jupyterstan-example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Installation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`pip install jupyterstan`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing %%stan magic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pystan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using `%%stan` to generate a pystan.StanModel\n",
    "\n",
    "By default, writing a stan program in a `%%stan` cell saves the model into your namespace under the variable name `_stan_model`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext jupyterstan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%stan\n",
    "data {\n",
    "    int male;\n",
    "    int female;\n",
    "}\n",
    "\n",
    "parameters {\n",
    "    real<lower=0, upper=1> p;\n",
    "}\n",
    "\n",
    "model {\n",
    "    female ~ binomial(male + female, p);\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(_stan_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Naming your model\n",
    "\n",
    "If you write a variable name after `%%stan`, your model will be saved under that variable name:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%stan paris_births\n",
    "data {\n",
    "    int male;\n",
    "    int female;\n",
    "}\n",
    "\n",
    "parameters {\n",
    "    real<lower=0, upper=1> p;\n",
    "}\n",
    "\n",
    "model {\n",
    "    female ~ binomial(male + female, p);\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(paris_births)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Passing custom arguments to the `%%stan` magic\n",
    "\n",
    "You can pass additional arguments to `pystan`'s `StanModel` as if they were command line arguments. To find out more about those arguments, check here: https://pystan.readthedocs.io/en/latest/api.html#pystan.StanModel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%stan paris_births --model_name my_model_name --boost_lib /my/custom/boosting/library\n",
    "data {\n",
    "    int male;\n",
    "    int female;\n",
    "}\n",
    "\n",
    "parameters {\n",
    "    real<lower=0, upper=1> p;\n",
    "}\n",
    "\n",
    "model {\n",
    "    female ~ binomial(male + female, p);\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(paris_births)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}