diff --git a/.vscode/settings.json b/.vscode/settings.json index b81381a7..35d5ef9f 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -11,12 +11,15 @@ }, "files.insertFinalNewline": true, "files.trimFinalNewlines": true, - + + "editor.formatOnSave": true, "editor.codeActionsOnSave": { "source.organizeImports": "explicit" }, - "editor.defaultFormatter": null, - "editor.formatOnSave": true, + "notebook.formatOnSave.enabled": true, + "notebook.codeActionsOnSave": { + "source.organizeImports": "explicit" + }, "autopep8.importStrategy": "fromEnvironment", "isort.importStrategy": "fromEnvironment", @@ -36,6 +39,7 @@ "*_test.py" ], + "editor.defaultFormatter": null, "[python]": { "editor.detectIndentation": false, "editor.insertSpaces": true, diff --git a/doc/devlog/2023-11-08-age-ipm.ipynb b/doc/devlog/2023-11-08-age-ipm.ipynb new file mode 100644 index 00000000..9599641a --- /dev/null +++ b/doc/devlog/2023-11-08-age-ipm.ipynb @@ -0,0 +1,304 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# devlog 2023-11-08: age-class IPMs\n", + "\n", + "NOTE: this notebook was started by Jarom. It demonstrates building a classed IPM with two classes, as well as a script to automate that construction. This is likely off-target for how we want the system to do this, but may have useful insights in any case." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# type: ignore\n", + "from sympy import Max\n", + "\n", + "from epymorph.data_shape import Shapes\n", + "from epymorph.ipm.attribute import param\n", + "from epymorph.ipm.compartment_ipm import CompartmentModelIpmBuilder\n", + "from epymorph.ipm.compartment_model import (compartment, create_model,\n", + " create_symbols, edge)\n", + "from epymorph.ipm.ipm import IpmBuilder\n", + "\n", + "\n", + "def constructAgeIPM() -> IpmBuilder:\n", + " symbols = create_symbols(\n", + " compartments=[\n", + " compartment('Sa'),\n", + " compartment('Sb'),\n", + " compartment('Ia'),\n", + " compartment('Ib'),\n", + " compartment('Ra'),\n", + " compartment('Rb'),\n", + " ],\n", + " attributes=[\n", + " param('betaAA', shape=Shapes.TxN), # infectivity from a to a\n", + " param('betaBA', shape=Shapes.TxN), # infectivity from a to b\n", + " param('betaBB', shape=Shapes.TxN), # infectivity from b to b\n", + " param('betaAB', shape=Shapes.TxN), # infectivity from b to a\n", + " param('gamma', shape=Shapes.TxN), # progression from infected to recovered\n", + " ])\n", + "\n", + " [Sa, Sb, Ia, Ib, Ra, Rb] = symbols.compartment_symbols\n", + " [βAA, βBA, βBB, βAB, γ,] = symbols.attribute_symbols\n", + "\n", + " # formulate N so as to avoid dividing by zero;\n", + " # this is safe in this instance because if the denominator is zero,\n", + " # the numerator must also be zero\n", + " N = Max(1, Sa + Ia + Ra + Sb + Ib + Rb)\n", + "\n", + " Age_SIR = create_model(\n", + " symbols=symbols,\n", + " transitions=[\n", + " edge(Sa, Ia, rate=Sa * (βAA * Ia + βAB * Ib) / N),\n", + " edge(Sb, Ib, rate=Sb * (βBB * Ib + βBA * Ia) / N),\n", + " edge(Ia, Ra, rate=γ * Ia),\n", + " edge(Ib, Rb, rate=γ * Ib),\n", + " ])\n", + "\n", + " return CompartmentModelIpmBuilder(Age_SIR)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# type: ignore\n", + "from sympy import Max\n", + "\n", + "from epymorph.data_shape import Shapes\n", + "from epymorph.ipm.attribute import param\n", + "from epymorph.ipm.compartment_ipm import CompartmentModelIpmBuilder\n", + "from epymorph.ipm.compartment_model import (compartment, create_model,\n", + " create_symbols, edge)\n", + "from epymorph.ipm.ipm import IpmBuilder\n", + "\n", + "\n", + "def iterateAgeIPM(age_classes) -> IpmBuilder:\n", + "\n", + " # Create empty arrays for compartments and attributes\n", + " all_compartments = [None] * age_classes * 3 # S, I, and R for each age class\n", + " # Beta value for each age class interaction with\n", + " all_attributes = [None] * (age_classes * age_classes + 1)\n", + " # other classes (including itself), plus one for gamma\n", + "\n", + " # Create a set of compartments for each age class\n", + " for comp in range(age_classes):\n", + " # Classifier id starts at 'a' and increments each age class\n", + " classId = chr(97 + comp)\n", + " all_compartments[comp] = compartment('S' + classId) # Susceptible\n", + " all_compartments[comp + age_classes] = compartment('I' + classId) # Infected\n", + " all_compartments[comp + 2 *\n", + " age_classes] = compartment('R' + classId) # Recovered\n", + "\n", + " num = 0 # Value to increment location of beta value\n", + " # Creating beta values for each interaction\n", + " for rec in range(age_classes):\n", + " # Classifier id for the reciever starts at 'A' and increments for each age class\n", + " recId = chr(65 + rec)\n", + " for tran in range(age_classes):\n", + " # Classifier id for the transmitter starts at 'A' and increments\n", + " tranId = chr(65 + tran)\n", + " # Beta value between reciever and transmitter\n", + " all_attributes[num] = param('beta' + recId + tranId, shape=Shapes.TxN)\n", + " num += 1 # Increment location value\n", + "\n", + " # Add gamma at the last index\n", + " all_attributes[-1] = param('gamma', shape=Shapes.TxN)\n", + "\n", + " # Create symbols using compartment and attribute arrays\n", + " symbols = create_symbols(\n", + " compartments=all_compartments,\n", + " attributes=all_attributes)\n", + "\n", + " # Create empty arrays for the transmission rates and the number of transitions\n", + " num_rates = [None] * age_classes\n", + " all_transitions = [None] * (age_classes * 2)\n", + "\n", + " # formulate N so as to avoid dividing by zero;\n", + " # this is safe in this instance because if the denominator is zero,\n", + " # the numerator must also be zero\n", + " N = 0\n", + " for sym in range(len(symbols.compartment_symbols)):\n", + " N += symbols.compartment_symbols[sym]\n", + " N = Max(1, N)\n", + "\n", + " # Create a rate for each S -> I transition\n", + " for age in range(age_classes):\n", + " additiveRates = 0 # Value to track the additive rate between the current susceptible and all infected compartments\n", + " for pairs in range(age_classes):\n", + " # Add each rate to the additive rate (Apropriate beta value * Infected of age class)\n", + " additiveRates += (symbols.attribute_symbols[age * age_classes + pairs] * # Beta value\n", + " symbols.compartment_symbols[age_classes + pairs]) # Infected compartment of age class\n", + "\n", + " # Calculate final rate and place in the rates array\n", + " rate = symbols.compartment_symbols[age] * additiveRates / N\n", + " num_rates[age] = rate\n", + "\n", + " # Create each transition\n", + " for trans in range(age_classes):\n", + " # Create S -> I transition\n", + " SItransition = edge(symbols.compartment_symbols[trans], # Susceptible compartment\n", + " # Infected compartment\n", + " symbols.compartment_symbols[age_classes + trans],\n", + " rate=num_rates[trans]) # Transition rate\n", + "\n", + " # Place transition in the transition array\n", + " all_transitions[trans] = SItransition\n", + "\n", + " # Create I -> R transition (rate is gamma value * infected)\n", + " IRtransition = edge(symbols.compartment_symbols[age_classes + trans], # Infected compartment\n", + " # Recovered compartment\n", + " symbols.compartment_symbols[age_classes * 2 + trans],\n", + " rate=symbols.attribute_symbols[-1] * # Gamma value\n", + " symbols.compartment_symbols[age_classes + trans]) # Infected compartment\n", + "\n", + " # Place transition in the transition array\n", + " all_transitions[age_classes + trans] = IRtransition\n", + "\n", + " # Create model with symbols object and the transition array\n", + " Age_SIR_Iterable = create_model(\n", + " symbols=symbols,\n", + " transitions=all_transitions\n", + " )\n", + "\n", + " # return the model builder\n", + " return CompartmentModelIpmBuilder(Age_SIR_Iterable)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import date\n", + "from functools import partial\n", + "\n", + "import numpy as np\n", + "\n", + "from epymorph.data import geo_library, mm_library\n", + "from epymorph.initializer import explicit\n", + "from epymorph.simulation import Simulation\n", + "\n", + "# Note: the 'library' dictionaries contain functions which load the named component,\n", + "# so you have to apply the function to get the _actual_ component.\n", + "\n", + "# The 'pei' model family (IPM/MM/GEO) implement an SIRS model in 6 US states.\n", + "# (Remember: it is possible to mix-and-match the models!)\n", + "sim = Simulation(\n", + " geo=geo_library['pei'](),\n", + " ipm_builder=constructAgeIPM(),\n", + " mvm_builder=mm_library['pei']()\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "out = sim.run(\n", + " param={\n", + " 'theta': 0.1,\n", + " 'move_control': 0.9,\n", + " 'betaAA': 2.3,\n", + " 'betaBA': 1.4,\n", + " 'betaAB': 1.8,\n", + " 'betaBB': 1.7,\n", + " 'gamma': 0.75,\n", + " },\n", + " start_date=date(2015, 1, 1),\n", + " duration_days=150,\n", + " initializer=partial(explicit, initials=np.array([\n", + " [100000, 10000, 1000, 1, 1, 1],\n", + " [100000, 10000, 1, 1, 1, 1],\n", + " [100000, 10000, 1, 1, 1, 1],\n", + " [100000, 10000, 1, 1, 1, 1],\n", + " [100000, 10000, 1, 1, 1, 1],\n", + " [100000, 10000, 1, 1, 1, 1]\n", + " ], dtype=np.int64)),\n", + " # I've provided a seeded RNG here just to keep this notebook's results consistent,\n", + " # but the rng param is optional! If not given, a new RNG is constructed for each run\n", + " # using numpy's default_rng.\n", + " rng=np.random.default_rng(1)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[97294 9770 1073 31 199 1]\n", + " [97967 9868 2201 121 833 13]\n", + " [94982 9593 2551 147 1113 31]\n", + " [93173 9539 5107 353 2721 110]]\n" + ] + } + ], + "source": [ + "from epymorph.run import plot_event, plot_pop\n", + "\n", + "plot_pop(out, 0) # prevalence for all compartments in population 0.