diff --git a/examples/laugesen_2024_fig_6.ipynb b/examples/laugesen_2024_fig_6.ipynb new file mode 100644 index 0000000..560218d --- /dev/null +++ b/examples/laugesen_2024_fig_6.ipynb @@ -0,0 +1,452 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": "# Impact of changing damage function location on forecast value" + }, + { + "cell_type": "code", + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:13:26.674808Z", + "start_time": "2024-10-15T13:13:26.670553Z" + } + }, + "source": [ + "# Copyright 2023 Richard Laugesen\n", + "\n", + "# Licensed under the Apache License, Version 2.0 (the \"License\");\n", + "# you may not use this file except in compliance with the License.\n", + "# You may obtain a copy of the License at\n", + "\n", + "# https://www.apache.org/licenses/LICENSE-2.0\n", + "\n", + "# Unless required by applicable law or agreed to in writing, software\n", + "# distributed under the License is distributed on an \"AS IS\" BASIS,\n", + "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", + "# See the License for the specific language governing permissions and\n", + "# limitations under the License." + ], + "outputs": [], + "execution_count": 1 + }, + { + "cell_type": "code", + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:13:28.016652Z", + "start_time": "2024-10-15T13:13:26.684815Z" + } + }, + "source": [ + "import sys\n", + "import numpy as np\n", + "import pandas as pd\n", + "from matplotlib import pyplot as plt\n", + "\n", + "sys.path.append('..')\n", + "from ruv.relative_utility_value import relative_utility_value\n", + "from ruv.damage_functions import logistic\n", + "from ruv.economic_models import cost_loss, cost_loss_analytical_spend\n", + "from ruv.utility_functions import cara\n", + "from ruv.decision_rules import optimise_over_forecast_distribution\n", + "from ruv.helpers import risk_aversion_coef_to_risk_premium, risk_premium_to_risk_aversion_coef" + ], + "outputs": [], + "execution_count": 2 + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": "# Load example forecast dataset" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:13:29.176026Z", + "start_time": "2024-10-15T13:13:28.205081Z" + } + }, + "cell_type": "code", + "source": [ + "# Steamflow at Biggara in the Murray catchment of the southern Murray-Darling basin\n", + "# Subseasonal streamflow forecasts from MuTHRE\n", + "\n", + "# load forecasts (and obs) and climatology\n", + "data = pd.read_csv('example_data/401012-muthre.csv.zip', index_col=0, parse_dates=True, dayfirst=True, compression='zip')\n", + "clim = pd.read_csv('example_data/401012-climatology.csv.zip', index_col=0, parse_dates=True, dayfirst=True, compression='zip')\n", + "\n", + "# convert runoff to cumecs\n", + "data *= 1165 / 86.4\n", + "clim *= 1165 / 86.4\n", + "\n", + "# filter to the first week of each month\n", + "data = data[(data.index.day >= 1) & (data.index.day <= 7)]\n", + "clim = clim[(clim.index.day >= 1) & (clim.index.day <= 7)]\n", + "\n", + "# fetch the obs and forecast ensemble\n", + "obs = data['obs']\n", + "fcst = data[[col for col in data.columns if col.startswith('ens-')]]\n", + "clim = clim[[col for col in clim.columns if col.startswith('ens-')]]\n", + "\n", + "# clean climatology of NA ensemble members from ragged 14-day moving average climatology dataset\n", + "clim_arr = clim.to_numpy()\n", + "sorted_arr = np.take_along_axis(clim_arr, np.argsort(np.isnan(clim_arr), axis=1, kind='stable'), axis=1)\n", + "max_size_ens = np.count_nonzero(~np.isnan(clim_arr), axis=1).min()\n", + "ens = sorted_arr[:, :max_size_ens]\n", + "clim = pd.DataFrame(ens, index=clim.index, columns=[f\"ens-{i+1}\" for i in range(max_size_ens)])\n", + "\n", + "# RUV library expects numpy arrays\n", + "obs = obs.values\n", + "fcst = fcst.values\n", + "clim = clim.values\n", + "\n", + "print(obs.shape, fcst.shape, clim.shape)" + ], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1932,) (1932, 100) (1932, 484)\n" + ] + } + ], + "execution_count": 3 + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": "# Experiment