{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Sparse Gaussian Process Regression\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's set some setting for this Jupyter Notebook." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2018-10-10T21:23:00.870033Z", "start_time": "2018-10-10T21:23:00.862325Z" } }, "outputs": [], "source": [ "%matplotlib inline \n", "from warnings import filterwarnings\n", "filterwarnings(\"ignore\")\n", "import os\n", "os.environ['MKL_THREADING_LAYER'] = 'GNU'\n", "os.environ['THEANO_FLAGS'] = 'device=cpu' \n", " \n", "import numpy as np\n", "import pandas as pd\n", "import pymc3 as pm\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "np.random.seed(12345)\n", "rc = {'xtick.labelsize': 20, 'ytick.labelsize': 20, 'axes.labelsize': 20, 'font.size': 20, \n", " 'legend.fontsize': 12.0, 'axes.titlesize': 10, \"figure.figsize\": [12, 6]}\n", "sns.set(rc = rc)\n", "from IPython.core.interactiveshell import InteractiveShell\n", "InteractiveShell.ast_node_interactivity = \"all\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " Now, let's import the `SparseGaussianProcessRegression` algorithm from the `pymc-learn` package." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2018-10-10T21:23:00.920865Z", "start_time": "2018-10-10T21:23:00.872217Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Running on pymc-learn v0.0.1.rc0\n" ] } ], "source": [ "import pmlearn\n", "from pmlearn.gaussian_process import SparseGaussianProcessRegressor\n", "print('Running on pymc-learn v{}'.format(pmlearn.__version__))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 1: Prepare the data\n", "Generate synthetic data." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2018-10-10T21:23:04.775521Z", "start_time": "2018-10-10T21:23:00.923976Z" }, "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n = 150 # The number of data points\n", "X = np.linspace(start = 0, stop = 10, num = n)[:, None] # The inputs to the GP, they must be arranged as a column vector\n", "\n", "# Define the true covariance function and its parameters\n", "length_scale_true = 1.0\n", "signal_variance_true = 3.0\n", "cov_func = signal_variance_true**2 * pm.gp.cov.ExpQuad(1, length_scale_true)\n", "\n", "# A mean function that is zero everywhere\n", "mean_func = pm.gp.mean.Constant(10)\n", "\n", "# The latent function values are one sample from a multivariate normal\n", "# Note that we have to call `eval()` because PyMC3 built on top of Theano\n", "f_true = np.random.multivariate_normal(mean_func(X).eval(),\n", " cov_func(X).eval() + 1e-8*np.eye(n), 1).flatten()\n", "\n", "# The observed data is the latent function plus a small amount of Gaussian distributed noise\n", "# The standard deviation of the noise is `sigma`\n", "noise_variance_true = 2.0\n", "y = f_true + noise_variance_true * np.random.randn(n)\n", "\n", "## Plot the data and the unobserved latent function\n", "fig = plt.figure(figsize=(12,5))\n", "ax = fig.gca()\n", "ax.plot(X, f_true, \"dodgerblue\", lw=3, label=\"True f\");\n", "ax.plot(X, y, 'ok', ms=3, label=\"Data\");\n", "ax.set_xlabel(\"X\"); ax.set_ylabel(\"y\"); plt.legend();" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2018-10-10T21:23:04.791693Z", "start_time": "2018-10-10T21:23:04.778062Z" } }, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 2: Instantiate a model" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2018-10-10T21:23:04.796678Z", "start_time": "2018-10-10T21:23:04.793911Z" } }, "outputs": [], "source": [ "model = SparseGaussianProcessRegressor()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 3: Perform Inference" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2018-10-10T21:29:36.156925Z", "start_time": "2018-10-10T21:23:04.798853Z" }, "scrolled": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Average Loss = -4,669.3: 100%|██████████| 200000/200000 [06:12<00:00, 536.41it/s]\n", "Finished [100%]: Average Loss = -4,669.6\n" ] }, { "data": { "text/plain": [ "SparseGaussianProcessRegressor(prior_mean=0.0)" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 4: Diagnose convergence" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2018-10-10T21:29:47.915144Z", "start_time": "2018-10-10T21:29:47.454124Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.plot_elbo()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2018-08-19T21:50:48.056972Z", "start_time": "2018-08-19T21:50:47.285444Z" }, "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pm.traceplot(model.trace);" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2018-08-19T21:50:54.234130Z", "start_time": "2018-08-19T21:50:53.503497Z" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pm.traceplot(model.trace, lines = {\"signal_variance\": signal_variance_true, \n", " \"noise_variance\": noise_variance_true, \n", " \"length_scale\": length_scale_true}, \n", " varnames=[\"signal_variance\", \"noise_variance\", \"length_scale\"]);" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2018-08-19T14:07:51.411335Z", "start_time": "2018-08-19T14:07:51.217745Z" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pm.forestplot(model.trace, varnames=[\"signal_variance\", \"noise_variance\", \"length_scale\"]);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 5: Critize the model" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2018-08-19T14:07:58.271275Z", "start_time": "2018-08-19T14:07:57.913154Z" }, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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meansdmc_errorhpd_2.5hpd_97.5
signal_variance__02.266128e-203.632205e-213.731201e-231.578536e-202.999736e-20
length_scale__0_02.233311e+002.182089e+002.042519e-021.187429e-016.257235e+00
noise_variance__02.216509e-203.491209e-213.041214e-231.571128e-202.914439e-20
\n", "
" ], "text/plain": [ " mean sd mc_error hpd_2.5 \\\n", "signal_variance__0 2.266128e-20 3.632205e-21 3.731201e-23 1.578536e-20 \n", "length_scale__0_0 2.233311e+00 2.182089e+00 2.042519e-02 1.187429e-01 \n", "noise_variance__0 2.216509e-20 3.491209e-21 3.041214e-23 1.571128e-20 \n", "\n", " hpd_97.5 \n", "signal_variance__0 2.999736e-20 \n", "length_scale__0_0 6.257235e+00 \n", "noise_variance__0 2.914439e-20 " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pm.summary(model.trace, varnames=[\"signal_variance\", \"length_scale\", \"noise_variance\"])" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2018-08-19T14:08:05.635140Z", "start_time": "2018-08-19T14:08:04.895809Z" } }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pm.plot_posterior(model.trace, varnames=[\"signal_variance\", \"noise_variance\", \"length_scale\"], \n", " figsize = [14, 8]);" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2018-08-19T22:10:53.354840Z", "start_time": "2018-08-19T22:10:53.331237Z" }, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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ParameterPredicted Mean ValueTrue value
0length_scale2.1825211.0
1signal_variance9.2614353.0
2noise_variance0.0022412.0
\n", "
" ], "text/plain": [ " Parameter Predicted Mean Value True value\n", "0 length_scale 2.182521 1.0\n", "1 signal_variance 9.261435 3.0\n", "2 noise_variance 0.002241 2.0" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# collect the results into a pandas dataframe to display\n", "# \"mp\" stands for marginal posterior\n", "pd.DataFrame({\"Parameter\": [\"length_scale\", \"signal_variance\", \"noise_variance\"],\n", " \"Predicted Mean Value\": [float(model.trace[\"length_scale\"].mean(axis=0)), \n", " float(model.trace[\"signal_variance\"].mean(axis=0)), \n", " float(model.trace[\"noise_variance\"].mean(axis=0))],\n", " \"True value\": [length_scale_true, signal_variance_true, noise_variance_true]})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 6: Use the model for prediction" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2018-08-19T22:24:43.024923Z", "start_time": "2018-08-19T22:11:10.376997Z" } }, "outputs": [], "source": [ "y_predict1 = model.predict(X_test)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2018-08-19T14:08:32.926468Z", "start_time": "2018-08-19T14:08:32.525Z" } }, "outputs": [], "source": [ "y_predict1" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2018-08-10T14:03:42.646070Z", "start_time": "2018-08-10T14:03:11.416334Z" } }, "outputs": [], "source": [ "model.score(X_test, y_test)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "model.save('pickle_jar/sgpr')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Use already trained model for prediction" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "model_new = SparseGaussianProcessRegressor()\n", "model_new.load('pickle_jar/sgpr')\n", "model_new.score(X_test, y_test)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Multiple Features" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "num_pred = 2\n", "X = np.random.randn(1000, num_pred)\n", "noise = 2 * np.random.randn(1000,)\n", "Y = X.dot(np.array([4, 5])) + 3 + noise" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "y = np.squeeze(Y)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "model_big = SparseGaussianProcessRegressor()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "model_big.fit(X, y, inference_args={\"n\" : 1000})" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "pm.summary(model_big.trace, varnames=[\"signal_variance\", \"length_scale\", \"noise_variance\"])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## MCMC" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Perform inference" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "scrolled": true }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Multiprocess sampling (4 chains in 4 jobs)\n", "NUTS: [f_rotated_, noise_variance_log__, signal_variance_log__, length_scale_log__]\n", "100%|██████████| 1500/1500 [00:24<00:00, 60.20it/s]\n", "There were 92 divergences after tuning. Increase `target_accept` or reparameterize.