  0.002848 -0.002906 -0.002266 -0.008011  0.001619  0.000897  0.000320   \n",
       "\n",
       "        336       337       338       339       340       341       342  \\\n",
       "0  0.006852 -0.003110 -0.003492  0.011977 -0.001746 -0.006554 -0.004790   \n",
       "1  0.001971 -0.003489  0.000003  0.002011  0.001543  0.000571  0.002954   \n",
       "2  0.002471 -0.002637 -0.000214  0.003513 -0.000983 -0.004609 -0.002597   \n",
       "3 -0.005943 -0.006190  0.003126 -0.001738  0.008161 -0.005443  0.000175   \n",
       "4 -0.004550 -0.001730  0.000913 -0.002610 -0.002464 -0.000137  0.002739   \n",
       "\n",
       "        343       344       345       346       347       348       349  \\\n",
       "0  0.003478  0.004946  0.004604 -0.012539 -0.001268 -0.001721 -0.000085   \n",
       "1 -0.004249 -0.000031 -0.002090 -0.006160 -0.001220  0.002064 -0.000844   \n",
       "2  0.000676  0.001903  0.001754 -0.006350 -0.000185  0.000572  0.000867   \n",
       "3 -0.007528  0.007868  0.005668  0.011491  0.004316  0.009442 -0.007122   \n",
       "4 -0.003543 -0.002181  0.001272  0.007591  0.001683  0.002744 -0.004292   \n",
       "\n",
       "        350       351       352       353       354       355       356  \\\n",
       "0  0.002606 -0.003262  0.008400 -0.006088 -0.006039 -0.001080  0.004411   \n",
       "1  0.005637  0.002212  0.002191 -0.004165  0.006326  0.000222 -0.001233   \n",
       "2  0.001571 -0.000751  0.004707 -0.004768 -0.000309 -0.003802  0.001033   \n",
       "3  0.001432 -0.000035  0.003566 -0.006418  0.006594 -0.008582  0.005260   \n",
       "4  0.002358 -0.004141 -0.005304  0.001516 -0.000224  0.001790  0.008032   \n",
       "\n",
       "        357       358       359       360       361       362       363  \\\n",
       "0  0.002365 -0.004801 -0.006958 -0.000641  0.002824  0.006942 -0.005025   \n",
       "1  0.004685 -0.002974  0.000532 -0.008781  0.000585 -0.000520 -0.003381   \n",
       "2  0.002071 -0.003668 -0.004895 -0.006001  0.000758  0.004973 -0.007410   \n",
       "3  0.002441  0.002633  0.000655 -0.009667  0.005820 -0.003021  0.007652   \n",
       "4  0.000050 -0.001383  0.000406  0.004917 -0.000847 -0.004276  0.007006   \n",
       "\n",
       "        364       365       366       367       368       369       370  \\\n",
       "0  0.002441  0.001353 -0.000082 -0.004659  0.001985  0.001751  0.007858   \n",
       "1 -0.000096  0.004933 -0.001777  0.000204  0.002057 -0.000291 -0.006100   \n",
       "2  0.001144  0.003964 -0.000051 -0.000279  0.000758  0.001544 -0.001437   \n",
       "3  0.010012 -0.001932 -0.002825 -0.000553 -0.002318  0.000619 -0.005500   \n",
       "4 -0.003003 -0.001622  0.001375  0.004074 -0.001774 -0.003822 -0.005093   \n",
       "\n",
       "        371       372       373       374       375       376       377  \\\n",
       "0  0.001790  0.000919 -0.000298 -0.002244  0.004237  0.000828 -0.006844   \n",
       "1  0.005486  0.000856  0.005285 -0.000910 -0.007412 -0.001051  0.000210   \n",
       "2  0.002331 -0.000014  0.001253 -0.000283 -0.002273  0.001916 -0.003672   \n",
       "3  0.001682 -0.006809  0.004185  0.003385  0.000322 -0.002018  0.004385   \n",
       "4  0.001612  0.001097 -0.004537  0.002555 -0.000288 -0.007979  0.005640   \n",
       "\n",
       "        378       379       380       381       382       383       384  \\\n",
       "0  0.008459  0.005118 -0.000023 -0.013254 -0.000635  0.001363 -0.001795   \n",
       "1 -0.000926 -0.000028  0.000468 -0.002332 -0.002915 -0.001808 -0.003136   \n",
       "2 -0.000143  0.001645  0.002330 -0.010662  0.001321 -0.000864 -0.002499   \n",
       "3 -0.011242 -0.008273  0.004208  0.001734 -0.004746 -0.006230 -0.002114   \n",
       "4  0.006600 -0.004001 -0.001309  0.008440 -0.000717 -0.007569 -0.002529   \n",
       "\n",
       "        385       386       387       388       389       390       391  \\\n",
       "0 -0.002976 -0.002670 -0.004095 -0.004342  0.002858 -0.010473 -0.003198   \n",
       "1  0.000648  0.001136 -0.003341 -0.001253  0.005500 -0.003532 -0.000047   \n",
       "2 -0.001460 -0.000200 -0.002046 -0.002664  0.006770 -0.005767 -0.000921   \n",
       "3  0.000901 -0.002506  0.003958  0.007301  0.015434  0.008088 -0.003450   \n",
       "4  0.004958  0.000790  0.006025  0.007009 -0.004792  0.002331 -0.005401   \n",
       "\n",
       "        392       393       394       395       396       397       398  \\\n",
       "0 -0.002863 -0.000459  0.004597  0.004563  0.001963 -0.001478 -0.003395   \n",
       "1  0.000018  0.004065 -0.003817  0.006483 -0.002586 -0.000813 -0.008039   \n",
       "2 -0.001066  0.002041  0.001461  0.005656 -0.001666 -0.001130 -0.003461   \n",
       "3  0.004394 -0.003394  0.000268 -0.000212  0.001074  0.014988 -0.008361   \n",
       "4  0.000707 -0.007436 -0.006361 -0.004932  0.000383 -0.000114 -0.003236   \n",
       "\n",
       "        399       400       401       402       403       404       405  \\\n",
       "0 -0.009020  0.004000 -0.001206 -0.002643 -0.002629 -0.002933 -0.002904   \n",
       "1 -0.004399  0.000164  0.001488  0.002707  0.000867 -0.001973  0.002025   \n",
       "2 -0.005652  0.000897 -0.000950  0.000699 -0.002795 -0.002364 -0.001244   \n",
       "3  0.010381 -0.006635  0.003316 -0.002516 -0.000403  0.002445 -0.006312   \n",
       "4  0.013075 -0.002431  0.000638 -0.000726  0.000708  0.000391 -0.000539   \n",
       "\n",
       "        406       407       408       409       410       411       412  \\\n",
       "0 -0.003276  0.008862 -0.001322  0.000425 -0.008587 -0.002175  0.005011   \n",
       "1 -0.000853  0.003696 -0.001473 -0.000225  0.003349  0.001429  0.003255   \n",
       "2 -0.004487  0.004600 -0.002025 -0.000370 -0.002842 -0.002636  0.003808   \n",
       "3 -0.008796 -0.000116  0.001852 -0.004929  0.008533  0.000095 -0.004769   \n",
       "4  0.000512  0.001225  0.004515 -0.007087  0.005318 -0.002076  0.003204   \n",
       "\n",
       "        413       414       415       416       417       418       419  \\\n",
       "0  0.002639  0.001981  0.001597  0.003285  0.006081  0.009656 -0.000778   \n",
       "1 -0.005715  0.003484 -0.000862 -0.002179  0.001604 -0.002499 -0.002114   \n",
       "2 -0.000494  0.002871 -0.000364  0.000790  0.003250  0.002966 -0.000429   \n",
       "3  0.008146 -0.007155 -0.003321  0.000307 -0.001060  0.001441  0.000053   \n",
       "4  0.001008 -0.003370 -0.001116  0.001061 -0.006357  0.000351  0.008104   \n",
       "\n",
       "        420       421       422       423       424       425       426  \\\n",
       "0 -0.000198 -0.000004  0.004717  0.008202 -0.005843  0.003433  0.002622   \n",
       "1 -0.006316  0.000491 -0.003621  0.000323 -0.000413  0.001487  0.001529   \n",
       "2 -0.003006 -0.000956 -0.000765  0.003959 -0.001882  0.002661  0.000686   \n",
       "3 -0.002304 -0.001602 -0.007708  0.003524  0.014231  0.002595 -0.004719   \n",
       "4  0.003967  0.003960 -0.000475 -0.002753  0.002951 -0.000413  0.000598   \n",
       "\n",
       "        427       428       429       430       431       432       433  \\\n",
       "0 -0.007305 -0.001266  0.003037  0.000979  0.003750  0.000326 -0.004067   \n",
       "1  0.000567 -0.007458  0.000960  0.001414  0.002622 -0.001311 -0.001550   \n",
       "2 -0.002113 -0.001376  0.000169  0.001094  0.004328 -0.001399 -0.000251   \n",
       "3  0.012870 -0.002978 -0.013729  0.000558  0.014707  0.007637  0.005685   \n",
       "4  0.010207 -0.001567 -0.005640 -0.005142  0.002730  0.003111  0.001751   \n",
       "\n",
       "        434       435       436       437       438       439       440  \\\n",
       "0 -0.003417 -0.001478  0.002335 -0.002801  0.006955  0.000015  0.005252   \n",
       "1 -0.000834 -0.003316 -0.001409  0.004381  0.001285 -0.000183  0.001479   \n",
       "2  0.000794  0.001056  0.001543  0.000200  0.003106  0.000123  0.003024   \n",
       "3  0.001102 -0.000620 -0.004628 -0.001868  0.003153 -0.007812  0.004223   \n",
       "4 -0.001908  0.003468 -0.005181  0.001222 -0.000392 -0.009367  0.000565   \n",
       "\n",
       "        441       442       443       444       445       446       447  \\\n",
       "0 -0.005993 -0.001634 -0.004723  0.002039  0.002762 -0.000594 -0.002401   \n",
       "1 -0.002749 -0.004522 -0.003197 -0.002027 -0.000521 -0.000284 -0.001985   \n",
       "2 -0.002709 -0.001892 -0.004055 -0.000025  0.003034  0.001007 -0.005975   \n",
       "3  0.006406  0.001885 -0.007560  0.006905 -0.004586  0.008165 -0.012605   \n",
       "4  0.006181  0.002171 -0.003833 -0.002744 -0.004780 -0.002748 -0.001617   \n",
       "\n",
       "        448       449       450       451       452       453       454  \\\n",
       "0 -0.002338  0.004323 -0.003520  0.000300  0.003160 -0.002437  0.003282   \n",
       "1 -0.002740 -0.002361  0.001156 -0.000268  0.000690  0.000133  0.003523   \n",
       "2 -0.002149  0.002412 -0.003539  0.000337  0.001650 -0.001221  0.004999   \n",
       "3  0.001803  0.000333 -0.004281 -0.000286  0.001895 -0.006753 -0.003258   \n",
       "4  0.001901 -0.001115 -0.000330  0.000460 -0.002645 -0.007317  0.002992   \n",
       "\n",
       "        455       456       457       458       459       460       461  \\\n",
       "0  0.002997 -0.001690  0.005104  0.003124  0.021138 -0.008735 -0.001766   \n",
       "1 -0.003181 -0.003115 -0.002571  0.003337  0.000541 -0.004239 -0.000300   \n",
       "2 -0.000844 -0.000573  0.000180  0.001845  0.009868 -0.006403 -0.000967   \n",
       "3 -0.003839  0.005622 -0.009538  0.004394 -0.002947 -0.006281 -0.005271   \n",