\n", + "\n", + "plot_event(out, 0) # incidence data for the S->I event across all populations.\n", + "\n", + "print(out.prevalence[0:4, 0, :])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/doc/devlog/2024-02-06.ipynb b/doc/devlog/2024-02-06.ipynb new file mode 100644 index 00000000..cd8036f9 --- /dev/null +++ b/doc/devlog/2024-02-06.ipynb @@ -0,0 +1,432 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# devlog 2024-02-06\n", + "\n", + "Development of age-structured IPMs.\n", + "\n", + "Our first task is to \"hand-build\" an age-structured IPM where the compartmental model for each class is the same. (I will use age as the class distinction here, because it is relatively straight-forward to acquire breakdowns of population by age. But it's worth remembering that in many ways \"age\" is a placeholder for any type of classification -- by race/ethnicity, or risk category, socio-economic class, etc.)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from sympy import Max\n", + "\n", + "from epymorph import *\n", + "from epymorph.compartment_model import *\n", + "\n", + "# Basing these age classes on:\n", + "# \"Age-stratified transmission model of COVID-19 in Ontario with human mobility during pandemic's first wave\"; 2021; Fields, et al\n", + "# https://doi.org/10.1016%2Fj.heliyon.2021.e07905\n", + "\n", + "# age classes:\n", + "# 1: [0,20) years\n", + "# 2: [20,60) years\n", + "# 3: [60,80) years\n", + "\n", + "\n", + "def construct_ipm_1() -> CompartmentModel:\n", + " # IPM 1:\n", + " # This IPM combines all infection pressure for an age class into one event.\n", + " symbols = create_symbols(\n", + " compartments=[\n", + " compartment('S_1'),\n", + " compartment('S_2'),\n", + " compartment('S_3'),\n", + " compartment('I_1'),\n", + " compartment('I_2'),\n", + " compartment('I_3'),\n", + " compartment('R_1'),\n", + " compartment('R_2'),\n", + " compartment('R_3'),\n", + " ],\n", + " attributes=[\n", + " # infectivity matrix\n", + " # (Would be nicer to pass a CxC, TxCxC, or TxNxCxC array... but how would we unpack it?)\n", + " param('beta_11', shape=Shapes.TxN),\n", + " param('beta_12', shape=Shapes.TxN),\n", + " param('beta_13', shape=Shapes.TxN),\n", + " param('beta_21', shape=Shapes.TxN),\n", + " param('beta_22', shape=Shapes.TxN),\n", + " param('beta_23', shape=Shapes.TxN),\n", + " param('beta_31', shape=Shapes.TxN),\n", + " param('beta_32', shape=Shapes.TxN),\n", + " param('beta_33', shape=Shapes.TxN),\n", + " # progression from infected to recovered\n", + " param('gamma', shape=Shapes.TxN),\n", + " # progression from recovered to susceptible\n", + " param('xi', shape=Shapes.TxN),\n", + " ])\n", + "\n", + " [S_1, S_2, S_3, I_1, I_2, I_3, R_1, R_2, R_3] = symbols.compartment_symbols\n", + " [beta_11, beta_12, beta_13, beta_21, beta_22, beta_23, beta_31,\n", + " beta_32, beta_33, gamma, xi] = symbols.attribute_symbols\n", + "\n", + " N_1 = Max(1, S_1 + I_1 + R_1)\n", + " N_2 = Max(1, S_2 + I_2 + R_2)\n", + " N_3 = Max(1, S_3 + I_3 + R_3)\n", + "\n", + " return create_model(\n", + " symbols=symbols,\n", + " transitions=[\n", + " edge(S_1, I_1,\n", + " rate=S_1 * ((beta_11 * I_1 / N_1) + (beta_12 * I_2 / N_2) + (beta_13 * I_3 / N_3))),\n", + " edge(S_2, I_2,\n", + " rate=S_2 * ((beta_21 * I_1 / N_1) + (beta_22 * I_2 / N_2) + (beta_23 * I_3 / N_3))),\n", + " edge(S_3, I_3,\n", + " rate=S_3 * ((beta_31 * I_1 / N_1) + (beta_32 * I_2 / N_2) + (beta_33 * I_3 / N_3))),\n", + " edge(I_1, R_1, rate=gamma * I_1),\n", + " edge(I_2, R_2, rate=gamma * I_2),\n", + " edge(I_3, R_3, rate=gamma * I_3),\n", + " edge(R_1, S_1, rate=xi * R_1),\n", + " edge(R_2, S_2, rate=xi * R_2),\n", + " edge(R_3, S_3, rate=xi * R_3),\n", + " ])\n", + "\n", + "\n", + "def construct_ipm_2() -> CompartmentModel:\n", + " # IPM 2:\n", + " # This IPM mocks a more modular configuration, as though three separate IPMs were combined with meta-edges.\n", + " # In this case, the infection pressures attributed to each pair of age classes are represented as separate events.