{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Dancing statistics\n", "\n", "[Dataset download](https://s3.amazonaws.com/bebi103.caltech.edu/data/mean_rest_bouts.csv)\n", "\n", "This lesson was inspired by [Geoff Cumming](https://scholars.latrobe.edu.au/gdcumming).\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "nbsphinx": "hidden", "tags": [] }, "outputs": [], "source": [ "#| code-fold: true\n", "\n", "# Colab setup ------------------\n", "import os, sys, subprocess\n", "if \"google.colab\" in sys.modules:\n", " cmd = \"pip install --upgrade polars iqplot bebi103 watermark\"\n", " process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n", " stdout, stderr = process.communicate()\n", " data_path = \"https://s3.amazonaws.com/bebi103.caltech.edu/data/\"\n", "else:\n", " data_path = \"../data/\"\n", "# ------------------------------" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", "
\n", " \n", " Loading BokehJS ...\n", "
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\\n\"+\n", " \"

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\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded(error = null) {\n const el = document.getElementById(\"bd78374c-7531-45de-841c-94400d0c204b\");\n if (el != null) {\n const html = (() => {\n if (typeof root.Bokeh === \"undefined\") {\n if (error == null) {\n return \"BokehJS is loading ...\";\n } else {\n return \"BokehJS failed to load.\";\n }\n } else {\n const prefix = `BokehJS ${root.Bokeh.version}`;\n if (error == null) {\n return `${prefix} successfully loaded.`;\n } else {\n return `${prefix} encountered errors while loading and may not function as expected.`;\n }\n }\n })();\n el.innerHTML = html;\n\n if (error != null) {\n const wrapper = document.createElement(\"div\");\n wrapper.style.overflow = \"auto\";\n wrapper.style.height = \"5em\";\n wrapper.style.resize = \"vertical\";\n const content = document.createElement(\"div\");\n content.style.fontFamily = \"monospace\";\n content.style.whiteSpace = \"pre-wrap\";\n content.style.backgroundColor = \"rgb(255, 221, 221)\";\n content.textContent = error.stack ?? 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\n", "\n", "In this fun exercise, we will investigate how **replicable** certain statistical conclusions are. What I mean by replicability is best understood be working through this notebook.\n", "\n", "For this lesson we will use the zebrafish embryo sleep data from the [Prober lab](http://www.proberlab.caltech.edu). A description of their work on the genetic regulation of sleep can be found on the [research page of the lab website](http://www.proberlab.caltech.edu/Research). In particular, the [movie](prober_fish.mp4) below comes from their experiments watching moving/sleeping larvae over time.\n", "\n", "
\n", "\n", "\n", " \n", "
\n", "\n", "The data we will use are processed from raw data published in [Gandhi et al., 2015](https://doi.org/10.1016/j.neuron.2015.02.016). In their experiment they were studying the effect of a deletion in the gene coding for arylalkylamine N-acetyltransferase (aanat), which is a key enzyme in the rhythmic production of melatonin. Melatonin is a hormone responsible for regulation of circadian rhythms. It is often taken as a drug to treat sleep disorders. The goal of this study is to investigate the effects of aanat deletion on sleep pattern in 5+ day old zebrafish larvae.\n", "\n", "Among other sleep properties, they measured the mean rest bout length on the sixth night, comparing wild type larvae to the homozygous mutant. A rest bout is defined as a period of time in which the fish does not move. The length of a rest bout is just the amount of time the fish is still. We are primarily interested in the *difference* in the mean bout lengths between the two genotypes. The processed data are found [here](https://s3.amazonaws.com/bebi103.caltech.edu/data/mean_rest_bouts.csv).\n", "\n", "Let's load the data." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# Load data\n", "df = pl.read_csv(os.path.join(data_path, 'mean_rest_bouts.csv'), comment_prefix='#')\n", "\n", "# Pull out wild type and mutant and drop NAs\n", "df = df.filter(pl.col('genotype').is_in(['wt', 'mut'])).drop_nulls()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's look at these data with an ECDF." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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Let's add 95% confidence intervals to the plot to see how the ECDFs might change if we did the experiment again." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1098" } }, "output_type": "display_data" } ], "source": [ "p = iqplot.ecdf(\n", " df,\n", " cats=\"genotype\",\n", " q=\"mean_rest_bout_length\",\n", " order=[\"wt\", \"mut\"],\n", " x_axis_label=\"mean rest bout length (min)\",\n", " conf_int=True,\n", ")\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These is strong overlap of the confidence intervals, so it may just be that the differences are due to the finite sample size. We will investigate further with some modeling." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Cohen's d\n", "\n", "Cohen's d is a commonly used measure of **effect size** in comparison of two data sets. It is the ratio of the difference of means compared to a pooled standard deviation.\n", "\n", "\\begin{align}\n", "d = \\frac{|\\bar{x} - \\bar{y}|}{\\sqrt{\\left.(n_x \\hat{\\sigma}_x^2 + n_y \\hat{\\sigma}_y^2) \\middle/ (n_x + n_y - 2)\\right.}}.\n", "\\end{align}\n", "\n", "Here, $\\bar{x}$ is the plug-in estimate for the mean of the data from sample $x$, $\\hat{\\sigma}_x^2$ is the plug-in estimate for the variance from sample $x$, and $n_x$ is the number of measurements in sample $x$. The values for sample $y$ are similarly defined.\n", "\n", "Roughly speaking, Cohen's d tells us how different the means of the data sets are compared to the variability in the data. A large Cohen's d means that the effect is large compared to the variability of the measurement." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Estimates of the difference of means and Cohen's d\n", "\n", "First, we will compute nonparametric estimates from the data. We will estimate the difference in the mean bout length and Cohen's d. For speed, we save the two data sets as NumPy arrays." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "wt = df.filter(pl.col('genotype') == 'wt')['mean_rest_bout_length'].to_numpy()\n", "mut = df.filter(pl.col('genotype') == 'mut')['mean_rest_bout_length'].to_numpy()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we'll write some functions to conveniently generate bootstrap replicates and do our hypothesis tests. These borrow heavily from the lessons on hacker stats." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "@numba.jit(nopython=True)\n", "def cohen_d(x, y, return_abs=False):\n", " \"\"\"Cohen's d for two data sets.\"\"\"\n", " diff = x.mean() - y.mean()\n", " pooled_variance = (len(x) * np.var(x) + len(y) * np.var(y)) / (len(x) + len(y) - 2)\n", "\n", " if return_abs:\n", " return np.abs(diff) / np.sqrt(pooled_variance)\n", " return diff / np.sqrt(pooled_variance)\n", "\n", "\n", "@numba.jit(nopython=True)\n", "def t_stat(x, y):\n", " \"\"\"Welch's t-statistic.\"\"\"\n", " return (np.mean(x) - np.mean(y)) / np.sqrt(\n", " np.var(x) / (len(x) - 1) + np.var(y) / (len(y) - 1)\n", " )\n", "\n", "\n", "@numba.jit(nopython=True)\n", "def draw_perm_sample(x, y):\n", " \"\"\"Generate a permutation sample.\"\"\"\n", " concat_data = np.concatenate((x, y))\n", " np.random.shuffle(concat_data)\n", " return concat_data[: len(x)], concat_data[len(x) :]\n", "\n", "\n", "@numba.jit(nopython=True)\n", "def draw_bs_sample(data):\n", " \"\"\"Draw a single bootstrap sample.