{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "(mmm_evaluation)=\n", "# Model Evaluation in PyMC-Marketing\n", "\n", "This notebook demonstrates how to evaluate Marketing Mix Models using PyMC-Marketing's evaluation metrics and functions. We'll cover:\n", "\n", "1. Standard evaluation metrics (RMSE, MAE, MAPE)\n", "2. Normalized metrics (NRMSE, NMAE)\n", "3. Calculating and visualizing metric distributions and summaries of those distributions\n", "4. Creating evaluation plots (prior vs posterior plots)\n", "\n", "First, let's import the necessary libraries:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import arviz as az\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "from sklearn.metrics import (\n", " root_mean_squared_error,\n", ")\n", "\n", "from pymc_marketing.mmm import (\n", " MMM,\n", " GeometricAdstock,\n", " LogisticSaturation,\n", ")\n", "from pymc_marketing.mmm.evaluation import (\n", " calculate_metric_distributions,\n", " compute_summary_metrics,\n", " summarize_metric_distributions,\n", ")\n", "\n", "az.style.use(\"arviz-darkgrid\")\n", "plt.rcParams[\"figure.figsize\"] = [12, 7]\n", "plt.rcParams[\"figure.dpi\"] = 100\n", "\n", "%load_ext autoreload\n", "%autoreload 2\n", "%config InlineBackend.figure_format = \"retina\"" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "seed: int = sum(map(ord, \"mmm-evaluation\"))\n", "rng: np.random.Generator = np.random.default_rng(seed=seed)\n", "hdi_prob: float = 0.89 # change this to whatever HDI you want" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Setting up a Demo Model\n", "\n", "Let's first create a simple MMM model using the example dataset:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2f46c5724cae428786abf194dc9ca01e", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/3500 [00:00\n" ], "text/plain": [] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Load example data\n", "data_url = \"https://raw.githubusercontent.com/pymc-labs/pymc-marketing/main/data/mmm_example.csv\"\n", "data = pd.read_csv(data_url, parse_dates=[\"date_week\"])\n", "\n", "X = data.drop(\"y\", axis=1)\n", "y = data[\"y\"]\n", "\n", "# Create and fit the model\n", "mmm = MMM(\n", " adstock=GeometricAdstock(l_max=8),\n", " saturation=LogisticSaturation(),\n", " date_column=\"date_week\",\n", " channel_columns=[\"x1\", \"x2\"],\n", " control_columns=[\n", " \"event_1\",\n", " \"event_2\",\n", " \"t\",\n", " ],\n", " yearly_seasonality=2,\n", ")\n", "\n", "fit_kwargs = {\n", " \"tune\": 1_500,\n", " \"chains\": 4,\n", " \"draws\": 2_000,\n", " \"nuts_sampler\": \"numpyro\",\n", " \"target_accept\": 0.92,\n", " \"random_seed\": rng,\n", "}\n", "_ = mmm.fit(X, y, **fit_kwargs)\n", "\n", "# Generate posterior predictive samples\n", "posterior_preds = mmm.sample_posterior_predictive(X, random_seed=rng)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Understanding the Evaluation Metrics\n", "\n", "PyMC-Marketing provides several metrics for evaluating your models:\n", "\n", "1. Standard metrics from scikit-learn:\n", " - RMSE (Root Mean Squared Error)\n", " - MAE (Mean Absolute Error)\n", " - MAPE (Mean Absolute Percentage Error)\n", "\n", "2. Bayesian R-Squared (from `arviz.az.r2_score`)\n", "\n", "3. Normalized metrics:\n", " - NRMSE (Normalized Root Mean Squared Error), such as is used by Robyn\n", " - NMAE (Normalized Mean Absolute Error)\n", "\n", "Let's calculate these metrics for our model:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "R_SQUARED:\n", " mean: 0.9057\n", " median: 0.9062\n", " std: 0.0100\n", " min: 0.8605\n", " max: 0.9343\n", " 89%_hdi_lower: 0.8902\n", " 89%_hdi_upper: 0.9217\n", "\n", "RMSE:\n", " mean: 351.3628\n", " median: 350.5780\n", " std: 19.7836\n", " min: 286.7718\n", " max: 431.5480\n", " 89%_hdi_lower: 320.3752\n", " 89%_hdi_upper: 382.8984\n", "\n", "NRMSE:\n", " mean: 0.0686\n", " median: 0.0685\n", " std: 0.0039\n", " min: 0.0560\n", " max: 0.0843\n", " 89%_hdi_lower: 0.0626\n", " 89%_hdi_upper: 0.0748\n", "\n", "MAE:\n", " mean: 281.3655\n", " median: 280.6294\n", " std: 16.6181\n", " min: 223.4076\n", " max: 346.8520\n", " 89%_hdi_lower: 256.0472\n", " 89%_hdi_upper: 308.4454\n", "\n", "NMAE:\n", " mean: 0.0550\n", " median: 0.0548\n", " std: 0.0032\n", " min: 0.0436\n", " max: 0.0678\n", " 89%_hdi_lower: 0.0500\n", " 89%_hdi_upper: 0.0602\n", "\n", "MAPE:\n", " mean: 0.0556\n", " median: 0.0554\n", " std: 0.0033\n", " min: 0.0443\n", " max: 0.0683\n", " 89%_hdi_lower: 0.0503\n", " 89%_hdi_upper: 0.0608\n" ] } ], "source": [ "# Calculate metrics for all posterior samples\n", "results = compute_summary_metrics(\n", " y_true=mmm.y,\n", " y_pred=posterior_preds.y.to_numpy(),\n", " metrics_to_calculate=[\n", " \"r_squared\",\n", " \"rmse\",\n", " \"nrmse\",\n", " \"mae\",\n", " \"nmae\",\n", " \"mape\",\n", " ],\n", " hdi_prob=hdi_prob,\n", ")\n", "\n", "# Print results in a formatted way\n", "for metric, stats in results.items():\n", " print(f\"\\n{metric.upper()}:\")\n", " for stat, value in stats.items():\n", " print(f\" {stat}: {value:.4f}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`compute_summary_metrics` actually combines the steps of two other functions:\n", "\n", "1. `calculate_metric_distributions`\n", "2. `summarize_metric_distributions`\n", "\n", "The metric distributions (unsummarised) can sometimes be useful on their own, e.g. if you'd like to visualise the distribution of a metric." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RMSE Summary:\n", " Mean: 351.3628\n", " Median: 350.5780\n", " Standard Deviation: 19.7836\n", " 89% HDI: [320.3752, 382.8984]\n", "\n", "MAE Summary:\n", " Mean: 281.3655\n", " Median: 280.6294\n", " Standard Deviation: 16.6181\n", " 89% HDI: [256.0472, 308.4454]\n", "\n", "R_SQUARED Summary:\n", " Mean: 0.9057\n", " Median: 0.9062\n", " Standard Deviation: 0.0100\n", " 89% HDI: [0.8902, 0.9217]\n" ] } ], "source": [ "# Calculate distributions for multiple metrics\n", "metric_distributions = calculate_metric_distributions(\n", " y_true=mmm.y,\n", " y_pred=posterior_preds.y.to_numpy(),\n", " metrics_to_calculate=[\"rmse\", \"mae\", \"r_squared\"],\n", ")\n", "\n", "# Summarize the distributions\n", "summaries = summarize_metric_distributions(metric_distributions, hdi_prob=0.89)\n", "\n", "# Create a nice display of the summaries\n", "for metric, summary in summaries.items():\n", " print(f\"\\n{metric.upper()} Summary:\")\n", " print(f\" Mean: {summary['mean']:.4f}\")\n", " print(f\" Median: {summary['median']:.4f}\")\n", " print(f\" Standard Deviation: {summary['std']:.4f}\")\n", " print(\n", " f\" 89% HDI: [{summary['89%_hdi_lower']:.4f}, {summary['89%_hdi_upper']:.4f}]\"\n", " )" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "image/png": { "height": 611, "width": 1011 } }, "output_type": "display_data" } ], "source": [ "# Visualise the distribution of R-squared\n", "fig, ax = plt.subplots(figsize=(10, 6))\n", "az.plot_dist(metric_distributions[\"r_squared\"], color=\"C0\", ax=ax)\n", "ax.axvline(\n", " summaries[\"r_squared\"][\"mean\"],\n", " color=\"C3\",\n", " linestyle=\"--\",\n", " label=f\"Mean: {metric_distributions['r_squared'].mean():.4f}\",\n", ")\n", "ax.set_title(\"Distribution of R-squared across posterior samples\")\n", "ax.set_xlabel(\"R-squared\")\n", "ax.set_ylabel(\"Density\")\n", "ax.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Understanding Metric Distributions in Bayesian Models\n", "\n", "In Bayesian modeling, we tend to work with distributions rather than point estimates. This is particularly important for model evaluation metrics because:\n", "\n", "1. **E[f(x)] is not guaranteed to be f(E[x])**: This means calculating metrics on mean predictions can give different (and potentially misleading) results compared to calculating the distribution of metrics across posterior samples.\n", "\n", "2. **Uncertainty Quantification**: Having distributions of metrics allows us to understand the uncertainty in our model's performance.\n", "\n", "Let's demonstrate this with an example:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "RMSE calculated on mean predictions: 237.8336\n", "Mean of RMSE distribution: 351.3628\n" ] }, { "data": { "image/png": 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9zs8zAAAKhTnnAQAACiRcRa6LM7pImi933XWXqxxOdrFMF35UqaJbvlsp5kLLquqRcDCv9pfpKmvydfHosMMOq3NRS+Fgqko5BQkKWnUxCUvoIuQZZ5zh9sFkFyR1ITBVZZguZiswr6/qL91c4Qru/MG8Brxo/0l2AVL7nC7+KdCPmwInXWxMdcFcbVmTXZRVNeT555/vKj8rWbJKp1wr+9QWfdttt03c18VvhSDpvPDCC4GKOAX82QiHagqD1alBFbT4XyVxMjpedX5I9/mkc4uOiUzonKCuNRowlCqY1+tqn8mHCy64oE7o67XMTzeoQBWiWs5kgZ53Lkv2+/oM0+enwob66GcPPPDAlEGGPvdUzZlNlbg+Dw899NCUwbzXWj3XgTf5cMUVV9TZRjoHp5rKQJ9L+p6QSWcehewaiJIs3PP2h2SDMhUcaT1GCbT0maLlShXMa5/WOi+FgYRaVlUZp3pf2i+SrX8NJlA1sPbx+gb8JaN1owr48Oev9vF8HfOFPo5L4X3G/bdGqs8JrTvtJ7olW4/aRxR4a9BAtjTgRWG3/9jVa6kdfbLvavoOoyBfg7pEQb0GWvj3V+/vmWTHvPYZhfOV9DdMIY73OD/PAAAoJCrnAQAACkRt2cMXhTU/nirqc6WLuuEgT+1LdeFmk002ca38/BfKdDFPF5VUSayKBVVuJaPKr2T/n+x+mOaUrY8qTFRZ7FWd6qKY2kxqfkRdyNIFJFV8RK0My4Qu4nmhnVphqn2tKpd0QUf0mm+99ZbdcccdgXmwtb60rhVGF5vWsbcdNNBD7W39/6btXwi6UKsKQz9dfDv66KNdm3YvcFX7cHWMUAtO//QFqoBR1aUqnzIJE1R5qRBEwZsunO65555urnC1rffmN9W+reNOF/28C6hekKbtG8ec1t7+o4uM4QvNaimsC+kbbLCBe69aJl3MVECs7ecPEVVVp/ODqp3CtG3VytWj7gP+C8qqMk42v3A+zjf5oAuxujAd3mfU4jlXapvrVUXpdbRudQE9Vfj29ddfJ+6roi/TVuEenT90XvFvQw0+0XZSNZ+2o87FDZ3mH9b8x+qascIKK7h14gUXOh4UNmjwjI5Z/wA2nR80yE3HeH0UHCmEUDvdcAtkXdRXi2C1yvfON/qs0blCAbP2Sw3qyIR+x/ssUyCmVtU77LCDe68Kd7RP6PnD07Yo9NUAjnBYon1Fg5Y0/YfOUXo/mrtaAZ5u3rlMj1900UXuuF5nnXVSLp/OD/5pFrRM6hChdalWwv59Xm2cFXpoWdU9IDwlT5gCqfBAGw2QUecPDVjxn4e0HrRN1fZZz60AJ93UBvmk9+FV5OrzQedhnSu8baT3rUrY+++/33038g+k1PlDLa7rmxtZr6Fwzv+e9N1L21KfT6rA132tB81FrZbMqrL3V+Tq3K328um+Q2mQgQZxebQfq+JYn7d6Df9yqgOF9j0Fj6pODR8THu0P3gAjnTP9UxPo38JTC0X5XNG60/Q1/qkktD/rnOi9nrfvaf3rXPzoo4+6lt3+71zaf3WcZELHhReUa50oONf3YW/KGH0f0XkmH51NCnUcF/t9xvW3RjKadmGLLbZw607zymv+dO9zQuGtnkvPqc8JfRf0f2/S1DSZti1Xdb+OPR2D2lbquKNjVsuh96RtpM8Hfd/1nx/0mD6b9HfEdddd5x5TGK/toIF+3nGs59Xx969//SswYFB/B+l1dB4q979hCnW8x/l5BgBAIRHOAwAAFEiy+b/TzUOaCQWj/kBIF1F1wTxVpZou0ummoFAXQFTh613Q8dPF3lRhvP/fsuWFGboYqQtI4WoKXXBea621LA7eRXpdzFIr2fBFd60fL1DTRTZ/qKJKTF10y3R+xHzTMnrbQRcL/eG8LmTmYxvVRxfXFLb76UKq1pGWwU8XzBQebLfddi7A0EU5jy7gqoJIrTCj8iqGdBFaLYiTtQNW2KuK25VXXjkwZ64uMutCaVxTOZx77rl1Kie1HOGWq7qoqGXUcbjLLru4UM9/IVUX3nWhOXxhPTxHs7aB//X0XPmcXzbf1C7cO/49O+20U14GSyjAXW655RIXiBWqpQrnFUL5gzSFdbkej6qc9VNwoH1bt969e7vzs+bf1U2fC6VQ3VoIClo053e6kE/Hg0IK3RRqKYBQy2KPQgXt2/W1t1eAEg4h9XmnYCTZoBVtA50jdFN4rwBZQW1U3r6s5Va427lz58C/KwzWYADdwh1H/IGefk77ic6RfgqHvH1G51AFMd4cvgqN1Epb3wOSfebr+cODpxRupOoQ0axZs8S6UMCuDgTp1oW/84ScddZZLqBJRu9PAzJ007y/eg9vv/22FYL3ma/tr89K/7bw3rf2UQ0cUfWtP4TUADJ9T9B5PRUNxNJnjP98os88nZvD32O0HnSe0k3ncq0zrxJZYbr2i2eeeSZpta1CKX/nFz2XzjkKMZPRPqEBa7oddNBB7vfDg0REA8Z089aVP5zXcg4YMMAypc9zf1Cn8FZzcWs/DtP613zQummfUocbr4L23nvvdceE3kOmx6S6EWg5wucMbZtsu6T4Feo4Lvb7jPNvDT+FrDomdI5IRd8TNBBBN32n0nMr1BUNeNCxm8mUJOJ979LfIfp7JDxIQttOj+n8rsGk/spwPabX1TbUeUXH/DLLLBP4ff2NoW2u51Dw7w2o0P6jAaTa38v9b5hCHO9xf54BAFBItLUHAAAokGRt/DSvaT6oEsdPQVQmF/d0sSjTqo180cWbu+++O2Vb2TgpRNaFo3TVcLqQqAtF/vmkdQFOrT1hLhT3V6RrfelCZTiYD1/kVFDtbz8uqiJUu8pM6CKt5s6tb55eBQsKXvzeeOMNi4MqFD/++OPAY7oIX99cqApqdSz4A2pVvfkHXZQ7Vaepsu3qq6+uEyBoHeWDwgl/dbXm4/VXx3u8qnr/xewNN9wwp9dWuJJuQJG6JDz33HN2ySWXuAv0a6+9ttsvFCYna/OfDQWE2peyuUWpSs+W3me6YD5ZYK75wf1TwqjTgarf0tFgCJ2D/BQO6VyVLJhPRtWOmQ5uUlW+gqpwMJ+KqhrDA1Q0GCcc6IVpH9Ugg/BAP1VbJ6N1pvOIR9sgk7BOVaDqApDqePa309Z5P5OOLfrsVUhfKAq7FbyHg/nwz+g7VDiMru/zSYNI/BW8opCwvgGGGmyicN5PHYNStYVW1wH/AADtL6mC+WS0jXKZ3zyTKWc0AM7jDYpIFtQlC2j9lbN6v/oelint5xpQUd9gnlwU6jgu9vss1N8amkc8XTAfpu8O+vz0d29Qx5rwNolK2yRd9wJ9P9P29a9rnQM1oEvff/UdLhzM++nf1PHJL9xFqBz/hinU8R7n5xkAAIVGOA8AAFAgycJnVUjlQ7h1dilXzIbponQc82JGoYBYVRX1UWV2+GLawIEDY2m3X04UeoZbRKqCLN2FSX8Aotby/ouKCnoynXdV7UCjBhP77rtv4H6y6sF8CFdsqeWoKq2iUCWTKnf9VEHpVdeVMlVkKsAK39R2VpVop59+uqtKVWDln69Wx6Aqn/LRdtd/sdfPa3PvF56PXiFhruGGAmUFtFGrTFUFpiBBgaFCOgX2UeacbkhU9efnbymcjAIBfxWrLsZfc801sU1h4dExnsk+7O8cIgqEVNkXhTp+hLt+hDs2eFQpGNf3g/Bza7Bd3AFhrueFqG3D//nPf7oBFx7tU2pfnYwGqD3++OOBx3Q+UVVo1IErap/tl6ryt1y+74XDNX2H0mdhVFonmuLIow4LmQzeU/W6vuPFrVDHcbHfZynve/rc1TQVmXxOJKPpTvQdpT46z2lgXZgGGKYbmOrRwA3/3x76WyKbwdql9DdMoY73OD/PAAAotNL9qwkAAKDCJKsu8beHzIX/ArJXdVUOVMkRbs9dKGol7q/IrI8utPvXs9ov1lfBWen0/v0VfKqUyaTyVkFWuIIl02Ayk+rWcAWjKp38Vf/5Et4vNCggk9blukjpb2esC+L+FsOlSutT01+Eb6p+VviuVqThVv9qNarwXpXN+aQqOn83Bc3rrLlH/cIVirm0tPdr3ry5XXXVVW6giSpUMwmFf/jhBzv66KNd0OuvDmvIwtX29R0L4SpEBWX+qsE4KCDLZP+ZNWuWm6vYTy3HMxEOo3T8qf16fQMDNSgpX+e98HcPze2br0GHcTjggAMi/6wqTjVXcjjQSkZVuuFpiurrlOKnAQ3h7a9wMXzOSrY9S/H7nkI1VdL695NMz686b/q/H2ifTdYBJRWde6MEpbko5HFczPdZDn9rZPo5kUzUQRUSrghXR6iog/L096D+BgmfO8v1b5hCHu9xfp4BAFBozDkPAABQIHPmzKnzWL7mGta8fP4W3QqGdLEukws3xaAKo7irGVPJdFCAqlMUIL722muBi3+ZXMyrNOGL0qo4ynSfVjtKf0iqi72qUIzyPLpIpzlHo9LgAV001AV10QU9HZfhC865UHvTcACd6Xyvqh5SaO2v7B80aFDOLddLiS5kq/26goxk8yrnq0rWm5dVAxzefffdRNimTgT+EFcX2vM9tYfOy2qlroo4VYFpDnRdbA63vk5Gy6qBJ+o8oLa9mb7vTNrH+9U3H3C+aTso2NQ60bGo+/VdaPfm6k1G892q7a1fIdqmq71wJutOnx3+96lwX1WbmVhvvfXca06bNi1wnghXK2qgiv+8N3z4cFdxqTbYme5byUImtaD2WkjrOFPF5JVXXhn7gIhMqaNLJnOWi6qa1a7e39Zbgyq1vdJ9Fi633HIZv5aqabVNvAFveh0N1glX+utcpXOm93Oaf16DnzSgJ1/fKXOlucX9A/e0r0ap8A3T52B4PYenw0mlEN9/C3kcp1LI7/nF+ltD5y6dYxQCa9Cauiz59y8Jf+9K9zmRjI6pqF01vGPcT9PCZPJdUr/v/47nnZ/L8W+YQh7vcX6eAQBQaITzAAAABZLswku6eQIzoWpltYr2Wl9PnTrVVePoQpoqETbeeGN34SiuECyXQKNYwheBov6O/8LWkCFDrCH75Zdf6rRkz1T4d1QpqHb5UeYc1cXNTPdpTaHgPxZ1oTef4Xx4nailtr9VZybrxX/hNvy85U5t7TXvvP6byRzVmdhpp51ceOC1ONf88l44r3mC/QOmwm3w86ljx44uaPe6PKiVrLatgjcF9uGAx6M56HXBWfPpZkJBSdQKvmLQ+1d7cHUz+P333zOuegu3Vk43VYUu1mcyf3G29PmaifDxrGXMNMzQuU+t0D/++OOUz+sNhFEAc//99yce0/rXMaDvB1tssYWtu+667lyVjf32288uu+yyxH3NO6xqXoUqCiq1P+oYKLZw2/hsfkehoCqbw/tUPj4Lta/26tXLhU3+5w0HhmpRrSDfP7hI04Y89dRT7vymQXLqElOs6YKSVS3ru6kGGmUqXE0cZWBTIb9fFvI4LoXv0YX8W0PHwXPPPef2c30nzFS6z4lUx1+y6cdSCf/91qVLl5y6qWXaKaeU/oYp5PEe9+cZAACFRDgPAABQIOF58iTK3NxR6MK3Wkdr/nZ/0PH999+7m+iiky6gaZ5EVTVonm5d5CgmVTIXS6YX0rx5JtNV6jQ0+Zj7UceALmb72/cmO1aSyeRCqie8z/vnPs+HfM2HGf69qOukmHReCc+TrGoqheAKtNRCVf/uzSOqtqoKz9XSOdzaNx90cVYhoRdiKfxQFbvOlwrq/dWOCvILRdM56Kbg8pRTTnFhtearfuihhxKhh0fLrgvf2VbClxLtC3fffbcLEsPvM9cuNB5/9al3HBViDvRMP8sKfZ446aSTXJv0cKWmpl7QTWGaOkfoe4GCDXXpiNoqW4NOdGz7pyTR+fyVV15xN1EVsPZhnSM22GCDrAYsFeMzX9X/mqZCoXy6z/18bk9/OJ/qO8YFF1zgusyMHTs28ZiCUp1fdVNHIoW2Cum1PbXOC/l9S8vip5bX/rbX2crkc7AQ77cUPu8LuV0L8beGBtNdf/319uijj7rvCHF8TiST6SDN8HvKtGo7/PuZDlIrpb9hCn28x/l5BgBAITHnPAAAQIEkq1DI5uJKKmrde88991jPnj1TVpEonLr55pvtwAMPdNVV11xzTUaVSPkWrhwppGzaH4Yv3mVamVNpwhfOsm0pGV6vUS8YlloniGT7RLbVi+F1Ug7hfKptpP1ClaRqu6xq6XDQrAr6TOYSzoR/3lMNxHj55Zddu1tVrHtUaVXodu5+CurVClzVX+FWufKf//zHKoFaz95www05BfMSbmecLpzPZgBPIT7L4jp3pjpPaPkUdu27775JgzKtU3UxULDxz3/+030/0ICZd955p95l0PPddtttdswxx6SsGtYc2i+99JLbB9QqXpWPms4k34Oj0olzHRd6e2pQm7ZVqilTFGqqBb+2uQYAbbLJJnbsscfaF198YYUQ1+dVJueOQny/LPR2L4Xv0XH+raFg/oQTTrAHH3wwp2C+vs+JOL5PFvr7aCn9DVPo4z3OzzMAAAqJcB4AAKBAvLmP/fr165fX19AFWLUsVBtktT1NF0zoQpnaAqr1rC5gAEDcVOWnymn/wCQFdGrf7rWfzyfNseqf+1qB4IsvvhioUouzpX0mVOmlQCPMP5CgXKlTwTPPPFPnAvuee+7pght9Bqn6WnMtqxpObZ39N+RO61tVr+rGoIEy6dpP6/hQZaKCsoMPPtgmTZqU9rnVfeL000+3d99918444wxXOZuuWlZVtmeffbYbPDNs2LCc31tDpPOavutp0IOmBlFL/FQ0f/17773ntqXC+kxbaGdKr4fKFdffGuqsos8BPw2cO+igg+zGG290be7/+9//urnINfjE/xmhcw+KoxjHe5yfZwAAFApt7QEAAApEFwbCF1bV6jXf1M5U1VS66YKELlqpKlW3L7/8sk71iioTVM0mqmZrKLK5OO2fqzzuqsxMW1wWg9qG+/enbC/4h9drMac7yFV4n8i0tWqqdVJJ82dqzuSLL77Yjj766MRjanuvajn/Y/k6H+6yyy7uuUXnQ7WR91/4V1VVqVhjjTVcK1aFD57x48e7gQtNmza1cqQqtvCgA7WZVdgSpWNBJsdQ+PlKtbtJ+HjO17kzynlCLeUV0OqmLiVfffWVGxSh2w8//FCnYlXV1gp/Nad5fdWaqujWMayb3pP2Y3330HPr/8MDcHQ8qqJRAzc6d+5scYpzHRdzeyqUOuecc9xNoZO3PbXeBw8eXKeC+I033nBTi+icGNfURuHlPvLII+0f//iHVZpibvdiy/ffGjrPqyLfb+edd7bLL7+8zvzuycydO9caklL6G6aYx3ucn2cAAMSNynkAAIACUKWHwic/BUJxt0HUXLuqzveqTj766CPXOllzxKrSLdxauiHNoT5u3LiMf8c/v2t9IXJ4nuNMw/bwRbRSFH7/4fUThS7g+uebL5cL03GuExkzZkzFrJNkdP5TVbufLszHEaaGK+P95zld/A+fC4tNUwCElfO5WXNj+8+3CgQU1kedSiDcqj6d8HPqOCrFgU6lcp7QcqjNvFr/avqETz/91K666io3X7nf0KFD6wRn9VHwoWP81FNPtYcfftgNULzpppvc4JPwZ8C//vUvK8XPfM2l7J9vPtXnflzbM9OBappXeccdd3QhqLqEqL24/j8817QCKlUhxzkAq1LOX+VwHBdbPv7W0O/4jzV1gtC5KEown+nnRCWI+2+Ycjze4/w8AwAgDoTzAAAABaCWjmHFaKWswQAKflS1qovl/otmqsJQ29OGQi0xc/2dvn37Rp4HNNOqnmwv8hZS+IKXQrhMhX9Hcxana89bbutEFylHjx6d83pRdWSl0TzrfgrmH3rooby/jkKDVOuvVFra+yULI6IGFKUo3JZ+iy22yCh8UvVbtgMb9Ln266+/WqmfJ7SMmU7roIpoTQGQz/OEBk4MGDDABbtbbbVV4N9efvnlnJ5bn4l/+9vfXGiiuaj93n777TqDtPItvK6y+Z3mzZsn/XzKx2eh9tXwIM5ct2fHjh1dG+dXXnnFTTXgp3b4cQl/N1IFfyUq1eO42LL5WyP8OaFzRSbdYjL5nKgEcf8NUwnHe5yfZwAA5APhPAAAQMwee+wxV73kt8oqq9j6669vxbTWWmu5OSD90s3tG25/qnmiy1mm81MqOAhvxzXXXDPlz4fbRYYro9LRulVLxkwUY/uEKyDff//9jC9Mv/XWW4H7uqBbapXMmejdu3edaqR33nkno+fQvhK+iKrjtdLoPLjlllsGHtOF/Di6Rmhu67AVVlghaZV6sU2YMCFwXwFF69atrVyphbbfcsstl9HvZzJoTK3Rw9PFxBlCZkufHf7uKpqzV+fPTKh1dLhaNF/nCbWsPvPMM+sMGMvXXOWan95/nlfFbDiYzjdV6Guu+0yEz90rr7xy0s+n8GehqlozHQygAQr+FvR6ndVWW83yQQMjTjrppMBj6Qat5Pp9YuONN64T1vmnE6kUpX4cl4Kof2uoS0WhPicqQdx/w1TS8R735xkAANkinAcAAIjRhx9+6Fo4hitKzj77bCsF3bp1i1zdvdRSS5Vd2/V0fv/9d9faNSoFPP6W27p4vdlmm6UNaf00D2dUb775ZsZtIcNzJxZi++j9+6dm0DK/+uqrkX9f8+Nq/ttwVW25C89hrkpRXbSP6tFHHw2ENKoyDoc/leL4448P3NcxpoA+3zTvvNo9+2/HHXeclRrtJ5oGJRwIlrNwmJnJ1AXjx4+31157LaPXU8Wln+YzDwc/xabBFuEATsd9Jh555JHA/ZqamjoDE3KdyzdM80bngz6vwoOY8vXc6TzxxBORf1aBaXjfCw8m8g/0CbeOz2R76nwf/nkN4FQnmVL4vpdpiKVg1V+pr6klKrGNdDkcx6Ugyr4XrpLP5HPiu+++c3ONNyRx/w1Tacd7nJ9nAABki3AeAAAgpoDl1ltvtWOOOaZOJfHhhx9u6623Xl5fb+HChVn9nubd81tmmWXStkdN97vl6LLLLotU6a3KT82j6acWiZ06dUr5O+GKN7WVDc9dm8yMGTPsuuuus0yFt49aqWdaxZ6pnj171rm4p7mDw5WyqVx++eWBi7RqGbz33ntbudO8q36qCL377rsj/a4q5sMX6/faay+3biqRLuiG555Xa/t8VzTp+NAx7L/ttNNOeX2NG264wW27XI67O++8s06QnCoQLBfh86Sq96J8ZqlaV3PHZjKwRQ455JBAqKlz6llnnZX152RcwucJzcn+wgsvRK4SDXcdUfvyOL8fKMwJzy2c7XPrMyL8ORH+DIuD2htHHSh37bXXBga5aZCJzsXJqHr6gAMOqPNaUcMzdVgKt8LXfpxMtut82LBhBf2+d8IJJwTuP/744xlXlfv5B6w1xOO4FMT5t0b4cyLqvqLvkKUy4LmS/oYp1eM9zs8zAAAKjXAeAAAgj1Tld9ddd7mLHrfccourHghX9IVb6+WrKvT222/PqDpQFwXDbSDTtdoPV2/qwkupXiyNSm1dTz755LShuarnjjzyyMC61UUdDbxIZ+uttw5UjKpK/Kqrrqr3AtrRRx/tWuJmShfT/Rc