From cfbe952cc7be1baa29b907b1a94b47fe71397b1b Mon Sep 17 00:00:00 2001 From: lisrte Date: Mon, 16 Dec 2024 17:25:31 +0100 Subject: [PATCH 01/14] Add dynawo simulation nordic case Signed-off-by: lisrte --- dynawo/nordic case/Network.par | 38 + dynawo/nordic case/Nordic.par | 1023 ++++++++++ dynawo/nordic case/Nordic.xiidm | 2207 +++++++++++++++++++++ dynawo/nordic case/Solver.par | 56 + dynawo/nordic case/config.yml | 10 + dynawo/nordic case/pypowsybl_dynawo.ipynb | 326 +++ 6 files changed, 3660 insertions(+) create mode 100644 dynawo/nordic case/Network.par create mode 100644 dynawo/nordic case/Nordic.par create mode 100644 dynawo/nordic case/Nordic.xiidm create mode 100644 dynawo/nordic case/Solver.par create mode 100644 dynawo/nordic case/config.yml create mode 100644 dynawo/nordic case/pypowsybl_dynawo.ipynb diff --git a/dynawo/nordic case/Network.par b/dynawo/nordic case/Network.par new file mode 100644 index 0000000..fe37dfe --- /dev/null +++ b/dynawo/nordic case/Network.par @@ -0,0 +1,38 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/dynawo/nordic case/Nordic.par b/dynawo/nordic case/Nordic.par new file mode 100644 index 0000000..424ba18 --- /dev/null +++ b/dynawo/nordic case/Nordic.par @@ -0,0 +1,1023 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/dynawo/nordic case/Nordic.xiidm b/dynawo/nordic case/Nordic.xiidm new file mode 100644 index 0000000..753b35b --- /dev/null +++ b/dynawo/nordic case/Nordic.xiidm @@ -0,0 +1,2207 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/dynawo/nordic case/Solver.par b/dynawo/nordic case/Solver.par new file mode 100644 index 0000000..88201fd --- /dev/null +++ b/dynawo/nordic case/Solver.par @@ -0,0 +1,56 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/dynawo/nordic case/config.yml b/dynawo/nordic case/config.yml new file mode 100644 index 0000000..4627340 --- /dev/null +++ b/dynawo/nordic case/config.yml @@ -0,0 +1,10 @@ +dynawo: + homeDir: /home/dynawo + +dynawo-simulation-default-parameters: + parametersFile: Nordic.par + network.parametersFile: Network.par + network.parametersId: "Network" + solver.type: SIM + solver.parametersFile: Solvers.par + solver.parametersId: "Solver" diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb new file mode 100644 index 0000000..3650fe4 --- /dev/null +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -0,0 +1,326 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Dynawo simulation - Nordic case" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "TODO - description" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1 - Dynawo install" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!curl -L $(curl -s -L -X GET https://api.github.com/repos/dynawo/dynaflow-launcher/releases/latest | grep \"DynaFlowLauncher_Linux\" | grep url | cut -d '\"' -f 4) -o DynaflowLauncher_Linux_latest.zip\n", + "!unzip DynaflowLauncher_Linux_latest.zip > /dev/null 2>&1\n", + "!./dynaflow-launcher/dynaflow-launcher.sh help" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2 - Powsybl install" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pip install pypowsybl" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!mkdir /home/jovyan/.itools/\n", + "!cp /home/jovyan/dynaflow/config.yml /home/jovyan/.itools/\n", + "!cat /home/jovyan/.itools/config.yml" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3 - Base case" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pypowsybl as pp\n", + "import pypowsybl.dynamic as dyn\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import os.path" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# Load initial situation\n", + "network = pp.network.load('Nordic.xiidm')\n", + "network.get_network_area_diagram()\n", + "report_node = pp.report.Reporter()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Add generators dynamic models" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "model_mapping = dyn.ModelMapping()\n", + "generator_mapping_df = pd.DataFrame.from_records(\n", + " index='static_id',\n", + " columns=['static_id', 'parameter_set_id', 'model_name'],\n", + " data=[('g01', 'g01', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g02', 'g02', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g03', 'g03', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g04', 'g04', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g05', 'g05', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g06', 'g06', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g07', 'g07', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g08', 'g08', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g09', 'g09', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g10', 'g10', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g11', 'g11', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g12', 'g12', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g13', 'g13', 'GeneratorSynchronousThreeWindingsPmConstVRNordic'),\n", + " ('g14', 'g14', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g15', 'g15', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g16', 'g16', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g17', 'g17', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g18', 'g18', 'GeneratorSynchronousFourWindingsPmConstVRNordic'),\n", + " ('g19', 'g19', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic'),\n", + " ('g20', 'g20', 'GeneratorSynchronousThreeWindingsGoverNordicVRNordic')])\n", + "model_mapping.add_synchronous_generator(generator_mapping_df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Add node fault and disconnect line event" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "event_mapping = dyn.EventMapping()\n", + "event_mapping.add_node_fault(static_id='4032_401', start_time=1, fault_time=0.1, r_pu=0.025, x_pu=0.025)\n", + "event_mapping.add_disconnection(static_id='L4032-4044', start_time=1.1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Request curves output" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "variables_mapping = dyn.OutputVariableMapping()\n", + "variables_mapping.add_standard_model_curves('1042_131', 'Upu_value')\n", + "# equipment_names = {'1011_131', '4011_401', 'B11___21', 'BG09__11', '1012_131', '4012_401', 'B12___21', 'BG01__11', 'BG10__11',\n", + "# '1013_131', 'B13___21', 'BG02__11', '1014_131', 'BG03__11', '1021_131', 'BG04__11', '1022_131', '4022_401',\n", + "# 'B22___21', 'BG05__11', '1041_131', 'B01___21', '1042_131', 'B02___21', 'BG06__11', '1043_131', 'B03___21',\n", + "# 'BG07__11', '1044_131', '4044_401', 'B04___21', '1045_131', '4045_401', 'B05___21', '2031_221', '4031_401',\n", + "# 'B31___21', 'BG12__11', '2032_221', 'B32___21', 'BG08__11', '4021_401', 'BG11__11', '4032_401', '4041_401',\n", + "# 'B41___21', 'BG13__11', '4042_401', 'B42___21', 'BG14__11', '4043_401', 'B43___21', '4046_401', 'B46___21',\n", + "# '4047_401', 'B47___21', 'BG15__11', '4051_401', 'B51___21', 'BG16__11', '4061_401', 'B61___21', '4062_401',\n", + "# 'B62___21', 'BG17__11', '4063_401', 'B63___21', 'BG18__11', '4071_401', 'B71___21', 'BG19__11', '4072_401',\n", + "# 'B72___21', 'BG20__11'}\n", + "# for eq in equipment_names:\n", + "# variables_mapping.add_standard_model_curves(eq, 'Upu_value')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "sim = dyn.Simulation()\n", + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175, report_node)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Display curves" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "res.curves().plot()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4 - Second simulation with tap changer blocking automation system" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "tcb_df = pd.DataFrame.from_records(\n", + " index='dynamic_model_id',\n", + " columns=['dynamic_model_id', 'parameter_set_id'],\n", + " data=[('TCB', 'TCB')])\n", + "# Transformers\n", + "tfo_ids = ['Tr11-1011', 'Tr12-1012', 'Tr13-1013', 'Tr22-1022', 'Tr1-1041', 'Tr2-1042', 'Tr3-1043', 'Tr4-1044', 'Tr5-1045', 'Tr31-2031',\n", + " 'Tr32-2032', 'Tr41-4041', 'Tr42-4042', 'Tr43-4043', 'Tr46-4046', 'Tr47-4047', 'Tr51-4051', 'Tr61-4061', 'Tr62-4062', 'Tr63-4063'\n", + " 'Tr71-4071', 'Tr72-4072']\n", + "tfo_df = pd.DataFrame.from_records(\n", + " index='dynamic_model_id',\n", + " columns=['dynamic_model_id', 'transformer_id'],\n", + " data={'dynamic_model_id': ['TCB' for tfo in tfo_ids],\n", + " 'transformer_id': tfo_ids})\n", + "# Measurement point\n", + "measurement1_df = pd.DataFrame.from_records(\n", + " index='dynamic_model_id',\n", + " columns=['dynamic_model_id', 'measurement_point_id'],\n", + " data=[('TCB', '1042_131')])\n", + "model_mapping.add_tap_changer_blocking_automation_system(df=tcb_df,\n", + " tfo_df=tfo_df,\n", + " mp1_df=measurement1_df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run second simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "variables_mapping.add_standard_model_final_state_values('1042_131', 'Upu_value')\n", + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175, report_node)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Display final state values " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " values\n", + "variables \n", + "NETWORK_1042_131_Upu_value 0.8069\n" + ] + } + ], + "source": [ + "print(res.final_state_values())" + ] + } + ], + "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": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} From bcef593cd7ab34b91dd6d7433c005a64e147374f Mon Sep 17 00:00:00 2001 From: lisrte Date: Wed, 18 Dec 2024 11:23:17 +0100 Subject: [PATCH 02/14] Edit install Signed-off-by: lisrte --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index 3650fe4..d83d04f 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -27,9 +27,9 @@ "metadata": {}, "outputs": [], "source": [ - "!curl -L $(curl -s -L -X GET https://api.github.com/repos/dynawo/dynaflow-launcher/releases/latest | grep \"DynaFlowLauncher_Linux\" | grep url | cut -d '\"' -f 4) -o DynaflowLauncher_Linux_latest.zip\n", - "!unzip DynaflowLauncher_Linux_latest.zip > /dev/null 2>&1\n", - "!./dynaflow-launcher/dynaflow-launcher.sh help" + "!curl -L $(curl -s -L -X GET https://api.github.com/repos/dynawo/dynawo/releases/latest | grep \"Dynawo_Linux\" | grep url | cut -d '\"' -f 4) -o Dynawo_Linux_latest.zip\n", + "!unzip Dynawo_Linux_latest.zip > /dev/null 2>&1\n", + "!./dynawo/dynawo.sh help" ] }, { @@ -54,9 +54,9 @@ "metadata": {}, "outputs": [], "source": [ - "!mkdir /home/jovyan/.itools/\n", - "!cp /home/jovyan/dynaflow/config.yml /home/jovyan/.itools/\n", - "!cat /home/jovyan/.itools/config.yml" + "!mkdir /home/USER/.itools/\n", + "!cp /home/USER/dynaflow/config.yml /home/USER/.itools/\n", + "!cat /home/USER/.itools/config.yml" ] }, { From a49867255fb83364905fc53e77d264d96ba634e6 Mon Sep 17 00:00:00 2001 From: lisrte Date: Wed, 18 Dec 2024 15:51:03 +0100 Subject: [PATCH 03/14] Update installation instruction Use network variant Display TCB simulation curve Signed-off-by: lisrte --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 4308 ++++++++++++++++++++- 1 file changed, 4273 insertions(+), 35 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index d83d04f..d8d2f80 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -55,7 +55,7 @@ "outputs": [], "source": [ "!mkdir /home/USER/.itools/\n", - "!cp /home/USER/dynaflow/config.yml /home/USER/.itools/\n", + "!cp /home/USER/dynawo/nordic case/config.yml /home/USER/.itools/\n", "!cat /home/USER/.itools/config.yml" ] }, @@ -83,12 +83,4256 @@ "cell_type": "code", "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/svg+xml": [ + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 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+ " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " -300\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " -2,138\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 2,138\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " 2,000\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " -2,000\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
1011_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
138.0 kV / 57.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1012_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
138.2 kV / 61.1°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1013_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
137.1 kV / 65.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1014_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
137.9 kV / 68.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1021_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
134.0 kV / 66.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1022_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
136.7 kV / 45.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1041_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
131.6 kV / -17.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1042_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
131.9 kV / -3.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1043_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
133.6 kV / -12.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1044_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
130.9 kV / -3.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
1045_130
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
131.4 kV / -7.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
2031_220
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
226.1 kV / 27.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
2032_220
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
235.3 kV / 40.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4011_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
409.0 kV / 56.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4012_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
409.4 kV / 58.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4021_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
419.5 kV / 28.1°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4022_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
397.9 kV / 43.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4031_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
414.7 kV / 24.8°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4032_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
419.5 kV / 19.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4041_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
420.2 kV / 9.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4042_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
417.2 kV / 6.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4043_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
414.8 kV / 0.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4044_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
415.8 kV / 0.0°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4045_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
421.4 kV / -4.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4046_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
414.3 kV / 0.1°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4047_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
423.6 kV / 4.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4051_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
426.4 kV / -6.8°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4061_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
415.5 kV / 6.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4062_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
422.4 kV / 9.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4063_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
421.4 kV / 13.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4071_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
419.4 kV / 59.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
4072_400
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
423.6 kV / 60.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B01___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -20.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B02___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -6.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B03___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / -15.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B04___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -6.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B05___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / -10.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B11___20
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\n", + "
20.1 kV / 54.8°
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\n", + " \n", + " \n", + "
\n", + "
B12___20
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\n", + "
20.0 kV / 58.3°
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\n", + " \n", + " \n", + "
\n", + "
B13___20
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\n", + "
19.9 kV / 62.6°
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\n", + "
B22___20
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\n", + "
19.9 kV / 42.3°
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\n", + "
B31___20
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\n", + "
20.1 kV / 24.8°
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\n", + "
B32___20
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\n", + "
20.0 kV / 37.5°
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\n", + " \n", + " \n", + "
\n", + "
B41___20
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\n", + "
19.9 kV / 7.1°
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\n", + " \n", + " \n", + "
\n", + "
B42___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
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\n", + "
19.9 kV / 4.0°
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\n", + " \n", + " \n", + "
\n", + "
