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@AndreasEppler
AndreasEppler committed Nov 20, 2024
2 parents 2bd2ca7 + b07da00 commit 9623660
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124 changes: 15 additions & 109 deletions examples/notebooks/04_reinforcement_learning_algorithm_example.ipynb
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{
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"text": [
"Requirement already satisfied: assume-framework[learning] in c:\\users\\aeppl\\.conda\\envs\\assume\\lib\\site-packages (0.4.3)\n",
"Requirement already satisfied: argcomplete>=3.1.4 in c:\\users\\aeppl\\.conda\\envs\\assume\\lib\\site-packages (from assume-framework[learning]) (3.5.1)\n",
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"Requirement already satisfied: typing-extensions>=4.6.0 in c:\\users\\aeppl\\.conda\\envs\\assume\\lib\\site-packages (from sqlalchemy>=2.0.9->assume-framework[learning]) (4.12.2)\n",
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"Requirement already satisfied: colorama in c:\\users\\aeppl\\.conda\\envs\\assume\\lib\\site-packages (from tqdm>=4.64.1->assume-framework[learning]) (0.4.6)\n",
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]
}
],
"outputs": [],
"source": [
"import importlib.util\n",
"\n",
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},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "d5e77f71",
"metadata": {
"colab": {
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},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"id": "de097384",
"metadata": {
"colab": {
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},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "7d9899ff",
"metadata": {},
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},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"id": "ade14744",
"metadata": {
"id": "xUsbeZdPJ_2Q"
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},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"id": "94517a3e",
"metadata": {
"id": "UXYSesx4Ifp5"
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},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": null,
"id": "daed035c",
"metadata": {},
"outputs": [],
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},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": null,
"id": "632844c2",
"metadata": {
"id": "0ww-L9fABnw3"
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},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"id": "c715f90e",
"metadata": {},
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},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": null,
"id": "753dbab1",
"metadata": {},
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},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": null,
"id": "6bb09b5b",
"metadata": {
"id": "moZ_UD7FfkOh"
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},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": null,
"id": "5cff2f6a",
"metadata": {
"id": "iPz8v4N5hpfr"
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"lines_to_next_cell": 0,
"outputId": "e30f4279-7a4e-4efc-9cfb-61416e4fe2f1"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:assume.world:connected to db\n",
"INFO:assume.scenario.loader_csv:Starting Scenario example_02a/base from ../inputs\n",
"INFO:assume.scenario.loader_csv:storage_units not found. Returning None\n",
"INFO:assume.scenario.loader_csv:industrial_dsm_units not found. Returning None\n",
"INFO:assume.scenario.loader_csv:residential_dsm_units not found. Returning None\n",
"INFO:assume.scenario.loader_csv:forecasts_df not found. Returning None\n",
"INFO:assume.scenario.loader_csv:Downsampling demand_df successful.\n",
"INFO:assume.scenario.loader_csv:cross_border_flows not found. Returning None\n",
"INFO:assume.scenario.loader_csv:availability_df not found. Returning None\n",
"INFO:assume.scenario.loader_csv:electricity_prices not found. Returning None\n",
"INFO:assume.scenario.loader_csv:price_forecasts not found. Returning None\n",
"INFO:assume.scenario.loader_csv:temperature not found. Returning None\n",
"INFO:assume.scenario.loader_csv:Adding markets\n",
"INFO:assume.scenario.loader_csv:Read units from file\n",
"INFO:assume.scenario.loader_csv:Adding power_plant units\n",
"INFO:assume.scenario.loader_csv:Adding demand units\n",
"INFO:assume.scenario.loader_csv:Adding unit operators and units\n",
"INFO:assume.scenario.loader_csv:storage_units not found. Returning None\n",
"INFO:assume.scenario.loader_csv:industrial_dsm_units not found. Returning None\n",
"INFO:assume.scenario.loader_csv:residential_dsm_units not found. Returning None\n",
"INFO:assume.scenario.loader_csv:forecasts_df not found. Returning None\n",
"INFO:assume.scenario.loader_csv:Downsampling demand_df successful.\n",
"INFO:assume.scenario.loader_csv:cross_border_flows not found. Returning None\n",
"INFO:assume.scenario.loader_csv:availability_df not found. Returning None\n",
"INFO:assume.scenario.loader_csv:electricity_prices not found. Returning None\n",
"INFO:assume.scenario.loader_csv:price_forecasts not found. Returning None\n",
"INFO:assume.scenario.loader_csv:temperature not found. Returning None\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Training Episodes: 0%| | 0/100 [00:00<?, ?it/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"INFO:assume.world:activating container\n",
"INFO:assume.world:all agents up - starting simulation\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": []
}
],
"outputs": [],
"source": [
"import os\n",
"\n",
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],
"metadata": {
"kernelspec": {
"display_name": "assume",
"display_name": "assume-framework",
"language": "python",
"name": "python3"
},
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.7"
"version": "3.11.9"
}
},
"nbformat": 4,
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4 changes: 2 additions & 2 deletions examples/notebooks/04_reinforcement_learning_example.ipynb
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],
"metadata": {
"kernelspec": {
"display_name": "assume",
"display_name": "assume-framework",
"language": "python",
"name": "python3"
},
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.7"
"version": "3.11.9"
}
},
"nbformat": 4,
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