\"\"\"\n", " return np.random.choice(data, size=len(data))\n", "\n", "\n", "@numba.jit(nopython=True)\n", "def draw_perm_reps_t(x, y, size=10000):\n", " out = np.empty(size)\n", " for i in range(size):\n", " x_perm, y_perm = draw_perm_sample(x, y)\n", " out[i] = t_stat(x_perm, y_perm)\n", " return out\n", "\n", "\n", "@numba.jit(nopython=True)\n", "def draw_bs_reps_mean(data, size=10000):\n", " out = np.empty(size)\n", " for i in range(size):\n", " out[i] = np.mean(draw_bs_sample(data))\n", " return out\n", "\n", "\n", "@numba.jit(nopython=True)\n", "def draw_bs_reps_diff_mean(x, y, size=10000):\n", " out = np.empty(size)\n", " for i in range(size):\n", " out[i] = np.mean(draw_bs_sample(x)) - np.mean(draw_bs_sample(y))\n", " return out\n", "\n", "\n", "@numba.jit(nopython=True)\n", "def draw_bs_reps_cohen_d(x, y, size=10000, return_abs=False):\n", " out = np.empty(size)\n", " for i in range(size):\n", " out[i] = cohen_d(draw_bs_sample(x), draw_bs_sample(y), return_abs)\n", " return out\n", "\n", "\n", "@numba.jit(nopython=True)\n", "def draw_bs_reps_t(x, y, size=10000):\n", " \"\"\"\n", " Bootstrap replicates using the Welch's t-statistic.\n", " \"\"\"\n", " out = np.empty(size)\n", " for i in range(size):\n", " out[i] = t_stat(draw_bs_sample(x), draw_bs_sample(y))\n", " return out" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can compute the replicates. First, let's look at the means and their respective confidence intervals." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "wt_reps = draw_bs_reps_mean(wt)\n", "mut_reps = draw_bs_reps_mean(mut)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And from these, compute the 95% confidence interval." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1211" } }, "output_type": "display_data" } ], "source": [ "wt_mean_conf_int = np.percentile(wt_reps, [2.5, 97.5])\n", "mut_mean_conf_int = np.percentile(mut_reps, [2.5, 97.5])\n", "\n", "summaries = [\n", " dict(estimate=est, conf_int=conf, label=name)\n", " for est, conf, name in zip(\n", " [wt.mean(), mut.mean()], [wt_mean_conf_int, mut_mean_conf_int], [\"WT\", \"mutant\"]\n", " )\n", "]\n", "\n", "p = bebi103.viz.confints(summaries, x_axis_label='mean rest bout lengths (min)')\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There is some overlap in the confidence interval, though wild type tend to have longer rest bouts. Just looking at these numbers, we may not be all that certain that there is a discernible difference between wild type and mutant.\n", "\n", "Now, let's look at the *difference* in the mean rest bout lengths, which we define as $\\delta = \\bar{x}_\\mathrm{wt} - \\bar{x}_\\mathrm{mut}$." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "δ = WT - MUT: [-0.06, 0.31, 0.66] minutes\n" ] } ], "source": [ "reps = draw_bs_reps_diff_mean(wt, mut)\n", "diff_mean_conf_int = np.percentile(reps, [2.5, 97.5])\n", "\n", "print(\n", " \"δ = WT - MUT: [{1:.2f}, {0:.2f}, {2:.2f}] minutes\".format(\n", " np.mean(wt) - np.mean(mut), *tuple(diff_mean_conf_int)\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we might expect, on the tail end of the confidence interval for the difference of means, we see that the mutant might actually have longer rest bouts that wild type.\n", "\n", "Finally, lets compute the Cohen's d to check the effect size." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WT - MUT Cohen's d: [-0.08, 0.54, 1.43]\n" ] } ], "source": [ "reps = draw_bs_reps_cohen_d(wt, mut)\n", "cohen_d_conf_int = np.percentile(reps, [2.5, 97.5])\n", "\n", "print(\n", " \"WT - MUT Cohen's d: [{1:.2f}, {0:.2f}, {2:.2f}]\".format(\n", " cohen_d(wt, mut), *tuple(cohen_d_conf_int)\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, the effect size is 0.54, meaning that the mutant tends to have rest bouts 0.5 standard deviations as large as wild type fix. Jacob Cohen would call this a \"medium\" sized effect. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Null hypothesis significance testing\n", "\n", "We will now perform an NHST on these two data sets. We formulate the hypothesis as follows.\n", "\n", "- $H_0$: Wild type and mutant fish have the same mean rest about length. \n", "- Test statistic: Cohen's d.\n", "- At least as extreme as: Cohen's d larger than what was observed.\n", "\n", "We can then perform a bootstrap hypothesis test." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cohen's d p-value: 0.06688\n" ] } ], "source": [ "@numba.jit(nopython=True)\n", "def cohen_nhst(wt, mut, size=100000):\n", " \"\"\"\n", " Perform hypothesis test assuming equal means, using\n", " Cohen-d as test statistic.\n", " \"\"\"\n", " # Shift data sets so that they have the same mean.\n", " wt_shifted = wt - np.mean(wt) + np.mean(np.concatenate((wt, mut)))\n", " mut_shifted = mut - np.mean(mut) + np.mean(np.concatenate((wt, mut)))\n", "\n", " # Draw replicates of Cohen's d\n", " reps = draw_bs_reps_cohen_d(wt_shifted, mut_shifted, size=size)\n", "\n", " # Compute p-value\n", " return np.sum(reps >= cohen_d(wt, mut)) / len(reps)\n", "\n", "print(\"Cohen's d p-value:\", cohen_nhst(wt, mut))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We get a p-value of about 0.07, which, if we use the typical bright line p-value for statistical significance, we would say that this difference is not statistically significant. We could also test what would happen if we used a different test statistic, like the difference of means." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Difference of means p-value: 0.04077\n" ] } ], "source": [ "# Shift data sets so that they have the same mean.\n", "wt_shifted = wt - np.mean(wt) + np.mean(np.concatenate((wt, mut)))\n", "mut_shifted = mut - np.mean(mut) + np.mean(np.concatenate((wt, mut)))\n", "\n", "# Draw replicates of difference of means\n", "reps = draw_bs_reps_diff_mean(wt_shifted, mut_shifted, size=100000)\n", "\n", "# Compute p-value\n", "p_val = np.sum(reps >= np.mean(wt) - np.mean(mut)) / len(reps)\n", "\n", "print('Difference of means p-value:', p_val)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here, we get a p-value of about 0.04. We would say that the result is statistically significant if we used a bright line value of 0.05.\n", "\n", "Finally, let's try a canonical test for this circumstance, the Welch's t-test. As a reminder, the test statistic for the Welch's t-test is\n", "\n", "\\begin{align}\n", "T = \\frac{\\bar{x}_w - \\bar{x}_m}{\\sqrt{\\hat{\\sigma}_w^2/n_w + \\hat{\\sigma}_m^2/n_m}},\n", "\\end{align}\n", "\n", "where $\\hat{\\sigma}_w^2$ and $\\hat{\\sigma}_m^2$ are plug-in estimates for the variances. Importantly, when performing a Welch's t-test, Normality of the two samples is assumed. So, the hypothesis test is defined as follows.\n", "\n", "- $H_0$: The two samples are both Normally distributed with equal means.\n", "- Test statistic: t-statistic.\n", "- At least as extreme as: t-statistic (wild type minus mutant) greater than or equal to what was observed.\n", "\n", "This is implemented as `scipy.stats.ttest_ind()` using the kwarg `equal_var=False`. We divide by two to get the one-tailed test. Note that Welch's t-test is not exact, but is asymptotically exact for large sample sizes." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Welch's p-value: 0.05254200490883057\n" ] } ], "source": [ "print(\"Welch's p-value:\", st.ttest_ind(wt, mut, equal_var=False)[1]/2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here, we are just above the bright line value of 0.05. We can perform a similar hypothesis test without the Normal assumption using the same test statistic as in the Welch's test." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Welch's t-test without Normal assumption p-value: 0.06416\n" ] } ], "source": [ "# Draw replicates of t statistic\n", "reps = draw_bs_reps_t(wt_shifted, mut_shifted, size=100000)\n", "\n", "# Compute p-value\n", "p_val = np.sum(reps >= t_stat(wt, mut)) / len(reps)\n", "\n", "print(\"Welch's t-test without Normal assumption p-value:\", p_val)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, we will perform a permutation test. This test is specified as follows.\n", "\n", "- $H_0$: The sleep bout lengths of mutant and wild type fish are identically distributed.\n", "- Test statistic: Welch's t-statistic\n", "- At least as extreme as : difference of means is greater than what was observed." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Permutation test p-value: 0.04999\n" ] } ], "source": [ "# Draw permutation replicates\n", "reps = draw_perm_reps_t(wt, mut, size=100000)\n", "\n", "# Compute p-value\n", "p_val = np.sum(reps >= t_stat(wt, mut)) / len(reps)\n", "\n", "print(\"Permutation test p-value:\", p_val)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, all of our tests give p-values that are close to each other, ranging from about 0.04 to 0.07. If we choose bright line p-values to deem something as significant or not, some similar hypothesis/test statistic pairs can give different results. So, my advice is **do not use brightline p-values.