From 7fa3c4bfce11556b9c73f705f4d1b74447c54280 Mon Sep 17 00:00:00 2001 From: Florencia Caro <154555752+florenciacaromartinez@users.noreply.github.com> Date: Sun, 18 Feb 2024 14:07:11 -0300 Subject: [PATCH] Delete Implementation Example 2/Implementation Example 2.ipynb --- .../Implementation Example 2.ipynb | 12419 ---------------- 1 file changed, 12419 deletions(-) delete mode 100644 Implementation Example 2/Implementation Example 2.ipynb diff --git a/Implementation Example 2/Implementation Example 2.ipynb b/Implementation Example 2/Implementation Example 2.ipynb deleted file mode 100644 index 6c326cd..0000000 --- a/Implementation Example 2/Implementation Example 2.ipynb +++ /dev/null @@ -1,12419 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Bio2Py: Implementation Example 2\n", - "### Evaluation of Chemical Consumption for Physicochemical Phosphorus Removal" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The following simple example illustrates how the user can combine Bio2Py auxiliary functions to automate diffrent actions in BioWin that are not defined on first hand as main functions in Bio2Py. It also demonstrates how Bio2Py can enhance data acquisition processes. \n", - "\n", - "In this example, we explore a physicochemical phosphorus removal system using FeCl3, within a specified influent. NaOH is used for adjusting pH.\n", - "The goal was to generate response surfaces for effluent TP and pH in relation to FeCl3 and NaOH consumption. This analysis could assist in determining the optimal combination of chemicals for influents with particular characteristics. \n", - "\n", - "***Steps***\n", - "1. Define a range of FeCl3 and NaOH flow rates to test.\n", - "2. Randomly select N (FeCl3, NaOH) pairs within these ranges.\n", - "3. Run N simulations in BioWin for the correspondig (FeCl3, NaOH) pais. --> This can be automated using Bio2Py auxiliary functions!\n", - "4. Save simulation results for each (FeCl3, NaOH) pair. --> This can be automated using Bio2Py auxiliary functions!\n", - "5. Visualize the results to understand how P and pH vary with FeCl3 and NaOH.\n", - "\n", - "***Benefits of Bio2Py***\n", - "\n", - "Bio2Py simplifies the execution of numerous simulations. In this example, 300 simulations were conducted by the API, enabling the generation of response surfaces for effluent TP and pH regarding FeCl3 and NaOH consumption. Analysis of these surfaces shows that various combinations of FeCl3 and NaOH achieve comparable levels of P removal. other criteria such as minimizing costs, could be considered to determine the most suitable chemical consumption for the effluent plant.\n", - "Manually performing these simulations would be laborious and prone to data transfer errors.\n", - "\n", - "This example utilizes matplotlib and plotly to visualize BioWin simulation results. Users can install these libraries using pip:\n", - " \n", - " pip install set_matplotlib\n", - " pip install plotly\n", - " pip install nbformat" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Remember**\n", - "\n", - "Bio2Py automatices the process of loading influent data, changing parameters and running simulations in BioWin. It is necessary to set the system configuration layout, project options, unit system, report options, etc before using Bio2Py. \n", - "\n", - "In order to use Bio2Py, **BioWin simulation window must be fully visible**, as Bio2Py relies on image recognition to perform its tasks. \n", - "\n", - "Placing BioWin window on the left side of the screen is recomended. \n", - "\n", - "**Before using Bio2Py**:\n", - "- Open BioWin simulation file --> Implementation Example 2 (in this case)\n", - "- Set the zoom to 100% on BioWin window.\n", - "- Manually run a single flow balance and steady state/dynamic simulation. Check for any warning messages that could interrupt Bio2Py process. If necessary, the user may consider disabling BioWin alarms to prevent Bio2Py interruption. \n", - "- Choose locations (if applicable): \n", - " - For saving BioWin generated reports with simulation results (File -> Report to Excel (TM) -> Choose directory).\n", - " - From where variable influent data will be loaded (Influent icon -> Open file -> Choose directory)(***). Only necessary if running simulations with variable influent. Choose the same filepath arg .\n", - "- Place BioWin simulation window on the left side of the screen. \n", - "- Make sure influent icon is visible. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Load libraries and set the environment" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import Bio2Py\n", - "import pandas as pd\n", - "import pyautogui\n", - "import time\n", - "import pyperclip\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "filepath=r\"C:\\Users\\Usuario\\OneDrive - Facultad de Ingeniería\\Maestría\\Biowin - python\\Case study\\Implementation example 2\" #change" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "simulation_window,influen_window=Bio2Py.setting_the_environment()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Define functions for changing FeCl3 flow and NaOH flow \n", - "\n", - "Use Bio2Py auxiliary functions\n", - "\n", - "**Important:**\n", - "Make sure you have dowloaded all the images contained in the 'Implementation Example 2' and save them in the same folder as this notebook." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def load_FeCl3 (flow):\n", - " \n", - " decimal_separator=Bio2Py.get_decimal_separator()\n", - "\n", - " pyautogui.doubleClick(pyautogui.locateCenterOnScreen('FeCl3.PNG',confidence=0.7, grayscale=True))\n", - " time.sleep(2)\n", - " pyautogui.click(pyautogui.locateCenterOnScreen('edit.PNG',confidence=0.7, grayscale=True))\n", - " time.sleep(2)\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('enter')\n", - " \n", - " if decimal_separator == ',':\n", - " formatted_value = str(flow).replace('.', ',') \n", - " pyautogui.write(str(formatted_value), interval=0.05)\n", - " elif decimal_separator == '.':\n", - " pyautogui.write(str(flow), interval=0.05)\n", - " else: \n", - " print('Error while getting decimal separator') \n", - " \n", - " pyautogui.press('\\t')\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('enter')\n", - " time.sleep(1)\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('enter')\n", - "\n", - "def load_influent_state_variable(flow):\n", - " \n", - " decimal_separator=Bio2Py.get_decimal_separator()\n", - "\n", - " pyautogui.doubleClick(pyautogui.locateCenterOnScreen('NaOH_5N.PNG',confidence=0.7, grayscale=True))\n", - " time.sleep(2.5)\n", - " pyautogui.click(pyautogui.locateCenterOnScreen('edit.PNG',confidence=0.65, grayscale=True))\n", - " time.sleep(2)\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('enter')\n", - " \n", - " if decimal_separator == ',':\n", - " formatted_value = str(flow).replace('.', ',') \n", - " pyautogui.write(str(formatted_value), interval=0.05)\n", - " elif decimal_separator == '.':\n", - " pyautogui.write(str(flow), interval=0.05)\n", - " else: \n", - " print('Error while getting decimal separator') \n", - "\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('enter')\n", - " time.sleep(1)\n", - " pyautogui.press('\\t')\n", - " pyautogui.press('enter')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Generating Random FeCl3 and NaOH Pairs\n", - "\n", - "1. Define a range of FeCl3 and NaOH flow rates to test \n", - "2. Randomly select N (FeCl3, NaOH) pairs within these ranges." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "random_state=55\n", - "n_points= 370\n", - "x=np.random.randint(400, 1200, n_points)\n", - "y=np.random.randint(0, 1750, n_points)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Run simulations in BioWin and save results using Bio2Py" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "00:02:13.062: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 799:\n", - "NaOH (L/d): 1200\n", - "TP (mg-P/L): 4.03\n", - "pH: 6.73\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "00:02:44.415: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 919:\n", - "NaOH (L/d): 1042\n", - "TP (mg-P/L): 3.57\n", - "pH: 5.46\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "00:03:15.578: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 1040:\n", - "NaOH (L/d): 574\n", - "TP (mg-P/L): 23.74\n", - "pH: 2.47\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "00:03:46.752: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 1010:\n", - "NaOH (L/d): 111\n", - "TP (mg-P/L): 24.49\n", - "pH: 2.29\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "00:04:17.971: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 565:\n", - "NaOH (L/d): 1283\n", - "TP (mg-P/L): 20.69\n", - "pH: 8.88\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "00:04:49.208: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - 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"name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 612:\n", - "NaOH (L/d): 1525\n", - "TP (mg-P/L): 24.28\n", - "pH: 9.43\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "03:46:39.513: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 1170:\n", - "NaOH (L/d): 1619\n", - "TP (mg-P/L): 3.43\n", - "pH: 5.75\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "03:47:29.358: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 429:\n", - "NaOH (L/d): 1303\n", - "TP (mg-P/L): 24.56\n", - "pH: 9.89\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "03:48:20.948: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 557:\n", - "NaOH (L/d): 1003\n", - "TP (mg-P/L): 8.29\n", - "pH: 7.78\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "03:49:13.056: Steady State\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FeCl3 (L/d): 1034:\n", - "NaOH (L/d): 606\n", - "TP (mg-P/L): 23.5\n", - "pH: 2.5\n", - "FeCl3 (L/d): 1141:\n", - "NaOH (L/d): 906\n", - "TP (mg-P/L): 23.5\n", - "pH: 2.5\n" - ] - }, - { - "ename": "ImageNotFoundException", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mImageNotFoundException\u001b[0m Traceback (most recent call last)", - "File \u001b[1;32mc:\\Users\\Usuario\\anaconda3\\envs\\data2\\Lib\\site-packages\\pyautogui\\__init__.py:172\u001b[0m, in \u001b[0;36mraisePyAutoGUIImageNotFoundException..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 171\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 172\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mwrappedFunction\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 173\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m pyscreeze\u001b[38;5;241m.\u001b[39mImageNotFoundException:\n", - "File \u001b[1;32mc:\\Users\\Usuario\\anaconda3\\envs\\data2\\Lib\\site-packages\\pyautogui\\__init__.py:204\u001b[0m, in \u001b[0;36mlocateCenterOnScreen\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 202\u001b[0m \u001b[38;5;129m@raisePyAutoGUIImageNotFoundException\u001b[39m\n\u001b[0;32m 203\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlocateCenterOnScreen\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 204\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpyscreeze\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlocateCenterOnScreen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[1;32mc:\\Users\\Usuario\\anaconda3\\envs\\data2\\Lib\\site-packages\\pyscreeze\\__init__.py:447\u001b[0m, in \u001b[0;36mlocateCenterOnScreen\u001b[1;34m(image, **kwargs)\u001b[0m\n\u001b[0;32m 444\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m 445\u001b[0m \u001b[38;5;124;03mTODO\u001b[39;00m\n\u001b[0;32m 446\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m--> 447\u001b[0m coords \u001b[38;5;241m=\u001b[39m \u001b[43mlocateOnScreen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 448\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m coords \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "File \u001b[1;32mc:\\Users\\Usuario\\anaconda3\\envs\\data2\\Lib\\site-packages\\pyscreeze\\__init__.py:405\u001b[0m, in \u001b[0;36mlocateOnScreen\u001b[1;34m(image, minSearchTime, **kwargs)\u001b[0m\n\u001b[0;32m 404\u001b[0m screenshotIm \u001b[38;5;241m=\u001b[39m screenshot(region\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m--> 405\u001b[0m retVal \u001b[38;5;241m=\u001b[39m \u001b[43mlocate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mscreenshotIm\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 406\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n", - "File \u001b[1;32mc:\\Users\\Usuario\\anaconda3\\envs\\data2\\Lib\\site-packages\\pyscreeze\\__init__.py:383\u001b[0m, in \u001b[0;36mlocate\u001b[1;34m(needleImage, haystackImage, **kwargs)\u001b[0m\n\u001b[0;32m 382\u001b[0m kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlimit\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m--> 383\u001b[0m points \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mlocateAll\u001b[49m\u001b[43m(\u001b[49m\u001b[43mneedleImage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhaystackImage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 384\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(points) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n", - "File \u001b[1;32mc:\\Users\\Usuario\\anaconda3\\envs\\data2\\Lib\\site-packages\\pyscreeze\\__init__.py:257\u001b[0m, in \u001b[0;36m_locateAll_opencv\u001b[1;34m(needleImage, haystackImage, grayscale, limit, region, step, confidence)\u001b[0m\n\u001b[0;32m 256\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m USE_IMAGE_NOT_FOUND_EXCEPTION:\n\u001b[1;32m--> 257\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ImageNotFoundException(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCould not locate the image (highest confidence = \u001b[39m\u001b[38;5;132;01m%.3f\u001b[39;00m\u001b[38;5;124m)\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;241m%\u001b[39m result\u001b[38;5;241m.\u001b[39mmax())\n\u001b[0;32m 258\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", - "\u001b[1;31mImageNotFoundException\u001b[0m: Could not locate the image (highest confidence = 0.436)", - "\nDuring handling of the above exception, another exception occurred:\n", - "\u001b[1;31mImageNotFoundException\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[8], line 7\u001b[0m\n\u001b[0;32m 5\u001b[0m y_2\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mrandint(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1750\u001b[39m, n_puntos)\n\u001b[0;32m 6\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m n \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(n_puntos):\n\u001b[1;32m----> 7\u001b[0m \u001b[43mload_FeCl3\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx_2\u001b[49m\u001b[43m[\u001b[49m\u001b[43mn\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 8\u001b[0m load_influent_state_variable(y_2[n])\n\u001b[0;32m 9\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(\u001b[38;5;241m1\u001b[39m)\n", - "Cell \u001b[1;32mIn[4], line 2\u001b[0m, in \u001b[0;36mload_FeCl3\u001b[1;34m(flow)\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mload_FeCl3\u001b[39m (flow):\n\u001b[1;32m----> 2\u001b[0m pyautogui\u001b[38;5;241m.\u001b[39mdoubleClick(\u001b[43mpyautogui\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlocateCenterOnScreen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mFeCl3.PNG\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43mconfidence\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.7\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgrayscale\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m)\n\u001b[0;32m 3\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(\u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m 4\u001b[0m pyautogui\u001b[38;5;241m.\u001b[39mclick(pyautogui\u001b[38;5;241m.\u001b[39mlocateCenterOnScreen(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124medit.PNG\u001b[39m\u001b[38;5;124m'\u001b[39m,confidence\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.7\u001b[39m, grayscale\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m))\n", - "File \u001b[1;32mc:\\Users\\Usuario\\anaconda3\\envs\\data2\\Lib\\site-packages\\pyautogui\\__init__.py:174\u001b[0m, in \u001b[0;36mraisePyAutoGUIImageNotFoundException..wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 172\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wrappedFunction(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m 173\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m pyscreeze\u001b[38;5;241m.\u001b[39mImageNotFoundException:\n\u001b[1;32m--> 174\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m ImageNotFoundException\n", - "\u001b[1;31mImageNotFoundException\u001b[0m: " - ] - } - ], - "source": [ - "results=pd.DataFrame([])\n", - "\n", - "for n in range(n_points):\n", - " #Load chemical flows \n", - " load_FeCl3(x[n])\n", - " time.sleep(0.5)\n", - " load_influent_state_variable(y[n])\n", - " time.sleep(1)\n", - " \n", - " #Run steady state simulation\n", - " Bio2Py.steady_state('None', 'current',60) \n", - " \n", - " #Save results\n", - " time.sleep(1)\n", - " Bio2Py.save_results('table','P',0,filepath)\n", - " effluent=pd.read_csv('P_0.csv')\n", - " TP_effluent=effluent.iloc[0,1]\n", - " pH_effluent=effluent.iloc[0,3]\n", - " results_iteration=effluent\n", - " results_iteration['FeCl3(L/d)']=x[n]\n", - " results_iteration['NaOH(L/d)']=y[n]\n", - " results = pd.concat([results, results_iteration], axis=0)\n", - " \n", - " print(f'FeCl3 (L/d): {x[n]}:')\n", - " print(f'NaOH (L/d): {y[n]}')\n", - " print(f'TP (mg-P/L): {TP_effluent}')\n", - " print(f'pH: {pH_effluent}')\n", - " \n", - " time.sleep(1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#results.to_csv('results_1.csv', index=False)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## If the user prefers not to execute all iterations, they have the option to load our results instead:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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ElementsP - Total P [mgP/L]P - Soluble PO4-P [mgP/L]pH []COD - Total [mg/L]N - Total Kjeldahl Nitrogen [mgN/L]Total suspended solids [mg/L]FeCl3(L/d)NaOH(L/d)
0Effluent4.962.146.9656.333.0754.829441600
1Effluent4.581.725.7256.333.0744.98680589
2Effluent6.233.563.3056.333.0755.799791006
3Effluent14.9613.282.6456.333.0747.62841357
4Effluent24.5623.969.6256.333.0735.916261616
..............................