B43___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -2.1°
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\n", + " \n", + " \n", + "
\n", + "
B46___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -2.7°
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\n", + " \n", + " \n", + "
\n", + "
B47___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / 1.9°
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\n", + " \n", + " \n", + "
\n", + "
B51___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / -9.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B61___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / 3.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B62___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / 7.0°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B63___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.0 kV / 10.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B71___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
20.1 kV / 56.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
B72___20
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
19.9 kV / 57.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG01__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
16.0 kV / 66.8°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG02__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.8 kV / 69.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG03__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.9 kV / 74.5°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG04__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.5 kV / 72.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG05__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.4 kV / 51.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG06__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.1 kV / 4.8°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG07__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.2 kV / -4.7°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG08__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.7 kV / 47.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG09__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.0 kV / 62.6°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG10__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.2 kV / 65.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG11__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.3 kV / 35.2°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG12__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.3 kV / 32.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG13__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.3 kV / 9.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG14__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.7 kV / 14.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG15__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.7 kV / 12.0°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG16__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.8 kV / 0.1°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG17__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.1 kV / 17.4°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG18__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.5 kV / 20.9°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG19__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.5 kV / 64.3°
\n", + "
\n", + " \n", + " \n", + "
\n", + "
BG20__15
\n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
\n", + "
\n", + "
15.3 kV / 64.2°
\n", + "
\n", + " \n", + " \n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Load initial situation\n", "network = pp.network.load('Nordic.xiidm')\n", - "network.get_network_area_diagram()\n", - "report_node = pp.report.Reporter()" + "network.clone_variant('InitialState', 'BaseCase')\n", + "network.set_working_variant('BaseCase')\n", + "network.get_network_area_diagram()" ] }, { @@ -163,18 +4407,7 @@ "outputs": [], "source": [ "variables_mapping = dyn.OutputVariableMapping()\n", - "variables_mapping.add_standard_model_curves('1042_131', 'Upu_value')\n", - "# equipment_names = {'1011_131', '4011_401', 'B11___21', 'BG09__11', '1012_131', '4012_401', 'B12___21', 'BG01__11', 'BG10__11',\n", - "# '1013_131', 'B13___21', 'BG02__11', '1014_131', 'BG03__11', '1021_131', 'BG04__11', '1022_131', '4022_401',\n", - "# 'B22___21', 'BG05__11', '1041_131', 'B01___21', '1042_131', 'B02___21', 'BG06__11', '1043_131', 'B03___21',\n", - "# 'BG07__11', '1044_131', '4044_401', 'B04___21', '1045_131', '4045_401', 'B05___21', '2031_221', '4031_401',\n", - "# 'B31___21', 'BG12__11', '2032_221', 'B32___21', 'BG08__11', '4021_401', 'BG11__11', '4032_401', '4041_401',\n", - "# 'B41___21', 'BG13__11', '4042_401', 'B42___21', 'BG14__11', '4043_401', 'B43___21', '4046_401', 'B46___21',\n", - "# '4047_401', 'B47___21', 'BG15__11', '4051_401', 'B51___21', 'BG16__11', '4061_401', 'B61___21', '4062_401',\n", - "# 'B62___21', 'BG17__11', '4063_401', 'B63___21', 'BG18__11', '4071_401', 'B71___21', 'BG19__11', '4072_401',\n", - "# 'B72___21', 'BG20__11'}\n", - "# for eq in equipment_names:\n", - "# variables_mapping.add_standard_model_curves(eq, 'Upu_value')" + "variables_mapping.add_standard_model_curves('1042_131', 'U_value')" ] }, { @@ -191,24 +4424,24 @@ "outputs": [], "source": [ "sim = dyn.Simulation()\n", - "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175, report_node)" + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Display curves" + "Display curve" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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ycrplDc7Oznj66afxyiuvQC6Xo3fv3rh8+TLmz5+PIUOGYOjQoSbtV61ahS5duqB79+744IMPUFBQgCeffBIAEBERAQcHB7z++ut44YUXcOTIkVpzCDXkoYcewqxZszBr1iyMHDkS/v7+xte6dOmC//znP/j5558RHByMb775BseOHUNwcHC927v77ruxdu1ajBs3Dq6urli8eLFJh/GoqChERkbiwQcfxD//+U+EhYXh6tWr2LFjByZMmICBAweaVX+zmD1uyQq11jDqGn//LkF0mr9dfLo3pVHtfzufK4IXbBed5m8X/zmUXut1vd4gzmdrxMajGWL+96fF6BX7RNCN9jc/RizfK17dfEqsP3JJnMvSiCp944eSEjVHfUMebcFfh4UKUT2kVaFQ1BpGXdfjr8OCGxpyHRMTIwCId99912T5m2++KQCIZcuW1VqnsrJSLF++XPTs2VMoFAqhVqtFdHS0OHDggEm7+ob5xsfHCwDiyJEjQog/h1Hf7MyZM8Lb21uMHz9eaLXaOmu/+X3qOhY3D50tLy8Xf//734Wbm5twcHAQEyZMMBlC/ld1Hbfhw4fX+T7Tpk27ZX1/3WZ965eXl4sJEyYIf39/oVAohJ+fn3jggQfE0aNHTbYzbdq0OrdTM9S9IeXl5SImJkZ069ZN2Nvbi+DgYPHss8+KvLw8Y5uaYdTr1q0TgwcPFgqFQvTo0UPs2bPHZFtbt24VnTt3Fvb29uL+++8X//73vxs1jPpmEydOFADEmjVrTJZXVFSI6dOnCxcXF+Hq6ipmzZolFixYIMLDw02Oxc3/vxQVFYlJkyYJtVotAgICxNq1a2sNo9ZoNOL5558X/v7+ws7OTgQEBIipU6eKjIyMWx6zlh5GLRHCjN5kVkqj0cDFxQVFRUXG65MtadXeFCz/ORkPhPvjo8n9btn28vUyjPvkAArLKvHIgI7459/6NKrfjKaiEscvXsfhtOs4nHYNZzOLYPjLb8ZJKUffAFeEB7igh58LevqrEejuAKmUdwymllVRUWEcBqxS8UwgkbkuXryI4OBgnDx5slmdZtuK+v6mNOf7m5eQGqGxQ6nLdXo8+00CCssq0aejC956sFejO/2qVXa4u5sP7u7mAwAoKq8ONAmXCnAyoxCnrxSiRFuFAyn5OJCSb1zPUSFDdz81evir0dNfjR5+Luji4wRVE0dtEBER2QIGmEaoGYmUmldqHFH0V0IILNjyO5KyNPBwVOCzxwY0K0S42NthVHcfjOpeHWiq9AaczynBiYwC/HG1CH9c1eBcdjFKdXocv1SA45f+nDK9pt9Ndz81Ons7IdTLCZ29HRHo7giFnCOfiNqT/fv3Y+zYsfW+XlJSchurqV9GRgZ69OhR7+uJiYmNnl+mOWbOnIlvv/22ztcee+wxfPbZZ61eQ42ePXvi0qVLdb72+eefG+d7aa8YYBrBV62Cq4MdCssqkZJbgl4danc2++bwJfx46ipkUglWTe0Pf1f7Fq1BLpOih7/aZDbgKr0BafmlSLyqwR9Xi5CUVYw/rhahoKwS57KLcS7bdO4amVSCTu4OCL0RakK9HI3/7WLf/JEKRGR9Bg4caPbIFkvw9/e/ZZ03d05tTUuXLq133iBzLnEEBQWZNd9PXXbu3FnvsGofH59mbbstYIBphJpbCsSnXUNilqZWgBFC4Iv91dNmzx/TFUNCmjdFdGPJZVKE+TgjzMcZD/brYKwlW1OBxBtnaFJzS5CaV4LUvFKUaKuQll+KtPxS7IbpXWTdHOzQ0c0BHd3s0dHNHh1c7eHrYg8vZyW8nZXwclbyshSRDbK3tzfOI2PN5HK5VdTp7e1tkQnv6nLzMG2qjQGmkbr7VQeYpKza/WD+uKrB5evlUNlJ8dgQy37gJBIJ/Fzs4edib7z8BFQHmxyNFim5JUjLL0FqbglS8kqQmluKbE0FCsoqUVBWhDOZRfVu21klh5ezEl5O1YHG+LjpubezCu6OCsjYsbhNMBh4F3Yiar7W+FvCANNI3W505K0rwPx0tnrSn+FhXlY7U6lEIoGviwq+LioM62J6T5ASbRWuFJThyvXy6p8F5bhSUI6c4grkFWuRW6yFrsqA4ooqFFdUIS2v9JbvJZUA7o4KqO3toFbZwcXeDmp7O/iqlXhqWAjnt7EBCoUCUqkUV69ehZeXFxQKhVmzUBMRAdX/eNbpdMjLy4NUKoVCoWixbVvnt60V6nHTPZHETbcUEELgp7PVkzHd29vPYvU1h5NSjm6+anTzrfv6rhACxdoq5Gq0yCvWIq/kxs8bj9ziCuSX6JBXXIFrpToYBJBfokN+ia7WtmLP5eL7mUPh7thyH2JqeVKpFMHBwcjKyjJObkZE1FQODg4IDAyEVNpyA0kYYBqps7cTZFIJisorka2pgJ9LdSfdC7klSMsrhUImxd3drOO6aUuTSCRQq6rPpnT2vvUslVV6A66XVocXTUUlNOWV0FRUoai8EmsOpCMtrxQzvjqKdc8MgaOSHz9rplAoEBgYiKqqKuj1ekuXQ0Q2SiaTQS6Xt/hZXH6DNJLKToZQL0eczylBUpbGGGB+OlN99mVYF084qziSRy6TwlutqvOWC8PDvPDIZ4dw+koRZn6bgC+nDeKwbisnkUhgZ2fXIvfTISJqSfz2MEP3my4j1ajp/zK2l69FarIlnb2dsGb6INjbybD/Qj7mbT4Nw1+nGyYiImoEBhgz1ASYxBsdedPzS3EuuxhyqQT39OCY/MboF+iGzx4fALlUgv+evoq3diQ2e64EIiJqf8y+hPTbb79h+fLlSEhIQFZWFrZu3YoHH3zwluvExcVh7ty5+OOPPxAQEIBFixZh+vTpJm1WrVqF5cuXIzs7G+Hh4fj4449NbkFvDf48A1MdYGrOvkSGesDVgZ1SG2t4mBf+9Ug4Xtp4Cl8dvIhtJzMhl0khl0ogk0pu+imFXPbn8yBPR9zX2w/DunhCKeecNERE7ZnZAaa0tBTh4eF48skn8dBDDzXYPj09Hffddx9mzpyJ7777DrGxsXj66afh5+eH6OhoAMDGjRsxd+5cfPbZZ4iIiMDKlSsRHR2N5ORkq5lQCAC6+1YPpb6YX4pynR67bow+GsPLR2Z7sF8HXC/V4f92JKKgrO6ZJv/qREYhtpzIhLNKjnt6+OD+Pn4Y1tmL/WiIiNqhZt2NWiKRNHgGZv78+dixYwfOnj1rXPboo4+isLAQu3btAgBERERg0KBB+OSTTwBUT3gTEBCA559/HgsWLGiwjta+G3UNIQQG/t+vuFaqw6dT++Pv352AVAIceT0KXs7KVnvftiyvWIuCMh2q9AJ6g0CVwXDjp7jppwHaSgOOpF/HzjNZyC3WGtdXq+QY3dMX9/X2wx2dPRlmiIhsiFXfjTo+Ph5RUVEmy6Kjo/HSSy8BAHQ6HRISErBw4ULj61KpFFFRUYiPj69zm1qtFlrtn19iGs2t7xLdUiQSCbr7qXEgJR8rfz0PABgU5M7w0gw1M/g2xtjeflh8fw8cv1SAnWeyjGHm+4Qr+D7hCtQqOaJ7+uLePn64I5RhhoioLWv1AJOdnV3rplM+Pj7QaDQoLy9HQUEB9Hp9nW3OnTtX5zaXLVuGJUuWtFrNt9LdzxkHUvJxPqf6Dq4cfXR7SaUSDA52x+Bgd7xxfw8cv1h9Vmbn2WzkFWuxOeEKNidcgYu9HaJ7+uC+Pv4YGuoBO9mtw4zeIKCrMqC8Uo/rpbpaE/Yp5FKT2yZ4Oyvh56KCvIHtEhFR67DJeWAWLlyIuXPnGp9rNBoEBATclveu6chbY0wv25x9ty2QSSWICPFARIgHFo/riWM1YeZMNvJLtNh0/Ao2Hb8CVwc7DOvsCQEYJ9bTlFeiuKISFZUGaKv0qNSbfyU10N0BXzwxEF1v9I0iIqLbp9UDjK+vL3JyTO98nJOTA7VaDXt7e8hkMshksjrb+PrWfXZDqVRCqbTMZZubA0z/QFfe18dKyKQSDAnxwJAQD8SM64mj6dex48xV7DqbjfwSHbb/ntXobdXctLL6LtwqeDopUKk3GO8LVfMz43oZ/vbZIXz++AAMDfVseMNERNRiWj3AREZGYufOnSbLdu/ejcjISADV05UPGDAAsbGxxs7ABoMBsbGxmDNnTmuXZ7ZQLyfYySSo1AuM5dkXqySTShAZ6oHIUA8seaAXjqRfw8mMQjgqZFDb/3lzSWeVHPZ2MijlMijlUijkUijl0kZdFioo1eGZ/xzH8UsFmLbmKP71SDjG9+3Q5Jor9QZcLSwHAGM9SjsplHIZ7+xNRFQHswNMSUkJUlJSjM/T09Nx6tQpuLu7IzAwEAsXLkRmZib+85//AABmzpyJTz75BK+99hqefPJJ7NmzB5s2bcKOHTuM25g7dy6mTZuGgQMHYvDgwVi5ciVKS0sxY8aMFtjFlqWQSzG6hy+OpF/DA339LV0ONUAmlWBoqGeLnyFxc1Tg26cjMHfTKew8k40XN5xCZmE5Zg0PNd7vw2AQyCvRIlejhbZKD22VARWV1T9LKqqQll+K1LwSpOaVIONaGarqmZV4TE9fvPdwH7g4cDp/IqIaZg+jjouLw8iRI2stnzZtGtauXYvp06fj4sWLiIuLM1nn5ZdfRmJiIjp27Ig33nij1kR2n3zyiXEiu759++Kjjz5CREREo2q6XcOob6Y3CP7LmGAwCLy9MwlfHkgHANwV5gUhBDILynGlsBy6KkOjt2VvV322pa4+OZ08HPDZYwNq9cEiIrJlzfn+btY8MNbCEgGG6GZrDqTfuC2C6XKppHqouPFSlV31ZSp7hRxBHg4I9XJCqJcTOns7wUetNJ69qRkVdS5bg+fXn8SVgnKo7KR496E+eLBf0y5VGQwCZZV6FFdUIr9Yh9ziCuMoK53egMeGdIJPHTfhJCJqLQwwDDBkBY6mX8fhtGvwdVEhwM0BHd3s4euianAId0MKSnV4ceMp/HY+DwAwfWgQXr4nDDmaClwpKMOVgnJcKShHfokWZVo9SnVVKNPpUaqt/lmmq0KpVo/ySv0t32fm8FAsGNutWbUSEZmDAYYBhto4vUFg5a/n8fGelIYbN0AulcDzxnw2Xs5KXC0sx7nsYjwR2QlLx/e6ZQ3/O30Vl66VQVulNw5B11YZUKargqa8CpqKSuNQdb1B1Jo7J9DDAQ+E+/PeYUQEwMpn4iWi5pNJJXhldFf06eiKeZtPo6i8EmqVHB1vnOnp6OYAb7USjko5HBUyOCjkcFT++dNRIYeDQgZHpRxKudR4qQoAVvySjHPZxbd8//M5xXj1+99x+nKhWXUXlVciJbfEZNl7P53DlIhAPH1nCC9ZEVGTMcAQ2ZB7evjg+KIolOn0cLFv2VFJdZ2LrdQb8Pm+VHwUmwKd3gBnlRz39/GDvZ3c2J9HKZfBQSG7MTxdDrWqepi6BKg1o/FvF/KRlKXBF/vT8fWhS3iofwc8NzwUwZ6OLbovRNT2McAQ2Rg7mRQu9i14C4MbZ2PWHc3AiYwC9A90Q79AV/ioVXhnZxL+uFp9r7FR3bzx9oTeZk3e2MXHdJbiBUIg7nweVu9NxdGL17Hh2GVsPH4Zwzp74pGBARjdwwcqO1nL7RsRtVnsA0PUzv1+pRCzvj2BzBsT6f2Vi70d3nygBx7s28Hk0lNzHb94HavjUhF7Lte4zFklx7hwf/xtQEeEd3TlVAVEbRw78TLAEDXb1cJynMwoxMmMApy8XIgLOcW4s4sXYh7oAW/n1uurculaKX44kYkfEq6YhCiFXIoQT8cbQ80dEeLlBJWdFNoqA7Q3dSBW2sng5aSEt/rPDsM8i0NkGxhgGGCIbJ7BIHA47Ro2J1zBrrPZDQ77vpUgDwc8HhmEiQM7wlnFGYyJrBUDDAMMUZuiN1TPZlxzq4WU3BKk5ZfCYBDGe0TV3L+qTKc3dhLOK9GazH7spJRj4sAATB8ahEAPBwvuERHVhQGGAYaIAAghUFhWiZ/OZmPNwXTjEG6pBBge5oX+gW7o4a9GD381fNWqFu3TQ0TmY4BhgCGivzAYBPan5OPLA+nGWYxv5uZghzAfZ7g7Kox3KFer5FDb2xkn+vO+Mdmfg4IDNolaAwMMAwwR3UJKbjH2nstDYpYGiVc1SMkrgb6eu3/XxVEhg6uDAs43Ak71XDdyjOjqjXF9/Hgmh6iJGGAYYIjIDBWVepzPKUZqXkn1LRDKK1Gsrf5ZWFaJ/JLq/jS5Gm2DnYlHdvXCOw/1hp+L/W2qnqjtYIBhgCGiVlKqrUJesRZF5ZU37vVUhaLySly6VoqvDl2ErsoAZ6Ucr9/XHY8OCuDZGCIzMMAwwBCRBaTkVt8j6mRGIQBgWGdPLHuoNwLcOeKJqDGa8/3dgvORExG1L529nfH9zKFYdF93KOVSHEjJR9SKfVi2MwmFZTpLl0fUpvEMDBFRC0jPL8XCLb/jcNp1ANW3RZg5PBRP3hEMewVnBiaqCy8hMcAQkRUQQiAuOQ/v7TqHc9nFAABvZyX+NqAjKvWG6g7DFdV9aSoqDVDIpMa7eituTM6nlEuhspMZ7/TtqJRhbG8/dHBlJ2FqexhgGGCIyIoYDAI/ns7E+7+cx5WCum+SaQ5HhQwL7u2OqYMDIeUNLqkNYYBhgCEiK6SrMmDT8cv442oRnFV/TpSnVtlBZSdDpd5QfXPKKj20lQZU3Pip0/95w8qzVzU4fbkQADAkxB3vPdwHnTwcLbtjRC2EAYYBhojaKINB4D/xF/HermSUV+phbyfDq9FdMX1oEM/GkM3jKCQiojZKKpVg+h3B+PmluxAZ4oHySj2Wbk/EhE8P4vjF65Yuj8hiGGCIiGxAoIcDvns6Am9P6AUnpRynrxThb5/FY/Z3J3D5epmlyyO67XgJiYjIxuQVa7FidzI2HrsMgwAUMimeHBaM6J4+yC/RIa9YW/0oqYDeAHjduCmll5MS3molAtwc4OWstPRuELEPDAMMEbVHSVkavL0jCQdS8s1et09HF4zu4YPonr7o7O3EWyCQRTDAMMAQUTslhMDe5Fx8sPsC8ku08K4523LjjItEIqm+OWVx9Q0q84q1yCwsx81/+YM9HTG6hw9G9/RFvwBXdg6m24YBhgGGiKjR8oq1iE3KwS+JOThwIR86vcH4mqeTEvf08EF0Tx9EhnpAKecswtR6GGAYYIiImqREW4V9yXn4JTEbe5JyUaytMr7mrJRj2tAgzBoRCkel3IJVUlvFAMMAQ0TUbLoqAw6nXcMvidn45Y8c5BZrAVR3Ap43Ogx/GxAAGS8vUQtigGGAISJqUQaDwC+JOVj2UxIuXasept3DT41F93VHkKcjrhSU40pBGa4UlCNbU4Honr4YHuZl4arJ1jDAMMAQEbUKXZUB/4m/iA9jL6C4oqrediFejtjzyojbVxi1CZyJl4iIWoVCLsXTd4Zg36sjMS2yE+RSCexkEnTycMAdnT2MZ10uXSuDtkpv4WqpPWGvLCIiapC7owJLxvfC6/d1h1wqNfaFEUKgz5u/oFhbhYv5Zejq62zhSqm94BkYIiJqNKVcZtKRVyKRoLOPEwDgQm6xpcqidogBhoiImqWL940Ak1Ni4UqoPWGAISKiZuniXX3ZKCWXAYZuHwYYIiJqFl5CIktggCEiomapuYSUnl+KyptuS0DUmhhgiIioWfxd7OGgkKFSL4yT3hG1NgYYIiJqFqlUgs43zsKk8DIS3SYMMERE1GydORKJbjMGGCIiarYwn+qRSBc4EoluEwYYIiJqNuNcMAwwdJswwBARUbPVzAWTmlcCvcHm7xFMNoABhoiImq2Dmz1UdlLoqgy4fJ0jkaj1McAQEVGzyaQShHpVX0Y6n8ORSNT6GGCIiKhFsB8M3U4MMERE1CK6+PCeSHT7MMAQEVGLMM4Fw8ns6DZggCEiohbRxTgbbwkMHIlErYwBhoiIWkSguwMUMikqKg3ILCy3dDnUxjHAEBFRi5DLpAjxcgTAy0jU+hhgiIioxfCeSHS7MMAQEVGLqZmRl0OpqbUxwBARUYvp4sO5YOj2YIAhIqIWYxyJlFMMITgSiVoPAwwREbWYTh6OkEslKNXpkVVUYelyqA1jgCEiohajkEsR5FkzEomXkaj1MMAQEVGLMt4TiTd1pFbEAENERC3q5hl5iVoLAwwREbWozj4cSk2tjwGGiIhaVM0ZmPM5xajSGyxcDbVVDDBERNSiQrwc4epgh+KKKqw/dtnS5VAbxQBDREQtSimXYe49YQCA939JRmGZzsIVUVvEAENERC1uyuBAdPVxRmFZJVb+esHS5VAbxABDREQtTi6TYvG4HgCAbw5fwnkOqaYWxgBDRESt4o7Onoju6QO9QeCt7Ym8tQC1KAYYIiJqNf+4twcUMin2X8jH7sQcS5dDbQgDDBERtZpADwc8fWcwAOD/diRBW6W3cEXUVjDAEBFRq5o9sjO8nZXIuF6GNQcuWrocaiOaFGBWrVqFoKAgqFQqRERE4OjRo/W2raysxNKlSxEaGgqVSoXw8HDs2rXLpM2bb74JiURi8ujWrVtTSiMiIivjqJRjwdjqv+mf7LmAHA3vUk3NZ3aA2bhxI+bOnYuYmBicOHEC4eHhiI6ORm5ubp3tFy1ahM8//xwff/wxEhMTMXPmTEyYMAEnT540adezZ09kZWUZHwcOHGjaHhERkdV5sG8H9At0RalOj6XbEy1dDrUBZgeYFStW4JlnnsGMGTPQo0cPfPbZZ3BwcMCaNWvqbP/NN9/g9ddfx7333ouQkBDMmjUL9957L95//32TdnK5HL6+vsaHp6dnvTVotVpoNBqTBxERWS+pVIK3xveCVALs+D0Lv53Ps3RJZOPMCjA6nQ4JCQmIior6cwNSKaKiohAfH1/nOlqtFiqVymSZvb19rTMsFy5cgL+/P0JCQjB16lRkZGTUW8eyZcvg4uJifAQEBJizG0REZAG9Orhg2tAgAMDiH8+iopIdeqnpzAow+fn50Ov18PHxMVnu4+OD7OzsOteJjo7GihUrcOHCBRgMBuzevRtbtmxBVlaWsU1ERATWrl2LXbt2YfXq1UhPT8edd96J4uK6Jz5auHAhioqKjI/Ll3mvDSIiWzD3njD4qJW4eK0Mn+1LtXQ5ZMNafRTShx9+iC5duqBbt25QKBSYM2cOZsyYAan0z7ceO3YsHnnkEfTp0wfR0dHYuXMnCgsLsWnTpjq3qVQqoVarTR5ERGT9nFV2eOP+6hl6P41LxcX8UgtXRLbKrADj6ekJmUyGnBzTyYhycnLg6+tb5zpeXl7Ytm0bSktLcenSJZw7dw5OTk4ICQmp931cXV0RFhaGlJQUc8ojIiIbcF9vP9zZxRO6KgPe+PEsZ+ilJjErwCgUCgwYMACxsbHGZQaDAbGxsYiMjLzluiqVCh06dEBVVRV++OEHjB8/vt62JSUlSE1NhZ+fnznlERGRDZBIqjv0KuTVM/TuOJPV8EpEf2H2JaS5c+fiiy++wNdff42kpCTMmjULpaWlmDFjBgDgiSeewMKFC43tjxw5gi1btiAtLQ379+/HmDFjYDAY8NprrxnbzJs3D/v27cPFixdx6NAhTJgwATKZDJMnT26BXSQiImsT5OmIWcNDAQBL/5eI4opKC1dEtkZu7gqTJk1CXl4eFi9ejOzsbPTt2xe7du0yduzNyMgw6d9SUVGBRYsWIS0tDU5OTrj33nvxzTffwNXV1djmypUrmDx5Mq5duwYvLy8MGzYMhw8fhpeXV/P3kIiIrNKsEaH48VQmLl4rw7ojGXjuRqAhagyJaAMXHzUaDVxcXFBUVMQOvURENmTTsct47Yff0cHVHvteHQG5jHe4aU+a8/3NTwoREVnMA3394eZgh8zCcvyaVPeM7kR1YYAhIiKLUdnJMHlwIABg7aF0C1dDtoQBhoiILOrxyE6QSSU4nHYdSVm8NQw1DgMMERFZlJ+LPcb0qp5LbO3Bi5YthmwGAwwREVncjBv3SNp2KhPXS3WWLYZsAgMMERFZ3IBObujVQQ1tlQEbjtV/M1+iGgwwRERkcRKJBNOHBgMAvom/hCq9wcIVkbVjgCEiIqtwfx8/eDgqkFVUgV8Scxpegdo1BhgiIrIKKjsZpkRUD6n+6iCHVNOtMcAQEZHVeGxIJ8ilEhy7WIAl//sD3xy+hL3JuUjJLUa5Tm/p8siKmH0vJCIiotbio1bh/j5+2HbqKr6qY0h1N19nDAnxwJAQD0QEu8PNUXH7iySrwHshERGRVSkqq8SWk1dw6VoZrhSU40pB9c8SbZVJO4kE6OarxvShnTBxYAAkEomFKqamas73NwMMERFZPSEE8kt0OJp+HYfTruFw2jVcyC0xvv5w/454e0IvqOxkFqySzMUAwwBDRNTu5BVrsen4Zbz/SzIMAujpr8Znjw1AgLuDpUujRuLdqImIqN3xclZi9sjO+PapCLg7KvDHVQ3u//gA9p3Ps3RpdBswwBARkU0b2tkT258fhvAAVxSVV2L6V0fx//anWbosamUMMEREZPP8Xe2x6bkhmBIRCCGAd3Ym4XxOsaXLolbEAENERG2CUi7DOxN6I7qnDwwC+OeuZEuXRK2IAYaIiNqU18Z0g0wqwa9JOTh28bqly6FWwgBDRERtSqiXEyYODAAALNuZhDYw2JbqwABDRERtzktRXaCyk+JERiFvDNlGMcAQEVGb46NW4elhIQCAf+46hyq9wcIVUUtjgCEiojbp2eEhcHOwQ2peKb5PuGLpcqiFMcAQEVGbpFbZYc7dXQAAH/x6nnezbmMYYIiIqM16bEggOrjaI0ejxZqD6ZYuh1oQAwwREbVZSrkM86LDAACfxaWiuKLSwhVRS2GAISKiNm18eAeEeDmiWFuFH09dtXQ51EIYYIiIqE2TSiWYMjgQALDuSAbnhWkjGGCIiKjNe7h/RyhkUiRmaXAms8jS5VALYIAhIqI2z81RgbG9fQEA649etnA11BIYYIiIqF2YfOMy0n9PZaJEW2Xhaqi5GGCIiKhdiAh2R4inI0p1evzvNDvz2joGGCIiahckEonxLMz6oxkWroaaiwGGiIjajYcHVHfm/f1KEc6yM69NY4AhIqJ2w91RgeheNZ15eRbGljHAEBFRuzJ5cAAA4MdTV1HKzrw2iwGGiIjalcgQDwR5OKBEW4Xtv7Mzr61igCEionbl5s68645koFJvsHBF1BQS0QbmVNZoNHBxcUFRURHUarWlyyEiIiuXX6JF5LJYVOoF5FIJOnk4INTLCaHeTujm64xR3X3gpJRbusw2rznf3/ztEBFRu+PppMTfR3TGF/vTUKbTIzWvFKl5pUBiDgDAUSHDg/064LEhndDdj/8wtkY8A0NERO2WEALZmgqk5JYgNbcEqXmlOJiSj7T8UmOb/oGueGxIJ9zb2w8qO5kFq217mvP9zQBDRER0EyEE4tOu4bvDGfj5j2xUGaq/Jl0d7PDIgI6YEtEJwZ6OFq6ybWCAYYAhIqJWkKupwKbjl7H+6GVkFpYblw/r7ImpEYEY3dMXMqnEghXaNgYYBhgiImpFeoNAXHIuvjuSgb3Juaj55nxqWDDeuL+HZYuzYezES0RE1IpkUglGdffBqO4+uHy9DO/tOoftv2chLa/E0qW1W5wHhoiIyAwB7g64K8zL0mW0ewwwREREZrKTVfd7KdPpLVxJ+8UAQ0REZKYu3s4AgHPZxWgDXUltEgMMERGRmcJ8nKGQSVFUXonL18sbXoFaHAMMERGRmRRyKbr5VZ+FOZNZZOFq2icGGCIioibo1cEFAAOMpTDAEBERNUHvGwHmLAOMRTDAEBERNUHvm87AsCPv7ccAQ0RE1ARhPs6wk0lQVF6JKwXsyHu7McAQERE1gUIuRVdfduS1FAYYIiKiJurNjrwWwwBDRETURL3YkddiGGCIiIiaiB15LYcBhoiIqIm6+lZ35C0sY0fe240BhoiIqImUchnCfKo78vIy0u3FAENERNQM7MhrGQwwREREzcBbClgGAwwREVEz3HxLAXbkvX0YYIiIiJqhq68z5FIJCsoqkVnIjry3CwMMERFRM6jsbu7Iq7FwNe0HAwwREVEz8c7Utx8DDBERUTP16siOvLcbAwwREVEzsSPv7ccAQ0RE1EzdbnTkvVaqQ1ZRhaXLaRcYYIiIiJpJZSdDlxsdeXkZ6fZoUoBZtWoVgoKCoFKpEBERgaNHj9bbtrKyEkuXLkVoaChUKhXCw8Oxa9euZm2TiIjI2vTuoAbAjry3i9kBZuPGjZg7dy5iYmJw4sQJhIeHIzo6Grm5uXW2X7RoET7//HN8/PHHSExMxMyZMzFhwgScPHmyydskIiKyNrylwO0lEWb2NoqIiMCgQYPwySefAAAMBgMCAgLw/PPPY8GCBbXa+/v74x//+Admz55tXPbwww/D3t4e3377bZO