       "4  0.002923  0.000848 -0.005538 -0.003953 -0.008905  0.000331 -0.000291   \n",
       "\n",
       "        462       463       464       465       466       467       468  \\\n",
       "0 -0.007534  0.006001  0.005115 -0.005641  0.006440  0.000479 -0.005883   \n",
       "1 -0.001187 -0.004446  0.002863 -0.000953  0.002714 -0.001473  0.000342   \n",
       "2 -0.006023 -0.001569  0.003088 -0.001335  0.001644  0.001898 -0.003921   \n",
       "3 -0.011118 -0.015571 -0.010631 -0.004490 -0.009815  0.000306  0.012209   \n",
       "4 -0.000121 -0.008729 -0.005692  0.001733 -0.006690 -0.000877  0.008125   \n",
       "\n",
       "        469       470       471       472       473       474       475  \\\n",
       "0  0.005565  0.000001 -0.005525  0.002366  0.001094 -0.004438 -0.003804   \n",
       "1 -0.000817  0.003521 -0.004910 -0.001112 -0.000411  0.001621  0.000500   \n",
       "2  0.002789  0.002971 -0.005832 -0.000669  0.000396 -0.001430 -0.001625   \n",
       "3  0.006021  0.006984  0.004114 -0.005553 -0.003706 -0.000458 -0.003128   \n",
       "4  0.005272 -0.003766  0.001985 -0.001519  0.000517  0.000013  0.000965   \n",
       "\n",
       "        476       477       478       479       480       481       482  \\\n",
       "0  0.000252 -0.004086  0.007175  0.002231  0.002621 -0.000050  0.003858   \n",
       "1  0.002201 -0.006457  0.004645  0.001603 -0.001066 -0.004928 -0.000288   \n",
       "2  0.001568 -0.004271  0.004049  0.002908 -0.001834 -0.003282  0.002760   \n",
       "3  0.000801 -0.002175 -0.006965 -0.002316 -0.010232 -0.002298  0.006447   \n",
       "4  0.004496  0.001580 -0.007750 -0.005869 -0.007786  0.001544 -0.000680   \n",
       "\n",
       "        483       484       485       486       487       488       489  \\\n",
       "0  0.009224  0.006117  0.004712  0.007446  0.003142  0.005351  0.001471   \n",
       "1  0.007518  0.003553  0.002274 -0.000873  0.001896  0.002269  0.002745   \n",
       "2  0.006411  0.003782  0.003147  0.002358  0.002040  0.002744  0.000921   \n",
       "3 -0.004175 -0.007377 -0.009964  0.004610  0.002130 -0.007100  0.011058   \n",
       "4 -0.003887 -0.007272 -0.009140 -0.000963 -0.002012 -0.010825  0.004503   \n",
       "\n",
       "        490       491       492       493       494  ...       783       784  \\\n",
       "0 -0.004765 -0.000367 -0.006590 -0.001904 -0.003761  ...  0.001853 -0.004825   \n",
       "1  0.003929  0.002371  0.000128  0.005033 -0.001226  ... -0.002494  0.000747   \n",
       "2 -0.001223  0.001132 -0.001797  0.000665 -0.002556  ...  0.000433 -0.001007   \n",
       "3  0.008136  0.002592 -0.010724 -0.007064 -0.004359  ... -0.002789  0.004718   \n",
       "4  0.002203 -0.001153 -0.004419 -0.002674 -0.003784  ... -0.002440  0.003578   \n",
       "\n",
       "        785       786       787       788       789       790       791  \\\n",
       "0 -0.004105  0.005022  0.003571 -0.001795 -0.001572  0.006370 -0.001410   \n",
       "1 -0.001385  0.009638  0.003521 -0.000522  0.000561 -0.000192  0.001406   \n",
       "2 -0.003479  0.005989  0.002503  0.000435  0.000992  0.002852  0.000655   \n",
       "3 -0.003479 -0.000263  0.003572  0.004727  0.000771  0.002442  0.006991   \n",
       "4  0.000496 -0.005749 -0.001555  0.000727  0.004111 -0.002372 -0.001511   \n",
       "\n",
       "        792       793       794       795       796       797       798  \\\n",
       "0 -0.004103 -0.002774 -0.003145 -0.003326  0.000314 -0.000896  0.004464   \n",
       "1 -0.001567  0.001872 -0.001337 -0.006624  0.003946 -0.002637  0.002448   \n",
       "2 -0.002492  0.000261 -0.002169 -0.000887  0.003594 -0.001009  0.001598   \n",
       "3 -0.005417  0.006208  0.004296  0.010111  0.002681 -0.001555 -0.009507   \n",
       "4  0.001224  0.003049  0.001377  0.000223 -0.004406  0.003568 -0.004115   \n",
       "\n",
       "        799       800       801       802       803       804       805  \\\n",
       "0  0.006698  0.010924 -0.001516  0.003525 -0.005164 -0.000705  0.003306   \n",
       "1  0.000594 -0.000353 -0.002710  0.001619 -0.003120  0.003322  0.003156   \n",
       "2  0.003293  0.002903 -0.000700  0.003077 -0.005147  0.001776  0.002632   \n",
       "3  0.000257 -0.003381 -0.010428 -0.004871  0.004610 -0.008839  0.000388   \n",
       "4 -0.002926 -0.005698  0.001095 -0.003753  0.000078 -0.007364 -0.001632   \n",
       "\n",
       "        806       807       808       809       810       811       812  \\\n",
       "0 -0.000277  0.004697 -0.007911  0.003834 -0.003547 -0.005056  0.000232   \n",
       "1 -0.001034  0.000347 -0.000194 -0.000791  0.001370 -0.000717 -0.001479   \n",
       "2 -0.001892  0.001713 -0.001691  0.000848  0.000766 -0.003730  0.000932   \n",
       "3  0.006411 -0.002544 -0.001637 -0.001551  0.009239  0.001057 -0.000726   \n",
       "4 -0.003815 -0.000898  0.004058 -0.000930  0.002614  0.001044  0.001816   \n",
       "\n",
       "        813       814       815       816       817       818       819  \\\n",
       "0 -0.002777 -0.002308  0.001011  0.003399 -0.011207 -0.005757 -0.005707   \n",
       "1  0.002841 -0.001648  0.002490  0.000622  0.001481 -0.004538 -0.002973   \n",
       "2  0.001728 -0.004056  0.000083  0.003931 -0.004466 -0.004109 -0.004257   \n",
       "3  0.013650 -0.000676  0.005630  0.003068  0.009164 -0.005227  0.005770   \n",
       "4  0.006050  0.001786  0.000512 -0.004546  0.005492  0.000930  0.004144   \n",
       "\n",
       "        820       821       822       823       824       825       826  \\\n",
       "0  0.006208  0.006205 -0.004009 -0.006675 -0.004794  0.001098  0.001365   \n",
       "1 -0.004161 -0.002375 -0.002207 -0.001935 -0.000621  0.006917 -0.000483   \n",
       "2  0.001282  0.001845 -0.001606 -0.002569 -0.003462  0.004505  0.000581   \n",
       "3  0.000063 -0.006457 -0.001392  0.002213 -0.004814  0.014181 -0.006488   \n",
       "4 -0.002696 -0.002503  0.005134  0.002485  0.000257  0.004762 -0.000612   \n",
       "\n",
       "        827       828       829       830       831       832       833  \\\n",
       "0  0.011387 -0.001293  0.010500  0.000524  0.002752 -0.002868  0.000371   \n",
       "1  0.004052  0.000223  0.000122 -0.000655 -0.002002 -0.000417 -0.003626   \n",
       "2  0.006636 -0.000550  0.003573 -0.002108  0.002484 -0.002274  0.000615   \n",
       "3 -0.008543 -0.004331 -0.000550 -0.002211 -0.004660 -0.010791 -0.006687   \n",
       "4 -0.004920 -0.000470 -0.004702 -0.003881  0.002894  0.000904  0.001864   \n",
       "\n",
       "        834       835       836       837       838       839       840  \\\n",
       "0 -0.000415  0.004123 -0.001168 -0.003838  0.000399  0.006600  0.004980   \n",
       "1 -0.003995  0.000151  0.004092 -0.002145 -0.000563 -0.000019 -0.000545   \n",
       "2 -0.001032  0.001960  0.002325 -0.001879 -0.000156 -0.000166  0.001412   \n",
       "3  0.007169  0.006782  0.005833 -0.005731 -0.004347  0.000218 -0.006834   \n",
       "4  0.006960  0.001752 -0.001262 -0.001182 -0.008065 -0.000019 -0.001122   \n",
       "\n",
       "        841       842       843       844       845       846       847  \\\n",
       "0 -0.010759  0.000608  0.000529  0.001002 -0.005758 -0.003974  0.007797   \n",
       "1 -0.004100  0.001835  0.001928 -0.004750  0.001604  0.000758 -0.005482   \n",
       "2 -0.006539  0.000359 -0.000113  0.000285 -0.003895 -0.001474  0.002026   \n",
       "3 -0.000546 -0.007544 -0.006154  0.004892 -0.014094 -0.002611 -0.004265   \n",
       "4  0.003914 -0.005908 -0.000939  0.005159  0.001858  0.000722 -0.005833   \n",
       "\n",
       "        848       849       850       851       852       853       854  \\\n",
       "0 -0.009725  0.005865 -0.003664  0.008944  0.009346  0.000797  0.000887   \n",
       "1 -0.004904 -0.004869 -0.003482 -0.001946  0.001213  0.001538  0.000325   \n",
       "2 -0.004296 -0.001474 -0.001252  0.003544  0.003752  0.001999  0.000215   \n",
       "3  0.007592  0.003699  0.005374  0.002248 -0.003863  0.000038  0.000098   \n",
       "4  0.001347  0.001139  0.001493  0.006612 -0.002556 -0.003409  0.001042   \n",
       "\n",
       "        855       856       857       858       859       860       861  \\\n",
       "0  0.002772 -0.003367  0.003296  0.001201 -0.000482  0.005248  0.005021   \n",
       "1  0.000696 -0.005030 -0.000800  0.002104  0.000886 -0.002643  0.002751   \n",
       "2 -0.000308 -0.002747  0.000604 -0.000867 -0.000699  0.000951  0.003611   \n",
       "3 -0.002378  0.004232 -0.011772 -0.002318 -0.002896 -0.012400 -0.012538   \n",
       "4 -0.004241  0.001463 -0.003543 -0.001175 -0.000636 -0.006529 -0.006263   \n",
       "\n",
       "        862       863       864       865       866       867       868  \\\n",
       "0  0.001763  0.003390 -0.005972 -0.004258 -0.000625  0.004447 -0.002024   \n",
       "1 -0.001919 -0.005029 -0.003694 -0.001568  0.004757  0.002956 -0.000047   \n",
       "2  0.001004 -0.000646 -0.002978 -0.003646  0.002683  0.002488 -0.000338   \n",
       "3  0.009027  0.004523  0.006960 -0.003576  0.002492  0.000723  0.002521   \n",
       "4  0.006715  0.005717  0.006899  0.000988 -0.005719 -0.004945  0.001491   \n",
       "\n",
       "        869       870       871       872       873       874       875  \\\n",
       "0  0.000723  0.003046 -0.006266  0.004699 -0.001824  0.004019 -0.003601   \n",
       "1 -0.000024  0.003003 -0.002677  0.003872  0.000547  0.002726 -0.000146   \n",
       "2  0.002324  0.002267 -0.004413  0.003299 -0.002138  0.004568  0.000583   \n",
