From 6d8199b0839b50a917f565a60fcc60986ad5a796 Mon Sep 17 00:00:00 2001
From: romainsacchi <r_s@me.com>
Date: Tue, 28 Jan 2025 19:24:35 +0200
Subject: [PATCH] Add notebook to use premise matrices

---
 dev/Untitled1.ipynb                           | 496 ++++++++++++++++-
 .../example_matrices_to_bw_processing.ipynb   | 504 ++++++++++++++++++
 .../examples user-defined scenarios.ipynb     |   2 +-
 3 files changed, 986 insertions(+), 16 deletions(-)
 create mode 100644 examples/example_matrices_to_bw_processing.ipynb

diff --git a/dev/Untitled1.ipynb b/dev/Untitled1.ipynb
index ad0f834e..73484e97 100644
--- a/dev/Untitled1.ipynb
+++ b/dev/Untitled1.ipynb
@@ -5,15 +5,7 @@
    "execution_count": 1,
    "id": "5018b7ee-0169-49d7-9455-2f1aea562e9e",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "USER_DATA_BASE_DIR: test\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from premise import *\n",
     "from datapackage import Package\n",
@@ -50,7 +42,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "premise v.(2, 2, 2)\n",
+      "premise v.(2, 3, 0, 'dev0')\n",
       "+------------------------------------------------------------------+\n",
       "| Warning                                                          |\n",
       "+------------------------------------------------------------------+\n",
@@ -85,7 +77,432 @@
       "Hide these messages?\n",
       "NewDatabase(..., quiet=True)\n",
       "- Extracting source database\n",
+      "Cannot find cached database. Will create one now for next time...\n",
+      "Getting activity data\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████| 23523/23523 [00:00<00:00, 385863.57it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Adding exchange data to activities\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|████████████████████████████████| 743409/743409 [00:30<00:00, 24109.44it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Filling out exchange data\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|███████████████████████████████████| 23523/23523 [00:02<00:00, 8119.15it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Set missing location of datasets to global scope.\n",
+      "Set missing location of production exchanges to scope of dataset.\n",
+      "Correct missing location of technosphere exchanges.\n",
+      "Correct missing flow categories for biosphere exchanges\n",
+      "Remove empty exchanges.\n",
+      "Remove uncertainty data.\n",
       "- Extracting inventories\n",
+      "Cannot find cached inventories. Will create them now for next time...\n",
+      "Importing default inventories...\n",
+      "\n",
+      "Extracted 1 worksheets in 0.12 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 4 worksheets in 0.16 seconds\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 7 worksheets in 0.02 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.03 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.03 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 2 worksheets in 0.02 seconds\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.27 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "The following datasets to import already exist in the source database. They will not be imported\n",
+      "+--------------------------------+--------------------------------+----------+-------------+\n",
+      "|              Name              |       Reference product        | Location |     File    |\n",
+      "+--------------------------------+--------------------------------+----------+-------------+\n",
+      "| fluorspar production, 97% puri |     fluorspar, 97% purity      |   GLO    | lci-PV.xlsx |\n",
+      "| metallization paste production | metallization paste, back side |   RER    | lci-PV.xlsx |\n",
+      "| metallization paste production | metallization paste, back side |   RER    | lci-PV.xlsx |\n",
+      "| metallization paste production | metallization paste, front sid |   RER    | lci-PV.xlsx |\n",
+      "| photovoltaic module production | photovoltaic module, building- |   RER    | lci-PV.xlsx |\n",
+      "| photovoltaic module production | photovoltaic module, building- |   RER    | lci-PV.xlsx |\n",
+      "| photovoltaic mounting system p | photovoltaic mounting system,  |   RER    | lci-PV.xlsx |\n",
+      "| photovoltaic mounting system p | photovoltaic mounting system,  |   RER    | lci-PV.xlsx |\n",
+      "| photovoltaic mounting system p | photovoltaic mounting system,  |   RER    | lci-PV.xlsx |\n",
+      "| photovoltaic panel factory con |   photovoltaic panel factory   |   GLO    | lci-PV.xlsx |\n",
+      "|  polyvinylfluoride production  |       polyvinylfluoride        |    US    | lci-PV.xlsx |\n",
+      "| polyvinylfluoride production,  | polyvinylfluoride, dispersion  |    US    | lci-PV.xlsx |\n",
+      "| polyvinylfluoride, film produc |    polyvinylfluoride, film     |    US    | lci-PV.xlsx |\n",
+      "| silicon production, metallurgi |  silicon, metallurgical grade  |    NO    | lci-PV.xlsx |\n",
+      "|   vinyl fluoride production    |         vinyl fluoride         |    US    | lci-PV.xlsx |\n",
+      "|   wafer factory construction   |         wafer factory          |    DE    | lci-PV.xlsx |\n",
+      "+--------------------------------+--------------------------------+----------+-------------+\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.04 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "The following datasets to import already exist in the source database. They will not be imported\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "|              Name              |       Reference product        | Location |              File              |\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "| carbon dioxide, captured at ce | carbon dioxide, captured and r |   RER    | lci-synfuels-from-methanol-fro |\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "Extracted 1 worksheets in 0.00 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "The following datasets to import already exist in the source database. They will not be imported\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "|              Name              |       Reference product        | Location |              File              |\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "| hydrogen production, coal gasi | hydrogen, gaseous, low pressur |   RoW    | lci-hydrogen-coal-gasification |\n",
+      "| methanol production, coal gasi |            methanol            |   RoW    | lci-hydrogen-coal-gasification |\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "Extracted 1 worksheets in 0.00 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "The following datasets to import already exist in the source database. They will not be imported\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "|              Name              |       Reference product        | Location |              File              |\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "| hydrogen production, steam met | hydrogen, gaseous, low pressur |   RER    | lci-hydrogen-smr-atr-natgas.xl |\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.00 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "The following datasets to import already exist in the source database. They will not be imported\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "|              Name              |       Reference product        | Location |              File              |\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "| methanol production facility,  | methanol production facility,  |   RER    | lci-synfuels-from-methanol-fro |\n",
+      "+--------------------------------+--------------------------------+----------+--------------------------------+\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.00 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 5 worksheets in 0.13 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.03 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.00 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.07 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.04 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.01 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 19 worksheets in 0.28 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 1.54 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.15 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.73 seconds\n",
+      "Migrating to 3.8 first\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.03 seconds\n",
+      "Applying strategy: migrate_datasets\n",
+      "Applying strategy: migrate_exchanges\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Extracted 1 worksheets in 0.02 seconds\n",
+      "Data cached. It is advised to restart your workflow at this point.\n",
+      "This allows premise to use the cached data instead, which results in\n",
+      "a faster workflow.\n",
       "- Fetching IAM data\n",
       "Done!\n"
      ]
@@ -119,7 +536,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "0c80994c-cbac-4143-81ee-1de1531a6f95",
    "metadata": {},
    "outputs": [
@@ -129,6 +546,40 @@
      "text": [
       "Processing scenarios for all sectors:   0%|     | 0/1 [00:00<?, ?it/s]"
      ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Warning: No activities found for Gas ST -- revise mapping.\n",
+      "Warning: No activities found for CON_LOSSHF -- revise mapping.\n",
+      "Warning: No activities found for PP_ENGGAS -- revise mapping.\n",
+      "Warning: No activities found for PP_MOD_CCSBIOG -- revise mapping.\n",