setup" + }, + { + "cell_type": "code", + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:13:29.209043Z", + "start_time": "2024-10-15T13:13:29.202554Z" + } + }, + "source": [ + "parallel_nodes = 2\n", + "\n", + "# define range of alphas we will calculate over\n", + "alpha_step = 0.05\n", + "alphas = np.arange(alpha_step, 1, alpha_step)\n", + "select_alphas = [0.1, 0.5, 0.9]\n", + "\n", + "# define the thresholds we will move the damage function through \n", + "threshold_step = 10\n", + "damage_function_thresholds = np.arange(0, np.nanmax(obs) * 1.3, threshold_step)\n", + "select_damage_function_thresholds = [50, 100, 150]\n", + "\n", + "# calculate adjust the risk aversion coefficient according to the max damages\n", + "target_unity_risk_aversion = 0.15\n", + "max_damages = 10000\n", + "target_risk_premium = risk_aversion_coef_to_risk_premium(target_unity_risk_aversion, 1)\n", + "adjusted_risk_aversion = risk_premium_to_risk_aversion_coef(target_risk_premium, max_damages)\n", + "\n", + "# use 14-day moving average climatology as reference\n", + "ref = clim" + ], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\me\\work\\research\\software\\relative-utility-value\\ruv\\helpers.py:64: RuntimeWarning: overflow encountered in exp\n", + " return np.log(0.5 * (np.exp(-A * gamble_size) + np.exp(A * gamble_size))) / (A * gamble_size) - risk_premium\n" + ] + } + ], + "execution_count": 4 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "# Value diagram for three damage functions" + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Define decision context" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:13:29.238198Z", + "start_time": "2024-10-15T13:13:29.233614Z" + } + }, + "cell_type": "code", + "source": [ + "decision_context = {\n", + " 'utility_function': [cara, {'A': adjusted_risk_aversion}],\n", + " 'decision_rule': [optimise_over_forecast_distribution, None],\n", + " 'decision_thresholds': None,\n", + " 'economic_model': [cost_loss, cost_loss_analytical_spend, alphas],\n", + " 'damage_function': [logistic, {'k': 0.2, 'A': max_damages, 'threshold': None}]\n", + "}" + ], + "outputs": [], + "execution_count": 5 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Calculate RUV" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:16:58.026659Z", + "start_time": "2024-10-15T13:13:29.264196Z" + } + }, + "cell_type": "code", + "source": [ + "results = pd.DataFrame(index=alphas, columns=select_damage_function_thresholds)\n", + "for damage_function_threshold in select_damage_function_thresholds:\n", + " print('Calculating RUV for damage function threshold %.2f' % damage_function_threshold)\n", + " decision_context['damage_function'][1]['threshold'] = damage_function_threshold\n", + " results[damage_function_threshold] = relative_utility_value(obs, fcst, ref, decision_context, parallel_nodes)['ruv'] " + ], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating RUV for damage function threshold 50.00\n", + "Calculating RUV for damage function threshold 100.00\n", + "Calculating RUV for damage function threshold 150.00\n" + ] + } + ], + "execution_count": 6 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Plot results" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:16:58.596378Z", + "start_time": "2024-10-15T13:16:58.076696Z" + } + }, + "cell_type": "code", + "source": [ + "for damage_function_threshold in select_damage_function_thresholds:\n", + " results[damage_function_threshold].plot(label=r'$q_\\tau$ = %.0f' % damage_function_threshold)\n", + "plt.title('Value diagram for three damage functions')\n", + "plt.xlabel(r'Relative expense of mitigation ($\\alpha$)')\n", + "plt.ylabel('Forecast value (RUV)')\n", + "plt.ylim(0, 1)\n", + "plt.xlim(0, 1)\n", + "plt.legend()" + ], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": [ + "