\n", "There were 88 divergences after tuning. Increase `target_accept` or reparameterize.\n", "There were 87 divergences after tuning. Increase `target_accept` or reparameterize.\n", "There were 40 divergences after tuning. Increase `target_accept` or reparameterize.\n", "The number of effective samples is smaller than 10% for some parameters.\n", "Multiprocess sampling (4 chains in 4 jobs)\n", "NUTS: [f_rotated_, noise_variance_log__, signal_variance_log__, length_scale_log__]\n", "100%|██████████| 4000/4000 [11:41<00:00, 5.70it/s]\n", "There were 4 divergences after tuning. Increase `target_accept` or reparameterize.\n", "There were 2 divergences after tuning. Increase `target_accept` or reparameterize.\n", "There were 1 divergences after tuning. Increase `target_accept` or reparameterize.\n", "There were 1 divergences after tuning. Increase `target_accept` or reparameterize.\n" ] }, { "data": { "text/plain": [ "GaussianProcessRegression()" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model2 = SparseGaussianProcessRegressor()\n", "model2.fit(X_train, y_train, inference_type='nuts')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Diagnose convergence" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", " $(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " if (mpl.ratio != 1) {\n", " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " fig.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " '
');\n", " var titletext = $(\n", " '
');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
');\n", "\n", " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", "\n", " function canvas_keyboard_event(event) {\n", " return fig.key_event(event, event['data']);\n", " }\n", "\n", " canvas_div.keydown('key_press', canvas_keyboard_event);\n", " canvas_div.keyup('key_release', canvas_keyboard_event);\n", " this.canvas_div = canvas_div\n", " this._canvas_extra_style(canvas_div)\n", " this.root.append(canvas_div);\n", "\n", " var canvas = $('');\n", " canvas.addClass('mpl-canvas');\n", " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", "\n", " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", " var backingStore = this.context.backingStorePixelRatio ||\n", "\tthis.context.webkitBackingStorePixelRatio ||\n", "\tthis.context.mozBackingStorePixelRatio ||\n", "\tthis.context.msBackingStorePixelRatio ||\n", "\tthis.context.oBackingStorePixelRatio ||\n", "\tthis.context.backingStorePixelRatio || 1;\n", "\n", " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", " var pass_mouse_events = true;\n", "\n", " canvas_div.resizable({\n", " start: function(event, ui) {\n", " pass_mouse_events = false;\n", " },\n", " resize: function(event, ui) {\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " stop: function(event, ui) {\n", " pass_mouse_events = true;\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " });\n", "\n", " function mouse_event_fn(event) {\n", " if (pass_mouse_events)\n", " return fig.mouse_event(event, event['data']);\n", " }\n", "\n", " rubberband.mousedown('button_press', mouse_event_fn);\n", " rubberband.mouseup('button_release', mouse_event_fn);\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband.mousemove('motion_notify', mouse_event_fn);\n", "\n", " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", "\n", " canvas_div.on(\"wheel\", function (event) {\n", " event = event.originalEvent;\n", " event['data'] = 'scroll'\n", " if (event.deltaY < 0) {\n", " event.step = 1;\n", " } else {\n", " event.step = -1;\n", " }\n", " mouse_event_fn(event);\n", " });\n", "\n", " canvas_div.append(canvas);\n", " canvas_div.append(rubberband);\n", "\n", " this.rubberband = rubberband;\n", " this.rubberband_canvas = rubberband[0];\n", " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", " this.rubberband_context.strokeStyle = \"#000000\";\n", "\n", " this._resize_canvas = function(width, height) {\n", " // Keep the size of the canvas, canvas container, and rubber band\n", " // canvas in synch.\n", " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", " canvas.attr('width', width * mpl.ratio);\n", " canvas.attr('height', height * mpl.ratio);\n", " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", " }\n", "\n", " // Set the figure to an initial 600x600px, this will subsequently be updated\n", " // upon first draw.\n", " this._resize_canvas(600, 600);\n", "\n", " // Disable right mouse context menu.\n", " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", " return false;\n", " });\n", "\n", " function set_focus () {\n", " canvas.focus();\n", " canvas_div.focus();\n", " }\n", "\n", " window.setTimeout(set_focus, 100);\n", "}\n", "\n", "mpl.figure.prototype._init_toolbar = function() {\n", " var fig = this;\n", "\n", " var nav_element = $('
