{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "
\n", "\n", "**This is a fixed-text formatted version of a Jupyter notebook**\n", "\n", "- Try online [![Binder](https://static.mybinder.org/badge.svg)](https://mybinder.org/v2/gh/gammapy/gammapy-webpage/v0.18.2?urlpath=lab/tree/mcmc_sampling.ipynb)\n", "- You can contribute with your own notebooks in this\n", "[GitHub repository](https://github.com/gammapy/gammapy/tree/master/docs/tutorials).\n", "- **Source files:**\n", "[mcmc_sampling.ipynb](../_static/notebooks/mcmc_sampling.ipynb) |\n", "[mcmc_sampling.py](../_static/notebooks/mcmc_sampling.py)\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Fitting and error estimation with MCMC\n", "\n", "## Introduction\n", "\n", "The goal of Markov Chain Monte Carlo (MCMC) algorithms is to approximate the posterior distribution of your model parameters by random sampling in a probabilistic space. For most readers this sentence was probably not very helpful so here we'll start straight with and example but you should read the more detailed mathematical approaches of the method [here](https://www.pas.rochester.edu/~sybenzvi/courses/phy403/2015s/p403_17_mcmc.pdf) and [here](https://github.com/jakevdp/BayesianAstronomy/blob/master/03-Bayesian-Modeling-With-MCMC.ipynb).\n", "\n", "### How does it work ?\n", "\n", "The idea is that we use a number of walkers that will sample the posterior distribution (i.e. sample the Likelihood profile).\n", "\n", "The goal is to produce a \"chain\", i.e. a list of $\\theta$ values, where each $\\theta$ is a vector of parameters for your model.
\n", "If you start far away from the truth value, the chain will take some time to converge until it reaches a stationary state. Once it has reached this stage, each successive elements of the chain are samples of the target posterior distribution.
\n", "This means that, once we have obtained the chain of samples, we have everything we need. We can compute the distribution of each parameter by simply approximating it with the histogram of the samples projected into the parameter space. This will provide the errors and correlations between parameters.\n", "\n", "\n", "Now let's try to put a picture on the ideas described above. With this notebook, we have simulated and carried out a MCMC analysis for a source with the following parameters:
\n", "$Index=2.0$, $Norm=5\\times10^{-12}$ cm$^{-2}$ s$^{-1}$ TeV$^{-1}$, $Lambda =(1/Ecut) = 0.02$ TeV$^{-1}$ (50 TeV) for 20 hours.\n", "\n", "The results that you can get from a MCMC analysis will look like this :\n", "\n", "\n", "\n", "On the first two top panels, we show the pseudo-random walk of one walker from an offset starting value to see it evolve to a better solution.\n", "In the bottom right panel, we show the trace of each 16 walkers for 500 runs (the chain described previsouly). For the first 100 runs, the parameter evolve towards a solution (can be viewed as a fitting step). Then they explore the local minimum for 400 runs which will be used to estimate the parameters correlations and errors.\n", "The choice of the Nburn value (when walkers have reached a stationary stage) can be done by eye but you can also look at the autocorrelation time.\n", "\n", "### Why should I use it ?\n", "\n", "When it comes to evaluate errors and investigate parameter correlation, one typically estimate the Likelihood in a gridded search (2D Likelihood profiles). Each point of the grid implies a new model fitting. If we use 10 steps for each parameters, we will need to carry out 100 fitting procedures. \n", "\n", "Now let's say that I have a model with $N$ parameters, we need to carry out that gridded analysis $N*(N-1)$ times. \n", "So for 5 free parameters you need 20 gridded search, resulting in 2000 individual fit. \n", "Clearly this strategy doesn't scale well to high-dimensional models.\n", "\n", "Just for fun: if each fit procedure takes 10s, we're talking about 5h of computing time to estimate the correlation plots. \n", "\n", "There are many MCMC packages in the python ecosystem but here we will focus on [emcee](https://emcee.readthedocs.io), a lightweight Python package. A description is provided here : [Foreman-Mackey, Hogg, Lang & Goodman (2012)](https://arxiv.org/abs/1202.3665)." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import astropy.units as u\n", "from astropy.coordinates import SkyCoord\n", "from gammapy.irf import load_cta_irfs\n", "from gammapy.maps import WcsGeom, MapAxis\n", "from gammapy.modeling.models import (\n", " ExpCutoffPowerLawSpectralModel,\n", " GaussianSpatialModel,\n", " SkyModel,\n", " Models,\n", " FoVBackgroundModel,\n", ")\n", "from gammapy.datasets import MapDataset\n", "from gammapy.makers import MapDatasetMaker\n", "from gammapy.data import Observation\n", "from gammapy.modeling.sampling import (\n", " run_mcmc,\n", " par_to_model,\n", " plot_corner,\n", " plot_trace,\n", ")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import logging\n", "\n", "logging.basicConfig(level=logging.INFO)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Simulate an observation\n", "\n", "Here we will start by simulating an observation using the `simulate_dataset` method." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING:gammapy.irf.background:Invalid unit found in background table! Assuming (s-1 MeV-1 sr-1)\n" ] } ], "source": [ "irfs = load_cta_irfs(\n", " \"$GAMMAPY_DATA/cta-1dc/caldb/data/cta/1dc/bcf/South_z20_50h/irf_file.fits\"\n", ")\n", "\n", "observation = Observation.create(\n", " pointing=SkyCoord(0 * u.deg, 0 * u.deg, frame=\"galactic\"),\n", " livetime=20 * u.h,\n", " irfs=irfs,\n", ")" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# Define map geometry\n", "axis = MapAxis.from_edges(\n", " np.logspace(-1, 2, 15), unit=\"TeV\", name=\"energy\", interp=\"log\"\n", ")\n", "\n", "geom = WcsGeom.create(\n", " skydir=(0, 0), binsz=0.05, width=(2, 2), frame=\"galactic\", axes=[axis]\n", ")\n", "\n", "empty_dataset = MapDataset.create(geom=geom, name=\"dataset-mcmc\")\n", "maker = MapDatasetMaker(selection=[\"background\", \"edisp\", \"psf\", \"exposure\"])\n", "dataset = maker.run(empty_dataset, observation)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Models\n", "\n", "Component 0: SkyModel\n", "\n", " Name : source\n", " Datasets names : None\n", " Spectral model type : ExpCutoffPowerLawSpectralModel\n", " Spatial model type : GaussianSpatialModel\n", " Temporal model type : \n", " Parameters:\n", " index : 2.000 \n", " amplitude : 3.00e-12 1 / (cm2 s TeV)\n", " reference (frozen) : 1.000 TeV \n", " lambda_ : 0.050 1 / TeV \n", " alpha (frozen) : 1.000 \n", " lon_0 : 0.000 deg \n", " lat_0 : 0.000 deg \n", " sigma : 0.200 deg \n", " e (frozen) : 0.000 \n", " phi (frozen) : 0.000 deg \n", "\n", "Component 1: FoVBackgroundModel\n", "\n", " Name : dataset-mcmc-bkg\n", " Datasets names : ['dataset-mcmc']\n", " Spectral model type : PowerLawNormSpectralModel\n", " Parameters:\n", " norm : 1.000 \n", " tilt (frozen) : 0.000 \n", " reference (frozen) : 1.000 TeV \n", "\n", "\n" ] } ], "source": [ "# Define sky model to simulate the data\n", "spatial_model = GaussianSpatialModel(\n", " lon_0=\"0 deg\", lat_0=\"0 deg\", sigma=\"0.2 deg\", frame=\"galactic\"\n", ")\n", "\n", "spectral_model = ExpCutoffPowerLawSpectralModel(\n", " index=2,\n", " amplitude=\"3e-12 cm-2 s-1 TeV-1\",\n", " reference=\"1 TeV\",\n", " lambda_=\"0.05 TeV-1\",\n", ")\n", "\n", "sky_model_simu = SkyModel(\n", " spatial_model=spatial_model, spectral_model=spectral_model, name=\"source\"\n", ")\n", "\n", "bkg_model = FoVBackgroundModel(dataset_name=\"dataset-mcmc\")\n", "models = Models([sky_model_simu, bkg_model])\n", "print(models)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "dataset.models = models\n", "dataset.fake()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAVIAAAEMCAYAAACWUT5oAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO2de7xVZbX3vz9Qrt4QNMUbmCiiecEbqRl5QTMVMzP0iFqWryfM7PKWVm91Osc3s7KTxzzmSfKKiMprZKTihQwTFAkU8EaCijcE75ogMN4/5lyyWHM8e6/NWnuz9t7j+/msz15rzDHnfOaacz9rzuf3jDFkZgRBEATrTpf13YAgCIL2TnSkQRAENRIdaRAEQY1ERxoEQVAj0ZEGQRDUSHSkQRAENdKmHamksZKWSJpbZusv6V5Jf5C0UW7rLukmSQskzZA0oMz/dElP56/Ty+xTy/2CIAjaira+I70aOKrCdi7wNeB3wKm57UzgdTPbCfgV8DMASZsDPwIOAPYHfiSpT0saIOm6dW18I9NRjws67rHFcXUc2rQjNbP7gdcqzF2B1flLuW0kcE3+/hbgMEkCjgSmmNlrZvY6MIU1HfNrwKoqmnHCuh9BQ9NRjws67rHFcXUQGmGM9DLgt8DZwPW5bRvgeQAzWwm8CfQtt+cszm2Y2QlmVr4sCIIASdtJuk/S45LmSfp62bKvSXoyt19cZr8gH1p8UtKRze