** You went through the trouble of computing the p-value, just report it and leave it at that. Don't change a `float` to a `bool`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Model comparison\n", "\n", "As an alternative to NHST, we can ask a similar (but different) question. We can *compare* two generative models. In one model, wild type and mutant sleep mean bout lengths come from the same Normal distribution. In the other, they come from different Normal distributions. We can compute an AIC for each model and then the Akaike weight for the first model (that they come from the same Normal distribution). Again, we can use the convenient feature that for Normal distributions, the MLE is given by the plug-in estimates for the parameters." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "def akaike_weight(wt, mut):\n", " \"\"\"Compute the Akaike weight for model 1\"\"\"\n", " x_concat = np.concatenate((wt, mut))\n", " mu_1 = np.mean(x_concat)\n", " sigma_1 = np.std(x_concat)\n", " aic_1 = -2 * (st.norm.logpdf(x_concat, mu_1, sigma_1).sum() - 2)\n", " \n", " mu_wt = np.mean(wt)\n", " sigma_wt = np.std(wt)\n", " mu_mut = np.mean(mut)\n", " sigma_mut = np.std(mut)\n", " aic_2 = -2 * (\n", " st.norm.logpdf(wt, mu_wt, sigma_wt).sum()\n", " + st.norm.logpdf(mut, mu_mut, sigma_mut).sum()\n", " - 4\n", " )\n", "\n", " aic_max = max(aic_1, aic_2)\n", "\n", " return np.exp(-(aic_1 - aic_max) / 2) / (\n", " np.exp(-(aic_1 - aic_max) / 2) + np.exp(-(aic_2 - aic_max) / 2)\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have this function, we can compute the Akaike weight for this data set." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "np.float64(0.598909687738875)" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "akaike_weight(wt, mut)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Akaike weight says that we should slightly favor the model where the data points come from the *same* Normal distribution. This runs contrary to our hypothesis tests. The AIC is penalizing the model with more parameters." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Dancing\n", "\n", "We will now do a fun, instructive experiment. We will \"re-acquire\" the data by drawing random samples out of Normal distributions parametrized by the maximum likelihood estimates we obtain from the data. (Recall that the MLE for the mean and variance of a Normally distributed random variable is given by the plug-in estimates.) We will then compute the confidence interval and credible region for $\\delta$ and see how they vary from experiment to experiment. We will later repeat this with p-values and odds ratios.\n", "\n", "The idea here is that if the data are indeed Gaussian distributed, we are looking at data that could plausibly be generated in an identical experiment.\n", "\n", "First, we'll write a function to generate new data and use it to generate 500 new data sets." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "def new_data(mu, sigma, n):\n", " \"\"\"Generate new data\"\"\"\n", " return np.maximum(np.random.normal(mu, sigma, n), 0.01)\n", "\n", "# Values from real data\n", "mu_wt = np.mean(wt)\n", "mu_mut = np.mean(mut)\n", "sigma_wt = np.std(wt, ddof=0)\n", "sigma_mut = np.std(mut, ddof=0)\n", "\n", "# How many new data sets to generate\n", "n_new_data = 500\n", "\n", "# Generate new data\n", "new_wt = [new_data(mu_wt, sigma_wt, len(wt)) for _ in range(n_new_data)]\n", "new_mut = [new_data(mu_mut, sigma_mut, len(mut)) for _ in range(n_new_data)]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can do the calculations. First, we'll compute the confidence intervals for $\\delta$." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "500it [00:02, 198.75it/s]\n" ] } ], "source": [ "# Set up arrays for storing results\n", "conf_int = np.empty((n_new_data, 2))\n", "delta = np.empty(n_new_data)\n", "\n", "# Do calcs!\n", "for i, (wt_data, mut_data) in enumerate(tqdm.tqdm(zip(new_wt, new_mut))):\n", " # Compute confidence interval\n", " bs_reps = draw_bs_reps_diff_mean(wt_data, mut_data)\n", " conf_int[i, :] = np.percentile(bs_reps, (2.5, 97.5))\n", "\n", " # Sample difference of means\n", " delta[i] = wt_data.mean() - mut_data.mean()\n", "\n", "# Store the results conveniently\n", "df_res = pl.DataFrame(\n", " schema=[\"conf_low\", \"conf_high\", \"delta\"],\n", " data=np.hstack((conf_int, delta.reshape(n_new_data, 1))),\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we can do some null hypothesis significance testing. We will compute three p-values, our custom bootstraped p-value with Cohen's d, the p-value from a permutaiton test, and a p-value from Welch's t-test. Remember, with our custom bootstrapped p-value, the hypothesis is that the mutant and wild type sleep bout lengths were drawn out of distributions of the same mean (and no other assumptions). The test statistic is Cohen's d. The hypothesis in the permutation test is that the two data sets are identically distributed. The hypothesis in Welch's t-test is that the mutant and wild type were drawn from Normal distributions with the same mean, but with difference variances. The test statistic is a t-statistic, defined above." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "500it [00:45, 11.11it/s]\n" ] } ], "source": [ "# Set up arrays for storing results\n", "cohen_p = np.empty(n_new_data)\n", "perm_test_p = np.empty(n_new_data)\n", "welch_p = np.empty(n_new_data)\n", "\n", "\n", "@numba.jit(nopython=True)\n", "def perm_test_t(wt, mut, size=100000):\n", " reps = draw_perm_reps_t(wt, mut, size=size)\n", " return np.sum(reps >= t_stat(wt, mut)) / len(reps)\n", "\n", "\n", "# Do calcs!\n", "for i, (wt_data, mut_data) in enumerate(tqdm.tqdm(zip(new_wt, new_mut))):\n", " # Compute p-values\n", " cohen_p[i] = cohen_nhst(wt_data, mut_data)\n", " perm_test_p[i] = perm_test_t(wt_data, mut_data)\n", " welch_p[i] = st.ttest_ind(wt_data, mut_data, equal_var=False)[1] / 2\n", "\n", "df_res = df_res.with_columns(\n", " pl.Series(cohen_p).alias(\"cohen_p\"),\n", " pl.Series(perm_test_p).alias(\"perm_p\"),\n", " pl.Series(welch_p).alias(\"welch_p\"),\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, we can compute the Akaike weights for all of our generated data sets." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "df_res = df_res.with_columns(\n", " pl.Series(\n", " [akaike_weight(wt_data, mut_data) for wt_data, mut_data in zip(new_wt, new_mut)]\n", " ).alias(\"akaike_weight\")\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Dancing confidence intervals(?)\n", "\n", "To visualize the results, we'll plot the confidence intervals. We'll plot the confidence interval as a bar, and then the bounds of the credible region as dots. For ease of viewing, we will only plot 100 of these and will sort them by the plug-in estimate for δ." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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"p.scatter(np.arange(len(df_res_sorted)), df_res_sorted['delta'])\n", "x_conf = [[i, i] for i in range(len(df_res_sorted))]\n", "y_conf = [[r[\"conf_low\"], r[\"conf_high\"]] for r in df_res_sorted.iter_rows(named=True)]\n", "p.multi_line(x_conf, y_conf, line_width=2, color=\"#1f77b4\")\n", "\n", "# Turn off axis ticks for x\n", "p.xaxis.visible = False\n", "p.xgrid.visible = False\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The confidence interval can vary from experiment to experiment, but not that much. That is, the confidence intervals \"dance\" around, but all within about a factor of 3 of the original observed values." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Dancing: p-values\n", "\n", "Now, let's look at the p-values and the Akaike weights." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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"display_data" } ], "source": [ "p = bokeh.plotting.figure(\n", " x_axis_type=\"log\",\n", " y_axis_type=\"log\",\n", " x_axis_label=\"Welch's p-value\",\n", " frame_width=500,\n", " frame_height=500,\n", " x_range=[1e-6, 1],\n", " y_range=[1e-6, 1],\n", ")\n", "p.scatter(\n", " df_res[\"welch_p\"],\n", " df_res[\"cohen_p\"],\n", " color=\"#1f77b4\",\n", " alpha=0.5,\n", " legend_label=\"Cohen's d p-value\",\n", ")\n", "p.scatter(\n", " df_res[\"welch_p\"],\n", " df_res[\"perm_p\"],\n", " color=\"#ffbb78\",\n", " alpha=0.5,\n", " legend_label=\"permuation test p-value\",\n", ")\n", "p.scatter(\n", " df_res[\"welch_p\"],\n", " df_res[\"akaike_weight\"],\n", " color=\"#2ca02c\",\n", " alpha=0.5,\n", " legend_label=\"Akaike weight\",\n", ")\n", "\n", "p.legend.location = \"bottom_right\"\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The custom p-value computed with a Cohen's d test statistic and the permutation test p-value are nearly equal to the Welch's p-value.\n", "\n", "But what is really striking here is the scale! Wow! In 500 repeats, we get p-values ranging over four or five orders of magnitude! That's three exclamations in a row! Four, now. Those exclamation points are there to highlight that the p-value is not a reproducible statistic at all.\n", "\n", "The Akaike weights are less variable, and more conservative. Not many of them dip below 0.1, and we would be unlikely to select one model against another for most of the values of the Akaike weights we calculated. However, they are still rather variable, and in 500 repeats the can var over many orders of magnitude as well. Though better than the p-values, they are still not terribly reproducible.\n", "\n", "Conversely, both confidence intervals don't really dance much, and p-values and odds ratios dance like [this](https://www.youtube.com/watch?v=XQ7z57qrZU8)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The effect of sample size on dancing\n", "\n", "The zebrafish sleep experiment had only about 20 samples, so maybe larger sample sizes will result in less extreme dancing of p-values. Let's do a numerical experiment to look at that. We will take 15, 20, 50, and 100 samples for our experimental \"repeats\" and investigate how the p-value varies. For speed, we will only compute the p-value from Welch's t-test, which we showed previously to track closely with our custom p-values." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████████████████████████████████████████████████| 1000/1000 [00:01<00:00, 704.11it/s]\n" ] } ], "source": [ "n_new_data = 1000\n", "n_samples = [15, 20, 50, 100]\n", "p_vals = np.empty((n_new_data, len(n_samples)))\n", "akaike_weights = np.empty((n_new_data, len(n_samples)))\n", "\n", "# Do calcs!\n", "for i in tqdm.tqdm(range(n_new_data)):\n", " for j, n in enumerate(n_samples):\n", " # Generate new data\n", " new_wt = new_data(mu_wt, sigma_wt, n)\n", " new_mut = new_data(mu_mut, sigma_mut, n)\n", "\n", " # Compute p-values and Akaikie weights\n", " p_vals[i,j] = st.ttest_ind(new_wt, new_mut, equal_var=False)[1]/2\n", " akaike_weights[i, j] = akaike_weight(new_wt, new_mut)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's look at the ECDFs of p-values and Akaike weights." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
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vUovD8pXI/C9Si8P9Ei2/l+arw/0SLb+X5qvD956SYxCKy8P3npJjEIrLw/IbByaJHtvD8hsHJoke28P8l2vp8aL70/yXa+nxovvT9xPQrXo3C9P3E9CtejcL0/GQRWDi2yvT8ZBFYOLbK9P8HKoUW2870/wcqhRbbzvT9oke18PzW+P2iR7Xw/Nb4/EFg5tMh2vj8QWDm0yHa+P7gehetRuL4/uB6F61G4vj9g5dAi2/m+P2Dl0CLb+b4/CKwcWmQ7vz8IrBxaZDu/P7ByaJHtfL8/sHJoke18vz9YObTIdr6/P1g5tMh2vr8/AAAAAAAAwD8AAAAAAADAP1TjpZvEIMA/VOOlm8QgwD+oxks3iUHAP6jGSzeJQcA//Knx0k1iwD/8qfHSTWLAP1CNl24Sg8A/UI2XbhKDwD+kcD0K16PAP6RwPQrXo8A/+FPjpZvEwD/4U+Olm8TAP0w3iUFg5cA/TDeJQWDlwD+gGi/dJAbBP6AaL90kBsE/9P3UeOkmwT/0/dR46SbBP0jhehSuR8E/SOF6FK5HwT+cxCCwcmjBP5zEILByaME/8KfGSzeJwT/wp8ZLN4nBP0SLbOf7qcE/RIts5/upwT+YbhKDwMrBP5huEoPAysE/7FG4HoXrwT/sUbgehevBPz81XrpJDMI/PzVeukkMwj+TGARWDi3CP5MYBFYOLcI/5/up8dJNwj/n+6nx0k3CPzvfT42XbsI/O99PjZduwj+PwvUoXI/CP4/C9Shcj8I/46WbxCCwwj/jpZvEILDCPzeJQWDl0MI/N4lBYOXQwj+LbOf7qfHCP4ts5/up8cI/30+Nl24Swz/fT42XbhLDPzMzMzMzM8M/MzMzMzMzwz+HFtnO91PDP4cW2c73U8M/2/l+arx0wz/b+X5qvHTDPy/dJAaBlcM/L90kBoGVwz+DwMqhRbbDP4PAyqFFtsM/16NwPQrXwz/Xo3A9CtfDPyuHFtnO98M/K4cW2c73wz9/arx0kxjEP39qvHSTGMQ/001iEFg5xD/TTWIQWDnEPycxCKwcWsQ/JzEIrBxaxD97FK5H4XrEP3sUrkfhesQ/z/dT46WbxD/P91PjpZvEPyPb+X5qvMQ/I9v5fmq8xD93vp8aL93EP3e+nxov3cQ/y6FFtvP9xD/LoUW28/3EPx+F61G4HsU/H4XrUbgexT9zaJHtfD/FP3Noke18P8U/x0s3iUFgxT/HSzeJQWDFPxsv3SQGgcU/Gy/dJAaBxT9vEoPAyqHFP28Sg8DKocU/w/UoXI/CxT/D9Shcj8LFPxfZzvdT48U/F9nO91PjxT9qvHSTGATGP2q8dJMYBMY/vp8aL90kxj++nxov3STGPxKDwMqhRcY/EoPAyqFFxj9mZmZmZmbGP2ZmZmZmZsY/ukkMAiuHxj+6SQwCK4fGPw4tsp3vp8Y/Di2yne+nxj9iEFg5tMjGP2IQWDm0yMY/tvP91Hjpxj+28/3UeOnGPwrXo3A9Csc/CtejcD0Kxz9eukkMAivHP166SQwCK8c/sp3vp8ZLxz+yne+nxkvHPwaBlUOLbMc/BoGVQ4tsxz9aZDvfT43HP1pkO99Pjcc/rkfhehSuxz+uR+F6FK7HPwIrhxbZzsc/AiuHFtnOxz9WDi2yne/HP1YOLbKd78c/qvHSTWIQyD+q8dJNYhDIP/7UeOkmMcg//tR46SYxyD9SuB6F61HIP1K4HoXrUcg/ppvEILByyD+mm8QgsHLIP/p+arx0k8g/+n5qvHSTyD9OYhBYObTIP05iEFg5tMg/okW28/3UyD+iRbbz/dTIP/YoXI/C9cg/9ihcj8L1yD9KDAIrhxbJP0oMAiuHFsk/nu+nxks3yT+e76fGSzfJP/LSTWIQWMk/8tJNYhBYyT9GtvP91HjJP0a28/3UeMk/mpmZmZmZyT+amZmZmZnJP+58PzVeusk/7nw/NV66yT9CYOXQItvJP0Jg5dAi28k/lkOLbOf7yT+WQ4ts5/vJP+kmMQisHMo/6SYxCKwcyj89CtejcD3KPz0K16NwPco/ke18PzVeyj+R7Xw/NV7KP+XQItv5fso/5dAi2/l+yj85tMh2vp/KPzm0yHa+n8o/jZduEoPAyj+Nl24Sg8DKP+F6FK5H4co/4XoUrkfhyj81XrpJDALLPzVeukkMAss/iUFg5dAiyz+JQWDl0CLLP90kBoGVQ8s/3SQGgZVDyz8xCKwcWmTLPzEIrBxaZMs/hetRuB6Fyz+F61G4HoXLP9nO91Pjpcs/2c73U+Olyz8tsp3vp8bLPy2yne+nxss/gZVDi2znyz+BlUOLbOfLP9V46SYxCMw/1XjpJjEIzD8pXI/C9SjMPylcj8L1KMw/fT81XrpJzD99PzVeuknMP9Ei2/l+asw/0SLb+X5qzD8lBoGVQ4vMPyUGgZVDi8w/eekmMQiszD956SYxCKzMP83MzMzMzMw/zczMzMzMzD8hsHJoke3MPyGwcmiR7cw/dZMYBFYOzT91kxgEVg7NP8l2vp8aL80/yXa+nxovzT8dWmQ730/NPx1aZDvfT80/cT0K16NwzT9xPQrXo3DNP8UgsHJokc0/xSCwcmiRzT8ZBFYOLbLNPxkEVg4tss0/bef7qfHSzT9t5/up8dLNP8HKoUW2880/wcqhRbbzzT8UrkfhehTOPxSuR+F6FM4/aJHtfD81zj9oke18PzXOP7x0kxgEVs4/vHSTGARWzj8QWDm0yHbOPxBYObTIds4/ZDvfT42Xzj9kO99PjZfOP7gehetRuM4/uB6F61G4zj8MAiuHFtnOPwwCK4cW2c4/YOXQItv5zj9g5dAi2/nOP7TIdr6fGs8/tMh2vp8azz8IrBxaZDvPPwisHFpkO88/XI/C9Shczz9cj8L1KFzPP7ByaJHtfM8/sHJoke18zz8EVg4tsp3PPwRWDi2ync8/WDm0yHa+zz9YObTIdr7PP6wcWmQ7388/rBxaZDvfzz8AAAAAAADQPwAAAAAAANA/qvHSTWIQ0D+q8dJNYhDQP1TjpZvEINA/VOOlm8Qg0D/+1HjpJjHQP/7UeOkmMdA/qMZLN4lB0D+oxks3iUHQP1K4HoXrUdA/UrgehetR0D/8qfHSTWLQP/yp8dJNYtA/ppvEILBy0D+mm8QgsHLQP1CNl24Sg9A/UI2XbhKD0D/6fmq8dJPQP/p+arx0k9A/pHA9Ctej0D+kcD0K16PQP05iEFg5tNA/TmIQWDm00D/4U+Olm8TQP/hT46WbxNA/okW28/3U0D+iRbbz/dTQP0w3iUFg5dA/TDeJQWDl0D/2KFyPwvXQP/YoXI/C9dA/oBov3SQG0T+gGi/dJAbRP0oMAiuHFtE/SgwCK4cW0T/0/dR46SbRP/T91HjpJtE/nu+nxks30T+e76fGSzfRP0jhehSuR9E/SOF6FK5H0T/y0k1iEFjRP/LSTWIQWNE/nMQgsHJo0T+cxCCwcmjRP0a28/3UeNE/Rrbz/dR40T/wp8ZLN4nRP/Cnxks3idE/mpmZmZmZ0T+amZmZmZnRP0SLbOf7qdE/RIts5/up0T/ufD81XrrRP+58PzVeutE/mG4Sg8DK0T+YbhKDwMrRP0Jg5dAi29E/QmDl0CLb0T/sUbgehevRP+xRuB6F69E/lkOLbOf70T+WQ4ts5/vRPz81XrpJDNI/PzVeukkM0j/pJjEIrBzSP+kmMQisHNI/kxgEVg4t0j+TGARWDi3SPz0K16NwPdI/PQrXo3A90j/n+6nx0k3SP+f7qfHSTdI/ke18PzVe0j+R7Xw/NV7SPzvfT42XbtI/O99PjZdu0j/l0CLb+X7SP+XQItv5ftI/j8L1KFyP0j+PwvUoXI/SPzm0yHa+n9I/ObTIdr6f0j/jpZvEILDSP+Olm8QgsNI/jZduEoPA0j+Nl24Sg8DSPzeJQWDl0NI/N4lBYOXQ0j/hehSuR+HSP+F6FK5H4dI/i2zn+6nx0j+LbOf7qfHSPzVeukkMAtM/NV66SQwC0z/fT42XbhLTP99PjZduEtM/iUFg5dAi0z+JQWDl0CLTPzMzMzMzM9M/MzMzMzMz0z/dJAaBlUPTP90kBoGVQ9M/hxbZzvdT0z+HFtnO91PTPzEIrBxaZNM/MQisHFpk0z/b+X5qvHTTP9v5fmq8dNM/hetRuB6F0z+F61G4HoXTPy/dJAaBldM/L90kBoGV0z/ZzvdT46XTP9nO91PjpdM/g8DKoUW20z+DwMqhRbbTPy2yne+nxtM/LbKd76fG0z/Xo3A9CtfTP9ejcD0K19M/gZVDi2zn0z+BlUOLbOfTPyuHFtnO99M/K4cW2c730z/VeOkmMQjUP9V46SYxCNQ/f2q8dJMY1D9/arx0kxjUPylcj8L1KNQ/KVyPwvUo1D/TTWIQWDnUP9NNYhBYOdQ/fT81XrpJ1D99PzVeuknUPycxCKwcWtQ/JzEIrBxa1D/RItv5fmrUP9Ei2/l+atQ/exSuR+F61D97FK5H4XrUPyUGgZVDi9Q/JQaBlUOL1D/P91PjpZvUP8/3U+Olm9Q/eekmMQis1D956SYxCKzUPyPb+X5qvNQ/I9v5fmq81D/NzMzMzMzUP83MzMzMzNQ/d76fGi/d1D93vp8aL93UPyGwcmiR7dQ/IbByaJHt1D/LoUW28/3UP8uhRbbz/dQ/dZMYBFYO1T91kxgEVg7VPx+F61G4HtU/H4XrUbge1T/Jdr6fGi/VP8l2vp8aL9U/c2iR7Xw/1T9zaJHtfD/VPx1aZDvfT9U/HVpkO99P1T/HSzeJQWDVP8dLN4lBYNU/cT0K16Nw1T9xPQrXo3DVPxsv3SQGgdU/Gy/dJAaB1T/FILByaJHVP8UgsHJokdU/bxKDwMqh1T9vEoPAyqHVPxkEVg4tstU/GQRWDi2y1T/D9Shcj8LVP8P1KFyPwtU/bef7qfHS1T9t5/up8dLVPxfZzvdT49U/F9nO91Pj1T/ByqFFtvPVP8HKoUW289U/arx0kxgE1j9qvHSTGATWPxSuR+F6FNY/FK5H4XoU1j++nxov3STWP76fGi/dJNY/aJHtfD811j9oke18PzXWPxKDwMqhRdY/EoPAyqFF1j+8dJMYBFbWP7x0kxgEVtY/ZmZmZmZm1j9mZmZmZmbWPxBYObTIdtY/EFg5tMh21j+6SQwCK4fWP7pJDAIrh9Y/ZDvfT42X1j9kO99