8VRHy3HPPWdyOPfbYQFvXKVOm2N///ve0Ab1CtyuuuMJ1CPBTuLH00ktbJQTOm2yySeAxnQ+eeuqptL/322+/ue3vv/ioyrxDDz3UKlm4el5haqbVh6VAx7gGnKiFrz4Hwu3p09E21zlcg7r8tP3LfcCKBqP5O2xo4NC///3vegMXteHOpDLQfy7UOcjvo48+cp0StG9FoQE1mVRZZ0P7iSqu/S644IJ6Aw2tE7WF9+vSpUvSqRu8z2p9Xn3yySeRP7P1+XHllVcGHlt77bXrtDvXsuq8rZbsUUMT7/zvb5Wuytpw5Xkc9P4VIg0ZMiTtz+k4DH9+7rfffmnDnH322SfwGazXOvHEE+ttpa/q/PB3Aw3uS1XVev3119sZZ5zhqoWjShbOZfJ9T9s30zbV6oLj/xzU9tb3rUyPKy3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5cuCYzeQc6Z0nvQGdeh49X337SL6PHbXSf/nllxPnmIceesieeeYZ91mvv0s00EiDdYs5dQAAAGg47ri71sJfX884rcrWWzc/30Xefc9swB61tsbqfLcBAACViXA+C5oX1h9wqRL16KOPrvf33nzzzcT/q91o1AqoKMvz2GOPBdpYRwnn9XN+Udpba+71ww8/3F2Y9P/eNddcE2j7mSm1YFZrTy+U13/1WvVd/NTP+VvKal7gVJVcqiZUNbE3tYDev+akjWM9lbp+30RvvRvWaKnUp40VB+5mluUA50YtUs+P3fvZHcwWZffEVc1SP2/Pe7a02oX1V8CVI80l752nBg4caGeccYa99957iQv/mkd7gw02yOq5/QNzJEoVYTrJqpDzKcqc3/lYD1ErMfPNX2mp87C2bVT6WYU53tQHUYLbqMF8Mv4pFvIpagvvcHCV7XtJ9j4KdVzoeL7gggsCc39nwt8mvT75XD/5Ut9c8+HlV2Wyd4xEqejPpJtIeJtnu01SbW//8mrwYSbBaybrqZzOd9kIb/co036kW5c6T9b3/TTfx466P2kO+yuvvDJxDKsTyVtvveVu3sA8VezrbwD9beCvyAcAAMiX73+otVeXzOblbLG52c475jdIv+2OWrvr9rp/wwEAAFQCwvksKJy97LLLEiHv008/7QLrdPO1q3rJX7GlEFlVUPmw3nrruYBl2rRp7v6rr77qgrh0F+VUHam5TP3z8NZX/a/n1/tUm2yPBhjcdNNNeWltusMOOyTCeV3gfvLJJ+3kk09O+ztPPPFEnedIF9Cpqk3BhgwbNsw+++yztAGltrEqkzxNmzZ1FzzLXXWH5vE8b/uYnrddfufO9TRu29Qq1UYbbeTCnOnTp7vQ56OPPgrMh63219ket/luWZ1riFmfuFovh6un83VOz5S/VbwCoUwuXijM1+94gzaiTouC4hwXmuteXWr8IfBqq63mvpeoVbemEdBnnQYraPoBz6WXXpo4/uMMzgsh3MWgPtq/vW0TpaLfv94Kuc2TbW//8mbzvivxfJeN8HQama6b8Hst1nlS33FVxf/AAw+4wXfhgTYaNPDBBx+424033mh77bWXHXXUUXnfFwAAQMOlvyVuviX494S+pp5yYv4D9J8HayCA2RrRZlQDAAAoK4TzWVC1kNpLPv7444mWwnfffbedcMIJSX9+3rx5dvnllyfuKzg57rjjUj7/mDFjAtXZamPqBcrJKDDW/O/XXXdd4mLx1Vdf7aprUl0AvuiiiwIXgo8//vi071nhnl7D39ZUbTRvu+029/r5oDnrtR69FvL33nuv7bLLLlZTU5P057/44gt76aWXAvNxhudPDtN6969LDbJ4/vnnU74HtST2t4zeb7/98l6NBsQVSG+zzTaJwSWPPvpooAVzti3tJXyh/5///KcNGDDAGhpV5JZCYONfDrXW1gWTqAG9Pgf88xaXU+BWagpxXGhqFn2n8Jx22mm277771vt7cbaZL7RM34t//8404M5km+u7gX8AVD74lzeX911J57t8LHum66aUBiboO7EG2+h7+ddff+2mdvrxxx9t8ODBgWk1dJ5QVy19V9b89HF1kAEAAA3LJ5+a/fJr8LEjj6iyZZbJTzjfaVmziaOX3P/Pk7S2BwAAlSn7PuQN3LHHHhu42HfLLbfYgw8+WKfy6Y8//nChtn9eWLWbVpCcTwcddJCrmPM8++yzrtV8uKpGF/NUVe+fh1QtMBXipaLnUHivi3/+uUYVpOfzQrcudvoHCejCoir1dcEx7L///a/7WX8FoEKK+gIpzcm5/fbbJ+5ru2j7aDv5aTvef//9duuttwZa3R5zzDFZvz+g0HSu8QwZMiRxvKg9bt++fbN+3vCc4arOb4jC68E/3Uch+dtw69zldVGJQj/rP4/SBtlK+rj4+OOPE/+/1lprRQrmJfwZV84y2b/1PcJfNZ1Jy/pMt7mqlvPdBcS/vNqfMul6kO9tXirnu2yEt7s3CDTbdVkK50mF7erCpemZ7rnnHnvnnXfshhtucJ/7/gGnv/32m918881FXVYAAFA5Hn40+H1UDTj33CN/z7/rLsH7H39iNnpMeXf+AgAASIbK+SxprkldBFMlti7G6oLpVVdd5dqsq0262kmrdbzmePZX6PTp08dVvOSbqrdUxX7ggQcmqqsULr/yyivu4p3m19Tc7Koa988pvMwyy7i29OmoKufzzz8PPPbzzz+7dvqZWHfdde2hhx6qd5DBoEGDXGt+r4XvHnvs4drnq5WnqoK+//77RPt7/2CJzTbbLNJyqIvBr7/+mphmQO9Nrep1U2t/XfjX4AV/xbza3KpFaDnNsQpoEFCvXr1sxIgRgcdzqZoXPad/nnJ/RX5Dsvzyywfu//TTT2mn1ohLjx49Avd1fks3XYdfeNv17Nkzr8vWkMR9XOi7xKRJkxL3Na90FGqBr32iUihsjErdfvyBeapOPNnS83311Vfu//X9RK+3wgor5HWf0ncir3pb0wp169Yt7+upnM532dB3XQ0A9SrgMz0e/MeynkfPV2r0d4Cms9Ft//33d4NJvferOek1MJf29gAAIBeDh9TaTz8HHzv04Cqrrs5fZft225g98ZDZ7P8fX6s/rZ58utbOPI3qeQAAUFmonM/BFlts4QJ5f/W4QrD//Oc/duedd9rrr78eCOY1H6zapMfVWlLzxquCXwMDPLqQ//TTT7vleeGFFwLBvC7wqvq9c+fOaZ83WaWWLnbrgn8mt6gVZVqn/gu+en1VC953330u3PcH8wpCDj30UDv11FMtKlU8qcrIXzmsAQ0aEKD1pLnu/cG8LsRqmgDNVw+Um3AQrznGcw1UdI7xB1AKp8Jz+uZ7rvi456XPNqzyn281GMvfVrhQ1BHE78MPP4z8u5q32E/zl6M0j4vw/OZRq8A/+eSTimprr/cTtYL8o48+qvM9KZ806NBPc33nk7oUhbsGRaH9Ti3Py+V8F/e5XgMs/R2r1JFpypQpkX534sSJrvOMfx/S52gp03lIA1v9HST832sBAACy8ezzwe/gyy5rts1W+X2NFi2qbNddg4+9+Za+z1A9DwAAKktpX10qA7vvvrs999xzri18kyZNkv6MKmw0H/1TTz0VueIpWwqQX375ZbdcqVrOqzXpwQcfbC+++GLe2+vnQ7NmzVwLTrXlX3HFFVP+3JprrukGF5x77rmR51f2qEJegxbUGj9VBZS257bbbuu2767hvw6AMrHzzju7wSve7YILLshL1d92220XCIIef/xxyzf/vL7hYLIU6Lyjc4RHYY/OF4WmsEjzXXvefPPNSG2b1ZZarZA92i/yHV42NHEeF+F5rtVZpj4KOuvrWFNuxo0bVyd0T0ZVw+oe5NHAyHCYnit1EFp66aUT9/W9Ip/TGagK2v/dUueXKIG4vt8pkC2X810hzvX+AZYaMKqBmFGoI5Z/wIC6UZWDLl26BO4vWLCgaMuChqVRqybW4/bNAjc9BgAob3/+WWvvh8ah7rFbblXzLZu2tgu2vDtw02N77VFl/rGQGmf86Wc5LDwAAEAJoq19Hmj+ZrWUVzt0tR9V+3hdlFcLdIXAmhdWVTtRKcDPpR3usssu64LtCy+80FXu6QL+jBkzXHjTtWtXW2eddQLzUdZn/fXXL0rbag0w0E2vrfasql7SetT7U4CUa/tlrQPN1XniiSe67TZ69Gh3sXmppZZy3QS03fwX3YFypCkt9ttvv7w/75577mmPPfZYYv7nBx980FXrqaNIVLNnz3bHnbqKJLPccssl2g/rPKCApNQqFg844AAXUCnsEX0WaFCRBg9FoQrgTAcXhSm8U5WkuouIPn/0GaAuJKk+exTwXXnllYm2xzJgwIBABStK67jQZ5Om1NFnoTcI4/DDD0/bqloD2H788UerNJqOR10e0n1Gq5OQf150dRHJd1tvPZ/OATruRd+1zjnnHLv++uvrDKaob/ogDZYMfzdTpfqWW27p2pKLpkt64IEH7Kijjkr5XPoZ71xQLuc7nes96vKgaYfyPQWBBqqpe5V3zlPorsA+3HnET98NNeDCP8Bjp512smLQNAKZDJ7SPuVXX5csIF8aNWtsbXfuVezFAADkmeZ+9zUGtcaNzHbKbbY8a9q4mW1eU7cQRhX5/desta//N7uT887AWttic1rbAwCAylFaKUeZ00Xirbfe2s37fvTRR7ugQ1VamQTz+aQL+arwUTCnuSf33ntvV4WVSTBfCjTXvC6q/v3vf7fDDjvMdtxxx7zOi6zto+2k7aXtpu2n7UgwD6SmzhwKobygRWGN7qvrxR9//JE2nPn+++/thhtusN12283eeOONlD/rb7GugTPXXXedq5otJQqVjj322MR9Vatq0I8C2vnz5yf9Ha2rL774wv7xj39EqgCOGpr5wxe1tldXkWTbQlX1Z511ln366aeBQWH77rtvXpalIYv7uPBX7WogoJ5bgXCygF8DNDQ4wFuuSqHvMDoPaGDd77//XuffFe7qvT///POBkPuII46IZXn0Hct/rtLUOxo0ofb76Wi7abohBe06h6SqdNe/+befgndNwZOsElqvfdJJJ7kBOnF814vrfBeeTkPbT63kvUEA+fpOrO/C/gFKmof93XffTfrzb7/9tp155pmBZVC3pWIdS/oOrOV/6aWX0nZn0H5x//33u+X3aACCBuoBAABk6+13gm3l117brH37+MLyrbcKPrcq5+fOpbU9AACoHJTIAQCystlmm7mA7NZbb3Xhom6qRnzmmWdcFagqhjWNhkIQtSrWnLeqhJ85c2ak599hhx3snnvuSYRWCtt004Aaf/C0xhpruEraYjnooINcdw+vulXLq6pdVbiuvfbarr2wqmgVmGkdqALSC1Q18ChfwdMll1xiJ598cmJ9af7rzz77zHU/8QY0qar2888/DwSBWrZLL700o0pfFOe40L6mVu1e9a8GWKhrggbeqVOPgjlV3SsM9eaZ79+/vxu48fr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" ] }, "metadata": { "image/png": { "height": 611, "width": 1011 } }, "output_type": "display_data" } ], "source": [ "# Wrong way: Calculate metrics using mean predictions\n", "mean_predictions = posterior_preds.y.mean(axis=1)\n", "naive_rmse = root_mean_squared_error(mmm.y, mean_predictions)\n", "\n", "# Correct way: Calculate distribution of metrics\n", "metric_distributions = calculate_metric_distributions(\n", " y_true=mmm.y, y_pred=posterior_preds.y, metrics_to_calculate=[\"rmse\"]\n", ")\n", "\n", "proper_rmse_mean = metric_distributions[\"rmse\"].mean()\n", "\n", "print(f\"RMSE calculated on mean predictions: {naive_rmse:.4f}\")\n", "print(f\"Mean of RMSE distribution: {proper_rmse_mean:.4f}\")\n", "\n", "# Visualize the RMSE distribution\n", "fig, ax = plt.subplots(figsize=(10, 6))\n", "az.plot_dist(metric_distributions[\"rmse\"], color=\"C0\", ax=ax)\n", "ax.axvline(naive_rmse, color=\"C3\", linestyle=\"--\", label=\"Metric on mean predictions\")\n", "ax.axvline(\n", " proper_rmse_mean, color=\"C2\", linestyle=\"--\", label=\"Mean of metric distribution\"\n", ")\n", "ax.set_title(\"Distribution of RMSE across posterior samples\")\n", "ax.set_xlim(0, 500)\n", "ax.set_xlabel(\"RMSE\")\n", "ax.set_ylabel(\"Density\")\n", "ax.