{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "block_hidden": true,
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython\n",
    "%matplotlib inline\n",
    "from fbprophet import Prophet\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "df = pd.read_csv('../examples/example_wp_peyton_manning.csv')\n",
    "df['y'] = np.log(df['y'])\n",
    "m = Prophet()\n",
    "m.fit(df)\n",
    "future = m.make_future_dataframe(periods=366)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "block_hidden": true,
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: Loading required package: Rcpp\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "STAN OPTIMIZATION COMMAND (LBFGS)\n",
       "init = user\n",
       "save_iterations = 1\n",
       "init_alpha = 0.001\n",
       "tol_obj = 1e-12\n",
       "tol_grad = 1e-08\n",
       "tol_param = 1e-08\n",
       "tol_rel_obj = 10000\n",
       "tol_rel_grad = 1e+07\n",
       "history_size = 5\n",
       "seed = 1595444319\n",
       "initial log joint probability = -19.4685\n",
       "Optimization terminated normally: \n",
       "  Convergence detected: relative gradient magnitude is below tolerance\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "library(prophet)\n",
    "df <- read.csv('../examples/example_wp_peyton_manning.csv')\n",
    "df$y <- log(df$y)\n",
    "m <- prophet(df)\n",
    "future <- make_future_dataframe(m, periods=366)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default Prophet will return uncertainty intervals for the forecast `yhat`. There are several important assumptions behind these uncertainty intervals.\n",
    "\n",
    "There are three sources of uncertainty in the forecast: uncertainty in the trend, uncertainty in the seasonality estimates, and additional observation noise.\n",
    "\n",
    "### Uncertainty in the trend\n",
    "The biggest source of uncertainty in the forecast is the potential for future trend changes. The time series we have seen already in this documentation show clear trend changes in the history. Prophet is able to detect and fit these, but what trend changes should we expect moving forward? It's impossible to know for sure, so we do the most reasonable thing we can, and we assume that the *future will see similar trend changes as the history*. In particular, we assume that the average frequency and magnitude of trend changes in the future will be the same as that which we observe in the history. We project these trend changes forward and by computing their distribution we obtain uncertainty intervals.\n",
    "\n",
    "One property of this way of measuring uncertainty is that allowing higher flexibility in the rate, by increasing `changepoint_prior_scale`, will increase the forecast uncertainty. This is because if we model more rate changes in the history then we will expect more in the future, and makes the uncertainty intervals a useful indicator of overfitting.\n",
    "\n",
    "The width of the uncertainty intervals (by default 80%) can be set using the parameter `interval_width`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "forecast = Prophet(interval_width=0.95).fit(df).predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "output_hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STAN OPTIMIZATION COMMAND (LBFGS)\n",
       "init = user\n",
       "save_iterations = 1\n",
       "init_alpha = 0.001\n",
       "tol_obj = 1e-12\n",
       "tol_grad = 1e-08\n",
       "tol_param = 1e-08\n",
       "tol_rel_obj = 10000\n",
       "tol_rel_grad = 1e+07\n",
       "history_size = 5\n",
       "seed = 1989486813\n",
       "initial log joint probability = -19.4685\n",
       "Optimization terminated normally: \n",
       "  Convergence detected: relative gradient magnitude is below tolerance\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "m <- prophet(df, interval.width = 0.95)\n",
    "forecast <- predict(m, future)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, these intervals assume that the future will see the same frequency and magnitude of rate changes as the past. This assumption is probably not true, so you should not expect to get accurate coverage on these uncertainty intervals.\n",
    "\n",
    "### Uncertainty in seasonality\n",
    "By default Prophet will only return uncertainty in the trend and observation noise. To get uncertainty in seasonality, you must do full Bayesian sampling. This is done using the parameter `mcmc.samples` (which defaults to 0). We do this here for the Peyton Manning data from the Quickstart:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "m = Prophet(mcmc_samples=500)\n",
    "forecast = m.fit(df).predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "output_hidden": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: The following numerical problems occurred the indicated number of times on chain 1\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning:                                                                                 count\n",
      "Exception thrown at line 39: normal_log: Scale parameter is 0, but must be > 0!     5\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: When a numerical problem occurs, the Hamiltonian proposal gets rejected.\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: See http://mc-stan.org/misc/warnings.html#exception-hamiltonian-proposal-rejected\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: If the number in the 'count' column is small, there is no need to ask about this message on stan-users.\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: The following numerical problems occurred the indicated number of times on chain 2\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: The following numerical problems occurred the indicated number of times on chain 3\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: The following numerical problems occurred the indicated number of times on chain 4\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
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       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "m <- prophet(df, mcmc.samples = 500)\n",
    "forecast <- predict(m, future)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This replaces the typical MAP estimation with MCMC sampling, and takes much longer - think 10 minutes instead of 10 seconds. If you do full sampling, then you will see the uncertainty in seasonal components when you plot them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "output_hidden": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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j1GV/iZho4V1RFDxWI55iNzPyHHSFEjT1R6nOc/Dz82fSMhjjoQ1tPN7QzuMN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\n6P8D09n9GazbetsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f07006c89d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m.plot_components(forecast);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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7v/71r0OHDuE4fssttzz88MNCYRBe41AMZdMkEglJkp5BP5/v42u67OuON9bp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\n8p9NbbK7tl/R0pO35xerbup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0DMMwDIvMFx3DMKlUynYVLKBfdA7mEzM4uLdbrVafLcF8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\nAAAAjvw/rQC5c8/CJisAAAAASUVORK5CYII=\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -w 9 -h 9 -u in\n",
    "prophet_plot_components(m, forecast);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can access the raw posterior predictive samples in Python using the method `m.predictive_samples(future)`, or in R using the function `predictive_samples(m, future)`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are upstream issues in PyStan for Windows which make MCMC sampling extremely slow. The best choice for MCMC sampling in Windows is to use R, or Python in a Linux VM."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