1jg9ZqfLWY2bPAIRVmea5N2Jskf9Qo/Ur22kxaa51NE9/C6tVF2weODWBD5ycp5es1uHtX37erY/eiensB23VVYcmGGzrt+sDfV7X7B5BzJlYljrdnj6Jt+Yrq27ABsHHFOds44etttod31QArve+xu+/71vKiLbFZ+vQu2t57r2jr3QV27FE8Zyuc8/N+4rv1zM4pz+zONboisV3vX6JL4oB79qzw69IFSe+WmSaa2ehEs1yOOuooW7p0aVW+jzzyyJ1mVjlkWM5K4FtmNkvSxsAjkqYAHyF7+t3DzJZL2hJA0hBgFLAb0B+4W9LOZpZ84l3vHWmCxcB2wGJJGwCbkj26LwaGl/ltC0xtbmP5SRwNsJlkn6xYfnQ/fz3v4n/5Ld93q42KthcTvisd246b+r6bbVa0rXB6i7dS7dqqaHv5Zd/XY5NNfHu3bkXbm4k27Dq4aHvuuerbcLXjOzzh6z2S7JLoHJe+X7QN3cH3nfJU0ZbqsE7cs2ibNato2357f/3Fi4u2+c61COCZ+yfa1d/5QXsusV3vX6JH4nvcY/e1P/+fVXszc+ZM5+ekepYuXcrMmTOr8pWU+A/OMLOXgJfy929LepzsSfYrwEVmtjxftiRfZSQwPrcvlLSATJN5MLWPRni095gElBT5E4F7LcuucicwQlKfXGQakduCIOhwrK7yRT9JM8teZ6W2mM/s2RuYAewMfCKfGfQXSfvlbskhxBRtekcq6Uaym4l+khYDPzKzqxzXq4Dr8l+C18huszGz1yT9O/Bw7vcTM6sUr4IgaPcY/rOby1Iz27c5p3x65a3AeWb2Vv602wcYBuwHTJC0I+swhNimHamZnVyl3/vA5xPLxgJj69muIAgakcQA7jogaUOyTvQGM5uYmxeTjd8a8JCk1WSjGqWhxRLbAi82tf1GHSNtNXoAlUN2g50xvBQrEz+SV04r2rZMbMMbHtw/Mcoz1RmbO2ZoYsMOk531d0r4jhhRtKXG+5csKdrmJ3x7LiraLnPGAQHuOLtoG7SgaJs921//facN3nguwD+cMdL3ne8LYKhzfv6RON5pfyvaBu9cfbv6Oft6KDGmfJJj23xz3/cp59nt6P19X49hw3z7DeMqDIlx5pZh1KsjzadOXgU8bmaXlC26DTgUmCppZ6AbsJRsaHGcpEvIhpwHAQ81tY9O15EGQdBeqNsd6UFkYvNjkko/wd8je7Idm0dargBOz+9O50maAMwnG18Y05RiD9GRBkHQkNTvjtTMppGerXaqZzSzC4ELq91HdKRBEDQo9RsjbW2iIw2CoAFpkWq/3omONAiCBiXuSBuWvn1g9GFr22ZM931fa8EM1eMdVXZ2QgE+2ok2GjDA933G2caLzkSMlAI81IlMejURgeQp9M8m1OLevYq2HzmKO/hRPWcnbja+fUXRdqgTAZSaIfB3x/aZRPTOJ5zvJjUro6+jhO/inHPwr5tFi4q2nVLTJxwuSszUuNz5bocnjtcJbEpeN945uzyhWx/ZZFzRulK/MdK2oNN1pEEQtBeiIw2CIKiBuCMNgiCoAyE2BUEQ1EDckTY0b74Bf7p9bdtBB/u+k+8u2rZOhd85otDZp/m+Z1xbtKVSqnlNe9FJgzcsEer3C0csujRxvB4pQeVuJwzyj45QBDDUucqGD/d9JzvH9rBzDHs6gh1AV2f9j+1etAFc4YSZnpv4Hqc7QstGiTDXHXcs2jxR54BEyOXNE4q2bbf1fUc4gtkbCTHRy7t7vRPaDHD8XkXbJon0i4VzVpcQUYiONAiCoCbijjQIgqAOREcaBEFQI9GRBkEQ1ECEiAZBENRIjJE2NN26FRXyKY46D9DHCYP0kuMC7Oyo+ec76jz4xcluToTf7eq04WBHdR93l7/+TScWbRfe4vv2dGypgqM/cWYkpI73A+fG4vXE9+hNXviBE3o6wVG2IaumWsmMRBLoEx0lPFWU7wzneKclFO/b5hZtTg1DV50HmOyo7hsmwo2fcHxTBVq3d87DmYf7vrc6/xN7JGaWVBYzeiGx/5YTHWkQBEGNREcaBEFQA/FoHwRBUCMhNgVBENSBuCNtWN5ZDn+tGLj/ZKKK6FZOGOJtUxMbdsSTExLbvf2Jou35xGa3cHJLTnCEpe09lQX4hiMsbVc0AfApJ7TxU4f6vttu36Vg69uCC9/LqQp+VcvzndDTRMpNTnLCQe9yxB+Afzohnn0T/xEXOULaYCc8E/wqrcsd24aJXKD7ObbnE/lXv3x00TZ5su/rpd09NHHTd74j8F2UCAHer0KEarLcZouoWxXR7YBrga3yjV5pZr8uW/5t4OfAFma2NLddAJwJrALONbM7m9pHp+tIgyBoD9R1jHQl8C0zmyVpY+ARSVPMbH7eyR5BWZV0SUOAUcBuZJNs7pa0c1OVRIu3FUEQBA3B6ipfTWNmL5nZrPz928DjrJm19SvgO2Q9d4mRwHgzW25mC4EFQCKdTUZ0pEEQNCClO9KqOtJ+kmaWvc5KbVXSAGBvYIak44AXzGxOhds2rD3atpjidNm1iEf7IAgalKpV+6Vmtm9zTpI2Am4Fzss3/n1ghOfq2MyxfUh0pEEQNCD1nUcqaUOyTvQGM5so6WPAQGCOJIBtgVmS9ie7Ay3XZLcFEvJoRqfrSDfuAZ8csLZtm0TS3N86YXLnJ6o5elUXU3zXCdvcPZF8+LLLirZNHbX4zUQy38GOvD08sa9nninaUmGMK1cWL/L3fVc2dK4yL2wUYMGCou1bzvc1L6HEe+yfOL9dnIGtTRJKfG8ndPSZxHfu/VN5ovvLCSV+pJNU+XeJMNfpjhQ/ODFb5AlntshfE2Gu3vU81JnVAXB75XWzhe/Xcuqm2gu4CnjczC4BMLPHgC3LfBYB+5rZUkmTgHGSLiETmwbRzGSETteRBkHQHqjrHelBwGjgMUmln6TvmZk7UczM5kmaAMwnGwIY05RiD9GRBkHQsNSnIzWzafjjnuU+Ayo+XwhcWO0+oiMNgqBBicimIAiCGohY+4bGDFZX/NCNTeQjPaBf0faDhKh0hiNSvJeIY/TygZ6fuGZ69ijaljoiRUqs6uvkSfXWB1jitPdgR/hIbWNX35WlznafSbThE07Oy4edYf4XmtRQ12ZZ4rv1zCcO930nOOJW38T+qv2nSs2nmeUISyMS1WuHOZVIxyVCRBOFV12edoS0PfbwfS+tmED0mYdbsKMkkf0pCIKgDkRHGgRBUCPRkQZBENRAPNoHQRDUSIhNQRAEdSDuSBuW95bDrIrEzmN/sbHr++cJbxdsExJVF2+7rWhbssT3PddJk3CTsz74VTyH7ly0vZ+Iz/TsQ1Nhro7a2y2RfHilc7OwPFG+svgtwj99V+Y7oZjezIHpiWqfI5zZCxskrvJLHHX8uMQxjHDCTFOzH55xvnOvCSc1mZhtbf7hhO8CzHVmExw/3Pf1kmmnzu91znb7e5mhcb6H3r5fy4hH+yAIgjoQHWkQBEGNREcaBEFQA/FoHwRBUCOh2jc0K4FlFbbrLvfkED8/Zyrs0xNwZidySP5fpwroqYkckl6u1Bec6pdzHvXXP8ARNKYlclAe7OSbfCQREuvlRH07cd3/79OKNi/vKPjiWB8nPLK/vzorHLFox0QezeOd8zvpb76v94+yWaINXmXP/+cIeZckMlx6epcTCQrAzs718VYiT+rsp4q2/ROhxcc7th2c8F2AzSvPj1cydZ2IO9IgCIIaaT8daZsWv5N0lKQnJS2QdH5u6y/pXkl/yGuqIOlsSY9Jmi1pWl4etbSN0yU9nb9OL7NPzQtbBUHQ7mlR8bv1TpvdkUrqCvyGrIb0YuDhPKX/acDXgB2BU4ErgHFmdkW+3nHAJcBRkjYHfgTsS/ZNPyJpkpm93lbHEQRBW9EYnWQ1tOUd6f7AAjN7xsxWAOPJ6kd3Zc1PiwDMrHyUpzdrMo4dCUwxs9fyznMKcFS+7DWgyXIAQRC0F+KONIVXK/oA4OfAdcCbwCmlhZLGAN8EugGHNrGNbQDM7ITWangQBOuDUO093FrRZvYscIiz4DfAbySdAvwAOD21jWZ3LF0HnADQuwt8okLp7OckcAbYysmE+7uEqvs1J3T03oTC3xIeSCjs1eKFEB7hVfIGbnYSTg92wlHBV9e7vub7euGk3owI8JMHP+rMSDj4YH/9bzrf1ymJcFKvkmkiQtR91DnuON/Xm60xyFG8+yRCTJ9zrpvdEzMPNnOmDtyemGnhzcpIMdqp3Pqn233faRXncuHmC5H0bplpopmNrn7vUM95pJK2A64ly229GrjSzH4t6efAsWSn/R/AF83sjXydC4AzyU79uWZ2Z1P7aMtH+xbXis4Zz5rZGOu0DTMbbWa9zax3v5inEAStysCBAyn9v+WvFnaiOatXV/dqnpXAt8xsV7KZZGNyAXsKsLuZ7QE8BVwAkC8bBexGNnR4ea7xJGnLjvRhYJCkgZK6kTV0kucoaVDZx88AT+fv7wRGSOojqQ8wIrcFQdCRKNUEqkNHamYvmdms/P3bwOPANmZ2l5mVnkumk92YQabdjDez5Wa2EFhApvEkabP7MzNbKekcso6vKzDWzOYl3M+RdDhZ8qPXyR7rMbPXJP07WacM8BMzSzxQBkHQrqnubhOgn6SZZZ+vNLMrPcd8iuTewIyKRV8Cbsrfb0PWsZb4UItJ0aYPumY2GUiU5lrL7+tNLBsLjK1nu4IgaDDM/EFsn6Vmtm9zTvk89VuB88pnBkn6Ptnj/w0lk9eiprbd6UYMV6+Cd95Z2zY1Earnhd9tmdjuD51KpIcmvt1BOxVtTydCJr0KmE50Jqee4hiBS8cVbfMcAQrA02QOTghxlzqi21mJPKdePtBURcrKcwPwqiPKjEgIZucuKtpSOTcHO2G55yV+5r3nupRg5uWh7b1R0ZbKk+pdCtsmlAAvZPmrXnwn8FdHiFuQOIYDnJjUGYmct5+qCBF9xHdrOVa/qU2SNiTrRG8ws4ll9tOBY4DDzKzUWbZYi2nTyKYgCIKqqOMYqSQBVwGPm9klZfajgO8Cx5lZ+U/SJGCUpO6SBgKDgMTtVkanuyMNgqCdUP0YaXMcBIwGHpNUmpz2PeBSoDswJetrmW5mZ5vZPEkTgPlkj/xjzKzJYJ/oSIMgaDyMunWkZjYNf9wzqdeY2YXAhdXuIzrSIAgaEKvnHWmr0+k60hWr4LmKCVM//7Hvu9jJ+/nc73xfT1h6PiE6PvBE0ZZK4bifYzvEiep5LhG9s78TzbJoke871Mn7+cNEJJcXWNSrl+/7riOIrEr8jxxxTFEZOuKsYvbRZTMXuet7bRjv5OEEOPyNou3sRPTP/o7aNHWq7ztkSNHmCUsTEqNuezu2yQmh55tO9N31iUKKgx3xNHHZuMUcv5DImZs67zXRMtV+vdPpOtIgCNoJcUcaBEFQA0Zdpz+1NlVNf5K0Qx5phKSekvxC8EEQBHWhftOf2oJmO1JJXwFuAX6bm7YFEqMwQRAEdaIjdaTAGLJ5WG8BmNnTpAN8giAIaqeOE/LbgmrGSJeb2Yp8wiqSNqCKHKCNSp9N4ISK8Ld7nPBO8EP9evXwfd90VNVUpctXHVsiivHDtFfl7LyoaEspp3OdEMB+Cd/FTvqXaxOhp/feW7TtklB1t3XU4gcTswHmPFTMCLrVVosKttQshZO/WkzQ+dZFjjwPnOZUN12WSIFzn3O8Xogp+PlTvZy3ZyXCXC93qswmCnjy8suJBQ47OaHJ3swUgClOWG6PRP7UwqW/T/VtSmL4iWwblGo60r9I+h7QU9IRwFeBP7Zus4Ig6NxYeo5cA1LNo/35ZDdRjwH/iywa4Aet2aggCDo5pcimjvJob2argf/JX0EQBG2AtavpT8mOVNJjNDEWmqfnD4IgaB0a5G6zGpq6Iz0m/zsm/3td/vdfgDqUdVs/9OwJe+21tu2RRLEwb6y7S2IwZFcntDCVr7IyfyP4xeTAL4T2miOIpMblD9yraEu1a5RTzO0NX6dxQyZfSmRs3MIRWj5+oO/L5sUvZ/mLxQP+iBMaCfD0Q8UGe0UMAXr2LwpTf7rWP+CTTirarr/e364nLHnnZ6IjKgEc6ihLExPimnd+3iqaMruzYPfdfd/BTnufcEKbAV6p+PxCYv8twqxjiE15dU8kHWRmB5UtOl/SA8BPWrtxQRB0YtrRHWk1YlNvSR/mqJB0INC79ZoUBEGnx3LVvppXA1DN9KczgbGSNs0/v0FWKCoIgqD1aEd3pNWo9o8Ae0raBJCZvdn6zQqCoFNjHSwfqaQfVnwGwMxijDQIgtajI0x/KuPdsvc9yNT8x1unOa3P4lfgOxevbUuIkQxybAMT4ZVLnfC5Tbxyn8AhhxRt4xJpYIY6Cu7w4UXbXQkF2FPo+ydiV70EzJsVhW0AFjrb3Xln37f72V8s2JZf8Xvf97iRRZt3cEN2ddfvubgY73vUUX675kxNTElw6NO/GBs8ZIg/1eJFZ/bCs47qvm8ixPQvzgWZqjXszRDwrhmA2bOLthcT8288vfwjid5ii9YQ1zuKal/CzH5Z/lnSL8iq7AVBELQedXq0l7QdcC2wFbAauNLMfi1pc+AmYACwCDjJzF7P17mATB9aBZxrZnc2tY91KcfcC0gUZAiCIKgD9c3+tBL4lpntCgwDxkgaQhb+fo+ZDQLuyT+TLxsF7AYcBVwuqWtTO6hmjLQ8wqkrsAXw79W0PgiCYJ2pXxXRl4CX8vdvS3oc2AYYCQzP3a4BppLVuR8JjDez5cBCSQuA/YEHU/uoZoz0mLL3K4FXzKz9DF4EQdD+MFoyR7SfpJlln680sys9R0kDyOoLzgA+kneymNlLkkp5lrcBppettji3JammI/0PMxtd0ZjrKm3thY17wPCKvIzbLvB9b3G0hK87YZQA06YVbQ8lcj2+5QhLQxPCw3uOGODta49E5gPP9513fF9PjNg10a5jTyqKL6+/mIhzdZS47j/8ju877YGi7dR/qc4P6Onki+3+7a+5vns6SVVXrJjn+t50dfHY7k2olMMcsae3I1Jenlj/NCd/awov7HNWIuTZq0SaiJ5lqPM9zkic3i8OXfvznxLbbBkGq6q+X1tqZik97kMkbQTcCpxnZm+VZiB5rn6D0lTTke5W0ZgNqE/q1iAIAp86zyOVtCFZJ3qDmU3Mza9I2jq/G90aKKVyXwxsV7b6tkAik0RGUmySdIGkt4E9JL2Vv94my1Hwh3U8niAIguqok9ik7NbzKuBxM7ukbNEk4PT8/ems6dcmAaMkdZc0kGwm5ENN7aOppCU/BX4q6admdkGzrQ2CIKgn9bsjPQgYDTwmqTSA9T3gImCCpDOB54DPA5jZPEkTgPlkutAYM1vV1A6aykc62MyeAG6WNLRyuZklRmKCIAhqpI6P9mY2DX/cE+CwxDoXAhdWu4+mxki/CZwF/NJZZsCh1e4kCIKgxTRIZqdqaOrR/qz87afNbC29TlKilmbj8+77MH3u2raDneTHACc9VbR1S5T79KLZUjN4jz66aLt2su97zqiizVPyvfBO8BMov5CYTTC08NwBex/uZKEGnp9dTLa83TnF8E4ABu9StPVMTH84wsnQ+LijpHuZpYG+RzilOW+8wd+Xk9V46/6+au+FYqYSRnsJkO911PXjEyHEXvLwRxOJnc84vmi7OhFufITz375pog1eaPBPnOsD4JpbKgx1qSLavkJEq4ls8grnJorpBkEQ1AlbXd2rAWhqjHQrskmoPSXtzZoxhk3IwkSDIAhahw6URu9I4AyyOVTlUwbeJlO8giAIWo+O0JGa2TXANZI+Z2a3tmGbgiDo7HSgO1IAzOxWSZ8hi3DqUWZvl4mdVwOVkW69EgMVXgXPuXOLNoDJLxdtxyfyQi5wQlJTlRenTi3aBjthm6nKoJ4g8qqTOxXgC46w9fYip2QpsOWWjnHRIn/DHnu/nljwuaJpV+cgHr/HX32cIyylSmX2KgpbXogpwOPzizYvBy343/mRjm6ySyJ/qydopvoUT1jqm/ivPtLR4VLX80PO9ZTSflptnK8jdaSSriD7rj4F/A44kWZm+QdBENSEGXzQsVT7A83sNOB1M/s34OOsHYcaBEFQX4x65iNtdapJWvLP/O97kvoDy4CBrdekIAgCa5ipTdVQTUd6u6TNgJ8Ds8h+K/6nVVsVBEHQIHeb1VCN2FTKhn+rpNvJBKdElsogCII6UHq0bydUc0f6IXnq/eWSbgYSmnRj04WiyjiuBXFaKWHai55LVRH1wg27O+GoKTxV11PyAXo4KvSnT0hI086Fu/EmK3zfr44p2p5IFJfd++OOMTE69Op/F21bnFS0bZmQm0/8fNGWyHS8+KLrCra+fkQsR1x6bME25z/+6Ds7jDx144LtzxPedn295qbOrzcfwQshBpg+vWjbPvFfvMgJST0wcdkMqWhb3RI7d7AQUY9kaul6IukoSU9KWiCpVJhqc0lTJD2d/+2T24dLurot2