2qdVqodVqjc81Gg0CAgJQVFQEtVptzu4QERG1iN+vFOKBTw7CSSnH8UVRUNnJLF2S1dNoNHBxcWnS97dZZ2B0Oh0SEhIQFRX15wakUkRFRSE+Pr7OdbRaLVQqlckye3t7HDhwoMnbXLZsGVxcXIyPgIAAc3aDiIioxfXyd0EHV3uUaKuw9xyvILQ2swJMfn4+9Ho9fHx8TJb7+PggOzu7znWio6OxYsUKXLhwAQaDAbt378aWLVuQlZXV5G0uXLgQRUVFxsfly5fN2Q0iIqIWJ5VKMC7cHwDw46mrFq6m7Wv1UUgffvghunTpgm7dukGhUGDOnDmYMWMGpNKmv7VSqYRarTZ5EBERWdoDNwLMnuRcaCoqLVxN22ZWivD09IRMJkNOTo7J8pycHPj6+ta5jpeXF7Zt24bS0lJcunQJ586dg5OTE0JCQpq8TSIiImvU3c8ZXbydoKsy4OezdV9FoJZhVoBRKBQYMGAAYmNjjcsMBgNiY2MRGRl5y3VVKhU6dOiAqqoq/PDDDxg/fnyzt0lERGRNJBIJxvetPgvz39O8jNSazL6OM3fuXHzxxRf4+uuvkZSUhFmzZqG0tBQzZswAADzxxBNYuHChsf2RI0ewZcsWpKWlYf/+/RgzZgwMBgNee+21Rm+TiIjIVtT0gzmYko+8Ym0Dramp5OauMGnSJOTl5WHx4sXIzs5G3759sWvXLmMn3IyMDJP+LRUVFVi0aBHS0tLg5OSEe++9F9988w1cXV0bvU0iIiJb0cnDEX0DXHHqciF2/H4V0+8ItnRJbZLZ88BYo+aMIyciImppaw6kY+n2RPQLdMXWv99h6XKs1m2bB4aIiIgadn8fP0glwMmMQmRcK7N0OW0SAwwREVEL81arMDTUEwDwv9/Zmbc1MMAQERG1ggeMk9plWriStokBhoiIqBVE9/KFQibF+ZwSnMvWWLqcNocBhoiIqBW42NthRFcvALy1QGtggCEiImol4/t2AABsPZGJ3OIKC1fTtjDAEBERtZJR3b3h56JCtqYCf1sdj0vXSi1dUpvBAENERNRKVHYybHh2CALdHZBxvQwPrz6Es5lFli6rTWCAISIiakWdPBzx/axI9PBTI79Eh0f/fRiHUvMtXZbNY4AhIiJqZd7OKmx4bgiGhLijRFuF6WuO4b+nr6INTIZvMQwwREREt4FaZYe1MwZjTE9f6PQGvLD+JKJW7MPquFTkaNjB11y8FxIREdFtpDcI/HPXOXwdfxEVlQYAgFQC3BXmhSmDAzG6p6+FK7x9mvP9zQBDRERkAcUVldh5JgvfJ1zBsYsFxuUbnx2CiBAPC1Z2+zTn+1veSjURERHRLTir7DBpUCAmDQpEen4pZnx1FBevlaGgTGfp0mwC+8AQERFZWLCnI7zVKgCAprzKwtXYBgYYIiIiKzDkxmWjH0/z5o+NwQBDRERkBSYO7AiJBDiYco0z9jYCAwwREZEV6OjmgDu7VN/8ceOxyxauxvoxwBAREVmJyYMCAACbE66gUm+wcDXWjQGGiIjISozq7gMPRwXyirXYey7X0uVYNQYYIiIiK6GQS/G3AR0BABt4GemWGGCIiIisyKQbl5HiknORVVRu4WqsFwMMERGRFQnxcsLgYHcYBLD5+BVLl2O1GGCIiIiszOTB1WdhNh67DIPB5u/40yoYYIiIiKzM2F5+UKvkyCwsx/6UfEuXY5UYYIiIiKyMyk6GCf06AAA2HsuwcDXWiQGGiIjICj06OBAAsDsxB/klWgtXY30YYIiIiKxQdz81wgNcUakX+D6BnXn/igGGiIjISk29cRbmuyOX2Jn3LxhgiIiIrNS4cH+oVXJcvl6OfRfyLF2OVWGAISIislL2ChkeGVg9pPrb+EsWrsa6MMAQERFZsakR1ZeR9iTn4vL1MgtXYz0YYIiIiKxYiJcThnX2hBDAuqMcUl2DAYaIiMjKPTakE4DqmXm1VXoLV2MdGGCIiIisXFR3b/iqVbheqsOus9mWLscqMMAQERFZOblMiik3+sJ8w868ABhgiIiIbMKjgwIgl0pw/FIBEq9qLF2OxTHAEBER2QBvtQrRvXwBAN8e4VkYBhgiIiIb8fiNzrzbTmZCU1Fp4WosiwGGiIjIRkQEu6OLtxPKdHpsPZFp6XIsigGGiIjIRkgkEkwaVD0z769JORauxrIYYIiIiGzIsC6eAICESwWo1BssXI3lMMAQERHZkDBvZ7jY26FMp8cf7Xg0EgMMERGRDZFKJRgU5AYAOJp+zcLVWA4DDBERkY0ZHOwOADiaXmDhSiyHAYaIiMjGDA72AAAcu3gdBoOwcDWWwQBDRERkY3r6q+GgkKGovBLnc4stXY5FMMAQERHZGDuZFP0Da/rBXLdwNZbBAENERGSD/uwHwwBDRERENuLmACNE++sHwwBDRERkg/oGuEIhkyK3WItL18osXc5txwBDRERkg1R2MvTp6AKgfV5GYoAhIiKyUcbLSBcZYIiIiMhGtOeOvAwwRERENmpAJzdIJUDG9TJkFZVbupzbigGGiIjIRjmr7NDTv332g2GAISIismGDgqovIx1rZ/1gGGCIiIhsWHvtB8MAQ0REZMMGBVXfUuB8Tgmul+osXM3twwBDRERkwzyclOji7QSgfV1GYoAhIiKycYNuXEY61o4uIzHAEBER2biIGwEm9lwuDIb2cV8kBhgiIiIbF9XdB84qOdLzSxF3PtfS5dwWDDBEREQ2zlEpx+TBgQCA/7c/3cLV3B4MMERERG3AtKFBkEklOJR6DYlXNZYup9UxwBAREbUBHVztMbaXLwBgzcG2fxaGAYaIiKiNeGpYMADgv6euIre4wsLVtC4GGCIiojaiX6Ab+ge6Qqc34Nv4S5Yup1UxwBAREbUhTw0LAQB8eyQDFZV6C1fTehhgiIiI2pDonj7o4GqP66U6bD2ZaelyWk2TAsyqVasQFBQElUqFiIgIHD169JbtV65cia5du8Le3h4BAQF4+eWXUVHx57W5N998ExKJxOTRrVu3ppRGRETUrsllUsy4IwgAsOZAOoRomxPbmR1gNm7ciLlz5yImJgYnTpxAeHg4oqOjkZtb98Q569atw4IFCxATE4OkpCR8+eWX2LhxI15//XWTdj179kRWVpbxceDAgabtERERUTs3cVAAHBUyXMgtwW8X8i1dTqswO8CsWLECzzzzDGbMmIEePXrgs88+g4ODA9asWVNn+0OHDuGOO+7AlClTEBQUhNGjR2Py5Mm1ztrI5XL4+voaH56envXWoNVqodFoTB5ERERUTa2yw8RBAQCAz/eltsmzMGYFGJ1Oh4SEBERFRf25AakUUVFRiI+Pr3OdoUOHIiEhwRhY0tLSsHPnTtx7770m7S5cuAB/f3+EhIRg6tSpyMjIqLeOZcuWwcXFxfgICAgwZzeIiIjavCfvCIadrHpiu2+P1P+daqvMCjD5+fnQ6/Xw8fExWe7j44Ps7Ow615kyZQqWLl2KYcOGwc7ODqGhoRgxYoTJJaSIiAisXbsWu3btwurVq5Geno4777wTxcXFdW5z4cKFKCoqMj4uX75szm4QERG1eQHuDpg/pro/6VvbE9vc7LytPgopLi4O77zzDj799FOcOHECW7ZswY4dO/DWW28Z24wdOxaPPPII+vTpg+joaOzcuROFhYXYtGlTndtUKpVQq9UmDyIiIjL11LBgjOrmDV2VAXPWnUCptsrSJbUYswKMp6cnZDIZcnJyTJbn5OTA19e3znXeeOMNPP7443j66afRu3dvTJgwAe+88w6WLVsGg8FQ5zqurq4ICwtDSkqKOeURERHRTSQSCZY/Eg5ftQpp+aV448ezli6pxZgVYBQKBQYMGIDY2FjjMoPBgNjYWERGRta5TllZGaRS07eRyWQAUG+nopKSEqSmpsLPz8+c8oiIiOgv3B0V+GhyP0glwJYTmfg+4YqlS2oRZl9Cmjt3Lr744gt8/fXXSEpKwqxZs1BaWooZM2YAAJ544gksXLjQ2H7cuHFYvXo1NmzYgPT0dOzevRtvvPEGxo0bZwwy8+bNw759+3Dx4kUcOnQIEyZMgEwmw+TJk1toN4mIiNqvwcHumHtPGADgjW1nkZJbYuGKmk9u7gqTJk1CXl4eFi9ejOzsbPTt2xe7du0yduzNyMgwOeOyaNEiSCQSLFq0CJmZmfDy8sK4cePw9ttvG9tcuXIFkydPxrVr1+Dl5YVhw4bh8OHD8PLyaoFdJCIiolkjOiM+7RoOplzDnHUnsP35YZDLbHdCfoloA4PDNRoNXFxcUFRUxA69RERE9cgtrsDoD35DYVklVk/tj7G9LdtVoznf37YbvYiIiMgs3s4qTI0IBACsPXTRssU0EwMMERFROzI1ohNkUgmOpF/HuWzbnRuGAYaIiKgd8Xe1x+ge1f1Wvz50ycLVNB0DDBERUTszbWgQAGDbyUwUlVVatpgmYoAhIiJqZyKC3dHN1xnllXpsTrDN2/EwwBAREbUzEonEeBbmP/GXoDfY3oBkBhgiIqJ2aHxff6hVcmRcL0Nccq6lyzEbAwwREVE75KCQY9KgAAC2OaSaAYaIiKidenxIECQSYP+FfKTm2dbtBRhgiIiI2qlADweM6uYNAPgm3raGVDPAEBERtWNPRAYBAL5PuIISbZVlizEDAwwREVE7dmcXTwR5OKBEW4UDF/ItXU6jMcAQERG1YxKJBJGhngCAkxkFFq6m8RhgiIiI2rkBndwAAAmXGGCIiIjIRtQEmN8zi6CrMli4msZhgCEiImrngjwc4O6ogK7KgD+uFlm6nEZhgCEiImrnJBIJ+ge6ArCdy0gMMERERIT+Ny4jnbCRjrwMMERERIQBgX925BXC+m/uyABDRERE6NPRFXKpBDkaLTILyy1dToMYYIiIiAj2Chl6+qsB2EY/GAYYIiIiAgD0u3EZ6WRGoWULaQQGGCIiIgJgWxPaMcAQERERgD8DTGKWBmU6676xIwMMERERAQD8Xe3h56KC3iBw+rJ1T2jHAENERERGtjIfDAMMERERGd08H4w1Y4AhIiIio5vPwFjzhHYMMERERGTUw08NpVyKwrJKpOWXWrqcejHAEBERkZFCLkV4R1cA1n0ZiQGGiIiITBgvIzHAEBERka2whQntGGCIiIjIRP9AVwDAhdwSFJVVWraYejDAEBERkQkPJyWCPBwAACcuW+dZGAYYIiIiqqWnvwsAID3POkciMcAQERFRLV7OSgBAfonWwpXUjQGGiIiIaqkJMHnFDDBERERkI7ycbgQYnoEhIiIiW8FLSERERGRzPJ14CYmIiIhszJ9nYHQwGKzvpo4MMERERFSLh5MCAKA3CBSWW99kdgwwREREVIudTAo3BzsA1nkZiQGGiIiI6mTNQ6kZYIiIiKhO1jwSiQGGiIiI6uRlxSORGGCIiIioTp5WPJkdAwwRERHViX1giIiIyOawDwwRERHZHGuejZcBhoiIiOrES0hERERkc2oCzPUyHar0BgtXY4oBhoiIiOrk5qCAVAIIAVwv1Vm6HBMMMERERFQnmVQCjxv9YHKt7DISAwwRERHVq2YyO2sbicQAQ0RERPXytNKOvAwwREREVC8vK52NlwGGiIiI6mWtQ6kZYIiIiKhenk4KAEB+CUchERERkY348wxMhYUrMcUAQ0RERPXiJSQiIiKyOd7GGzryEhIRERHZCE8nJSQSwE4mQaUV3U5AbukCiIiIyHq52Nvhwv+NhVxmXec8GGCIiIioXhKJBHKZxNJl1GJdcYqIiIioERhgiIiIyOYwwBAREZHNYYAhIiIim9OkALNq1SoEBQVBpVIhIiICR48evWX7lStXomvXrrC3t0dAQABefvllVFSYzuhn7jaJiIio/TI7wGzcuBFz585FTEwMTpw4gfDwcERHRyM3N7fO9uvWrcOCBQsQExODpKQkfPnll9i4cSNef/31Jm+TiIiI2jeJEEKYs0JERAQGDRqETz75BABgMBgQEBCA559/HgsWLKjVfs6cOUhKSkJsbKxx2SuvvIIjR47gwIEDTdrmX2k0Gri4uKCoqAhqtdqc3SEiIiILac73t1lnYHQ6HRISEhAVFfXnBqRSREVFIT4+vs51hg4dioSEBOMlobS0NOzcuRP33ntvk7ep1Wqh0WhMHkRERNR+mDWRXX5+PvR6PXx8fEyW+/j44Ny5c3WuM2XKFOTn52PYsGEQQqCqqgozZ840XkJqyjaXLVuGJUuWmFM6ERERtSGtPgopLi4O77zzDj799FOcOHECW7ZswY4dO/DWW281eZsLFy5EUVGR8XH58uUWrJiIiIisnVlnYDw9PSGTyZCTk2OyPCcnB76+vnWu88Ybb+Dxxx/H008/DQDo3bs3SktL8eyzz+If//hHk7apVCqhVCrNKZ2IiIjaELPOwCgUCgwYMMCkQ67BYEBsbCwiIyPrXKesrAxSqenbyGQyAIAQoknbJCIiovbN7Js5zp07F9OmTcPAgQMxePBgrFy5EqWlpZgxYwYA4IknnkCHDh2wbNkyAMC4ceOwYsUK9OvXDxEREUhJScEbb7yBcePGGYNMQ9skIiIiupnZAWbSpEnIy8vD4sWLkZ2djb59+2LXrl3GTrgZGRkmZ1wWLVoEiUSCRYsWITMzE15eXhg3bhzefvvtRm+zITUjwTkaiYiIyHbUfG+bOaMLgCbMA2ONrly5goCAAEuXQURERE1w+fJldOzY0ax12kSAMRgMuHr1KpydnSGRSFp02xqNBgEBAbh8+XK7nCSvve8/wGPQ3vcf4DFo7/sP8Bi01v4LIVBcXAx/f/9a/WUbYvYlJGsklUrNTm7mUqvV7fJDW6O97z/AY9De9x/gMWjv+w/wGLTG/ru4uDRpPd6NmoiIiGwOAwwRERHZHAaYBiiVSsTExLTbifPa+/4DPAbtff8BHoP2vv8Aj4E17n+b6MRLRERE7QvPwBAREZHNYYAhIiIim8MAQ0RERDaHAYaIiIhsDgNMA1atWoWgoCCoVCpERETg6NGjli6pQcuWLcOgQYPg7OwMb29vPPjgg0hOTjZpM2LECEgkEpPHzJkzTdpkZGTgvvvug4ODA7y9vfHqq6+iqqrKpE1cXBz69+8PpVKJzp07Y+3atbXqud3H8M0336y1b926dTO+XlFRgdmzZ8PDwwNOTk54+OGHkZOTY7INW933GkFBQbWOgUQiwezZswG0vd//b7/9hnHjxsHf3x8SiQTbtm0zeV0IgcWLF8PPzw/29vaIiorChQsXTNpcv34dU6dOhVqthqurK5566imUlJSYtPn9999x5513QqVSISAgAP/85z9r1bJ582Z069YNKpUKvXv3xs6dO82upSX3v7KyEvPnz0fv3r3h6OgIf39/PPHEE7h69arJNur6zLz77rs2sf8NHQMAmD59eq39GzNmjEmbtvoZAFDn3wOJRILly5cb29jcZ0BQvTZs2CAUCoVYs2aN+OOPP8QzzzwjXF1dRU5OjqVLu6Xo6Gjx1VdfibNnz4pTp06Je++9VwQGBoqSkhJjm+HDh4tnnnlGZGVlGR9FRUXG16uqqkSvXr1EVFSUOHnypNi5c6fw9PQUCxcuNLZJS0sTDg4OYu7cuSIxMVF8/PHHQiaTiV27dhnbWOIYxsTEiJ49e5rsW15envH1mTNnioCAABEbGyuOHz8uhgwZIoYOHdom9r1Gbm6uyf7v3r1bABB79+4VQrS93//OnTvFP/7xD7FlyxYBQGzdutXk9XfffVe4uLiIbdu2idOnT4sHHnhABAcHi/LycmObMWPGiPDwcHH48GGxf/9+0blzZzF58mTj60VFRcLHx0dMnTpVnD17Vqxfv17Y29uLzz//3Njm4MGDQiaTiX/+858iMTFRLFq0SNjZ2YkzZ86YVUtL7n9hYaGIiooSGzduFOfOnRPx8fFi8ODBYsCAASbb6NSpk1i6dKnJZ+LmvxnWvP8NHQMhhJg2bZoYM2aMyf5dv37dpE1b/QwIIUz2OysrS6xZs0ZIJBKRmppqbGNrnwEGmFsYPHiwmD17tvG5Xq8X/v7+YtmyZRasyny5ubkCgNi3b59x2fDhw8WLL75Y7zo7d+4UUqlUZGdnG5etXr1aqNVqodVqhRBCvPbaa6Jnz54m602aNElER0cbn1viGMbExIjw8PA6XyssLBR2dnZi8+bNxmVJSUkCgIiPjxdC2Pa+1+fFF18UoaGhwmAwCCHa9u//r3+8DQaD8PX1FcuXLzcuKywsFEqlUqxfv14IIURiYqIAII4dO2Zs89NPPwmJRCIyMzOFEEJ8+umnws3Nzbj/Qggxf/580bVrV+PziRMnivvuu8+knoiICPHcc881upbmquvL66+OHj0qAIhLly4Zl3Xq1El88MEH9a5jK/svRN3HYNq0aWL8+PH1rtPePgPjx48Xd999t8kyW/sM8BJSPXQ6HRISEhAVFWVcJpVKERUVhfj4eAtWZr6ioiIAgLu7u8ny7777Dp6enujVqxcWLlyIsrIy42vx8fHo3bs3fHx8jMuio6Oh0Wjwxx9/GNvcfHxq2tQcH0sewwsXLsDf3x8hISGYOnUqMjIyAAAJCQmorKw0qalbt24IDAw01mTr+/5XOp0O3377LZ588kmTm5225d//zdLT05GdnW1Sh4uLCyIiIkx+566urhg4cKCxTVRUFKRSKY4cOWJsc9ddd0GhUBjbREdHIzk5GQUFBcY2tzomjanldigqKoJEIoGrq6vJ8nfffRceHh7o168fli9fbnLJsC3sf1xcHLy9vdG1a1fMmjUL165dM77Wnj4DOTk52LFjB5566qlar9nSZ6BN3MyxNeTn50Ov15v8AQcAHx8fnDt3zkJVmc9gMOCll17CHXfcgV69ehmXT5kyBZ06dYK/vz9+//13zJ8/H8nJydiyZQsAIDs7u859r3ntVm00Gg3Ky8tRUFBgkWMYERGBtWvXomvXrsjKysKSJUtw55134uzZs8jOzoZCoaj1h9vHx6fB/ap57VZtLL3vddm2bRsKCwsxffp047K2/Pv/q5p666rj5n3x9vY2eV0ul8Pd3d2kTXBwcK1t1Lzm5uZW7zG5eRsN1dLaKioqMH/+fEyePNnkpnwvvPAC+vfvD3d3dxw6dAgLFy5EVlYWVqxYYazdlvd/zJgxeOihhxAcHIzU1FS8/vrrGDt2LOLj4yGTydrVZ+Drr7+Gs7MzHnroIZPltvYZYIBp42bPno2zZ8/iwIEDJsufffZZ43/37t0bfn5+GDVqFFJTUxEaGnq7y2xRY8eONf53nz59EBERgU6dOmHTpk2wt7e3YGWW8eWXX2Ls2LHw9/c3LmvLv3+qX2VlJSZOnAghBFavXm3y2ty5c43/3adPHygUCjz33HNYtmyZVU0f31SPPvqo8b979+6NPn36IDQ0FHFxcRg1apQFK7v91qxZg6lTp0KlUpkst7XPAC8h1cPT0xMymazW6JScnBz4+vpaqCrzzJkzB9u3b8fevXvRsWPHW7aNiIgAAKSkpAAAfH1969z3mtdu1UatVsPe3t5qjqGrqyvCwsKQkpICX19f6HQ6FBYW1ltTW9r3S5cu4ddff8XTTz99y3Zt+fdf8163qsPX1xe5ubkmr1dVVeH69est8rm4+fWGamktNeHl0qVL2L17t8nZl7pERESgqqoKFy9eBGD7+/9XISEh8PT0NPnMt/XPAADs378fycnJDf5NAKz/M8AAUw+FQoEBAwYgNjbWuMxgMCA2NhaRkZEWrKxhQgjMmTMHW7duxZ49e2qd8qvLqVOnAAB+fn4AgMjISJw5c8bkf+iaP3o9evQwtrn5+NS0qTk+1nIMS0pKkJqaCj8/PwwYMAB2dnYmNSUnJyMjI8NYU1va96+++gre3t647777btmuLf/+g4OD4evra1KHRqPBkSNHTH7nhYWFSEhIMLbZs2cPDAaDMdxFRkbit99+Q2VlpbHN7t270bVrV7i5uRnb3OqYNKaW1lATXi5cuIBff/0VHh4eDa5z6tQpSKVS42UVW97/uly5cgXXrl0z+cy35c9AjS+//BIDBgxAeHh4g22t/jNgVpffdmbDhg1CqVSKtWvXisTERPHss88KV1dXk5EZ1mjWrFnCxcVFxMXFmQyHKysrE0IIkZKSIpYuXSqOHz8u0tPTxY8//ihCQkLEXXfdZdxGzTDa0aNHi1OnToldu3YJLy+vOofRvvrqqyIpKUmsWrWqzmG0t/sYvvLKKyIuLk6kp6eLgwcPiqioKOHp6Slyc3OFENXDqAMDA8WePXvE8ePHRWRkpIiMjGwT+34zvV4vAgMDxfz5802Wt8Xff3FxsTh58qQ4efKkACBWrFghTp48aRxl8+677wpXV1fx448/it9//12MHz++zmHU/fr1E0eOHBEHDhwQXbp0MRlCW1hYKHx8fMTjjz8uzp49KzZs2CAcHBxqDSGVy+XiX//6l0hKShIxMTF1DiFtqJaW3H+dTiceeOAB0bFjR3Hq1CmTvwk1o0kOHTokPvjgA3Hq1CmRmpoqvv32W+Hl5SWeeOIJm9j/ho5BcXGxmDdvnoiPjxfp6eni119/Ff379xddunQRFRUVxm201c9AjaKiIuHg4CBWr15da31b/AwwwDTg448/FoGBgUKhUIjBgweLw4cPW7qkBgGo8/HVV18JIYTIyMgQd911l3B3dxdKpVJ07txZvPrqqybzgAghxMWLF8XYsWOFvb298PT0FK+88oqorKw0abN3717Rt29foVAoREhIiPE9bna7j+GkSZOEn5+fUCgUokOHDmLSpEkiJSXF+Hp5ebn4+9//Ltzc3ISDg4OYMGGCyMrKMtmGre77zX7++WcBQCQnJ5ssb4u//71799b5mZ82bZoQonro5htvvCF8fHyEUqkUo0aNqnVcrl27JiZPniycnJyEWq0WM2bMEMXFxSZtTp8+LYYNGyaUSqXo0KGDePfdd2vVsmnTJhEWFiYUCoXo2bOn2LFjh8nrjamlJfc/PT293r8JNfMCJSQkiIiICOHi4iJUKpXo3r27eOedd0y+3K15/xs6BmVlZWL06NHCy8tL2NnZiU6dOolnnnmmVpBuq5+BGp9//rmwt7cXhYWFtda3xc+ARAghzDtnQ0RERGRZ7ANDRERENocBhoiIiGwOAwwRERHZHAYYIiIisjkMMERERGRzGGCIiIjI5jDAEBERkc1hgCEiIiKbwwBDRA2Ki4uDRCKpdRNMIiJLYYAholpGjBiBl156yfh86NChyMrKgouLi8VqYogiopvJLV0AEVk/hUJh9q3uiYhaE8/AEJGJ6dOnY9++ffjwww8hkUggkUiwdu1ak7Mfa9euhaurK7Zv346uXbvCwcEBf/vb31BWVoavv/4aQUFBcHNzwwsvvAC9Xm/ctlarxbx589ChQwc4OjoiIiICcXFxxtcvXbqEcePGwc3NDY6OjujZsyd27tyJixcvYuTIkQAANzc3SCQSTJ8+HQCwa9cuDBs2DK6urvDw8MD999+P1NRU4zYvXrwIiUSCTZs24c4774S9vT0GDRqE8+fP49ixYxg4cCCcnJwwduxY5OXlmRyHBx98EEuWLIGXlxfUajVmzpwJnU7XegefiBqNZ2CIyMSHH36I8+fPo1evXli6dCkA4I8//qjVrqysDB999BE2bNiA4uJiPPTQQ5gwYQJcXV2xc+dOpKWl4eGHH8Ydd9yBSZMmAQDmzJmDxMREbNiwAf7+/ti6dSvGjBmDM2fOoEuXLpg9ezZ0Oh1+++03ODo6IjExEU5OTggICMAPP/yAhx9+GMnJyVCr1bC3twcAlJaWYu7cuejTpw9KSkqwePFiTJgwAadOnYJU+ue/0WJiYrBy5UoEBgbiySefxJQpU+Ds7IwPP/wQDg4OmDhxIhYvXozVq1cb14mNjYVKpUJcXBwuXryIGTNmwMPDA2+//XZr/gqIqDHMvn81EbV5w4cPFy+++KLx+d69ewUAUVBQIIQQ4quvvhIAREpKirHNc889JxwcHERxcbFxWXR0tHjuueeEEEJcunRJyGQykZmZafJeo0aNEgsXLhRCCNG7d2/x5ptv1lnTX2uoT15engAgzpw5I4QQIj09XQAQ/+///T9jm/Xr1wsAIjY21rhs2bJlomvXrsbn06ZNE+7u7qK0tNS4bPXq1cLJyUno9fpb1kBErY+XkIioSRwcHBAaGmp87uPjg6CgIDg5OZksy83NBQCcOXMGer0eYWFhcHJyMj727dtnvOTzwgsv4P/+7/9wxx13ICYmBr///nuDdVy4cAGTJ09GSEgI1Go1goKCAAAZGRkm7fr06WNSFwD07t27zlprhIeHw8HBwfg8MjISJSUluHz5coN1EVHr4iUkImoSOzs7k+cSiaTOZQaDAQBQUlICmUyGhIQEyGQyk3Y1oefpp59GdHQ0duzYgV9++QXLli3D+++/j+eff77eOsaNG4dOnTrhiy++gL+/PwwGA3r16lWrr8rNtUkkkjqX1dRKRNaPZ2CIqBaFQmHS+bYl9OvXD3q9Hrm5uejcubPJ4+YRTgEBAZg5cya2bNmCV155BV988YWxJgAmdV27dg3JyclYtGgRRo0ahe7du6OgoKDFaj59+jTKy8uNzw8fPmzsk0NElsUAQ0S1BAUF4ciRI7h48SLy8/Nb5MxEWFgYpk6diieeeAJbtmxBeno6jh49imXLlmHHjh0AgJdeegk///wz0tPTceLECezduxfdu3cHAHTq1AkSiQTbt29HXl4eSkpK4ObmBg8PD/z73/9GSkoK9uzZg7lz5za71ho6nQ5PPfUUEhMTsXPnTsTExGDOnDkmnYOJyDL4fyER1TJv3jzIZDL06NEDXl5etfqTNNVXX32FJ554Aq+88gq6du2KBx98EMeOHUNgYCCA6rMrs2fPRvfu3TFmzBiEhYXh008/BQB06NABS5YswYIFC+Dj42MMEhs2bEBCQgJ69eqFl19+GcuXL2+RWgFg1KhR6NKlC+666y5MmjQJDzzwAN58880W2z4RNZ1ECCEsXQQRkbWZPn06CgsLsW3bNkuXQkR14BkYIiIisjkMMERERGRzeAmJiIiIbA7PwBAREZHNYYAhIiIim8MAQ0RERDaHAYaIiIhsDgMMERER2RwGGCIiIrI5DDBERERkcxhgiIiIyOb8f4iA9oY6VO1oAAAAAElFTkSuQmCC", + "image/png": 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", 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" ] @@ -218,7 +4451,8 @@ } ], "source": [ - "res.curves().plot()\n", + "c = res.curves().plot()\n", + "c.set_xlabel('Time (ms)')\n", "plt.show()" ] }, @@ -231,7 +4465,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -267,38 +4501,42 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ - "variables_mapping.add_standard_model_final_state_values('1042_131', 'Upu_value')\n", - "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175, report_node)" + "network.clone_variant('InitialState', 'TCBCase')\n", + "network.set_working_variant('TCBCase')\n", + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 300)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Display final state values " + "Display curve" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - " values\n", - "variables \n", - "NETWORK_1042_131_Upu_value 0.8069\n" - ] + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "print(res.final_state_values())" + "c = res.curves().plot()\n", + "c.set_xlabel('Time (ms)')\n", + "plt.show()" ] } ], From bff87a003e6f7b5ca53982c8692c9f7862989fc9 Mon Sep 17 00:00:00 2001 From: Joy El Feghali Date: Mon, 10 Feb 2025 16:04:55 +0100 Subject: [PATCH 04/14] Add description to Nordic test case Signed-off-by: Joy El Feghali --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 36 ++++++++++++++++++++--- 1 file changed, 32 insertions(+), 4 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index d8d2f80..55b38c0 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -11,7 +11,10 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "TODO - description" + "The Nordic test system is a variation of the so-called Nordic 32-bus system, which was created by the CIGRE Task Force 38-02-08 in 1995 to illustrate the voltage collapse in Sweden that happened in the year 1983. \n", + "The test case consists of four areas: an equivalent simplified network that has the biggest generators and therefore serves usually as the system reference, the northern region with few loads and more generation, a central area with more load than generation and a southern region loosely connected to the rest of the system.\n", + "One important characteristic of the system is the high power transfer from the North to the Central area. This characteristic is what ultimately results in long-term voltage collapse if the power transfer capability is affected, e.g. by losing one of the transmission lines that connect both areas.\n", + "The system comprises 20 generators (nineteen generators and one synchronous condenser) that are hydro and thermal generations. All loads are connected to 20 kV buses and controlled by Load Tap Changers (LTC)." ] }, { @@ -4339,7 +4342,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Add generators dynamic models" + "Add generators dynamic models : \n", + "Out of the total of twenty generators, the Equivalent and the North networks have twelve hydro generators that are modeled by salient-pole machines (GeneratorSynchronousThreeWindingsGoverNordicVRNordic). The two biggest generators belong to the Equivalent grid while the North area has ten generators. On the other hand, there are seven thermal generators modeled by round-rotor machines (GeneratorSynchronousFourWindingsPmConstVRNordic), two of them belong to the small South region, and the remaining five to the Central one that also has a synchronous condenser that is modeled as a salient-pole machine (GeneratorSynchronousThreeWindingsPmConstVRNordic)." ] }, { @@ -4379,7 +4383,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Add node fault and disconnect line event" + "Add node fault and disconnect line event:\n", + "The scenario consists of a three-phase fault at bus 4032 with a subsequent opening of the line 4032-4044 without further re-connection." ] }, { @@ -4431,7 +4436,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Display curve" + "Display curve " ] }, { @@ -4456,6 +4461,14 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Comment on the result:\n", + "The line 4032-4044 is tripped 0.1 s later. The system is short-term stable and it settles to a new equilibrium in 30 s. At around 35 s, the LTCs start acting attempting to restore the distribution voltage and hence the load consumption. The action of the LTC forces the generators to increase their reactive power injection and therefore their field current. Due to the actions of the LTCs, the OELs of some generators limit the field current. This leads to the voltage collapse depicted in the figure." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -4463,6 +4476,13 @@ "## 4 - Second simulation with tap changer blocking automation system" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Add a tap changer blocking automaton that will block the transformer when the monitored voltage is below a certain threshold" + ] + }, { "cell_type": "code", "execution_count": 10, @@ -4538,6 +4558,14 @@ "c.set_xlabel('Time (ms)')\n", "plt.show()" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Comment on the result :\n", + "When adding a Tap Changer Blocking Automaton, that blocks the LTCs when the voltage at bus 1042 is below 120kV, the voltage collapse is avoided, as shown in the figure." + ] } ], "metadata": { From 00fe62d9369bd1da2b7ef7fbf7991c9d5829abb5 Mon Sep 17 00:00:00 2001 From: Joy El Feghali Date: Tue, 11 Feb 2025 13:37:00 +0100 Subject: [PATCH 05/14] Add more detailed descriptions on the events Signed-off-by: Joy El Feghali --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index 55b38c0..3aa7835 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -4466,7 +4466,7 @@ "metadata": {}, "source": [ "Comment on the result:\n", - "The line 4032-4044 is tripped 0.1 s later. The system is short-term stable and it settles to a new equilibrium in 30 s. At around 35 s, the LTCs start acting attempting to restore the distribution voltage and hence the load consumption. The action of the LTC forces the generators to increase their reactive power injection and therefore their field current. Due to the actions of the LTCs, the OELs of some generators limit the field current. This leads to the voltage collapse depicted in the figure." + "The line 4032-4044 is tripped at 1.1s, 0.1 s after the fault occurred. The system tends to settle to a new equilibrium around 30 s, where the voltage rate of change is slow. At around 34 s, the LTCs start acting, by changing taps several times, attempting to restore the distribution voltage and hence the load consumption. It can be seen in the figure with the different spikes where the LTC action, leads to an increase in the voltage level. The action of the LTC forces the generators to increase their reactive power injection and therefore their field current. Due to the actions of the LTCs, the OELs of some generators limit the field current. This leads to the voltage collapse depicted in the figure." ] }, { From d2d045a406579f7cb5f682c004d9236875f04cd3 Mon Sep 17 00:00:00 2001 From: lisrte Date: Tue, 11 Feb 2025 16:56:49 +0100 Subject: [PATCH 06/14] Review fix Replace automaton with automation system Signed-off-by: lisrte --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 4287 +-------------------- 1 file changed, 32 insertions(+), 4255 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index 3aa7835..e3c4530 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -32,6 +32,7 @@ "source": [ "!curl -L $(curl -s -L -X GET https://api.github.com/repos/dynawo/dynawo/releases/latest | grep \"Dynawo_Linux\" | grep url | cut -d '\"' -f 4) -o Dynawo_Linux_latest.zip\n", "!unzip Dynawo_Linux_latest.zip > /dev/null 2>&1\n", + "!rm Dynawo_Linux_latest.zip \n", "!./dynawo/dynawo.sh help" ] }, @@ -48,7 +49,7 @@ "metadata": {}, "outputs": [], "source": [ - "pip install pypowsybl" + "pip install pypowsybl matplotlib pypowsybl-jupyter" ] }, { @@ -57,9 +58,9 @@ "metadata": {}, "outputs": [], "source": [ - "!mkdir /home/USER/.itools/\n", - "!cp /home/USER/dynawo/nordic case/config.yml /home/USER/.itools/\n", - "!cat /home/USER/.itools/config.yml" + "!mkdir /home/$USER/.itools/\n", + "!cp config.yml /home/$USER/.itools/\n", + "!cat /home/$USER/.itools/config.yml" ] }, { @@ -71,7 +72,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -79,4253 +80,27 @@ "import pypowsybl.dynamic as dyn\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", - "import os.path" + "import os.path\n", + "from pypowsybl_jupyter import display_nad" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { - "image/svg+xml": [ - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - 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" \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 591\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 700\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -700\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -1,080\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 1,080\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 100\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -100\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -600\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 600\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 800\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -800\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -346\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 348\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 500\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -500\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 235\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -233\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 235\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -233\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -530\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 530\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -1,060\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 1,060\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 590\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -590\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -69\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 69\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -69\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 69\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -300\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -2,138\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 2,138\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " 2,000\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " -2,000\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
1011_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
138.0 kV / 57.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1012_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
138.2 kV / 61.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1013_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
137.1 kV / 65.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1014_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
137.9 kV / 68.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1021_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
134.0 kV / 66.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1022_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
136.7 kV / 45.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1041_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
131.6 kV / -17.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1042_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
131.9 kV / -3.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1043_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
133.6 kV / -12.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1044_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
130.9 kV / -3.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
1045_130
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
131.4 kV / -7.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
2031_220
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
226.1 kV / 27.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
2032_220
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
235.3 kV / 40.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4011_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
409.0 kV / 56.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4012_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
409.4 kV / 58.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4021_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
419.5 kV / 28.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4022_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
397.9 kV / 43.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4031_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
414.7 kV / 24.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4032_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
419.5 kV / 19.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4041_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
420.2 kV / 9.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4042_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
417.2 kV / 6.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4043_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
414.8 kV / 0.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4044_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
415.8 kV / 0.0°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4045_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
421.4 kV / -4.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4046_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
414.3 kV / 0.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4047_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
423.6 kV / 4.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4051_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
426.4 kV / -6.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4061_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
415.5 kV / 6.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4062_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
422.4 kV / 9.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4063_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
421.4 kV / 13.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4071_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
419.4 kV / 59.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
4072_400
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
423.6 kV / 60.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B01___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -20.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B02___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -6.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B03___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / -15.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B04___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -6.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B05___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / -10.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B11___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.1 kV / 54.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B12___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / 58.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B13___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 62.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B22___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 42.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B31___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.1 kV / 24.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B32___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / 37.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B41___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 7.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B42___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 4.0°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B43___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -2.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B46___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -2.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B47___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 1.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B51___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / -9.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B61___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 3.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B62___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / 7.0°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B63___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.0 kV / 10.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B71___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
20.1 kV / 56.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
B72___20
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
19.9 kV / 57.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG01__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
16.0 kV / 66.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG02__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.8 kV / 69.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG03__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.9 kV / 74.5°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG04__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.5 kV / 72.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG05__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.4 kV / 51.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG06__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.1 kV / 4.8°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG07__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.2 kV / -4.7°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG08__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.7 kV / 47.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG09__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.0 kV / 62.6°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG10__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.2 kV / 65.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG11__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.3 kV / 35.2°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG12__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.3 kV / 32.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG13__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.3 kV / 9.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG14__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.7 kV / 14.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG15__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.7 kV / 12.0°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG16__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.8 kV / 0.1°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG17__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.1 kV / 17.4°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG18__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.5 kV / 20.9°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG19__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.5 kV / 64.3°
\n", - "
\n", - " \n", - " \n", - "
\n", - "
BG20__15
\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
\n", - "
\n", - "
15.3 kV / 64.2°
\n", - "
\n", - " \n", - " \n", - "\n" - ], + "application/vnd.jupyter.widget-view+json": { + "model_id": "5553c204da48470c941f93591c6232d7", + "version_major": 2, + "version_minor": 1 + }, "text/plain": [ - "" + "NadWidget(diagram_data={'svg_data': '\\n" ] @@ -4457,7 +232,8 @@ ], "source": [ "c = res.curves().plot()\n", - "c.set_xlabel('Time (ms)')\n", + "plt.gca().xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))\n", + "c.set_xlabel('Time')\n", "plt.show()" ] }, @@ -4485,7 +261,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 50, "metadata": {}, "outputs": [], "source": [ @@ -4521,7 +297,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 51, "metadata": {}, "outputs": [], "source": [ @@ -4539,12 +315,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 52, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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o0aP11vXp0we7d+9GcnIypkyZYvWldjP69u0LDw8P7N6927JMq9UiOzvb0lfom2++wfHjxy1flv/+978B1F4NmzdvnuVzn3/+OR577DF8/vnnuPfee9EWzGYzqqqqWmRbXbt2hUwmQ2pqqtXy8+fPQ6fTWQXSxowfPx4GgwE7duzAhg0bMH36dMu6M2fO4MqVK1i5ciXuvPNOxMTEoLCwsNHtBQcHIz8/3yrY/H5ofmhoKDQaDc6fP28V5KOjoxEVFdWkmm8Ubz8REbWQ2NhYTJ8+HW+//Xa9dYWFhTAYDFbLAgMDm3wbysvLC4MGDcI777yD22+/3dJ5Vy6XWy3//famTp2KjRs3YubMmXj99dcxYsQI6PV6rF69Glu3bsXGjRvr9Zf5vfDwcEycOBFLlizB9u3b662Pi4vDnj17MGLECEyZMgVfffXVdY+nuLgY2dnZyM3NBVAbWIDaKzRqtRoqlQqzZs3CggULEBAQAKVSiaeeegqDBw+2dBLu0qWL1TaLiooA1PYTquuLs2HDBsycORNvvfUWBg4caOmP4+Xl1aQrHGVlZUhPT7e8z8zMRFpaGgICAhAREYHy8nK8/PLLGDduHMLCwlBUVITVq1cjJyfHahh8dna25ZhNJpPlyz86Ovq6/VX8/Pzw+OOP47nnnoO7uztiY2Nx8eJFLFy4EIMGDcKQIUOuexxA7dWkCRMmYPHixTh9+jSmTZtmWRcREQG5XI533nkHc+fOxcmTJ/HSSy81ur2EhARcvnwZr732Gu6//37s2LED33//vdVzmZYvX46nn34aKpUKY8aMQVVVFY4cOYKrV69aHoTdKq47PspJtNaQ7j966KMUDukmaobGhnK2dzNnzhTjx4+3WpaZmSnkcnm9Id22Xn8cony94d9Lly4VAMTKlSutli9btkwAECtWrKj3GaPRKF5//XVx6623CrlcLpRKpRg9erQ4cOCAVbuGhhynpKQIAOLgwYNCiN+GdP/eL7/8IkJCQsT48eNFVVWVzdp/vx9b52Lp0qWWNpWVleIvf/mL6NChg/D29hYTJ060Gs7+R7bO27Bhw2zuZ+bMmY3W98dtNvT5yspKMXHiRKHRaIRcLhdhYWFi3Lhx4tChQ1bbmTlzps3t1A27v57KykqxdOlSERMTI7y8vERUVJSYM2eOuHz5cpM+X+e7774TAMTQoUPrrduwYYPo1KmTUCgUYvDgwWLr1q1Ww+1tnd/3339fhIeHCx8fHzFjxgzx8ssv1xvSvX79etGnTx8hl8tFhw4dxNChQ8WmTZsaPM6WGNLNp3S3sLoh3W9N7YPxfW6xWpd6oRgHzl2Bn6c7/L09EOirwMCoAHjeROdEIkfHp3QTUUs9pZu3n9qI0WTG458ewdUK6/vOGpUnnhvVHRPib4GbjMPDiYiIbhQ7CreRn89fwdUKI5Se7rivdxju7BqEED8FcnUGPLfxOO575wCSz16+/oaIiNqp/fv3w9fXt8FXe5Gdnd1onX983lVrmTt3boM1/PFZXw155ZVXGtxGYmJiKx9B+8MrNW3kh19rO6nd2zsMKybVzr5pMJrwyU9ZWL03Hafz9Jjx8SHcER2EvyXGoNctrTuWn4iopfXr18/mAyrbG41G02idGo2mTep48cUXG5zXqKndJObOndvghIJeXl43XJujYqhpA2azwH9/rX3C7Khb1Zblnh5umDusCx7sF47Ve9PxWcoFHEgvwn3vHMDE+Fvw3Khu6NjB215lExE1i5eXF6Kjo+1dxnW5u7u3izpDQkJuepK+gICAVnv0gyPi7ac2cOxiCQpLq+CncMeQLoH11nfwkeOF+3pi93PDML5P7b8QNh/LwV1v7MMr352GrqJl5n8gas/qZjElItfTUmOWeKWmDdTdehoeEwKFe8MjncIDvPHW1Hg8fkdnrPj+NH7KuIIPk8/jy8MX8eTwaDwyOJIjpcjpyOVyyGQy5ObmIjg4GHK5nM9UI3IhQghcvnwZkiQ1+/Ehf8RQ08qEENhxsjbUjOmlvk7rWrEdVVj/+EDsO3sZK78/gzP5pXj5u9P45Kcs/HV0N4yPuwUyjpQiJyGTyRAVFYW8vDzLhGxE5FokSULHjh3rPRG+uRhqWtmZ/FJkF1dA4S7DsG7BTf6cJElI6B6CO7sGY9PRS/jnf88ip6QS8788jg+TM/FEQhfc00sNdzfeQSTHJ5fLERERgZqaGphMJnuXQ0RtzMPD46YDDcBQ0+rqrtLc2TUYPormn243mYQH+oVjbJwGH/+Yiff3ZuB0nh5Pf34Mr/p74bHbO2FK/3AoPW/ukh2RvdVder7Zy89E5Lr4z/xWVtefpqm3nhri6eGGvyREI/l/hmPB3d0Q6CNHTkkl/vGf0xj48m48v/E4jmVfbbHOVkRERI6GV2pa0YUr5TiTXwo3mYSRPW5u2F6dDj5yPD2iK+YM7Ywtx3Lw8Y+ZOFtQho2pl7Ax9RK6h/phfLwG4+I0HA5OREQuhaGmFaVeuAoAiA/3h7+3vEW37enhhqkDIvBg/3CkXriKDYey8Z8TedAWlOK1HVq8tkOLfpEdMKaXGiN6hCIqqOEn8RIRETkDhppWlF1cAQDoEtx604NLkoR+nQLQr1MAlt53K74/mYetx3ORcv4Kjly4iiMXruIf/zmNLsE+uCsmBEOigzCgU8AN9e8hIiJqz/jN1orqQk1EYNvcBlJ5e2DqgAhMHRCBAr0B3/+Sh12nC/Hz+SvIuFyOjMuZ+Gh/JjzcJPQJ90ffyAD0jeyA2yL8EeiraJMaiYiIWgtDTSu6VFwJoHZSvbYWqvTEo7dH4dHbo6A3GLFPexk/phdh/7ki5JRU4nDWVRzOumppH6byRHe1H7qH+qG72g/dQv0QHeLLyf6IiMhhMNS0IsuVGjuEmt9TenpgbJwGY+M0EEIgu7gCB88X42j2VaReuIpzhWXI0xmQpzMgSfvbk8JlUu2ts5cm9MKgzvUf70BERNSeMNS0kiqjGfl6AwD7h5rfkyQJkYE+iAz0wZT+4QAAvcGIs/ml0BaUQpt/7VVQipIKI84VluFf/z2Lr+YOtnPlREREjWOoaSWXrtZepfFVuKODd/ueTEzp6WHpbFxHCIH0wjKMejMZh7KKcbG4wi630YiIiJqKk++1krpbT+EB3g75cD5JktA11A+3dwkCUPvUcCIiovaMoaaVXLx6rZNwBy87V3JzJsbfAgDYdPQSZysmIqJ2jaGmlbSXTsI3a0wvNbw83JB1pQLHLpbYuxwiIqIGMdS0ksulVQDabo6a1uKjcLc8t2rT0Ut2roaIiKhhDDWtzBk61066rfYW1LbjeaiqMdm5GiIiItsYalqZo99+AoAhXYIQqlRAV2nE3jOF9i6HiIjIJg7pbkWSBNzi79gdhQHATSZhQp9b8EHyeazZdx55OgM8PdzgLXdDoI8CQX5yBPkqoHD/LSMbTQKlBiP0lTWoqjEhtqMKCnfOTkxERK2HoaYVqZWeTvOYgUm3dcQHyeeRdrEEaTfQYXhq/3CsnNy75QsjIiK6ptm3n5KTkzF27FhoNBpIkoQtW7ZYrV+2bBliYmLg4+ODDh06YOTIkTh48KBVm+LiYkyfPh1KpRL+/v6YNWsWysrKGt2vwWDAvHnzEBgYCF9fX0yePBkFBQXNLb9NOUN/mjrd1X54ZWIsJt/WEff1DsPIHqEY0iUQ3UP9EOAjh62peHzkbghV1j4oc/OxHOgqjG1cNRERuZJmX6kpLy9HXFwc/vSnP2HSpEn11nfr1g3vvvsuOnfujMrKSqxatQqjRo1Ceno6goODAQDTp09HXl4edu7cCaPRiMceewxz5szBhg0bGtzv/Pnz8Z///AcbN26ESqXCk08+iUmTJuHHH39s7iG0mfAOzhNqAOChgRF4aGCEzXU1JjNqzLXz2EgS4CZJcHeTQQiBxLf240x+Kbak5WDmkE5tWDEREbkSSdzEjGqSJGHz5s2YMGFCg230ej1UKhV27dqFESNG4PTp0+jZsycOHz6Mfv36AQB27NiBe+65B5cuXYJGo6m3DZ1Oh+DgYGzYsAH3338/AODMmTPo0aMHUlJSMGjQoOvWWleHTqeDUqm8sQNugun//hk/pl8BAMwf2Q3PjOzaavtyFJ/8mIll204hRu2H75+50yFnWCYiIvtozvd3q45+qq6uxocffgiVSoW4uDgAQEpKCvz9/S2BBgBGjhwJmUxW7zZVndTUVBiNRowcOdKyLCYmBhEREUhJSbH5maqqKuj1eqtXW4sIdPxOwi1hQvwtkLvLcCa/FL/k6OxdDhEROalWCTXbt2+Hr68vPD09sWrVKuzcuRNBQbXPEMrPz0dISIhVe3d3dwQEBCA/P9/m9vLz8yGXy+Hv72+1PDQ0tMHPrFixAiqVyvIKDw+/+QNrJmcYzt0S/L3lSLw2gd8Xhy/auRoiInJWrRJqhg8fjrS0NPz0008YM2YMpkyZgsLCtp3fZNGiRdDpdJbXxYtt/2XqTB2Fb9bU/rV9cbam5aK8qua67WtMZugqjHzeFBERNVmrDOn28fFBdHQ0oqOjMWjQIHTt2hVr167FokWLoFar6wWcmpoaFBcXQ61W29yeWq1GdXU1SkpKrK7WFBQUNPgZhUIBhULRYsfUXJ4eMgT72m//7c2gzgHoFOiNrCsV+M8veZjSLxwGowmZReUo0BtwubQKhaVVyCgsw5n8UqRfLkN1jRn+3h6IDvZF11BfTB8YiV63qOx9KERE1E61yTw1ZrMZVVW1z0IaPHgwSkpKkJqair59+wIA9uzZA7PZjIEDB9r8fN++feHh4YHdu3dj8uTJAACtVovs7GwMHjy4LQ6h2SICvNkh9nckScKD/SPw6o4zeOMHLT5MPo/zl8tgvs6FmJIKI45cuIojF67i4Pli7FowDDIZzysREdXX7FBTVlaG9PR0y/vMzEykpaUhICAAgYGBePnllzFu3DiEhYWhqKgIq1evRk5ODh544AEAQI8ePTBmzBjMnj0ba9asgdFoxJNPPompU6daRj7l5ORgxIgR+OyzzzBgwACoVCrMmjULCxYsQEBAAJRKJZ566ikMHjy4SSOf7IH9aeqb3PcW/GunFoXXrsoAgMrLA2EqT4QoPRHip0BEgDdi1H6IUSsR7KdAZlE5zhWWYvGWkzhfVI7dZwpxd89QOx8JERG1R80ONUeOHMHw4cMt7xcsWAAAmDlzJtasWYMzZ87g008/RVFREQIDA9G/f3/s378ft956q+Uz69evx5NPPokRI0ZAJpNh8uTJePvtty3rjUYjtFotKioqLMtWrVplaVtVVYXRo0fjvffeu6GDbgsdnWyOmpYQ4ueJtTP743SeHt3UfugZpkSIn6LRK1o9NUr01ChxOq8Ua/Zl4KP95xlqiIjIppuap8aRtPU8NUvu64k/3RHVavtxNfk6A+54dQ9qzALfzrsdceH+9i6JiIjaQHO+v/nspxbWu6M/DmdexeAugfYuxamoVZ4Y10eDTUdz8NH+83j3odsabV+gN2DjkYs4cuEq/L08LLe3RvVUIyKQV9GIiJwRr9S0AoPR5DQPsmxPTuXqcc/b++Emk5D01wTLkHldpRGFegMKS6uQpzNgx8l87NUWwmSjF3J4gBd2L0iA3L1V550kIqIWwis1dsZA0zp6apS4IzoIB9KLsGrXWUSH+GLHyXycuGR7luL+nTrg3tgwVNWYUVhahc3HcnCxuBIbUy9i+sDINq6eiIhaG0MNOZTH74zCgfQibDqaY7Vc6eluucV0q0aJB/uHIzrEz6pNxw5eWL7tFN7dk47Jt3Vk+CQicjIMNeRQhnULxoBOATiaXdtvaUwvNUb1VCPY7/oTHU4bEIEPk88jT2fA54ey8djtzevIXVZVg9N5enQO8kEgJ1YkImp32KeGHI7JLGA0mW/oSsv6gxfwv5tPIshXgf3/MxxectvbMBhNSC8sw6lcPX7J0SH1wlWcydfDLIC4cH98O+/2mz0MIiJqAvapIafmJpPgJruxW0cP9A3Hmn0ZuFhciU9+ykLfyA747pc8JJ+7jMpqE8xCwCyA4vJqmx2NASDnaoXN5UREZF8MNeRS5O4yPH1XVzz/9Qm8uuNMo239vT1wq0aJnmFKxEd0gK/CHTM+PtToZ8xmgYJSAy5cqUBuSSUK9FUo0BugqzSiYwcvxKiV6K72Q1SQD9z4uAciohbFUEMuZ2L8Lfgw+TzOFZbBz9Mdo3qqMaaXGmqlJyQJkCQgwEd+7f1vwUObX9rgNi8WV2DWp4dxtqCsSTX07qjC/3t8IJSeHjd9PEREVIuhhlyOu5sMn88ZhPOXy9En3P+m56wRQmDmukM4f7kcQO3tsY4dvHCLvxfUSk+Eqjyh9PRAVlE5zhSU4kyeHicu6fDsF2n4aEY/XrEhImohDDXkkoJ8FQhqoRFM20/kWQLN/80agMGdA+Hu1nBQOnGpBA+sScGeM4X453+1+J8xMS1SBxGRq+O0qkQ3QW8w4qXtpwAA80d2w51dgxsNNEDtozRendwbAPBeUga2Hc9t9TqJiFwBQw1RE9V1r7laYcRbu86hstqEf/33LApLqxAV5IO5CZ2bvK0J8bfgz0Nr2z//9XEcPH+lNUomInIpDDVETRQZ6I0hXQJhMgus2nUWd/0zCZ+lZAEAXhrfCwr35g0z/58xMUjoHgyD0YxH1h7Ct2k51/8QERE1iKGGqIkU7m5Y//hAvDMtHrf4eyFPZ4BZAOPiNLija1Czt+cmk7Dm4b4Yc6sa1SYznvkiDav3psNF5sMkImpxnFGY6AYYjCasPZCJswWlWHJfz5t6bILJLPDKd6ex9kAmACChezAeGRSJYd2u3z+HiMjZNef7m6GGqJ345MdMvLj9FOomMg5VKnBXTCg83CSYr/0x7RTog54aJW7VqKDy4hw3ROT8GGpsYKghR5BeWIovDl3EpmM5KC6vbrTtoM4B+ODhflB5M9wQkfNiqLGBoYYcSXWNGbtOF+DXXB1kkgSZJMFkFjhXWIpfc/W4dLUSANC/Uwf836yBN/RwTyIiR8BQYwNDDTmTU7l6TP0wBXpDDUb2CMGah/uy/w0ROaXmfH/zb0EiB9RTo8TaR/tD4S7DrtOF+NumXzhqiohcHkMNkYPq3ykAqx+6DW4yCV+nXsJ97xzAd7/kwWRmuCEi18TbT0QObvOxS/j7ppOoNJoAAJ2DfDC+zy3oEuKDqCAfdA7yhZecfW6IyDGxT40NDDXkzIrLq/HJT1n49Kcs6CqNVuskCYgM8EZ3tR9i1ErEqP3QXe2HyEAfPiGciNo9hhobGGrIFZRV1WDT0Us4cUmH85fLcL6oHCUVRpttPT1kGBETin9OiePoKSJqt5rz/e3eRjURURvwVbhjxuBOVsuKyqqgzS/F6Tw9tPmlOJNfirMFpTAYzfjPL3noHOyD50Z1t0/BREQtiKGGyMkF+SoQFK3A7dG/PZ/KZBbYejwH8788jjX7MjAh/hZ0Cfa1Y5VERDePo5+IXJCbTMKEPrdgePdgGE0Ci7ec5JBwInJ4DDVELkqSJCwf1wsKdxl+yriCrcdz7V0SEdFNYaghcmERgd54cng0AOAf/zkNvcF2p2IiIkfAUEPk4uYM64zOQT64XFqFf2w/Ze9yiIhuGEMNkYtTuLvhlUmxkCTgqyOXsI23oYjIQTHUEBEGdQ603Ib6+6ZfcLG4ws4VERE1H0MNEQEAnhnRFf0iO6C0qgZPfn4MRpMZAFCoN+BY9lVkFZWjvKrGzlUSETWMMwoTkcWlqxW456390BtqEKP2Q1FZNYrKqqzaeMvdEOynQLCvAsF+CvSN7IBHh3SCuxv/jURELY8zChPRDenYwRuv3d8bc//fUZzJLwUAyCQgxM8TukojKo0mVFSbcOFKBS5cqb1F9f3JfJiFwJyhXexZOhERQw0RWRvTKwwfPtIXl8uq0DNMiRi1El5yNwghUF5tQlFpFS6XVeFyaRVSL1zF2gOZWLXzHBJ7hSE8wNve5RORC+PtJyK6YUIIPPjhzziUWYzh3YPx8aP9IUl88jcRtZzmfH/zJjgR3TBJkvDKxFh4uEnYq72M737Jt3dJROTCGGqI6KZEh/jiiYTa4eDLtv3KWYmJyG6aHWqSk5MxduxYaDQaSJKELVu2WNYZjUYsXLgQsbGx8PHxgUajwYwZM5Cb+9tkXklJSZAkyebr8OHDDe43ISGhXvu5c+c2t3wiagV/SeiCqGuzEr+8/bS9yyEiF9XsUFNeXo64uDisXr263rqKigocPXoUixcvxtGjR7Fp0yZotVqMGzfO0mbIkCHIy8uzej3++OOIiopCv379Gt337NmzrT732muvNbd8ImoFnh5ueGVi7azEXx65iO9+ybN3SUTkgpo9+ikxMRGJiYk216lUKuzcudNq2bvvvosBAwYgOzsbERERkMvlUKvVlvVGoxHffvstnnrqqet2MPT29rb6LBG1H4O7BGLusC54PykDf/vmBHp3VKFjB46GIqK20+p9anQ6HSRJgr+/v831W7duxZUrV/DYY49dd1vr169HUFAQevXqhUWLFqGiouGp3KuqqqDX661eRNS6FtzdDXHh/tAbavDsF2mouTYrcanBiF9zdTAYTXaukIicWavOU2MwGLBw4UJMmzatwWFYa9euxejRo9GxY8dGt/XQQw8hMjISGo0GJ06cwMKFC6HVarFp0yab7VesWIHly5ff9DEQUdN5uMnwztR43Pv2fhy5cBUz1x1CcbkR2nw9zAKQu8nQJ9wfAzsHoHOwD/wUHvDzdIfG34tz3BDRTbupeWokScLmzZsxYcKEeuuMRiMmT56MS5cuISkpyWaouXTpEiIjI/HVV19h8uTJzdr3nj17MGLECKSnp6NLl/ozmVZVVaGq6rfp3fV6PcLDwzlPDVEb+DYtB898kWa1zFfhjrIGnh0lScAnjw3AsG7BbVAdETkSuz8mwWg0YsqUKbhw4QL27NnTYBHr1q1DYGCgVUfipho4cCAANBhqFAoFFApFs7dLRDdvfJ9boDfU4EJROW6L7IB+kR0Q7KdA1pUKHDx/BYeyilGor0KpwYjC0irk6Qz4+6Zf8MP8ofBVcKJzIroxLf63R12gOXfuHPbu3YvAwECb7YQQWLduHWbMmAEPD49m7yctLQ0AEBYWdjPlElEreWRQZL1lUUE+iArywdQBEZZlFdU1GP1mMi4WV+L1HWewfHyvtiyTiJxIszsKl5WVIS0tzRIqMjMzkZaWhuzsbBiNRtx///04cuQI1q9fD5PJhPz8fOTn56O6utpqO3v27EFmZiYef/zxevvIyclBTEwMDh06BADIyMjASy+9hNTUVGRlZWHr1q2YMWMGhg4dit69e9/AYRNRe+Etd8eKibV/jj/7+QIOZxXbuSIiclTNDjVHjhxBfHw84uPjAQALFixAfHw8lixZgpycHGzduhWXLl1Cnz59EBYWZnn99NNPVttZu3YthgwZgpiYmHr7MBqN0Gq1ltFNcrkcu3btwqhRoxATE4PnnnsOkydPxrZt227kmImonbmjaxCm9OsIIYCF35zgKCkiuiF8oCURtQu6CiNGrtqHy6VVeCKhCxaOqf8PHiJyPXygJRE5HJW3B1661p9mzb4M/JheZOeKiMjRMNQQUbsxppca0waEQwjg2S/TUFRWdf0PERFdw1BDRO3KkvtuRdcQX1wurcJzXx2H2Vx7h9xgNOHClXLLeyKiP2KfGiJqd7T5pRj37gFU1ZgxKf4WXK2oRvK5IpjMAq9MjMVDAyOuvxEicgrsU0NEDq272g9LxvYEAGw6loO92sswXbtCcypPZ8/SiKgd49SdRNQuPTQgAheLK/Frrg63RwchvbAMX6degr7S9qMWiIgYaoioXZIkCX9L/G1Y91dHLuLr1EvQVRrtWBURtWe8/UREDkHlVfs4FYYaImoIQw0ROYS6UKNnqCGiBjDUEJFD4JUaIroehhoicgi/DzUuMhMFETUTQw0ROQTltVBTYxaoqOYDL4moPoYaInIIPnI3uMkkAIDewFtQRFQfQw0ROQRJktivhogaxVBDRA7DEmoqGGqIqD6GGiJyGEpeqSGiRjDUEJHD4O0nImoMQw0ROQyGGiJqDEMNETkMlVft4+o4qzAR2cJQQ0QOg1dqiKgxDDVE5DAYaoioMQw1ROQwGGqIqDEMNUTkMBhqiKgxDDVE5DA4Tw0RNYahhogcRt2VGr2hxs6VEFF7xFBDRA5D6ckrNUTUMIYaInIYKu/aUFNdY4bBaLJzNUTU3jDUEJHD8JW7QybV/syrNUT0Rww1ROQwZDKJnYWJqEEMNUTkUDism4gawlBDRA7FEmoqGGqIyBpDDRE5FF6pIaKGMNQQkUNhnxoiaghDDRE5FF6pIaKGMNQQkUNhqCGihjDUEJFDsTwqgaGGiP6AoYaIHAqv1BBRQxhqiMih/PZQS4YaIrLGUENEDoUPtSSihjDUEJFD4e0nImpIs0NNcnIyxo4dC41GA0mSsGXLFss6o9GIhQsXIjY2Fj4+PtBoNJgxYwZyc3OtttGpUydIkmT1WrlyZaP7NRgMmDdvHgIDA+Hr64vJkyejoKCgueUTkYNjqCGihjQ71JSXlyMuLg6rV6+ut66iogJHjx7F4sWLcfToUWzatAlarRbjxo2r1/bFF19EXl6e5fXUU081ut/58+dj27Zt2LhxI/bt24fc3FxMmjSpueUTkYOrCzUGoxlVNSY7V0NE7Yl7cz+QmJiIxMREm+tUKhV27txptezdd9/FgAEDkJ2djYiICMtyPz8/qNXqJu1Tp9Nh7dq12LBhA+666y4AwLp169CjRw/8/PPPGDRoUHMPg4gclJ+nOyQJEKL2ak2In5u9SyKidqLV+9TodDpIkgR/f3+r5StXrkRgYCDi4+Px+uuvo6ampsFtpKamwmg0YuTIkZZlMTExiIiIQEpKis3PVFVVQa/XW72IyPHJZBL8FLX/HuNcNUT0e82+UtMcBoMBCxcuxLRp06BUKi3Ln376adx2220ICAjATz/9hEWLFiEvLw//+te/bG4nPz8fcrm8XjAKDQ1Ffn6+zc+sWLECy5cvb7FjIaL2Q+XtAb2hhv1qiMhKq4Uao9GIKVOmQAiB999/32rdggULLD/37t0bcrkcf/7zn7FixQooFIoW2f+iRYus9qPX6xEeHt4i2yYi+1J5eeAiKhlqiMhKq9x+qgs0Fy5cwM6dO62u0tgycOBA1NTUICsry+Z6tVqN6upqlJSUWC0vKChosF+OQqGAUqm0ehGRc+AIKCKypcVDTV2gOXfuHHbt2oXAwMDrfiYtLQ0ymQwhISE21/ft2xceHh7YvXu3ZZlWq0V2djYGDx7cYrUTkWOwhJoKhhoi+k2zbz+VlZUhPT3d8j4zMxNpaWkICAhAWFgY7r//fhw9ehTbt2+HyWSy9HkJCAiAXC5HSkoKDh48iOHDh8PPzw8pKSmYP38+Hn74YXTo0AEAkJOTgxEjRuCzzz7DgAEDoFKpMGvWLCxYsAABAQFQKpV46qmnMHjwYI58InJBv12paXiAARG5nmaHmiNHjmD48OGW93X9VmbOnIlly5Zh69atAIA+ffpYfW7v3r1ISEiAQqHAF198gWXLlqGqqgpRUVGYP3++Vf8Xo9EIrVaLiooKy7JVq1ZBJpNh8uTJqKqqwujRo/Hee+81t3wicgJKPv+JiGyQhBDC3kW0Bb1eD5VKBZ1Ox/41RA7uvaR0vLZDi/v7dsQbD8TZuxwiakXN+f7ms5+IyOGwozAR2cJQQ0QOh0/qJiJbGGqIyOHUXanhjMJE9HsMNUTkcHj7iYhsYaghIodTF2quVlTDRcY6EFETMNQQkcPR+HvB00MGg9GMjMvl9i6HiNoJhhoicjhydxn6hPsDAA5nFdu3GCJqNxhqiMgh9e8UAIChhoh+w1BDRA6p37VQcyTrqp0rIaL2gqGGiBzSbRH+kElAdnEFCvQGe5dDRO0AQw0ROSQ/Tw/0CKudMp23oIgIYKghIgfWn7egiOh3GGqIyGHVhZpDmbxSQ0QMNUTkwPp16gAAOJOvh97A2YWJXB1DDRE5rFClJyICvGEWwLHsEnuXQ0R2xlBDRA7NMl8Nb0ERuTyGGiJyaP2v3YLiCCgiYqghIodWNwlf2sUSVNeY7VwNEdkTQw0RObQuwT4I8JGjqsaMX3J09i6HiOyIoYaIHJokSegXWXsLikO7iVwbQw0RObyBnQMBAAczr9i5EiKyJ4YaInJ4gzr/NrNwjYn9aohcFUMNETm8GLUSSk93lFXV4Ndcvb3LISI7YaghIofnJpMwIKr2ag1vQRG5LoYaInIKg671q/n5PDsLE7kqhhoicgoDo2pDzeHMYpjMws7VEJE9MNQQkVPoqVHCT+GO0qoanGK/GiKXxFBDRE7BTSahP/vVELk0hhoichoDr4Wan88z1BC5IoYaInIadZ2FD7FfDZFLYqghIqdxq0YJX4U79IYanM5jvxoiV8NQQ0ROw91Nhn6dap8DdZDPgSJyOQw1RORU6oZ2s18NkethqCEip1J3peZkjs7OlRBRW2OoISKn0i3UDwCQpzNAV2m0czVE1JYYaojIqai8PKBReQIAzhaU2rkaImpLDDVE5HS6qWuv1mjzGWqIXAlDDRE5ne7XbkHxSg2Ra2GoISKnU9evhldqiFwLQw0ROZ3u6t+u1AjBmYWJXEWzQ01ycjLGjh0LjUYDSZKwZcsWyzqj0YiFCxciNjYWPj4+0Gg0mDFjBnJzcy1tsrKyMGvWLERFRcHLywtdunTB0qVLUV1d3eh+ExISIEmS1Wvu3LnNLZ+IXEB0iC9kEnC1wojLZVX2LoeI2kizQ015eTni4uKwevXqeusqKipw9OhRLF68GEePHsWmTZug1Woxbtw4S5szZ87AbDbjgw8+wK+//opVq1ZhzZo1+Pvf/37dfc+ePRt5eXmW12uvvdbc8onIBXh6uKFToA8A4Gx+mZ2rIaK24t7cDyQmJiIxMdHmOpVKhZ07d1ote/fddzFgwABkZ2cjIiICY8aMwZgxYyzrO3fuDK1Wi/fffx9vvPFGo/v29vaGWq1ubslE5IK6hfrhfFE5tAWluKNrkL3LIaI20Op9anQ6HSRJgr+/f6NtAgICrrut9evXIygoCL169cKiRYtQUVHRYNuqqiro9XqrFxG5jt+GdfPPPpGraPaVmuYwGAxYuHAhpk2bBqVSabNNeno63nnnnetepXnooYcQGRkJjUaDEydOYOHChdBqtdi0aZPN9itWrMDy5ctv+hiIyDHVDevWFvD2E5GraLVQYzQaMWXKFAgh8P7779tsk5OTgzFjxuCBBx7A7NmzG93enDlzLD/HxsYiLCwMI0aMQEZGBrp06VKv/aJFi7BgwQLLe71ej/Dw8Bs8GiJyNN3VvgCAcwWlMJsFZDLJzhURUWtrldtPdYHmwoUL2Llzp82rNLm5uRg+fDiGDBmCDz/8sNn7GDhwIIDaKz22KBQKKJVKqxcRuY7IQB/I3WSoqDYhp6TS3uUQURto8VBTF2jOnTuHXbt2ITAwsF6bnJwcJCQkoG/fvli3bh1ksuaXkZaWBgAICwu72ZKJyAl5uMnQJaT2ag0n4SNyDc1OE2VlZUhLS7OEiszMTKSlpSE7OxtGoxH3338/jhw5gvXr18NkMiE/Px/5+fmWeWjqAk1ERATeeOMNXL582dKmTk5ODmJiYnDo0CEAQEZGBl566SWkpqYiKysLW7duxYwZMzB06FD07t27BU4DETmj7qHXQg0fl0DkEprdp+bIkSMYPny45X1dv5WZM2di2bJl2Lp1KwCgT58+Vp/bu3cvEhISsHPnTqSnpyM9PR0dO3a0alM386fRaIRWq7WMbpLL5di1axfefPNNlJeXIzw8HJMnT8YLL7zQ3PKJyIV0U/MZUESuRBIuMoe4Xq+HSqWCTqdj/xoiF7H7dAFmfXoEMWo/7Hh2qL3LIaIb0Jzvbz77iYicVt2DLTMul8FoMtu5GiJqba06Tw0RkT117OAFH7kbyqtNSHxrP27vEojBXYIwPCYYCnc3e5dHRC2MV2qIyGlJkoSpAyIAAOmFZfg05QLm/r9UJL65HykZV+xcHRG1NPapISKnV1xejYPnryDl/BV890s+iq49ufuBvh3x93t6oIOP3M4VElFDmvP9zVBDRC5FV2nEazvOYP3BbAC1t6j+O38ovOW8G0/UHrGjMBFRA1ReHnh5Yiy+njsYaqUnLl2txGcpF+xdFhG1AIYaInJJ/ToF4PnR3QEAH+zLQFlVjZ0rIqKbxVBDRC5rfB8NOgf54GqFEZ/+lGXvcojoJjHUEJHLcneT4ZmRXQEAHyafh95gtHNFRHQzGGqIyKXd11uD6BBf6CqNWHcgy97lENFNYKghIpfmJpPwzIjaqzX/PnAeugperSFyVAw1ROTy7o0NQ7dQX5QaarAx9aK9yyGiG8RQQ0QuTyaTMOm2jgCAI1lX7VwNEd0ohhoiIgDx4f4AgKPZV+Eic5ISOR2GGiIiALEdVXCTSSgsrUKezmDvcojoBjDUEBEB8Ja7o0eYHwDgWHaJfYshohvCUENEdE18eAcAwLFs9qshckQMNURE18RH+AMAjl0ssWsdRHRjGGqIiK6Jj6i9UvNLjg7VNWY7V0NEzcVQQ0R0TadAb/h7e6C6xozTeXp7l0NEzcRQQ0R0jSRJlqHd7FdD5HgYaoiIfqfuFhT71RA5HoYaIqLfsXQW5rBuIofDUENE9Dtx4f6QJCC7uAJFZVX2LoeImoGhhojod5SeHuga4guAV2uIHA1DDRHRH3ASPiLHxFBDRPQH7FdD5JgYaoiI/iDu2rDuk7k6PrGbyIEw1BAR/UHnYB/IJKDUUIPL7CxM5DAYaoiI/kDh7oaIAG8AQHphmZ2rIaKmYqghIrKhS3DtCKgMhhoih8FQQ0RkQ/S1Yd28UkPkOBhqiIhs6HIt1GRcLrdzJUTUVAw1REQ28EoNkeNhqCEisqGuT02+3oBSg9HO1RBRUzDUEBHZoPLyQLCfAgBvQRE5CoYaIqIGRAfzFhSRI2GoISJqQLSlszBDDZEjYKghImpAl2AfALxSQ+QoGGqIiBoQHeIHgBPwETmKZoea5ORkjB07FhqNBpIkYcuWLZZ1RqMRCxcuRGxsLHx8fKDRaDBjxgzk5uZabaO4uBjTp0+HUqmEv78/Zs2ahbKyxv/SMBgMmDdvHgIDA+Hr64vJkyejoKCgueUTETVZ3e2nC8UVqK4x27kaIrqeZoea8vJyxMXFYfXq1fXWVVRU4OjRo1i8eDGOHj2KTZs2QavVYty4cVbtpk+fjl9//RU7d+7E9u3bkZycjDlz5jS63/nz52Pbtm3YuHEj9u3bh9zcXEyaNKm55RMRNVmoUgFfhTtMZoELVzgCiqi9k4QQ4oY/LEnYvHkzJkyY0GCbw4cPY8CAAbhw4QIiIiJw+vRp9OzZE4cPH0a/fv0AADt27MA999yDS5cuQaPR1NuGTqdDcHAwNmzYgPvvvx8AcObMGfTo0QMpKSkYNGjQdWvV6/VQqVTQ6XRQKpU3dsBE5HLGv3sAxy/p8P7025AYG2bvcohcTnO+v1u9T41Op4MkSfD39wcApKSkwN/f3xJoAGDkyJGQyWQ4ePCgzW2kpqbCaDRi5MiRlmUxMTGIiIhASkqKzc9UVVVBr9dbvYiImqsLZxYmchitGmoMBgMWLlyIadOmWdJVfn4+QkJCrNq5u7sjICAA+fn5NreTn58PuVxuCUZ1QkNDG/zMihUroFKpLK/w8PCbPyAicjmWxyVwWDdRu9dqocZoNGLKlCkQQuD9999vrd00aNGiRdDpdJbXxYsX27wGInJ8dRPwca4aovbPvTU2WhdoLly4gD179ljdA1Or1SgsLLRqX1NTg+LiYqjVapvbU6vVqK6uRklJidXVmoKCggY/o1AooFAobv5giMilWZ7WXVgOs1lAJpPsXBERNaTFr9TUBZpz585h165dCAwMtFo/ePBglJSUIDU11bJsz549MJvNGDhwoM1t9u3bFx4eHti9e7dlmVarRXZ2NgYPHtzSh0BEZBEZ4A0PNwmVRhMuXa20dzlE1IhmX6kpKytDenq65X1mZibS0tIQEBCAsLAw3H///Th69Ci2b98Ok8lk6fMSEBAAuVyOHj16YMyYMZg9ezbWrFkDo9GIJ598ElOnTrWMfMrJycGIESPw2WefYcCAAVCpVJg1axYWLFiAgIAAKJVKPPXUUxg8eHCTRj4REd0odzcZooJ8cLagDGPeSsbwmBAk9lIjvIM33GQS3N0khCm9oPL2sHepRC6v2UO6k5KSMHz48HrLZ86ciWXLliEqKsrm5/bu3YuEhAQAtZPvPfnkk9i2bRtkMhkmT56Mt99+G76+tZd5s7KyEBUVZfUZg8GA5557Dp9//jmqqqowevRovPfeew3efvojDukmohu1/UQuVnx3Bjkltq/UKD3dsXPBMIQqPdu4MiLn15zv75uap8aRMNQQ0c0QQuDEJR2+O5mHfdrLKDXUoMZshr6yBpVGEx67vROWjr3V3mUSOR2GGhsYaoioNew/dxmPrD0EhbsM+/9nOEJ4tYaoRbWryfeIiJzZHdFBuC3CH1U1ZnyQfN7e5RC5NIYaIqKbIEkSnhnZDQCw/uAFXC6tsnNFRK6LoYaI6CYN7RqEPuH+MBjN+DA5w97lELkshhoioptUe7WmKwDg/36+gKIyXq0hsgeGGiKiFpDQLRhxHVUwGM344lC2vcshckkMNURELUCSJIzpFQYAOF9UbudqiFwTQw0RUQtRq2qfN1egN9i5EiLXxFBDRNRCQv1q56jJ1zHUENkDQw0RUQsJVdWGmgI9OwoT2QNDDRFRC1Ffm024rKoGZVU1dq6GyPUw1BARtRAfhTv8FO4A2K+GyB4YaoiIWlCI8lpnYfarIWpzDDVERC1Ifa1fTT6v1BC1OYYaIqIWFKpkqCGyF4YaIqIWVNdZuJAjoIjaHEMNEVELslypYZ8aojbHUENE1IJ4+4nIfhhqiIhakNoyAR9DDVFbY6ghImpBlj41pVUwm4WdqyFyLQw1REQtKMhXDpkEmMwCReXsLEzUlhhqiIhakLubDEG+dRPwMdQQtSWGGiKiFsYJ+Ijsg6GGiKiF1Y2AYmdhorbFUENE1MJC657/xFBD1KYYaoiIWpiaE/AR2QVDDRFRC+MEfET2wVBDRNTC6joK8/lPRG2LoYaIqIXxSg2RfTDUEBG1sLpQo6s0wmA02bkaItfBUENE1MKUnu7w8nADwM7CRG2JoYaIqIVJksQHWxLZAUMNEVErCPGrnauG/WqI2g5DDRFRK+CVGqK2x1BDRNQKfpuAj8O6idqKu70LICJyRpbnP5UaYDSZ8WHyeWxNy0VZVQ0qjSZUGU0Y3CUIf0vsjugQPztXS+QcGGqIiFpBXaj5NUeHse8cwJn80nptdp0uwF5tIaYPjMCzI7shwEfe1mUSORWGGiKiVqBW1XYUzrpSAQDo4O2BhWNiEBOmhLfcDQajCe/sScfOUwX4LOUCvk3LxTvT4jG0W7A9yyZyaAw1REStIDzAG5IECAGMjdNg6dieCPJVWLX5aEY//JRRhJe2n8bpPD0e++QwFt/bAzOHdIIkSXaqnMhxSUIIYe8i2oJer4dKpYJOp4NSqbR3OUTkAnafLoCXhxuGRAc12q6qxoS/bzqJb45eAgBMGxCB5eNuhdydYzmImvP93ew/McnJyRg7diw0Gg0kScKWLVus1m/atAmjRo1CYGAgJElCWlqa1fqsrCxIkmTztXHjxgb3++ijj9ZrP2bMmOaWT0TUZkb0CL1uoAEAhbsb3nigN/73nh6QJODzQ9l4e/e5NqiQyLk0O9SUl5cjLi4Oq1evbnD9HXfcgVdffdXm+vDwcOTl5Vm9li9fDl9fXyQmJja67zFjxlh97vPPP29u+URE7ZIkSZg9tDP+MaEXgNpOxETUPM3uU5OYmNho+HjkkUcA1F6RscXNzQ1qtdpq2ebNmzFlyhT4+vo2um+FQlHvs0REzmT0rWr87+aT0BaUoqSiGv7eHBFF1FR2v2GbmpqKtLQ0zJo167ptk5KSEBISgu7du+OJJ57AlStXGmxbVVUFvV5v9SIiau+CfBXoHOwDIYAjWVftXQ6RQ7F7qFm7di169OiBIUOGNNpuzJgx+Oyzz7B79268+uqr2LdvHxITE2EymWy2X7FiBVQqleUVHh7eGuUTEbW4gVEBAIDDWcV2roTIsdg11FRWVmLDhg1NukozdepUjBs3DrGxsZgwYQK2b9+Ow4cPIykpyWb7RYsWQafTWV4XL15s4eqJiFpH/061oeZgJkMNUXPYNdR8/fXXqKiowIwZM5r92c6dOyMoKAjp6ek21ysUCiiVSqsXEZEjGHDtSs3JHB0qqmvsXA2R47BrqFm7di3GjRuH4ODmz6B56dIlXLlyBWFhYa1QGRGR/XTs4I1b/L1QYxY4ll1i73KIHEazQ01ZWRnS0tIs889kZmYiLS0N2dnZAIDi4mKkpaXh1KlTAACtVou0tDTk5+dbbSc9PR3Jycl4/PHHbe4nJiYGmzdvtuzz+eefx88//4ysrCzs3r0b48ePR3R0NEaPHt3cQyAiavf6d+oAgLegiJqj2aHmyJEjiI+PR3x8PABgwYIFiI+Px5IlSwAAW7duRXx8PO69914AtX1h4uPjsWbNGqvtfPzxx+jYsSNGjRplcz9arRY6nQ5A7TDwEydOYNy4cejWrRtmzZqFvn37Yv/+/VAoFDY/T0TkyAZEBQIADmU2PMqTiKzxMQlERO1QemEpRv4rGQp3GX5ZNpqPTCCX1aqPSSAiotbXJdgXAT5yVNWY8UtOib3LIXIIDDVERO2QJEkYwKHdRM3CUENE1E71r5uEj6GGqEkYaoiI2qm6mYV/TL+Cpz4/hq9TL6Gw1GDnqojar2Y/0JKIiNpGjzAlYtR+OJNfim3Hc7HteC7cZBIWJcbg8Ts727s8onaHoYaIqJ1yk0nY/tQdSLtYgiTtZezVFuLXXD3+8Z/TKCqrxsIx3SFJkr3LJGo3OKSbiMiBrNmXgZXfnwEATOnXEa9MjIW7G3sSkPPikG4iIic1d1gXvDa5N2QS8NWRS3hywzEYTWZ7l0XULjDUEBE5mCn9w7Hm4b6Qu8uw49d8PPfVcZjMLnHRnahRDDVERA5o1K1qrHn4Nni4Sdh6PBeLNp2AmcGGXBxDDRGRg7orJhRvTY233Ipavu1XuEg3SSKbGGqIiBzYPbFh+OeUOEgS8GnKBaz8/gyDDbkshhoiIgc3Mb4jXp4QCwD4IPk83tp9zs4VEdkHQw0RkRN4aGAEFt/XEwDw5q5z+GBfhp0rImp7DDVERE5i1h1ReH50dwDAiu/P4OMDmXauiKhtMdQQETmRecOj8eTwaADAi9tPYfXedPaxIZfBUENE5GSeG9UNz4zoCgB4/QctVu5g52FyDQw1RERORpIkzL+7G/73nh4AgA/2nccLW05ygj5yegw1REROavbQznhlYiwkCVh/MBuzPzuCsqoae5dF1GoYaoiInNhDAyOw+qHboHCXYc+ZQtz//k+4dLXC3mURtQqGGiIiJ3dPbBi+/PNgBPspcCa/FBNW/4jDWcX2LouoxTHUEBG5gD7h/vh23u3oEaZEUVk1pn74M97dc479bMipMNQQEbkIjb8Xvp47GBPjb4HJLPDGf89i5seHUFhqsHdpRC2CoYaIyIX4KNzxrylxeP3+3vDycMOB9CKMXpWMLcdyOOybHB5DDRGRi5EkCQ/0C8e2p25HjNoPVyuMePbLNDz2yWF2IiaHxlBDROSiokP8sPXJO/DXUd0gd5MhSXsZo1Yl4+3d51BRzaHf5Hgk4SLXG/V6PVQqFXQ6HZRKpb3LISJqV9ILy7Bo0wkczroKAAjxU2DB3d3wQL9wuMkkO1dHrqw5398MNUREBAAwmwW2/5KH1384g4vFlQCAToHemDO0Cybddgs8PdzsXCG5IoYaGxhqiIiapqrGhP9LuYB396ajpMIIAAj2U+DRIZ0wpV84gv0Udq6QXAlDjQ0MNUREzVNeVYMvDl/Ev/efR56udti3u0zCXTEhmDogHHd2DYaHG7tmOjMhBMwCMJkFzKL2ZTILmM2Aqe7n3y13k0kIU3m1aA0MNTYw1BAR3ZjqGjO2Hs/F+oMXcCy7xLJc5eWBkT1CMfrWUNzZNRhect6euhkms0BFdQ0qjSZUGc2oNJpgMJpQWW269rMZhrplRutl1TVmGE1m1JgEjCYzqk21741172vMqDH/9vPv19X9bDJfewkBsyWsNO8YugT7YPdzCS16XhhqbGCoISK6eWcLSvHl4YvYciwHV8qrLcvlbjL07qhC/6gADOgUgLhwfwT4yO1YadsymQXKqmpQajBCX1n731JDDUqrrv3XUAP9tWX6yrplv60rNRhRXm2y92HcEJkEyCQJMpmEzkE+2PHs0BbdPkONDQw1REQtx2QWOJJVjB2/5uO/vxYgp6SyXpuOHbzQu6MKPdRKRIf4okuILzoF+kDu3r5uWZnNAmXVNX8IGr+FE73Bxro/hJKWfvq5l4cbvORu8HSXwVPuBk/32vdeHm7w9JDB08MNnh6/vZe7y+DhVvuSu8ng7iZZfvZwr/3ZXSaD/NrPv70ky3/dZDK4SRJkMsBNJtUGFUmCm0xqcLlMqp33qDUx1NjAUENE1DqEEMgursDBzGIcyixG6oWryCwqt9lWkmqHi4epvKDx90SAjxxKTw+ovDyg9Lr2X08P+Hm6w91NsvnlKkn47fZKjUD1726pGIwmlFfXoKzKhPKqGpRX1YaO8qoam8v1lUaUVdegpb4J5e4yKD3d4XftGOqOxe93y36/Tmm13B0+Cnco3GWtHhQcCUONDQw1RERtR1dpxK85OpzI0eFsQSkyLpcjo7Csxa9otCQPN+l3IaR+GFHWCyq/tVF61f6scGe/opbWnO9v9zaqiYiIXIjKywNDooMwJDrIskwIgSvl1cgrMSCnpBJ5ukqUVBihqzRCbzBCX1l7y0dXaUSpwYga82+jampH2dTe9hIQkLv94ZbLtZ8V7jL4Ktzho3CDj8L92s/X/iv/bZnvH0OJpwevkDgBhhoiImoTkiQhyFeBIF8FYjuq7F0OOaH21VuLiIiI6AYx1BAREZFTYKghIiIip9DsUJOcnIyxY8dCo9FAkiRs2bLFav2mTZswatQoBAYGQpIkpKWl1dtGQkICJEmyes2dO7fR/QohsGTJEoSFhcHLywsjR47EuXPnmls+EREROalmh5ry8nLExcVh9erVDa6/44478Oqrrza6ndmzZyMvL8/yeu211xpt/9prr+Htt9/GmjVrcPDgQfj4+GD06NEwGAzNPQQiIiJyQs0e/ZSYmIjExMQG1z/yyCMAgKysrEa34+3tDbVa3aR9CiHw5ptv4oUXXsD48eMBAJ999hlCQ0OxZcsWTJ06tWnFExERkdOyW5+a9evXIygoCL169cKiRYtQUVHRYNvMzEzk5+dj5MiRlmUqlQoDBw5ESkqKzc9UVVVBr9dbvYiIiMh52WWemoceegiRkZHQaDQ4ceIEFi5cCK1Wi02bNtlsn5+fDwAIDQ21Wh4aGmpZ90crVqzA8uXLW7ZwIiIiarfsEmrmzJlj+Tk2NhZhYWEYMWIEMjIy0KVLlxbZx6JFi7BgwQLLe71ej/Dw8BbZNhEREbU/7WJI98CBAwEA6enpNtfX9b0pKCiwWl5QUNBgvxyFQgGlUmn1IiIiIufVLkJN3bDvsLAwm+ujoqKgVquxe/duyzK9Xo+DBw9i8ODBbVEiERERtXPNvv1UVlZmdUUlMzMTaWlpCAgIQEREBIqLi5GdnY3c3FwAgFarBVB7tUWtViMjIwMbNmzAPffcg8DAQJw4cQLz58/H0KFD0bt3b8t2Y2JisGLFCkycOBGSJOHZZ5/FP/7xD3Tt2hVRUVFYvHgxNBoNJkyYcJOngIiIiJyCaKa9e/cKAPVeM2fOFEIIsW7dOpvrly5dKoQQIjs7WwwdOlQEBAQIhUIhoqOjxfPPPy90Op3VfgCIdevWWd6bzWaxePFiERoaKhQKhRgxYoTQarVNrlun0wkA9fZDRERE7Vdzvr8lIYSwS5pqY3q9HiqVCjqdjv1riIiIHERzvr/tMvrJHuqyG+erISIichx139tNuQbjMqGmtLQUADism4iIyAGVlpZCpVI12sZlbj+ZzWbk5ubCz88PkiS16Lbr5sC5ePEib221EJ7T1sHz2vJ4Tlsez2nrcNTzKoRAaWkpNBoNZLLGB227zJUamUyGjh07tuo+OB9Oy+M5bR08ry2P57Tl8Zy2Dkc8r9e7QlOnXcxTQ0RERHSzGGqIiIjIKTDUtACFQoGlS5dCoVDYuxSnwXPaOnheWx7PacvjOW0drnBeXaajMBERETk3XqkhIiIip8BQQ0RERE6BoYaIiIicAkMNEREROQWGmiZavXo1OnXqBE9PTwwcOBCHDh2yd0kOZdmyZZAkyeoVExNj1cZgMGDevHkIDAyEr68vJk+ejIKCAjtV3P4kJydj7Nix0Gg0kCQJW7ZsqddGCIElS5YgLCwMXl5eGDlyJM6dO2fVpri4GNOnT4dSqYS/vz9mzZqFsrKyNjqK9qUp5/TRRx+t97s7ZswYqzY8p9ZWrFiB/v37w8/PDyEhIZgwYQK0Wq1Vm6b8ec/Ozsa9994Lb29vhISE4Pnnn0dNTU1bHkq70ZRzmpCQUO93de7cuVZtnP2cMtQ0wZdffokFCxZg6dKlOHr0KOLi4jB69GgUFhbauzSHcuuttyIvL8/yOnDggNX6+fPnY9u2bdi4cSP27duH3NxcTJo0yU7Vtj/l5eWIi4vD6tWrG2zz2muv4e2338aaNWtw8OBB+Pj4YPTo0TAYDJY206dPx6+//oqdO3di+/btSE5Oxpw5c9riENqdppxTABgzZozV7+7nn39utZ7n1Nq+ffswb948/Pzzz9i5cyeMRiNGjRqF8vJyS5vr/Xk3mUy49957UV1djZ9++gmffvopPvnkEyxZssQeh2R3TTmnADB79myr39XXXnvNss4lzqmg6xowYICYN2+e5b3JZBIajUasWLGiwc/s3btX9O/fX3h7ewuVSiWGDBkisrKy2qLcdmnp0qUiLi6uwfUlJSXCw8NDbNy40bLs9OnTAoBISUlp8HOrV68W0dHRQqFQiJCQEDF58uSWLLvdAiA2b95stcxsNgu1Wi1ef/11y7KSkhKhUCjE559/LoQQ4tSpUwKAOHz4sKXN999/LyRJEjk5OTb3ZTabxdKlS0V4eLiQy+UiLCxMPPXUUy1/UHZm65wKIcTMmTPF+PHjG/wcz+n1FRYWCgBi3759Qoim/Xn/7rvvhEwmE/n5+ZY277//vlAqlaKqqsrmfqqqqsS8efOEWq0WCoVCREREiFdeeaUVj8x+/nhOhRBi2LBh4plnnmnwM65wTnml5jqqq6uRmpqKkSNHWpbJZDKMHDkSKSkpNj9TU1ODCRMmYNiwYThx4gRSUlIwZ86cFn+QpqM5d+4cNBoNOnfujOnTpyM7O9uyLjU1FUaj0eo8x8TEICIiosHzfOTIETz99NN48cUXodVqsWPHDgwdOrTVj6O9yszMRH5+vtU5VKlUGDhwoOUcpqSkwN/fH/369bO0GTlyJGQyGQ4ePGhzu9988w1WrVqFDz74AOfOncOWLVsQGxvbugfTziQlJSEkJATdu3fHE088gStXrljW8Zxen06nAwAEBAQAaNqf95SUFMTGxiI0NNTSZvTo0dDr9fj1119t7uftt9/G1q1b8dVXX0Gr1WL9+vXo1KlTKx2Vff3xnNZZv349goKC0KtXLyxatAgVFRWWda5wTl3mgZY3qqioCCaTyeqXAABCQ0Nx5swZm5/R6/XQ6XS477770KVLFwBAjx49Wr3W9mzgwIH45JNP0L17d+Tl5WH58uW48847cfLkSfj5+SE/Px9yuRz+/v5WnwsNDUV+fr7NbWZnZ8PHxwf33Xcf/Pz8EBkZifj4+DY4mvap7jzZ+l2tW5efn4+QkBCr9e7u7ggICGj0PKvVaowcORIeHh6IiIjAgAEDWuEI2qcxY8Zg0qRJiIqKQkZGBv7+978jMTERKSkpcHNz4zm9DrPZjGeffRa33347evXqBQBN+vOen59v83e5bp0t2dnZ6Nq1K+644w5IkoTIyMgWPpr2wdY5BYCHHnoIkZGR0Gg0OHHiBBYuXAitVotNmzYBcI1zyis1rSAgIACPPvooRo8ejbFjx+Ktt95CXl6evcuyq8TERDzwwAPo3bs3Ro8eje+++w4lJSX46quvbnibd999NyIjI9G5c2c88sgjWL9+vdW/SqhlPPDAA6isrETnzp0xe/ZsbN682ak6Fl7P1KlTMW7cOMTGxmLChAnYvn07Dh8+jKSkpBvepiud03nz5uHkyZP44osvWn1fjz76KNLS0tC9e3c8/fTT+O9//9vq+7SHhs7pnDlzMHr0aMTGxmL69On47LPPsHnzZmRkZNzwvhztnDLUXEdQUBDc3Nzq9covKCiAWq1u8HPr1q1DSkoKhgwZgi+//BLdunXDzz//3NrlOgx/f39069YN6enpAAC1Wo3q6mqUlJRYtWvsPPv5+eHo0aP4/PPPERYWhiVLliAuLq7eNlxF3Xlq7HdVrVbX6+BeU1OD4uLiBs9zeHg4tFot3nvvPXh5eeEvf/kLhg4dCqPR2ApH0f517twZQUFBVr+7PKe2Pfnkk9i+fTv27t2Ljh07WpY35c+7Wq22+btct86W2267DZmZmXjppZdQWVmJKVOm4P7772/BI7K/hs6pLQMHDgQAq99Vpz+n9u7U4wgGDBggnnzySct7k8kkbrnllkY7Cv/RoEGDnLojYHOVlpaKDh06iLfeeksI8VvHwa+//trS5syZM9ftKPx7ZWVlwt3dXXzzzTetUnN7gkY6Cr/xxhuWZTqdzmZH4SNHjlja/PDDD412av2juv8vqampN38g7Yitc2rLxYsXhSRJ4ttvvxVC8JzaYjabxbx584RGoxFnz56tt74pf97rOrUWFBRY2nzwwQdCqVQKg8HQpDp27NghAIgrV67c5BHZ3/XOqS0HDhwQAMTx48eFEK5xThlqmuCLL74QCoVCfPLJJ+LUqVNizpw5wt/f36oH+e+dP39e/O1vfxM//fSTyMrKEj/88IMIDAwU7733XhtX3n4899xzIikpSWRmZooff/xRjBw5UgQFBYnCwkJLm7lz54qIiAixZ88eceTIETF48GAxePDgBre5bds28dZbb4ljx46JrKws8d577wmZTCZOnjzZFofU5kpLS8WxY8fEsWPHBADxr3/9Sxw7dkxcuHDB0mblypXC399ffPvtt+LEiRNi/PjxIioqSlRWVlrajBkzRsTHx4uDBw+KAwcOiK5du4pp06Y1uN9169aJf//73+KXX34RGRkZ4oUXXhBeXl6iqKioVY+3LVzvnJaWloq//vWvIiUlRWRmZopdu3aJ2267TXTt2tXqS4Dn1NoTTzwhVCqVSEpKEnl5eZZXRUWFpc31/rzX1NSIXr16iVGjRom0tDSxY8cOERwcLBYtWtTgfv/5z3+KDRs2iNOnTwutVitmzZol1Gq1MJlMrXq8beF65zQ9PV28+OKL4siRIyIzM1N8++23onPnzmLo0KGWbbjCOWWoaaJ33nlHRERECLlcLgYMGCB+/vnnBtvm5+eLCRMmiLCwMCGXy0VkZKRYsmRJu/0laAsPPvig5Xzccsst4sEHHxTp6elWbSorK8Vf/vIX0aFDB+Ht7S0mTpwo8vLyGtzm/v37xbBhw0SHDh2El5eX6N27t/jyyy9b+1DsZu/evQJAvdfMmTMtbcxms1i8eLEIDQ0VCoVCjBgxQmi1WqvtXLlyRUybNk34+voKpVIpHnvsMVFaWtrgfjdv3iwGDhwolEql8PHxEYMGDRK7du1qrcNsU9c7pxUVFWLUqFEiODhYeHh4iMjISDF79ux6/6DhObVm65wCEOvWrbO0acqf96ysLJGYmCi8vLxEUFCQeO6554TRaGxwvx9++KHo06eP8PHxEUqlUowYMUIcPXq0tQ6zTV3vnGZnZ4uhQ4eKgIAAoVAoRHR0tHj++eeFTqez2o6zn1NJCCFa+Q4XERERUatjR2EiIiJyCgw1RERE5BQYaoiIiMgpMNQQERGRU2CoISIiIqfAUENEREROgaGGiIiInAJDDRERETkFhhoicgiPPvooJkyYYO8yiKgdc7d3AUREkiQ1un7p0qV46623wAnQiagxDDVEZHd5eXmWn7/88kssWbIEWq3WsszX1xe+vr72KI2IHAhvPxGR3anVastLpVJBkiSrZb6+vvVuPyUkJOCpp57Cs88+iw4dOiA0NBQfffQRysvL8dhjj8HPzw/R0dH4/vvvrfZ18uRJJCYmwtfXF6GhoXjkkUdQVFTUxkdMRK2BoYaIHNann36KoKAgHDp0CE899RSeeOIJPPDAAxgyZAiOHj2KUaNG4ZFHHkFFRQUAoKSkBHfddRfi4+Nx5MgR7NixAwUFBZgyZYqdj4SIWgJDDRE5rLi4OLzwwgvo2rUrFi1aBE9PTwQFBWH27Nno2rUrlixZgitXruDEiRMAgHfffRfx8fF45ZVXEBMTg/j4eHz88cfYu3cvzp49a+ejIaKbxT41ROSwevfubfnZzc0NgYGBiI2NtSwLDQ0FABQWFgIAjh8/jr1799rsn5ORkYFu3bq1csVE1JoYaojIYXl4eFi9lyTJalndqCqz2QwAKCsrw9ixY/Hqq6/W21ZYWFgrVkpEbYGhhohcxm233YZvvvkGnTp1grs7//ojcjbsU0NELmPevHkoLi7GtGnTcPjwYWRkZOCHH37AY489BpPJZO/yiOgmMdQQkcvQaDT48ccfYTKZMGrUKMTGxuLZZ5+Fv78/ZDL+dUjk6CTBKTqJiIjICfCfJkREROQUGGqIiIjIKTDUEBERkVNgqCEiIiKnwFBDREREToGhhoiIiJwCQw0RERE5BYYaIiIicgoMNUREROQUGGqIiIjIKTDUEBERkVP4/xuw8cvSJq3sAAAAAElFTkSuQmCC", "text/plain": [ "
" ] @@ -4555,7 +331,8 @@ ], "source": [ "c = res.curves().plot()\n", - "c.set_xlabel('Time (ms)')\n", + "plt.gca().xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))\n", + "c.set_xlabel('Time')\n", "plt.show()" ] }, @@ -4564,7 +341,7 @@ "metadata": {}, "source": [ "Comment on the result :\n", - "When adding a Tap Changer Blocking Automaton, that blocks the LTCs when the voltage at bus 1042 is below 120kV, the voltage collapse is avoided, as shown in the figure." + "When adding a Tap Changer Blocking automation system, that blocks the LTCs when the voltage at bus 1042 is below 120kV, the voltage collapse is avoided, as shown in the figure." ] } ], From 1f760a337304ae9e8fe726b3b5d77d76a7595dee Mon Sep 17 00:00:00 2001 From: lisrte Date: Wed, 12 Feb 2025 11:27:35 +0100 Subject: [PATCH 07/14] Use axes directly instead of pyplot Mutualize plot configuration in plot function Signed-off-by: lisrte --- dynawo/nordic case/pypowsybl_dynawo.ipynb | 50 ++++++++++++----------- 1 file changed, 26 insertions(+), 24 deletions(-) diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic case/pypowsybl_dynawo.ipynb index e3c4530..64ac43d 100644 --- a/dynawo/nordic case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic case/pypowsybl_dynawo.ipynb @@ -72,27 +72,36 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pypowsybl as pp\n", "import pypowsybl.dynamic as dyn\n", "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", "import os.path\n", - "from pypowsybl_jupyter import display_nad" + "from pypowsybl_jupyter import display_nad\n", + "\n", + "def plot(df):\n", + " df.plot(xlabel='Time').xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Load initial situation" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5553c204da48470c941f93591c6232d7", + "model_id": "c70975f73f56400dbdb07d2941360af0", "version_major": 2, "version_minor": 1 }, @@ -100,13 +109,12 @@ "NadWidget(diagram_data={'svg_data': '\\n" ] @@ -231,10 +239,7 @@ } ], "source": [ - "c = res.curves().plot()\n", - "plt.gca().xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))\n", - "c.set_xlabel('Time')\n", - "plt.show()" + "plot(res.curves())" ] }, { @@ -261,7 +266,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -297,7 +302,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -315,7 +320,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -330,10 +335,7 @@ } ], "source": [ - "c = res.curves().plot()\n", - "plt.gca().xaxis.set_major_formatter(lambda x, pos: '{:.0f} s'.format(x/1000))\n", - "c.set_xlabel('Time')\n", - "plt.show()" + "plot(res.curves())" ] }, { From bb187a690026394c98008b4abc806c3b8e3a61bc Mon Sep 17 00:00:00 2001 From: Florian Dupuy Date: Fri, 14 Feb 2025 16:11:50 +0100 Subject: [PATCH 08/14] Add mybinder link Signed-off-by: Florian Dupuy --- README.md | 1 + dynawo/{nordic case => nordic_case}/Network.par | 0 dynawo/{nordic case => nordic_case}/Nordic.par | 0 dynawo/{nordic case => nordic_case}/Nordic.xiidm | 0 dynawo/{nordic case => nordic_case}/Solver.par | 0 dynawo/{nordic case => nordic_case}/config.yml | 0 dynawo/{nordic case => nordic_case}/pypowsybl_dynawo.ipynb | 0 7 files changed, 1 insertion(+) rename dynawo/{nordic case => nordic_case}/Network.par (100%) rename dynawo/{nordic case => nordic_case}/Nordic.par (100%) rename dynawo/{nordic case => nordic_case}/Nordic.xiidm (100%) rename dynawo/{nordic case => nordic_case}/Solver.par (100%) rename dynawo/{nordic case => nordic_case}/config.yml (100%) rename dynawo/{nordic case => nordic_case}/pypowsybl_dynawo.ipynb (100%) diff --git a/README.md b/README.md index bd8e82b..ebb95c5 100644 --- a/README.md +++ b/README.md @@ -7,6 +7,7 @@ - Network, load flow calculation, security analysis and sensitivity analysis [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=pypowsybl_lf_security_sensitivity_analysis.ipynb) - Operator strategy notebook: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=operator_strategy.ipynb) - Computation using Dynaflow : [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=dynaflow/pypowsybl_dynaflow.ipynb) +- Dynamic simulation using dynawo: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/dynawo_simulation_nordic_case?labpath=dynawo/nordic_case/pypowsybl_dynawo.ipynb) - Sensitivity analysis and PTDF calculation [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=sensitivity_analysis.ipynb) - Pypowsybl-Jupyter widgets notebook : [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=pypowsybl_jupyter_widgets_demo.ipynb) diff --git a/dynawo/nordic case/Network.par b/dynawo/nordic_case/Network.par similarity index 100% rename from dynawo/nordic case/Network.par rename to dynawo/nordic_case/Network.par diff --git a/dynawo/nordic case/Nordic.par b/dynawo/nordic_case/Nordic.par similarity index 100% rename from dynawo/nordic case/Nordic.par rename to dynawo/nordic_case/Nordic.par diff --git a/dynawo/nordic case/Nordic.xiidm b/dynawo/nordic_case/Nordic.xiidm similarity index 100% rename from dynawo/nordic case/Nordic.xiidm rename to dynawo/nordic_case/Nordic.xiidm diff --git a/dynawo/nordic case/Solver.par b/dynawo/nordic_case/Solver.par similarity index 100% rename from dynawo/nordic case/Solver.par rename to dynawo/nordic_case/Solver.par diff --git a/dynawo/nordic case/config.yml b/dynawo/nordic_case/config.yml similarity index 100% rename from dynawo/nordic case/config.yml rename to dynawo/nordic_case/config.yml diff --git a/dynawo/nordic case/pypowsybl_dynawo.ipynb b/dynawo/nordic_case/pypowsybl_dynawo.ipynb similarity index 100% rename from dynawo/nordic case/pypowsybl_dynawo.ipynb rename to dynawo/nordic_case/pypowsybl_dynawo.ipynb From e23113ba2a9c437cdac6b1e260f96b0f898947cf Mon Sep 17 00:00:00 2001 From: lisrte Date: Tue, 25 Feb 2025 16:18:59 +0100 Subject: [PATCH 09/14] Review fix Signed-off-by: lisrte --- dynawo/nordic_case/config.yml | 8 +++--- dynawo/nordic_case/pypowsybl_dynawo.ipynb | 30 ++++++++++++++++++++--- 2 files changed, 30 insertions(+), 8 deletions(-) diff --git a/dynawo/nordic_case/config.yml b/dynawo/nordic_case/config.yml index 4627340..35df1ce 100644 --- a/dynawo/nordic_case/config.yml +++ b/dynawo/nordic_case/config.yml @@ -1,10 +1,10 @@ dynawo: - homeDir: /home/dynawo + homeDir: "WORKING_DIR/dynawo" dynawo-simulation-default-parameters: - parametersFile: Nordic.par - network.parametersFile: Network.par + parametersFile: "WORKING_DIR/Nordic.par" + network.parametersFile: "WORKING_DIR/Network.par" network.parametersId: "Network" solver.type: SIM - solver.parametersFile: Solvers.par + solver.parametersFile: "WORKING_DIR/Solver.par" solver.parametersId: "Solver" diff --git a/dynawo/nordic_case/pypowsybl_dynawo.ipynb b/dynawo/nordic_case/pypowsybl_dynawo.ipynb index 64ac43d..9b3c003 100644 --- a/dynawo/nordic_case/pypowsybl_dynawo.ipynb +++ b/dynawo/nordic_case/pypowsybl_dynawo.ipynb @@ -24,6 +24,16 @@ "## 1 - Dynawo install" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**For Windows**\n", + "Follow [this link](https://github.com/dynawo/dynawo?tab=readme-ov-file#installation) to install Dynawo.\n", + "**For Linux**\n", + "You can launch the following commands to download the latest distribution:" + ] + }, { "cell_type": "code", "execution_count": null, @@ -52,6 +62,20 @@ "pip install pypowsybl matplotlib pypowsybl-jupyter" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `config.yml` file provided with the notebook has to be edited for some properties:\n", + "- `dynawo/homeDir` with the Dynawo installation path\n", + "- `dynawo-simulation-default-parameters` properties with the path of the provided parameters files:\n", + " - `parametersFile` with `Nordic.par`\n", + " - `network.parametersFile` with `Network.par`\n", + " - `solver.parametersFile` with the path of `Solver.par`\n", + "\n", + "For Linux users, you can run the following commands:" + ] + }, { "cell_type": "code", "execution_count": null, @@ -60,6 +84,7 @@ "source": [ "!mkdir /home/$USER/.itools/\n", "!cp config.yml /home/$USER/.itools/\n", + "!sed -i \"s|WORKING_DIR|$(pwd)|g\" /home/$USER/.itools/config.yml\n", "!cat /home/$USER/.itools/config.yml" ] }, @@ -116,8 +141,6 @@ ], "source": [ "network = pp.network.load('Nordic.xiidm')\n", - "network.clone_variant('InitialState', 'BaseCase')\n", - "network.set_working_variant('BaseCase')\n", "display_nad(network.get_network_area_diagram())" ] }, @@ -306,8 +329,7 @@ "metadata": {}, "outputs": [], "source": [ - "network.clone_variant('InitialState', 'TCBCase')\n", - "network.set_working_variant('TCBCase')\n", + "network = pp.network.load('Nordic.xiidm')\n", "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 300)" ] }, From 5299967d3e93911e1844b6ba5a51077182fc5b96 Mon Sep 17 00:00:00 2001 From: Florian Dupuy Date: Thu, 25 Sep 2025 16:55:17 +0200 Subject: [PATCH 10/14] Change link to point to main branch Signed-off-by: Florian Dupuy --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2d6c571..cee3cf3 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,7 @@ - Network, load flow calculation, security analysis and sensitivity analysis [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=pypowsybl_lf_security_sensitivity_analysis.ipynb) - Operator strategy notebook: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=operator_strategy.ipynb) - Computation using Dynaflow: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=dynaflow/pypowsybl_dynaflow.ipynb) -- Dynamic simulation using Dynawo: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/dynawo_simulation_nordic_case?labpath=dynawo/nordic_case/pypowsybl_dynawo.ipynb) +- Dynamic simulation using Dynawo: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=dynawo/nordic_case/pypowsybl_dynawo.ipynb) - Sensitivity analysis and PTDF calculation [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=sensitivity_analysis.ipynb) - Pypowsybl-Jupyter widgets notebooks: - Introduction [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=pypowsybl_jupyter_widgets_demo.ipynb) From d356fe1b461f8af7fee8bbc805c905df995bd8ea Mon Sep 17 00:00:00 2001 From: Florian Dupuy Date: Thu, 25 Sep 2025 16:56:44 +0200 Subject: [PATCH 11/14] Move data to data folder and notebook to root Signed-off-by: Florian Dupuy --- {dynawo => data/dynawo}/nordic_case/Network.par | 0 {dynawo => data/dynawo}/nordic_case/Nordic.par | 0 {dynawo => data/dynawo}/nordic_case/Nordic.xiidm | 0 {dynawo => data/dynawo}/nordic_case/Solver.par | 0 data/dynawo/nordic_case/config.yml | 10 ++++++++++ dynawo/nordic_case/config.yml | 10 ---------- .../pypowsybl_dynawo.ipynb => pypowsybl_dynawo.ipynb | 0 7 files changed, 10 insertions(+), 10 deletions(-) rename {dynawo => data/dynawo}/nordic_case/Network.par (100%) rename {dynawo => data/dynawo}/nordic_case/Nordic.par (100%) rename {dynawo => data/dynawo}/nordic_case/Nordic.xiidm (100%) rename {dynawo => data/dynawo}/nordic_case/Solver.par (100%) create mode 100644 data/dynawo/nordic_case/config.yml delete mode 100644 dynawo/nordic_case/config.yml rename dynawo/nordic_case/pypowsybl_dynawo.ipynb => pypowsybl_dynawo.ipynb (100%) diff --git a/dynawo/nordic_case/Network.par b/data/dynawo/nordic_case/Network.par similarity index 100% rename from dynawo/nordic_case/Network.par rename to data/dynawo/nordic_case/Network.par diff --git a/dynawo/nordic_case/Nordic.par b/data/dynawo/nordic_case/Nordic.par similarity index 100% rename from