PjZfWPw4tsp3vp9Y/Di2yne+n1j+4HoXrUbjWP7gehetRuNY/YhBYObTI1j9iEFg5tMjWPwwCK4cW2dY/DAIrhxbZ1j+28/3UeOnWP7bz/dR46dY/YOXQItv51j9g5dAi2/nWPwrXo3A9Ctc/CtejcD0K1z+0yHa+nxrXP7TIdr6fGtc/XrpJDAIr1z9eukkMAivXPwisHFpkO9c/CKwcWmQ71z+yne+nxkvXP7Kd76fGS9c/XI/C9Shc1z9cj8L1KFzXPwaBlUOLbNc/BoGVQ4ts1z+wcmiR7XzXP7ByaJHtfNc/WmQ730+N1z9aZDvfT43XPwRWDi2yndc/BFYOLbKd1z+uR+F6FK7XP65H4XoUrtc/WDm0yHa+1z9YObTIdr7XPwIrhxbZztc/AiuHFtnO1z+sHFpkO9/XP6wcWmQ739c/Vg4tsp3v1z9WDi2yne/XPwAAAAAAANg/AAAAAAAA2D+q8dJNYhDYP6rx0k1iENg/VOOlm8Qg2D9U46WbxCDYP/7UeOkmMdg//tR46SYx2D+oxks3iUHYP6jGSzeJQdg/UrgehetR2D9SuB6F61HYP/yp8dJNYtg//Knx0k1i2D+mm8QgsHLYP6abxCCwctg/UI2XbhKD2D9QjZduEoPYP/p+arx0k9g/+n5qvHST2D+kcD0K16PYP6RwPQrXo9g/TmIQWDm02D9OYhBYObTYP/hT46WbxNg/+FPjpZvE2D+iRbbz/dTYP6JFtvP91Ng/TDeJQWDl2D9MN4lBYOXYP/YoXI/C9dg/9ihcj8L12D+gGi/dJAbZP6AaL90kBtk/SgwCK4cW2T9KDAIrhxbZP/T91HjpJtk/9P3UeOkm2T+e76fGSzfZP57vp8ZLN9k/SOF6FK5H2T9I4XoUrkfZP/LSTWIQWNk/8tJNYhBY2T+cxCCwcmjZP5zEILByaNk/Rrbz/dR42T9GtvP91HjZP/Cnxks3idk/8KfGSzeJ2T+amZmZmZnZP5qZmZmZmdk/RIts5/up2T9Ei2zn+6nZP+58PzVeutk/7nw/NV662T+YbhKDwMrZP5huEoPAytk/QmDl0CLb2T9CYOXQItvZP+xRuB6F69k/7FG4HoXr2T+WQ4ts5/vZP5ZDi2zn+9k/PzVeukkM2j8/NV66SQzaP+kmMQisHNo/6SYxCKwc2j+TGARWDi3aP5MYBFYOLdo/PQrXo3A92j89CtejcD3aP+f7qfHSTdo/5/up8dJN2j+R7Xw/NV7aP5HtfD81Xto/O99PjZdu2j8730+Nl27aP+XQItv5fto/5dAi2/l+2j+PwvUoXI/aP4/C9Shcj9o/ObTIdr6f2j85tMh2vp/aP+Olm8QgsNo/46WbxCCw2j+Nl24Sg8DaP42XbhKDwNo/N4lBYOXQ2j83iUFg5dDaP+F6FK5H4do/4XoUrkfh2j+LbOf7qfHaP4ts5/up8do/NV66SQwC2z81XrpJDALbP99PjZduEts/30+Nl24S2z+JQWDl0CLbP4lBYOXQIts/MzMzMzMz2z8zMzMzMzPbP90kBoGVQ9s/3SQGgZVD2z+HFtnO91PbP4cW2c73U9s/MQisHFpk2z8xCKwcWmTbP9v5fmq8dNs/2/l+arx02z+F61G4HoXbP4XrUbgehds/L90kBoGV2z8v3SQGgZXbP9nO91Pjpds/2c73U+Ol2z+DwMqhRbbbP4PAyqFFtts/LbKd76fG2z8tsp3vp8bbP9ejcD0K19s/16NwPQrX2z+BlUOLbOfbP4GVQ4ts59s/K4cW2c732z8rhxbZzvfbP9V46SYxCNw/1XjpJjEI3D9/arx0kxjcP39qvHSTGNw/KVyPwvUo3D8pXI/C9SjcP9NNYhBYOdw/001iEFg53D99PzVeukncP30/NV66Sdw/JzEIrBxa3D8nMQisHFrcP9Ei2/l+atw/0SLb+X5q3D97FK5H4XrcP3sUrkfhetw/JQaBlUOL3D8lBoGVQ4vcP8/3U+Olm9w/z/dT46Wb3D956SYxCKzcP3npJjEIrNw/I9v5fmq83D8j2/l+arzcP83MzMzMzNw/zczMzMzM3D93vp8aL93cP3e+nxov3dw/IbByaJHt3D8hsHJoke3cP8uhRbbz/dw/y6FFtvP93D91kxgEVg7dP3WTGARWDt0/H4XrUbge3T8fhetRuB7dP8l2vp8aL90/yXa+nxov3T9zaJHtfD/dP3Noke18P90/HVpkO99P3T8dWmQ730/dP8dLN4lBYN0/x0s3iUFg3T9xPQrXo3DdP3E9CtejcN0/Gy/dJAaB3T8bL90kBoHdP8UgsHJokd0/xSCwcmiR3T9vEoPAyqHdP28Sg8DKod0/GQRWDi2y3T8ZBFYOLbLdP8P1KFyPwt0/w/UoXI/C3T9t5/up8dLdP23n+6nx0t0/F9nO91Pj3T8X2c73U+PdP8HKoUW2890/wcqhRbbz3T9qvHSTGATeP2q8dJMYBN4/FK5H4XoU3j8UrkfhehTeP76fGi/dJN4/vp8aL90k3j9oke18PzXeP2iR7Xw/Nd4/EoPAyqFF3j8Sg8DKoUXeP7x0kxgEVt4/vHSTGARW3j9mZmZmZmbeP2ZmZmZmZt4/EFg5tMh23j8QWDm0yHbeP7pJDAIrh94/ukkMAiuH3j9kO99PjZfeP2Q730+Nl94/Di2yne+n3j8OLbKd76feP7gehetRuN4/uB6F61G43j9iEFg5tMjeP2IQWDm0yN4/DAIrhxbZ3j8MAiuHFtneP7bz/dR46d4/tvP91Hjp3j9g5dAi2/neP2Dl0CLb+d4/CtejcD0K3z8K16NwPQrfP7TIdr6fGt8/tMh2vp8a3z9eukkMAivfP166SQwCK98/CKwcWmQ73z8IrBxaZDvfP7Kd76fGS98/sp3vp8ZL3z9cj8L1KFzfP1yPwvUoXN8/BoGVQ4ts3z8GgZVDi2zfP7ByaJHtfN8/sHJoke183z9aZDvfT43fP1pkO99Pjd8/BFYOLbKd3z8EVg4tsp3fP65H4XoUrt8/rkfhehSu3z9YObTIdr7fP1g5tMh2vt8/AiuHFtnO3z8CK4cW2c7fP6wcWmQ7398/rBxaZDvf3z9WDi2yne/fP1YOLbKd798/AAAAAAAA4D8AAAAAAADgP9V46SYxCOA/1XjpJjEI4D+q8dJNYhDgP6rx0k1iEOA/f2q8dJMY4D9/arx0kxjgP1TjpZvEIOA/VOOlm8Qg4D8pXI/C9SjgPylcj8L1KOA//tR46SYx4D/+1HjpJjHgP9NNYhBYOeA/001iEFg54D+oxks3iUHgP6jGSzeJQeA/fT81XrpJ4D99PzVeukngP1K4HoXrUeA/UrgehetR4D8nMQisHFrgPycxCKwcWuA//Knx0k1i4D/8qfHSTWLgP9Ei2/l+auA/0SLb+X5q4D+mm8QgsHLgP6abxCCwcuA/exSuR+F64D97FK5H4XrgP1CNl24Sg+A/UI2XbhKD4D8lBoGVQ4vgPyUGgZVDi+A/+n5qvHST4D/6fmq8dJPgP8/3U+Olm+A/z/dT46Wb4D+kcD0K16PgP6RwPQrXo+A/eekmMQis4D956SYxCKzgP05iEFg5tOA/TmIQWDm04D8j2/l+arzgPyPb+X5qvOA/+FPjpZvE4D/4U+Olm8TgP83MzMzMzOA/zczMzMzM4D+iRbbz/dTgP6JFtvP91OA/d76fGi/d4D93vp8aL93gP0w3iUFg5eA/TDeJQWDl4D8hsHJoke3gPyGwcmiR7eA/9ihcj8L14D/2KFyPwvXgP8uhRbbz/eA/y6FFtvP94D+gGi/dJAbhP6AaL90kBuE/dZMYBFYO4T91kxgEVg7hP0oMAiuHFuE/SgwCK4cW4T8fhetRuB7hPx+F61G4HuE/9P3UeOkm4T/0/dR46SbhP8l2vp8aL+E/yXa+nxov4T+e76fGSzfhP57vp8ZLN+E/c2iR7Xw/4T9zaJHtfD/hP0jhehSuR+E/SOF6FK5H4T8dWmQ730/hPx1aZDvfT+E/8tJNYhBY4T/y0k1iEFjhP8dLN4lBYOE/x0s3iUFg4T+cxCCwcmjhP5zEILByaOE/cT0K16Nw4T9xPQrXo3DhP0a28/3UeOE/Rrbz/dR44T8bL90kBoHhPxsv3SQGgeE/8KfGSzeJ4T/wp8ZLN4nhP8UgsHJokeE/xSCwcmiR4T+amZmZmZnhP5qZmZmZmeE/bxKDwMqh4T9vEoPAyqHhP0SLbOf7qeE/RIts5/up4T8ZBFYOLbLhPxkEVg4tsuE/7nw/NV664T/ufD81XrrhP8P1KFyPwuE/w/UoXI/C4T+YbhKDwMrhP5huEoPAyuE/bef7qfHS4T9t5/up8dLhP0Jg5dAi2+E/QmDl0CLb4T8X2c73U+PhPxfZzvdT4+E/7FG4HoXr4T/sUbgehevhP8HKoUW28+E/wcqhRbbz4T+WQ4ts5/vhP5ZDi2zn++E/arx0kxgE4j9qvHSTGATiPz81XrpJDOI/PzVeukkM4j8UrkfhehTiPxSuR+F6FOI/6SYxCKwc4j/pJjEIrBziP76fGi/dJOI/vp8aL90k4j+TGARWDi3iP5MYBFYOLeI/aJHtfD814j9oke18PzXiPz0K16NwPeI/PQrXo3A94j8Sg8DKoUXiPxKDwMqhReI/5/up8dJN4j/n+6nx0k3iP7x0kxgEVuI/vHSTGARW4j+R7Xw/NV7iP5HtfD81XuI/ZmZmZmZm4j9mZmZmZmbiPzvfT42XbuI/O99PjZdu4j8QWDm0yHbiPxBYObTIduI/5dAi2/l+4j/l0CLb+X7iP7pJDAIrh+I/ukkMAiuH4j+PwvUoXI/iP4/C9Shcj+I/ZDvfT42X4j9kO99PjZfiPzm0yHa+n+I/ObTIdr6f4j8OLbKd76fiPw4tsp3vp+I/46WbxCCw4j/jpZvEILDiP7gehetRuOI/uB6F61G44j+Nl24Sg8DiP42XbhKDwOI/YhBYObTI4j9iEFg5tMjiPzeJQWDl0OI/N4lBYOXQ4j8MAiuHFtniPwwCK4cW2eI/4XoUrkfh4j/hehSuR+HiP7bz/dR46eI/tvP91Hjp4j+LbOf7qfHiP4ts5/up8eI/YOXQItv54j9g5dAi2/niPzVeukkMAuM/NV66SQwC4z8K16NwPQrjPwrXo3A9CuM/30+Nl24S4z/fT42XbhLjP7TIdr6fGuM/tMh2vp8a4z+JQWDl0CLjP4lBYOXQIuM/XrpJDAIr4z9eukkMAivjPzMzMzMzM+M/MzMzMzMz4z8IrBxaZDvjPwisHFpkO+M/3SQGgZVD4z/dJAaBlUPjP7Kd76fGS+M/sp3vp8ZL4z+HFtnO91PjP4cW2c73U+M/XI/C9Shc4z9cj8L1KFzjPzEIrBxaZOM/MQisHFpk4z8GgZVDi2zjPwaBlUOLbOM/2/l+arx04z/b+X5qvHTjP7ByaJHtfOM/sHJoke184z+F61G4HoXjP4XrUbgeheM/WmQ730+N4z9aZDvfT43jPy/dJAaBleM/L90kBoGV4z8EVg4tsp3jPwRWDi2yneM/2c73U+Ol4z/ZzvdT46XjP65H4XoUruM/rkfhehSu4z+DwMqhRbbjP4PAyqFFtuM/WDm0yHa+4z9YObTIdr7jPy2yne+nxuM/LbKd76fG4z8CK4cW2c7jPwIrhxbZzuM/16NwPQrX4z/Xo3A9CtfjP6wcWmQ73+M/rBxaZDvf4z+BlUOLbOfjP4GVQ4ts5+M/Vg4tsp3v4z9WDi2yne/jPyuHFtnO9+M/K4cW2c734z8AAAAAAADkPwAAAAAAAOQ/1XjpJjEI5D/VeOkmMQjkP6rx0k1iEOQ/qvHSTWIQ5D9/arx0kxjkP39qvHSTGOQ/VOOlm8Qg5D9U46WbxCDkPylcj8L1KOQ/KVyPwvUo5D/+1HjpJjHkP/7UeOkmMeQ/001iEFg55D/TTWIQWDnkP6jGSzeJQeQ/qMZLN4lB5D99PzVeuknkP30/NV66SeQ/UrgehetR5D9SuB6F61HkPycxCKwcWuQ/JzEIrBxa5D/8qfHSTWLkP/yp8dJNYuQ/0SLb+X5q5D/RItv5fmrkP6abxCCwcuQ/ppvEILBy5D97FK5H4XrkP3sUrkfheuQ/UI2XbhKD5D9QjZduEoPkPyUGgZVDi+Q/JQaBlUOL5D/6fmq8dJPkP/p+arx0k+Q/z/dT46Wb5D/P91PjpZvkP6RwPQrXo+Q/pHA9Ctej5D956SYxCKzkP3npJjEIrOQ/TmIQWDm05D9OYhBYObTkPyPb+X5qvOQ/I9v5fmq85D/4U+Olm8TkP/hT46WbxOQ/zczMzMzM5D/NzMzMzMzkP6JFtvP91OQ/okW28/3U5D93vp8aL93kP3e+nxov3eQ/TDeJQWDl5D9MN4lBYOXkPyGwcmiR7eQ/IbByaJHt5D/2KFyPwvXkP/YoXI/C9eQ/y6FFtvP95D/LoUW28/3kP6AaL90kBuU/oBov3SQG5T91kxgEVg7lP3WTGARWDuU/SgwCK4cW5T9KDAIrhxblPx+F61G4HuU/H4XrUbge5T/0/dR46SblP/T91HjpJuU/yXa+nxov5T/Jdr6fGi/lP57vp8ZLN+U/nu+nxks35T9zaJHtfD/lP3Noke18P+U/SOF6FK5H5T9I4XoUrkflPx1aZDvfT+U/HVpkO99P5T/y0k1iEFjlP/LSTWIQWOU/x0s3iUFg5T/HSzeJQWDlP5zEILByaOU/nMQgsHJo5T9xPQrXo3DlP3E9CtejcOU/Rrbz/dR45T9GtvP91HjlPxsv3SQGgeU/Gy/dJAaB5T/wp8ZLN4nlP/Cnxks3ieU/xSCwcmiR5T/FILByaJHlP5qZmZmZmeU/mpmZmZmZ5T9vEoPAyqHlP28Sg8DKoeU/RIts5/up5T9Ei2zn+6nlPxkEVg4tsuU/GQRWDi2y5T/ufD81XrrlP+58PzVeuuU/w/UoXI/C5T/D9Shcj8LlP5huEoPAyuU/mG4Sg8DK5T9t5/up8dLlP23n+6nx0uU/QmDl0CLb5T9CYOXQItvlPxfZzvdT4+U/F9nO91Pj5T/sUbgehevlP+xRuB6F6+U/wcqhRbbz5T/ByqFFtvPlP5ZDi2zn++U/lkOLbOf75T9qvHSTGATmP2q8dJMYBOY/PzVeukkM5j8/NV66SQzmPxSuR+F6FOY/FK5H4XoU5j/pJjEIrBzmP+kmMQisHOY/vp8aL90k5j++nxov3STmP5MYBFYOLeY/kxgEVg4t5j9oke18PzXmP2iR7Xw/NeY/PQrXo3A95j89CtejcD3mPxKDwMqhReY/EoPAyqFF5j/n+6nx0k3mP+f7qfHSTeY/vHSTGARW5j+8dJMYBFbmP5HtfD81XuY/ke18PzVe5j9mZmZmZmbmP2ZmZmZmZuY/O99PjZdu5j8730+Nl27mPxBYObTIduY/EFg5tMh25j/l0CLb+X7mP+XQItv5fuY/ukkMAiuH5j+6SQwCK4fmP4/C9Shcj+Y/j8L1KFyP5j9kO99PjZfmP2Q730+Nl+Y/ObTIdr6f5j85tMh2vp/mPw4tsp3vp+Y/Di2yne+n5j/jpZvEILDmP+Olm8QgsOY/uB6F61G45j+4HoXrUbjmP42XbhKDwOY/jZduEoPA5j9iEFg5tMjmP2IQWDm0yOY/N4lBYOXQ5j83iUFg5dDmPwwCK4cW2eY/DAIrhxbZ5j/hehSuR+HmP+F6FK5H4eY/tvP91Hjp5j+28/3UeOnmP4ts5/up8eY/i2zn+6nx5j9g5dAi2/nmP2Dl0CLb+eY/NV66SQwC5z81XrpJDALnPwrXo3A9Cuc/CtejcD0K5z/fT42XbhLnP99PjZduEuc/tMh2vp8a5z+0yHa+nxrnP4lBYOXQIuc/iUFg5dAi5z9eukkMAivnP166SQwCK+c/MzMzMzMz5z8zMzMzMzPnPwisHFpkO+c/CKwcWmQ75z/dJAaBlUPnP90kBoGVQ+c/sp3vp8ZL5z+yne+nxkvnP4cW2c73U+c/hxbZzvdT5z9cj8L1KFznP1yPwvUoXOc/MQisHFpk5z8xCKwcWmTnPwaBlUOLbOc/BoGVQ4ts5z/b+X5qvHTnP9v5fmq8dOc/sHJoke185z+wcmiR7XznP4XrUbgehec/hetRuB6F5z9aZDvfT43nP1pkO99Pjec/L90kBoGV5z8v3SQGgZXnPwRWDi2ynec/BFYOLbKd5z/ZzvdT46XnP9nO91Pjpec/rkfhehSu5z+uR+F6FK7nP4PAyqFFtuc/g8DKoUW25z9YObTIdr7nP1g5tMh2vuc/LbKd76fG5z8tsp3vp8bnPwIrhxbZzuc/AiuHFtnO5z/Xo3A9CtfnP9ejcD0K1+c/rBxaZDvf5z+sHFpkO9/nP4GVQ4ts5+c/gZVDi2zn5z9WDi2yne/nP1YOLbKd7+c/K4cW2c735z8rhxbZzvfnPwAAAAAAAOg/AAAAAAAA6D/VeOkmMQjoP9V46SYxCOg/qvHSTWIQ6D+q8dJNYhDoP39qvHSTGOg/f2q8dJMY6D9U46WbxCDoP1TjpZvEIOg/KVyPwvUo6D8pXI/C9SjoP/7UeOkmMeg//tR46SYx6D/TTWIQWDnoP9NNYhBYOeg/qMZLN4lB6D+oxks3iUHoP30/NV66Seg/fT81XrpJ6D9SuB6F61HoP1K4HoXrUeg/JzEIrBxa6D8nMQisHFroP/yp8dJNYug//Knx0k1i6D/RItv5fmroP9Ei2/l+aug/ppvEILBy6D+mm8QgsHLoP3sUrkfheug/exSuR+F66D9QjZduEoPoP1CNl24Sg+g/JQaBlUOL6D8lBoGVQ4voP/p+arx0k+g/+n5qvHST6D/P91PjpZvoP8/3U+Olm+g/pHA9Ctej6D+kcD0K16PoP3npJjEIrOg/eekmMQis6D9OYhBYObToP05iEFg5tOg/I9v5fmq86D8j2/l+arzoP/hT46WbxOg/+FPjpZvE6D/NzMzMzMzoP83MzMzMzOg/okW28/3U6D+iRbbz/dToP3e+nxov3eg/d76fGi/d6D9MN4lBYOXoP0w3iUFg5eg/IbByaJHt6D8hsHJoke3oP/YoXI/C9eg/9ihcj8L16D/LoUW28/3oP8uhRbbz/eg/oBov3SQG6T+gGi/dJAbpP3WTGARWDuk/dZMYBFYO6T9KDAIrhxbpP0oMAiuHFuk/H4XrUbge6T8fhetRuB7pP/T91HjpJuk/9P3UeOkm6T/Jdr6fGi/pP8l2vp8aL+k/nu+nxks36T+e76fGSzfpP3Noke18P+k/c2iR7Xw/6T9I4XoUrkfpP0jhehSuR+k/HVpkO99P6T8dWmQ730/pP/LSTWIQWOk/8tJNYhBY6T/HSzeJQWDpP8dLN4lBYOk/nMQgsHJo6T+cxCCwcmjpP3E9CtejcOk/cT0K16Nw6T9GtvP91HjpP0a28/3UeOk/Gy/dJAaB6T8bL90kBoHpP/Cnxks3iek/8KfGSzeJ6T/FILByaJHpP8UgsHJokek/mpmZmZmZ6T+amZmZmZnpP28Sg8DKoek/bxKDwMqh6T9Ei2zn+6npP0SLbOf7qek/GQRWDi2y6T8ZBFYOLbLpP+58PzVeuuk/7nw/NV666T/D9Shcj8LpP8P1KFyPwuk/mG4Sg8DK6T+YbhKDwMrpP23n+6nx0uk/bef7qfHS6T9CYOXQItvpP0Jg5dAi2+k/F9nO91Pj6T8X2c73U+PpP+xRuB6F6+k/7FG4HoXr6T/ByqFFtvPpP8HKoUW28+k/lkOLbOf76T+WQ4ts5/vpP2q8dJMYB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P1KFyPwuE/w/UoXI/C4T+YbhKDwMrhP5huEoPAyuE/bef7qfHS4T9t5/up8dLhP0Jg5dAi2+E/QmDl0CLb4T8X2c73U+PhPxfZzvdT4+E/7FG4HoXr4T/sUbgehevhP8HKoUW28+E/wcqhRbbz4T+WQ4ts5/vhP5ZDi2zn++E/arx0kxgE4j9qvHSTGATiPz81XrpJDOI/PzVeukkM4j8UrkfhehTiPxSuR+F6FOI/6SYxCKwc4j/pJjEIrBziP76fGi/dJOI/vp8aL90k4j+TGARWDi3iP5MYBFYOLeI/aJHtfD814j9oke18PzXiPz0K16NwPeI/PQrXo3A94j8Sg8DKoUXiPxKDwMqhReI/5/up8dJN4j/n+6nx0k3iP7x0kxgEVuI/vHSTGARW4j+R7Xw/NV7iP5HtfD81XuI/ZmZmZmZm4j9mZmZmZmbiPzvfT42XbuI/O99PjZdu4j8QWDm0yHbiPxBYObTIduI/5dAi2/l+4j/l0CLb+X7iP7pJDAIrh+I/ukkMAiuH4j+PwvUoXI/iP4/C9Shcj+I/ZDvfT42X4j9kO99PjZfiPzm0yHa+n+I/ObTIdr6f4j8OLbKd76fiPw4tsp3vp+I/46WbxCCw4j/jpZvEILDiP7gehetRuOI/uB6F61G44j+Nl24Sg8DiP42XbhKDwOI/YhBYObTI4j9iEFg5tMjiPzeJQWDl0OI/N4lBYOXQ4j8MAiuHFtniPwwCK4cW2eI/4XoUrkfh4j/hehSuR+HiP7bz/dR46eI/tvP91Hjp4j+LbOf7qfHiP4ts5/up8eI/YOXQItv54j9g5dAi2/niPzVeukkMAuM/NV66SQwC4z8K16NwPQrjPwrXo3A9CuM/30+Nl24S4z/fT42XbhLjP7TIdr6fGuM/tMh2vp8a4z+JQWDl0CLjP4lBYOXQIuM/XrpJDAIr4z9eukkMAivjPzMzMzMzM+M/MzMzMzMz4z8IrBxaZDvjPwisHFpkO+M/3SQGgZVD4z/dJAaBlUPjP7Kd76fGS+M/sp3vp8ZL4z+HFtnO91PjP4cW2c73U+M/XI/C9Shc4z9cj8L1KFzjPzEIrBxaZOM/MQisHFpk4z8GgZVDi2zjPwaBlUOLbOM/2/l+arx04z/b+X5qvHTjP7ByaJHtfOM/sHJoke184z+F61G4HoXjP4XrUbgeheM/WmQ730+N4z9aZDvfT43jPy/dJAaBleM/L90kBoGV4z8EVg4tsp3jPwRWDi2yneM/2c73U+Ol4z/ZzvdT46XjP65H4XoUruM/rkfhehSu4z+DwMqhRbbjP4PAyqFFtuM/WDm0yHa+4z9YObTIdr7jPy2yne+nxuM/LbKd76fG4z8CK4cW2c7jPwIrhxbZzuM/16NwPQrX4z/Xo3A9CtfjP6wcWmQ73+M/rBxaZDvf4z+BlUOLbOfjP4GVQ4ts5+M/Vg4tsp3v4z9WDi2yne/jPyuHFtnO9+M/K4cW2c734z8AAAAAAADkPwAAAAAAAOQ/1XjpJjEI5D/VeOkmMQjkP6rx0k1iEOQ/qvHSTWIQ5D9/arx0kxjkP39qvHSTGOQ/VOOlm8Qg5D9U46WbxCDkPylcj8L1KOQ/KVyPwvUo5D/+1HjpJjHkP/7UeOkmMeQ/001iEFg55D/TTWIQWDnkP6jGSzeJQeQ/qMZLN4lB5D99PzVeuknkP30/NV66SeQ/UrgehetR5D9SuB6F61HkPycxCKwcWuQ/JzEIrBxa5D/8qfHSTWLkP/yp8dJNYuQ/0SLb+X5q5D/RItv5fmrkP6abxCCwcuQ/ppvEILBy5D97FK5H4XrkP3sUrkfheuQ/UI2XbhKD5D9QjZduEoPkPyUGgZVDi+Q/JQaBlUOL5D/6fmq8dJPkP/p+arx0k+Q/z/dT46Wb5D/P91PjpZvkP6RwPQrXo+Q/pHA9Ctej5D956SYxCKzkP3npJjEIrOQ/TmIQWDm05D9OYhBYObTkPyPb+X5qvOQ/I9v5fmq85D/4U+Olm8TkP/hT46WbxOQ/zczMzMzM5D/NzMzMzMzkP6JFtvP91OQ/okW28/3U5D93vp8aL93kP3e+nxov3eQ/TDeJQWDl5D9MN4lBYOXkPyGwcmiR7eQ/IbByaJHt5D/2KFyPwvXkP/YoXI/C9eQ/y6FFtvP95D/LoUW28/3kP6AaL90kBuU/oBov3SQG5T91kxgEVg7lP3WTGARWDuU/SgwCK4cW5T9KDAIrhxblPx+F61G4HuU/H4XrUbge5T/0/dR46SblP/T91HjpJuU/yXa+nxov5T/Jdr6fGi/lP57vp8ZLN+U/nu+nxks35T9zaJHtfD/lP3Noke18P+U/SOF6FK5H5T9I4XoUrkflPx1aZDvfT+U/HVpkO99P5T/y0k1iEFjlP/LSTWIQWOU/x0s3iUFg5T/HSzeJQWDlP5zEILByaOU/nMQgsHJo5T9xPQrXo3DlP3E9CtejcOU/Rrbz/dR45T9GtvP91HjlPxsv3SQGgeU/Gy/dJAaB5T/wp8ZLN4nlP/Cnxks3ieU/xSCwcmiR5T/FILByaJHlP5qZmZmZmeU/mpmZmZmZ5T9vEoPAyqHlP28Sg8DKoeU/RIts5/up5T9Ei2zn+6nlPxkEVg4tsuU/GQRWDi2y5T/ufD81XrrlP+58PzVeuuU/w/UoXI/C5T/D9Shcj8LlP5huEoPAyuU/mG4Sg8DK5T9t5/up8dLlP23n+6nx0uU/QmDl0CLb5T9CYOXQItvlPxfZzvdT4+U/F9nO91Pj5T/sUbgehevlP+xRuB6F6+U/wcqhRbbz5T/ByqFFtvPlP5ZDi2zn++U/lkOLbOf75T9qvHSTGATmP2q8dJMYBOY/PzVeukkM5j8/NV66SQzmPxSuR+F6FOY/FK5H4XoU5j/pJjEIrBzmP+kmMQisHOY/vp8aL90k5j++nxov3STmP5MYBFYOLeY/kxgEVg4t5j9oke18PzXmP2iR7Xw/NeY/PQrXo3A95j89CtejcD3mPxKDwMqhReY/EoPAyqFF5j/n+6nx0k3mP+f7qfHSTeY/vHSTGARW5j+8dJMYBFbmP5HtfD81XuY/ke18PzVe5j9mZmZmZmbmP2ZmZmZmZuY/O99PjZdu5j8730+Nl27mPxBYObTIduY/EFg5tMh25j/l0CLb+X7mP+XQItv5fuY/ukkMAiuH5j+6SQwCK4fmP4/C9Shcj+Y/j8L1KFyP5j9kO99PjZfmP2Q730+Nl+Y/ObTIdr6f5j85tMh2vp/mPw4tsp3vp+Y/Di2yne+n5j/jpZvEILDmP+Olm8QgsOY/uB6F61G45j+4HoXrUbjmP42XbhKDwOY/jZduEoPA5j9iEFg5tMjmP2IQWDm0yOY/N4lBYOXQ5j83iUFg5dDmPwwCK4cW2eY/DAIrhxbZ5j/hehSuR+HmP+F6FK5H4eY/tvP91Hjp5j+28/3UeOnmP4ts5/up8eY/i2zn+6nx5j9g5dAi2/nmP2Dl0CLb+eY/NV66SQwC5z81XrpJDALnPwrXo3A9Cuc/CtejcD0K5z/fT42XbhLnP99PjZduEuc/tMh2vp8a5z+0yHa+nxrnP4lBYOXQIuc/iUFg5dAi5z9eukkMAivnP166SQwCK+c/MzMzMzMz5z8zMzMzMzPnPwisHFpkO+c/CKwcWmQ75z/dJAaBlUPnP90kBoGVQ+c/sp3vp8ZL5z+yne+nxkvnP4cW2c73U+c/hxbZzvdT5z9cj8L1KFznP1yPwvUoXOc/MQisHFpk5z8xCKwcWmTnPwaBlUOLbOc/BoGVQ4ts5z/b+X5qvHTnP9v5fmq8dOc/sHJoke185z+wcmiR7XznP4XrUbgehec/hetRuB6F5z9aZDvfT43nP1pkO99Pjec/L90kBoGV5z8v3SQGgZXnPwRWDi2ynec/BFYOLbKd5z/ZzvdT46XnP9nO91Pjpec/rkfhehSu5z+uR+F6FK7nP4PAyqFFtuc/g8DKoUW25z9YObTIdr7nP1g5tMh2vuc/LbKd76fG5z8tsp3vp8bnPwIrhxbZzuc/AiuHFtnO5z/Xo3A9CtfnP9ejcD0K1+c/rBxaZDvf5z+sHFpkO9/nP4GVQ4ts5+c/gZVDi2zn5z9WDi2yne/nP1YOLbKd7+c/K4cW2c735z8rhxbZzvfnPwAAAAAAAOg/AAAAAAAA6D/VeOkmMQjoP9V46SYxCOg/qvHSTWIQ6D+q8dJNYhDoP39qvHSTGOg/f2q8dJMY6D9U46WbxCDoP1TjpZvEIOg/KVyPwvUo6D8pXI/C9SjoP/7UeOkmMeg//tR46SYx6D/TTWIQWDnoP9NNYhBYOeg/qMZLN4lB6D+oxks3iUHoP30/NV66Seg/fT81XrpJ6D9SuB6F61HoP1K4HoXrUeg/JzEIrBxa6D8nMQisHFroP/yp8dJNYug//Knx0k1i6D/RItv5fmroP9Ei2/l+aug/ppvEILBy6D+mm8QgsHLoP3sUrkfheug/exSuR+F66D9QjZduEoPoP1CNl24Sg+g/JQaBlUOL6D8lBoGVQ4voP/p+arx0k+g/+n5qvHST6D/P91PjpZvoP8/3U+Olm+g/pHA9Ctej6D+kcD0K16PoP3npJjEIrOg/eekmMQis6D9OYhBYObToP05iEFg5tOg/I9v5fmq86D8j2/l+arzoP/hT46WbxOg/+FPjpZvE6D/NzMzMzMzoP83MzMzMzOg/okW28/3U6D+iRbbz/dToP3e+nxov3eg/d76fGi/d6D9MN4lBYOXoP0w3iUFg5eg/IbByaJHt6D8hsHJoke3oP/YoXI/C9eg/9ihcj8L16D/LoUW28/3oP8uhRbbz/eg/oBov3SQG6T+gGi/dJAbpP3WTGARWDuk/dZMYBFYO6T9KDAIrhxbpP0oMAiuHFuk/H4XrUbge6T8fhetRuB7pP/T91HjpJuk/9P3UeOkm6T/Jdr6fGi/pP8l2vp8aL+k/nu+nxks36T+e76fGSzfpP3Noke18P+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kQA2e9y8I/QBc0G/7Vwj9AFzQb/tXCP6WD6ZR6EcM/pYPplHoRwz8wTJcEFivEPzBMlwQWK8Q/7zhcERBGxD/vOFwREEbEP/A4DEXLSsQ/8DgMRctKxD9xBfkP6lnEP3EF+Q/qWcQ/+OEI2wSkxD/44QjbBKTEP10Jy2EWqcQ/XQnLYRapxD/+iqm3DAjFP/6KqbcMCMU/zHazbrIhxT/MdrNusiHFPzCP4mn0TcU/MI/iafRNxT+onXyg7HHFP6idfKDsccU/OIEtrNWLxT84gS2s1YvFP3r4YHg2mMU/evhgeDaYxT/NVpKoW6nFP81WkqhbqcU/nWZTPeqtxT+dZlM96q3FPyLpz+1Vv8U/IunP7VW/xT+7dNu5+cDFP7t027n5wMU/jgDtmi/RxT+OAO2aL9HFPycVB9x4PsY/JxUH3Hg+xj/WmRYwm0vGP9aZFjCbS8Y/nYWgl5Zxxj+dhaCXlnHGPwLd9wD9gcY/At33AP2Bxj+fDhW9QqfGP58OFb1Cp8Y/LcOAG7m1xj8tw4AbubXGPz9ekuPrwMY/P16S4+vAxj/Szyf9DdTGP9LPJ/0N1MY/KYAxsWfUxj8pgDGxZ9TGP2CeKl6YJsc/YJ4qXpgmxz/6g47ID0PHP/qDjsgPQ8c/24OBRedVxz/bg4FF51XHPyssrrU7Vsc/KyyutTtWxz+3N/fqTJLHP7c39+pMksc/Hkw2e8K3xz8eTDZ7wrfHP3mlZMoF0sc/eaVkygXSxz/2s/7eFfHHP/az/t4V8cc/DwGVSul3yD8PAZVK6XfIPybONGd6kcg/Js40Z3qRyD9bBMQF9pXIP1sExAX2lcg/3FhhSnPJyD/cWGFKc8nIPyI/PQuw/Mg/Ij89C7D8yD/gm1Da1hnJP+CbUNrWGck/e4TMKBkoyT97hMwoGSjJPziXWwgELsk/OJdbCAQuyT+JmGE/QWzJP4mYYT9BbMk/DklT9ZVtyT8OSVP1lW3JP0fyxRbQeck/R/LFFtB5yT8aCei+uKbJPxoJ6L64psk/aMzPWubRyT9ozM9a5tHJPxixFFDv5Mk/GLEUUO/kyT8Y4ySZYDTKPxjjJJlgNMo/C2VhQNpqyj8LZWFA2mrKP0QUF/owm8o/RBQX+jCbyj9tPepDtKrKP2096kO0qso/uB/t87atyj+4H+3ztq3KP35oTtGUy8o/fmhO0ZTLyj9Q/C68c8/KP1D8Lrxzz8o/FT8B0PrVyj8VPwHQ+tXKP2wO2ZluX8s/bA7ZmW5fyz9gJLW0vWjLP2AktbS9aMs/KqHd4EZ5yz8qod3gRnnLP80tU37kpss/zS1TfuSmyz+oI80z7fHLP6gjzTPt8cs/PIuQatf8yz88i5Bq1/zLP8r1owlQDsw/yvWjCVAOzD+VcGDvKBPMP5VwYO8oE8w/YEwxh89qzD9gTDGHz2rMP6LKFJQNjsw/osoUlA2OzD/vHOyYaazMP+8c7JhprMw/A2LZCxTMzD8DYtkLFMzMP99lsoAX1cw/32WygBfVzD+3Ejdtk/jMP7cSN22T+Mw/xv3A40JFzT/G/cDjQkXNP0xTJsKYSs0/TFMmwphKzT8pg/cwBVLNPymD9zAFUs0/lidaQzhozT+WJ1pDOGjNP3MZrpEvi80/cxmukS+LzT/r7u15Z5rNP+vu7