')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button = $('');\n", " button.click(method_name, toolbar_event);\n", " button.mouseover(tooltip, toolbar_mouse_event);\n", " nav_element.append(button);\n", " }\n", "\n", " // Add the status bar.\n", " var status_bar = $('');\n", " nav_element.append(status_bar);\n", " this.message = status_bar[0];\n", "\n", " // Add the close button to the window.\n", " var buttongrp = $('
');\n", " var button = $('');\n", " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", " buttongrp.append(button);\n", " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", " titlebar.prepend(buttongrp);\n", "}\n", "\n", "mpl.figure.prototype._root_extra_style = function(el){\n", " var fig = this\n", " el.on(\"remove\", function(){\n", "\tfig.close_ws(fig, {});\n", " });\n", "}\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(el){\n", " // this is important to make the div 'focusable\n", " el.attr('tabindex', 0)\n", " // reach out to IPython and tell the keyboard manager to turn it's self\n", " // off when our div gets focus\n", "\n", " // location in version 3\n", " if (IPython.notebook.keyboard_manager) {\n", " IPython.notebook.keyboard_manager.register_events(el);\n", " }\n", " else {\n", " // location in version 2\n", " IPython.keyboard_manager.register_events(el);\n", " }\n", "\n", "}\n", "\n", "mpl.figure.prototype._key_event_extra = function(event, name) {\n", " var manager = IPython.notebook.keyboard_manager;\n", " if (!manager)\n", " manager = IPython.keyboard_manager;\n", "\n", " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", " event.shiftKey = false;\n", " // Send a \"J\" for go to next cell\n", " event.which = 74;\n", " event.keyCode = 74;\n", " manager.command_mode();\n", " manager.handle_keydown(event);\n", " }\n", "}\n", "\n", "mpl.figure.prototype.handle_save = function(fig, msg) {\n", " fig.ondownload(fig, null);\n", "}\n", "\n", "\n", "mpl.find_output_cell = function(html_output) {\n", " // Return the cell and output element which can be found *uniquely* in the notebook.\n", " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", " // IPython event is triggered only after the cells have been serialised, which for\n", " // our purposes (turning an active figure into a static one), is too late.\n", " var cells = IPython.notebook.get_cells();\n", " var ncells = cells.length;\n", " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", " data = data.data;\n", " }\n", " if (data['text/html'] == html_output) {\n", " return [cell, data, j];\n", " }\n", " }\n", " }\n", " }\n", "}\n", "\n", "// Register the function which deals with the matplotlib target/channel.\n", "// The kernel may be null if the page has been refreshed.\n", "if (IPython.notebook.kernel != null) {\n", " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", "}\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pm.energyplot(model2.trace);" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "pm.forestplot(model2.trace, varnames=[\"signal_variance\", \"noise_variance\", \"length_scale\"]);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Criticize the model" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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meansdmc_errorhpd_2.5hpd_97.5n_effRhat
signal_variance__03.3545215.0599690.0726110.00438810.4941863949.5659161.001348
length_scale__0_02.0040011.4464050.0132860.0338104.79092212131.0096360.999767
noise_variance__02.5443280.2640450.0030212.0746303.0869818803.8029240.999830
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" ], "text/plain": [ " mean sd mc_error hpd_2.5 hpd_97.5 \\\n", "signal_variance__0 3.354521 5.059969 0.072611 0.004388 10.494186 \n", "length_scale__0_0 2.004001 1.446405 0.013286 0.033810 4.790922 \n", "noise_variance__0 2.544328 0.264045 0.003021 2.074630 3.086981 \n", "\n", " n_eff Rhat \n", "signal_variance__0 3949.565916 1.001348 \n", "length_scale__0_0 12131.009636 0.999767 \n", "noise_variance__0 8803.802924 0.999830 " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pm.summary(model2.trace, varnames=[\"signal_variance\", \"length_scale\", \"noise_variance\"])" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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ParameterPredicted Mean ValueTrue value