       "3  0.005172  0.005398  0.000399  0.003636 -0.000958 -0.004564 -0.002525   \n",
       "4  0.000852 -0.003704  0.006189  0.004543 -0.000086 -0.001014 -0.001267   \n",
       "\n",
       "        876       877       878       879       880       881       882  \\\n",
       "0 -0.028502 -0.000853  0.000028  0.004616  0.005497  0.001255  0.001495   \n",
       "1  0.011734  0.000455  0.000752 -0.001889  0.003672 -0.000692  0.002164   \n",
       "2 -0.010170  0.000810  0.001265  0.000947  0.006531  0.002066 -0.000972   \n",
       "3 -0.006415 -0.002690 -0.007712 -0.019142  0.001955 -0.001671  0.002396   \n",
       "4 -0.004788  0.000200  0.002416 -0.003725 -0.004215  0.000523  0.001659   \n",
       "\n",
       "        883       884       885       886       887       888       889  \\\n",
       "0 -0.012231 -0.009861  0.005232 -0.008915  0.005231 -0.002353 -0.004961   \n",
       "1  0.002887 -0.001416  0.002405  0.000307  0.001953 -0.002931  0.003204   \n",
       "2 -0.003245 -0.000239  0.001623 -0.003105  0.002114 -0.001234 -0.000855   \n",
       "3  0.012967 -0.000634 -0.002383 -0.001253 -0.012169 -0.008524 -0.000142   \n",
       "4  0.003605  0.002989 -0.000029  0.002694 -0.007722 -0.002443  0.003299   \n",
       "\n",
       "        890       891       892       893       894       895       896  \\\n",
       "0  0.006445  0.003820 -0.004297  0.007125  0.003156  0.007652 -0.002011   \n",
       "1 -0.003072 -0.000341  0.005361 -0.001850 -0.001096 -0.000558 -0.000967   \n",
       "2  0.003455  0.002724  0.001943  0.003262  0.000809  0.005380 -0.000384   \n",
       "3 -0.004119 -0.000909 -0.000283  0.010044 -0.002188 -0.006571 -0.002219   \n",
       "4 -0.004109  0.000633 -0.003849  0.005786 -0.002362 -0.006972 -0.002625   \n",
       "\n",
       "        897       898       899       900       901       902       903  \\\n",
       "0 -0.003582 -0.001509  0.000779  0.002303 -0.003520  0.005689  0.010472   \n",
       "1 -0.003816 -0.003976 -0.000630  0.000081  0.003379 -0.002186  0.001462   \n",
       "2 -0.003195 -0.002797  0.001275  0.000339  0.001141  0.001686  0.003658   \n",
       "3 -0.000708 -0.003496  0.005212 -0.008632  0.012524  0.000226 -0.001055   \n",
       "4  0.007393  0.009215 -0.001103 -0.005710  0.003802 -0.001138 -0.005780   \n",
       "\n",
       "        904       905       906       907       908       909       910  \\\n",
       "0  0.005543 -0.003652  0.004436 -0.004752  0.004456  0.003100  0.008039   \n",
       "1  0.005445 -0.005174  0.003430  0.000904  0.004320  0.001745 -0.000899   \n",
       "2  0.004915 -0.004764  0.001600 -0.002305  0.003290  0.002297 -0.000738   \n",
       "3  0.003622  0.001682 -0.009452 -0.011821 -0.006998 -0.003859 -0.016605   \n",
       "4 -0.004400 -0.003323 -0.002462 -0.001829 -0.006636 -0.004310 -0.009812   \n",
       "\n",
       "        911       912       913       914       915       916       917  \\\n",
       "0 -0.002783 -0.004633 -0.002108 -0.010201  0.001383  0.002102  0.006877   \n",
       "1 -0.003137 -0.004041 -0.000435 -0.003659  0.001378 -0.001996  0.002496   \n",
       "2 -0.002228 -0.003098  0.000897 -0.006696  0.001484 -0.000039  0.003103   \n",
       "3 -0.009689 -0.003057 -0.003918  0.004505  0.012329  0.005905  0.000423   \n",
       "4 -0.003027  0.000720 -0.006053  0.004773  0.004995  0.002276 -0.002932   \n",
       "\n",
       "        918       919       920       921       922       923       924  \\\n",
       "0 -0.011129  0.001141  0.006317 -0.008450  0.001704 -0.000311  0.011933   \n",
       "1 -0.000900  0.001333 -0.002189 -0.002776  0.001087  0.002395 -0.000890   \n",
       "2 -0.003043  0.000854  0.000210 -0.004403  0.003371  0.001631  0.008503   \n",
       "3  0.001961 -0.009720  0.006879 -0.000380  0.003894  0.006366  0.000451   \n",
       "4  0.004482 -0.002625  0.001419  0.000633 -0.000740  0.000977 -0.003378   \n",
       "\n",
       "        925       926       927       928       929       930       931  \\\n",
       "0  0.004289 -0.005513 -0.000602  0.003280  0.007059  0.004133 -0.003220   \n",
       "1  0.004375 -0.001467 -0.000606  0.001189  0.004796 -0.007712 -0.000275   \n",
       "2  0.004136 -0.002198  0.001331  0.000127  0.005136 -0.003257 -0.001834   \n",
       "3 -0.002149  0.005586  0.008883 -0.005197  0.003697 -0.024970  0.001268   \n",
       "4 -0.007951  0.007089  0.001211  0.003707  0.000034 -0.006759 -0.001843   \n",
       "\n",
       "        932       933       934       935       936       937       938  \\\n",
       "0 -0.002597  0.007762 -0.005168  0.005155 -0.001474  0.008265 -0.007314   \n",
       "1 -0.001116 -0.000139 -0.002867  0.003639  0.003427  0.001717 -0.004914   \n",
       "2 -0.000589  0.004771 -0.001900  0.003834  0.002597  0.003465 -0.005570   \n",
       "3  0.003824  0.001234  0.007010 -0.009388  0.001050  0.011935  0.005011   \n",
       "4  0.005588  0.000461  0.009947 -0.000429 -0.003201  0.002961  0.003578   \n",
       "\n",
       "        939       940       941       942       943       944       945  \\\n",
       "0  0.002857 -0.000681 -0.002008 -0.003248  0.001069  0.003655  0.001974   \n",
       "1 -0.002428 -0.001729  0.000485 -0.001695 -0.002192  0.000638  0.001852   \n",
       "2 -0.002061 -0.000266  0.002084 -0.002867  0.000317  0.002323 -0.000034   \n",
       "3 -0.006414  0.009406  0.006568 -0.001005  0.009956 -0.001823 -0.001707   \n",
       "4  0.004429  0.007892  0.004225  0.002567  0.000637  0.000865 -0.000494   \n",
       "\n",
       "        946       947       948       949       950       951       952  \\\n",
       "0  0.009681 -0.008204  0.003589  0.002943  0.005035  0.000491 -0.001282   \n",
       "1  0.001845 -0.000111  0.000407 -0.002436 -0.001365  0.002021  0.001851   \n",
       "2  0.004767 -0.005834  0.001657  0.000658  0.001024  0.001304 -0.001445   \n",
       "3 -0.009748  0.004161  0.003833 -0.002299 -0.001462 -0.003109 -0.014126   \n",
       "4 -0.005048  0.003975 -0.003921  0.000092 -0.001471 -0.004624  0.003038   \n",
       "\n",
       "        953       954       955       956       957       958       959  \\\n",
       "0 -0.000248  0.002212  0.002148  0.003609  0.008287 -0.004587 -0.008573   \n",
       "1  0.002180 -0.001217  0.000679 -0.003685 -0.003890 -0.001024  0.001088   \n",
       "2 -0.000115  0.001606  0.003634 -0.002547  0.000907 -0.001185 -0.004377   \n",
       "3 -0.003046 -0.011102 -0.002238  0.008416 -0.007870  0.006612 -0.009689   \n",
       "4 -0.002907 -0.003765  0.000646  0.006916 -0.003745  0.007293  0.005219   \n",
       "\n",
       "        960       961       962       963       964       965       966  \\\n",
       "0  0.000723  0.001434 -0.003390 -0.002041  0.007911  0.006009 -0.002130   \n",
       "1  0.002543  0.005739 -0.002018  0.000495  0.000955 -0.001939  0.005252   \n",
       "2  0.004333  0.000962 -0.002190 -0.000114  0.002327  0.002658  0.000926   \n",
       "3  0.005125 -0.008288  0.003471 -0.007264 -0.010433  0.003808 -0.004035   \n",
       "4 -0.000962 -0.000175  0.004902  0.002143 -0.003517 -0.000975 -0.004573   \n",
       "\n",
       "        967       968       969       970       971       972       973  \\\n",
       "0  0.005947 -0.004412 -0.006648  0.010594 -0.003362  0.002635 -0.009418   \n",
       "1  0.001891  0.000566 -0.004282  0.007317 -0.000687  0.003051 -0.000897   \n",
       "2  0.005232 -0.000648 -0.005277  0.007134 -0.000677  0.001168 -0.005339   \n",
       "3 -0.000027  0.010557  0.001609  0.003614 -0.000886 -0.004510  0.005688   \n",
       "4 -0.008031  0.002911  0.001631 -0.007392 -0.001785 -0.002386  0.005854   \n",
       "\n",
       "        974       975       976       977       978       979       980  \\\n",
       "0 -0.001327 -0.005974 -0.005435  0.001865  0.000867 -0.005751  0.005233   \n",
       "1 -0.004686  0.000562  0.003005  0.000522 -0.000916  0.000446  0.003708   \n",
       "2 -0.003922 -0.001905 -0.000304  0.000742 -0.001232 -0.000536  0.006279   \n",
       "3  0.002767 -0.006711 -0.003819 -0.027639 -0.001664  0.003189 -0.013366   \n",
       "4  0.001024 -0.001811  0.001193 -0.012547 -0.003798 -0.002171 -0.005774   \n",
       "\n",
       "        981       982       983       984       985       986       987  \\\n",
       "0 -0.002514 -0.004314  0.001509  0.006846  0.006396  0.003910  0.000732   \n",
       "1  0.000044 -0.000352  0.004183  0.000147  0.004579 -0.000387  0.001955   \n",
       "2 -0.000840 -0.000034  0.002845  0.003053  0.005551  0.001298 -0.000123   \n",
       "3  0.002838  0.001337 -0.007892  0.004753 -0.003217 -0.005543 -0.003545   \n",
       "4 -0.000603  0.001878 -0.005006 -0.000121 -0.003011 -0.004765 -0.002176   \n",
       "\n",
       "        988       989       990       991       992       993       994  \\\n",
       "0  0.007434  0.002479 -0.000767  0.003164  0.001642  0.006758 -0.009542   \n",
       "1  0.006274 -0.000868  0.003246  0.004949  0.000960  0.001794 -0.005426   \n",
       "2  0.005662  0.000809  0.000482  0.005148 -0.000664  0.004202 -0.006927   \n",
       "3  0.001269 -0.006059  0.006750  0.009795 -0.010899 -0.010615  0.005228   \n",
       "4 -0.007227 -0.001165  0.002824 -0.003718 -0.003393 -0.003780  0.007759   \n",
       "\n",
       "        995       996       997       998       999      1000      1001  \\\n",
       "0 -0.007527  0.002650  0.004797  0.009927  0.007912 -0.002413 -0.002616   \n",
       "1  0.001095 -0.002318 -0.001666  0.009929 -0.001606  0.001832 -0.002037   \n",
       "2 -0.000422  0.001865  0.004531  0.008443  0.003474  0.000647 -0.001987   \n",