\n", + " symbols = create_symbols(\n", + " compartments=[\n", + " compartment('S_1'),\n", + " compartment('S_2'),\n", + " compartment('S_3'),\n", + " compartment('I_1'),\n", + " compartment('I_2'),\n", + " compartment('I_3'),\n", + " compartment('R_1'),\n", + " compartment('R_2'),\n", + " compartment('R_3'),\n", + " ],\n", + " attributes=[\n", + " # infectivity matrix\n", + " param('beta_11', shape=Shapes.TxN),\n", + " param('beta_12', shape=Shapes.TxN),\n", + " param('beta_13', shape=Shapes.TxN),\n", + " param('beta_21', shape=Shapes.TxN),\n", + " param('beta_22', shape=Shapes.TxN),\n", + " param('beta_23', shape=Shapes.TxN),\n", + " param('beta_31', shape=Shapes.TxN),\n", + " param('beta_32', shape=Shapes.TxN),\n", + " param('beta_33', shape=Shapes.TxN),\n", + " # progression from infected to recovered\n", + " param('gamma', shape=Shapes.TxN),\n", + " # progression from recovered to susceptible\n", + " param('xi', shape=Shapes.TxN),\n", + " ])\n", + "\n", + " [S_1, S_2, S_3, I_1, I_2, I_3, R_1, R_2, R_3] = symbols.compartment_symbols\n", + " [beta_11, beta_12, beta_13, beta_21, beta_22, beta_23, beta_31,\n", + " beta_32, beta_33, gamma, xi] = symbols.attribute_symbols\n", + "\n", + " N_1 = Max(1, S_1 + I_1 + R_1)\n", + " N_2 = Max(1, S_2 + I_2 + R_2)\n", + " N_3 = Max(1, S_3 + I_3 + R_3)\n", + "\n", + " return create_model(\n", + " symbols=symbols,\n", + " transitions=[\n", + " # SIR for age class 1\n", + " edge(S_1, I_1, rate=S_1 * beta_11 * I_1 / N_1),\n", + " edge(I_1, R_1, rate=gamma * I_1),\n", + " edge(R_1, S_1, rate=xi * R_1),\n", + "\n", + " # SIR for age class 2\n", + " edge(S_2, I_2, rate=S_2 * beta_22 * I_2 / N_2),\n", + " edge(I_2, R_2, rate=gamma * I_2),\n", + " edge(R_2, S_2, rate=xi * R_2),\n", + "\n", + " # SIR for age class 3\n", + " edge(S_3, I_3, rate=S_3 * beta_33 * I_3 / N_3),\n", + " edge(I_3, R_3, rate=gamma * I_3),\n", + " edge(R_3, S_3, rate=xi * R_3),\n", + "\n", + " # The meta-edges describing the interactions between each age class\n", + " edge(S_1, I_1, rate=S_1 * beta_12 * I_2 / N_2), # 2 infects 1\n", + " edge(S_1, I_1, rate=S_1 * beta_13 * I_3 / N_3), # 3 infects 1\n", + " edge(S_2, I_2, rate=S_2 * beta_21 * I_1 / N_1), # 1 infects 2\n", + " edge(S_2, I_2, rate=S_2 * beta_23 * I_3 / N_3), # 3 infects 2\n", + " edge(S_3, I_3, rate=S_3 * beta_31 * I_1 / N_1), # 1 infects 3\n", + " edge(S_3, I_3, rate=S_3 * beta_32 * I_2 / N_2), # 2 infects 3\n", + " ])\n", + "\n", + "\n", + "infection_events_ipm1 = [[0], [1], [2]]\n", + "infection_events_ipm2 = [[0, 9, 10], [3, 11, 12], [6, 13, 14]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we need a simple one-node geo with population-by-age data and an initializer to tie this together.\n", + "\n", + "I manually scraped the data for this GEO but in the near future our ADRIOs should take care of that for us." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "from epymorph.geo.spec import LABEL, NO_DURATION, AttribDef, StaticGeoSpec\n", + "from epymorph.geo.static import StaticGeo\n", + "from epymorph.initializer import InitContext\n", + "\n", + "geo = StaticGeo(\n", + " spec=StaticGeoSpec(\n", + " attributes=[\n", + " LABEL,\n", + " AttribDef('population_by_age', SimDType, Shapes.NxA(3)),\n", + " ],\n", + " time_period=NO_DURATION,\n", + " ),\n", + " values={\n", + " # Data from 2022 ACS 1-year (S0101)\n", + " # https://data.census.gov/table/ACSST1Y2022.S0101?q=population%20by%20age&g=050XX00US04013\n", + " 'label': np.array(['Maricopa County'], dtype=np.str_),\n", + " 'population_by_age': np.array([[1_136_107, 2_412_395, 839_799]], dtype=SimDType),\n", + " },\n", + ")\n", + "\n", + "\n", + "def initializer(ctx: InitContext):\n", + " _, N, C, _ = ctx.dim.TNCE\n", + " values = np.zeros((N, C), dtype=SimDType)\n", + " # Start with population in Susceptible\n", + " values[:, 0:3] = ctx.geo['population_by_age']\n", + " # Initialize 100 Infected in class 2 (20-to-60-year-olds)\n", + " values[0, 1] -= 100\n", + " values[0, 4] += 100\n", + " return values" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Set up a function to try the different IPMs and plot the results." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from functools import reduce\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "\n", + "def run_experiment(ipm: CompartmentModel, infection_events: list[list[int]]) -> None:\n", + " # Construct sim and run\n", + " sim = StandardSimulation(\n", + " geo=geo,\n", + " ipm=ipm,\n", + " mm=mm_library['no'](),\n", + " params={\n", + " 'beta_11': 0.05,\n", + " 'beta_12': 0.05,\n", + " 'beta_13': 0.05,\n", + " 'beta_21': 0.20,\n", + " 'beta_22': 0.20,\n", + " 'beta_23': 0.20,\n", + " 'beta_31': 0.35,\n", + " 'beta_32': 0.35,\n", + " 'beta_33': 0.35,\n", + " 'gamma': 1 / 10,\n", + " 'xi': 1 / 90,\n", + " },\n", + " time_frame=TimeFrame.of(\"2022-01-01\", 165),\n", + " initializer=initializer,\n", + " # rng=default_rng(1),\n", + " )\n", + "\n", + " with sim_messaging(sim):\n", + " out = sim.run()\n", + " # calc total new infections (depending on the IPM this may represent this as separate events)\n", + " infections = [\n", + " reduce(lambda a, b: a + b,\n", + " (out.incidence[:, 0, j] for j in infection_events[i]))\n", + " for i in [0, 1, 2]\n", + " ]\n", + " # print(infections[0][0:15])\n", + "\n", + " # Plot results\n", + " age_label = ['age [0,20)', 'age [20,60)', 'age [60,80)']\n", + " age_total_thousands = geo['population_by_age'][0] / 1000\n", + " t_window = slice(0, None)\n", + "\n", + " # Day of Peak Infection by age