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First round of inference using PyMC3 with Nuts
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# Inference comparing different models and simulated data" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 1, | ||
"metadata": { | ||
"ExecuteTime": { | ||
"end_time": "2021-03-17T15:05:50.552831Z", | ||
"start_time": "2021-03-17T15:05:50.011627Z" | ||
} | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"import numpy as np\n", | ||
"from matplotlib import pyplot as plt\n", | ||
"from scipy.integrate import odeint\n", | ||
"import cmdstanpy" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"## Full SIR model\n", | ||
"Let's start with the SIR model (S(t),I(t)), with LogNormal data. See Data Simulation Notebook for details on how the data was generated. " | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 2, | ||
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"end_time": "2021-03-17T15:10:41.576000Z", | ||
"start_time": "2021-03-17T15:10:41.565578Z" | ||
} | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"data = np.load('logNSIRdata.npy')" | ||
] | ||
}, | ||
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"ExecuteTime": { | ||
"end_time": "2021-03-17T15:10:45.139430Z", | ||
"start_time": "2021-03-17T15:10:45.118708Z" | ||
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/+dub.json: | ||
{ | ||
"name": "sir_stoch", | ||
"authors": [ | ||
"Flávio Codeço Coelho" | ||
], | ||
"description": "Example usage of SIR model from epistochmodels", | ||
"copyright": "Copyright © 2020, Flávio Codeço Coelho", | ||
"license": "GPL-3", | ||
"dependencies": { | ||
"epistochmodels": "*" | ||
} | ||
} | ||
+/ | ||
import std.datetime.stopwatch; | ||
import std.stdio; | ||
import std.file; | ||
import std.algorithm; | ||
import std.range; | ||
import core.exception : RangeError; | ||
import std.typecons : tuple, Tuple; | ||
import models; | ||
|
||
/** | ||
Save the simulation as a CSV file | ||
*/ | ||
void save(string filename, string[] varnames, Tuple!(double[], int[][]) data) | ||
{ | ||
import std.array: join; | ||
import std.conv: text; | ||
File outf = File(filename, "w"); | ||
auto head = join(varnames, ","); | ||
outf.writeln("t,", head); | ||
foreach (i, int[] row; data[1]) | ||
{ | ||
try | ||
{// writes t on column 0 | ||
outf.writeln(text(data[0][i]), ",", row.map!text.join(",")); | ||
} | ||
catch (RangeError e) | ||
{ | ||
writefln("Some error %s: %s", e, row); | ||
} | ||
} | ||
outf.close(); | ||
} | ||
|
||
void main(){ | ||
double beta = 0.9; | ||
double gam = 0.1; | ||
int N = 100; | ||
int I0 = 10; | ||
double tf = 1000; | ||
auto sw = StopWatch(AutoStart.no); | ||
auto model = new SIR(N, beta, gam); | ||
model.initialize(N-I0, I0, 0); | ||
sw.start(); | ||
auto sim = model.run(0, tf); | ||
sw.stop(); | ||
save("sir_stoch.csv",["S","I","R"],sim); | ||
writefln("Time of the SIR run with N=%s: %s", N, sw.peek()); | ||
writefln("Number of steps: %s", sim[0].length); | ||
} |
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