       "3  0.009636  0.000486 -0.001129 -0.009402  0.008821  0.006143  0.000300   \n",
       "4  0.005468 -0.003689 -0.002886 -0.012854  0.001604  0.009180  0.004220   \n",
       "\n",
       "       1002      1003      1004      1005      1006      1007      1008  \\\n",
       "0  0.000845  0.002013 -0.000816 -0.000949 -0.005307 -0.001706  0.004884   \n",
       "1 -0.001793  0.000806  0.000860  0.001025 -0.004991 -0.000144  0.002480   \n",
       "2 -0.001830 -0.001166  0.002247  0.000942 -0.002277 -0.001117  0.003283   \n",
       "3 -0.000341 -0.003522 -0.002881  0.003854  0.000789  0.005915 -0.010355   \n",
       "4  0.002954 -0.001210 -0.003428 -0.002271  0.001851  0.003840 -0.007585   \n",
       "\n",
       "       1009      1010      1011      1012      1013      1014      1015  \\\n",
       "0  0.002780 -0.000456 -0.003082  0.010725  0.006711  0.005910  0.000381   \n",
       "1 -0.003896  0.000367  0.000829  0.003670  0.003671  0.004156 -0.001881   \n",
       "2  0.001231 -0.000141  0.001368  0.005194  0.002548  0.002964  0.001227   \n",
       "3 -0.004280 -0.003020 -0.001607 -0.006273 -0.004918 -0.014880  0.008853   \n",
       "4 -0.001564  0.000789  0.000328 -0.005998 -0.004830 -0.009269  0.003636   \n",
       "\n",
       "       1016      1017      1018      1019      1020      1021      1022  \\\n",
       "0  0.003895  0.007585  0.004521  0.007398 -0.003492 -0.000129 -0.003768   \n",
       "1  0.000812  0.000850  0.003391  0.001766  0.001131 -0.000713 -0.004386   \n",
       "2  0.001356  0.001781  0.003912  0.002740  0.001812 -0.000197 -0.001587   \n",
       "3  0.003023 -0.003390  0.000519 -0.000332  0.012038  0.001560  0.002485   \n",
       "4 -0.002792 -0.001797 -0.001252 -0.004151  0.002248  0.003810  0.002370   \n",
       "\n",
       "       1023      1024      1025      1026      1027      1028      1029  \\\n",
       "0 -0.002924 -0.001704  0.004513  0.004837 -0.001674 -0.007842 -0.002553   \n",
       "1  0.002673 -0.002020  0.002296  0.002220  0.001291 -0.001561  0.003964   \n",
       "2 -0.000933 -0.000626  0.002844  0.002911  0.000564 -0.003354  0.000811   \n",
       "3 -0.000056 -0.000745  0.005487 -0.008767  0.001178  0.001327 -0.005863   \n",
       "4  0.001541  0.003043 -0.004578 -0.005639  0.002382  0.003181  0.000018   \n",
       "\n",
       "       1030      1031      1032      1033      1034      1035      1036  \\\n",
       "0  0.004770  0.004965 -0.003042  0.000574 -0.001793 -0.000634  0.011419   \n",
       "1 -0.002158  0.002620  0.003389  0.001761 -0.000022 -0.001588  0.004331   \n",
       "2  0.001608  0.003075 -0.000030  0.000915 -0.000362 -0.001756  0.007517   \n",
       "3  0.006762 -0.003472  0.006037 -0.001943  0.002984 -0.006977  0.001240   \n",
       "4  0.000735 -0.000612  0.002972 -0.000486  0.000183 -0.002488 -0.006943   \n",
       "\n",
       "       1037      1038      1039      1040      1041      1042      1043  \\\n",
       "0 -0.012274  0.007318  0.005310 -0.002118 -0.004183 -0.005952 -0.005874   \n",
       "1 -0.007911  0.004321  0.001742  0.004874  0.001602 -0.001650 -0.001933   \n",
       "2 -0.009313  0.005702  0.001698 -0.000440  0.000160 -0.002866 -0.003232   \n",
       "3 -0.001522 -0.004316  0.009255 -0.000403  0.014436  0.001368  0.006142   \n",
       "4  0.006430 -0.008495  0.001057  0.003234  0.004276  0.005450  0.001425   \n",
       "\n",
       "       1044      1045      1046      1047      1048      1049      1050  \\\n",
       "0 -0.002159  0.005735  0.000972  0.001641  0.004541 -0.003215  0.002098   \n",
       "1 -0.002093  0.001448 -0.003245  0.002422  0.002507 -0.002441 -0.004023   \n",
       "2 -0.002612  0.002072  0.000222  0.001083  0.001696 -0.002966 -0.000709   \n",
       "3  0.001537 -0.002476  0.001323  0.000437  0.000573  0.011829  0.007153   \n",
       "4  0.001308 -0.002968  0.005625 -0.001577 -0.006387  0.007392  0.002295   \n",
       "\n",
       "       1051      1052      1053      1054      1055      1056      1057  \\\n",
       "0  0.001160 -0.004673  0.007593 -0.004132 -0.004235  0.009154  0.007042   \n",
       "1  0.001685  0.000815  0.003674  0.002426  0.001362 -0.000356 -0.000395   \n",
       "2 -0.000048 -0.001926  0.004157 -0.000919 -0.001277  0.003237  0.001963   \n",
       "3  0.000742 -0.001113  0.005721  0.006887 -0.004399 -0.006866  0.003969   \n",
       "4 -0.003306  0.002022 -0.004258  0.007435 -0.001989 -0.007882  0.002799   \n",
       "\n",
       "       1058      1059      1060      1061      1062      1063      1064  \\\n",
       "0  0.002043 -0.005049 -0.006457  0.004323 -0.003796 -0.000677  0.001260   \n",
       "1 -0.000506 -0.004125 -0.002061  0.000086 -0.001102 -0.003258  0.005661   \n",
       "2  0.000028 -0.005614 -0.003715  0.001582 -0.003014 -0.001688  0.002360   \n",
       "3  0.012598  0.001537  0.007366  0.007686 -0.000895  0.003221 -0.005785   \n",
       "4  0.004047  0.001144  0.003983  0.002129  0.003350  0.002134 -0.005590   \n",
       "\n",
       "       1065      1066      1067      1068      1069      1070      1071  \\\n",
       "0 -0.004335  0.000987 -0.000387 -0.010761  0.006239  0.001163  0.002810   \n",
       "1  0.003965  0.000133 -0.004082 -0.000135 -0.001579  0.005034  0.003602   \n",
       "2  0.002443  0.000940 -0.001468 -0.005785  0.001494  0.001355  0.000702   \n",
       "3  0.008888 -0.003175  0.007031  0.003802  0.008191 -0.007958 -0.003317   \n",
       "4  0.000710 -0.007778 -0.001891  0.003862  0.003214 -0.005978  0.000474   \n",
       "\n",
       "       1072      1073      1074      1075      1076      1077      1078  \\\n",
       "0  0.002129  0.008587  0.000520  0.002393 -0.001776 -0.004646 -0.001924   \n",
       "1  0.000775  0.000414 -0.002283  0.000509  0.000184 -0.004333  0.002305   \n",
       "2 -0.000106  0.003197  0.000730  0.000893  0.000192 -0.004399  0.001022   \n",
       "3  0.007669  0.005389  0.011699 -0.005045 -0.004139  0.002811  0.003813   \n",
       "4  0.005371  0.002037  0.006995 -0.005063  0.002264  0.005753 -0.002165   \n",
       "\n",
       "       1079      1080      1081      1082      1083      1084      1085  \\\n",
       "0 -0.001987 -0.002959 -0.006058 -0.004105  0.003657  0.004626  0.004524   \n",
       "1  0.000936  0.000402 -0.000009 -0.005472 -0.000710  0.000585 -0.003682   \n",
       "2  0.000061  0.000407  0.000426 -0.002261  0.000616  0.002420  0.001075   \n",
       "3  0.001670 -0.008682  0.009680  0.004962  0.000851  0.010386 -0.003440   \n",
       "4 -0.006393 -0.003897  0.005493  0.005321 -0.002703 -0.002980 -0.002505   \n",
       "\n",
       "       1086      1087      1088      1089      1090      1091      1092  \\\n",
       "0 -0.000461  0.012908 -0.004787 -0.001794  0.003498  0.001557  0.000731   \n",
       "1 -0.003001 -0.002656 -0.001364  0.001641  0.000397  0.000929  0.001161   \n",
       "2 -0.001422  0.002973 -0.003820 -0.002766  0.000611  0.001048 -0.001471   \n",
       "3  0.001460  0.002038  0.007297  0.001546 -0.012513  0.003570 -0.004566   \n",
       "4  0.002743 -0.005221  0.005093  0.002640 -0.003089  0.005345  0.000383   \n",
       "\n",
       "       1093      1094      1095      1096      1097      1098      1099  \\\n",
       "0 -0.000431  0.002069  0.001653  0.002036  0.003535 -0.001400  0.002427   \n",
       "1 -0.000427  0.000508  0.001497  0.000118 -0.002483  0.000346 -0.000778   \n",
       "2 -0.000651 -0.000778 -0.001062 -0.000853  0.000886  0.000324  0.000289   \n",
       "3 -0.000986 -0.005267 -0.009787 -0.005350 -0.004647  0.002005 -0.009381   \n",
       "4 -0.001643 -0.001629 -0.003849  0.000733  0.000826 -0.004458 -0.003010   \n",
       "\n",
       "       1100      1101      1102      1103      1104      1105      1106  \\\n",
       "0  0.000632 -0.000073  0.003720 -0.004585  0.010733  0.002584  0.008741   \n",
       "1 -0.002458 -0.001003 -0.001132 -0.003157  0.003487  0.003784  0.004643   \n",
       "2  0.000870 -0.001526  0.000933 -0.003803  0.005082  0.004858  0.004316   \n",
       "3  0.007997  0.005250 -0.014698 -0.000505 -0.017321  0.010749  0.004073   \n",
       "4  0.003331  0.003342 -0.006916  0.000815 -0.013179  0.001554 -0.003302   \n",
       "\n",
       "       1107      1108      1109      1110      1111      1112      1113  \\\n",
       "0 -0.011122 -0.001453 -0.003604 -0.000493  0.003991  0.000632  0.000292   \n",
       "1 -0.005611  0.000625 -0.001392 -0.001760  0.002323  0.001822 -0.003009   \n",
       "2 -0.004715  0.000025  0.000076 -0.003433  0.004414  0.001262 -0.000826   \n",
       "3 -0.004085  0.003723  0.001736 -0.007749 -0.000832  0.000068 -0.000140   \n",
       "4  0.003517  0.002687 -0.001022  0.010075 -0.002407 -0.002101  0.003718   \n",
       "\n",
       "       1114      1115      1116      1117      1118      1119      1120  \\\n",
       "0  0.001253  0.006234 -0.001079  0.003224 -0.003889  0.003642  0.005208   \n",
       "1 -0.004915 -0.000982 -0.004607 -0.001477  0.002869  0.007182 -0.000507   \n",
       "2 -0.001564  0.003783 -0.003299 -0.001664 -0.000692  0.003720  0.000567   \n",
       "3 -0.008526  0.005793  0.004406 -0.007187 -0.002408 -0.006218  0.008370   \n",
       "4 -0.007985 -0.003279  0.003045 -0.005396  0.003376 -0.004243 -0.000980   \n",
       "\n",
       "       1121      1122      1123      1124      1125      1126      1127  \\\n",
       "0 -0.006301 -0.004531  0.003383 -0.003216 -0.001922  0.008373  0.000015   \n",
       "1 -0.001543  0.004684 -0.000522 -0.002789  0.003759 -0.002150 -0.000672   \n",
       "2 -0.004693 -0.000204  0.002204 -0.004405  0.001580  0.001316 -0.001586   \n",