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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "execution_count": 7 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "# Value for damage functions of varying location" + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Define decision context" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:16:58.645951Z", + "start_time": "2024-10-15T13:16:58.639591Z" + } + }, + "cell_type": "code", + "source": [ + "decision_context = {\n", + " 'utility_function': [cara, {'A': adjusted_risk_aversion}],\n", + " 'decision_rule': [optimise_over_forecast_distribution, None],\n", + " 'decision_thresholds': None,\n", + " 'economic_model': [cost_loss, cost_loss_analytical_spend, select_alphas],\n", + " 'damage_function': [logistic, {'k': 0.2, 'A': max_damages, 'threshold': None}]\n", + "}" + ], + "outputs": [], + "execution_count": 8 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Calculate RUV" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:23:19.943598Z", + "start_time": "2024-10-15T13:16:58.672143Z" + } + }, + "cell_type": "code", + "source": [ + "results = pd.DataFrame(index=damage_function_thresholds, columns=select_alphas)\n", + "for damage_function_threshold in damage_function_thresholds:\n", + " print('Calculating RUV for damage function threshold %.2f' % damage_function_threshold)\n", + " decision_context['damage_function'][1]['threshold'] = damage_function_threshold\n", + " results.loc[damage_function_threshold] = relative_utility_value(obs, fcst, ref, decision_context, parallel_nodes)['ruv']" + ], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating RUV for damage function threshold 0.00\n", + "Calculating RUV for damage function threshold 10.00\n", + "Calculating RUV for damage function threshold 20.00\n", + "Calculating RUV for damage function threshold 30.00\n", + "Calculating RUV for damage function threshold 40.00\n", + "Calculating RUV for damage function threshold 50.00\n", + "Calculating RUV for damage function threshold 60.00\n", + "Calculating RUV for damage function threshold 70.00\n", + "Calculating RUV for damage function threshold 80.00\n", + "Calculating RUV for damage function threshold 90.00\n", + "Calculating RUV for damage function threshold 100.00\n", + "Calculating RUV for damage function threshold 110.00\n", + "Calculating RUV for damage function threshold 120.00\n", + "Calculating RUV for damage function threshold 130.00\n", + "Calculating RUV for damage function threshold 140.00\n", + "Calculating RUV for damage function threshold 150.00\n", + "Calculating RUV for damage function threshold 160.00\n", + "Calculating RUV for damage function threshold 170.00\n", + "Calculating RUV for damage function threshold 180.00\n", + "Calculating RUV for damage function threshold 190.00\n", + "Calculating RUV for damage function threshold 200.00\n", + "Calculating RUV for damage function threshold 210.00\n", + "Calculating RUV for damage function threshold 220.00\n", + "Calculating RUV for damage function threshold 230.00\n", + "Calculating RUV for damage function threshold 240.00\n", + "Calculating RUV for damage function threshold 250.00\n", + "Calculating RUV for damage function threshold 260.00\n", + "Calculating RUV for damage function threshold 270.00\n", + "Calculating RUV for damage function threshold 280.00\n", + "Calculating RUV for damage function threshold 290.00\n", + "Calculating RUV for damage function threshold 300.00\n", + "Calculating RUV for damage function threshold 310.00\n", + "Calculating RUV for damage function threshold 320.00\n", + "Calculating RUV for damage function threshold 330.00\n" + ] + } + ], + "execution_count": 9 + }, + { + "metadata": {}, + "cell_type": "markdown", + "source": "## Plot results" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-10-15T13:23:20.148265Z", + "start_time": "2024-10-15T13:23:19.979414Z" + } + }, + "cell_type": "code", + "source": [ + "results.plot()\n", + "plt.title('Value for damage functions of varying location')\n", + "plt.xlabel(r'Logistic threshold $q_\\tau$ ($m^3/s$)')\n", + "plt.ylabel('Forecast value (RUV)')\n", + "plt.ylim(0, 1)\n", + "plt.legend()" + ], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": [ + "
" + ], + "image/png": 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" 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