Skip to content

Instantly share code, notes, and snippets.

@aflaxman
Created September 21, 2019 02:26
Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save aflaxman/3dfa4f0fe008b7982784b8f314c03331 to your computer and use it in GitHub Desktop.
Save aflaxman/3dfa4f0fe008b7982784b8f314c03331 to your computer and use it in GitHub Desktop.
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Fri Sep 20 19:25:01 PDT 2019\r\n"
]
}
],
"source": [
"import numpy as np, matplotlib.pyplot as plt, pandas as pd\n",
"pd.set_option('display.max_rows', 8)\n",
"!date\n",
"\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import seaborn as sns\n",
"import scipy.stats"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# How to measure and use the correlation between BW and WHZ"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>BIRTHWT</th>\n",
" <th>WHZ</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2359.232186</td>\n",
" <td>0.988714</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1132.751109</td>\n",
" <td>-0.518648</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>867.837623</td>\n",
" <td>-1.059356</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>909.120557</td>\n",
" <td>-2.398236</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9996</th>\n",
" <td>1777.715097</td>\n",
" <td>-0.730386</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9997</th>\n",
" <td>538.130832</td>\n",
" <td>-1.288791</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9998</th>\n",
" <td>1018.923986</td>\n",
" <td>-0.497596</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9999</th>\n",
" <td>2020.755532</td>\n",
" <td>1.299006</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10000 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" BIRTHWT WHZ\n",
"0 2359.232186 0.988714\n",
"1 1132.751109 -0.518648\n",
"2 867.837623 -1.059356\n",
"3 909.120557 -2.398236\n",
"... ... ...\n",
"9996 1777.715097 -0.730386\n",
"9997 538.130832 -1.288791\n",
"9998 1018.923986 -0.497596\n",
"9999 2020.755532 1.299006\n",
"\n",
"[10000 rows x 2 columns]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Ki has real data on this, but I will simulate for testing purposes\n",
"\n",
"N = 10_000\n",
"\n",
"# set random seed for reproducibility\n",
"np.random.seed(12345)\n",
"\n",
"# simulate data (to be replaced with real data, e.g. from DHS, eventually)\n",
"df = pd.DataFrame(index=range(N))\n",
"df['BIRTHWT'] = np.random.uniform(500, 2_500, size=N)\n",
"df['WHZ'] = np.random.normal((df.BIRTHWT-1_500)/500, 1, size=N)\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.JointGrid at 0x7fe01813e208>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x432 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.jointplot(df.BIRTHWT, df.WHZ,)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# What I want from Ki is simply the Spearman R value, which captures the correlation of birthweight and WHZ as continuous variables"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.766608698902087"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rho, p_val = scipy.stats.spearmanr(df.BIRTHWT, df.WHZ)\n",
"rho"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# What will I use that for?\n",
"\n",
"I will generate a multivariate normal with that rho, and then use that to generate a distribution that is marginally uniform, but with that rho, and then use that to generate a distribution that in its margins matches the birthweight and whz from GBD, but also has Spearman correlation rho:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.7543540528155405"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x432 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"probit_propensity = np.random.multivariate_normal([0,0], [[1, rho],\n",
" [rho, 1]], size=N)\n",
"sns.jointplot(probit_propensity[:,0], probit_propensity[:,1])\n",
"rho, p_val = scipy.stats.spearmanr(probit_propensity[:,0], probit_propensity[:,1])\n",
"rho"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.7543540528155405"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x432 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"propensity = scipy.stats.norm().cdf(probit_propensity)\n",
"sns.jointplot(propensity[:,0], propensity[:,1])\n",
"rho, p_val = scipy.stats.spearmanr(propensity[:,0], propensity[:,1])\n",
"rho"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# HACK: instead of loading marginals from GBD, I'm going to re-use the ones\n",
"# I synthesized above\n",
"\n",
"birthweight_vals = df['BIRTHWT'].sort_values().values\n",
"whz_vals = df['WHZ'].sort_values().values\n",
"\n",
"def birthweight_from_propensity(p):\n",
" p = np.array(p)\n",
" i = np.array(np.floor(p*len(birthweight_vals)), dtype=int)\n",
" return birthweight_vals[i]\n",
"\n",
"def whz_from_propensity(p):\n",
" p = np.array(p)\n",
" i = np.array(np.floor(p*len(whz_vals)), dtype=int)\n",
" return whz_vals[i]\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>BIRTHWT</th>\n",
" <th>WHZ</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1593.439862</td>\n",
" <td>1.830559</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2486.607353</td>\n",
" <td>3.591340</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>972.322415</td>\n",
" <td>-1.595476</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2210.164417</td>\n",
" <td>0.746329</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9996</th>\n",
" <td>1099.228917</td>\n",
" <td>1.342892</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9997</th>\n",
" <td>927.152800</td>\n",
" <td>-1.389638</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9998</th>\n",
" <td>827.031938</td>\n",
" <td>-1.933467</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9999</th>\n",
" <td>513.396060</td>\n",
" <td>-2.532905</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>10000 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" BIRTHWT WHZ\n",
"0 1593.439862 1.830559\n",
"1 2486.607353 3.591340\n",
"2 972.322415 -1.595476\n",
"3 2210.164417 0.746329\n",
"... ... ...\n",
"9996 1099.228917 1.342892\n",
"9997 927.152800 -1.389638\n",
"9998 827.031938 -1.933467\n",
"9999 513.396060 -2.532905\n",
"\n",
"[10000 rows x 2 columns]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# now map from propensity to value\n",
"df_synthetic = pd.DataFrame(index=range(N))\n",
"df_synthetic['BIRTHWT'] = birthweight_from_propensity(propensity[:,0])\n",
"df_synthetic['WHZ'] = whz_from_propensity(propensity[:,1])\n",
"df_synthetic"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.7543562388971939"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x432 with 3 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.jointplot(df_synthetic.BIRTHWT, df_synthetic.WHZ)\n",
"rho, p_val = scipy.stats.spearmanr(df_synthetic.BIRTHWT, df_synthetic.WHZ)\n",
"rho"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "vivarium_conic_sqlns",
"language": "python",
"name": "vivarium_conic_sqlns"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment