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@davidrichards
Created November 11, 2016 01:22
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Example of Data From Two Distributions\n",
"\n",
"In one example, we can look at a random variable that is expected to have come from two probability distributions. As part of the model. [source][source]\n",
"\n",
"[source]: http://stats.stackexchange.com/questions/46626/fitting-model-for-two-normal-distributions-in-pymc"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from pymc import *\n",
"\n",
"size = 10\n",
"p = Uniform( \"p\", 0 , 1) #this is the fraction that come from mean1 vs mean2\n",
"\n",
"ber = Bernoulli( \"ber\", p = p, size = size) # produces 1 with proportion p.\n",
"\n",
"precision = Gamma('precision', alpha=0.1, beta=0.1)\n",
"\n",
"mean1 = Normal( \"mean1\", 0, 0.001 ) #better to use normals versus Uniforms (unless you are certain the value is truncated at 0 and 200 \n",
"mean2 = Normal( \"mean2\", 0, 0.001 )\n",
"\n",
"@deterministic\n",
"def mean( ber = ber, mean1 = mean1, mean2 = mean2):\n",
" return ber*mean1 + (1-ber)*mean2\n",
"\n",
"\n",
"#generate some artificial data \n",
"v = np.random.randint( 0, 2, size)\n",
"data = v*(10+ np.random.randn(size) ) + (1-v)*(-10 + np.random.randn(size ) )\n",
"\n",
"\n",
"obs = Normal( \"obs\", mean, precision, value = data, observed = True)\n",
"\n",
"model = Model( {\"p\":p, \"precision\": precision, \"mean1\": mean1, \"mean2\":mean2, \"obs\":obs} )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To model this, we have a variable, `p`, that is the proportion of values take from the first distribution. We also have a Bernoulli variable, `ber` that represents the choice between the first and second distributions.\n",
"\n",
"Precision is used instead of standard deviation because it's mathematically easier to compute inside PyMC. It is just 1 / variance and is always positive. The smaller the precision, the wider the variance on a distribution. [source][precision]\n",
"\n",
"The `precision` variable is modeled with a Gamma distribution. That is because it is a [conjugate prior][conjugate] to precision, or a distribution in the same family as precision. Put another way, it is a reasonable choice for learning the precision of the observed data.\n",
"\n",
"The `mean1` and `mean2` variables are both normal distributions. We are learning these variables that are assumed to be the two data sources fueling our observed data.\n",
"\n",
"Our `mean` variable is deterministic, meaning if we know the parents, we know the value of the variable. In this case, it takes `ber`, `mean1`, and `mean2`. Or, if we knew what these three variables were, we'd just do the math and return our variable's value. We use this variable to produce our observed artificial data. If we had data from the real world, we would create an observed variable with that data instead. The `@deterministic` decorator tells pymc to treat this function as a variable.\n",
"\n",
"We have a stochastic variable, `obs`. It requires a value parameter, which is our artificial data in this case. It is also observed, so the sampling process does not try and fit the values in this case. The sampling process tries to fit all the variables in the model to the observed data.\n",
"\n",
"Finally, we combine our variables into a model.\n",
"\n",
"![model][model]\n",
"\n",
"[conjugate]: https://en.wikipedia.org/wiki/Conjugate_prior#Continuous_likelihood_distributions\n",
"[precision]: https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/blob/master/Chapter2_MorePyMC/Ch2_MorePyMC_PyMC2.ipynb\n",
"[model]: ./two_distributions.jpg"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" [-----------------100%-----------------] 40000 of 40000 complete in 9.8 sec"
]
}
],
"source": [
"mcmc = MCMC(model)\n",
"mcmc.sample(40000, 10000, 1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we build a sampling object, called `mcmc` and fit our model using 40,000 iterations, discarding the first 10,000 and tallying the values every iteration after the first 10,000. Put another way, we are using the first 25% of our sampling to begin to learn the values of or variables without trying to get too excited about the first things we see. Imagine a child buying the first candy they see in a candy store, only to be disappointed after they've made their purchase when they see what else was available. The discarding parameter allows us to sample the model space for a while before getting too excited. Then, we start to keep track of how well our data fits, tallying our opinion every time we try something.\n",
"\n",
"It might help to produce a better [explanation][explanation]. I'll paste the whole discussion here:\n",
"\n",
"> I think there's a nice and simple intuition to be gained from the (independence-chain) Metropolis-Hastings algorithm.\n",
"> \n",
"> First, what's the goal? The goal of MCMC is to draw samples from some probability distribution without having to know its exact height at any point. The way MCMC achieves this is to \"wander around\" on that distribution in such a way that the amount of time spent in each location is proportional to the height of the distribution. If the \"wandering around\" process is set up correctly, you can make sure that this proportionality (between time spent and height of the distribution) is achieved.\n",
"> \n",
"> Intuitively, what we want to do is to to walk around on some (lumpy) surface in such a way that the amount of time we spend (or # samples drawn) in each location is proportional to the height of the surface at that location. So, e.g., we'd like to spend twice as much time on a hilltop that's at an altitude of 100m as we do on a nearby hill that's at an altitude of 50m. The nice thing is that we can do this even if we don't know the absolute heights of points on the surface: all we have to know are the relative heights. e.g., if one hilltop A is twice as high as hilltop B, then we'd like to spend twice as much time at A as we spend at B.\n",
"> \n",
"> The simplest variant of the Metropolis-Hastings algorithm (independence chain sampling) achieves this as follows: assume that in every (discrete) time-step, we pick a random new \"proposed\" location (selected uniformly across the entire surface). If the proposed location is higher than where we're standing now, move to it. If the proposed location is lower, then move to the new location with probability p, where p is the ratio of the height of that point to the height of the current location. (i.e., flip a coin with a probability p of getting heads; if it comes up heads, move to the new location; if it comes up tails, stay where we are). Keep a list of the locations you've been at on every time step, and that list will (asyptotically) have the right proportion of time spent in each part of the surface. (And for the A and B hills described above, you'll end up with twice the probability of moving from B to A as you have of moving from A to B).\n",
"> \n",
"> There are more complicated schemes for proposing new locations and the rules for accepting them, but the basic idea is still: (1) pick a new \"proposed\" location; (2) figure out how much higher or lower that location is compared to your current location; (3) probabilistically stay put or move to that location in a way that respects the overall goal of spending time proportional to height of the location.\n",
"> \n",
"> What is this useful for? Suppose we have a probabilistic model of the weather that allows us to evaluate A*P(weather), where A is an unknown constant. (This often happens--many models are convenient to formulate in a way such that you can't determine what A is). So we can't exactly evaluate P(\"rain tomorrow\"). However, we can run the MCMC sampler for a while and then ask: what fraction of the samples (or \"locations\") ended up in the \"rain tomorrow\" state. That fraction will be the (model-based) probabilistic weather forecast.\n",
"\n",
"Setting the parameters in a sampling program is a bit of an art. It helps to visualize results and try different parameters to really produce the best results possible. Or, a more grown up approach would be to go find better data, better experts if our models aren't informative enough.\n",
"\n",
"[explanation]: http://stats.stackexchange.com/questions/165/how-would-you-explain-markov-chain-monte-carlo-mcmc-to-a-layperson/12657#12657"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"mean_1_samples = mcmc.trace('mean1')[:]\n",
"mean_2_samples = mcmc.trace('mean2')[:]\n",
"p_samples = mcmc.trace('p')[:]\n",
"precision_samples = mcmc.trace('precision')[:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we extract the posterior probabilities of our learned variables. We will summarize them next and see what might have produced the data we have."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x10a214d50>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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0u+HevXslOu6QIUMwc+ZMbN68GaNHjwbwaJaCUqnU+3uxbds29O3bFxYWFnjrrbdQv359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\nnxEREYGkpCQoFAr07t0bM2b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"text/plain": [
"<matplotlib.figure.Figure at 0x109ff2150>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%matplotlib inline\n",
"from IPython.core.pylabtools import figsize\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"plt.style.use('ggplot')\n",
"\n",
"figsize(12.5, 10)\n",
"\n",
"ax = plt.subplot(311)\n",
"ax.set_autoscaley_on(False)\n",
"plt.hist(mean_1_samples, histtype='stepfilled', bins=30, alpha=0.85,\n",
" label=\"posterior of mean 1\", normed=True)\n",
"plt.legend(loc=\"upper left\")\n",
"plt.title(r\"\"\"Posterior distributions of the variables\"\"\")\n",
"\n",
"ax = plt.subplot(311)\n",
"ax.set_autoscaley_on(False)\n",
"plt.hist(mean_2_samples, histtype='stepfilled', bins=30, alpha=0.85,\n",
" label=\"posterior of mean 2\", normed=True)\n",
"plt.legend(loc=\"upper left\")\n",
"plt.xlim([-15,15])\n",
"\n",
"ax = plt.subplot(312)\n",
"ax.set_autoscaley_on(False)\n",
"plt.hist(p_samples, histtype='stepfilled', bins=30, alpha=0.85,\n",
" label=\"posterior of p\", normed=True)\n",
"plt.legend(loc=\"upper left\")\n",
"plt.xlim([-15,15])\n",
"plt.xlabel(\"mean 1 and 2 values\")\n",
"plt.xlim([0, 1])\n",
"\n",
"ax = plt.subplot(313)\n",
"ax.set_autoscaley_on(False)\n",
