"Fossies" - the Fresh Open Source Software Archive  

Source code changes of the file "notebooks/trend_changepoints.ipynb" between
prophet-0.7.tar.gz and prophet-1.0.tar.gz

About: Prophet is a tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

trend_changepoints.ipynb  (prophet-0.7):trend_changepoints.ipynb  (prophet-1.0)
{ {
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 1,
"metadata": { "metadata": {
"block_hidden": true, "block_hidden": true
"collapsed": true
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"%load_ext rpy2.ipython\n", "%load_ext rpy2.ipython\n",
"%matplotlib inline\n", "%matplotlib inline\n",
"from fbprophet import Prophet\n", "from prophet import Prophet\n",
"import pandas as pd\n", "import pandas as pd\n",
"from matplotlib import pyplot as plt\n", "from matplotlib import pyplot as plt\n",
"import numpy as np\n", "import numpy as np\n",
"import logging\n", "import logging\n",
"logging.getLogger('fbprophet').setLevel(logging.ERROR)\n", "logging.getLogger('prophet').setLevel(logging.ERROR)\n",
"logging.getLogger('numexpr').setLevel(logging.ERROR)\n",
"import warnings\n", "import warnings\n",
"warnings.filterwarnings(\"ignore\")\n", "warnings.filterwarnings(\"ignore\")\n",
"df = pd.read_csv('../examples/example_wp_log_peyton_manning.csv')" "df = pd.read_csv('../examples/example_wp_log_peyton_manning.csv')"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 2,
"metadata": { "metadata": {
"block_hidden": true "block_hidden": true
}, },
"outputs": [ "outputs": [
{ {
"data": { "name": "stderr",
"text/plain": [ "output_type": "stream",
"Initial log joint probability = -19.4685\n", "text": [
"Optimization terminated normally: \n", "R[write to console]: Loading required package: Rcpp\n",
" Convergence detected: relative gradient magnitude is below tolerance\n "\n",
", "R[write to console]: Loading required package: rlang\n",
"Initial log joint probability = -19.4685\n", "\n",
"Optimization terminated normally: \n", "R[write to console]: Disabling daily seasonality. Run prophet with daily.
" Convergence detected: relative gradient magnitude is below tolerance\n seasonality=TRUE to override this.\n",
" "\n",
] "R[write to console]: Disabling daily seasonality. Run prophet with daily.
}, seasonality=TRUE to override this.\n",
"metadata": {}, "\n"
"output_type": "display_data" ]
} }
], ],
"source": [ "source": [
"%%R\n", "%%R\n",
"library(prophet)\n", "library(prophet)\n",
"df <- read.csv('../examples/example_wp_log_peyton_manning.csv')\n", "df <- read.csv('../examples/example_wp_log_peyton_manning.csv')\n",
"m <- prophet(df)\n", "m <- prophet(df)\n",
"future <- make_future_dataframe(m, periods=366)\n", "future <- make_future_dataframe(m, periods=366)\n",
"m <- prophet(df)\n", "m <- prophet(df)\n",
"forecast <- predict(m, future)" "forecast <- predict(m, future)"
skipping to change at line 74 skipping to change at line 74
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"### Automatic changepoint detection in Prophet\n", "### Automatic changepoint detection in Prophet\n",
"Prophet detects changepoints by first specifying a large number of *potenti al changepoints* at which the rate is allowed to change. It then puts a sparse p rior on the magnitudes of the rate changes (equivalent to L1 regularization) - t his essentially means that Prophet has a large number of *possible* places where the rate can change, but will use as few of them as possible. Consider the Peyt on Manning forecast from the Quickstart. By default, Prophet specifies 25 potent ial changepoints which are uniformly placed in the first 80% of the time series. The vertical lines in this figure indicate where the potential changepoints wer e placed:" "Prophet detects changepoints by first specifying a large number of *potenti al changepoints* at which the rate is allowed to change. It then puts a sparse p rior on the magnitudes of the rate changes (equivalent to L1 regularization) - t his essentially means that Prophet has a large number of *possible* places where the rate can change, but will use as few of them as possible. Consider the Peyt on Manning forecast from the Quickstart. By default, Prophet specifies 25 potent ial changepoints which are uniformly placed in the first 80% of the time series. The vertical lines in this figure indicate where the potential changepoints wer e placed:"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 2,
"metadata": { "metadata": {
"input_hidden": true "input_hidden": true
}, },
"outputs": [ "outputs": [
{ {
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"text/plain": [ "text/plain": [
"<Figure size 720x432 with 1 Axes>" "<Figure size 720x432 with 1 Axes>"
] ]
}, },
"metadata": {}, "metadata": {},
"output_type": "display_data" "output_type": "display_data"
} }
], ],
"source": [ "source": [
"m = Prophet()\n", "m = Prophet()\n",
skipping to change at line 109 skipping to change at line 109