+      "Warning: No activities found for PP_MOD_CCSHC1 -- revise mapping.\n",
+      "Warning: No activities found for TRA_OT_AIRGSL -- revise mapping.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing scenarios for all sectors: 100%|█| 1/1 [02:35<00:00, 155.23"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done!\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
     }
    ],
    "source": [
@@ -137,12 +588,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "5e8438a5-44d8-46f7-8fda-a85a35c52912",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Write new database(s) to matrix.\n",
+      "Running all checks...\n",
+      "Minor anomalies found: check the change report.\n",
+      "Matrices saved in /Users/romain/GitHub/premise/dev/export/remind/SSP2-NPi/2050.\n",
+      "Generate scenario report.\n",
+      "Report saved under /Users/romain/GitHub/premise/dev/export/scenario_report.\n",
+      "Generate change report.\n",
+      "Report saved under /Users/romain/GitHub/premise/dev.\n"
+     ]
+    }
+   ],
    "source": [
-    "ndb.write_db_to_brightway()"
+    "ndb.write_db_to_matrices()"
    ]
   },
   {
@@ -3456,7 +3922,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.11.11"
   }
  },
  "nbformat": 4,
diff --git a/examples/example_matrices_to_bw_processing.ipynb b/examples/example_matrices_to_bw_processing.ipynb
new file mode 100644
index 00000000..de0248f5
--- /dev/null
+++ b/examples/example_matrices_to_bw_processing.ipynb
@@ -0,0 +1,504 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3cc7b8fb-fa82-40ac-9921-c6a0c8200847",
+   "metadata": {},
+   "source": [
+    "## Examples on how to use premise's matrices with `bw_processing`\n",
+    "\n",
+    "Author: [romainsacchi](https://github.com/romainsacchi)\n",
+    "\n",
+    "This notebook show exmaples on how to compute LCA scores using the matrices produced by `premise` via `.export_db_to_matrices()`, together with the matrix processing library `bw_processing` and `bw2calc`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0581aa10-9841-46ec-9535-7fd6bf60eb08",
+   "metadata": {},
+   "source": [
+    "## Example of a regular LCA using premise's matrices"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "6b4ef7cd-2b66-430c-be86-4f575240017d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import bw2calc as bc\n",
+    "from bw2calc import __version__ as bw2calc_version\n",
+    "import bw_processing as bwp\n",
+    "from pathlib import Path\n",
+    "import csv\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "8c7ebfe5-2fcc-4a92-aa7d-291dda9aab85",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# we fetch filepaths to A and B matrices and indices' list.\n",
+    "fp_root=Path(\"/Users/romain/GitHub/premise/dev/export/remind/SSP2-NPi/2050\")\n",
+    "fp_A_idx = fp_root / \"A_matrix_index.csv\"\n",
+    "fp_B_idx = fp_root / \"B_matrix_index.csv\"\n",
+    "fp_A_matrix = fp_root / \"A_matrix.csv\"\n",
+    "fp_B_matrix = fp_root / \"B_matrix.csv\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "ad3e6f92-b3d4-4dec-a0b4-d62b22757bb5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def read_indices_csv(file_path: Path) -> dict:\n",
+    "    \"\"\"\n",
+    "    Reads a CSV file and returns its contents as a dictionary.\n",
+    "\n",
+    "    Each row of the CSV file is expected to contain four string values followed by an index.\n",
+    "    These are stored in the dictionary as a tuple of the four strings mapped to the index.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    indices = dict()\n",
+    "    with open(file_path, encoding=\"utf-8\") as read_obj:\n",
+    "        csv_reader = csv.reader(read_obj, delimiter=\";\")\n",
+    "        next(csv_reader, None)  # skip the headers\n",
+    "        for row in csv_reader:\n",
+    "            indices[(row[0], row[1], row[2], row[3])] = int(row[4])\n",
+    "    # remove any unicode characters\n",
+    "    indices = {tuple([str(x) for x in k]): v for k, v in indices.items()}\n",
+    "    return indices\n",
+    "\n",
+    "A_idx = read_indices_csv(fp_A_idx)\n",
+    "B_idx = read_indices_csv(fp_B_idx)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "13d71880-07d5-4eeb-ac99-097fec366a50",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def build_array(fp):\n",
+    "    array = np.genfromtxt(fp, delimiter=\";\", skip_header=1)\n",
+    "    \n",
+    "    # give `indices_array` a list of tuples of indices\n",
+    "    indices_array = np.array(\n",
+    "        list(zip(array[:, 1].astype(int), array[:, 0].astype(int))),\n",
+    "        dtype=bwp.INDICES_DTYPE,\n",
+    "    )\n",
+    "    \n",
+    "    data_array = array[:, 2]\n",
+    "    \n",
+    "    # make a boolean scalar array to store the sign of the data\n",
+    "    flip_array = array[:, -1].astype(bool)\n",
+    "    \n",
+    "    distributions_array = np.array(\n",
+    "        list(\n",
+    "            zip(\n",
+    "                array[:, 3].astype(int),  # uncertainty type\n",
+    "                array[:, 4].astype(float),  # loc\n",
+    "                array[:, 5].astype(float),  # scale\n",
+    "                array[:, 6].astype(float),  # shape\n",
+    "                array[:, 7].astype(float),  # minimum\n",
+    "                array[:, 8].astype(float),  # maximum\n",
+    "                array[:, 9].astype(bool),  # negative\n",
+    "            )\n",
+    "        ),\n",
+    "        dtype=bwp.UNCERTAINTY_DTYPE,\n",
+    "    )\n",
+    "    return indices_array, data_array, flip_array, distributions_array"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "795016db-8704-4db7-a750-84ac08b4d6cb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# we create a static data package\n",
+    "dp = bwp.create_datapackage()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "92a2483e-6e81-4c42-8298-5aa526eedf67",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "indices_array, data_array, flip_array, _ = build_array(fp_A_matrix)\n",
+    "\n",
+    "# we add the technosphere vector\n",
+    "dp.add_persistent_vector(\n",
+    "    matrix=\"technosphere_matrix\",\n",
+    "    indices_array=indices_array,\n",
+    "    data_array=data_array,\n",
+    "    flip_array=flip_array,\n",
+    "    #distributions_array=distributions_array,\n",
+    ")\n",
+    "\n",
+    "indices_array, data_array, _, _ = build_array(fp_B_matrix)\n",
+    "\n",
+    "# we add the biosphere vector\n",
+    "dp.add_persistent_vector(\n",
+    "    matrix=\"biosphere_matrix\",\n",
+    "    indices_array=indices_array,\n",
+    "    data_array=data_array,\n",
+    "    flip_array=None,\n",
+    "    #distributions_array=distributions_array,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "62482300-8ccb-43c1-a95c-9fd426be5055",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# let's build a characterization matrix for fossil CO2 = 1\n",
+    "# more complex LCIA vector building is possible \n",
+    "# if one accesses bw2data.Method()\n",
+    "c_indices = np.array(\n",
+    "    [\n",
+    "        (v, v) \n",
+    "        for k, v in B_idx.items() \n",
+    "        if \"carbon dioxide, fossil\" in str(k).lower()\n",
+    "    ],\n",
+    "    dtype=bwp.INDICES_DTYPE   \n",
+    ")\n",
+    "c_data = np.ones(len(c_indices))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "d035cddf-4c74-4545-adb4-8db2aeb54ab3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# we add the method vector\n",
+    "dp.add_persistent_vector(\n",
+    "    matrix='characterization_matrix',\n",
+    "    indices_array=c_indices,\n",
+    "    data_array=c_data,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "757c9934-426b-4a81-814c-615bfe10eedb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "25553"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# let's look for a gasoline car\n",
+    "ix = [\n",
+    "    v for k, v in A_idx.items() \n",
+    "    if \"transport, passenger car\" in str(k)\n",
+    "    and \"gasoline\" in str(k)\n",
+    "][0]\n",
+    "ix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "aff74989-c3c2-4448-a5cd-3adc9f263908",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lca = bc.LCA(\n",
+    "    demand={ix: 1},\n",
+    "    data_objs=[\n",
+    "        dp,\n",
+    "    ],\n",
+    "    use_distributions=False,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "21099522-8802-473b-a006-4ffa50e3a1c2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.27376991977578063"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lca.lci()\n",
+    "lca.lcia()\n",
+    "lca.score"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4b39de01-9afa-4aea-952f-98d56c7db24f",
+   "metadata": {},
+   "source": [
+    "## Scenarios\n",
+    "\n",
+    "Now, let's vary the input of gasoline in the car dataset (and related CO2 emissions)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "db6fb89e-d25c-465d-9cfb-e578c7b1a81e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# let's build reverse indices' lists for convenience\n",
+    "rev_A_idx = {v: k for k, v in A_idx.items()}\n",
+    "rev_B_idx = {v: k for k, v in B_idx.items()}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "fe2f5d0f-67f9-4d0c-b73a-dfa1fdd83128",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Gasoline input index 28947\n",
+      "Scenario values [0.04 0.05 0.06 0.07 0.08 0.09]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# let's print the inputs labels and indices to the car dataset\n",
+    "for i in np.argwhere(lca.technosphere_matrix[:, ix]):\n",
+    "    i_ = lca.activity_dict.reversed[i[0]]\n",
+    "    label = rev_A_idx[i_]\n",
+    "    if label[0] == 'market for petrol, low-sulfur':\n",
+    "        gasoline_ix = i_\n",
+    "gasoline_values = np.arange(4/100, 10/100, 0.01)\n",
+    "\n",
+    "print(\"Gasoline input index\", gasoline_ix)\n",
+    "print(\"Scenario values\", gasoline_values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "4659d0f7-d45f-42b2-a6a7-e71582024bc1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.08797021909304188"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# current gasoline consumption\n",
+    "lca.technosphere_matrix[lca.dicts.product[gasoline_ix], lca.dicts.activity[ix]] * -1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "200212e0-2738-4f30-9c68-e4ff2001d164",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "401\n",
+      "[0.126  0.1575 0.189  0.2205 0.252  0.2835]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# same for CO2 emissions\n",
+    "# let's print the inputs labels and indices to the car dataset\n",
+    "for i in np.argwhere(lca.biosphere_matrix[:, ix]):\n",
+    "    i_ = lca.biosphere_dict.reversed[i[0]]\n",
+    "    label = rev_B_idx[i_]\n",
+    "    if label[0] == 'Carbon dioxide, fossil':\n",
+    "        co2_ix = i_\n",
+    "print(co2_ix)\n",
+    "co2_values = gasoline_values * 3.15 # kg CO2/kg gasoline\n",
+    "print(co2_values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "b56f90ba-1587-4530-9a5e-dd0bb41da3a4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.13075946643594696"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# current CO2 emissions of the car\n",
+    "lca.biosphere_matrix[lca.biosphere_dict[co2_ix], lca.dicts.activity[ix]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "id": "0504e37c-7c29-44ed-84cb-29ba153b4c9e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# we create a second data package, to store our scenario values\n",
+    "dp_scenarios = bwp.create_datapackage(sequential=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "1cf1246f-9fa5-4c10-9f4d-348742b411bc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dp_scenarios.add_persistent_array(\n",
+    "    matrix='technosphere_matrix',\n",
+    "    indices_array=np.array([(gasoline_ix, ix)], dtype=bwp.INDICES_DTYPE),\n",
+    "    data_array=np.array([tuple(gasoline_values)]).reshape(1, -1),\n",
+    "    flip_array=np.array([True])\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "9b08c9a0-a494-4fc5-9c26-957bae12c99b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dp_scenarios.add_persistent_array(\n",
+    "    matrix='biosphere_matrix',\n",
+    "    indices_array=np.array([(co2_ix, ix)], dtype=bwp.INDICES_DTYPE),\n",
+    "    data_array=np.array([tuple(co2_values)]).reshape(1, -1),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "311a5e51-87db-4125-958c-235841c6f78a",
+   "metadata": {},
+   "source": [
+    "Now we can iterate over the LCA object (which is a generator) for as many times as we have scenario values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "ed4e0e66-69ee-4b6e-98ad-e15c8f01b070",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fuel: 0.04 CO2: 0.126 Score: 0.2378711545922471\n",
+      "Fuel: 0.05 CO2: 0.1575 Score: 0.2758625359818526\n",
+      "Fuel: 0.060000000000000005 CO2: 0.189 Score: 0.31385391737145824\n",
+      "Fuel: 0.07 CO2: 0.2205 Score: 0.3518452987610632\n",
+      "Fuel: 0.08000000000000002 CO2: 0.25200000000000006 Score: 0.38983668015066975\n",
+      "Fuel: 0.09000000000000001 CO2: 0.28350000000000003 Score: 0.42782806154027464\n"
+     ]
+    }
+   ],
+   "source": [
+    "for v, val in enumerate(gasoline_values):\n",
+    "    if v == 0:\n",
+    "        lca = bc.LCA(\n",
+    "            demand={ix: 1},\n",
+    "            data_objs=[\n",
+    "                dp, dp_scenarios\n",
+    "            ],\n",
+    "            use_distributions=False,\n",
+    "            use_arrays=True,\n",
+    "        )\n",
+    "        lca.lci()\n",
+    "        lca.lcia()\n",
+    "    else:\n",
+    "        next(lca)\n",
+    "    print(\n",
+    "        \"Fuel:\", -1 * lca.technosphere_matrix[lca.dicts.product[gasoline_ix], lca.dicts.activity[ix]], \n",
+    "        \"CO2:\", lca.biosphere_matrix[lca.biosphere_dict[co2_ix], lca.dicts.activity[ix]], \n",
+    "        \"Score:\", lca.score\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4eb165b7-b96a-4288-a916-492ec257f8a7",
+   "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": "3.11.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/examples user-defined scenarios.ipynb b/examples/examples user-defined scenarios.ipynb
index de716f9c..6b692ff1 100644
--- a/examples/examples user-defined scenarios.ipynb	
+++ b/examples/examples user-defined scenarios.ipynb	
@@ -572,7 +572,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.11.11"
   }
  },
  "nbformat": 4,