class\n", + " dpi = [\n", + " int(np.argmax(infections[i])) // out.dim.tau_steps\n", + " for i in [0, 1, 2]\n", + " ]\n", + " dpi_x_pos = 80 # an absolute x offset (to keep them horizontally aligned)\n", + " dpi_y_pos = -5000 # an offset from the peak's y position\n", + "\n", + " fig, (ax1, ax2) = plt.subplots(nrows=2, sharex=True, figsize=(8, 6))\n", + " x_axis = np.arange(out.dim.days)[t_window]\n", + "\n", + " ax1.set_title('New infections by age class')\n", + " ax1.set_ylabel('occurrences')\n", + " for i in [0, 1, 2]:\n", + " color = ax1._get_lines.get_next_color()\n", + " y_axis = infections[i][t_window]\n", + " ax1.plot(x_axis, y_axis, color=color, label=age_label[i])\n", + " # Mark day of peak infection\n", + " d = dpi[i]\n", + " ax1.text(dpi_x_pos, y_axis[d] + dpi_y_pos, f\"day {d}\", color=color)\n", + " ax1.hlines(y=y_axis[d], xmin=d, xmax=dpi_x_pos - 1,\n", + " color=color, linewidth=0.5, linestyle='dashed')\n", + " ax1.legend()\n", + "\n", + " ax2.set_title('New infections by age class (per thousand)')\n", + " ax2.set_xlabel('days')\n", + " ax2.set_ylabel('occurrences per thousand')\n", + " for i in [0, 1, 2]:\n", + " y_axis = infections[i][t_window] / age_total_thousands[i]\n", + " ax2.plot(x_axis, y_axis, label=age_label[i])\n", + " ax2.legend()\n", + "\n", + " fig.tight_layout()\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running simulation (StandardSimulation):\n", + "• 2022-01-01 to 2022-06-15 (165 days)\n", + "• 1 geo nodes\n", + "|####################| 100% \n", + "Runtime: 0.056s\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Running simulation (StandardSimulation):\n", + "• 2022-01-01 to 2022-06-15 (165 days)\n", + "• 1 geo nodes\n", + "|####################| 100% \n", + "Runtime: 0.071s\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "run_experiment(construct_ipm_1(), infection_events_ipm1)\n", + "run_experiment(construct_ipm_2(), infection_events_ipm2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Aside: code generation" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# This is some quick-and-dirty code generation I used in defining the above model (IPM 1), by copy-pasting the results.\n", + "# Generating this meant I was less likely to make typo bugs.\n", + "# So yeah, this cell is chronologically out of order, but I stuck this at the end so it doesn't distract from the real content above.\n", + "\n", + "# Compartments\n", + "# for c, a in [(c, a) for c in ['S', 'I', 'R'] for a in [1, 2, 3]]:\n", + "# print(f\"compartment({c}_{a}),\")\n", + "\n", + "# print()\n", + "\n", + "# # Beta parameter definitions\n", + "# for a, b in [(a, b) for a in [1, 2, 3] for b in [1, 2, 3]]:\n", + "# print(f\"param('beta_{a}{b}', shape=Shapes.TxN),\")\n", + "\n", + "# print()\n", + "\n", + "# # Beta parameter unpacking\n", + "# params = [f\"beta_{a}{b}\" for a in [1, 2, 3] for b in [1, 2, 3]]\n", + "# print(\", \".join(params))\n", + "\n", + "# print()\n", + "\n", + "# # Edges\n", + "# for a in [1, 2, 3]:\n", + "# beta_times_I = [f\"beta_{a}{b} * I_{b}\" for b in [1, 2, 3]]\n", + "# print(\n", + "# f\"edge(S_{a}, I_{a}, rate=S_{a} * ({' + '.join(beta_times_I)}) / N),\")\n", + "\n", + "# for a in [1, 2, 3]:\n", + "# print(f\"edge(I_{a}, R_{a}, rate=gamma * I_{a}),\")\n", + "\n", + "# for a in [1, 2, 3]:\n", + "# print(f\"edge(R_{a}, S_{a}, rate=xi * R_{a}),\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/doc/devlog/2024-02-12.ipynb b/doc/devlog/2024-02-12.ipynb new file mode 100644 index 00000000..eb40a883 --- /dev/null +++ b/doc/devlog/2024-02-12.ipynb @@ -0,0 +1,418 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# devlog 2024-02-12\n", + "\n", + "Development of age-structured IPMs.\n", + "\n", + "Repeating the task of 2024-02-06, but now with a more complex GEO and some movement." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Assemble GEO" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "from functools import partial\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "from census import Census\n", + "\n", + "census = Census(os.environ.get('CENSUS_API_KEY'))\n", + "\n", + "\n", + "def query_pop_by_age(state_fips: str, county_fips: str, tract_ids: list[str]):\n", + " query_result = census.acs5.get(\n", + " 'group(B01001)',\n", + " geo={'for': f'tract:{\",\".join(tract_ids)}',\n", + " 'in': f'state:{state_fips} county:{county_fips}'},\n", + " year=2021,\n", + " )\n", + "\n", + " raw_df = pd.DataFrame.from_records(query_result)\n", + "\n", + " def group_cols(first: int, last: int, *, source: pd.DataFrame, table: str, dtype) -> pd.Series:\n", + " def est_name(line: int) -> str:\n", + " return f\"{table}_{line:03d}E\"\n", + " result = source[est_name(first)]\n", + " for i in range(first + 1, last + 1):\n", + " result = result + source[est_name(i)]\n", + " return result.astype(dtype)\n", + "\n", + " group = partial(group_cols, source=raw_df, table='B01001', dtype=np.int64)\n", + "\n", + " return pd.DataFrame({\n", + " 'geoid': raw_df['state'] + raw_df['county'] + raw_df['tract'],\n", + " 'population_1': group(3, 8) + group(27, 32),\n", + " 'population_2': group(9, 17) + group(33, 41),\n", + " 'population_3': group(18, 24) + group(42, 48),\n", + " })\n", + "\n", + "\n", + "age_df = query_pop_by_age(\n", + " state_fips='04',\n", + " county_fips='013',\n", + " tract_ids=['117300', '114000', '117200', '114900', '113204', '113301', '113202', '113100', '113000', '114100',\n", + " '115300', '114200', '115400', '114301', '114401', '116800', '114302', '114402', '112900', '113900', '114800'],\n", + ")\n", + "# age_df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from epymorph.data_shape import Shapes\n", + "from epymorph.geo.cache import save_to_cache\n", + "from epymorph.geo.spec import LABEL, NO_DURATION, AttribDef, StaticGeoSpec\n", + "from epymorph.geo.static import StaticGeo\n", + "from epymorph.simulation import SimDType\n", + "\n", + "geo = StaticGeo(\n", + " spec=StaticGeoSpec(\n", + " attributes=[\n", + " LABEL,\n", + " AttribDef('population_1', SimDType, Shapes.N),\n", + " AttribDef('population_2', SimDType, Shapes.N),\n", + " AttribDef('population_3', SimDType, Shapes.N),\n", + " ],\n", + " time_period=NO_DURATION,\n", + " ),\n", + " values={\n", + " 'label': age_df['geoid'].to_numpy(dtype=np.str_),\n", + " 'population': (age_df['population_1'] + age_df['population_2'] + age_df['population_3']).to_numpy(dtype=SimDType),\n", + " 'population_1': age_df['population_1'].to_numpy(dtype=SimDType),\n", + " 'population_2': age_df['population_2'].to_numpy(dtype=SimDType),\n", + " 'population_3': age_df['population_3'].to_numpy(dtype=SimDType),\n", + " },\n", + ")\n", + "\n", + "save_to_cache(geo, 'devlog-20240212')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define IPM" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from sympy import Max\n", + "\n", + "from epymorph import *\n", + "from epymorph.compartment_model import *\n", + "\n", + "# Basing these age classes on:\n", + "# \"Age-stratified transmission model of COVID-19 in Ontario with human mobility during pandemic's first wave\"; 2021; Fields, et al\n", + "# https://doi.org/10.1016%2Fj.heliyon.2021.e07905\n", + "\n", + "# age classes:\n", + "# 1: [0,20) years\n", + "# 2: [20,60) years\n", + "# 3: [60,80) years\n", + "\n", + "\n", + "def construct_ipm() -> CompartmentModel:\n", + " symbols = create_symbols(\n", + " compartments=[\n", + " compartment('S_1'),\n", + " compartment('S_2'),\n", + " compartment('S_3'),\n", + " compartment('I_1'),\n", + " compartment('I_2'),\n", + " compartment('I_3'),\n", + " compartment('R_1'),\n", + " compartment('R_2'),\n", + " compartment('R_3'),\n", + " ],\n", + " attributes=[\n", + " # infectivity matrix\n", + " param('beta_11', shape=Shapes.TxN),\n", + " param('beta_12', shape=Shapes.TxN),\n", + " param('beta_13', shape=Shapes.TxN),\n", + " param('beta_21', shape=Shapes.TxN),\n", + " param('beta_22', shape=Shapes.TxN),\n", + " param('beta_23', shape=Shapes.TxN),\n", + " param('beta_31', shape=Shapes.TxN),\n", + " param('beta_32', shape=Shapes.TxN),\n", + " param('beta_33', shape=Shapes.TxN),\n", + " # progression from infected to recovered\n", + " param('gamma', shape=Shapes.TxN),\n", + " # progression from recovered to susceptible\n", + " param('xi', shape=Shapes.TxN),\n", + " ])\n", + "\n", + " [S_1, S_2, S_3, I_1, I_2, I_3, R_1, R_2, R_3] = symbols.compartment_symbols\n", + " [beta_11, beta_12, beta_13, beta_21, beta_22, beta_23, beta_31,\n", + " beta_32, beta_33, gamma, xi] = symbols.attribute_symbols\n", + "\n", + " N_1 = Max(1, S_1 + I_1 + R_1)\n", + " N_2 = Max(1, S_2 + I_2 + R_2)\n", + " N_3 = Max(1, S_3 + I_3 + R_3)\n", + "\n", + " return create_model(\n", + " symbols=symbols,\n", + " transitions=[\n", + " # SIR for age class 1\n", + " edge(S_1, I_1, rate=S_1 * beta_11 * I_1 / N_1),\n", + " edge(I_1, R_1, rate=gamma * I_1),\n", + " edge(R_1, S_1, rate=xi * R_1),\n", + "\n", + " # SIR for age class 2\n", + " edge(S_2, I_2, rate=S_2 * beta_22 * I_2 / N_2),\n", + " edge(I_2, R_2, rate=gamma * I_2),\n", + " edge(R_2, S_2, rate=xi * R_2),\n", + "\n", + " # SIR for age class 3\n", + " edge(S_3, I_3, rate=S_3 * beta_33 * I_3 / N_3),\n", + " edge(I_3, R_3, rate=gamma * I_3),\n", + " edge(R_3, S_3, rate=xi * R_3),\n", + "\n", + " # The meta-edges describing the interactions between each age class\n", + " edge(S_1, I_1, rate=S_1 * beta_12 * I_2 / N_2), # 2 infects 1\n", + " edge(S_1, I_1, rate=S_1 * beta_13 * I_3 / N_3), # 3 infects 1\n", + " edge(S_2, I_2, rate=S_2 * beta_21 * I_1 / N_1), # 1 infects 2\n", + " edge(S_2, I_2, rate=S_2 * beta_23 * I_3 / N_3), # 3 infects 2\n", + " edge(S_3, I_3, rate=S_3 * beta_31 * I_1 / N_1), # 1 infects 