hUEQStjliUtqebVAKxrR9pk2v16kFft+w3waWAIcHJTlf+CIOhgdATVXtIf8TtMAX1brUVr2B9YYGbP5O0ZT1bdL1X5bwXwZhu0KwiC1qYDjZH+Yh2X1YttgOfLPi8GDiBR+c/M/kZkpQqCDkIHmf5kZn9py4Y4tLiSX3JD0nXACQC9u8DuA9ZePjkRXjncCfVLhZMOGFC0XZ6oITDCEaES0YIud9xVtA3z03Oy005F2z23++UgDzu8aHs4EcO233FOUtM99vSdbxxbtJ08yPf1lDivnHjflNbpqDKDffVl2/88qGhMxUw6Qtr99/uun3JSnnvC0qOP+usvdU7PeKfCK8DhTsXRWX5ULyOci+xvie2e4vg+lBBEKyWhhZsvRNK7ZaaJ61R1uIPcka5vUpX8UpX/kuQncTTAwO5q9fHdIOjMDBw4kGXLljkZuluAwaqV7edfdV3FprbgYWCQpIGSugGjyKr7pSr/BUHQQTCD1auqezUCDduRmtlK4BzgTuBxYIKZzSOr/HeEpKeBI/LPQRB0MFZbda/mkDRW0hJJc8tse0maLmm2pJmS9i9bdkE+5fJJSUdW09Zqsj9NAT5vZm/kn/sA482sqh3UgplNBiZX2JaRqPwXBEHHoM6i/dXAZcC1ZbaLgX8zsz9LOjr/PDyfYjmKLG1of+BuSTuvcznmMvqVOlEAM3u9pJS3R15fARMqxKUBCd8XnRyjryZ8P75j0bZ1wvcZpxBaIqCGZ5027OOEszySEracHJQTJ/q+BzqF8vZLiFg8Oqdoe+5Z3/fozxRtN17g+578pGO83bElZuC9eXPRtsMRvu8DRRHsutPudl1Hn1c8Q3snisH93TkXLzvn8aCD/fUPPrwYQvSXO3yB8K/TirZDnWsR4H1nEzsmCvgd7xTVe+pi37dV6rJb/R7bzex+SQOKe6Ak+25Kpr9ANr1yfB7FuVDSArKpmI7iuYZqOtLVkrY3s+cAJO1AG0zID4Kgc9OCO9J+kmaWfb7SzK5sZp3zgDsl/YJsiLN0G7ENUB5Muzi3NUk1Hen3gWmSStOhDiGrdx8EQdAqmMHK6u9Il5rZvi3cxb8C38grgJwEXAUczjpOu6wm+9MdkoYCw/KdfMPMEkUWgiAIaqcNAptOB76ev7+ZrPoHpKddNklStZc0OP87lCzT04tkpYW2z21BEAStQ+tPf3oR+GT+/lDg6fz9JGCUpO6SBgKDqKK0UlN3pN8ke4T/pbPM8p0HQRDUHaO6qU3VIOlGsvwc/SQtBn4EfAX4taQNyOphngVgZvMkTQDmkwVtjWlOsQeQWdOtldTDzN5vztZe2FyySg13s4Svk/aTREpGNnV+kl5MpFPs6tiOTyi4Nziq7MmOup7KV7nRRkVbKrRxM+eLGJp49tjAOd6e5yWGzp9wlPhUIsxuGxZt2x3gODqxrwAP/LRo88q2gptcdlli0OolR3X/IJGqddKkou3ss4u2VIjok04o5vxWGkz7dOL8enl3vesD4NGKWTD37bMPM2fOrCnV5p5byO5wCsp69P8tj6zDGGldqWZCvpcIJJKDBEHQapjByg+qezUCTaXR24pM9u8paW/WqFmb0IqlrIMgCKB+j/ZtQVNjpEcCZ5CpVr9kTUf6FvC91m1WEASdmXaWjrTJNHrXANdI+pyZ3dqGbQqCoLNjHaQjLWMfSfdUxNp/y8x+0LpNax369oIzKkIsPeEE/CJkXRKjykudlJefSwhI1zsCUuqi8cStXYcUbTdc769/wglF2xBnffCPd+PN/AOeM6vY4D1vT5Q92+NjBdM/rywWngPo+bPxBdvyC0YVbN37+0G1y18sJuNM+d7jRIPumAiv7O4oj7fd5vt6eV0nTy7aDk5cH884+XE/6wiMKV8vtDsgGW8AABx+SURBVBlgI2dA7sFEfOfWzleWEpu2T8U310ijZHaqhmrEpk9XxtoDR7dek4Ig6OyUpj/VI/tTW1DNHWlXSd3zIH4k9QS6t26zgiDozJRU+/ZCNR3p9cA9kn5P9kPxJbKic0EQBK1DRxsjNbOLJT1GlgNUwL+b2Z2t3rIgCDo1jfLYXg1V1Wwysz8Df27ltgRBEAB5qZGOdEcqaRjwX8CuZFGTXYF3zcyphdn4LHkPLq1IQfDzE33fpU78Vr9EjOhWzreRqjg62NnGE0/4vp5wed+9Rdt7iYDdnk4bnkzsaxunIuXcR/2rua9T7HPO5Bdc3z2dwa6e++7mN+Kq/10wdT/x2ILt7XF/dFf3vsf9hvnhqIcd/U7BtvAJP+7znaIrOySiXMc6swG2K5qYP85f34ssnptQ4k9zZN9pzgwBgIOdazTVWb3mVCJdmQh5Tl3ntdKhOlKyFP2jyFJN7QucRjLQOQiCoHZKxe/aC9U+2i+Q1DXPgvJ7SRFrHwRBq9KCxM7rnWo60vfycsizJV0MvATUVrM6CIKgCdrbHWk1E/JHk42LngO8SzbcU2WCqyAIgnVj9erqXo1As/lIOxq7bCy7fK+1bV5oJMDmTujbTonR4alTi7Y3iibAz3/aNfFs8IozwO9F5H3ly/76DzjhqFslKkeucHQWT6wCeGFx0ZZKMbq7U/X0TaeSKsC7jqjzkJOffPQtI931V038Q8H2nhO+C35o8Ny5RRvA9OlFW2q73vew1Mkn6gk6AD0cMfKZhJjoXUtDE7lpX3Xa8IlEmOpEJ/zViUYF4IAK4fHqHWrPR7rLJrIrq8wwOvy+9Z+PtKk0eo/RRNEnM9ujVVoUBEHQgaY/HdNmrQiCICijw4SImtmzbdmQIAiCctpTZFOzYpOkYZIelvSOpBWSVklKjHAFQRDUTimxcz3EJkljJS2RNLfC/jVJT0qal89IKtkvkLQgX3ZkNe2NCflBEDQe9Z3+dDVZP3ZtySDpU8BIYA8zWy5py9w+hKy/2w3oD9wtaefmKol2ugn5b78D91co2c8nfE/eq2h7ORGq54jN9Exs11PNJye26wns3iSDc3/nr/+JFoSuvvhi0dYSxfsLp/gPOH+5t3jb8EZiSoMXhnjKKUXbP8cX1XmAcU7Y5TGJ0X5PiZ822/cd4SRWToX1esm/5dhSSaQnOPL45V/yfb89tmjr95zvu4lzLaQqynqTBJz6rgDsVfl/8nrCsYXUS2wys/slDagw/ytwUSk9qJktye0jgfG5faGkBcD+wINN7aOaeaRrTciX9A1iQn4QBK2IVZnUOR9H7SdpZtkrURd8LXYGPiFphqS/SNovt2/D2vdWi3Nbk1RzRzqarMM9B/gGMSE/CIJWxkgnSXFYug7zSDcA+gDDgP2ACZJ2ZE2Rz8rmNLuxJilT798H/q36dgZBEKwjrR8iuhiYaFlE0kOSVgP9cnt5sq5tAWfQa22Sj/aSRkoaU/Z5hqRn8lci8VwQBEF9aOWaTbcBhwJI2pksRehSYBIwSlJ3SQOBQYATW7c2Td2RfodMvSrRnewWuDfwe+CWdWn9+qZ3LxhWEbLYJfE1TXIktY0T2z24BcKUJ/Yc4eT3BJjhhPV9b0TR5oUggi+IXJoIifWObZDvys8u37Jgm3PXEsfTF9c+ee6eru9N35tTsHnVOlMVLb3KnF6IKfiiUOpp0juXDyVCPE9zQjRnOufh0ITYdJJjG18srpr5OuG3/RLXkvc9zEqIicsd28cTIuUfK/Ov7uP7tYR6JnaWdCMwnGwsdTHwI2AsMDafErUCOD2/O50naQIwn+xyGNOcYg9Nd6TdzKx80HWamS0DlkkKsSkIglalXo/2ZnZyYtGpCf8LgQtbso+mOtI+FRs/p+zjFi3ZSRAEQUswa1/5SJua/jRD0lcqjZL+F1WMGQRBEKwr9YxsaguauiP9BnCbpFNYMwd8H7Kx0uNbu2FBEHRiOkr2p3ym/4GSDiULlwL4k5k5pdeCIAjqS3vKkF/NPNJ7gQ7TeS57D66uGJg4Y3/f11PXvTBKgBlOaOEXndBGgEudMMadvWzNgCeULlpUtKVmCHiJmb/pKL0ACxYUbd26+b4P315U6G9PVK/s5SQq7jetqM4DPOUkjO7nHMM7CbX5iMOLtmcTIZP/dLZx7mm+7113FW39fVd3psRJTrXPexP/VR84Uwe2TiTjvstJRN030a4jhxdt70z1fU91rt07ne8AYKuqAs1bRocrxxwEQbA+aE9p9KIjDYKg4egwiZ2DIAjWJ/FoHwRBUANGPNo3NFtsBF+tyBOTEpC8XJzvJ6o57uMIOF6+S4Dhju/jidyW3xxVtE12RJ03EjULTnHWn1IZ0pfjVfZcloiZ7OW092AnZyfAtBZkrz16eNHmfY+pEg2vOKLbk4nw2YmO7f5rHSMwwhED30604TIndHSxc872T4h+3vWYCgE+3hFKb07M8va+xy0S4aQ/cATRgxOC6KutUS+jnYlN1eQjrQvKuDRP4f+opKFly0ZJmiXpvDLbHZLm5GUArpDUNbd3l3RTvp0ZpYStkgZImtpWxxMEQethZNOfqnk1Am3WkQKfJsuBMQg4C/jvsmWjyBKiDJO0UW47ycz2BHYnC0n9fG4/E3jdzHYCfgX8rA3aHgRBW2LtK7KpLTvSkcC1ljEd2EzS1vmyUjJVK703s9IDwwZkKa6sbDvX5O9vAQ6TJGAVkMjHEwRBe8IsS+xczasRaMuOtKkU/hOBmcBMM/tw6EnSncASsuGoWyq3Y2YrgTeBvmb2vJmd0KpHEARBmxF3pD7JFP5mdo2Z7W1mv1xrodmRwNZk8f2HNred5I6l6yS9K+ndlxJiURAE9WHhwoWU/t/y13Ut3UZHSlpSM3mG/VIGqYdZhxT+Zva+pElkj/RTWFMKYLGkDYBNaeaR3sxGk9WeYgvJxk1de/nwnf31JjjhdymGORUan06omTs4IZPbJOINp00r2o52wg2vSCT+fc35Zp5NKMB7OImG90moup6y7CVKBhjmKMv/kVCWj3Pattj58fvxOUUb+KGcCbGZQxzbXs65AVjqfI9HOsm8AYY4Ya4POMe1OnF9Ddm+aEuF6nrVWHdNJGD2Kr/OSlwLXsLo1MySSr1n4MCBLFu2rOacxQ3SR1ZFq96RmtlvzGwvM9uLLLX/abl6Pwx408xe8taTtFFp/DTvLI8GSqdxEnB6/v5E4N48s3UQBB2I1VW+GoG2nEc6maxDXAC8B3yxCd/ewCRJ3YGuZElTrsiXXQVcl9ebfo21y6EEQdABMNJlXxqRNutI87vGMc06Zr6vkE2H8pa9z5qpUEEQdECMxrnbrIa2FJuCIAiqpl6P9pLGSlqSF7qrXPZtSSapX5ntgjzg50lJR1bT1k4XIiqysYJyliWkqo+14Nt5yxGWPpLwne2IJ30SOTP32bZoW+yIGV7VR4BHnIqhpxzn+/7JCWN89Bnfd6gj0HnCWIofJ8JJvRDcZ51juDEhrs13xJOUKDTAOe9PJM6DFw46YIDv+5yzDS+d6L5OtVGA+Y6ok1JTP+Ic70cT1UlnP1W0pRSh6Y4Qtmni/yGhQdVMHe9IrwYuA9YKAJa0HXAE8FyZbQjZcOFuZCln75a0c3OVROOONAiChqP0aF+PO1Izux//t+hXZGXny8XqkcB4M1tuZgvJNJ1E6vc1REcaBEFD0oKOtJ+kmWWvs5rbtqTjgBfMrLJUQ1OBQ0k63aN9EASNTwtV+6Vmtm/zbhmSegHfB0Z4ixPNaZLoSIMgaEhaUbX/KDAQmJOl6WBbYJak/VkT8FOiqsChTteRrqIoHHgCBcDHnUH7uQnx5WynaFpKfDnQUR5SOTu9yKRDnJCcp/3V+ZwjaHjbBJjh3AIkgmTY1Pke/HJ2MNS5yrZ3oncA/uZ8D591hKlUsT/veHdMiC+33FK0nehEjYGfm9YrQphisHPOV6xI+DpCXio5xxXOefhyIgx6kbcv35UBzvl5OiHEHVgRDXZzYpstoTWnP5nZY8CWpc+SFgH7mtnSPIpynKRLyMSmQUAiDm8NMUYaBEFDUsfpTzcCDwK7SFos6cyUr5nNAyYA84E7gDHNKfbQCe9IgyBofOp5R2pmJzezfEDF5wuBC1uyj+hIgyBoSNpTZFN0pEEQNBwRax8EQVAH4o60gdmkG4yoCLv0FFnwc26mKj+e61SfdCI5AdjbUVpHJsIYvTyU45wKj4MS+7ramTnw3RN93184ebQmTfJ9FzjfWUoB3tTJ1ZpS3ZcsKdq28uIrE9zqHO+gR33fWc4xvOiEyQI4h8C+Qx0jIEfCnescbyL1KVs6UyX+nLhGvZCbVLLjLzuzH+5KzBbZy7keU9vdt2IG583P+34tob0lLel0HWkQBO2D6EiDIAhqJDrSIAiCGgixKQiCoEZijLTBeXsF3Fch9qQG/b2Qx90TBcvOcESoRxO+53+naJub8J0+vWjr6xSk29FTQ/BFnfvu9X2f88JRE4JKPyesNpXL0xPMeiViT4c6+7vFEUROTOQz3cwR8rxcseD/o56SCBG93RGh5s/3fZc6IZpeDcFUDtlHHWEpJSYec3DR9tVEaPJQR/08LlH48TxHZPx8ohDiTbdVGPbx/VpKdKRBEAQ1EHekQRAEdSA60iAIghqJjjQIgqAGQrUPgiCokRgjbXC6sXb6a4ChifDM3rOLtkMTZbC8MMa7Ekr8qIuLtnMd9RXgb46SfrwTizktUcpxhKOCpxISewp9KvnwbY5Cf5xT8RRgF6e9SxPJtK9wUuh6ExLuS4Q2br150eaFbAIMcdqQapfHk4kEytWyUyL09QDHnkrs7IUAe/UzIKviVolXWRTgh871eH1iNsCbif3VSnSkQRAENRIdaRAEQQ3Eo30QBEEdiI40CIKgBkK1b4cMGODbZzhiUyq08SwnpO7shPiy0UZFW/dEnOrhzjbucISlQxJVOe+fVbQNTrTrYEdguPRS3/dLjkB3kfN9ARzlhCa+4btyolPx83En7HPPRPJTrzrpuLt8X0eX4hHn+wLYwgmPfC0hTHmRlF677k+E1J7phBs/kBB6dnH+g722AvRzwoVTYaqeIJnYLIlUqTVTrztSSWOBY4AlZrZ7bvs5cCywAvgH8EUzeyNfdgFwJlnR4XPN7M7m9hFVRIMgaDhKY6T1qCIKXA0cVWGbAuxuZnsATwEXAEgaAowCdsvXuVxS1+Z2EB1pEAQNSb06UjO7H3itwnaXmZVGD6YDpee0kcB4M1tuZgvJZo0lJj2uITrSIAgajhbekfaTNLPsdVYLd/cl4M/5+22A8mIpi3Nbk8QYaRAEDUkLxKalZrZv825FJH0/39UNJZPjZs1tJzrSIAgajraYRyrpdDIR6jAzK3WWi1k7+HFbwCmDuTadriPtuzmcWjHs/GWnKifA704p2n6R8D3XUZv79/d9pzkKrFc9E+BNJynxMCeEMBXa6Cn0IxIxhM85KnJqlsJTTmhh5Wh+idsd2w8SYbleYmfve/TCTgFuq0wyDBydGOEa54Sjbpe4DZrifL9fTbRhojOrYhNnmoJ36wOw2WZFW2pmyQbOf/AVidBkT3U/JZG426us2y8xs+StGkNlU7RmRyrpKOC7wCfNrPxoJwHjJF0C9CfLqe1cKWvT6TrSIAgan3rekUq6ERhONpa6GPgRmUrfHZgiCWC6mZ1tZvMkTQDmkz3yjzGzVc3tIzrSIAgaknp1pGZ2smO+qgn/C4ELW7KP6EiDIGhIIkQ0CIKgBtpbiKjWiFWdg36SHVthOzWRC3S185M4NpEH0wu1+6wjQAE864g6byaumtNPLNq8KqDPOHlLAQ52wg0fSogRhzuVOd9PCAnedzMuESLqRTee7rtyo2P7lqOSzGpB3tAjEpUyT3EEsx8ntvE55zw89qjve4Wz3YMcvx0S+UjvdEI5P5MI633CCb9NaT/eXVPPhO8fHFsqz+mwCtHt5733YebMmSktrSo2lCwVklrJy/DIuk5/qhdxRxoEQUMSj/ZBEAQ1Eh1pEARBDURi5yAIgjoQHWkQBEENtDfVvtN1pH03glMrwhNTVTU9RXRgYrtHH160TZ3q+x52aNF2j6PEA7ziKLh/dxT6j3mlNoEXnSjhoYnQxreccNSUwu9xQmK73ZyQyQ0T25h4XNE225kNkFrfi8qdlKiU6eyKbRPquBd62jsRPuucXjf58Qzn3IKv0A8Z4vs+4FyjfX1Xt2N6OOF7jGPb1suEDVxaeX73SWy0hbSnO9I2S6MnabCkByUtl/TtimWjJM2SdF6ZbR9Jj0laIOlS5XFckrpLuim3z5A0ILcPkDS1rY4nCILWo86JnVudtsxH+hpwLvALZ9koYD9gmKRSIY7/Bs4iSxowiDU5Mc4EXjeznYBfAT9rzUYHQbB+iI7UwcyWmNnDwAfO4tLkXQMkaWtgEzN7ME9vdS1wfO4zErgmf38LcFh+t7qKiizYQRC0T+KOdN2YCMwEZprZ22QZqctHf8qzVH+YwTovFfAm0NfMnjezE9quyUEQtCYrq3w1Am0eIirpx8A7ZuY94pd89gN+amaH558/AXzHzI6VNA840swW