       "3  0.005194  0.007689 -0.005904  0.005939  0.004482 -0.005056  0.003243   \n",
       "4  0.012561  0.001858 -0.002216  0.002927  0.000277 -0.006694 -0.001347   \n",
       "\n",
       "       1128      1129      1130      1131      1132      1133      1134  \\\n",
       "0  0.006317  0.001862 -0.002463 -0.000178  0.000207  0.002494 -0.004085   \n",
       "1  0.000430  0.000777  0.002088  0.002297  0.000165 -0.004206  0.001031   \n",
       "2  0.000363  0.003229  0.000530  0.001888  0.000988 -0.001594 -0.001511   \n",
       "3 -0.009869 -0.007245  0.006185 -0.006239 -0.011484 -0.008518 -0.007950   \n",
       "4 -0.006589  0.000164  0.001895 -0.005986 -0.007113  0.000191  0.004452   \n",
       "\n",
       "       1135      1136      1137      1138      1139      1140      1141  \\\n",
       "0 -0.000317 -0.004050 -0.002591 -0.000578 -0.007256 -0.000095  0.000828   \n",
       "1 -0.001919 -0.000946  0.005356 -0.002754  0.001922 -0.000066  0.002864   \n",
       "2 -0.000620 -0.003069  0.000079  0.000335 -0.000861 -0.001490  0.002620   \n",
       "3 -0.004320 -0.004224  0.003527 -0.001120  0.005529  0.001387  0.004295   \n",
       "4 -0.003357  0.001659  0.000060  0.000911  0.001960 -0.003563  0.001039   \n",
       "\n",
       "       1142      1143      1144      1145      1146      1147      1148  \\\n",
       "0 -0.001294  0.001070 -0.003755 -0.003444  0.003891 -0.000255  0.013864   \n",
       "1  0.003399 -0.001069 -0.002727 -0.001410 -0.004574 -0.003438  0.001970   \n",
       "2  0.001336  0.002098 -0.001556 -0.004735 -0.000642 -0.001379  0.007653   \n",
       "3  0.003376  0.003163  0.012282 -0.002306 -0.002013  0.001356 -0.004786   \n",
       "4  0.001211  0.001736 -0.000745  0.003839 -0.007487  0.001948 -0.009391   \n",
       "\n",
       "       1149      1150      1151      1152      1153      1154      1155  \\\n",
       "0 -0.001735 -0.002377 -0.009057  0.001671  0.001164  0.002980 -0.009550   \n",
       "1  0.001062 -0.003287 -0.001799 -0.000047  0.000368 -0.004688 -0.002218   \n",
       "2 -0.000416 -0.001686 -0.003135  0.001527  0.001953 -0.000403 -0.005697   \n",
       "3  0.011900  0.000919  0.007332  0.002184  0.002864 -0.018468  0.010034   \n",
       "4  0.003020  0.000959  0.008670 -0.001196  0.003210 -0.001581  0.006536   \n",
       "\n",
       "       1156      1157      1158      1159      1160      1161      1162  \\\n",
       "0 -0.008745  0.002028  0.005308 -0.000641  0.033912  0.002231 -0.002407   \n",
       "1 -0.003762 -0.005283 -0.003763 -0.003124 -0.001896 -0.001691  0.008579   \n",
       "2 -0.003899 -0.000030  0.000595 -0.004442  0.003507  0.001786  0.001744   \n",
       "3  0.000553  0.006191 -0.009226  0.008989 -0.004457 -0.000800 -0.000518   \n",
       "4  0.004418  0.005121 -0.009717  0.004144 -0.008547  0.000554  0.001406   \n",
       "\n",
       "       1163      1164      1165      1166      1167      1168      1169  \\\n",
       "0  0.001768 -0.001168 -0.004282 -0.003597 -0.003565 -0.003218  0.001302   \n",
       "1  0.007583  0.003213 -0.000449  0.003214 -0.000219 -0.000517  0.002234   \n",
       "2  0.005222  0.002536 -0.004478 -0.000007 -0.004313 -0.000970  0.003568   \n",
       "3 -0.001062  0.008006 -0.010530  0.003928 -0.003129  0.004882  0.000328   \n",
       "4 -0.006212  0.003426 -0.003931  0.002286  0.002905  0.001368 -0.002835   \n",
       "\n",
       "       1170      1171      1172      1173      1174      1175      1176  \\\n",
       "0 -0.002086 -0.008752  0.001775  0.002813  0.002518  0.006637 -0.006155   \n",
       "1 -0.000257  0.000024 -0.000741 -0.000982  0.000183  0.003615 -0.005491   \n",
       "2 -0.000307 -0.000105 -0.003397  0.001009  0.000454  0.005946 -0.007346   \n",
       "3  0.008715  0.009887 -0.001589 -0.001407 -0.004055  0.001394 -0.008486   \n",
       "4  0.006987  0.003766 -0.001711 -0.002004 -0.006303 -0.007697 -0.000948   \n",
       "\n",
       "       1177      1178      1179      1180      1181      1182      1183  \\\n",
       "0  0.003113 -0.003088  0.003588  0.000525 -0.008758  0.002451  0.001703   \n",
       "1  0.000358 -0.003905 -0.000435 -0.003215 -0.003982  0.003442  0.000444   \n",
       "2  0.003109 -0.003658  0.001517 -0.003145 -0.006120  0.002802 -0.001303   \n",
       "3  0.004310 -0.005357  0.004375  0.002478  0.002729  0.003002 -0.011194   \n",
       "4 -0.004791 -0.004272 -0.001037 -0.000489  0.005916 -0.001943 -0.004365   \n",
       "\n",
       "       1184      1185      1186      1187      1188      1189      1190  \\\n",
       "0 -0.004010  0.001648  0.002025 -0.004000  0.000372 -0.012531 -0.001429   \n",
       "1 -0.002314  0.004182  0.000052 -0.001429 -0.002954  0.001522  0.001930   \n",
       "2 -0.002125  0.003493  0.000404 -0.005149 -0.004391 -0.007192  0.001592   \n",
       "3  0.007009  0.000714  0.014408  0.006603 -0.004174  0.011914  0.009980   \n",
       "4  0.006818 -0.003776  0.001974  0.011620 -0.000924  0.003449  0.007249   \n",
       "\n",
       "       1191      1192      1193      1194      1195      1196      1197  \\\n",
       "0 -0.007036 -0.001672  0.001931 -0.000335  0.004489  0.001426  0.002925   \n",
       "1  0.003185 -0.003132  0.000109 -0.000184  0.002173  0.001814 -0.006247   \n",
       "2 -0.000869 -0.000918 -0.000899 -0.000842  0.003269  0.003082 -0.001193   \n",
       "3  0.012751 -0.005883 -0.009657 -0.001705  0.007608  0.004737 -0.008167   \n",
       "4  0.003084 -0.003317 -0.003446 -0.003963 -0.003640 -0.001127 -0.001690   \n",
       "\n",
       "       1198      1199      1200      1201      1202      1203      1204  \\\n",
       "0 -0.005068  0.000946  0.001076  0.000817 -0.006266 -0.006568  0.002272   \n",
       "1  0.003999 -0.000282  0.000965 -0.000213  0.005772 -0.002476 -0.002544   \n",
       "2 -0.000758  0.001173 -0.000831  0.000899  0.001563 -0.003624 -0.000650   \n",
       "3  0.009936 -0.001411 -0.014298 -0.002624  0.007873  0.005376 -0.000106   \n",
       "4  0.002598 -0.001005 -0.005238 -0.000333 -0.000551 -0.001576 -0.001935   \n",
       "\n",
       "       1205      1206      1207      1208      1209      1210      1211  \\\n",
       "0  0.002776  0.002689  0.001243  0.010112 -0.004836  0.002611  0.003935   \n",
       "1 -0.000967  0.001775 -0.001085  0.002551 -0.002846  0.000493  0.002565   \n",
       "2 -0.002048  0.001292  0.002027  0.004819 -0.001560  0.001423  0.003461   \n",
       "3 -0.006798 -0.000324  0.000126 -0.004922  0.020413 -0.000375 -0.001113   \n",
       "4  0.003699 -0.001511 -0.001963 -0.008522  0.011874  0.004201 -0.000671   \n",
       "\n",
       "       1212      1213      1214      1215      1216      1217      1218  \\\n",
       "0  0.003538  0.006074 -0.001749 -0.003450 -0.003461  0.000416 -0.004331   \n",
       "1 -0.000049  0.003042  0.002458  0.001157 -0.003079  0.003549 -0.002870   \n",
       "2  0.001985  0.005454 -0.000235 -0.000876 -0.002509  0.002964 -0.004921   \n",
       "3 -0.016149 -0.000477 -0.000023 -0.013357  0.005865  0.000101  0.007961   \n",
       "4 -0.004653 -0.006324  0.000169 -0.008368  0.002840  0.000280  0.003849   \n",
       "\n",
       "       1219      1220      1221      1222      1223      1224      1225  \\\n",
       "0 -0.000705 -0.003025  0.004187 -0.008011 -0.002535  0.001290  0.003631   \n",
       "1 -0.001641  0.000906 -0.002574  0.003358  0.000392 -0.006646 -0.001252   \n",
       "2 -0.002823  0.000685  0.000392 -0.003351 -0.000157 -0.003875  0.001611   \n",
       "3 -0.003085  0.009965 -0.007398  0.006291  0.003187  0.007088 -0.001882   \n",
       "4 -0.001673 -0.002002 -0.002434  0.002833  0.002729  0.004236 -0.004682   \n",
       "\n",
       "       1226      1227      1228      1229      1230      1231      1232  \\\n",
       "0 -0.004148 -0.007724 -0.004900  0.001873  0.002570  0.002026 -0.002774   \n",
       "1  0.002143  0.003294 -0.001132 -0.000098  0.003329  0.000252  0.002045   \n",
       "2  0.000193 -0.002321 -0.003488  0.002336  0.002921  0.001887 -0.001929   \n",
       "3  0.008161  0.009741 -0.000460 -0.001436 -0.007137 -0.007437  0.003878   \n",
       "4  0.004260  0.003642  0.008232 -0.005737 -0.000487 -0.005699  0.004266   \n",
       "\n",
       "       1233      1234      1235      1236      1237      1238      1239  \\\n",
       "0 -0.002987  0.002104  0.001275  0.000386  0.000118  0.001486  0.001503   \n",
       "1 -0.001054 -0.000043  0.000951  0.000570  0.001261  0.000425 -0.005690   \n",
       "2  0.001034  0.000725  0.001609  0.000630  0.000811  0.000050  0.000612   \n",
       "3  0.006034 -0.009194  0.000843  0.008307  0.005829 -0.003962 -0.003075   \n",
       "4  0.003859 -0.006486 -0.001472 -0.002495  0.004884 -0.001086 -0.000399   \n",
       "\n",
       "       1240      1241      1242      1243      1244      1245      1246  \\\n",
       "0  0.003058  0.004697 -0.002407 -0.005566 -0.003793 -0.000626 -0.000390   \n",
       "1 -0.003137 -0.000632  0.000790  0.000191 -0.001748  0.000250  0.000128   \n",
       "2 -0.002673  0.001426  0.001154 -0.001617 -0.005566  0.001887 -0.002332   \n",
       "3 -0.007779  0.001405 -0.003967  0.008015 -0.001405  0.008397  0.002877   \n",
       "4 -0.002601 -0.004319 -0.001082  0.002546  0.005598  0.005924 -0.002384   \n",
       "\n",
       "       1247      1248      1249      1250      1251      1252      1253  \\\n",
       "0  0.001811  0.004139  0.009623 -0.002554  0.001318  0.006217  0.001786   \n",
       "1 -0.001355  0.002444  0.002274 -0.004300  0.001348  0.000502 -0.001999   \n",
       "2 -0.001287  0.003442  0.005313 -0.002194 -0.002129  0.000546 -0.001055   \n",
       "3  0.008065  0.001060  0.000964  0.009822  0.013424 -0.003469  0.001062   \n",
       "4  0.006545 -0.002430 -0.006307  0.002711  0.005242 -0.005628  0.000864   \n",
       "\n",
       "       1254      1255      1256      1257      1258      1259      1260  \\\n",
       "0 -0.004694 -0.000620 -0.000839  0.000981 -0.000774  0.000527 -0.000049   \n",
       "1  0.001594  0.000865  0.004196  0.002273 -0.002218  0.000885  0.007369   \n",
       "2 -0.001138  0.001241 -0.000449  0.002954 -0.003886 -0.001415  0.003804   \n",
       "3 -0.005695 -0.001510  0.005355 -0.007122 -0.012169 -0.007502  0.004943   \n",
       "4  0.001913 -0.007391  0.005219  0.003791  0.001190 -0.004289 -0.002755   \n",
       "\n",
       "       1261      1262      1263      1264      1265      1266      1267  \\\n",
       "0  0.000246 -0.006903 -0.007978 -0.004754  0.002166 -0.004440 -0.002391   \n",
       "1 -0.002596 -0.001608  0.001013  0.003873 -0.004223 -0.000815  0.007243   \n",
       "2 -0.001086 -0.004927 -0.005850 -0.002068 -0.000393 -0.003590  0.001722   \n",
       "3 -0.003612 -0.000596 -0.005103 -0.001728 -0.004516 -0.012891 -0.002525   \n",
       "4 -0.007370  0.000787  0.001424 -0.004954  0.000784 -0.003405  0.001943   \n",
       "\n",
       "       1268      1269      1270      1271      1272      1273      1274  \\\n",
       "0 -0.000643 -0.000126 -0.006577  0.008047  0.004099  0.003754  0.002841   \n",
       "1 -0.003368  0.002374  0.000447  0.002127 -0.000243 -0.000179 -0.001908   \n",
       "2 -0.002203  0.000800 -0.002868  0.003846 -0.001309  0.002737  0.000492   \n",
       "3  0.000833 -0.000366  0.003219 -0.005892 -0.003820  0.000123  0.002821   \n",
       "4  0.004562 -0.000358  0.001799 -0.007718 -0.001927 -0.004853  0.001723   \n",
       "\n",
       "       1275      1276      1277      1278      1279  len         preds  \n",
       "0  0.008031  0.001052  0.005231 -0.004897 -0.000695  221 -10884.404301  \n",
       "1 -0.000759  0.000466 -0.001078 -0.003322  0.000893  221 -10884.868028  \n",
       "2  0.001449  0.001184  0.004764 -0.005017  0.000357  220 -10317.575149  \n",
       "3 -0.005008  0.004118 -0.001402  0.000100 -0.001173  221 -10908.172922  \n",
       "4 -0.003374  0.000668 -0.009545  0.003395 -0.007194  221 -10903.710743  \n",
       "\n",
       "[5 rows x 1286 columns]"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols=['seq_id','preds']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "submission = test_df.loc[:,cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "submission.rename(columns={\"preds\":\"tm\"},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "submission.to_csv('sub.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_df.to_csv('predictions.csv',index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check prediction score and plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stats.spearmanr(valid_preds, valid_ds.y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter(x='oof',y='y_normalize');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check spearman score per group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "group\n",
       "0     0.073685\n",
       "1     0.271525\n",
       "2     0.162579\n",
       "3     0.310813\n",
       "4     0.207076\n",
       "5     0.178303\n",
       "6     0.139770\n",
       "7     0.224328\n",
       "8     0.009251\n",
       "9     0.251276\n",
       "10    0.062934\n",
       "11    0.315801\n",
       "12    0.431585\n",
       "13    0.388309\n",
       "14    0.299967\n",
       "15   -0.163214\n",
       "16   -0.012990\n",
       "17    0.170564\n",
       "18    0.324426\n",
       "19    0.571364\n",
       "20    0.076772\n",
       "21    0.313968\n",
       "22    0.497625\n",
       "23   -0.136987\n",
       "24    0.295745\n",
       "25    0.441062\n",
       "26    0.107100\n",
       "27    0.277696\n",
       "28    0.507661\n",
       "29    0.539755\n",
       "30    0.321945\n",
       "31   -0.148490\n",
       "32    0.191930\n",
       "34    0.177243\n",
       "35    0.463575\n",
       "36    0.007946\n",
       "38    0.452398\n",
       "39    0.173144\n",
       "40    0.039131\n",
       "41    0.273554\n",
       "dtype: float64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('group')[['oof','y_normalize']].apply(lambda x: x.corr('spearman').oof.y_normalize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>oof</th>\n",
       "      <th>y_normalize</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>oof</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.038054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>y_normalize</th>\n",
       "      <td>0.038054</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  oof  y_normalize\n",
       "oof          1.000000     0.038054\n",
       "y_normalize  0.038054     1.000000"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['oof','y_normalize']].corr('spearman')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.47156996],\n",
       "       [0.53584355],\n",
       "       [0.5202725 ],\n",
       "       ...,\n",
       "       [0.5280656 ],\n",
       "       [0.5192892 ],\n",
       "       [0.6572173 ]], dtype=float32)"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sequential(\n",
       "  (0): Linear(in_features=1282, out_features=500, bias=True)\n",
       "  (1): BatchNorm1d(500, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "  (2): Linear(in_features=500, out_features=200, bias=True)\n",
       "  (3): BatchNorm1d(200, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "  (4): Linear(in_features=200, out_features=1, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.cuda()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1\n",
      "-------------------------------\n",
      "loss: 1.080293  [    0/ 3764]\n",
      "loss: 1.687482  [  800/ 3764]\n",
      "loss: 1.118925  [ 1600/ 3764]\n",
      "loss: 0.757889  [ 2400/ 3764]\n",
      "loss: 0.668643  [ 3200/ 3764]\n",
      "Test Error: Avg loss: 0.945010\n",
      "Epoch 2\n",
      "-------------------------------\n",
      "loss: 0.988457  [    0/ 3764]\n",
      "loss: 0.538472  [  800/ 3764]\n",
      "loss: 1.003537  [ 1600/ 3764]\n",
      "loss: 0.696454  [ 2400/ 3764]\n",
      "loss: 0.936770  [ 3200/ 3764]\n",
      "Test Error: Avg loss: 0.940664\n",
      "Epoch 3\n",
      "-------------------------------\n",
      "loss: 0.864447  [    0/ 3764]\n",
      "loss: 0.333849  [  800/ 3764]\n",
      "loss: 0.419051  [ 1600/ 3764]\n",
      "loss: 1.874793  [ 2400/ 3764]\n",
      "loss: 0.546775  [ 3200/ 3764]\n",
      "Test Error: Avg loss: 0.917771\n",
      "Epoch 4\n",
      "-------------------------------\n",
      "loss: 0.171663  [    0/ 3764]\n",
      "loss: 0.947445  [  800/ 3764]\n",
      "loss: 1.595440  [ 1600/ 3764]\n",
      "loss: 0.756516  [ 2400/ 3764]\n",
      "loss: 0.356026  [ 3200/ 3764]\n",
      "Test Error: Avg loss: 0.940091\n",
      "Epoch 5\n",
      "-------------------------------\n",
      "loss: 1.478294  [    0/ 3764]\n",
      "loss: 0.909177  [  800/ 3764]\n",
      "loss: 0.459987  [ 1600/ 3764]\n",
      "loss: 1.149477  [ 2400/ 3764]\n",
      "loss: 0.503476  [ 3200/ 3764]\n",
      "Test Error: Avg loss: 0.915178\n"
     ]
    }
   ],
   "source": [
    "for epoch in range(5):\n",
    "    print(f\"Epoch {epoch+1}\\n-------------------------------\")\n",
    "    train(dl)\n",
    "    test(dl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine.to_csv('with_esm_feature.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "gc.collect();torch.cuda.empty_cache()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get WT feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_wt = pd.DataFrame(df2.wildtype.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_wt.rename(columns={0: 'protein_sequence'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "49ec8d1e790c4a93abd0c2240bddd63f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/78 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wt_feature = get_feature_df(df_wt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "wt_combine = pd.concat([df_wt, wt_feature], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "wt_combine.to_csv('wildtype_feature.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get WT-mutant differences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>protein_sequence</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>...</th>\n",
       "      <th>1270</th>\n",
       "      <th>1271</th>\n",
       "      <th>1272</th>\n",
       "      <th>1273</th>\n",
       "      <th>1274</th>\n",
       "      <th>1275</th>\n",
       "      <th>1276</th>\n",
       "      <th>1277</th>\n",
       "      <th>1278</th>\n",
       "      <th>1279</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCND...</td>\n",
       "      <td>0.015805</td>\n",
       "      <td>-0.033919</td>\n",
       "      <td>0.005356</td>\n",
       "      <td>-0.001142</td>\n",
       "      <td>-0.037829</td>\n",
       "      <td>-0.062076</td>\n",
       "      <td>0.034698</td>\n",
       "      <td>0.074689</td>\n",
       "      <td>0.025458</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031189</td>\n",
       "      <td>-0.033546</td>\n",
       "      <td>-0.103467</td>\n",
       "      <td>0.056230</td>\n",
       "      <td>-0.052916</td>\n",
       "      <td>-0.003619</td>\n",
       "      <td>-0.020674</td>\n",
       "      <td>-0.058185</td>\n",
       "      <td>0.027794</td>\n",
       "      <td>0.081028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MEELQDDYEDMMEENLEQEEYEDPDIPESQMEEPAAHDTEATATDY...</td>\n",
       "      <td>-0.017728</td>\n",
       "      <td>0.002291</td>\n",
       "      <td>-0.005282</td>\n",
       "      <td>-0.005080</td>\n",
       "      <td>-0.027136</td>\n",
       "      <td>-0.036133</td>\n",
       "      <td>0.065131</td>\n",
       "      <td>0.004717</td>\n",
       "      <td>0.007467</td>\n",
       "      <td>...</td>\n",
       "      <td>0.056245</td>\n",
       "      <td>0.033457</td>\n",
       "      <td>-0.124666</td>\n",
       "      <td>-0.020386</td>\n",
       "      <td>0.027567</td>\n",
       "      <td>-0.074638</td>\n",
       "      <td>0.048811</td>\n",
       "      <td>-0.047698</td>\n",
       "      <td>0.007801</td>\n",
       "      <td>0.049899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MTDITANVVVSNPRPIFTESRSFKAVANGKIYIGQIDTDPVNPANQ...</td>\n",
       "      <td>0.016938</td>\n",
       "      <td>0.050288</td>\n",
       "      <td>0.001779</td>\n",
       "      <td>-0.010340</td>\n",
       "      <td>-0.100914</td>\n",
       "      <td>0.016280</td>\n",
       "      <td>0.007097</td>\n",
       "      <td>-0.068371</td>\n",
       "      <td>0.050936</td>\n",
       "      <td>...</td>\n",
       "      <td>0.037742</td>\n",
       "      <td>-0.022452</td>\n",
       "      <td>0.080056</td>\n",
       "      <td>0.028671</td>\n",
       "      <td>0.020483</td>\n",
       "      <td>0.058210</td>\n",
       "      <td>0.075229</td>\n",
       "      <td>-0.084503</td>\n",
       "      <td>0.046309</td>\n",
       "      <td>0.086032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MSSRKELANAIRALSMDAVQKAKSGHPGAPMGMADIAEVLWRDFLK...</td>\n",
       "      <td>-0.011090</td>\n",
       "      <td>0.016666</td>\n",
       "      <td>-0.012930</td>\n",
       "      <td>0.030634</td>\n",
       "      <td>-0.012921</td>\n",
       "      <td>-0.012898</td>\n",
       "      <td>0.045492</td>\n",
       "      <td>-0.175886</td>\n",
       "      <td>0.034107</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.067271</td>\n",
       "      <td>-0.067047</td>\n",
       "      <td>-0.062890</td>\n",
       "      <td>-0.037578</td>\n",
       "      <td>-0.029985</td>\n",
       "      <td>0.007193</td>\n",
       "      <td>0.019816</td>\n",
       "      <td>-0.198807</td>\n",
       "      <td>-0.022456</td>\n",
       "      <td>0.110925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MRPSLPPLLTCLLAALPALLSAGCSPATPSAHAAEPASRNVPFPYA...</td>\n",
       "      <td>-0.005208</td>\n",
       "      <td>-0.068409</td>\n",
       "      <td>0.039885</td>\n",
       "      <td>-0.062333</td>\n",
       "      <td>0.012764</td>\n",
       "      <td>-0.049863</td>\n",
       "      <td>0.015773</td>\n",
       "      <td>-0.156441</td>\n",
       "      <td>-0.020250</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.021826</td>\n",
       "      <td>-0.072720</td>\n",
       "      <td>-0.002612</td>\n",
       "      <td>-0.078776</td>\n",
       "      <td>-0.078234</td>\n",
       "      <td>0.016206</td>\n",
       "      <td>0.081448</td>\n",
       "      <td>-0.206387</td>\n",
       "      <td>0.055972</td>\n",
       "      <td>0.011760</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 1281 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    protein_sequence         0         1  \\\n",
       "0  MPVRRGHVAPQNTFLDTIIRKFEGQSRKFIIANARVENCAVIYCND...  0.015805 -0.033919   \n",
       "1  MEELQDDYEDMMEENLEQEEYEDPDIPESQMEEPAAHDTEATATDY... -0.017728  0.002291   \n",
       "2  MTDITANVVVSNPRPIFTESRSFKAVANGKIYIGQIDTDPVNPANQ...  0.016938  0.050288   \n",
       "3  MSSRKELANAIRALSMDAVQKAKSGHPGAPMGMADIAEVLWRDFLK... -0.011090  0.016666   \n",
       "4  MRPSLPPLLTCLLAALPALLSAGCSPATPSAHAAEPASRNVPFPYA... -0.005208 -0.068409   \n",
       "\n",
       "          2         3         4         5         6         7         8  ...  \\\n",
       "0  0.005356 -0.001142 -0.037829 -0.062076  0.034698  0.074689  0.025458  ...   \n",
       "1 -0.005282 -0.005080 -0.027136 -0.036133  0.065131  0.004717  0.007467  ...   \n",
       "2  0.001779 -0.010340 -0.100914  0.016280  0.007097 -0.068371  0.050936  ...   \n",
       "3 -0.012930  0.030634 -0.012921 -0.012898  0.045492 -0.175886  0.034107  ...   \n",
       "4  0.039885 -0.062333  0.012764 -0.049863  0.015773 -0.156441 -0.020250  ...   \n",
       "\n",
       "       1270      1271      1272      1273      1274      1275      1276  \\\n",
       "0  0.031189 -0.033546 -0.103467  0.056230 -0.052916 -0.003619 -0.020674   \n",
       "1  0.056245  0.033457 -0.124666 -0.020386  0.027567 -0.074638  0.048811   \n",
       "2  0.037742 -0.022452  0.080056  0.028671  0.020483  0.058210  0.075229   \n",
       "3 -0.067271 -0.067047 -0.062890 -0.037578 -0.029985  0.007193  0.019816   \n",
       "4 -0.021826 -0.072720 -0.002612 -0.078776 -0.078234  0.016206  0.081448   \n",
       "\n",
       "       1277      1278      1279  \n",
       "0 -0.058185  0.027794  0.081028  \n",
       "1 -0.047698  0.007801  0.049899  \n",
       "2 -0.084503  0.046309  0.086032  \n",
       "3 -0.198807 -0.022456  0.110925  \n",
       "4 -0.206387  0.055972  0.011760  \n",
       "\n",
       "[5 rows x 1281 columns]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wt_combine.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "wt_combine.rename(columns={'protein_sequence': 'wildtype'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_enzymes_wildtype_feature = df_combine[['wildtype']].merge(wt_combine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_enzymes_wildtype_feature.to_csv('all_enzymes_wildtype_feature.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get WT-mutant differences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# wt = pd.read_csv('all_enzymes_wildtype_feature.csv')\n",
    "# df_combine = pd.read_csv('all_enzymes_feature')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "wt = all_enzymes_wildtype_feature.iloc[:,1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [],
   "source": [
    "mutant = df_combine.iloc[:,-1280:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>1270</th>\n",
       "      <th>1271</th>\n",
       "      <th>1272</th>\n",
       "      <th>1273</th>\n",
       "      <th>1274</th>\n",
       "      <th>1275</th>\n",
       "      <th>1276</th>\n",
       "      <th>1277</th>\n",
       "      <th>1278</th>\n",
       "      <th>1279</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.015805</td>\n",
       "      <td>-0.033919</td>\n",
       "      <td>0.005356</td>\n",
       "      <td>-0.001142</td>\n",
       "      <td>-0.037829</td>\n",
       "      <td>-0.062076</td>\n",
       "      <td>0.034698</td>\n",
       "      <td>0.074689</td>\n",
       "      <td>0.025458</td>\n",
       "      <td>0.099601</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031189</td>\n",
       "      <td>-0.033546</td>\n",
       "      <td>-0.103467</td>\n",
       "      <td>0.056230</td>\n",
       "      <td>-0.052916</td>\n",
       "      <td>-0.003619</td>\n",
       "      <td>-0.020674</td>\n",
       "      <td>-0.058185</td>\n",
       "      <td>0.027794</td>\n",
       "      <td>0.081028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.015805</td>\n",
       "      <td>-0.033919</td>\n",
       "      <td>0.005356</td>\n",
       "      <td>-0.001142</td>\n",
       "      <td>-0.037829</td>\n",
       "      <td>-0.062076</td>\n",
       "      <td>0.034698</td>\n",
       "      <td>0.074689</td>\n",
       "      <td>0.025458</td>\n",
       "      <td>0.099601</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031189</td>\n",
       "      <td>-0.033546</td>\n",
       "      <td>-0.103467</td>\n",
       "      <td>0.056230</td>\n",
       "      <td>-0.052916</td>\n",
       "      <td>-0.003619</td>\n",
       "      <td>-0.020674</td>\n",
       "      <td>-0.058185</td>\n",
       "      <td>0.027794</td>\n",
       "      <td>0.081028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.015805</td>\n",
       "      <td>-0.033919</td>\n",
       "      <td>0.005356</td>\n",
       "      <td>-0.001142</td>\n",
       "      <td>-0.037829</td>\n",
       "      <td>-0.062076</td>\n",
       "      <td>0.034698</td>\n",
       "      <td>0.074689</td>\n",
       "      <td>0.025458</td>\n",
       "      <td>0.099601</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031189</td>\n",
       "      <td>-0.033546</td>\n",
       "      <td>-0.103467</td>\n",
       "      <td>0.056230</td>\n",
       "      <td>-0.052916</td>\n",
       "      <td>-0.003619</td>\n",
       "      <td>-0.020674</td>\n",
       "      <td>-0.058185</td>\n",
       "      <td>0.027794</td>\n",
       "      <td>0.081028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.015805</td>\n",
       "      <td>-0.033919</td>\n",
       "      <td>0.005356</td>\n",
       "      <td>-0.001142</td>\n",
       "      <td>-0.037829</td>\n",
       "      <td>-0.062076</td>\n",
       "      <td>0.034698</td>\n",
       "      <td>0.074689</td>\n",
       "      <td>0.025458</td>\n",
       "      <td>0.099601</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031189</td>\n",
       "      <td>-0.033546</td>\n",
       "      <td>-0.103467</td>\n",
       "      <td>0.056230</td>\n",
       "      <td>-0.052916</td>\n",
       "      <td>-0.003619</td>\n",
       "      <td>-0.020674</td>\n",
       "      <td>-0.058185</td>\n",
       "      <td>0.027794</td>\n",