dynawo/nordic_case/Nordic.par rename to data/dynawo/nordic_case/Nordic.par diff --git a/dynawo/nordic_case/Nordic.xiidm b/data/dynawo/nordic_case/Nordic.xiidm similarity index 100% rename from dynawo/nordic_case/Nordic.xiidm rename to data/dynawo/nordic_case/Nordic.xiidm diff --git a/dynawo/nordic_case/Solver.par b/data/dynawo/nordic_case/Solver.par similarity index 100% rename from dynawo/nordic_case/Solver.par rename to data/dynawo/nordic_case/Solver.par diff --git a/data/dynawo/nordic_case/config.yml b/data/dynawo/nordic_case/config.yml new file mode 100644 index 0000000..9a7c058 --- /dev/null +++ b/data/dynawo/nordic_case/config.yml @@ -0,0 +1,10 @@ +dynawo: + homeDir: "WORKING_DIR/dynawo" + +dynawo-simulation-default-parameters: + parametersFile: "WORKING_DIR/data/dynawo/nordic_case/Nordic.par" + network.parametersFile: "WORKING_DIR/data/dynawo/nordic_case/Network.par" + network.parametersId: "Network" + solver.type: SIM + solver.parametersFile: "WORKING_DIR/data/dynawo/nordic_case/Solver.par" + solver.parametersId: "Solver" diff --git a/dynawo/nordic_case/config.yml b/dynawo/nordic_case/config.yml deleted file mode 100644 index 35df1ce..0000000 --- a/dynawo/nordic_case/config.yml +++ /dev/null @@ -1,10 +0,0 @@ -dynawo: - homeDir: "WORKING_DIR/dynawo" - -dynawo-simulation-default-parameters: - parametersFile: "WORKING_DIR/Nordic.par" - network.parametersFile: "WORKING_DIR/Network.par" - network.parametersId: "Network" - solver.type: SIM - solver.parametersFile: "WORKING_DIR/Solver.par" - solver.parametersId: "Solver" diff --git a/dynawo/nordic_case/pypowsybl_dynawo.ipynb b/pypowsybl_dynawo.ipynb similarity index 100% rename from dynawo/nordic_case/pypowsybl_dynawo.ipynb rename to pypowsybl_dynawo.ipynb From 8a42bc1fb8bc16099e1819f8a36877d33dbae0f0 Mon Sep 17 00:00:00 2001 From: Florian Dupuy Date: Thu, 25 Sep 2025 16:59:18 +0200 Subject: [PATCH 12/14] Fix link and notebook Signed-off-by: Florian Dupuy --- README.md | 2 +- pypowsybl_dynawo.ipynb | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index cee3cf3..733b1cd 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,7 @@ - Network, load flow calculation, security analysis and sensitivity analysis [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=pypowsybl_lf_security_sensitivity_analysis.ipynb) - Operator strategy notebook: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=operator_strategy.ipynb) - Computation using Dynaflow: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=dynaflow/pypowsybl_dynaflow.ipynb) -- Dynamic simulation using Dynawo: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=dynawo/nordic_case/pypowsybl_dynawo.ipynb) +- Dynamic simulation using Dynawo: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=pypowsybl_dynawo.ipynb) - Sensitivity analysis and PTDF calculation [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=sensitivity_analysis.ipynb) - Pypowsybl-Jupyter widgets notebooks: - Introduction [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/powsybl/pypowsybl-notebooks/main?labpath=pypowsybl_jupyter_widgets_demo.ipynb) diff --git a/pypowsybl_dynawo.ipynb b/pypowsybl_dynawo.ipynb index 9b3c003..a35ef77 100644 --- a/pypowsybl_dynawo.ipynb +++ b/pypowsybl_dynawo.ipynb @@ -140,7 +140,7 @@ } ], "source": [ - "network = pp.network.load('Nordic.xiidm')\n", + "network = pp.network.load('data/dynawo/nordic_case/Nordic.xiidm')\n", "display_nad(network.get_network_area_diagram())" ] }, From 8abee8e4fc9610922887ceca12c9054c1c15e2fc Mon Sep 17 00:00:00 2001 From: lisrte Date: Fri, 26 Sep 2025 17:16:27 +0200 Subject: [PATCH 13/14] Add parameters and report node in simulation run Signed-off-by: lisrte --- pypowsybl_dynawo.ipynb | 59 ++++++++++++++++++++++++++++++++---------- 1 file changed, 46 insertions(+), 13 deletions(-) diff --git a/pypowsybl_dynawo.ipynb b/pypowsybl_dynawo.ipynb index a35ef77..cef07c9 100644 --- a/pypowsybl_dynawo.ipynb +++ b/pypowsybl_dynawo.ipynb @@ -103,8 +103,8 @@ "source": [ "import pypowsybl as pp\n", "import pypowsybl.dynamic as dyn\n", + "import pypowsybl.report as rp\n", "import pandas as pd\n", - "import os.path\n", "from pypowsybl_jupyter import display_nad\n", "\n", "def plot(df):\n", @@ -126,7 +126,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c70975f73f56400dbdb07d2941360af0", + "model_id": "26c9750351094bb2810e1f5b5dd0b390", "version_major": 2, "version_minor": 1 }, @@ -225,7 +225,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Run simulation" + "Set simulation parameters and report node" ] }, { @@ -233,9 +233,26 @@ "execution_count": 6, "metadata": {}, "outputs": [], + "source": [ + "param = dyn.Parameters(start_time=0, stop_time=175)\n", + "report_node = rp.Reporter()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], "source": [ "sim = dyn.Simulation()\n", - "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 175)" + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, param, report_node)" ] }, { @@ -247,12 +264,12 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -289,7 +306,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -316,6 +333,22 @@ " mp1_df=measurement1_df)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Modify simulation stop time" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "param.stop_time = 300" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -325,12 +358,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ - "network = pp.network.load('Nordic.xiidm')\n", - "res = sim.run(network, model_mapping, event_mapping, variables_mapping, 0, 300)" + "network = pp.network.load('data/dynawo/nordic_case/Nordic.xiidm')\n", + "res = sim.run(network, model_mapping, event_mapping, variables_mapping, param, report_node)" ] }, { @@ -342,12 +375,12 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 25, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -385,7 +418,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.10.12" } }, "nbformat": 4, From b21d7d651fe73a9e7b2d7deb8f546c08c301b2d7 Mon Sep 17 00:00:00 2001 From: Florian Dupuy Date: Tue, 30 Sep 2025 15:34:33 +0200 Subject: [PATCH 14/14] Fix path of config.yml Signed-off-by: Florian Dupuy --- pypowsybl_dynawo.ipynb | 104 ++++++++++++++++++++++++++++++----------- 1 file changed, 77 insertions(+), 27 deletions(-) diff --git a/pypowsybl_dynawo.ipynb b/pypowsybl_dynawo.ipynb index cef07c9..eac9c2d 100644 --- a/pypowsybl_dynawo.ipynb +++ b/pypowsybl_dynawo.ipynb @@ -37,7 +37,12 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2025-09-30T13:27:40.952466Z", + "start_time": "2025-09-30T13:27:38.730473Z" + } + }, "outputs": [], "source": [ "!curl -L $(curl -s -L -X GET https://api.github.com/repos/dynawo/dynawo/releases/latest | grep \"Dynawo_Linux\" | grep url | cut -d '\"' -f 4) -o Dynawo_Linux_latest.zip\n", @@ -56,7 +61,12 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2025-09-30T13:27:41.889985Z", + "start_time": "2025-09-30T13:27:40.967241Z" + } + }, "outputs": [], "source": [ "pip install pypowsybl matplotlib pypowsybl-jupyter" @@ -79,11 +89,16 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2025-09-30T13:27:42.409371Z", + "start_time": "2025-09-30T13:27:41.960157Z" + } + }, "outputs": [], "source": [ "!mkdir /home/$USER/.itools/\n", - "!cp config.yml /home/$USER/.itools/\n", + "!cp data/dynawo/nordic_case/config.yml /home/$USER/.itools/\n", "!sed -i \"s|WORKING_DIR|$(pwd)|g\" /home/$USER/.itools/config.yml\n", "!cat /home/$USER/.itools/config.yml" ] @@ -97,8 +112,13 @@ }, { "cell_type": "code", - "execution_count": 1, - "metadata": {}, + "execution_count": 4, + "metadata": { + "ExecuteTime": { + "end_time": "2025-09-30T13:27:42.963054Z", + "start_time": "2025-09-30T13:27:42.430684Z" + } + }, "outputs": [], "source": [ "import pypowsybl as pp\n", @@ -120,13 +140,18 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": {}, + "execution_count": 5, + "metadata": { + "ExecuteTime": { + "end_time": "2025-09-30T13:27:43.165839Z", + "start_time": "2025-09-30T13:27:42.968649Z" + } + }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "26c9750351094bb2810e1f5b5dd0b390", + "model_id": "522976f69fff459e86b12783f9d2d41e", "version_major": 2, "version_minor": 1 }, @@ -134,7 +159,7 @@ "NadWidget(diagram_data={'svg_data': '\\n" ] @@ -306,7 +356,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -342,7 +392,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -358,7 +408,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -375,12 +425,12 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { - "image/png": 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P4siRI5g+fbrJh1pLDB48GA4ODjh48KBxXlpaGrKysoxjhb788kv8+uuvxg/LDz74AEDN1bDFixcb1/v000/x4IMP4tNPP8Vdd92FtvDXFzi3RM+ePSGTyZCcnGwy/8KFC1Cr1SaBtDH33HMPKisrsW/fPmzduhWzZ882Ljtz5gyuXr2Kl19+GbfddhvCwsJQWFjY6Pa8vb2Rn59vEmz+fGu+r68vAgICcOHCBZMgHxoaipCQkCbV3FzsfmplPX1qrtQUaLRQl+ugcm7+i7mIqH0JDw/H7NmzsX79+jrLCgsLUVlZaTLP09Ozyd1QTk5OGD58ON58803ceuutxsG7crncZP6ftzdjxgxs374d8+bNw2uvvYbo6GhoNBps2LABe/bswfbt2+uMl/mzwMBA3HvvvVi5ciX27t1bZ3lERAQOHTqE6OhoTJ8+HZ9//vkNj6eoqAhZWVnIzc0FUBNYgJorNH5+flCpVJg/fz6WLVsGDw8PKJVKLFmyBJGRkcZBwj169DDZ5pUrVwDUjBOqHYuzdetWzJs3D+vWrcOwYcOM43GcnJyadIWjsZc3BwUFoays7IYvcAZqunBqj1mv1xs//ENDQ+Hq6tpoDW5ubnj44Yfx1FNPwd7eHuHh4cjOzsby5csxfPhwjBgx4obHAdRcTZo0aRJWrFiB06dPY+bMmcZlQUFBkMvlePPNN7Fo0SKcPHkSL7zwQqPbi4qKwuXLl/Hqq69i6tSp2LdvH7755huTVxg899xzePzxx6FSqRATEwOtVoukpCRcu3bN+M5Ii7jh/VEdhKVu6a5P5EsHRPDyveKXjKtCiJpbVF/dd1os+jhJPPPlr2LN16fFd7/nm337KFFH1NitnLZu3rx54p577jGZl5GRIeRyeZ1buuub/nqL8o1u/161apUAIF5++WWT+atXrxYAxJo1a+qso9PpxGuvvSb69esn5HK5UCqVYvz48eKHH34wadfQLceJiYkCgDh69KgQ4o9buv/st99+Ez4+PuKee+4RWq223tr/vJ/6zsWqVauMbSoqKsSjjz4qunTpIpydncW9995rcjv7X9V33kaPHl3vfubNm9dofX/dZkPrV1RUiHvvvVcEBAQIuVwu/P39xcSJE8Uvv/xisp158+bVu53a2+5vpKKiQqxatUqEhYUJJycnERISIhYuXCguX77cpPVrff311wKAGDVqVJ1lW7duFd26dRMKhUJERkaKPXv2mNxuX9/5feedd0RgYKBwcXERc+fOFS+++GKdW7q3bNkiBg4cKORyuejSpYsYNWqU2LFjR4PH2Rq3dPOFlhYw7z+/4PDZy3jx3v6YPSwYv2QUYfq7dS9HDwpyR1xsHwwNscwthkTtAV9oSUR8oaUN6+1Xe1t3zWCpfSdrLnsODfHAsjt6YdawIDg52OF4VjGmv5uIh/97jLeAExERtRBDjQXUjqs5W1ACIQS+/b0m1Dw8MgSPR/fES/eG4/DTUZg1LAh2MgkHThdi/BtH8MyXJ1CgqWxs00RENuv77783eRbPXydbkZWV1Widf33flaUsWrSowRr++q6vhrz00ksNbiM2NtbCR2B72P1kAb9mF+OeDT/Cy1WOjx4cirvf/KHmyszKO+D4l+dgnL9cilf3ncG3v9e8rM3RQYb5I0Pwt9E9oHTkIGPq+Nj91HFUVFQgJyenweWhoaFtWE3DqqurkZmZ2eDybt26tcmzdwoLC6HRaOpdplQqm/Ssm6KiIhQVFdW7zMnJCTfddFOLamwrrdX9xLufLCD0+pWaK6VV2PpLTeKP6u1dJ9AAQA9vV7x7/xAkZRZhzTdnkHzxGjbEn8fWo1l4PLonZg8LhtyeF9SIyPY5OTnZTHBpjL29vU3U6ePj0+KH9Hl4eFjs1Q/tET8tLcBFYY9ADycAwBdJlwAAMf39Gl1nSDcPfLEoEu/ePxjdvV1wrVyH5746hbH/Pow9v+bCYOgUF9SoE6t9iikRdT6t1WnEKzUW0svHDdlFFajSG+BgJ2FM2I3TuCRJGN/PD9FhPvgsKRtvHDiHrKJyPP7pcbyTcB5/G9Uddw3wh4Mdsyh1HHK5HDKZDLm5ufD29oZcLm/Rk32JqH0RQuDy5cuQJMns14f8FcfUWMjL35zBxsPnAdR0PX304NAbrFFXeVU1Pvg+A+8ePo+yKj0AwF/liPsjgzFtcCC83RStWjORtVRVVSEvLw/l5eXWLoWIrECSJONLX/+KY2psQC/fP/7HjO/XeNdTQ5zl9ng8uifuHx6MLUcv4qOfLiJPXYlX96Xh39+dxbh+vpg+JBAjQ71gz6s31I7J5XIEBQWhuroaer3e2uUQURtzcHAwPiW7JRhqLKTX9XdASRJwR1/fFm2ri4scj93eEwtGdcee1FxsOZqF1OxifP1bPr7+LR+eLnLcNcAfdw8IwODgLrCT8dI9tT+1l55bevmZiDovdj9ZiBACL319Gv4qJzw0svVf4HU6T4Ntv2ThqxN5KCr7402qXZwdMCbMB7eH+SCyuyc8XdlFRURE7Zc5n98MNe2cTm/Aj+lXsOfXXBw8XQh1hembcvv4KzEsxAMDuqowoKs7unu5QMYrOURE1E4w1NSjo4aaP6vWG5B08RoOnCrAD+lXcCa/7qsX3BT26H+TCgMCVegXoEKotyu6e7vU+wwdIiIia2OoqUdnCDV/dblEi8QLV5Fy8RpOXCrG77kaaKvrPgtEkoCoXt74cN4tvIpDREQ2hXc/EQDA202BiREBmBgRAKCmq+pcQSlOXCrGr5fUOFtQgvTCUqgrdIhPu4xjmUUY1t3TylUTERE1D0NNJ+JgJ0PfACX6Bigx4/pjc4QQ+McXJ7A9+RJ2pOQw1BARUbvFh5t0cpIkYergrgCA//stD5U6PiOEiIjaJ4Yawi3dPNC1ixNKtdX47lSBtcshIiJqFoYagkwmYfKgmtfT70i5ZOVqiIiImoehhgAA995c0wV15OxlFJZUWrkaIiIi8zHUEAAgxMsFNwe5wyCAPam51i6HiIjIbLz7iYwm39wVKVnFeCfhPH46fxWODjK4KRzg5SaHl6sCLorrPy4C0FbroamshqZSh/4BKky4fts4ERGRtZgdao4cOYLXXnsNycnJyMvLw86dOzFp0iTj8tWrV2Pbtm3Izs6GXC7H4MGD8eKLL2LYsGHGNkVFRViyZAm++uoryGQyTJkyBevWrav3leO1Kisr8dRTT2Hbtm3QarUYP3483n77bfj6tuxlkfSHuwf4Y83Xp3G1rAqHzhSatW6/ACW6ezf8/4+IiMjSzA41ZWVliIiIwEMPPYTJkyfXWd6rVy+89dZb6N69OyoqKrB27VqMGzcO6enp8Pb2BgDMnj0beXl52L9/P3Q6HR588EEsXLgQW7dubXC/S5cuxf/93/9h+/btUKlUeOyxxzB58mT8+OOP5h4CNcDdWY7dj43E77lqaHUGVFbroS7X4UqpFldKq1BeVQ1JqnnisNxOBjdHe/x6qRhnC0rx2bFsxN3Zx8pHQEREnVmLXpMgSVKdKzV/Vft44wMHDiA6OhqnT59G3759cezYMQwZMgQAsG/fPtx55524dOkSAgLqdmOo1Wp4e3tj69atmDp1KgDgzJkz6NOnDxITEzF8+PAb1toZX5PQFr77PR8LP06Gp4sciXHRkNtzmBYREbUecz6/LfoJVFVVhffeew8qlQoREREAgMTERLi7uxsDDQCMHTsWMpkMR48erXc7ycnJ0Ol0GDt2rHFeWFgYgoKCkJiYWO86Wq0WGo3GZKLWd3uYD3zcFLhaVoUDp/mMGyIish6LhJq9e/fC1dUVjo6OWLt2Lfbv3w8vLy8AQH5+Pnx8fEza29vbw8PDA/n5+fVuLz8/H3K5HO7u7ibzfX19G1xnzZo1UKlUxikwMLDlB0Z12NvJMG1Ize3gn/6SZeVqiIioM7NIqBkzZgxSU1Px008/ISYmBtOnT0dhoXkDT1sqLi4OarXaOGVnZ7fp/juT+4YEAQB+SL+C7KLyBttVVOnxa3Yxki9eg7pc11blERFRJ2GRW7pdXFwQGhqK0NBQDB8+HD179sSHH36IuLg4+Pn51Qk41dXVKCoqgp+fX73b8/PzQ1VVFYqLi02u1hQUFDS4jkKhgEKhaLVjooYFeTrj1lBP/Jh+FZ/8fBGx4f44k6dB9rVyFGq0uFyqReaVMlwsKsefR3B5ucoxupcPXp06AHYyyXoHQEREHUKbPKfGYDBAq9UCACIjI1FcXIzk5GQMHjwYAHDo0CEYDAaT277/bPDgwXBwcMDBgwcxZcoUAEBaWhqysrIQGRnZFodANzDjliD8mH4V7x65gHePXGiwnZerHA52MuSpK3GltApfplzCuH6+GN+v/nBKRETUVGaHmtLSUqSnpxu/z8jIQGpqKjw8PODp6YkXX3wREydOhL+/P65cuYINGzYgJycH06ZNAwD06dMHMTExWLBgATZu3AidTofHHnsMM2bMMN75lJOTg+joaGzevBlDhw6FSqXC/PnzsWzZMnh4eECpVGLJkiWIjIxs0p1PZHnj+vki2NMZF6+Ww8tVjj7+SoR4ucBX6QhvVwVu6uKE3n5u8HKtuXpWpq3Ga9+m4aOfMvHB9xcYaoiIqMXMDjVJSUkYM2aM8ftly5YBAObNm4eNGzfizJkz+O9//4srV67A09MTt9xyC77//nv069fPuM6WLVvw2GOPITo62vjwvfXr1xuX63Q6pKWlobz8j/EZa9euNbb988P3yDYo7O3w7ZOjUKqtNgaXxrgo7PFIVA9sOXoRxzKv4XjWNQwK6tIGlRIRUUfVoufUtCd8To1t+vv2X/FF8iXcFe6PDbNvbrDdtbIq7E7NQU5xBbzdFPBxc0T/m1QI9eFTjImIOjJzPr/57ieyqodvC8EXyZfwzck8ZBeVI9DDGZU6PbKLylFYokVhSSUOnbmMb0/mo0pvMFlXbifDd0tHoZuXi5WqJyIiW8JQQ1YV5qfEqF7eOHL2Mlbt+R0KexkS0i6jQqev07b/TUoM7eaJq2VaHM8qRlZROdYdPIe19w1s+8KJiMjmMNSQ1S24LQRHzl42eYmm0tG+ZpCxmwI9fVwxbUgg+t+kMi7/7ZIaE976AbtSc/BoVA/09HWzRulERGRDGGrI6kaGeuGegQFIyy9BdB8fxPb3R78ApfHlmfUJ76pCTD8/7Ps9H2sPnMXbswc3ug8hBC5eLUfSxWtIvngNXZwd8PdxvSHj83GIiDoMhhqyOkmSsG7GILPXW3pHL3x7Kh9f/5aPkzlqhPq44odzV5BxpQwGISAAXC7R4lSuBqfyNFBXmD7F+JZuHhgT5lP/xomIqN1hqKF2q7efGyZGBGB3ai7+9nEyisurUFZVdyxOLbmdDOFdVdAbBFKzi/F5UnaDoUYIgaKyKuQWVyJXXQGDQaCnrxu6eTrD3o5vIiciskUMNdSuPRHdE3tP5CGnuAIA4K9yxJBuHnCwkyBBgsrJAX383dDHX4mevq5Q2NvhVK4Gd67/HgdOF6CorAoeLnIAwJ5fc/HZsayaIFNcAW21oc7+5PYyjOntjX9PHwgXBX99iIhsCf8qU7vW3dsV62cMwpl8DW4P80FEV/cbjpPpG6BE/5uUOJmjwe7UHDx4awhOXCrGE9uO469PbfJxU8Df3QkQAmcLSlGh0+Pb3wuw8fB5PDWutwWPjIiIzMVQQ+3eXQP8cdcAf7PWmTY4ECdzfsfnSZcwN7Ib/mfnSQgBjO3ji4dvC0GAygm+KgUU9nbGdQwGgd2/5mDpZ7/ivSMXMGNoEG5yd2rtwyEiombi4ADqlO4ZGAC5nQyn8zT4n52/4bccNdwc7fHS5P4Y3t0TQZ7OJoEGAGQyCZMG3oRhIR7QVhvw6r4zVqqeiIjqw1BDnZK7sxx39PMFAGw7lg0A+EdMGHzcHBtdT5IkrLi7LyQJ2J2ai+NZ1yxeKxERNQ1DDXVa04cEGr+OCHTHrKFBTVqv/00qTLm5KwDg+b2nUK2vO6CYiIjaHkMNdVojQ73Q3csFcjsZXpzUH3ZmPIjv6fG94Sy3w/GsYsz+4Cgul2gtWCkRETUF39JNnVpRWRXKtNUI9HA2e939pwrw5LbjKKvSw1epwIZZN2NINw8LVElE1HmZ8/nNUEPUAumFpVj0STLSC0sBACN6eGLG0CCM6+sLSQKq9QIOdjLI7XlRlIioORhq6sFQQ5ZSqq3Gil0nsSs1p85zbgDATiahp48r+gWorr/byq/R91oREdEfGGrqwVBDlnbpWjk+T7qEz49lI19T2WC79TMHYWJEQBtWRkTUfjHU1IOhhtqKwSCgrtDBzk6Cg0yGa+VV+D1Xg70ncrE7NRc+bgoc+nsUXPmaBSKiGzLn85sd/UStTCaT0MVFDqWjA5zkdghwd8IdfX3xypQB6ObpjMISLdYdOGvtMomIOhyGGqI24uhgh9UT+wEA/vNjJtLyS6xcERFRx8JQQ9SGonr7YHw/X+gNAs/u+g1FZVXWLomIqMNgqCFqYyvu7gtHBxmOZV7DsJcO4G8fJ2HPr7lIyy9BpU5v7fKIiNotDhQmsoKEtEL8e/9ZnLikNpkvSUDXLk7o46dEvwAV+gYo0S9ACX+VI28DJ6JOiXc/1YOhhmxRWn4Jvky5hKMXruLClTKUVFbX287d2QHDQjzw7+kD4cK7poioE2GoqQdDDdk6IQSKyqqQVlCCU7kanMrT4FSuBumFpag21PyaPjexH+aN6GbdQomI2pA5n9/8Jx+RjZAkCZ6uCoxwVWBEDy/j/EqdHu8fuYB/7T+LLUcvYm5kMLuiiIjqwYHCRDbO0cEOc0d0g5ODHc4WlCLp4jVrl0REZJMYaojaAZWTg/HVClt+vmjlaoiIbBNDDVE7MXt4EADg69/ycbVUa+VqiIhsD0MNUTsxoKs7wm9SoUpvwBfJl6xdDhGRzWGoIWpH5ly/WrP1lywYDJ3ixkUioiZjqCFqRyZEBMBNYY+LV8vx8OYkdkMREf0Jn1ND1M7sTs3B01+cQFW1Ad5uCsTFhsFOJqFQo4W2Wg8fpSP8lI7wVznCV+UIN4U9bwEnonaLD9+rB0MNdSSn8zR4/NPjOFdYesO2znI79PZzwwdzh8DTVdEG1RERtR5zPr/N7n46cuQIJkyYgICAAEiShF27dhmX6XQ6LF++HOHh4XBxcUFAQADmzp2L3NxcY5uEhARIklTvdOzYsQb3GxUVVaf9okWLzC2fqEPo46/EV0tG4uGRIQjzc0Nkd09MjAjAtMFdMaqXN3r7ukHpWPNszfIqPY5nFeM/P2ZYuWoiIssy+4nCZWVliIiIwEMPPYTJkyebLCsvL0dKSgpWrFiBiIgIXLt2DU888QQmTpyIpKQkAMCIESOQl5dnst6KFStw8OBBDBkypNF9L1iwAM8//7zxe2dnZ3PLJ+owHB3s8OzdfRttU1Glx94TuXj6ixP45OcsLB4TCmc5HyRORB2T2X/dYmNjERsbW+8ylUqF/fv3m8x76623MHToUGRlZSEoKAhyuRx+fn7G5TqdDrt378aSJUtu2O/v7Oxssi4RNc5JbofJN3fFW/HpuHi1HF8kX8LcyG7WLouIyCIsfveTWq2GJElwd3evd/mePXtw9epVPPjggzfc1pYtW+Dl5YX+/fsjLi4O5eXlDbbVarXQaDQmE1FnZCeT8NCtIQCAD3/IgJ63ghNRB2XRUFNZWYnly5dj5syZDQ7u+fDDDzF+/Hh07dq10W3NmjULn3zyCeLj4xEXF4ePP/4Yc+bMabD9mjVroFKpjFNgYGCLjoWoPZs2pCtUTg64eLUcB04XWLscIiKLaNHdT5IkYefOnZg0aVKdZTqdDlOmTMGlS5eQkJBQb6i5dOkSgoOD8fnnn2PKlClm7fvQoUOIjo5Geno6evToUWe5VquFVvvHMzw0Gg0CAwN59xN1Wq/uO4O3E87jlm5dsH3RCGuXQ0TUJBa9+6kpdDodpk+fjosXL2L//v0NFrFp0yZ4enpi4sSJZu9j2LBhAID09PR6lysUCiiVSpOJqDObN6IbHOwkHMu8hv/dewoVVXprl0RE1KpaPdTUBppz587hwIED8PT0rLedEAKbNm3C3Llz4eDgYPZ+UlNTAQD+/v4tKZeo0/BVOuLRqFAAwAc/ZCB23REcOlOAjCtlKCypRHlVNTrJY6uIqIMy++6n0tJSk6sjGRkZSE1NhYeHB/z9/TF16lSkpKRg79690Ov1yM/PBwB4eHhALpcb1zt06BAyMjLw8MMP19lHTk4OoqOjsXnzZgwdOhTnz5/H1q1bceedd8LT0xMnTpzA0qVLMWrUKAwYMKA5x03UKS29oxcGBrrjnzt/Q+bVcjz0UZLJckkCXOT2cFHYwUVhD1eFPbp2ccKayQOgcjL/Hx9ERG3J7DE1CQkJGDNmTJ358+bNw+rVqxESElLvevHx8YiKijJ+P2vWLFy8eBE//vhjnbaZmZkICQkxrpOdnY05c+bg5MmTKCsrQ2BgIO699148++yzTe5W4hOFif6gqdThtX1p2H+qAKXaapRVVaOxvwRPju2JJ8f2arsCiYiu42sS6sFQQ9Qwg0GgQqdHWVU1yrR6lGmrUaqtRlJmEV7/7iw8XeT48Znb4ehgZ+1SiaiTMefzm48WJSLIZBJcFPZwUdgDbn/MHxLcBZ/+ko2c4grsPJ6DmUODrFckEdENWPzhe0TUftnbyfDgrd0A1Dy4z8AH9xGRDWOoIaJG3XdLIFwV9kgvLMXhs5etXQ4RUYMYaoioUW6ODphxS80Tud///oKVqyEiahhDDRHd0IMjQ2Ank/DT+as4lllk7XKIiOrFUENEN3STuxMmD7oJAPD4p8dRVFZl5YqIiOpiqCGiJlk5oS+6e7kgT12JJ7Yd59u+icjmMNQQUZO4OTrg7Tk3w9FBhu/PXcGbh85ZuyQiIhMMNUTUZGF+Srx0bzgAYN3Bc0jLL7FyRUREf2CoISKzTL65K24OcocQwJl8jbXLISIyYqghIrN5uioAAKXaaitXQkT0B4YaIjKbq6LmDSullQw1RGQ7GGqIyGy1oaaMV2qIyIYw1BCR2Vwda0JNCUMNEdkQhhoiMhu7n4jIFjHUEJHZjN1PVQw1RGQ7GGqIyGy1oaaEV2qIyIYw1BCR2WrH1PCWbiKyJQw1RGQ23v1ERLaIoYaIzMaBwkRkixhqiMhsvKWbiGwRQw0Rme3P3U9CCCtXQ0RUg6GGiMxWG2oMAqjQ6a1cDRFRDYYaIjKbs9wOklTzNcfVEJGtYKghIrNJkvTHYGGOqyEiG8FQQ0TNwlBDRLaGoYaImoW3dRORrWGoIaJm4VOFicjWMNQQUbOw+4mIbA1DDRE1C0MNEdkahhoiahaGGiKyNQw1RNQsLhwoTEQ2hqGGiJrFjQOFicjGMNQQUbOw+4mIbI3ZoebIkSOYMGECAgICIEkSdu3aZVym0+mwfPlyhIeHw8XFBQEBAZg7dy5yc3NNttGtWzdIkmQyvfzyy43ut7KyEosXL4anpydcXV0xZcoUFBQUmFs+EbUSdj8Rka0xO9SUlZUhIiICGzZsqLOsvLwcKSkpWLFiBVJSUrBjxw6kpaVh4sSJddo+//zzyMvLM05LlixpdL9Lly7FV199he3bt+Pw4cPIzc3F5MmTzS2fiFoJu5+IyNbYm7tCbGwsYmNj612mUqmwf/9+k3lvvfUWhg4diqysLAQFBRnnu7m5wc/Pr0n7VKvV+PDDD7F161bcfvvtAIBNmzahT58++PnnnzF8+PA662i1Wmi1WuP3Go2mSfsioqap7X4qY6ghIhth8TE1arUakiTB3d3dZP7LL78MT09PDBo0CK+99hqqqxv+w5icnAydToexY8ca54WFhSEoKAiJiYn1rrNmzRqoVCrjFBgY2CrHQ0Q1akNNCUMNEdkIs6/UmKOyshLLly/HzJkzoVQqjfMff/xx3HzzzfDw8MBPP/2EuLg45OXl4d///ne928nPz4dcLq8TjHx9fZGfn1/vOnFxcVi2bJnxe41Gw2BD1Io4poaIbI3FQo1Op8P06dMhhMA777xjsuzPYWPAgAGQy+X429/+hjVr1kChULTK/hUKRatti4jqqh1Tw+4nIrIVFul+qg00Fy9exP79+02u0tRn2LBhqK6uRmZmZr3L/fz8UFVVheLiYpP5BQUFTR6XQ0StyzimpkoPvUFYuRoiIguEmtpAc+7cORw4cACenp43XCc1NRUymQw+Pj71Lh88eDAcHBxw8OBB47y0tDRkZWUhMjKy1Wonoqar7X4CgLIqXq0hIuszu/uptLQU6enpxu8zMjKQmpoKDw8P+Pv7Y+rUqUhJScHevXuh1+uNY148PDwgl8uRmJiIo0ePYsyYMXBzc0NiYiKWLl2KOXPmoEuXLgCAnJwcREdHY/PmzRg6dChUKhXmz5+PZcuWwcPDA0qlEkuWLEFkZGS9dz4RkeUp7GVwsJOg0wuUaauhdHSwdklE1MmZHWqSkpIwZswY4/e142PmzZuH1atXY8+ePQCAgQMHmqwXHx+PqKgoKBQKbNu2DatXr4ZWq0VISAiWLl1qMs5Gp9MhLS0N5eXlxnlr166FTCbDlClToNVqMX78eLz99tvmlk9ErUSSJLgq7HGtXFczWFhl7YqIqLOThBCdojNco9FApVJBrVbfcIwPETXNyFcO4dK1Cux4dARuDupi7XKIqAMy5/Ob734iombjA/iIyJYw1BBRsxlflcBn1RCRDWCoIaJm41OFiciWMNQQUbO5sPuJiGwIQw0RNRu7n4jIljDUEFGz1XY/lfJKDRHZAIYaImo2F4YaIrIhDDVE1Gy8UkNEtoShhoiajWNqiMiWMNQQUbOx+4mIbAlDDRE1G7ufiMiWMNQQUbMZu58YaojIBjDUEFGzuSocAPDhe0RkGxhqiKjZXBR2AIASDhQmIhvAUENEzeZ2/UqNttoAnd5g5WqIqLNjqCGiZqu9UgOwC4qIrI+hhoiazd5OBkeHmj8j7IIiImtjqCGiFqkdLMw7oIjI2hhqiKhFam/rZvcTEVkbQw0RtQjvgCIiW8FQQ0Qt4qd0AgCcztdYuRIi6uwYaoioRW4P8wEAfPd7gZUrIaLOjqGGiFpkbJ+aUJOaXYwCTaWVqyGizoyhhohaxEfpiEFB7gCA/ad4tYaIrIehhohabFxfPwDAdww1RGRFDDVE1GLj+vkCABLPX4GmUmflaoios2KoIaIW6+Htih7eLtDpBQ6nXbZ2OUTUSTHUEFGruINdUERkZQw1RNQqarug4s8UQlutt3I1RNQZMdQQUasY2NUd3m4KlGqrcf+Hv+DH9CsQQli7LCLqRBhqiKhVyGQSnh7fGw52En7JKMLsD45i2sZEFJVVWbs0IuokGGqIqNVMHxKIw0+PwQMjukFhL0PSxWs4cJpjbIiobTDUEFGrCnB3wuqJ/TB9SCAA4PzlUitXRESdBUMNEVlED28XAMCFy2VWroSIOguzQ82RI0cwYcIEBAQEQJIk7Nq1y7hMp9Nh+fLlCA8Ph4uLCwICAjB37lzk5uYa22RmZmL+/PkICQmBk5MTevTogVWrVqGqqvF+96ioKEiSZDItWrTI3PKJqI1093YFAFzglRoiaiNmh5qysjJERERgw4YNdZaVl5cjJSUFK1asQEpKCnbs2IG0tDRMnDjR2ObMmTMwGAx499138fvvv2Pt2rXYuHEj/vnPf95w3wsWLEBeXp5xevXVV80tn4jaSPfrV2qyispRrTdYuRoi6gzszV0hNjYWsbGx9S5TqVTYv3+/yby33noLQ4cORVZWFoKCghATE4OYmBjj8u7duyMtLQ3vvPMOXn/99Ub37ezsDD8/vybVqdVqodVqjd9rNJomrUdErSNA5QRHBxkqdQZkX6tAiJeLtUsiog7O4mNq1Go1JEmCu7t7o208PDxuuK0tW7bAy8sL/fv3R1xcHMrLyxtsu2bNGqhUKuMUGBjYnPKJqJlkMgndPGvH1bALiogsz6KhprKyEsuXL8fMmTOhVCrrbZOeno4333wTf/vb3xrd1qxZs/DJJ58gPj4ecXFx+PjjjzFnzpwG28fFxUGtVhun7OzsFh0LEZmvh3FcDQcLE5Hlmd391FQ6nQ7Tp0+HEALvvPNOvW1ycnIQExODadOmYcGCBY1ub+HChcavw8PD4e/vj+joaJw/fx49evSo016hUEChULTsIIioRWrH1Vy4wis1RGR5FrlSUxtoLl68iP3799d7lSY3NxdjxozBiBEj8N5775m9j2HDhgGoudJDRLapNtSc55UaImoDrX6lpjbQnDt3DvHx8fD09KzTJicnB2PGjMHgwYOxadMmyGTmZ6vU1FQAgL+/f0tLJiIL6e7F7iciajtmh5rS0lKTqyMZGRlITU2Fh4cH/P39MXXqVKSkpGDv3r3Q6/XIz88HAHh4eEAulyMnJwdRUVEIDg7G66+/jsuXLxu3VXtnU05ODqKjo7F582YMHToU58+fx9atW3HnnXfC09MTJ06cwNKlSzFq1CgMGDCgpeeAiCyk9krNlVItNJU6KB0drFwREXVkZoeapKQkjBkzxvj9smXLAADz5s3D6tWrsWfPHgDAwIEDTdaLj49HVFQU9u/fj/T0dKSnp6Nr164mbWrf6KvT6ZCWlma8u0kul+PAgQN44403UFZWhsDAQEyZMgXPPvusueUTURtyc3SAt5sCl0u0uHC5DAMD3a1dEhF1YJKoTRIdnEajgUqlglqtbvBOLCJqffe9m4ijGUX49/QITL65641XICL6E3M+v/nuJyKyqB4+HFdDRG2DoYaILKq7F2/rJqK2wVBDRBbFB/ARUVthqCEii6q9AyrjShkMhk4xhI+IrIShhogsqmsXZ8jtZNBWG5BTXGHtcoioA2OoISKLspNJCPZ0BgBcuMIuKCKyHIYaIrK4Xr5uAIAzeRorV0JEHRlDDRFZXN+AmmdL/J7LUENElsNQQ0QW90eoUVu5EiLqyBhqiMji+l0PNReulKG8qtrK1RBRR8VQQ0QW5+PmCG83BYQATueVWLscIuqgGGqIqE3UXq05xS4oIrIQhhoiahP9A1QAOFiYiCyHoYaI2kQ/3gFFRBbGUENEbaLf9Ss1afkl0OkNVq6GiDoihhoiahOBHk5wc7RHld6A9EK+sZuIWh9DDRG1CUmS0Ne/pgvqZA4HCxNR62OoIaI204+DhYnIghhqiKjN/HFbN0MNEbU+hhoiajP9broeavI0MBiElashoo6GoYaI2kwPb1fI7WUo1VYjq6jc2uUQUQfDUENEbcbBToY+fm4AgENnCq1cDRF1NAw1RNSmpg7uCgB448BZXC3VWrkaIupIGGqIqE3NGhaMvv5KaCqr8eq+NGuXQ0QdCEMNEbUpO5mEFyb1AwB8lpSN41nXrFwREXUUDDVE1OYGB3tgys013VArd/8OPe+EIqJWwFBDRFbxTGwY3Bzt8VuOGusOnrN2OUTUATDUEJFVeLspsGpCTTfU+oPnsOfXXCtXRETtHUMNEVnN1MFdseC2EADA09t/RWp2sXULIqJ2zd7aBRBR5/ZMbB9cuFyGg2cK8fB/j2FCRADC/NwwMLALel9/pg0RUVNIQohOMUJPo9FApVJBrVZDqVRauxwi+pNSbTWmvvMTzuSXmMzfumAYRvTwslJVRGQLzPn8ZvcTEVmdq8IeXzwyAq9OHYCHbg1BoIcTAOB4VrF1CyOidoXdT0RkE1wV9pg+JBAAoHJywNoDZ5FxpczKVRFRe2L2lZojR45gwoQJCAgIgCRJ2LVrl3GZTqfD8uXLER4eDhcXFwQEBGDu3LnIzTW9q6GoqAizZ8+GUqmEu7s75s+fj9LS0kb3W1lZicWLF8PT0xOurq6YMmUKCgoKzC2fiNqBbl7OAIBMhhoiMoPZoaasrAwRERHYsGFDnWXl5eVISUnBihUrkJKSgh07diAtLQ0TJ040aTd79mz8/vvv2L9/P/bu3YsjR45g4cKFje536dKl+Oqrr7B9+3YcPnwYubm5mDx5srnlE1E7EOLlAgDIvMpQQ0RN16KBwpIkYefOnZg0aVKDbY4dO4ahQ4fi4sWLCAoKwunTp9G3b18cO3YMQ4YMAQDs27cPd955Jy5duoSAgIA621Cr1fD29sbWrVsxdepUAMCZM2fQp08fJCYmYvjw4TeslQOFidoPTaUOA1Z/BwD4bfU4uDk6WLkiIrIWmxoorFarIUkS3N3dAQCJiYlwd3c3BhoAGDt2LGQyGY4ePVrvNpKTk6HT6TB27FjjvLCwMAQFBSExMbHedbRaLTQajclERO2D0tEBXq5yAEDmlXIrV0NE7YVFQ01lZSWWL1+OmTNnGtNVfn4+fHx8TNrZ29vDw8MD+fn59W4nPz8fcrncGIxq+fr6NrjOmjVroFKpjFNgYGDLD4iI2kw3z5ouqAx2QRFRE1ks1Oh0OkyfPh1CCLzzzjuW2k2D4uLioFarjVN2dnab10BEzdetdlwNBwsTURNZ5Jbu2kBz8eJFHDp0yKQPzM/PD4WFhSbtq6urUVRUBD8/v3q35+fnh6qqKhQXF5tcrSkoKGhwHYVCAYVC0fKDISKrCGGoISIztfqVmtpAc+7cORw4cACenp4myyMjI1FcXIzk5GTjvEOHDsFgMGDYsGH1bnPw4MFwcHDAwYMHjfPS0tKQlZWFyMjI1j4EIrIB7H4iInOZfaWmtLQU6enpxu8zMjKQmpoKDw8P+Pv7Y+rUqUhJScHevXuh1+uNY148PDwgl8vRp08fxMTEYMGCBdi4cSN0Oh0ee+wxzJgxw3jnU05ODqKjo7F582YMHToUKpUK8+fPx7Jly+Dh4QGlUoklS5YgMjKySXc+EVH7w2fVEJG5zA41SUlJGDNmjPH7ZcuWAQDmzZuH1atXY8+ePQCAgQMHmqwXHx+PqKgoAMCWLVvw2GOPITo6GjKZDFOmTMH69euNbXU6HdLS0lBe/sddD2vXrjW21Wq1GD9+PN5++21zyyeidqL2Ss21ch3U5TqonHlbNxE1ji+0JCKbNfTFAygs0WLX4lsxMNDd2uUQkRXY1HNqiIiai3dAEZE5GGqIyGaFXO+CusBQQ0RNwFBDRDaLV2qIyBwMNURks/hiSyIyB0MNEdms2lCTcaUMneSeBiJqAYYaIrJZwZ41z6opqaxGUVmVlashIlvHUENENsvRwQ4BKkcA7IIiohtjqCEim1Y7WPjCZYYaImocQw0R2bSePq4AgHOFpVauhIhsHUMNEdm0Xn5uAICzBSVWroSIbB1DDRHZtF6+10NNPkMNETWOoYaIbFovn5pQk6uuREmlzsrVEJEtY6ghIpumcnaAr1IBADhbwHE1RNQwhhoisnm1XVDnOK6GiBrBUENENq821KQx1BBRIxhqiMjm9fblHVBEdGMMNURk8/64rZtjaoioYQw1RGTzah/Ad7lEi2t8BxQRNYChhohsnovCHl27OAFgFxQRNYyhhojahV4cV0NEN8BQQ0Ttwh+hhuNqiKh+DDVE1C708q0ZV8PbuomoIQw1RNQu/PkBfEIIK1dDRLaIoYaI2oVQH1fIJOBauQ6XS7XWLoeIbBBDDRG1C44Odgj2dAEAnM5jFxQR1cVQQ0TtxqBAdwDA/+49hVJttXWLISKbw1BDRO3G8tgw+LgpcK6wFMs+S4XBwLE1RPQHhhoiajd8lY549/7BkNvJ8N2pAqw/dM7aJRGRDWGoIaJ2ZVBQF/zvvf0BAG8cOIfjWdesXBER2QqGGiJqd6YPCcSY3t4AgJSsYusWQ0Q2g6GGiNqlbl41d0JdLuHt3URUg6GGiNolbzcFAKCwpNLKlRCRrWCoIaJ2ydu1JtTwSg0R1WKoIaJ2yUfpCIChhoj+YHaoOXLkCCZMmICAgABIkoRdu3aZLN+xYwfGjRsHT09PSJKE1NRUk+WZmZmQJKneafv27Q3u94EHHqjTPiYmxtzyiaiDqL1Sc4WvTCCi68wONWVlZYiIiMCGDRsaXD5y5Ei88sor9S4PDAxEXl6eyfTcc8/B1dUVsbGxje47JibGZL1PP/3U3PKJqIOoHVNztawK1XqDlashIltgb+4KsbGxjYaP+++/H0DNFZn62NnZwc/Pz2Tezp07MX36dLi6uja6b4VCUWddIuqcPFzkkEmAQdQEG9/r3VFE1HlZfUxNcnIyUlNTMX/+/Bu2TUhIgI+PD3r37o1HHnkEV69ebbCtVquFRqMxmYio47CTSfDiYGEi+hOrh5oPP/wQffr0wYgRIxptFxMTg82bN+PgwYN45ZVXcPjwYcTGxkKv19fbfs2aNVCpVMYpMDDQEuUTkRXVdkEx1BAR0Izup9ZUUVGBrVu3YsWKFTdsO2PGDOPX4eHhGDBgAHr06IGEhARER0fXaR8XF4dly5YZv9doNAw2RB0Mn1VDRH9m1Ss1X3zxBcrLyzF37lyz1+3evTu8vLyQnp5e73KFQgGlUmkyEVHH4sMrNUT0J1YNNR9++CEmTpwIb29vs9e9dOkSrl69Cn9/fwtURkTtAbufiOjPzA41paWlSE1NNT5/JiMjA6mpqcjKygIAFBUVITU1FadOnQIApKWlITU1Ffn5+SbbSU9Px5EjR/Dwww/Xu5+wsDDs3LnTuM+nn34aP//8MzIzM3Hw4EHcc889CA0Nxfjx4809BCLqIGqfVVPIUENEaEaoSUpKwqBBgzBo0CAAwLJlyzBo0CCsXLkSALBnzx4MGjQId911F4CasTCDBg3Cxo0bTbbzn//8B127dsW4cePq3U9aWhrUajWAmtvAT5w4gYkTJ6JXr16YP38+Bg8ejO+//x4KhcLcQyCiDsLbjU8VJqI/SEIIYe0i2oJGo4FKpYJareb4GqIO4lhmEaZtTESwpzMOPz3G2uUQkQWY8/lt9Vu6iYiaiy+1JKI/Y6ghonardqBweZUepdpqK1dDRNbGUENE7ZaLwh4ucjsAvFpDRAw1RNTO8bZuIqrFUENE7RpDDRHVYqghonaNr0ogoloMNUTUrvnwWTVEdB1DDRG1a+x+IqJaDDVE1K4Zn1VTylBD1Nkx1BBRu2YcU6NhqCHq7BhqiKhdM3Y/8UoNUafHUENE7ZrP9VBztVQLvaFTvMqOiBrAUENE7ZqHixySBBgEUFRWZe1yiMiK7K1dABFRS9jbyeDposCVUi0uXC7F7tQc/JJRBE9XOfxVTujh7Ypx/XzhYMd/wxF1dAw1RNTuebvVhJqZ7/+M+nqghgR3wZuzBsFf5dT2xRFRm+E/XYio3fNT1oyrMQgg1McVz8SG4Ynonpg2uCvcFPZIungNd63/AQlphVaulIgsSRJCdIqRdRqNBiqVCmq1Gkql0trlEFErOpZZhM+OZePuAf4Y3csbkiQZl2VeKcOjW1JwKk8DANi+KBK3dPOwVqlEZCZzPr95pYaI2r1bunng9WkRiOrtYxJoAKCblwt2PDoCY3p7AwD2ncy3RolE1AYYaoiow3N0sMPEgQEAgONZ16xcDRFZCkMNEXUKgwK7AABO5mqgrdZbuRoisgSGGiLqFII9ndHF2QFV1QacziuxdjlEZAEMNUTUKUiShEFBNVdr2AVF1DEx1BBRpzEo0B0AcDyr2Kp1EJFlMNQQUadxc3DNlZoUXqkh6pAYaoio0xjQVQVJAi5dq0BhSaW1yyGiVsZQQ0SdhpujA3r5uAEAUtkFRdThMNQQUacyKMgdAHA8u9iqdRBR62OoIaJOxRhqOK6GqMNhqCGiTqX2tu4Tl9So1husXA0RtSaGGiLqVEK9XeGmsEd5lR5pBXwIH1FHwlBDRJ2KTCZh4PUuqAc2HcPHiZmoquYVG6KOgKGGiDqd5TFh6NrFCZdLtFix+3eM/fdhnONVG6J2j6GGiDqd/jepcOipKDx/Tz94uSqQVVSOv32SjDJttbVLI6IWYKghok5Jbi/D3Mhu+PbJ2+CndMSFy2X4587fIISwdmlE1Exmh5ojR45gwoQJCAgIgCRJ2LVrl8nyHTt2YNy4cfD09IQkSUhNTa2zjaioKEiSZDItWrSo0f0KIbBy5Ur4+/vDyckJY8eOxblz58wtn4jIhKerAm/NGgQ7mYTdqbnY+kuWtUsiomYyO9SUlZUhIiICGzZsaHD5yJEj8corrzS6nQULFiAvL884vfrqq422f/XVV7F+/Xps3LgRR48ehYuLC8aPH4/KSj7qnIhaZkg3DyyP6Q0AeG7PKZzMUVu5IiJqDntzV4iNjUVsbGyDy++//34AQGZmZqPbcXZ2hp+fX5P2KYTAG2+8gWeffRb33HMPAGDz5s3w9fXFrl27MGPGjDrraLVaaLVa4/cajaZJ+yKizmnBbd3xS8Y1HDhdgCe2HcfeJbfBSW5n7bKIyAxWG1OzZcsWeHl5oX///oiLi0N5eXmDbTMyMpCfn4+xY8ca56lUKgwbNgyJiYn1rrNmzRqoVCrjFBgY2OrHQEQdhyRJeG3qAPi4KXD+chnWfHPa2iURkZmsEmpmzZqFTz75BPHx8YiLi8PHH3+MOXPmNNg+Pz8fAODr62sy39fX17jsr+Li4qBWq41TdnZ26x0AEXVIXVzkeH1aBABgc+JFxJ8ptHJFRGQOs7ufWsPChQuNX4eHh8Pf3x/R0dE4f/48evTo0Sr7UCgUUCgUrbItIuo8RvXyxoO3dsOmHzPx9Be/Yt+To+Dlyr8lRO2BTdzSPWzYMABAenp6vctrx94UFBSYzC8oKGjyuBwioqZaHhOGXr6uuFJahWe+PMHbvInaCZsINbW3ffv7+9e7PCQkBH5+fjh48KBxnkajwdGjRxEZGdkWJRJRJ+LoYId1MwZBbifDgdOFvM2bqJ0wO9SUlpYiNTXVGEQyMjKQmpqKrKyaX/qioiKkpqbi1KlTAIC0tDSkpqYax76cP38eL7zwApKTk5GZmYk9e/Zg7ty5GDVqFAYMGGDcT1hYGHbu3AmgZgDfk08+if/93//Fnj178Ntvv2Hu3LkICAjApEmTWnL8RET16uOvxD+u3+b9wt5TOH+51MoVEdENCTPFx8cLAHWmefPmCSGE2LRpU73LV61aJYQQIisrS4waNUp4eHgIhUIhQkNDxdNPPy3UarXJfgCITZs2Gb83GAxixYoVwtfXVygUChEdHS3S0tKaXLdarRYA6uyHiKgher1BzHo/UQQv3ysmvPm9qKrWW7skok7HnM9vSYjO0Vms0WigUqmgVquhVCqtXQ4RtRN56grEvPE91BU6LLgtBP9zV19rl0TUqZjz+W0TY2qIiGyVv8oJr0yp6Rp///sM7DuZZ+WKiKghDDVERDcQ098PC0d1BwD8ffsJXOD4GiKbxFBDRNQE/xjfG0NDPFCqrcYjn6SgvKra2iUR0V8w1BARNYG9nQxvzRwEbzcF0gpKsPSzVOgNnWJIIlG7wVBDRNREPkpHvDP7ZsjtZPj29wKs+ZrvhyKyJQw1RERmGNLNA69Pr3k/1Ac/ZODjxEzrFkRERgw1RERmmhgRgKfH1zyYb9We3/Ht7/W/WJeI2hZDDRFRMzwa1QP3DQmEQQCPbU3hG72JbABDDRFRM0iShBfv7Y+7wv2h0wv87ZNkfH/usrXLIurUGGqIiJrJ3k6GN2YMxLi+vqiqNmDB5iQcOctgQ2QtDDVERC3gYCfDm7MG4fYwH1TqDHjoo2PYdTzH2mURdUoMNURELaSwt8M7c27GhIgAVBsEnvwsFe8fuWDtsog6HYYaIqJWoLC3w7r7BuKhW0MAAC9+fRrPfHkClTq9lSsj6jwYaoiIWolMJmHF3X3wzzvDIEnAtmPZmLYxEZeulVu7NKJOgaGGiKgVSZKEhaN64KMHh8Ld2QG/5ahx95s/8O3eRG2AoYaIyAJG9/LG3iUjMaCrCsXlOiz6JAWPbU1BUVmVtUsj6rAYaoiILKRrF2dsXxSJxWN6wE4mYe+JPNzx78P4PCmbL8MksgBJCNEpfrM0Gg1UKhXUajWUSqW1yyGiTubEpWI8vf0E0gpKAAB9/JVYcVcfjAj1snJlRLbNnM9vhhoiojairdZj808Xsf7QOZRUVgMAhoV4YFFUD0T18oYkSVaukMj2MNTUg6GGiGxFUVkV1h04i62/ZEGnr/kTHObnhjnDgzEhIgAqJwcrV0hkOxhq6sFQQ0S2Jk9dgQ+/z8Cnv2ShrKrmeTYKexnG9/NDbH8/3NbLG64KeytXSWRdDDX1YKghIlulLtdhe3I2Pk/KxtmCUuN8BzsJw0I8cXOQO/rdpEL/m1QIUDmym8pKhBDQGwR0eoEqvQEGg4BBCOiFgBCo+dpg+rXh+tcGIWAw/PF1R6Wwt0NvP7dW3SZDTT0YaojI1gkhcOKSGrtTc3HoTAEyr9Z9aF8XZwf0v0mFvv5KhHi5IMjDGV27OMNHqYCjg12L9q+t1kNdoYOmQgd1RfX1/9ZMV8uqcLVUC53egFnDgjEw0L1F+2oNQghoqw0or9KjvKoa5VV6lGmrUVGlR9kN5tX+t6raAJ3egCq9gO7619UGYZxfM9WEGJ3egM7xidl83b1dcOipqFbdJkNNPRhqiKi9OX+5FD+mX8HJHDVO5mhwtqAE1Y3cCu6qsIeHixxODnZQOMigsJdBYW8Hhb0MDnay6x/eBlRVG4wf0pU6A0oqa4JLpc7QpLoc7CQ8N7E/Zg0LavaxCSFQqq1GcXnNvq+VV6G4XIfiCh3Uf/q6vKoaZVr99VDyp0Ci1aNcp7eJW+MlCZBJEuwk6Y+vZaZfy6SaBzPWtumo19qCPJ2xbWFkq26ToaYeDDVE1N5pq/U4m1+Kk7lqnMnTIKuoHFlF5ci+VoGq6qYFkhuRJMBNYQ+VswNUTjWT0tEBnq5yeLgocCpXjQOnCwEA9w0JxOSbb4KbowOc5XbGkHKtvArFFToUl9X81xhYrs9XXw8srRlIFPYyuCjs4eRgBxeFHZzk9nCR28FZbg9nec282q+d5fZwUdjB0aEm8MntakKfg70MDnbSH9/bySC3l4xfO9jVtLW3k2ommcwYVshyGGrqwVBDRB2VEAIl2mpcKdGiqKwK2moDtNU1XSvaagO0uporMw520vUP6usf5PYyKOxkUNaGFycHuCnsIZM1/CEthMA7h8/j9W/T0BqZRG4vQxdnB3RxlkPl5AB3Zwe4O8nh7lxTj6uiNpTYw0luBxdjMKmZ5yy3g5ODHezt+CzZjsqcz28OqyciauckSYLSseaKSndvy+/r0ahQhN+kwluH0nG5VIuSymqUa6vh6mhvDCTutUHl+n/dawOLs9wkuLR0HBDRnzHUEBGR2W7r6Y3belo4QRGZidfriIiIqENgqCEiIqIOgaGGiIiIOgSGGiIiIuoQGGqIiIioQ2CoISIiog7B7FBz5MgRTJgwAQEBAZAkCbt27TJZvmPHDowbNw6enp6QJAmpqakmy4uKirBkyRL07t0bTk5OCAoKwuOPPw61Wt3ofh944AFIkmQyxcTEmFs+ERERdVBmh5qysjJERERgw4YNDS4fOXIkXnnllXqX5+bmIjc3F6+//jpOnjyJjz76CPv27cP8+fNvuO+YmBjk5eUZp08//dTc8omIiKiDMvvhe7GxsYiNjW1w+f333w8AyMzMrHd5//798eWXXxq/79GjB1588UXMmTMH1dXVsLdvuCSFQgE/P78m1anVaqHVao3fazSaJq1HRERE7ZNNjKmpfZ9DY4EGABISEuDj44PevXvjkUcewdWrVxtsu2bNGqhUKuMUGBjY2mUTERGRDbF6qLly5QpeeOEFLFy4sNF2MTEx2Lx5Mw4ePIhXXnkFhw8fRmxsLPR6fb3t4+LioFarjVN2drYlyiciIiIbYdV3P2k0Gtx1113o27cvVq9e3WjbGTNmGL8ODw/HgAED0KNHDyQkJCA6OrpOe4VCAYVC0dolExERkY2y2pWakpISxMTEwM3NDTt37oSDg4NZ63fv3h1eXl5IT0+3UIVERETUnlgl1Gg0GowbNw5yuRx79uyBo6Oj2du4dOkSrl69Cn9/fwtUSERERO2N2d1PpaWlJldHMjIykJqaCg8PDwQFBaGoqAhZWVnIzc0FAKSlpQEA/Pz84OfnZww05eXl+OSTT6DRaIx3Jnl7e8POzg4AEBYWhjVr1uDee+9FaWkpnnvuOUyZMgV+fn44f/48/vGPfyA0NBTjx49vUt1CCAC8C4qIiKg9qf3crv0cb5QwU3x8vABQZ5o3b54QQohNmzbVu3zVqlWNrg9AZGRkGPcDQGzatEkIIUR5ebkYN26c8Pb2Fg4ODiI4OFgsWLBA5OfnN7nu7OzsBvfLiRMnTpw4cbLtKTs7+4af9dL1ANHhGQwG5Obmws3NDZIkteq2NRoNAgMDkZ2dDaVS2arb7mh4rpqO56rpeK6ajufKPDxfTWepcyWEQElJCQICAiCTNT5qxqp3P7UlmUyGrl27WnQfSqWSP/RNxHPVdDxXTcdz1XQ8V+bh+Wo6S5wrlUrVpHZWf04NERERUWtgqCEiIqIOgaGmFSgUCqxatYoP+2sCnqum47lqOp6rpuO5Mg/PV9PZwrnqNAOFiYiIqGPjlRoiIiLqEBhqiIiIqENgqCEiIqIOgaGGiIiIOgSGmibasGEDunXrBkdHRwwbNgy//PKLtUuyCatXr4YkSSZTWFiYSZvKykosXrwYnp6ecHV1xZQpU1BQUGClitvGkSNHMGHCBAQEBECSJOzatatOGyEEVq5cCX9/fzg5OWHs2LE4d+6cSZuioiLMnj0bSqUS7u7umD9/PkpLS9voKNpGU87VAw88UOfnLCYmxqRNZzhXALBmzRrccsstcHNzg4+PDyZNmmR8x16tpvzOZWVl4a677oKzszN8fHzw9NNPo7q6ui0PxeKacq6ioqLq/GwtWrTIpE1nOFfvvPMOBgwYYHxwXmRkJL755huTNu3h54qhpgk+++wzLFu2DKtWrUJKSgoiIiIwfvx4FBYWWrs0m9CvXz/k5eUZpx9++MFk+dKlS/HVV19h+/btOHz4MHJzczF58mQrVds2ysrKEBERgQ0bNjTY5tVXX8X69euxceNGHD16FC4uLhg/fjwqKyuNbWbPno3ff/8d+/fvx969e3HkyBEsXLiwLQ6hzTTlXAFATEyMyc/Zp59+arK8M5wrADh8+DAWL16Mn3/+Gfv374dOp8O4ceNQVlZmbHOj3zm9Xo+77roLVVVV+Omnn/Df//4XH330EVauXGmNQ7KYppwrAFiwYIHJz9arr75qXNZZzlXXrl3x8ssvIzk5GUlJSbj99ttxzz334Pfffze2aRc/V01+I2QnNnToULF48WLj93q9XgQEBIg1a9Y0uE58fLy45ZZbhLOzs1CpVGLEiBEiMzOzLcptU6tWrRIRERENLi8uLhYODg5i+/btxnmnT58WAERiYmKD623YsEGEhoYKhUIhfHx8xJQpU1qz7DYFQOzcudNknsFgEH5+fuK1114zzisuLhYKhUJ8+umnQgghTp06JQCIY8eOGdt88803QpIkkZOTU+++DAaDWLVqlQgMDBRyuVz4+/uLJUuWtP5BWUh950oIIebNmyfuueeeBtfrjOeqVmFhoQAgDh8+LIRo2u/c119/LWQymclLgd955x2hVCqFVqutdz9arVYsXrxY+Pn5CYVCIYKCgsRLL71kwSNrfX89V0IIMXr0aPHEE080uE5nPVdCCNGlSxfxwQcfCCHaz88Vr9TcQFVVFZKTkzF27FjjPJlMhrFjxyIxMbHedaqrqzFp0iSMHj0aJ06cQGJiIhYuXNjqL9K0FefOnUNAQAC6d++O2bNnIysry7gsOTkZOp3O5PyFhYUhKCiowfOXlJSExx9/HM8//zzS0tKwb98+jBo1yuLH0ZYyMjKQn59vcl5UKhWGDRtmPC+JiYlwd3fHkCFDjG3Gjh0LmUyGo0eP1rvdL7/8EmvXrsW7776Lc+fOYdeuXQgPD7fswbSRhIQE+Pj4oHfv3njkkUdw9epV47LOfK7UajUAwMPDA0DTfucSExMRHh4OX19fY5vx48dDo9GY/Mv8z9avX489e/bg888/R1paGrZs2YJu3bpZ6Kgs46/nqtaWLVvg5eWF/v37Iy4uDuXl5cZlnfFc6fV6bNu2DWVlZYiMjATQfn6uOs0LLZvrypUr0Ov1Jv+TAMDX1xdnzpypdx2NRgO1Wo27774bPXr0AAD06dPH4rVaw7Bhw/DRRx+hd+/eyMvLw3PPPYfbbrsNJ0+ehJubG/Lz8yGXy+Hu7m6ynq+vL/Lz8+vdZlZWFlxcXHD33XfDzc0NwcHBGDRoUBscTdupPfb6fq5ql+Xn58PHx8dkub29PTw8PBo9d35+fhg7diwcHBwQFBSEoUOHWuAI2lZMTAwmT56MkJAQnD9/Hv/85z8RGxuLxMRE2NnZddpzZTAY8OSTT+LWW29F//79AaBJv3P5+fn1/uzVLqtPVlYWevbsiZEjR0KSJAQHB7fy0VhWfecKAGbNmoXg4GAEBATgxIkTWL58OdLS0rBjxw4Anetc/fbbb4iMjERlZSVcXV2xc+dO9O3bF0D7+bnilRoL8PDwwAMPPIDx48djwoQJWLduHfLy8qxdlkXExsZi2rRpGDBgAMaPH4+vv/4axcXF+Pzzz5u9zTvuuAPBwcHo3r077r//fmzZssXkX07UsGnTpqGiogLdu3fHggULsHPnzg4xoHHGjBmYOHEiwsPDMWnSJOzduxfHjh1DQkJCs7fZEc7V4sWLcfLkSWzbts3i+3rggQeQmpqK3r174/HHH8d3331n8X22pobO1cKFCzF+/HiEh4dj9uzZ2Lx5M3bu3Inz5883e1/t9Vz17t0bqampOHr0KB555BHMmzcPp06dsug+W/tcMdTcgJeXF+zs7OqM8C4oKICfn1+D623atAmJiYkYMWIEPvvsM/Tq1Qs///yzpcu1Ond3d/Tq1Qvp6ekAAD8/P1RVVaG4uNikXWPnz83NDSkpKfj000/h7++PlStXIiIios422rPaY2/s58rPz6/OYPTq6moUFRU1eO4CAwORlpaGt99+G05OTnj00UcxatQo6HQ6CxyF9XTv3h1eXl4mP2ed7Vw99thj2Lt3L+Lj49G1a1fj/Kb8zvn5+dX7s1e7rD4333wzMjIy8MILL6CiogLTp0/H1KlTW/GILKehc1WfYcOGAYDJz1ZnOVdyuRyhoaEYPHgw1qxZg4iICKxbtw5AO/q5avZonE5k6NCh4rHHHjN+r9frxU033dToQOG/Gj58eLschGiukpIS0aVLF7Fu3TohxB+Dy7744gtjmzNnztxwoPCflZaWCnt7e/Hll19apGZLQyMDhV9//XXjPLVaXe9A4aSkJGObb7/9ttHBr39Ve66Tk5NbfiBtoL5zVZ/s7GwhSZLYvXu3EKJznSuDwSAWL14sAgICxNmzZ+ssb8rvXO2AzoKCAmObd999VyiVSlFZWdmkOvbt2ycAiKtXr7bwiCznRueqPj/88IMAIH799VchROc5V/UZM2aMmDdvnhCi/fxcMdQ0wbZt24RCoRAfffSROHXqlFi4cKFwd3c3GeH9ZxcuXBDPPPOM+Omnn0RmZqb49ttvhaenp3j77bfbuHLLe+qpp0RCQoLIyMgQP/74oxg7dqzw8vIShYWFxjaLFi0SQUFB4tChQyIpKUlERkaKyMjIBrf51VdfiXXr1onjx4+LzMxM8fbbbwuZTCZOnjzZFofUKkpKSsTx48fF8ePHBQDx73//Wxw/flxcvHjR2Obll18W7u7uYvfu3eLEiRPinnvuESEhIaKiosLYJiYmRgwaNEgcPXpU/PDDD6Jnz55i5syZDe5306ZN4oMPPhC//fabOH/+vHj22WeFk5OTuHLlikWPtyVudK5KSkrE3//+d5GYmCgyMjLEgQMHxM033yx69uxp8oeyM5wrIYR45JFHhEqlEgkJCSIvL884lZeXG9vc6Heuurpa9O/fX4wbN06kpqaKffv2CW9vbxEXF9fgfv/1r3+JrVu3itOnT4u0tDQxf/584efnJ/R6vUWPtyVudK7S09PF888/L5KSkkRGRobYvXu36N69uxg1apRxG53lXD3zzDPi8OHDIiMjQ5w4cUI888wzQpIk8d133xnbtIefK4aaJnrzzTdFUFCQkMvlYujQoeLnn39usG1+fr6YNGmS8Pf3F3K5XAQHB4uVK1fa9A90c913333G47zpppvEfffdJ9LT003aVFRUiEcffVR06dJFODs7i3vvvVfk5eU1uM3vv/9ejB49WnTp0kU4OTmJAQMGiM8++8zSh9Kq4uPjBYA6U+2/eoSo+VfkihUrhK+vr1AoFCI6OlqkpaWZbOfq1ati5syZwtXVVSiVSvHggw+KkpKSBve7c+dOMWzYMKFUKoWLi4sYPny4OHDggKUOs1Xc6FyVl5eLcePGCW9vb+Hg4CCCg4PFggUL6vyjojOcKyFEvecKgNi0aZOxTVN+5zIzM0VsbKxwcnISXl5e4qmnnhI6na7B/b733nti4MCBwsXFRSiVShEdHS1SUlIsdZit4kbnKisrS4waNUp4eHgIhUIhQkNDxdNPPy3UarXJdjrDuXrooYdEcHCwkMvlwtvbW0RHR5sEGiHax8+VJIQQze+8IiIiIrINHChMREREHQJDDREREXUIDDVERETUITDUEBERUYfAUENEREQdAkMNERERdQgMNURERNQhMNQQERFRh8BQQ0TtwgMPPIBJkyZZuwwismH21i6AiEiSpEaXr1q1CuvWrQMfgE5EjWGoISKry8vLM3792WefYeXKlUhLSzPOc3V1haurqzVKI6J2hN1PRGR1fn5+xkmlUkGSJJN5rq6udbqfoqKisGTJEjz55JPo0qULfH198f7776OsrAwPPvgg3NzcEBoaim+++cZkXydPnkRsbCxcXV3h6+uL+++/H1euXGnjIyYiS2CoIaJ267///S+8vLzwyy+/YMmSJXjkkUcwbdo0jBgxAikpKRg3bhzuv/9+lJeXAwCKi4tx++23Y9CgQUhKSsK+fftQUFCA6dOnW/lIiKg1MNQQUbsVERGBZ599Fj179kRcXBwcHR3h5eWFBQsWoGfPnli5ciWuXr2KEydOAADeeustDBo0CC+99BLCwsIwaNAg/Oc//0F8fDzOnj1r5aMhopbimBoiarcGDBhg/NrOzg6enp4IDw83zvP19QUAFBYWAgB+/fVXxMfH1zs+5/z58+jVq5eFKyYiS2KoIaJ2y8HBweR7SZJM5tXeVWUwGAAApaWlmDBhAl555ZU62/L397dgpUTUFhhqiKjTuPnmm/Hll1+iW7dusLfnnz+ijoZjaoio01i8eDGKioowc+ZMHDt2DOfPn8e3336LBx98EHq93trlEVELMdQQUacREBCAH3/8EXq9HuPGjUN4eDiefPJJuLu7Qybjn0Oi9k4SfEQnERERdQD8pwkRERF1CAw1RERE1CEw1BAREVGHwFBDREREHQJDDREREXUIDDVERETUITDUEBERUYfAUENEREQdAkMNERERdQgMNURERNQhMNQQERFRh/D/ZIgR9O25+i0AAAAASUVORK5CYII=", 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", 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