58v+AexvZsua2N51wAkAXbp06bX33nvX7XgahYULFzJwYEoKa9901GPrqMf197//ndWrV5fraxPNbHRLtiHpDtKFSytZamapdLhtQquq9pLGAF/JPx5tZs1mms5ZzJpiVLB2lupSBuvFkjYANqWZR/r8JI7O2/TuzJkze1fZjnaDpHeXLVvW4Y4LOu6xdeTjMrOajmt9d4wtpVUf7c3sN2a2V/6qthPFzF4C3pY0LB//PI01eRQmsSbnxYnAvdbZMq8EQdBQtNmjvaStyMZBNyEbI34HGGJmzuxFkLQvWT3qnmQV/r5mZiapB3AdsDfZnegoM3umBe2o+deyEemoxwUd99jiuDoObTYh38xeZu3H9eb8ZwKFJHBm9j7w+RqaMrGGdRuZjnpc0HGPLY6rg9Dp8pEGQRDUm0aZ/hQEQdBuiY40CIKgRtp9RypprKQlkuaW2fpLulfSH0ohp6kY/XzZ6ZKezl+nl9mnlvu1JZKOkvRk3t7zc5t3XGfnOQlmS5omaUjZNhruuFIkjndzSVPy9k+R1Ce3D5d09XpqZw9JD0maI2mepH/L7T+W9EJ+HmZLOjq3d5P0+/wczZE0vGxbwyXNlHRxme2q3O9RSbeUnWflOScW5MuGlq2zqK2Ov5z2cs7aBDNr1y/gEGAoMLfMdhGwG3AscHZu+ypwRf5+FHBT/n5z4Jn8b5/8fZ982VRgwHo4pq7AP4AdgW7AHGBI4rg2KVvvOOCORj2udTjei4Hzc5/zgZ/l74cDV6+ntgrYKH+/ITADGEZW7unbjv8Y4Pf5+y2BR4Au+eebyGal/BIY7JzPS8qO/2iy2SvK9zejzG9RnLP1+2r3d6Rmdj/FCfldWROKW4rjT8XoHwlMMbPXzOx1YAprEqS8RhbD39bsDywws2fMbAUwnqz9heOytaeP9SYLU4bGPK4UqeMtP2fXsCbfwgqy0OA2xzLeyT9umL+aUmyHAPfk6y4B3gBKhdq6sCasfK3zmV+bPcu2PRK4Nt//dGCzPCcFwKt1OLSW0m7OWVvQ7jvSBJcBvwXOBq7PbW6Mfrk958O4fjM7wczKl7UVqTZ5x4WkMXmo7MVkGbaa2sb6PK4UqbZ+xLLgDPK/W+bv/2ZmX2/zVuZI6ippNrCE7MdqRr7onPyxe2zpkZbsTm2kpA0kDSTL1rldvux3wN/I7lAfL9v+74GXgcHAf+Xmps7nfnU/yOZpV+estemQHamZPWtmh5jZsZYlQYE1d6ZruTZhX5+4bUocF5ZFkH0U+C7wg6a20QptrQftqa2Y2Soz24tsXvT+knYnS/v4UWAv4CWyx3WAsWSdzEzgP8k6zpX5du40s6Fm9q2K7X+RLEf148AXcnOjfUeN1p71SofsSBOUYvSpiNH/0J5THte/vljXNo1nzaNUIx5XilRbXyk9vuZ/l6yHtiUxszfIxpuPMrNX8g52NfA/ZI++mNlKM/uGZWHSI4HNgKer2PYqsjHUz+WmRjuf7fKctRadqSNNxejfCYyQ1Cd/HBuR29YnDwODJA2U1I1MHJvkOUoaVPbxM6z5J23E40qROt7yc3Y6a/ItrDckbSFps/x9T+Bw4Imy8UqAzwJzc59eknrn748AVprZ/MS2JWmn0nsyUbFUyGMScFruMwx4s/QIvZ5oN+esTVjfaletL+BGskepD8h+Jc9M+PUAbgYWAA8BO5Yt+1JuXwB8cX0fU96mo4GnyJTR7zfh92tgHjAbuA/YrZGPqyXHSzaGfQ/Zj8M9wOYN0M49gL8Dj5J1lj/M7dcBj+X2ScDWuX0A8CTZY/rdwA5NbLsL8EC+nbnADeQqPtmj9G/y7+cxYN8G+C7axTlri1eEiAZBENRIZ3q0D4IgaBWiIw2CIKiR6EiDIAhqJDrSIAiCGomONAiCoEaiIw2CIKiR6Eg7EZI+ImmcpGckPSLpQUmfbWadASpLUdjC/Z0hqX/Z59+Vp/lrZt3hkm5fl/1Wuf3+km7J3+9VSnvXwm38WNK369+6oL0RHWknIY+UuQ2438x2NLN9yKJRqq6jtQ6cQRYzDoCZfdkSUT1tjZm9aGYn5h/3IptcHgTrRHSknYdDgRVmdkXJYFkSlP+CD+88/yppVv46sHIDTflI+k5Z8uKLJJ1Ili7uhjzRcU9lCaX3zf2PyrcxR9I91R6EpJPz/cyV9LMy+zuSLsy3N13SR3L7R/PPD0v6iaR3yo5lbh7e+BPgC3k7v1B5p5n7Dcjff19ZMuO7gV3KfD4q6Y78Tv+vkgZXe0xBB2B9h1bFq21eZOn1ftXE8l5Aj/z9IGBm/n4AedLsJnw+TZbVqFf+efP871TKQhlLn4EtyFKwDSz3r2jPcOD2Clt/4Ll8/Q2Ae4Hj82UGHJu/vxj4Qf7+duDk/P3ZwDvOcZ0BXFa2nx9TlqSZLFxzAFkKvMfy72ETstDbb+c+9wCD8vcHkOVyWO/nPV5t82qzcsxBYyHpN8DBZHep+5ElKL5M0l5kSZ93dlZL+RxOlgX+PQAzq0y0XckwsiGGhVX6l9gPmGpmr+bHcANZhYTbyBIHl8ZUHwGOyN9/nDUZscYBv6hyXx6fAP5f6TglTcr/bgQcCNycjaAA0L2G/QTtjOhIOw/zWJOSDTMbI6kfWZ5MgG8ArwB7kg35vO9sI+UjWpaLsqX+5eul+MDMSttcRW3X9krWHvbqUfbea3cX4A3LcpQGnZAYI+083Av0kPSvZbZeZe83BV6yLJ/maLKyJpWkfO4CviSpF2QF0HL728DGznYeBD6ZZ4wv92+OGfl6/SR1BU4G/tLMOtNZ8wMyKuFT2c5FZHXAUFZkbmBuvx/4bD7euzFZmjssKw+yUNLn83Ukac8qjynoAERH2knI79aOJ+uIFkp6iKymzndzl8uB0yVNJ3tkf9fZjOtjZneQpY6bqawER0mouRq4oiQ2lbXlVeAsYKKkOWQJjD0Ok7S49CIbp7yALF3gHGCWmTWX7/I84Jv58W6NXzfoPmBISWwCbgU2z4/lX8lSxWFms/K2zs59/lq2jX8BzsyPZx5Z7aKgkxBp9IIOTX6X/E8zM0mjyISn6OSCuhJjpEFHZx8ygUxkFTy/tJ7bE3RA4o40CIKgRmKMNAiCoEaiIw2CIKiR6EiDIAhqJDrSIAiCGomONAiCoEb+P9+RHcA00xKcAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "dataset.counts.sum_over_axes().plot(add_cbar=True);" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# If you want to fit the data for comparison with MCMC later\n", "\n", "# fit = Fit(dataset)\n", "# result = fit.run(optimize_opts={\"print_level\": 1})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Estimate parameter correlations with MCMC\n", "\n", "Now let's analyse the simulated data.\n", "Here we just fit it again with the same model we had before as a starting point.\n", "The data that would be needed are the following: \n", "- counts cube, psf cube, exposure cube and background model\n", "\n", "Luckily all those maps are already in the Dataset object.\n", "\n", "We will need to define a Likelihood function and define priors on parameters.
\n", "Here we will assume a uniform prior reading the min, max parameters from the sky model." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Define priors\n", "\n", "This steps is a bit manual for the moment until we find a better API to define priors.