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Comparing Prior vs Posterior Distributions\n", "\n", "We can also visualize how our prior beliefs compare to the posterior distributions using the `plot_prior_vs_posterior` method:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Sampling: [adstock_alpha, gamma_control, gamma_fourier, intercept, saturation_beta, saturation_lam, y, y_sigma]\n" ] }, { "data": { "image/png": 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IuUjFwbH1wMaXUzoXAAAAAACAkYxw1wjQ2NioK664ImHfF77wBeVZaZC9aKszksTfn5F23wBgKPF8mmjTZgtzeaGu997rerk9RNOmSYcc5NNBB0kV5TxmwEDk5/uUny/t16nNYzjsuO0cO4JfXgjMRl1d1/O0tUnr13vD0xH8KrJqX25bR58b9po6xVta2CwYHNz/Z3lOHRo8tkim4PrnY+vhSfPlE79f6cLX+f/7blr+YpDklihSOFX+PRvk3/G2fC11UvaYVM8KwD7gdSoAJA/PqQCQHDyfAh7CXSPAj370I63v+MRKM2bM0AUXXLBX5yosLNRINXbs2FRPAQBGhNH6fLp1W1iPPtaqhx9p0fJ3Il0ut78p5swO6Kj5GTrs0KDGjvWnZJ7ASGdPQdOnd93f2Oho+/aItu8Ia9s2W0a0bXtEO3ZEFAp1Pb662htLlkZTAN4yGLTAV0DTp/k1bZotA7FlYWHy/78erc+pyRQMWjWlxB9yMBhUYSGPLZIntPHFWGYod/ZJ8uURYEmFUKBrxTR/3D6rYo6hFZ52lJy3NsjnRDSm+h3557w/1VMCkCS8TgWA5OE5FQCSg+dTjGaEu4a5v/71r/r3v/8d287MzNQvf/lLZWVlpXReAACMBPX1ET3yWKv+fV+L3nizm3SIpFkzAzrqqAzNP4JAF5BKubk+zZgRcEe8SMTRrt0W/Aq74S8LfLkhsO0R7anpWt7FgmDr3gu7Q2pLuKyoyKdpU72g19T25bRpfk2eHFBmBt8aA0Yqp75Sztal3kbZLPnySlM9JSBt+CYfIeetO911Z93zEuEuAAAAAACApCPcNYw99NBD+sUvfpGw78orr9RB1v9pL+3Zs0cjiZVmjCZ4a2pq5Dj0ZwCAvTGank8tCPLmW9KDDzl65jlHLS1dj5k8WTricJ8OP1wqLrLHotUd9fWpmDGAvuTmSDOme6ODT01N0s5KaceOjhaPbrvHSi/k1Vl1taPq6pDefCvxQisaY+0cra2j2+Zxsj1PeG0eS4q7lgsfTc+pQyEUCnezLzTi/rZB6gTfvl/Rr0+1jZ+nxtraFM9o9MoKh9W5dlck3PEcUFdXx3PqUBszUzk+v1u5K/Tus6rjuRcY1nidCgDJw3MqACQHz6cYrgqT3DWPcNcw9dJLL+k73/mOIpGOtlDf/OY3ddZZZ+3TeUfyk6Hdt5F8/wBgqIzU59Ot2xw9/IijRx6Vtm3venlFuXTEPLmBrnFlHUGNkfhYAKNFdraFsbxhYa/4kKe1bIwPe7kBsEp7A6HreSxXsHmLN15alNjmMTdXmjzJC4Va8Cu6PPggR3l5vhH7nDqU5s2TysoS99njzOOKZAmsfSq2Hpp8lJxYg0YMtfD4Q+V0qpzmjJnYsW7Pqfx8hlZmriKlsxSoXCX/7jVS3Q45+eNSPSsAScDrVABIHp5TASA5eD7FaEa4axhasmSJvvKVr6itraNNzPnnn6+LLroopfMCAGC4aWqy6lzSQw971bo6y8nxAl3HHOUFBTpX3wEwMvn9PpWUyB0Hzkm8rLnZcUNe0dCXu2xfb7Uifp00NkqrVnsjGvjyllUqK/Np0kTHfX6ZPKk9+DVJGj9eyqDNY7996QJa4mIQhVoUWP+iu+pkj1WkdP9Uz2hUazvivC77fPIpJyWzQVR4/GFuuMsENr6s0IH/keopAQAAAAAAjCiEu4aZ1atXuyGuRvuUqN0nP/lJt4oXAADon3fXOLr3344ef9ILXsSz/NbsA6Sjj5IOPoiABYBE2dm+uGpfHewbY3tqug99VVXZ5V3PVVnpqLJS7eHSjgMCfqmiIhr68lo8ustJ0rhxXvgMwNAIbHpFvlBTrGqX/J2bAgIITzhMWnq7ux7YRLgLAAAAAAAg2Qh3DSMbN27UF7/4Re3Zsye27wMf+ICuvPLKlM4LAIDhoKXF0VPPyA11LX+n6+XW0ssCXUcdaX2wCU4AGBir7FdUKHcc0KmwT1vI0a5dFubyWj3acvfugLbviKiurmvqKxyRtmz1xsuv2J6OYzIzpYkTHE1qD3tNmmTVv7z10lIqDALJFoxryRiefHRK5wKkq0jZHDmBTPnCrQpseMlLNPPvEQAAAAAAQNIQ7homduzYoc9//vOqtE+C2i1YsEC//OUv5ffThgQAgJ5s2uzo3/c5eugRqbY28TILScw73Gu7OH06oQgAgyMj6NP4CrnD2HNNfn6eu75zZ5127mxv9VjpBb+s4lflLguldj2XtX58b703PB3Br+xsuW0eo8GviRO94JdtlxTzHAcMmOMosO4ZbzWQofCEw1M9IyA9BTMVrjhYwS2vy1+/Q/7d79LCFAAAAAAAIIkIdw0DVVVVbrBry5YtsX1HHXWUrr32WmVkZKR0bgAApKNQyNGLL0n3/NvRa693vXzCeOn446Ujj5Bysgk7AEid3Fyfpk6VOzq3ebRAajTw5Ya+ouu7pHC467mam6U1a73RfpaE4NfEiY4mT7Slhb987tLCXyUltHoEuuPf+Y4bVDHh8YdJGTmpnhKQtsITj3DDXSbw3vOEuwAAAAAAAJKIcFeaq6+v1wUXXKB169bF9h166KH64x//qKysrJTODQCAdFNV5eje+6T7HvBaoMULBKTDD5Ped7w0fRoVbACkN3uOGjtW7pg1M/GySMRR9Z6O0Fcs+LXL2j3a5d0Hv9au9Yana6tHC3u5Y4JPEyd4wa/ycikY5PkSo1Nw7dOx9fDko1I6FyDdhScdKS2+3l0PrH9ebfPPT/WUAAAAAAAARgzCXWmsublZF198sZYvXx7bN3v2bN1www3Ky/PauAAAAGnVakd3/svRk09JbW2Jl5WWSscfJx09X8rPJ6AAYPizKlvWZtHG7AMSLwuHHVVVeUEvC31Z0NVd7yX41Vurx4BfKq9w3KCXVT2c0B78mjDBQmBe5TFgpAqseTy2Hp58dErnAqQ7Z8xERfIr5K/frsCWN6TWBimT964AAAAAAACSgXBXmgqFQvr617+uV199NbZv+vTp+stf/qKx9vV9AABGOQswvPCi3FDXW0sSL/P7pYPmeqGuA/an3RiA0SMQ8KmsTO7QnK7Pm9XVHWGvaPjLHbu7b/UYjkhbt3qjc/DLFI513KCXO8Zb5S+fxld46zYHmw8wHPmq1yuwa7W7Hi6bLSevNNVTAtKbz6fwpCPkX/mgfJE2BTa+rPDMhameFQAAAAAAwIhAuCsNOY6j7373u3rmmWdi+yZNmqSbbrpJJSUlKZ0bAACpVlfn6IGHpLvvcbRte+JlubnSccdIJ7xPKioiUAAA8SxoZdUMbXTKfbmtHvfUdAS9dlnwa7cXArN9LS3dn9OuY+OdFd1U/QpYW0fHC3u54S8v+DXeKoCNlwoLk9Mi9/EnHbcqWTz7s+m0hfw7gL0XfDeuatfU41I6F3QIrHtGvsaqxJ25JdJh/5GqKaFTa8aMlQ+668H1zxPuAgAAAAAASBLCXWlo69atuv/++7vsO/nkkwd0nokTJ+rxxzvekAYAYDjbtNnRXf9y9NDDUlNz4mXl5dJJJ0pHHiFlZfFhPgAMlFU4LC6SO/af1fXLJ/X1Xthrd/twA2Dt63v2dH9OqwQWrfr1+hvumRIuz86WKiq88FeFhb4qfO7zuRsAq+h/+Mv+bVj+TuK+uQcS7sK+Ca55IrYemnp8SueCDhnv3KdA5cqEfVZZjXBXeghXHCrHH5QvElLgvefsHxC3ohcAAAAAAAD2DeGuNGQfnnQWiUQGfJ5wd31VAAAYZpYuc3TbPx09/2LXyw6cIy04UZp9QHKqvwAAurLn14ICuWP6tK6Xt7U5qqpqD3ztknZXyd12g2BVUnOnQG6U7V+/3huexL+DsrIs5OW4ga8KGxb+GucFem2UlkjBIM/9SD5f3TYFti9118PFM+SMGZ/qKQHDQ0a2IhUHKbD1Lfnrtsm/e40ipZ0SwwAAAAAAABgwwl0AACDtWHswC3NZqOvt5YmXZWZKR82XFpxgH+7zoT4ApFpGhldxy0Z3X1xpbOwIesWWFgDbLVVVS6FQ9+e1VpDrN3ij/WwJlwf8UmmZo7ra7oNjtbWOG0gj/IuBCr7bUbWLlozAwIQmHeWGu0xg3dOEuwAAAAAAAJKAcFcamjRpklatWpXqaQAAMORaWhw98pj0zzscbdqUeNnYsV6g67hjpdxcPqgHgOHAglV5eXLHlCndh3mt5WO02peFvdxl3HZbW/fnDkekHTu6v2ztOumD/+EoJ1sqK3M0bpzc4Vb+Gudz10tLpXFl3twIgCFe8N3HYuu0ZAQGJjzlGGnx9e56cM2TajvqolRPCQAAAAAAYNgj3AUAAFLOqqvc82/pX3c77gf58caPl045STpiHu23AGCk8ft9GjNG7uiu5aNV/qqrl6qrvWH/RnReb2jo+fxNzdLGTd6IO2vCMdEAWFmZLaWyUlv62pfedmGhFAjwb9Bo4KvfKf+W1931yJiJcgq7SSUC6JFTUKFI0TT5q9e77U3t/yknf1yqpwUAAAAAADCsEe4CAAAps327o3/e6ejBB70P4OPNnCmdeoo0ZzYVVQBgtLLn/zEFcsfUHjI2v7rG0caNifvy86SJE6XqPdKePVJr674FwKwFZHGx41b7Ki2RStylL7Zty5ISaewYL7CG4Su4+lH52n/+oekn2i9hqqcEDDuhKccqs3p9rDVj6JBPpXpKAAAAAAAAwxrhLgAAMOTWb3B0y62OHntCCoc79tvnp4ceIi08xT7E58NUAEDfustSWdjqK1/2xap/NTZ6Ia9o2MsdNd6yxpY11hq459uwFpCVu7zRUwDMBINScZHjBr1sFBdLJTYsCBa3r7hIysjg37l0FFz9cGw9NGNBSucCDOvWjEtui7VmJNwFAAAAAACwbwh3AQCAIbNypaObb3X03PP2YXvH/owM6ZijpZMWWPsrPuwGACS3+ldentxh1bx60tTsxIJf0cCXrdfWets2rEVk/L9fnYVC0s5KbyTqeqUxY5xY+KuoyFsWF/vc4JcbAGsPgY0dS1vioeKr3aLA1jfd9UjhVFoyAnspUjJTkdxS+Rt3KbDpZam1QcrMS/W0AAAAAAAAhi3CXQAAYFBZxZQ335L+caujxa8mXpaTI514grTgBCk/nw+uAQCpk5PtU06FNL6i52PCYUd1dVJNNPBVK9W2B8EsBOaOOqm+jxCYiR6/3utc1q7rlayq5dgxjhsAs8CXLYsKvSCYu8+2o6NQysri39O9FVz1SGydql3APvD5FJ5ytPwrH5Qv3KbA+hcU3v+MVM8KAAAAAABg2CLcBQAABi3U9dIi6eZbHL29PPGyMQXSySdLxx8rZWfzITQAYHgIBHwqLJQ7emMhMAt41cQFvmLhr/btuvZlW1vv57KQmFtFrEZ6r48gmMnLc9yQl4W9bJ6x8FehT4XxYbBCqaBA8nfX13KUSmjJOP3ElM4FGO5CU45VxsoH3fXgu48R7gIAAAAAANgHhLsAAEBS2QfaTz3jVepauzbxMms5depC6aj51oqRD5MBACM3BGbtFG30FYRuaWkPe7UHwGwZrQ5mAbHotrWE7CsIZhoavLF5S5db6zpPvwXAnI7QVywU1qkqWPv+kVwVzFe9XoEdXho9XDJTzpgJqZ4SMKxFxh8iJ2uMfC21Cq57Ri1tTVJGTqqnBQAAAAAAMCwR7gIAAEkRCjl67HHp77c42rw58TJrcXXaqdLhh3kfeAMAAOtc5lN2tlWxlMaV9R0Ea27pCHtZ8CsaCotux5b1UlNT37cfjki7q7yRmMfuvipYbm5HVTB3aW0i3epgHVXB3EBYsVSQ792/4SJjxQOx9dB0WjIC+8wfVGjqccpY/Yh8bY0KvPcc1bsAAAAAAAD2EuEuAACwT1pbHT30iHTLrY62bU+8bOpU6fRTpbkH0vYJAIB9YUGpnGy5o68gmGkLea0h69urfsVCYA1x++zy9svC4b7P2djojS1bO1/SNQyWkWHBL8erAGYhsCKvgmdxsc/d9ta9ZW5uioNgjqPgivu9VfkUnkG4C0iG0PQT3HCXyVj1MOEuAAAAAACAvUS4CwAA7JXmZkf3Pyjdepujyl2Jl82aKZ1xurccTlU7AAAYKTKCPq+6VmHfx7pVwZo7hcA6hb/c9falBbz6Yi0kd1Z6o9OtdTk2K8uCXk4s8GWjtMSn0hKppESxZWHh4ITF/dvekr9mo7semXConLzSpN8GMBpFKg6Rkz1WvuYaBd57VmptkDLzUj0tAAAAAACAYYdwFwAAGJCGRkf33Ovon3c4qq5OvGzObOmM06QZMwh0AQAwrKqC5cgd/akKZq2YGxoSw2DREWsVGdcm0um+y2NMS4u0bZs3OnS9UiBgbR8dL/BV6lX9KivzuetlNsq8Zf4AW0JmvPPvjvu238J+Xw9AH/wBhaYer4xVD8kXalZw3TMKzf5QqmcFAAAAAAAw7BDuAgAA/VJbG9EttzXr7/+IqLY28bKDD/JCXVOmEOoCAGCkCwZ9GjtW7uhLJNIeBIsLf7kBsNr29dqO/XZcb6x1pFULdSuGruo5BJadbeEvxwt8tYe+xpX5NG6cYqNwbHsALNSq4CqvbZwTzFJo6nF785AA6EFo+oluuMsEVz1MuAsAAAAAAGAvEO4CAAC9qq11dMddju66e4/q6zs+QLXPQw87VDr9NGniBEJdAACgK2ujWFAgd/SnIlg06FVT4wW/bNREl+376vqoBmYtJjdv9kaHxCtkZlrgy9H7pz6jr5bWuPs2Zx6nje/kuG0gLRSWlb239xpAVKR8riI5RfI3VSuw/jmpaY+U049+sQAAAAAAAIgh3AUAALpVvcfR7Xc4+tc9UlNTx36/XzpynnTaqVJ5OaEuAACQvIpgRUVyR2/CYcdt92hhrz013jJ+Pbq0kFdPWlulzVukuRM6WjLe+OLJevP+jhBYQb7X/tFt91gilZT63NBXafvIy/PC7gB64Q8oPOMk+ZffI1+4TcFVDyl02DmpnhUAAAAAAMCwQrgLAAAkqKpydNvtju75d+KHooGAdPxxGTppQcitaAEAAJAKgUBHW8gpvRzX0uK4Qa89ezpGdbUF2L11X2OlTih/1j12d3OJllQflnB9qxBm47313Vf/ysuRysZF2z5au8f21o8W/irzqoMBkNpmnqqM5fe46xnv/JtwFwAAAAAAwAAR7gIAAK5duxzdcpujf9/vVbOID3Ude4z00f/IV2mJX/X19XJ664UEAACQBrKyfCofJ3d0Z9KG+xVcF3bXtxct1AfOCKimvSWkO9rbQfb0sqehSWrYIK3fEN2TeKBVIPNCX1JFuU/l5d5cKsqlvHyqfmH0cIqnK1w8Q4GqdQpsXypf1To5xTNSPS0AAAAAAIBhg3AXAACj3I6djm651dEDD0qtbR37g0HpuGOlhadIxUV+5ef7UzlNAAC6deH5UsjL58QEA6maDYYNx1HF9rtjm+H9z9C8bF+3LSCtepdV+ooPfbntH6vlhsEike5vwq0SVi2tWu3eYJeqX27YKza88JcFvwoLCX71pHnhD+WLhBJ3+jOUlaoJod9CM09VYPH17nrG8nvVesJlqZ4SAAAAAADAsEG4CwCAUWrrNkc33+Lo4UekUNxnZBkZ1n5RWniytTvik0UAQHorKODfKgzcmJo3ldv4nrteW3CIWrLH99gCsnCs3NEdN/xV19Hq0R01XqirZo9U39hz1a91673h6Qh/ZWdL4yu8oFeFLSt87raN/AKNbjmFnWJykk88BwwHoRkLlPnqjfI5EQVX3K/W478u+UniAgAAAAAA9AfhLgAARplNmx3d/A9Hjz4mheMqTWRmSie8TzrlJD4oBwAAI1t81a5dZaft9Xnc8FehV22rO62tjhv4qrIqXnuk6iov+GXbNT20fGxult5b7w1Px0H5+V7oa/x4C3v5NHGCt25Vv+y1HJC2cooUnnSkgpsWy1+/XYENLyk8/YRUzwoAAAAAAGBYINwFAMAosX6Do7/f7OiJpxLbB2VlSQtOkE5aYB8YEuoCAAAjWyBUr7KdD7vroUCuqouPH7Tbysz0adw4uaOzUMhx2zta6KsqLvS1u8pr+9hdu8f6emmNjbWJoS9r41hW6gW9Jljwa7yvfSkVFdHmEekhNOt0N9xlMpbeTrgLAAAAAACgnwh3AQAwwq1d5+immx09/UxidYicHOmkE6UFJ0q5uXziBwAARodxO+5XINzkrleVnKxIIDsl8wgGfSopkTu0X9fgl7V3tNBXbFj4y4JftV3PZa/xdlZ6Y8lSd0/Caz4Lek2YYMuOal9WASyYMfj3E4gKTz5akdwS+Rt3K7DuGfnqdsgpKE/1tAAAAAAAANIe4S4AAEao1e86+tvfHT33fOL+3Fyv9aK1YMzJIdQFAABGEcfR+C23xzZ3ln9Q6ciCX6UlckdnbW2OV+Frt7Rrtxf4iq63tnY9vqnJwv7eiA99BfzSuHJpolX4igt+2cjNG9z7h1HKH1Bo/zOU+dat8jlhBd++S23HfiXVswIAAAAAAEh7hLsAABhh3l7utV986eXE/QX50iknS+873loxEuoCAACjz5iaN5XfsNpdr8ufo6bc6RpuMjJ8Kh8nd8RzHMdt22htHass7NUe+tq9S9pTm1jB1YQj0rZt3tAb7hlilxUVShMnehW/Jk70Ql9W+auwkBaP2DehWWcoY8k/5XMiylh2l9qO/pLk5+1JAAAAAACA3vDuCQAAI4B9mPfmW3LbL77ufjjXYcwYaeEp0vHHSpmZfBoHAABGr/FbO6p2VY5Lz6pde8vn86mgQO6YNrX7al+7dnVU+XKrfu2W2kJdz1W9xxtvL08MfeVZi0cLfU2QJk30tYe/pLJStygT0Ccnv0zhSfMV3PSK/PXbFXjvOYX3OyXV0wIAAAAAAEhrhLsAABjmoa6XX/FCXd6Hb0qouLBwoXTs0V6FBwAAgNEs2FqtsspH3fVQsEBVJe/TaNFTta9IxFFtnRf6iga/KtuXjU1dz9PQJL27xhvxoa/MDKnCgl7R0Fd7e8eKcikjc/DvH4aX0AEfcMNdJuPNfxDuAgAAAAAA6APhLgAAhiH7IO75F7xQ1+p3Ey+zygmnnirNP0IKBgl1AQBGtt/81tH6DYn7rGrRZf/Fv4FIVLHtX/JHWt31XaUL5fizNNr5/T4VjpU7Zu6XeFlDo+MFviz4FVftq6am63la26SNG70RH/ry+6VxZV7QywJfEya0t3gcL+XlD3y+2Q9cpkDlyoR94bLZ0jl/HvjJkDLhiUcoUjBe/rptCm5cJH/lakXK9k/1tAAAAAAAANIW4S4AAIaRUMjRU09Lf7/F0fr1iZeNr5BOO1U6/DApEOADbQAAgJhISBO23OauOvJpZ/mHUz2jtJeX61PeFGnqlMT9ra2OG/Jy2zu2V/xyWzxW2xcQEo+17e07vPH6m4nBr6Kx0vj2Cl8W+hpvlb/GSyUlks8/NPcRKeIPqO3AjyrrlT+6mxlv3KSWM36S6lkBAAAAAACkLcJdAAAMAy0tjh5+RLr1dkdbtyZeNnmSdPpp0sEHedUXAAAAkKhk99PKbtnmrtcUHqmW7AmpntKwlZnpcytv2ej8JQQLeEVDX7urvBaPVbu9yl6dVdd4450VnVo8ZnpfWrDzW+DLDX61b2cP/t3DEAnNOk2Zb94sX2uDgisfUOsJl8nJLUn1tAAAAAAAANIS4S4AANJYfb2je++T7rjT+7As3ozpXqhrzmzJ5yPUBQAA0JOJm/8RW99R/tGUzmWksnbg1oLRRud24rV1caGv9vaO1u6xvrHreVpbpQ0bveHpCH795mhpZqd2jm2tkj/kKIN25MNLRo7a9n+/Mt/+l3zhVgWX/FNtx34l1bMCAAAAAABIS4S7AABIQ1VVju78l6O775UaGhIvm32A135x5n6EugAAAPqSV79KhXteddebsierduzhqZ7SqGKVZQvHyh37zUi8rLHRcSt8RQNfVVXesrqbFo8mFO66b/1G6b8/WaPycguXOW6Vr4oKnyrKpfJyqbRECvDuV1oKzfmIMpbfI58TUeZbt6jtyC9IGbmpnhYAAAAAAEDa4e0tAADSyNZtjm673dGDD3lVC6Isw3XoIdKpC6Upkwl0AQAA9NeEuKpdO8s/7L2wQlrIzfUpN9drMx4vHHZUvccLfbnDAmC7LCjW/XnCYWnrVq99+VtLEqt9BQJSWak0bpzaA18+N/Rl62VlXhtIpIaTP07h6ScouO5Z+ZqqlbHsTrXNOy/V0wIAAAAAAEg7hLsAAEgDa9c5uuVWR08+JYXjqhTYh1FHzZcWnmwfSPFBJAAAwEBktFSqfPt97nookKddZQtTPSX0QyDgcytu2Yg3Ybn1LU/cl5sjTZjg065dTsKXI+KDX9t3eGPpssTgl+X8igq9VpJl49qXpT43CGbBr+IiyR8YpDsJV+shn3LDXSbj1b+o7ZDPSEESdwAAAAAAAPEIdwEAkCKO4+i11+VW6lrsdQqKsQoC7ztOOmmBVFhIqAsAAGBvTNhym/xOm7teOe4DigRo+TbSFBdLl74/z31tvXNno3btdtz2jtbasapabgUwW+8u+OU43jE2Vq6O7U34ooUFzCzoZcGv0lKfG/gqLZVKSrzbpvLXvnGKpik05VgFNy6Sv2Gngu/co9Ahn0r1tAAAAAAAANIK4S4AAIZYKORV6LJQ15q1iZfl5UkLTpROON7WCXUBAADsLX+40Q13mYgvoB0V/5HqKWEQ+Xw+FRRI+fk+TZuaeJkFvxoavZBXdLjBr2ppzx65l3XHqn7t2OmN9jN1OaZwrBf0smFBsJISn4qKvIpgFv6yZQYBsF61HfopN9xlMhffoNDcj0mBjFRPCwAAAAAAIG0Q7gIAYIjU1zu67wHprn852lmZeFlJsVel65ijpawsQl0AAAD7qnz7v5URqnHXq0oWqC2zNNVTQgqDX/l5csfkSV0vb211tKfGC3vV1HiBL1ta1S/b39LS87ntchtr1/UcACvIl4rag15W+csNfxX53GBYYaE0dow0tnD0VgGLlO6v0MQjFNzyuvy1WxRcbtW7zk71tAAAAAAAANIG4S4AAAbZjp2O7rzLC3Y1dqoKMGWKtPBk6ZCDre0LoS4AAICkiIQ0adPfYpvbKz6W0ukgvWVm+ty2izY6s6pfTU1STa1UW+uFvmxZW+et2/76eq/FY0/q6r2xcWPCmbscl5PTHvSy0NdYaYy79GnMGC8gZpXJvOpk3nZwBBW3ajvsHDfcZTJfvk6hOf8hZWSneloAAAAAAABpgXAXAACDZOVKR3fc5ejJp72WLvEOOkhaeJI0Y4ZXSQAAAADJU1b5mHKaNrnrNWMOU1PejFRPCcOUvVbPzZU7xld0f0w47Ljhrdq4sJeFv+rqpPq6jnBX578JOrMQmY3tO+L39pwaszBYNPRlga8xBV6bd5urtXj3llKeLdvXbZ9dz+dXWomMm6PQ5KMV3PSK/PU7lLHkNrUd+YVUTwsAAAAAACAtEO4CACCJQiFHzzwr3XW3o7eXJ14WDEpHz5dOOkkqH0egCwAAYFA4jiZvuD62uW0C7d0wuKwCr9ticWzPx0QijpqavbBXNPjV0CDVN3jL+NHcSxvI7sJgnVu+9xUK8/ulnCwp24Je2V7YK7rMTlj63GV2lrWOjxuZUlZ2+9K2s6WMDAvCaZ+0zvucApsWyydHmYuvV9vBn5Sy8vftpAAAAAAAACMA4S4AAJKgeo+j++6X7vm3o127Ei+zb8if8D7phOPtW/WEugAAAAZT8e5nld+w2l2vz5+tujGHpnpKgPx+X6yCVnl578e2hZzEwFej1NzkLS3M1WihrsaOpYXGemsL2VkkIjXY+Zr6OrL/J7VgV2amF/LKzGhfZravZybus2374ktGsH2ZYUufgsHpOj77JE1tflq+5j3adMeftXrSpe5x3jGJy+j1g3HrAVsGOo6jSjIAAAAAABgJCHcBALAPVr/r6K5/OXriSam1LfGyCeOlE0+UjpxnH2LwoQIAAMCgcxxN2fCn2ObWCZ/a93JCwBDLCPZdCaxzVbDmZi/sZcvoaGnxgl+x9SapxbZbvG0bra1d/47ZGxYui55zL8/g/vfp7M/qumOfV4Y/pOnb/6rLbv24tjVN2Ot5BfyOG/5yQ2ABLwgWHyyLDguDBeJCYQkBsm6XPu/y9n0ZnYJtCYG26Hb7yIous7yqbwAAAAAAAH0h3AUAwF60Xnz+Ba/14pKliZfZZ4cHHyQtOFGauR/fFAcAABhKhXte0ZjaJe56Y8401RTOT/WUgCGpCpabK3fsDQuHWcirxYJetmyR2tq33fWQ1Nbm7bMgWFunEd0XtmVICoWlUJv93eRtD6Sq2I7m8Xpg00d01tR7lB1o0aVzfqP/fuNXe3fHJIUjUnifQmc9GcCd6kUg4Lghr2jYKxr8snaYtm0tMm3ptsls35ed3d4us33kWlvNHO/n77bYjG7neOfib1IAAAAAAIY/wl0AAPTTjp2OHnjQ0f0PqkvrRXvz/NhjvPaLJcW8eQ4AADDkHEdT110b29w24WzJ50/plIDhEg6LBoWSzXEchS3sZSPUMdx97ctweyAsuq8u9Gk1NT+pHNXqA5Me1qbxn9V74cO9Yzsdn7De17CgV/S2O102kABaMtltN1qLzcaBXKv/kw347W9Vx/17NS+vY1gQzJb5sfX2tqH53r58W+ZLBQXedkYGf+MCAAAAAJBKhLsAAOhFOOxo8avSv+939NIi+1Z74uXl5dKCE6T5R9q3qHnDGwAAIFWKql7U2No33fWmnCmqKjkh1VMCRj2rGhVtc6is/l6rQDt2fE7T1v+vu/WZwqv15hH/lHyBQZunVS+Lhr4i0eBZpOcgWXxALSG41l6xrMv+9upn0WXCiF4WVwnNzp0Mdh/qG7xR2ekLSgMJjGVnOx2Br/Zh62PGeAGwMWN8GlMQvy1329ZpPQkAAAAAwL4j3AUAQDd273b04MPSffc72r4j8TLranHQXOnE90n770+bCwAAgLSo2vVeR9WuLRM/O6hBEACDq3LcGRq34wHlNq1XQd1yjd96p7ZN/PSgVi/z+61CldLmS0axlpftLTKjbTFbW9qXca0zbZ8tm229fV9su33Z3OxdtjfsujY6V7DuTzgsP8/R2LHqMgrH+twQWGH7tq0XFXpLAmEAAAAAACQi3AUAQNy3td9406vS9dzzXb8tbW84H3eMdMwx9qYzbzYDAACki+Ldz2hM3TJ3vTF3uqqLj0/1lADsC19AG6ZdojkrvuNuTl93jXaVnaq2zFKNBhZuCgSS3yrT/uaNBr3c0dQR/LLR1L6vqUlqbF82ddoeaEAsWjlsy9b+BcLsu1NjChwVFsodFviKrhcW+twwWFGRt9+WhMEAAAAAAKMB4S4AwKi3Y6ejRx6VHn7E0eYtXd9YnjNbOv446cA5vGkMAEC6mXe4NG1a4r7iolTNBikRCbnBj8SqXf6UTgmDo6rkRNXnz07Y15o1LmXzweCqH3OQdpWeqtJdTygYqtOMNb/SqgN/luppDWtWoSw3R+7YW6GQ44bAGhu7jobuths69veH40g1td7YsLHLpd3cJ/silhMLe3UEv3zesth7XVDcfllWFn/TAwAAAACGH8JdAIBRqaXF0bPPe4Gu11733kCOV1AgHXu0dOyxUkkxb/4CAJCuTlrAv9OjXcX2e5TXsMZdr8/bX3uKjk31lDBIdlSc2WWffRkjNyWzwVDYNOV8FVa/rGC4XuU77tOOio9qTzH/j6dSMOhTQb7cMdBWk1b9q8HCXvVe4Ks+ut5e3ctd1nujrr5/VcIiEam62ht6r+/KYHl5jhvyigW+3PCXT8XREFixvQdAEAwAAAAAkF4IdwEARg3HcbT8HemhRxw9+ZT3xnFn+8/yqnQdfJD3pjUAAADSVyDUoGnv/T62vWnqhV7aB8CIEMoYq82TP69p6//X3Z616kd6/ah7FQnsQ+kppIRVwY6Fwsr7d53WVsdr61gfN2y7zgt/RUNgdbZdZ1XF+j6nGy5rkDZv7jsIlm9BsPawV0f4yxcLgUX3WRAsI4N/ewAAAAAAg4dwFwBgxKusdPTIY16Vro2bul5eUiIdfZR01JHeG7UAAAAYHiZt/IsyW3e761VFx6m+YG6qpwQgySrHvV8lu59WQd1y5TRv0tT3/lfvzfx2qqeFIZCZ6VNxZv/aLduXuVpaOsJebvCrTqptD37FRvv+5ua+z+kGyRqkTZv6DoKNHdMRBLOwl7f0JW4XS4Vj+SIZAAAAAGDgCHcBAEak2lpHzzwnPfmUozff8lo1xMvMlA4/zAt17TfDCjzw5ioAAMBwkt20UZM2/cVdj/iC2jzli6meEoDB4PNr/fSva+6yr8jvtGnSpptUOe4Dqh9zUKpnhjRif9NnZ8sdZaX9qwoWX/UrOiwMVlubuG2hsb7U1Hpj/freg2D21sPYsU5H9a/41pDtVcCi+wsLCYIBAAAAADyEuwAAI0Zjo6MXXpSeeNLRK69K4XDXY2bOlI6eLx12qJSVxZukAAAAw5LjaNaqKxWIeJ+47yz/iFqyJ6R6VgAGSXPOJG2deI4mbb5JPkV0wMrv6Y0j75Ljz0z11DCMq4JZNS0b/QqC9RD8ii1rvWVbW+/nchxpzx5vrHsv4ZJeK4LFgl/u0qeiQm/bAmDR/Tk5vMcBAAAAACMV4S4AwLDW0uLo5cVeoOulRd1/o7a0VDpynnTUfFvnzU4AAIDhbtyOB1RU/ZK73pJZpi2T/jPVUwIwyLaP/7iKqp5XXuM65TWscdszrt/vslRPC6MlCFYid/SnNWR82MutDlbbtUWkrYdCyasIZrKzHTf0VWgBMFtGx1hfRxBsbMf+7GzeHwEAAACA4YJwFwBgWAa6Xn9DevoZR8+9IDU0dD1m7Fhp3uHSEYdLkyfTdhEAAGCkCLbt0Yw1P49tb5h2iSKBnJTOCcDgc/xBvbffN3Xg21+X3wlp8sa/aHfpQtWNPTTVUwO6tIYcV9Z3EKy5OTHwldAeslPLyL4qghk737bt3uh0a90en5PtuCEve//ERqEtC32qKG9UUaFfmVmOWzksellBAW0iAQAAACBVCHcBAIaF+npHL70sPf+Co5dfkZqauh6TlycdfpgX6poxXfL7edMRAABgRHEc7b/y+8psq3I3q4qOV03R0ameFYAh0pQ7XVsnfrajPeOK77rtGSPBvFRPDRhwECwnx1opSuXj+g6CtbZ6QbD6uNCXux7drpfq25eNjV77x740NUtNXcJgdsVu3nBpl5fnaMwYaxcpbzlWGlMQXfe5y+i2LS0Qlp8vBQK8PwMAAAAA+4JwFwAgbe3a5ej5F71A1xtvdt+ywL4Re+ghXqBr/1m8YQgAwGjzzLOOqqoT9xUXSSct4DXBSDRhyy0q3fW0u94WHKON0y5O9ZQwhMq336vMlp0J+1qzxql+v8+mbE4YetsmfEKF1S8rv2GVcps2aOaaq7V69lWpnhYwqEGwrCypzEZp38eHw44aGr2wV32DFwKLDjcEVp+4v79hMGOV021s29bdpT2fJD/PUcEYL+wVDX2NaQ9+5ef7VJDfEQSzYdvRdWuLCQAAAACjHeEuAEDasG+jbthoYS4v0PXOiu6PswpdB82VDj5ImjNbysjgjT4AAEYrC4Cv35C4b9pUC3elakYYLHl172jGml/Gtt+bcZnaMktSOicMreLdzym/fmXCvvr82YS7RhtfQOtmfltzl31VgUizKrbdrari47Vr3AdSPTMgLdiX3tzqWQX9Oz4Scdzq6Bb4amzwKRTOdqun797dovoGxw1zWQjMAmONDe3LAQTCjBsm24tQmMnMdJSfJ+VZ2CtPys31Ql/23pC73x2+2Lpd7i5zpNz2bVunpSQAAACA4YxwFwAgpRobHb3+hvTKYkevLO7cDiCxAsfBB0uHHOy1XKRCFwAAwOiR1bxNBy37ivxOm7u9veJM1RQdleppAUiRluwJ2jDtEs1Y9xt3e/9VP1J9wUFqzpmc6qkBw47f72sPSHlVwvLzM9z99fWtPQa4ooEwC3pZ+Csa+ooGvxJGk9TUfpldJxIZ2PysJWWVjU6VWhP1nTTLynKUZ0GvuGFtMS34FW2R6W7n+rrst6rx0WVu+9IGgTEAAAAAQ4VwFwBgyKtzrVlrYS4v0LV0mbUM6P7YCeO9MJeFuiZN9N5kBAAAwOgSaKvVQUu/pKyWHe52fd7+2jz5C6meFoAU2126UGNrXlfJ7mcVDNXpwLcv1VvzblUkkJPqqQGjKhCmsoG9J9Tc0hH2am72AmAW+oofjZ3W7bhmW7YMrGJYvJYWb/QeEnNn2e9zZmQ4seBXTraUZaGvrI7wl63H9lkoLMvn7s/K9PZbu013vf060fVM285qX8/kC44AAAAACHcBAIZA9R5Hb0Src70q7d7d/XGBgLTfDOnAOV6gq6yUN68AAAA02oNdyy5RXsMad7s5a7zePeBHcvxeVREAo5jPp/XTvqbchjXKad6i/PpVmrXqf7Rqzs/dywCkH/vSnoWgbBQXD/z