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"Even though we have a lot of places where the rate can possibly change, bec ause of the sparse prior, most of these changepoints go unused. We can see this by plotting the magnitude of the rate change at each changepoint:" "Even though we have a lot of places where the rate can possibly change, bec ause of the sparse prior, most of these changepoints go unused. We can see this by plotting the magnitude of the rate change at each changepoint:"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 3,
"metadata": { "metadata": {
"input_hidden": true "input_hidden": true
}, },
"outputs": [ "outputs": [
{ {
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"text/plain": [ "text/plain": [
"<Figure size 720x432 with 1 Axes>" "<Figure size 720x432 with 1 Axes>"
] ]
}, },
"metadata": {}, "metadata": {},
"output_type": "display_data" "output_type": "display_data"
} }
], ],
"source": [ "source": [
"deltas = m.params['delta'].mean(0)\n", "deltas = m.params['delta'].mean(0)\n",
skipping to change at line 145 skipping to change at line 145
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"The number of potential changepoints can be set using the argument `n_chang epoints`, but this is better tuned by adjusting the regularization. The location s of the signification changepoints can be visualized with:" "The number of potential changepoints can be set using the argument `n_chang epoints`, but this is better tuned by adjusting the regularization. The location s of the signification changepoints can be visualized with:"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 3,
"metadata": { "metadata": {
"output_hidden": true "output_hidden": true
}, },
"outputs": [ "outputs": [
{ {
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}, },
"metadata": {}, "metadata": {},
"output_type": "display_data" "output_type": "display_data"
} }
], ],
"source": [ "source": [
"%%R -w 10 -h 6 -u in\n", "%%R -w 10 -h 6 -u in\n",
"plot(m, forecast) + add_changepoints_to_plot(m)" "plot(m, forecast) + add_changepoints_to_plot(m)"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
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"text/plain": [ "text/plain": [
"<Figure size 720x432 with 1 Axes>" "<Figure size 720x432 with 1 Axes>"
] ]
}, },
"metadata": {}, "metadata": {},
"output_type": "display_data" "output_type": "display_data"
} }
], ],
"source": [ "source": [
"from fbprophet.plot import add_changepoints_to_plot\n", "from prophet.plot import add_changepoints_to_plot\n",
"fig = m.plot(forecast)\n", "fig = m.plot(forecast)\n",
"a = add_changepoints_to_plot(fig.gca(), m, forecast)" "a = add_changepoints_to_plot(fig.gca(), m, forecast)"
] ]
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"By default changepoints are only inferred for the first 80% of the time ser ies in order to have plenty of runway for projecting the trend forward and to av oid overfitting fluctuations at the end of the time series. This default works i n many situations but not all, and can be changed using the `changepoint_range` argument. For example, `m = Prophet(changepoint_range=0.9)` in Python or `m <- p rophet(changepoint.range = 0.9)` in R will place potential changepoints in the f irst 90% of the time series." "By default changepoints are only inferred for the first 80% of the time ser ies in order to have plenty of runway for projecting the trend forward and to av oid overfitting fluctuations at the end of the time series. This default works i n many situations but not all, and can be changed using the `changepoint_range` argument. For example, `m = Prophet(changepoint_range=0.9)` in Python or `m <- p rophet(changepoint.range = 0.9)` in R will place potential changepoints in the f irst 90% of the time series."
] ]
skipping to change at line 202 skipping to change at line 202
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"### Adjusting trend flexibility\n", "### Adjusting trend flexibility\n",
"If the trend changes are being overfit (too much flexibility) or underfit ( not enough flexibility), you can adjust the strength of the sparse prior using t he input argument `changepoint_prior_scale`. By default, this parameter is set t o 0.05. Increasing it will make the trend *more* flexible:" "If the trend changes are being overfit (too much flexibility) or underfit ( not enough flexibility), you can adjust the strength of the sparse prior using t he input argument `changepoint_prior_scale`. By default, this parameter is set t o 0.05. Increasing it will make the trend *more* flexible:"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 4,
"metadata": { "metadata": {
"output_hidden": true "output_hidden": true
}, },
"outputs": [ "outputs": [
{ {
"data": { "name": "stderr",
"text/plain": [ "output_type": "stream",
"Initial log joint probability = -19.4685\n", "text": [
"Optimization terminated normally: \n", "R[write to console]: Disabling daily seasonality. Run prophet with daily.
" Convergence detected: relative gradient magnitude is below tolerance\n seasonality=TRUE to override this.\n",
" "\n"
] ]
},
"metadata": {},
"output_type": "display_data"
}, },
{ {
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