3\n", + " edge(S_3, I_3, rate=S_3 * beta_32 * I_2 / N_2), # 2 infects 3\n", + " ])\n", + "\n", + "\n", + "infection_events = [[0, 9, 10], [3, 11, 12], [6, 13, 14]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define initialization" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "from functools import partial\n", + "from typing import Callable\n", + "\n", + "import numpy as np\n", + "from numpy.typing import NDArray\n", + "\n", + "from epymorph.initializer import InitContext\n", + "\n", + "\n", + "def init_empty(ctx: InitContext) -> NDArray[SimDType]:\n", + " _, N, C, _ = ctx.dim.TNCE\n", + " return np.zeros((N, C), dtype=SimDType)\n", + "\n", + "\n", + "def init_susceptible(ctx: InitContext, values: NDArray[SimDType], *, susceptible_compartment: int, pop_attribute: str) -> NDArray[SimDType]:\n", + " values[:, susceptible_compartment] = ctx.geo[pop_attribute]\n", + " return values\n", + "\n", + "\n", + "def init_seed(ctx: InitContext, values: NDArray[SimDType], *, node: int, susceptible_compartment: int, infected_compartment: int, count: int) -> NDArray[SimDType]:\n", + " avail = values[node, susceptible_compartment]\n", + " print(f\"Initializer debug: seeding {count} individuals, with {avail} available.\")\n", + " values[node, susceptible_compartment] -= count\n", + " values[node, infected_compartment] += count\n", + " return values\n", + "\n", + "\n", + "def composite_initializer(start: Callable[[InitContext], NDArray[SimDType]], *transforms: Callable[[InitContext, NDArray[SimDType]], NDArray[SimDType]]):\n", + " def initializer(ctx: InitContext) -> NDArray[SimDType]:\n", + " value = start(ctx)\n", + " for tx in transforms:\n", + " value = tx(ctx, value)\n", + " return value\n", + " return initializer\n", + "\n", + "\n", + "initializer = composite_initializer(\n", + " init_empty,\n", + " partial(init_susceptible, susceptible_compartment=0, pop_attribute='population_1'),\n", + " partial(init_susceptible, susceptible_compartment=1, pop_attribute='population_2'),\n", + " partial(init_susceptible, susceptible_compartment=2, pop_attribute='population_3'),\n", + " partial(init_seed, node=0, susceptible_compartment=1,\n", + " infected_compartment=4, count=100),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Set up and run simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Initializer debug: seeding 100 individuals, with 2829 available.\n", + "Running simulation (StandardSimulation):\n", + "• 2022-01-01 to 2022-06-15 (165 days)\n", + "• 21 geo nodes\n", + "|####################| 100% \n", + "Runtime: 2.722s\n" + ] + } + ], + "source": [ + "from functools import reduce\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from epymorph.geo.cache import load_from_cache\n", + "from epymorph.util import or_raise\n", + "\n", + "geo = or_raise(\n", + " load_from_cache('devlog-20240212'),\n", + " message=\"Oops, we need to cache the demo geo first (see above cell).\",\n", + ")\n", + "\n", + "# Construct sim and run\n", + "sim = StandardSimulation(\n", + " geo=geo,\n", + " ipm=construct_ipm(),\n", + " mm=mm_library['flat'](),\n", + " params={\n", + " 'beta_11': 0.05,\n", + " 'beta_12': 0.05,\n", + " 'beta_13': 0.05,\n", + " 'beta_21': 0.20,\n", + " 'beta_22': 0.20,\n", + " 'beta_23': 0.20,\n", + " 'beta_31': 0.35,\n", + " 'beta_32': 0.35,\n", + " 'beta_33': 0.35,\n", + " 'gamma': 1 / 10,\n", + " 'xi': 1 / 90,\n", + " 'commuter_proportion': 0.2,\n", + " },\n", + " time_frame=TimeFrame.of(\"2022-01-01\", 165),\n", + " initializer=initializer,\n", + " # rng=default_rng(1),\n", + ")\n", + "\n", + "with sim_messaging(sim):\n", + " out = sim.run()\n", + " # calc total new infections (depending on the IPM this may represent this as separate events)\n", + " infections = np.array([\n", + " reduce(lambda a, b: a + b,\n", + " (out.incidence_per_day[:, :, j].sum(axis=1) for j in infection_events[i]))\n", + " for i in [0, 1, 2]\n", + " ])" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot results\n", + "age_label = ['age [0,20)', 'age [20,60)', 'age [60,80)']\n", + "age_total_thousands = np.column_stack(\n", + " [geo['population_1'], geo['population_2'], geo['population_3']]).sum(axis=0) / 1000\n", + "t_window = slice(0, None)\n", + "\n", + "# Day of Peak Infection by age class\n", + "dpi = [\n", + " int(np.argmax(infections[i]))\n", + " for i in [0, 1, 2]\n", + "]\n", + "max_y_value = infections.max()\n", + "dpi_x_pos = 80 # an absolute x offset (to keep them horizontally aligned)\n", + "dpi_y_pos = -0.01 * max_y_value # an offset from the peak's y position\n", + "\n", + "fig, (ax1, ax2) = plt.subplots(nrows=2, sharex=True, figsize=(8, 6))\n", + "x_axis = np.arange(out.dim.days)[t_window]\n", + "\n", + "ax1.set_title('New infections by age class')\n", + "ax1.set_ylabel('occurrences')\n", + "for i in [0, 1, 2]:\n", + " color = ax1._get_lines.get_next_color()\n", + " y_axis = infections[i][t_window]\n", + " ax1.plot(x_axis, y_axis, color=color, label=age_label[i])\n", + " # Mark day of peak infection\n", + " d = dpi[i]\n", + " ax1.text(dpi_x_pos, y_axis[d] + dpi_y_pos, f\"day {d}\", color=color)\n", + " ax1.hlines(y=y_axis[d], xmin=d, xmax=dpi_x_pos - 1,\n", + " color=color, linewidth=0.5, linestyle='dashed')\n", + "ax1.legend()\n", + "\n", + "ax2.set_title('New infections by age class (per thousand)')\n", + "ax2.set_xlabel('days')\n", + "ax2.set_ylabel('occurrences per thousand')\n", + "for i in [0, 1, 2]:\n", + " y_axis = infections[i][t_window] / age_total_thousands[i]\n", + " ax2.plot(x_axis, y_axis, label=age_label[i])\n", + "ax2.legend()\n", + "\n", + "fig.tight_layout()\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/doc/devlog/README.md b/doc/devlog/README.md index 891da523..c76bd88a 100644 --- a/doc/devlog/README.md +++ b/doc/devlog/README.md @@ -35,11 +35,14 @@ This folder is a handy place to put Jupyter notebooks or other documents which h | 2023-10-26.ipynb | Tyler | | Describes a major Geo system refactor and introduces new systems. | | 2023-11-03-seirs-example.ipynb | Ajay | | Demonstrates the building and running of an SEIRS model. | | 2023-11-08.ipynb | Ajay | | Demonstration of using proxy geo to access data in parameter functions. | +| 2023-11-08-age-ipm.ipynb | Jarom | | Initial prototyping of age-class IPMs. | | 2023-11-15.ipynb | Ajay | | Detailed description of parameter functions functionality. | | 2023-11-20-adrio-phase-2-demo.ipynb | Trevor | | Demonstrates the refactor work on DynamicGeos and the ADRIO system, and geo cache handling. | | 2023-11-22-ipm-probs.ipynb | Tyler | | Analyzing statistical correctness of our IPM processing algorithms. | | 2023-12-05.ipynb | Tyler | | A brief tour of changes to epymorph due to the refactor effort. | | 2024-01-08.ipynb | Tyler | | Another functional parameters demonstration, revisiting the Bonus Example from 2023-10-10. | +| 2024-02-06.ipynb | Tyler | | Revisiting age-class IPMs, and thinking about modularity of approach. | +| 2024-02-12.ipynb | Tyler | | Continued age-class IPM work, this time in more than one geo node. | ## Contributing diff --git a/epymorph/data/mm/flat.movement b/epymorph/data/mm/flat.movement new file mode 100644 index 00000000..7d6b93a5 --- /dev/null +++ b/epymorph/data/mm/flat.movement @@ -0,0 +1,21 @@ +# This model evenly weights the probability of movement to all other nodes. +# It uses parameter 'commuter_proportion' to determine how many people should +# be moving, based on the total normal population of each node. + +[move-steps: per-day=2; duration=[1/3, 2/3]] + +[predef: function= +def flat_predef(): + ones = np.ones((dim.nodes, dim.nodes)) + np.fill_diagonal(ones, 0) + dispersal_kernel = row_normalize(ones) + return { 'dispersal_kernel': dispersal_kernel } +] + +# Assume a percentage of the population move around, +# evenly weighted to all other locations. +[mtype: days=all; leave=1; duration=0d; return=2; function= +def flat_movement(t): + n_commuters = np.floor(geo['population'] * params['commuter_proportion']).astype(SimDType) + return np.multinomial(n_commuters, predef['dispersal_kernel']) +] diff --git a/epymorph/movement/compile.py b/epymorph/movement/compile.py index 3a04a458..67bf66f2 100644 --- a/epymorph/movement/compile.py +++ b/epymorph/movement/compile.py @@ -134,6 +134,18 @@ def visit_Subscript(self, node: ast.Subscript) -> Any: return node return self.generic_visit(node) + def visit_Attribute(self, node: ast.Attribute) -> Any: + """Modify references to objects that should be in context.""" + if isinstance(node.value, ast.Name): + if node.value.id in ['dim']: + node.value = ast.Attribute( + value=ast.Name(id='ctx', ctx=ast.Load()), + attr=node.value.id, + ctx=ast.Load(), + ) + return node + return self.generic_visit(node) + def visit_FunctionDef(self, node: ast.FunctionDef) -> Any: """Modify function parameters.""" new_node = self.generic_visit(node) diff --git a/epymorph/simulation.py b/epymorph/simulation.py index e01e0395..7d5b37e4 100644 --- a/epymorph/simulation.py +++ b/epymorph/simulation.py @@ -232,6 +232,7 @@ def epymorph_namespace() -> dict[str, Any]: 'concatenate': partial(np.concatenate, dtype=SimDType), 'sum': partial(np.sum, dtype=SimDType), 'newaxis': np.newaxis, + 'fill_diagonal': np.fill_diagonal, # numpy math functions 'radians': np.radians, 'degrees': np.degrees, diff --git a/epymorph/util.py b/epymorph/util.py index 29981884..c2807636 100644 --- a/epymorph/util.py +++ b/epymorph/util.py @@ -33,6 +33,13 @@ def call_all(*fs: Callable[[], Any]) -> None: f() +def or_raise(value: T | None, message: str) -> T: + """Enforce that the given value is not None, or else raise an exception.""" + if value is None: + raise Exception(message) + return value + + # collection utilities