6VjGspbUj7NVky/ZhQTB33UJc7cvO2/H7B1pBrDttbd6oq+vvNfYumRYMOrGgVywA1r6M35/Z7fAlHJOR0dNxHZdlxW3b4MuWAAAAQOoR7gIADEqY6623pDffcvTmW9J763s+tqTEC3PNmS3NmmlvSvGGEQAAAKTMlh06eMlFymt4191uC47R6tk/ViijMNVTA5AmIsFcrZl1hQ5c/g0FIk0q3/GAGvJna/OUL6Z6agAGqWJYNBymfXg5YBXEQmEv7GVhsWhVr87DgmDWFtIdtq99vSV+f/T6rV7QKxmhsc5CIW9YC8y9uLf7fPuZGU5HACwaBosLicUCYxndH5OR4et6nfhgWUbP4bLoMbTABAAAwGhHuGsY2bNnj9544w1t375d9fX1GjdunCZNmqR58+bJ7/enenoARrHqakdvLelfmMvemLEQVzTQVVbGmzMAAABINKbmTc1e/k1lt2xPCHa1ZE9I9dQApJnm3Cl6b79vaOa7P3W3Z6z9lVozy7Sz4iOpnhqANGWVqDKCUka+lJ/kc4fDXnWxtmj4q81bWvArGgZz163qV/t69LLYelvX9VDcvraQtwyHNSTc+9Amaa/CZckJmAX8TtdQWGbXqmXdVTDzKpf5uq121rkKWnRf/HFULgMAAEA6INw1DKxfv16//vWv9fTTT6vN/mrrxEJen/rUp3TRRRcp0/7aAIBBZCXwN2+Wlr9jw9GSpb2Huez9j8mTpZn7SbMP8Nou2jf2AAAAgM58kVZNWf9HTdlwvXzySl80Z1W0B7smpnp6ANJUdfH7tHnSf2rS5n+42/uv/L7aMopUXfK+VE8NwCgTCPiUmyPJxhC8Rxcf+Ar1sHTDYfHL+GM6rSccG/Yui79ObL19OPue2+qXcMRrw2lj7+z9RLOynMTgV7a3np0tZUe3szrWbZmd7bXDjO7Pzonu77he/D5CZAAAAOgL4a40d9999+l//ud/1NjY2OMxO3fu1LXXXqunnnrKXU6cyBveAJKnts7RihUdYa53Vkh1dT0fb4UEJ0+SZs70KnRNn27l8nlzAgAAAL1wIirb+Yimrfudcpo3xXbX5c/RmlnfVyizOKXTA5D+tk34jDJbqzRu50PyOyHNffuremfuNaoqPTnVUwOAQWtTGQ0QpYK1t7TqYZ0DX92FwEKdwmPRdTsmHHds58t7CqVFQ222fzBaYcaLtukczDCZ5bqysxwv8NXeetRdtm/H9uVEL/O5l1mQMHpcdMS225fWRYHgGAAAwPBHuCuNPffcc/rud7+rcFx95WnTpunoo49WYWGhNm7c6Fbzam72vq6yfPlyXXzxxbrtttuUn5/sgtIARoPmZkdr10nvviu9s8JxA10bNvZ+HTfM1V6ZizAXAAAABsIfalD5jvs1YcutymtYE9sf8QW0deJntW3CJyVfIKVzBDBM+HzaMO3LCrbVqLj6RfkjrZr79qVaNfsn2lnxH6meHQCMOBYYCgbljuwUzsNaYUYDYdY+srvKZfEjelxP7S47t8ns3CozOpLJKqANrDJZ/8NjgYCFvBw3CJabmxgEi47c2Lovdkx0X/y2rdsIBnnvFwAAYKgR7kpTlZWVuuyyy2LBLvtD6fLLL9d5550nvyUp2lVVVenrX/+6Fi9e7G6vXr3arfRlbRwBoDc1NY7eXSOtfld6d423vnFj3992K8iXpk6Tpk+1wKk0ZbJ9Q5A/6AEAANA//nCjiqoWuZW6SnY/pUC4KeHy2jGHatOUC9SYt1/K5ghgmPIFtG7m5XLW/UYlu5+Rzwlr9orvKr9+hd6b8Q05/sxUzxAAMAitMC3AZBXM8oboNq0lphsSa+0IfrmBsE7b7rotoyO6v7t9LR3rViksWQEy+4ipvt4byQqNZWQ4CeGv6IgPgXmXeWGx+GBY7Dpx+zIyeG8ZAACgL4S70tQf//hH1cX1Pfva176mL3zhC12OKy4u1o033qizzjpLa9eudfc9+OCDuvDCCzV79uwhnTOA9NTW5mjTZmn9Bum99zoCXTt39n1de2Nk0kRpWnuQy5bFxZTyBgAAwAA4YeXXr1Rh9SsqqnpJY2tecyvqdFaXf6C2TvyMasfO83rTAMBecPxBrdvvWwoF8lS+80F336RNN2nMnje06sCfqSl3eqqnCAAYAS0xMzPljsEMkFnAqyUa/LLQV1wozAJg3S477YteP7rfhlUK2xc2rxobtckLi3WuDtYlFOZu+7oc0zVQRlgMAACMTIS70tDu3bt1xx13xLanTJmiiy66qMfjs7KydMUVV+jzn/98rNf9ddddp9///vdDMl8A6dNS0VoobrAQ1wbHXa5fL23ZIoX7qMYVDXKNr5AmTvQCXdZqcfIk/hgGAADA3oS5Vmls9Ssq3POaxtS8roxQ95/8hAL5qio5QTvHfVBNVOoCkCw+vzZOu0TNOVM0eeMN8jshjalbpiMWf1RbJn1OG6ddrHAwP9WzBACg1wCZVSOzoYLkndc+P4oPjVnYq7mlIxDW3NweBOu0dPe3HxcLijV7193XKmPRVpe1SQyLdWkr2XkZ14Yyt9dWlVJ2Nq0oAQBA6hHuSkNPPvmkWu1VdLuzzz5bGRkZvV7n2GOP1fTp0/Xee++5288++6yampqUY688AYwYLS2Otm7zAltbttrScZcbN0nbt/f/W1f2poAFuNwxyQt0VZTzRyoAAAD2TlbTFhVXvaDC6pfcCl09hblMS2aZagqP1J6iY1Q75jA5/t7/3gWAveLzaWfFR1RfMFv7vXu1slu2uyGvyZv+ooptd2nbhE9p66T/VGtWWapnCgDAkLGODLGqY/nJqzIWHxKLjmggzN0fv97TMe0jGWGxZFYWM5mZHYExC3t1DoO5o31/dravfd1RSUmLGyILhx1lZ9voONbW7edAlwwAANAfhLvS0FNPPZWw/f73v79f17Pj/vCHP7jrzc3NevHFF3XqqacOyhwBDA77I2/3bmlnpRfWsiDX5i2OtrpBLqly18DOZ7nQceO84JY7KqQJE6SSYu/bXwAAAMBecRwV1C1TSeUTKtn9jPIa1vR4aFtwjOoKDlLdmENVO/ZQNWdPpu0igCHTmDdLyw++ThXb7tT4rXfJ77S5AdQpG29wg17VRcdqZ/mHVVVyokIZhameLgAAw469zxwNOCXrPfJo1bCewmCx7Z4uj2tDGVdLYa9F22HuqenP0fGhsfpej7Q/i7KzHGVbKCzLC3zFD/uStgXBsmy7vZKbhce8Zfs+uzyz43hbz4pfz/I+JyBEBgDA8Ea4Kw299tprsfXS0lJNtt5o/XD44YcnbL/66quEu4A0Yt9gsm8L7dol7dgp7dwp7djhuEGuHTu8fbsq+9dCsTP7Ay0a3rJleXuYq5gQFwAAAJIZ6KpdqrKdj6i08lG3Ck53QsEC1RYcoroxh6h2zCFqzrEwl3/IpwsAUZFAtrZOOle7S0/V+K3/VMmup90qXj4n7FYdtOHI5wZRawvnqa7gYNU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" ] }, "metadata": { "image/png": { "height": 811, "width": 1211 } }, "output_type": "display_data" } ], "source": [ "# First, sample from the prior\n", "prior_preds = mmm.sample_prior_predictive(X, random_seed=rng)\n", "\n", "# Plot prior vs posterior for adstock parameter\n", "fig = mmm.plot_prior_vs_posterior(\n", " var_name=\"adstock_alpha\",\n", " alphabetical_sort=True, # Sort channels alphabetically\n", ")\n", "\n", "# Plot prior vs posterior for saturation parameter\n", "fig = mmm.plot_prior_vs_posterior(\n", " var_name=\"saturation_beta\",\n", " alphabetical_sort=False, # Sort by difference between prior and posterior means\n", ");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These visualizations help us understand:\n", "\n", "1. How much we learned from the data (difference between prior and posterior)\n", "2. The uncertainty in our parameter estimates (width of the distributions)\n", "3. Whether our priors were reasonable (by comparing prior and posterior ranges)\n", "\n", "The `plot_prior_vs_posterior` method allows us to sort channels either alphabetically or by the magnitude of change from prior to posterior, helping identify which channels had the strongest updates from the data." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusion\n", "\n", "In this notebook, we've demonstrated how to:\n", "\n", "1. Calculate various evaluation metrics for your MMM including normalized versions (NRMSE, NMAE), as both summaries and distributions\n", "2. Visualize metric distributions for a chosen evaluation metric\n", "3. Compare prior vs posterior distributions for different metrics\n", "\n", "These tools help us understand model performance and uncertainty in our predictions, which is crucial for making informed marketing decisions." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Last updated: Tue Jan 14 2025\n", "\n", "Python implementation: CPython\n", "Python version : 3.12.8\n", "IPython version : 8.31.0\n", "\n", "pymc_marketing: 0.10.0\n", "pytensor : 2.26.4\n", "\n", "arviz : 0.20.0\n", "pymc_marketing: 0.10.0\n", "matplotlib : 3.10.0\n", "sklearn : 1.6.0\n", "numpy : 1.26.4\n", "pandas : 2.2.3\n", "\n", "Watermark: 2.5.0\n", "\n" ] } ], "source": [ "%load_ext watermark\n", "%watermark -n -u -v -iv -w -p pymc_marketing,pytensor" ] } ], "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": "3.12.8" } }, "nbformat": 4, "nbformat_minor": 2 }