Xlnms0/ElmOs933zT8SWY6z3ffNPzDjtbfcJ84/MOO1t9wnzj/ofyrN2ErOP+h/Ks3YSs4/hxvVxEZMzj+HG9XERkzOP//5BFuQhM4///kEW5CEzj8vpKVff4bOPy+kpV9/hs4/+9elhFbKzj/716WEVsrOP2FnyTvRF88/YWfJO9EXzz9ebvn23TTPP15u+fbdNM8/zhVLokSXzz/OFUuiRJfPP9uCm1twmc8/24KbW3CZzz+JfQcSjaDPP4l9BxKNoM8/iKKIJsDxzz+IoogmwPHPPwTQeklQ/88/BNB6SVD/zz98wJWHlgbQP3zAlYeWBtA/MwEcoTYT0D8zARyhNhPQPyxtC48rRNA/LG0LjytE0D+i+nYJHXrQP6L6dgkdetA/G/L7v9F+0D8b8vu/0X7QP77yTcbeiNA/vvJNxt6I0D9kKBUNh5fQP2QoFQ2Hl9A/bS1E3Jum0D9tLUTcm6bQPyC2LOssuNA/ILYs6yy40D8/kFhf29PQPz+QWF/b09A/0/1L/i7d0D/T/Uv+Lt3QP4a3VwZy6tA/hrdXBnLq0D/LhqKRg/HQP8uGopGD8dA/cl4KpasU0T9yXgqlqxTRP5QvsR6VJdE/lC+xHpUl0T9XZvsJsDvRP1dm+wmwO9E/8gO6nPNH0T/yA7qc80fRPxnwjPoSYdE/GfCM+hJh0T8JbTUBFnLRPwltNQEWctE/7akJqgV80T/tqQmqBXzRP2+w1gbsmdE/b7DWBuyZ0T9xX0GnFZ/RP3FfQacVn9E/RrdVy7+k0T9Gt1XLv6TRPwXZRzY+v9E/BdlHNj6/0T8FPVud0M3RPwU9W53QzdE/0OJBv7vj0T/Q4kG/u+PRP7qZen3I5NE/upl6fcjk0T+cmwvKch3SP5ybC8pyHdI/MLyac1Jy0j8wvJpzUnLSPxhuzHUIgNI/GG7MdQiA0j/Q1/HJpp/SP9DX8cmmn9I/l8fVaSSg0j+Xx9VpJKDSP/m2u9bYuNI/+ba71ti40j8xqcwkoxXTPzGpzCSjFdM/gYWW91kc0z+BhZb3WRzTP4lnnLr/ItM/iWecuv8i0z9jKZWK3CfTP2MplYrcJ9M/fc2MLRIt0z99zYwtEi3TP88Ae+XLLdM/zwB75cst0z+ZdKL6o1HTP5l0ovqjUdM/aDV1mQZb0z9oNXWZBlvTP2TJlftHdNM/ZMmV+0d00z+tiOSoBY7TP62I5KgFjtM/gjN/lLKh0z+CM3+UsqHTP+jzPdWwr9M/6PM91bCv0z9H8hTPvLrTP0fyFM+8utM/bgLk6Ey70z9uAuToTLvTPwYYnh4LvdM/BhieHgu90z9mgHhSjtPTP2aAeFKO09M/Oa828lDa0z85rzbyUNrTPyS16kgn29M/JLXqSCfb0z98cNDnlfbTP3xw0OeV9tM/jJR+YND60z+MlH5g0PrTP+UbFm6JENQ/5RsWbokQ1D8zCRHOsyjUPzMJEc6zKNQ/wHviK5My1D/Ae+IrkzLUPw9KjNStTNQ/D0qM1K1M1D/Bj2vGE1DUP8GPa8YTUNQ/tmUHa+F21D+2ZQdr4XbUPyhr2S4Pi9Q/KGvZLg+L1D+YaiYrQovUP5hqJitCi9Q/jNaGJZCL1D+M1oYlkIvUP8eTgHIIlNQ/x5OAcgiU1D80hLEshJjUPzSEsSyEmNQ/Z1lJctCY1D9nWUly0JjUPynVKWWhq9Q/KdUpZaGr1D8TRSomFa3UPxNFKiYVrdQ/ZNp6kKY81T9k2nqQpjzVP8yjcEaEStU/zKNwRoRK1T/fIkMFD0vVP98iQwUPS9U/hGw3JQVV1T+EbDclBVXVPypf30bsXNU/Kl/fRuxc1T88mmSLSWPVPzyaZItJY9U/XbHxUIt91T9dsfFQi33VP+xn9woKiNU/7Gf3CgqI1T8Geheeb5zVPwZ6F55vnNU/xl8SmpHe1T/GXxKakd7VPzpX82HP5NU/OlfzYc/k1T++MjydrvrVP74yPJ2u+tU/mP3tesUI1j+Y/e16xQjWP1CWwsKQF9Y/UJbCwpAX1j8Jv2rG5iXWPwm/asbmJdY/VxyeSCQo1j9XHJ5IJCjWP47tO1rgNtY/ju07WuA21j9qfmTAVznWP2p+ZMBXOdY/qJpq9RNR1j+ommr1E1HWPweIsnNsWNY/B4iyc2xY1j9WpUndV13WP1alSd1XXdY/V9TSZpJr1j9X1NJmkmvWPwb0h/69b9Y/BvSH/r1v1j+PgybQUYfWP4+DJtBRh9Y/Pscjrt6W1j8+xyOu3pbWP4IZ5YV3p9Y/ghnlhXen1j/9XPQhjLnWP/1c9CGMudY/dchd7pvT1j91yF3um9PWP6OuHbCE2tY/o64dsITa1j8t114KaOzWPy3XXgpo7NY/7mq4K0r81j/uargrSvzWP69zjMVi/NY/r3OMxWL81j+YlBvOyQXXP5iUG87JBdc/N7rV67pS1z83utXrulLXPxlG08QCXdc/GUbTxAJd1z86ptEnKXPXPzqm0Scpc9c/EU/UVBJ71z8RT9RUEnvXP5UM+Gf6otc/lQz4Z/qi1z8Rppj4m7rXPxGmmPibutc/c40Eka7E1z9zjQSRrsTXPxHCUQus9Nc/EcJRC6z01z9v/1cHl/7XP2//VweX/tc/gPrwxZ8B2D+A+vDFnwHYP5xoznKfC9g/nGjOcp8L2D+KtOCI2xvYP4q04IjbG9g/RXGzogg42D9FcbOiCDjYPxAVpGwhOtg/EBWkbCE62D+nKwcoxGjYP6crByjEaNg/2kajNi6D2D/aRqM2LoPYP9mLthP8idg/2Yu2E/yJ2D/QgDDzT5PYP9CAMPNPk9g/mO5tALiV2D+Y7m0AuJXYP255fT6amNg/bnl9PpqY2D+2sj4OCqPYP7ayPg4Ko9g/L/RRhE2t2D8v9FGETa3YP7oIAiNBu9g/uggCI0G72D+4Uq8WFAHZP7hSrxYUAdk/ift38LIX2T+J+3fwshfZP+POhtlpGtk/486G2Wka2T+HClZiYSTZP4cKVmJhJNk/GasGkacv2T8ZqwaRpy/ZP4H6xv69X9k/gfrG/r1f2T8itrh0EmvZPyK2uHQSa9k/vKlo/U542T+8qWj9TnjZP78hyPmpgdk/vyHI+amB2T+EYlB1prHZP4RiUHWmsdk/bh5LAUPo2T9uHksBQ+jZP3dg3SVT8tk/d2DdJVPy2T9VXAnUjCTaP1VcCdSMJNo/qmlYxnEz2j+qaVjGcTPaP46YZHafldo/jphkdp+V2j/43on2Aq7aP/jeifYCrto/Xy7szd3C2j9fLuzN3cLaP6cwU3Skyto/pzBTdKTK2j8FOtufY83aPwU6259jzdo/o/qrqljO2j+j+quqWM7aP2wqHA1h09o/bCocDWHT2j+e1dRBeNjaP57V1EF42No/QCv0pun02j9AK/Sm6fTaP2zmCmCsCds/bOYKYKwJ2z/fWew6njvbP99Z7DqeO9s/nfA5tWE92z+d8Dm1YT3bP/AsDjAKTNs/8CwOMApM2z/ptc7raVPbP+m1zutpU9s/zAcYQklZ2z/MBxhCSVnbP9uHXe6jWts/24dd7qNa2z8YgscQI1vbPxiCxxAjW9s/+WTUKZBn2z/5ZNQpkGfbPwaSlJArc9s/BpKUkCtz2z+pTKsjdp3bP6lMqyN2nds/GmE/Injh2z8aYT8ieOHbPyjhqJDJ49s/KOGokMnj2z930ugP9gTcP3fS6A/2BNw/H/iZ1g813D8f+JnWDzXcP8pC3AZ7Rtw/ykLcBntG3D8F+3ci80vcPwX7dyLzS9w/8w52aJ9l3D/zDnZon2XcP1+Ml6Q+atw/X4yXpD5q3D8wxX7UWqfcPzDFftRap9w/WKEoX8es3D9YoShfx6zcP4fRhSuT6Nw/h9GFK5Po3D8PBLiYAu3cPw8EuJgC7dw/VrITwRME3T9WshPBEwTdP/OY74CpK90/85jvgKkr3T//U20/+SzdP/9TbT/5LN0/Et9FmFcz3T8S30WYVzPdPy9RUf/qQd0/L1FR/+pB3T9NBrqz12vdP00GurPXa90/ClqQ1lWy3T8KWpDWVbLdP5Dv7nnV3t0/kO/uedXe3T+0nShTaQPeP7SdKFNpA94/KgG8NR8o3j8qAbw1HyjeP1gKdbb1Qd4/WAp1tvVB3j+XDTeDUVHeP5cNN4NRUd4/Tq5UnzZX3j9OrlSfNlfeP7Ef+mIVXN4/sR/6YhVc3j//3ZkFE2TeP//dmQUTZN4/k+UKJD1m3j+T5QokPWbeP2nYG3/6dt4/adgbf/p23j+8QbY7dZbeP7xBtjt1lt4/gjHz/5ym3j+CMfP/nKbeP3DklRJR5N4/cOSVElHk3j/8mgs4P+neP/yaCzg/6d4/KNq3Zdfy3j8o2rdl1/LeP92HXCVd/94/3YdcJV3/3j/8TCf+jxDfP/xMJ/6PEN8/Gi7XFXwV3z8aLtcVfBXfPy8wvlbhMt8/LzC+VuEy3z/w7f/BPz7fP/Dt/8E/Pt8/KJLw1wNP3z8okvDXA0/fP1mPmDlHZ98/WY+YOUdn3z/4dwDcDGnfP/h3ANwMad8/hmGaNVOF3z+GYZo1U4XfP83a2tg1kt8/zdra2DWS3z9+hNoUkJLfP36E2hSQkt8/p+ZhDHeW3z+n5mEMd5bfP1SE5wbEuN8/VITnBsS43z9oNrj9IcXfP2g2uP0hxd8/JIdFV/XJ3z8kh0VX9cnfP/UrlyN61d8/9SuXI3rV3z+KHi1BjOTfP4oeLUGM5N8/kwxxcGv13z+TDHFwa/XfPx7SkbTxAeA/HtKRtPEB4D+TllU2egLgP5OWVTZ6AuA/Cku0gjoR4D8KS7SCOhHgPwvp6sw2GeA/C+nqzDYZ4D/XWyoGSB3gP9dbKgZIHeA/jx2f60Ef4D+PHZ/rQR/gP5r8fyvHLeA/mvx/K8ct4D+h7iFTuS/gP6HuIVO5L+A/9dMWNP9N4D/10xY0/03gP0qFhhL4YOA/SoWGEvhg4D/biurOfWHgP9uK6s59YeA/+3NNqLVn4D/7c02otWfgPyDI6AvybOA/IMjoC/Js4D/PcYHsWG7gP89xgexYbuA/E2iOZbZ84D8TaI5ltnzgPzsbnrglf+A/OxueuCV/4D+/Kfrp5JXgP78p+unkleA/PI9tWISc4D88j21YhJzgPxgV1C7LnuA/GBXULsue4D/171oFr63gP/XvWgWvreA/nAypJ46y4D+cDKknjrLgP2FK16PD0eA/YUrXo8PR4D9rV1h8g9fgP2tXWHyD1+A/9Etd/pza4D/0S13+nNrgPzgvyNPc3+A/OC/I09zf4D+b8BEUWO/gP5vwERRY7+A/yszwhP3x4D/KzPCE/fHgP5qKOsqP/uA/moo6yo/+4D904u5S7QDhP3Ti7lLtAOE/nESLnikj4T+cRIueKSPhP3XXVm+/NOE/dddWb7804T8ZRaKsMTjhPxlFoqwxOOE/yPgfQhU94T/I+B9CFT3hP7hB4PO1UuE/uEHg87VS4T9/fFcsqFjhP398VyyoWOE/DTMr3Rlv4T8NMyvdGW/hPxWLPewcieE/FYs97ByJ4T9UFYhgHY3hP1QViGAdjeE/OoQx9yu14T86hDH3K7XhPyOpev85teE/I6l6/zm14T/BrELS5rXhP8GsQtLmteE/DOV6x6K24T8M5XrHorbhP0azZmn7wuE/RrNmafvC4T+Uk0VECcThP5STRUQJxOE/ayf1XjLU4T9rJ/VeMtThP4kYdcE21uE/iRh1wTbW4T9bwR0RyerhP1vBHRHJ6uE/5sWi4kvv4T/mxaLiS+/hP677VY2a7+E/rvtVjZrv4T8Xn0V7IfLhPxefRXsh8uE/f0XrvX/z4T9/Reu9f/PhP8/5v9twB+I/z/m/23AH4j/7sFil9AriP/uwWKX0CuI/ex2gfpoL4j97HaB+mgviP5bBhm+3I+I/lsGGb7cj4j94lWcWmy/iP3iVZxabL+I/i/A1c7Q+4j+L8DVztD7iP3is7V5uUuI/eKztXm5S4j+/1xJ/6VTiP7/XEn/pVOI/ZtsGG3ld4j9m2wYbeV3iP8BHtfdiY+I/wEe192Jj4j+OFCAvfmfiP44UIC9+Z+I/I8ROXQt+4j8jxE5dC37iPx6+rcdpnOI/Hr6tx2mc4j9vneqc3J7iP2+d6pzcnuI/ZfxwmC+n4j9l/HCYL6fiP0yGqgGvqOI/TIaqAa+o4j8RkmWQhaziPxGSZZCFrOI/amhArVmw4j9qaECtWbDiP12G2Najt+I/XYbY1qO34j9Lb7LAo7riP0tvssCjuuI/aYMT6tLJ4j9pgxPq0sniPzJwxHVIyuI/MnDEdUjK4j87mchHk9TiPzuZyEeT1OI/3Z4fAm/i4j/dnh8Cb+LiPz/NCG7+4uI/P80Ibv7i4j+AoOyt8ubiP4Cg7K3y5uI/pzv9m7by4j+nO/2btvLiP3G5HaFl/OI/cbkdoWX84j/OsBjEsvziP86wGMSy/OI/0Hy8ywMO4z/QfLzLAw7jP/mCMLy7DuM/+YIwvLsO4z/w22ghGhfjP/DbaCEaF+M/jun/Ld0Z4z+O6f8t3RnjPxB2BLsUHuM/EHYEuxQe4z9biBpmgDLjP1uIGmaAMuM/Xe3Y1bA14z9d7djVsDXjP0MCnpi3NuM/QwKemLc24z8XgDMEEEPjPxeAMwQQQ+M/ZNEQXQhE4z9k0RBdCETjP6uflTZ9TeM/q5+VNn1N4z/b+fZBa1HjP9v59kFrUeM/n6v0Rw1o4z+fq/RHDWjjPzVVh+BkeuM/NVWH4GR64z/ePSknSXzjP949KSdJfOM/sHMQK62K4z+wcxArrYrjP5liRMWvnuM/mWJExa+e4z+OdaIutKvjP451oi60q+M/nGBBWoy24z+cYEFajLbjP6Lve0PLu+M/ou97Q8u74z/uX91PmszjP+5f3U+azOM/MpDB2Eni4z8ykMHYSeLjP0nl8aFv9+M/SeXxoW/34z8y/hNpdfjjPzL+E2l1+OM/8t1VW4ME5D/y3VVbgwTkPzZ4fuSeBeQ/Nnh+5J4F5D85GldDBRbkPzkaV0MFFuQ/DROMdLc05D8NE4x0tzTkPy8AWyDuROQ/LwBbIO5E5D8089rEDUrkPzTz2sQNSuQ/fVW5aVBc5D99VblpUFzkP8Jok3FbYuQ/wmiTcVti5D9ZG0TiwWbkP1kbROLBZuQ/Y8oDYXCT5D9jygNhcJPkP1Osmxvxm+Q/U6ybG/Gb5D+zNunaM57kP7M26doznuQ/RvWgz32z5D9G9aDPfbPkP6sKsuZovOQ/qwqy5mi85D9ixp//cb3kP2LGn/9xveQ/JuBatEDE5D8m4Fq0QMTkP4WYy7XtzOQ/hZjLte3M5D+q9Q2cU9HkP6r1DZxT0eQ/213nb6ne5D/bXedvqd7kP7rdVsUE3+Q/ut1WxQTf5D/epytMYe7kP96nK0xh7uQ/NhZCp+/z5D82FkKn7/PkPwNT5ouO/OQ/A1Pmi4785D/q6hlBDwHlP+rqGUEPAeU/vrf0Ro0I5T++t/RGjQjlP8qMZcIGDuU/yoxlwgYO5T/PBE1/ng7lP88ETX+eDuU/ebr+QX0R5T95uv5BfRHlP+1DOZG/FuU/7UM5kb8W5T/DjXnmwxblP8ONeebDFuU/JKfJRgEk5T8kp8lGASTlP/HoCT//NuU/8egJP/825T/XSODNaD7lP9dI4M1oPuU/qH+HylU/5T+of4fKVT/lPwm+zfcFTeU/Cb7N9wVN5T+uIJI/oGzlP64gkj+gbOU/1lJQLLV+5T/WUlAstX7lP+gaSpsfguU/6BpKmx+C5T8EiB1Je4nlPwSIHUl7ieU/nGnAMFyS5T+cacAwXJLlPxW3Cu6qmuU/FbcK7qqa5T/dkqcMR7LlP92SpwxHsuU/pbnUMevF5T+ludQx68XlPze8uQyHyOU/N7y5DIfI5T/giOJEUdTlP+CI4kRR1OU/DYl8Ad3V5T8NiXwB3dXlPxOz+KJY2OU/E7P4oljY5T/VTVAdu9rlP9VNUB272uU/yhdEcMna5T/KF0RwydrlP3fA1pnX3+U/d8DWmdff5T9OHszVQeHlP04ezNVB4eU/vAIurInu5T+8Ai6sie7lP7l9bjJW7+U/uX1uMlbv5T+QBu3lPfTlP5AG7eU99OU/vIxgFMn75T+8jGAUyfvlPzW//DDB/eU/Nb/8MMH95T8zs6woegHmPzOzrCh6AeY/q+HqqwUD5j+r4eqrBQPmP30xkI39CuY/fTGQjf0K5j/0kOy8axPmP/SQ7LxrE+Y/LXyjzp0j5j8tfKPOnSPmP6OXU3aaK+Y/o5dTdpor5j+UqNTimDnmP5So1OKYOeY/glnyDRI95j+CWfINEj3mP38eQNiUPuY/fx5A2JQ+5j8eFF0XY0nmPx4UXRdjSeY/ozLPauJS5j+jMs9q4lLmP3zVk0tPWuY/fNWTS09a5j9eFiRQTFvmP14WJFBMW+Y/i/n+WCVy5j+L+f5YJXLmPzvh6/C+c+Y/O+Hr8L5z5j/bAlABVnTmP9sCUAFWdOY/s1KDIUR25j+zUoMhRHbmPycHAX0/g+Y/JwcBfT+D5j/UFzLyiIrmP9QXMvKIiuY/OLVM/fSK5j84tUz99IrmP34+LoV2juY/fj4uhXaO5j/zfTIuc5TmP/N9Mi5zlOY/ez/9Ps+a5j97P/0+z5rmPx7CTXn1oeY/HsJNefWh5j9jxX7G3LPmP2PFfsbcs+Y/cSwgBO655j9xLCAE7rnmP/AwLERGu+Y/8DAsREa75j/Fh8FyiMrmP8WHwXKIyuY/6sVeheDQ5j/qxV6F4NDmPyAM2jUR0+Y/IAzaNRHT5j8nG8yqo9XmPycbzKqj1eY/itWRNKDa5j+K1ZE0oNrmP8T9ptFt5OY/xP2m0W3k5j9fnKRVhe7mP1+cpFWF7uY/BwkbDJz55j8HCRsMnPnmP7gD+nwR/eY/uAP6fBH95j+1V77ZBwLnP7VXvtkHAuc/MIeNkMUD5z8wh42QxQPnP6pVjf/OI+c/qlWN/84j5z/t1zM66C/nP+3XMzroL+c/HOiTBP4x5z8c6JME/jHnP7ooIV5PNOc/uighXk805z8FYU8U1DbnPwVhTxTUNuc/Lbcjn5Y35z8ttyOfljfnPxv70irjOec/G/vSKuM55z9/Xuel2DrnP39e56XYOuc/neXdy85L5z+d5d3LzkvnP6P3uOkzWec/o/e46TNZ5z/7GpmOzGHnP/samY7MYec/FwoNaEFl5z8XCg1oQWXnP6zhtPGxbuc/rOG08bFu5z+461UZkHDnP7jrVRmQcOc/+Crd+0p85z/4Kt37SnznPwPM3ixSguc/A8zeLFKC5z8i4PGWC4PnPyLg8ZYLg+c/GB93vciG5z8YH3e9yIbnP8D7S2Q9kOc/wPtLZD2Q5z8Rx2/7+5vnPxHHb/v7m+c/kO8MEZ+k5z+Q7wwRn6TnP/Pahybxquc/89qHJvGq5z+Rk+fzN6/nP5GT5/M3r+c/M2fXtaCv5z8zZ9e1oK/nPxetkSBxsuc/F62RIHGy5z8hiZmnLb7nPyGJmactvuc/bpQV3rO+5z9ulBXes77nP/mIOrLiw+c/+Yg6suLD5z/MBdXP+sTnP8wF1c/6xOc//LOvR4LU5z/8s69HgtTnP/GiA0Q11ec/8aIDRDXV5z+YFfBnVdXnP5gV8GdV1ec/vQ1rIcTj5z+9DWshxOPnP7M9DQ+8Aug/sz0ND7wC6D9//0X46QLoP3//RfjpAug/gpAVUvoJ6D+CkBVS+gnoP2RV/fccDeg/ZFX99xwN6D9plF0IgRXoP2mUXQiBFeg/+b0iDooh6D/5vSIOiiHoP0jZgwORIeg/SNmDA5Eh6D+QgIz+ISPoP5CAjP4hI+g/7ZONPr4j6D/tk40+viPoP8HRuINGJ+g/wdG4g0Yn6D/o2bBRgCjoP+jZsFGAKOg/kAoawtct6D+QChrC1y3oP90jmgqoMOg/3SOaCqgw6D95WzRs8TfoP3lbNGzxN+g/wEj3eDs56D/ASPd4OznoP+0SvthpOug/7RK+2Gk66D/hzuiN50boP+HO6I3nRug/KpssJ/BJ6D8qmywn8EnoP9ApZ8QGUug/0ClnxAZS6D+5q3sUlFfoP7mrexSUV+g/mV7QH79Y6D+ZXtAfv1joP+Ob/Ko2YOg/45v8qjZg6D+MRRLszGfoP4xFEuzMZ+g/W/O8vRF66D9b87y9EXroPyuQaIefhug/K5Boh5+G6D8FlfFZV4noPwWV8VlXieg/FYzTjiql6D8VjNOOKqXoP4RefN/Rq+g/hF5839Gr6D+bFi5JCa7oP5sWLkkJrug/d1c1u2av6D93VzW7Zq/oPwPjTPRGv+g/A+NM9Ea/6D+P/Zr6XMDoP4/9mvpcwOg/Ax/+vCTD6D8DH/68JMPoP6/0op1X0Og/r/SinVfQ6D/zOgqAw9HoP/M6CoDD0eg/sydeocvU6D+zJ16hy9ToPzjL2jHq4eg/OMvaMerh6D9mukoyOefoP2a6SjI55+g/2zdNEhzp6D/bN00SHOnoP+jFfUXR7Og/6MV9RdHs6D+G3U8zje7oP4bdTzON7ug/cWSoXkzv6D9xZKheTO/oP9jkuiJ3+ug/2OS6Inf66D9+98qZzwDpP373ypnPAOk/JMMdLnMC6T8kwx0ucwLpP1qHdOzBBuk/Wod07MEG6T9parIVXwfpP2lqshVfB+k/5YYUnZoW6T/lhhSdmhbpP/JxGWLGG+k/8nEZYsYb6T/MG/f/Ex/pP8wb9/8TH+k/Kg1jnJUg6T8qDWOclSDpP3wLtV9eJuk/fAu1X14m6T8upS1pEjXpPy6lLWkSNek/bEFlQ1816T9sQWVDXzXpPzvVqJlnP+k/O9WomWc/6T9yH5t36UPpP3Ifm3fpQ+k/RDPvGYpI6T9EM+8ZikjpP7QnxvTfSuk/tCfG9N9K6T8vyJDW/ErpPy/IkNb8Suk/Dly2vRlR6T8OXLa9GVHpP4SeQuERWOk/hJ5C4RFY6T91eMQvgljpP3V4xC+CWOk/08E2DmVc6T/TwTYOZVzpP9L7QMrBXek/0vtAysFd6T9mHNszv2/pP2Yc2zO/b+k/Q4HEimp96T9DgcSKan3pP9QCrhwAquk/1AKuHACq6T/5fFrfbK/pP/l8Wt9sr+k/mOaMsiay6T+Y5oyyJrLpP9IudTXvs+k/0i51Ne+z6T8JpOq54bbpPwmk6rnhtuk/FW98XBa56T8Vb3xcFrnpP7ntF8EoyOk/ue0XwSjI6T/zDpc2XcjpP/MOlzZdyOk/ktc1rVTJ6T+S1zWtVMnpP6J9HBCiyuk/on0cEKLK6T9ziQjb+szpP3OJCNv6zOk/vjZeavnP6T++Nl5q+c/pPzuGrXcG2Ok/O4atdwbY6T+bk9QONNzpP5uT1A403Ok/oxL7TV7c6T+jEvtNXtzpPz/pdpyZ6Ok/P+l2nJno6T+bKVgqUunpP5spWCpS6ek/ksII3gPu6T+SwgjeA+7pPxU6HPpf7uk/FToc+l/u6T94LtWZi+7pP3gu1ZmL7uk/k2QgzGr06T+TZCDMavTpP4oULy8Y9uk/ihQvLxj26T/VUV43n/vpP9VRXjef++k/6V7dIlH+6T/pXt0iUf7pP2hmEPgBBOo/aGYQ+AEE6j8Tn4xc9gbqPxOfjFz2Buo/r8BA0zYI6j+vwEDTNgjqP5fl0v0cCeo/l+XS/RwJ6j/2DOJ4CxTqP/YM4ngLFOo/1rO7VR8U6j/Ws7tVHxTqPzG2jybSKeo/MbaPJtIp6j87OWmX+CvqPzs5aZf4K+o/FP7b2Nwu6j8U/tvY3C7qP4aOaGDANeo/ho5oYMA16j+jEGgrgUTqP6MQaCuBROo/19Z2XrhF6j/X1nZeuEXqP0tdNRvgSuo/S101G+BK6j9ZjleM/lHqP1mOV4z+Ueo/n5TL0w5Y6j+flMvTDljqP69SgLEHXOo/r1KAsQdc6j92S0cly17qP3ZLRyXLXuo/pQ+UtBBo6j+lD5S0EGjqP0rKEoYuaeo/SsoShi5p6j/MevYXK4fqP8x69hcrh+o/U2btglGJ6j9TZu2CUYnqP/QRRUYLiuo/9BFFRguK6j8WY6CeyozqPxZjoJ7KjOo/iB7qryuT6j+IHuqvK5PqP7UjbJ8Uluo/tSNsnxSW6j8tP3xI8ZnqPy0/fEjxmeo/cw2ivn6q6j9zDaK+fqrqP19RjQzUq+o/X1GNDNSr6j85s0LSmqzqPzmzQtKarOo/lIhBzUmv6j+UiEHNSa/qP8Dw9s18s+o/wPD2zXyz6j+miO+ShbXqP6aI75KFteo/wwEgup666j/DASC6nrrqP8kEywxCu+o/yQTLDEK76j/Optyvc7vqP86m3K9zu+o/9oHn1fvH6j/2gefV+8fqPz6XxEGMy+o/PpfEQYzL6j+nXtVAhdHqP6de1UCF0eo/Fyt6xIPT6j8XK3rEg9PqP1Bx2Dob1+o/UHHYOhvX6j/sjssAA9jqP+yOywAD2Oo/XtCk1tDn6j9e0KTW0OfqP7zxh7C/6uo/vPGHsL/q6j/W5RNrFPDqP9blE2sU8Oo/xVK2Jgv76j/FUrYmC/vqP4dCQ0KVB+s/h0JDQpUH6z9q+WbyyBPrP2r5ZvLIE+s/m3T2NKMj6z+bdPY0oyPrP7HMdI3YLus/scx0jdgu6z9Pfq7ATDDrP09+rsBMMOs//Y/phTI16z/9j+mFMjXrPxQ/HD0QOOs/FD8cPRA46z+7m3nhbTvrP7ubeeFtO+s/FnNyKHtB6z8Wc3Ioe0HrPz0ULrrPQus/PRQuus9C6z/xbgBQ1ELrP/FuAFDUQus/wJ3dSlND6z/And1KU0PrP6yPIMqLTus/rI8gyotO6z8oB0i1n0/rPygHSLWfT+s/KqgNMvZS6z8qqA0y9lLrP1TjonSRY+s/VOOidJFj6z90VdKVhnPrP3RV0pWGc+s/NLfZKnR16z80t9kqdHXrP5tVwPa3eus/m1XA9rd66z+LOf2Tv33rP4s5/ZO/fes/RPTZBSB+6z9E9NkFIH7rP3/8bTMrhOs/f/xtMyuE6z+1ArJpXIfrP7UCsmlch+s/SAs016WN6z9ICzTXpY3rP7BwwuP0k+s/sHDC4/ST6z/oF35ZNJXrP+gXflk0les/LrifO9aZ6z8uuJ871pnrP5WIIq0+m+s/lYgirT6b6z9U4Btvq53rP1TgG2+rnes/HSxfFd6l6z8dLF8V3qXrP9XR2V4kq+s/1dHZXiSr6z9haRtIkq7rP2FpG0iSrus/yS6KBfq36z/JLooF+rfrP2o4JiaUw+s/ajgmJpTD6z9YBW7fCcjrP1gFbt8JyOs/T+SEiRXI6z9P5I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root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " let attempts = 0;\n", " const timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " clearInterval(timer);\n", " embed_document(root);\n", " } else {\n", " attempts++;\n", " if (attempts > 100) {\n", " clearInterval(timer);\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " }\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "p1705" } }, "output_type": "display_data" } ], "source": [ "# Make tidy data frames for convenient plotting\n", "df_p = pl.DataFrame(data=p_vals, schema=[\"n = \" + str(n) for n in n_samples])\n", "df_p = df_p.unpivot(variable_name=\"n\", value_name=\"p\")\n", "df_akaike = pl.DataFrame(\n", " data=akaike_weights, schema=[\"n = \" + str(n) for n in n_samples]\n", ")\n", "df_akaike = df_akaike.unpivot(variable_name=\"n\", value_name=\"akaike_weight\")\n", "\n", "# Make plots\n", "p1 = iqplot.ecdf(\n", " df_p,\n", " cats=[\"n\"],\n", " q=\"p\",\n", " x_axis_label=\"p-value\",\n", " x_axis_type=\"log\",\n", " order=[\"n = 15\", \"n = 20\", \"n = 50\", \"n = 100\"],\n", " frame_width=500,\n", " frame_height=150,\n", " palette=bokeh.palettes.d3[\"Category20c\"][4],\n", ")\n", "p2 = iqplot.ecdf(\n", " df_akaike,\n", " cats=[\"n\"],\n", " q=\"akaike_weight\",\n", " order=[\"n = 15\", \"n = 20\", \"n = 50\", \"n = 100\"],\n", " x_axis_label=\"Akaike weight\",\n", " x_axis_type=\"log\",\n", " frame_width=500,\n", " frame_height=150,\n", " palette=bokeh.palettes.d3[\"Category20c\"][8][4:],\n", ")\n", "p1.legend.location = \"top_left\"\n", "p2.legend.location = \"top_left\"\n", "p1.x_range = p2.x_range\n", "\n", "bokeh.io.show(bokeh.layouts.column(p1, p2))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that even though the p-value and Akaike weight have large spreads as the number of samples increases, they also shift leftward. This is because small differences in samples can be discerned with large sample sizes. But notice that the p-value and the Akaike weight varies over **orders of magnitude** for similar data set." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusion\n", "\n", "This little exercise in reproducibility tells use that because the p-values \"dance\", and to a lesser extent so do the Akaike weights, we had better be sure the dancefloor is far to the left. This suggests large $n$ is needed.\n", "\n", "I would argue that you should do a similar \"dancing\" analysis of your data sets when you have a reasonable generative model in mind so that you can decide what constitutes a small p-value of Akaike weight." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Computing environment" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Python implementation: CPython\n", "Python version : 3.13.5\n", "IPython version : 9.4.0\n", "\n", "numpy : 2.2.6\n", "scipy : 1.16.0\n", "polars : 1.31.0\n", "numba : 0.61.2\n", "tqdm : 4.67.1\n", "bokeh : 3.7.3\n", "iqplot : 0.3.7\n", "bebi103 : 0.1.28\n", "jupyterlab: 4.4.5\n", "\n" ] } ], "source": [ "%load_ext watermark\n", "%watermark -v -p numpy,scipy,polars,numba,tqdm,bokeh,iqplot,bebi103,jupyterlab" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.13.5" } }, "nbformat": 4, "nbformat_minor": 4 }