0length_scale2.0040011.0
1signal_variance3.3545213.0
2noise_variance2.5443282.0
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" ], "text/plain": [ " Parameter Predicted Mean Value True value\n", "0 length_scale 2.004001 1.0\n", "1 signal_variance 3.354521 3.0\n", "2 noise_variance 2.544328 2.0" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# collect the results into a pandas dataframe to display\n", "# \"mp\" stands for marginal posterior\n", "pd.DataFrame({\"Parameter\": [\"length_scale\", \"signal_variance\", \"noise_variance\"],\n", " \"Predicted Mean Value\": [float(model2.trace[\"length_scale\"].mean(axis=0)), \n", " float(model2.trace[\"signal_variance\"].mean(axis=0)), \n", " float(model2.trace[\"noise_variance\"].mean(axis=0))],\n", " \"True value\": [length_scale_true, signal_variance_true, noise_variance_true]})" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", " $(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " if (mpl.ratio != 1) {\n", " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " fig.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " '
');\n", " var titletext = $(\n", " '
');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
');\n", "\n", " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", "\n", " function canvas_keyboard_event(event) {\n", " return fig.key_event(event, event['data']);\n", " }\n", "\n", " canvas_div.keydown('key_press', canvas_keyboard_event);\n", " canvas_div.keyup('key_release', canvas_keyboard_event);\n", " this.canvas_div = canvas_div\n", " this._canvas_extra_style(canvas_div)\n", " this.root.append(canvas_div);\n", "\n", " var canvas = $('');\n", " canvas.addClass('mpl-canvas');\n", " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", "\n", " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", " var backingStore = this.context.backingStorePixelRatio ||\n", "\tthis.context.webkitBackingStorePixelRatio ||\n", "\tthis.context.mozBackingStorePixelRatio ||\n", "\tthis.context.msBackingStorePixelRatio ||\n", "\tthis.context.oBackingStorePixelRatio ||\n", "\tthis.context.backingStorePixelRatio || 1;\n", "\n", " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", " var pass_mouse_events = true;\n", "\n", " canvas_div.resizable({\n", " start: function(event, ui) {\n", " pass_mouse_events = false;\n", " },\n", " resize: function(event, ui) {\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " stop: function(event, ui) {\n", " pass_mouse_events = true;\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " });\n", "\n", " function mouse_event_fn(event) {\n", " if (pass_mouse_events)\n", " return fig.mouse_event(event, event['data']);\n", " }\n", "\n", " rubberband.mousedown('button_press', mouse_event_fn);\n", " rubberband.mouseup('button_release', mouse_event_fn);\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband.mousemove('motion_notify', mouse_event_fn);\n", "\n", " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", "\n", " canvas_div.on(\"wheel\", function (event) {\n", " event = event.originalEvent;\n", " event['data'] = 'scroll'\n", " if (event.deltaY < 0) {\n", " event.step = 1;\n", " } else {\n", " event.step = -1;\n", " }\n", " mouse_event_fn(event);\n", " });\n", "\n", " canvas_div.append(canvas);\n", " canvas_div.append(rubberband);\n", "\n", " this.rubberband = rubberband;\n", " this.rubberband_canvas = rubberband[0];\n", " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", " this.rubberband_context.strokeStyle = \"#000000\";\n", "\n", " this._resize_canvas = function(width, height) {\n", " // Keep the size of the canvas, canvas container, and rubber band\n", " // canvas in synch.\n", " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", " canvas.attr('width', width * mpl.ratio);\n", " canvas.attr('height', height * mpl.ratio);\n", " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", " }\n", "\n", " // Set the figure to an initial 600x600px, this will subsequently be updated\n", " // upon first draw.\n", " this._resize_canvas(600, 600);\n", "\n", " // Disable right mouse context menu.\n", " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", " return false;\n", " });\n", "\n", " function set_focus () {\n", " canvas.focus();\n", " canvas_div.focus();\n", " }\n", "\n", " window.setTimeout(set_focus, 100);\n", "}\n", "\n", "mpl.figure.prototype._init_toolbar = function() {\n", " var fig = this;\n", "\n", " var nav_element = $('
')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button = $('