365Effluent5.843.127.0156.333.0744.546801072
366Effluent11.559.482.7856.333.0760.0311371101
367Effluent4.091.185.9856.333.0755.319491218
368Effluent19.6118.452.4156.333.0746.1884532
369Effluent4.571.713.8556.333.0757.2310031130
\n", - "

370 rows × 9 columns

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"365 44.54 680 1072 \n", - "366 60.03 1137 1101 \n", - "367 55.31 949 1218 \n", - "368 46.18 845 32 \n", - "369 57.23 1003 1130 \n", - "\n", - "[370 rows x 9 columns]" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "results=pd.read_csv('results_1.csv')\n", - "results" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plotting the results" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "marker": { - "size": 5 - }, - "mode": "markers", - "type": "scatter3d", - "x": [ - 944, - 680, - 979, - 841, - 626, - 447, - 978, - 1087, - 406, - 849, - 714, - 876, - 603, - 850, - 664, - 1141, - 965, - 1174, - 852, - 814, - 691, - 798, - 1084, - 845, - 705, - 1162, - 848, - 749, - 1164, - 1097, - 672, - 444, - 606, - 1000, - 959, - 706, - 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"\n", - "# Show the plot\n", - "fig.show()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Identify the FeCl3 and NaOH combinations that ensure compliance with local regulatory standards for effluent quality: \n", - "\n", - "- Filter rows where the 'TP' (Total Phosphorus) is less than 5 and the 'pH' is greater than or equal to 6. \n", - "- Note that other parameters such as NTK and DQO already meet the local regulatory constraints (*).\n", - "\n", - "(*) Decreto 253/979. Uruguay, 1979." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "compliant_effluent_df =results[(results['P - Total P [mgP/L]'] < 5) & (results['pH []'] >= 6)]" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "marker": { - "size": 5 - }, - "mode": "markers", - "name": "Effluent", - "type": "scatter3d", - "x": [ - 944, - 680, - 979, - 841, - 626, - 447, - 978, - 1087, - 406, - 849, - 714, - 876, - 603, - 850, - 664, - 1141, - 965, - 1174, - 852, - 814, - 691, - 798, - 1084, - 845, - 705, - 1162, - 848, - 749, - 1164, - 1097, - 672, - 444, - 606, - 1000, - 959, - 706, - 977, - 407, - 925, - 709, - 1080, - 481, - 585, - 1132, - 802, - 512, - 991, - 606, - 1006, - 899, - 781, - 427, - 786, - 1167, - 998, - 1195, - 1112, - 715, - 476, - 573, - 1105, - 810, - 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"gridcolor": "white", - "gridwidth": 2, - "linecolor": "white", - "showbackground": true, - "ticks": "", - "zerolinecolor": "white" - }, - "zaxis": { - "backgroundcolor": "#E5ECF6", - "gridcolor": "white", - "gridwidth": 2, - "linecolor": "white", - "showbackground": true, - "ticks": "", - "zerolinecolor": "white" - } - }, - "shapedefaults": { - "line": { - "color": "#2a3f5f" - } - }, - "ternary": { - "aaxis": { - "gridcolor": "white", - "linecolor": "white", - "ticks": "" - }, - "baxis": { - "gridcolor": "white", - "linecolor": "white", - "ticks": "" - }, - "bgcolor": "#E5ECF6", - "caxis": { - "gridcolor": "white", - "linecolor": "white", - "ticks": "" - } - }, - "title": { - "x": 0.05 - }, - "xaxis": { - "automargin": true, - "gridcolor": "white", - "linecolor": "white", - "ticks": "", - "title": { - "standoff": 15 - }, - "zerolinecolor": "white", - "zerolinewidth": 2 - }, - "yaxis": { - "automargin": true, - "gridcolor": "white", - "linecolor": "white", - "ticks": "", - "title": { - "standoff": 15 - }, - "zerolinecolor": "white", - "zerolinewidth": 2 - } - } - }, - "title": { - "text": "Effluent TP as a function of FeCl3 and NaOH consumption" - }, - "width": 800 - } - } - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "x = results['FeCl3(L/d)']\n", - "y = results['NaOH(L/d)']\n", - "z = results['P - Total P [mgP/L]']\n", - "\n", - "a = compliant_effluent_df['FeCl3(L/d)']\n", - "b = compliant_effluent_df['NaOH(L/d)']\n", - "c = compliant_effluent_df['P - Total P [mgP/L]']\n", - "\n", - "\n", - "fig=go.Figure()\n", - "fig.add_trace(go.Scatter3d(x=x, y=y, z=z, mode='markers',\n", - " marker=dict(size=5),name='Effluent'))\n", - "\n", - "fig.add_trace(go.Scatter3d(x=a, y=b, z=c, mode='markers',\n", - " marker=dict(size=5),name='Compliant effluent'))\n", - "\n", - "fig.update_layout(title='Effluent TP as a function of FeCl3 and NaOH consumption',\n", - " scene=dict(\n", - " xaxis_title='FeCl3 (L/d)',\n", - " yaxis_title='NaOH (L/d)',\n", - " zaxis_title='TP (mg-P/L)'\n", - " ))\n", - "fig.update_layout(width=800, height=600)\n", - "\n", - "fig.show()\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "With the presented plot we can observe that different combinations of FeCl3 and NaOH can render the effluent compliant with local regulations. Additionally, other criteria, such as minimizing costs, could be considered to determine the most suitable chemical consumption for the effluent plant.\n", - "\n", - "Performing 370 simulations manually may seem daunting, but it can be easily achieved with Bio2Py." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "biowin", - "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": "3.12.0" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -}