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Update the examples
Signed-off-by: GitHub Actions Bot <[email protected]>
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-84
lines changed

‎examples/Asymmetric Calculation Example.ipynb‎

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"source": [
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"# some basic imports\n",
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"import numpy as np\n",
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"import warnings\n",
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"\n",
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"with warnings.catch_warnings(action=\"ignore\", category=DeprecationWarning):\n",
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" # suppress warning about pyarrow as future required dependency\n",
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" import pandas as pd\n",
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"import pandas as pd\n",
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"\n",
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"from power_grid_model import LoadGenType, ComponentType, DatasetType\n",
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"from power_grid_model import PowerGridModel, CalculationMethod, CalculationType, MeasuredTerminalType\n",

‎examples/Make Test Dataset.ipynb‎

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"# first build the network\n",
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"\n",
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"import numpy as np\n",
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"import warnings\n",
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"\n",
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"with warnings.catch_warnings(action=\"ignore\", category=DeprecationWarning):\n",
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" # suppress warning about pyarrow as future required dependency\n",
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" import pandas as pd\n",
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"import pandas as pd\n",
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"\n",
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"from power_grid_model import LoadGenType, ComponentType, DatasetType\n",
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"from power_grid_model import PowerGridModel\n",

‎examples/Power Flow Example.ipynb‎

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"source": [
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"# some basic imports\n",
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"import numpy as np\n",
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"import warnings\n",
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"\n",
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"with warnings.catch_warnings(action=\"ignore\", category=DeprecationWarning):\n",
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" # suppress warning about pyarrow as future required dependency\n",
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" import pandas as pd\n",
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"import pandas as pd\n",
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"\n",
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"from power_grid_model import LoadGenType, ComponentType, DatasetType, ComponentAttributeFilterOptions\n",
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"from power_grid_model import PowerGridModel, CalculationMethod, CalculationType\n",
@@ -640,15 +636,40 @@
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},
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{
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"cell_type": "markdown",
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"id": "fcc57354",
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"id": "25a3f722",
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"metadata": {},
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"source": [
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"Columnar data is also supported"
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"If you are updating all components of the same type (uniformly) in the same order as in the input data, providing IDs is optional."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "6a4d9802",
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"metadata": {},
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"outputs": [],
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"source": [
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"update_sym_load_no_id = initialize_array(DatasetType.update, ComponentType.sym_load, 2)\n",
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"update_sym_load_no_id[\"p_specified\"] = [30e6, 15e6] # change active power for both sym_loads\n",
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"# leave reactive power the same, no need to specify\n",
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"\n",
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"update_line_no_id = initialize_array(DatasetType.update, ComponentType.line, 3)\n",
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"update_line_no_id[\"from_status\"] = [0, 1, 1] # switch off at from side for line #3\n",
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"\n",
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"update_data_no_id = {ComponentType.sym_load: update_sym_load_no_id, ComponentType.line: update_line_no_id}"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fcc57354",
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"metadata": {},
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"source": [
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"Columnar data is also supported."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "aaf8fe64",
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"metadata": {},
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"outputs": [],
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"}\n",
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"# leave to-side swiching status the same, no need to specify\n",
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"\n",
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"update_data = {ComponentType.sym_load: update_sym_load, ComponentType.line: columnar_update_line}"
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"update_data_col = {ComponentType.sym_load: update_sym_load, ComponentType.line: columnar_update_line}"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f5179288",
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"metadata": {},
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"source": [
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"Columnar data also supports optional IDs."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "7eabed0c",
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"metadata": {},
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"outputs": [],
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"source": [
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"line_update_dtype = power_grid_meta_data[DatasetType.update][ComponentType.line].dtype\n",
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"columnar_no_ID_update_line = {\n",
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" # Update IDs are not specified\n",
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" \"from_status\": np.array(\n",
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" [0, 1, 1], dtype=line_update_dtype[\"from_status\"]\n",
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" ), # The update for the whole column needs to be specified\n",
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"}\n",
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"# leave to-side swiching status the same, no need to specify\n",
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"\n",
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"update_data_col_no_id = {ComponentType.sym_load: update_sym_load, ComponentType.line: columnar_no_ID_update_line}"
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]
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},
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{
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 18,
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"id": "63ea4cc3",
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"metadata": {},
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"outputs": [],
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"source": [
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"from power_grid_model.validation import assert_valid_batch_data\n",
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"\n",
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"assert_valid_batch_data(input_data=input_data, update_data=update_data, calculation_type=CalculationType.power_flow)"
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"assert_valid_batch_data(input_data=input_data, update_data=update_data, calculation_type=CalculationType.power_flow)\n",
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"assert_valid_batch_data(\n",
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" input_data=input_data, update_data=update_data_no_id, calculation_type=CalculationType.power_flow\n",
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")\n",
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"assert_valid_batch_data(input_data=input_data, update_data=update_data_col, calculation_type=CalculationType.power_flow)\n",
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"assert_valid_batch_data(\n",
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" input_data=input_data, update_data=update_data_col_no_id, calculation_type=CalculationType.power_flow\n",
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")"
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]
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},
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{
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"id": "188f6663",
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"metadata": {},
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"outputs": [],
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},
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"cell_type": "code",
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"execution_count": 20,
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"outputs": [
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},
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"cell_type": "code",
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"execution_count": 21,
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"output_type": "stream",
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"text": [
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"Node data with invalid results\n",
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"[[9.99401170e-001 9.92685785e-001 9.94521366e-001]\n",
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" [9.99347687e-001 9.86226389e-001 9.89352855e-001]\n",
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" [9.99288384e-001 9.79654011e-001 9.84095542e-001]\n",
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" [0.00000000e+000 3.04369633e+101 3.41345331e+241]\n",
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" [9.99151380e-001 9.66149483e-001 9.73298790e-001]\n",
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" [9.99073166e-001 9.59205860e-001 9.67750710e-001]\n",
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" [9.98988099e-001 9.52126208e-001 9.62096474e-001]\n",
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" [1.66994188e-321 3.12878333e-312 9.75772002e+199]\n",
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" [9.98796126e-001 9.37530046e-001 9.50447962e-001]\n",
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" [9.98688504e-001 9.29997471e-001 9.44441670e-001]]\n",
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"[[0.99940117 0.99268579 0.99452137]\n",
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" [0.99934769 0.98622639 0.98935286]\n",
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" [0.99928838 0.97965401 0.98409554]\n",
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" [0. 0. 0. ]\n",
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" [0.99915138 0.96614948 0.97329879]\n",
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" [0.99907317 0.95920586 0.96775071]\n",
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" [0.9989881 0.95212621 0.96209647]\n",
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" [0. 0. 0. ]\n",
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" [0.99879613 0.93753005 0.95044796]\n",
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" [0.9986885 0.92999747 0.94444167]]\n",
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"Node data with only valid results\n",
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"[[0.99940117 0.99268579 0.99452137]\n",
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" [0.99934769 0.98622639 0.98935286]\n",

‎examples/Serialization Example.ipynb‎

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"import json\n",
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"from pandas import DataFrame\n",
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"import pprint\n",
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"import warnings\n",
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"\n",
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"with warnings.catch_warnings(action=\"ignore\", category=DeprecationWarning):\n",
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" # suppress warning about pyarrow as future required dependency\n",
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" from pandas import DataFrame\n",
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"\n",
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"from power_grid_model import PowerGridModel, ComponentType, ComponentAttributeFilterOptions\n",
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"from power_grid_model.utils import json_deserialize, json_serialize"

‎examples/Short Circuit Example.ipynb‎

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"source": [
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"# some basic imports\n",
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"import numpy as np\n",
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"import warnings\n",
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"\n",
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"with warnings.catch_warnings(action=\"ignore\", category=DeprecationWarning):\n",
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" # suppress warning about pyarrow as future required dependency\n",
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" import pandas as pd\n",
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"import pandas as pd\n",
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"\n",
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"from power_grid_model import LoadGenType, ComponentType, DatasetType\n",
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"from power_grid_model import (\n",

‎examples/State Estimation Example.ipynb‎

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"source": [
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"# some basic imports\n",
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"import numpy as np\n",
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"import warnings\n",
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"\n",
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"with warnings.catch_warnings(action=\"ignore\", category=DeprecationWarning):\n",
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" # suppress warning about pyarrow as future required dependency\n",
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" import pandas as pd\n",
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"import pandas as pd\n",
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"\n",
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"from power_grid_model import LoadGenType, DatasetType, ComponentType\n",
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"from power_grid_model import PowerGridModel, CalculationMethod, CalculationType, MeasuredTerminalType\n",

‎examples/Transformer Examples.ipynb‎

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"# some basic imports\n",
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"import warnings\n",
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"\n",
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"with warnings.catch_warnings():\n",
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" warnings.simplefilter(\"ignore\", category=DeprecationWarning)\n",
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" # suppress warning about pyarrow as future required dependency\n",
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" import pandas as pd\n",
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"import pandas as pd\n",
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"\n",
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"from power_grid_model import LoadGenType, DatasetType, ComponentType\n",
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"from power_grid_model import (\n",

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