       "      <td>0.081028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.015805</td>\n",
       "      <td>-0.033919</td>\n",
       "      <td>0.005356</td>\n",
       "      <td>-0.001142</td>\n",
       "      <td>-0.037829</td>\n",
       "      <td>-0.062076</td>\n",
       "      <td>0.034698</td>\n",
       "      <td>0.074689</td>\n",
       "      <td>0.025458</td>\n",
       "      <td>0.099601</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031189</td>\n",
       "      <td>-0.033546</td>\n",
       "      <td>-0.103467</td>\n",
       "      <td>0.056230</td>\n",
       "      <td>-0.052916</td>\n",
       "      <td>-0.003619</td>\n",
       "      <td>-0.020674</td>\n",
       "      <td>-0.058185</td>\n",
       "      <td>0.027794</td>\n",
       "      <td>0.081028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6586</th>\n",
       "      <td>0.056222</td>\n",
       "      <td>-0.019059</td>\n",
       "      <td>0.034438</td>\n",
       "      <td>0.042787</td>\n",
       "      <td>-0.081775</td>\n",
       "      <td>0.047643</td>\n",
       "      <td>0.119286</td>\n",
       "      <td>-0.011242</td>\n",
       "      <td>-0.062220</td>\n",
       "      <td>-0.031445</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063324</td>\n",
       "      <td>-0.103465</td>\n",
       "      <td>-0.039717</td>\n",
       "      <td>-0.029019</td>\n",
       "      <td>0.053409</td>\n",
       "      <td>-0.129892</td>\n",
       "      <td>0.118203</td>\n",
       "      <td>-0.196604</td>\n",
       "      <td>0.070822</td>\n",
       "      <td>0.114469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6587</th>\n",
       "      <td>0.056222</td>\n",
       "      <td>-0.019059</td>\n",
       "      <td>0.034438</td>\n",
       "      <td>0.042787</td>\n",
       "      <td>-0.081775</td>\n",
       "      <td>0.047643</td>\n",
       "      <td>0.119286</td>\n",
       "      <td>-0.011242</td>\n",
       "      <td>-0.062220</td>\n",
       "      <td>-0.031445</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063324</td>\n",
       "      <td>-0.103465</td>\n",
       "      <td>-0.039717</td>\n",
       "      <td>-0.029019</td>\n",
       "      <td>0.053409</td>\n",
       "      <td>-0.129892</td>\n",
       "      <td>0.118203</td>\n",
       "      <td>-0.196604</td>\n",
       "      <td>0.070822</td>\n",
       "      <td>0.114469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6588</th>\n",
       "      <td>0.056222</td>\n",
       "      <td>-0.019059</td>\n",
       "      <td>0.034438</td>\n",
       "      <td>0.042787</td>\n",
       "      <td>-0.081775</td>\n",
       "      <td>0.047643</td>\n",
       "      <td>0.119286</td>\n",
       "      <td>-0.011242</td>\n",
       "      <td>-0.062220</td>\n",
       "      <td>-0.031445</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063324</td>\n",
       "      <td>-0.103465</td>\n",
       "      <td>-0.039717</td>\n",
       "      <td>-0.029019</td>\n",
       "      <td>0.053409</td>\n",
       "      <td>-0.129892</td>\n",
       "      <td>0.118203</td>\n",
       "      <td>-0.196604</td>\n",
       "      <td>0.070822</td>\n",
       "      <td>0.114469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6589</th>\n",
       "      <td>0.056222</td>\n",
       "      <td>-0.019059</td>\n",
       "      <td>0.034438</td>\n",
       "      <td>0.042787</td>\n",
       "      <td>-0.081775</td>\n",
       "      <td>0.047643</td>\n",
       "      <td>0.119286</td>\n",
       "      <td>-0.011242</td>\n",
       "      <td>-0.062220</td>\n",
       "      <td>-0.031445</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063324</td>\n",
       "      <td>-0.103465</td>\n",
       "      <td>-0.039717</td>\n",
       "      <td>-0.029019</td>\n",
       "      <td>0.053409</td>\n",
       "      <td>-0.129892</td>\n",
       "      <td>0.118203</td>\n",
       "      <td>-0.196604</td>\n",
       "      <td>0.070822</td>\n",
       "      <td>0.114469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6590</th>\n",
       "      <td>0.056222</td>\n",
       "      <td>-0.019059</td>\n",
       "      <td>0.034438</td>\n",
       "      <td>0.042787</td>\n",
       "      <td>-0.081775</td>\n",
       "      <td>0.047643</td>\n",
       "      <td>0.119286</td>\n",
       "      <td>-0.011242</td>\n",
       "      <td>-0.062220</td>\n",
       "      <td>-0.031445</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063324</td>\n",
       "      <td>-0.103465</td>\n",
       "      <td>-0.039717</td>\n",
       "      <td>-0.029019</td>\n",
       "      <td>0.053409</td>\n",
       "      <td>-0.129892</td>\n",
       "      <td>0.118203</td>\n",
       "      <td>-0.196604</td>\n",
       "      <td>0.070822</td>\n",
       "      <td>0.114469</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6591 rows × 1280 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5         6     \\\n",
       "0     0.015805 -0.033919  0.005356 -0.001142 -0.037829 -0.062076  0.034698   \n",
       "1     0.015805 -0.033919  0.005356 -0.001142 -0.037829 -0.062076  0.034698   \n",
       "2     0.015805 -0.033919  0.005356 -0.001142 -0.037829 -0.062076  0.034698   \n",
       "3     0.015805 -0.033919  0.005356 -0.001142 -0.037829 -0.062076  0.034698   \n",
       "4     0.015805 -0.033919  0.005356 -0.001142 -0.037829 -0.062076  0.034698   \n",
       "...        ...       ...       ...       ...       ...       ...       ...   \n",
       "6586  0.056222 -0.019059  0.034438  0.042787 -0.081775  0.047643  0.119286   \n",
       "6587  0.056222 -0.019059  0.034438  0.042787 -0.081775  0.047643  0.119286   \n",
       "6588  0.056222 -0.019059  0.034438  0.042787 -0.081775  0.047643  0.119286   \n",
       "6589  0.056222 -0.019059  0.034438  0.042787 -0.081775  0.047643  0.119286   \n",
       "6590  0.056222 -0.019059  0.034438  0.042787 -0.081775  0.047643  0.119286   \n",
       "\n",
       "          7         8         9     ...      1270      1271      1272  \\\n",
       "0     0.074689  0.025458  0.099601  ...  0.031189 -0.033546 -0.103467   \n",
       "1     0.074689  0.025458  0.099601  ...  0.031189 -0.033546 -0.103467   \n",
       "2     0.074689  0.025458  0.099601  ...  0.031189 -0.033546 -0.103467   \n",
       "3     0.074689  0.025458  0.099601  ...  0.031189 -0.033546 -0.103467   \n",
       "4     0.074689  0.025458  0.099601  ...  0.031189 -0.033546 -0.103467   \n",
       "...        ...       ...       ...  ...       ...       ...       ...   \n",
       "6586 -0.011242 -0.062220 -0.031445  ...  0.063324 -0.103465 -0.039717   \n",
       "6587 -0.011242 -0.062220 -0.031445  ...  0.063324 -0.103465 -0.039717   \n",
       "6588 -0.011242 -0.062220 -0.031445  ...  0.063324 -0.103465 -0.039717   \n",
       "6589 -0.011242 -0.062220 -0.031445  ...  0.063324 -0.103465 -0.039717   \n",
       "6590 -0.011242 -0.062220 -0.031445  ...  0.063324 -0.103465 -0.039717   \n",
       "\n",
       "          1273      1274      1275      1276      1277      1278      1279  \n",
       "0     0.056230 -0.052916 -0.003619 -0.020674 -0.058185  0.027794  0.081028  \n",
       "1     0.056230 -0.052916 -0.003619 -0.020674 -0.058185  0.027794  0.081028  \n",
       "2     0.056230 -0.052916 -0.003619 -0.020674 -0.058185  0.027794  0.081028  \n",
       "3     0.056230 -0.052916 -0.003619 -0.020674 -0.058185  0.027794  0.081028  \n",
       "4     0.056230 -0.052916 -0.003619 -0.020674 -0.058185  0.027794  0.081028  \n",
       "...        ...       ...       ...       ...       ...       ...       ...  \n",
       "6586 -0.029019  0.053409 -0.129892  0.118203 -0.196604  0.070822  0.114469  \n",
       "6587 -0.029019  0.053409 -0.129892  0.118203 -0.196604  0.070822  0.114469  \n",
       "6588 -0.029019  0.053409 -0.129892  0.118203 -0.196604  0.070822  0.114469  \n",
       "6589 -0.029019  0.053409 -0.129892  0.118203 -0.196604  0.070822  0.114469  \n",
       "6590 -0.029019  0.053409 -0.129892  0.118203 -0.196604  0.070822  0.114469  \n",
       "\n",
       "[6591 rows x 1280 columns]"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wt.iloc[1,:].sort_values().reset_index(drop=True).plot.line();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wt.iloc[1,:].sort_values().plot.line();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mutant.iloc[1,:].plot.line();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "difference = (wt-mutant)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0.320376\n",
       "1       0.481710\n",
       "2       0.312745\n",
       "3      -0.172836\n",
       "4       0.414252\n",
       "          ...   \n",
       "6586    0.675470\n",
       "6587    1.490860\n",
       "6588   -4.357233\n",
       "6589   -2.425898\n",
       "6590   -2.844078\n",
       "Length: 6591, dtype: float32"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "difference.sum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_combine['difference'] = difference.sum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub = df_combine.query('split == \"test\"')[['seq_id','difference']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub.reset_index(inplace=True,drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub.rename(columns ={'difference':'tm'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub.to_csv('submission.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2413"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sub)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}