\n", "Note the you **need** to define priors for each parameter otherwise your walkers can explore uncharted territories (e.g. negative norms)." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MapDataset\n", "----------\n", "\n", " Name : dataset-mcmc \n", "\n", " Total counts : 248259 \n", " Total background counts : 238923.09\n", " Total excess counts : 9335.91\n", "\n", " Predicted counts : 248096.17\n", " Predicted background counts : 238923.09\n", " Predicted excess counts : 9173.09\n", "\n", " Exposure min : 1.14e+10 m2 s\n", " Exposure max : 3.45e+11 m2 s\n", "\n", " Number of total bins : 22400 \n", " Number of fit bins : 22400 \n", "\n", " Fit statistic type : cash\n", " Fit statistic value (-2 log(L)) : -1296185.31\n", "\n", " Number of models : 2 \n", " Number of parameters : 13\n", " Number of free parameters : 7\n", "\n", " Component 0: SkyModel\n", " \n", " Name : source\n", " Datasets names : None\n", " Spectral model type : ExpCutoffPowerLawSpectralModel\n", " Spatial model type : GaussianSpatialModel\n", " Temporal model type : \n", " Parameters:\n", " index : 2.000 \n", " amplitude : 3.00e-12 1 / (cm2 s TeV)\n", " reference (frozen) : 1.000 TeV \n", " lambda_ : 0.050 1 / TeV \n", " alpha (frozen) : 1.000 \n", " lon_0 : 0.000 deg \n", " lat_0 : 0.000 deg \n", " sigma : 0.200 deg \n", " e (frozen) : 0.000 \n", " phi (frozen) : 0.000 deg \n", " \n", " Component 1: FoVBackgroundModel\n", " \n", " Name : dataset-mcmc-bkg\n", " Datasets names : ['dataset-mcmc']\n", " Spectral model type : PowerLawNormSpectralModel\n", " Parameters:\n", " norm : 1.000 \n", " tilt (frozen) : 0.000 \n", " reference (frozen) : 1.000 TeV \n", " \n", " \n" ] } ], "source": [ "print(dataset)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "DatasetModels\n", "\n", "Component 0: SkyModel\n", "\n", " Name : source\n", " Datasets names : None\n", " Spectral model type : ExpCutoffPowerLawSpectralModel\n", " Spatial model type : GaussianSpatialModel\n", " Temporal model type : \n", " Parameters:\n", " index : 2.000 \n", " amplitude : 3.20e-12 1 / (cm2 s TeV)\n", " reference (frozen) : 1.000 TeV \n", " lambda_ : 0.050 1 / TeV \n", " alpha (frozen) : 1.000 \n", " lon_0 (frozen) : 0.000 deg \n", " lat_0 (frozen) : 0.000 deg \n", " sigma (frozen) : 0.200 deg \n", " e (frozen) : 0.000 \n", " phi (frozen) : 0.000 deg \n", "\n", "Component 1: FoVBackgroundModel\n", "\n", " Name : dataset-mcmc-bkg\n", " Datasets names : ['dataset-mcmc']\n", " Spectral model type : PowerLawNormSpectralModel\n", " Parameters:\n", " norm (frozen) : 1.000 \n", " tilt (frozen) : 0.000 \n", " reference (frozen) : 1.000 TeV \n", "\n", "\n", "stat = -1296176.2925701041\n" ] } ], "source": [ "# Define the free parameters and min, max values\n", "parameters = dataset.models.parameters\n", "\n", "parameters[\"sigma\"].frozen = True\n", "parameters[\"lon_0\"].frozen = True\n", "parameters[\"lat_0\"].frozen = True\n", "parameters[\"amplitude\"].frozen = False\n", "parameters[\"index\"].frozen = False\n", "parameters[\"lambda_\"].frozen = False\n", "\n", "\n", "parameters[\"norm\"].frozen = True\n", "parameters[\"tilt\"].frozen = True\n", "\n", "parameters[\"norm\"].min = 0.5\n", "parameters[\"norm\"].max = 2\n", "\n", "parameters[\"index\"].min = 1\n", "parameters[\"index\"].max = 5\n", "parameters[\"lambda_\"].min = 1e-3\n", "parameters[\"lambda_\"].max = 1\n", "\n", "parameters[\"amplitude\"].min = 0.01 * parameters[\"amplitude\"].value\n", "parameters[\"amplitude\"].max = 100 * parameters[\"amplitude\"].value\n", "\n", "parameters[\"sigma\"].min = 0.05\n", "parameters[\"sigma\"].max = 1\n", "\n", "# Setting amplitude init values a bit offset to see evolution\n", "# Here starting close to the real value\n", "parameters[\"index\"].value = 2.0\n", "parameters[\"amplitude\"].value = 3.2e-12\n", "parameters[\"lambda_\"].value = 0.05\n", "\n", "print(dataset.models)\n", "print(\"stat =\", dataset.stat_sum())" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:gammapy.modeling.sampling:Free parameters: ['index', 'amplitude', 'lambda_']\n", "INFO:gammapy.modeling.sampling:Starting MCMC sampling: nwalkers=6, nrun=150\n", "INFO:gammapy.modeling.sampling: 0%\n", "INFO:gammapy.modeling.sampling: 50%\n", "INFO:gammapy.modeling.sampling:100% => sampling completed\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 5.77 s, sys: 42.5 ms, total: 5.82 s\n", "Wall time: 5.84 s\n" ] } ], "source": [ "%%time\n", "# Now let's define a function to init parameters and run the MCMC with emcee\n", "# Depending on your number of walkers, Nrun and dimensionality, this can take a while (> minutes)\n", "sampler = run_mcmc(dataset, nwalkers=6, nrun=150) # to speedup the notebook\n", "# sampler=run_mcmc(dataset,nwalkers=12,nrun=1000) # more accurate contours" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot the results\n", "\n", "The MCMC will return a sampler object containing the trace of all walkers.
\n", "The most important part is the chain attribute which is an array of shape:
\n", "_(nwalkers, nrun, nfreeparam)_\n", "\n", "The chain is then used to plot the trace of the walkers and estimate the burnin period (the time for the walkers to reach a stationary stage)." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_trace(sampler, dataset)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_corner(sampler, dataset, nburn=50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot the model dispersion\n", "\n", "Using the samples from the chain after the burn period, we can plot the different models compared to the truth model. To do this we need to the spectral models for each parameter state in the sample." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "emin, emax = [0.1, 100] * u.TeV\n", "nburn = 50\n", "\n", "fig, ax = plt.subplots(1, 1, figsize=(12, 6))\n", "\n", "for nwalk in range(0, 6):\n", " for n in range(nburn, nburn + 100):\n", " pars = sampler.chain[nwalk, n, :]\n", "\n", " # set model parameters\n", " par_to_model(dataset, pars)\n", " spectral_model = dataset.models[\"source\"].spectral_model\n", "\n", " spectral_model.plot(\n", " energy_range=(emin, emax),\n", " ax=ax,\n", " energy_power=2,\n", " alpha=0.02,\n", " color=\"grey\",\n", " )\n", "\n", "\n", "sky_model_simu.spectral_model.plot(\n", " energy_range=(emin, emax), energy_power=2, ax=ax, color=\"red\"\n", ");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Fun Zone\n", "\n", "Now that you have the sampler chain, you have in your hands the entire history of each walkers in the N-Dimensional parameter space.
\n", "You can for example trace the steps of each walker in any parameter space." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Here we plot the trace of one walker in a given parameter space\n", "parx, pary = 0, 1\n", "\n", "plt.plot(sampler.chain[0, :, parx], sampler.chain[0, :, pary], \"ko\", ms=1)\n", "plt.plot(\n", " sampler.chain[0, :, parx],\n", " sampler.chain[0, :, pary],\n", " ls=\":\",\n", " color=\"grey\",\n", " alpha=0.5,\n", ")\n", "\n", "plt.xlabel(\"Index\")\n", "plt.ylabel(\"Amplitude\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## PeVatrons in CTA ?\n", "\n", "Now it's your turn to play with this MCMC notebook. For example to test the CTA performance to measure a cutoff at very high energies (100 TeV ?).\n", "\n", "After defining your Skymodel it can be as simple as this :" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# dataset = simulate_dataset(model, geom, pointing, irfs)\n", "# sampler = run_mcmc(dataset)\n", "# plot_trace(sampler, dataset)\n", "# plot_corner(sampler, dataset, nburn=200)" ] } ], "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": "3.7.0" }, "nbsphinx": { "orphan": true } }, "nbformat": 4, "nbformat_minor": 4 }