"plt.hist(precision_samples, histtype='stepfilled', bins=30, alpha=0.85,\n",
" label=\"posterior of precision\", normed=True)\n",
"plt.legend(loc=\"upper left\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"We have learned two means, one near -10 or -11 and the other near 9. The proportion of values chosen for mean1 is somewhere around 40%, which explains why that distribution is centered a little further from 0 than the more-commonly sampled value from mean2. The precision is learned with an expected value around 1.25.\n",
"\n",
"Since there is a real art to our sampling, we could change our sampling approach and look at the traces. Since our data is artificial, we won't see this, but it will show up more often when we have natural data that we're analyzing. Here is an example of how you might experiment with your sampling to get a feel for how the algorithm is [converging][converging]:\n",
"\n",
"> An iterative algorithm is said to converge when as the iterations proceed the output gets closer and closer to a specific value. In some circumstances, an algorithm will diverge; its output will undergo larger and larger oscillations, never approaching a useful result.\n",
"> \n",
"> The \"converge to a global optimum\" phrase in your first sentence is a reference to algorithms which may converge, but not to the \"optimal\" value (e.g. a hill-climbing algorithm which, depending on initial conditions, may converge to a local maximum, never reaching the global maximum).\n",
"\n",
"[converging]: http://softwareengineering.stackexchange.com/questions/288777/what-does-it-mean-for-an-algorithm-to-converge"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\r",
" [-----------------100%-----------------] 1000 of 1000 complete in 0.3 sec"
]
},
{
"data": {
"image/png": 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F3d39gvH0t+fx1oHcplduQEKdng6CIKB/mBoDooI8foIslwlYEB+J3/Jafqf8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P1WZmogVARk4uMpL0PQRl7HnxXoJ29OtAQ8UANH6+FlJKWsz3D/XpGVBzfPK7dg3qgmuyaM3L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OBzC4J8HvraJBZCKRZEUH7bb2B9+0vRP8tUiIVEsmvEArUQVRULSbdiYXSFUzenjh8Xmx13\ny5lVAlAn/OTr5Hg1DLFYyuycUgrhtWmziYVsg+9DIPRxFxZekuhOo6YYgErIwMSs+CsWYiJA1xUL\nama1oCgW9Ay/2s5VPsMuI+HlXAoR4LEgA1ybWGjNyZ9P7IT1sXeCb38q+IWWXymErlhYJhu9sJDx\nSDvS7qcfp646fYOB6wq76HXIvf7vgL0T5M7fDBVyLYds0ajBJsN0hZtcY8LUZWtdIXi7pRAu80ar\nYRNsE+u6HD+uzIkAycetOj3zfkkAGRcsB1QrZJCoz+NdIRby4YgFORYX5oBMFkzGNAHvZUaM3qdt\nxnnNpPV/JZlbhyLGdOjrup0EGaJznJ2mazUzSbG4PN92MrzNlJWqGkwnFlSyWcuuhzY3V+ftgBau\n/Mb/Bb/zZopRbHNO6UuSbt+8USUWWJNOMa3CS7Ggrq0y4aIQC9Z1V4H/8oeAII94teIkBuT6rCYA\nXaUQjR0YQkNtE6macGqlEG5iIchjQfOyUwmnWAyY2Anrlz9ydURhB8wbOwxFscBlD2btphlv/SCM\nD3w+nOTfr91kLkcPp70wK8SCShjIYFMO5N5++n+52Oj/EEGxwB+4G9a/fy706wGQS39vP/i3vwjr\nXX8J6/Yb3PKZVhULfh4LMphXJ9NKiSbNzReCiQVk0SFr/EqFRsWCvIdBWTm5SCiKBf7sM7D+56fk\nXVEphyo1YFm9FKIVxYIkFjTFQqnokiEyI+byQGCxmKt1WCSIiZiNrqAuJ1GRSDZuZFUiT12wS8X2\nJNDyc2Q/6W5lPe1Nq1oKIRULE6QUiTdRLKiECufgj9zv/E1TFdh+AnKzl0o7HTUAIQeVdYkeGXxZ\nJiM3CmHLIXSTpLBwucN3qQOO15ztqVjQSyFE2zbdLMk2ec04buJ+5o0AHd/TY6FC9zabW4alED4G\ndoAzL0lioVV/Fjmm9LItHZaPYkE/r31UsRCpw41ZBVavo03wg/cCunGjBhaLIX3uhfRDmOskEwDC\noLMBcj3UA1+5xoSpS28wb1TaTUaBWgrBLdqQqRtZ2epOL2eU40j6EZimkzX321SpbaiXGn7lo10g\nFnghZCmEVLIszFGd+5HHgb3mEqCZItLLzV5uinr7KGnRIrHArTq4XrYiO24Nj7pajPOpPRSL2+Wo\nbWyqhdmyr4rP9Ddv9C2FUOPnZlDP3esZBsBnp4AdT1O8mJ9X2on22OfF2rkGgDtm7nhXCBmnK4oF\nNX6Qa/a84rHw1GPA6nUw3ioMpqVvAuCszy7FgloKIdUBUYgFGQeYjep1+zUhiYVkyulSYSc9NcUC\nt8Cv+gGVt/r5sCwC2nToWOZQZcRyotIGBzv+uQAA/sxW2//ANwsQ1G6yWgEvLNADVa97KhZYPA4O\n2Asry/WAA+BeigUZqLZQV2597ZN07Ev+KfR7MDIO4w1/D0zuhvXNz5HkrF5XfCFC9sWtua+zCypR\noU6mwlylwdl6MWGbN+btBZIlEuD5eUeeGUgsNCoW+DVXgv/uevCxVWDHPSdc1wVtUbMlaZ6KBdN2\ntabzywLMcJtvAQ2Kha4gHgeYAfbnfwHWTuY/kWgYO7xecxYlVX1ULgI1WrybmUV6oqYTC10qhdA7\nDiSSQM1E/cNvoyzi2EqHhU4oz7kqy4/FnNZIN18L/r3Lnb+VixR06Z8nx6uulKpWndIV9bqNjAO7\ntjuBqnx/2A2vML9qtd5elT9zs4quVOur5TQS8pmtlJ3nQycfpMOyXsYgz3lkjFrVffNz4PfcBhx8\nhPv9qmlTxYNYkNmLZGp5uc0DzbtCAHbbVLTaqlXvw+2HukWqER36+ruveSy0Y95oVsEO3Ujt93Y8\nBWw6tfl7xBzAq5Xmz5eMVWIx72dfmDA3ZMlbUixQmag9d5ttEgtqKQQA5OcdSTtEwgBoUCzYhKt8\nJpUOMV4mhQCVKfJKF41+W4Fff/oOtJvkD90DftfvnF88s5VKQfwgzyOdJrJ4YQ7I5MBSKbDn/1nz\nD/QynbOl3mkq4ZxrzWOB33kL+E+/Q5vkVJrKM+ScNjTmfvHsNJFRnVIsAKKUy2P+UpNCyZRb4as+\nc+2YN3odT4DvnXDaXAO07stnz1YspNpXLKS6WQqhdVbQFQtyTlAUC3zvBJWHHXQwPfeVMnV1YoY9\n1ljMcL53WS2FiL5Bt+cZs+p6ZpkhSs0ti76HGs/7jb9Ewkm+VSuOIlVCiWH4r37srM0HSiE6jFjc\nqWX06/urvBZA8ILvo1hgkiGfmSLpXVrp1ezFUskHPpGiIL6wQBtb9dzsTHgLmbxWMl89NImykRVg\nK9eAHXsSsbalAi2ytmIhpHmj7bHgDhi5Vae/KeaNDrEgHny9/nEx4eWxIJnBivRHCJhk1eynAJeT\n0p5nwXduC1eHrCsWAFqoveRspluxwAyDFkZlMeKcNygWuoJYnEwvM9m2CCIW9+oKoSkW9KxxVDPH\nRSMWhEmkItnj5RKwcxvYmS8AO/l5zlhTnxtlkWFq0DW1B+gbAPvbd9PPJS0Yr5u0uRdkj6cDcVwh\nriSGRaAlFyCbWAgZ7MvMfUgSy/aGKJccMqLLpRAuDI0CuV7wR/+okD/aM84Mmu91jwXxbLOzXwyM\nrST37Wq1kbxwKRZ8SiFSKZpz9G4uC3PRa847AF4PUixopRCtPoNBXjwq/BQL+vq7r7WcbMO8EWaV\ngv9DqI86G1vR9C12IiXM8yVjlVTa5QFio1xy+SvYkM99KPNGMbfYKp72iAVeayQWXKUQR58IjK0C\nO8Gj1FI9X9NU1gWfsR9PRJ6nPEtE24FfGzmptGoD1vVXg//hFvBtT4JvexIYGKIEiR/UuAmg9Tmo\ndEKHbrIOuOP13n7webcqjj/9OHUUkv89cLercwS//bfAhiNhfP57MOwyU3Ffh7QOIXPTNIYzWVqP\n2lIsKISyFxRigfmVQvT0AZMT4BM7wCd20PX0eu68oJ67x5jjv/0fKoM+6XTAMOgz7HaiIgYdHGno\nNtMyuuqxII6tKhbU6y19W1SPBelpBdC1XJijubh/0O2xIMdISSmFkM98VMIpkXRUIeoeTygV7JJz\nwGUg2QDVY0EkJlxJcCXO4bf/FvyOG9s77zbwJ6dY8CcWpImMR4ZLwsfYx94UzkwCG44Eq9fBi3nR\nl7buZAJlJlISALEYkM6CX381UMi7a93bMG/kVr0xq6CjbgErVoOd9ULnd7J/fTzhLFpxD5maF/Ta\nH/33HooF+8Hv13rxLibk/SwWbDNDO4AolxofXh1egVulDGzcBDz6R+Dh+4Ajj2t+HjZbrkqi0t7Z\nTC+zuFyP1qe3SmNvMRQL7bSrlEh4BG31mjNuFLdll2NvFJmXOiaTye5uagG3YkFkXtgxJ1LJgfze\nNVXS5vZYsBfNYoHqqtduIOWT7qSu+gkklNaiulEQ4MoGs8FhOp7eoi1ksM9lrWKI4IebVVjv2gLj\n0vfR8TM5IjC6dQ88OvmwWAxs08mUlZN1lYNaIBWL0TmJ7B+vmWAAuCBz2FkvgrH5QvCH7oH1hQ8B\nu3a43+9SLFTsY9ioVOh6pd1mdvz+O2F95aNArhfGZ77TviQ1CgI9FmQpxCT9v9XMu+iew6tNFCph\n2k0CnsoH64ffADv1HLCDD2/t3BYDNrEQYfNXrQKJFIy3/Qtd//HmprtMyntDbGy5JBb8lHI+JnIs\nk6P5I0SLOpZKi7mrTEq7TnosAI3EwsAQYh//mvd74wkASgLIz8hVwqslcgjwZ56E9cn3wPjUfzid\nwNqFn19YJ7pClItgxz0XxpveGerlLJmie6qOjVbiDqkOU6FIvVlvH3kSCfByCdYn39MQlxr/eBn4\nYRspI//QPWCv/VtK9KkG0OJ80dvvKO3mZsAyOYqZsz1tbcRsVbIfsaC3m5zYAT4/C9Y34Phpja8C\nv/V6cLW1adhxo8zbvFJunGMX5oCDD0fsze9F/f1vpnVrdAVdIxHLGn//fu+5txUoCqHIHTZ8wFJi\nvNmbcUd5xGs1pRSC9he8WKCyB5tYSAFScTcwBEi/n1jMXl94hxQLkOcpW9e7PBHiQIw7r2nyGSyR\ncM7L6/n32/MdKIXoMBQZcTNigcUTYkKoAX73wS/YkcRCqUhsmmVRRsfUBqR8r2Qm43FgdBx4/CGw\nF7wUbN2hzjGjKBYkzBqQajIx1Eywcy4EO/Qo5XvkHPMj1WMhzDn4eSzIEhSXx4L4/vMz9DndzqoH\nQW6wSkXlHEUtZbnUXG1gl6y4iQU2uhJ8w1HAYw8E1ydKyGBIXdRSPooFT2Kh12FFAbuWmXX72q48\nCFgbob+vDh/zRpZ2ggKuZ7eiZo80xULHs0kS6udAzDGS/LE3/WQIxlztJr09FlASz2ZGjEm9c0O9\n7g6idMkg4Iwv1VBJmsjqioWwEn0ZoIUhIIsFoJgHlxJMWTrWNY8F7zmbnXQGBW+/+gnY+Rc3usYb\nMc1cUlEsJJJOVuHwY+n/MoMvoSoWgkohdDM7GfAUFoBtjwOHbmzl23YGNdO/fEuSR1Ji3mrmXc6T\nzZ7dsB4LukKuXgf/zdXgt9+A2JdaaLW4WJAbqEiKBVGKkMkCq9eGf19YH5lqBUhnaJ4qLjT+vVL2\nJpHl2hW2K4Q8FuCY2UZtN2magGFQ0A0IYiHEegu4z7cWQrHgRX6HgYwFZ6fa8yFS4UeqG0Y0Y1AV\npWJrpqyqGlWilbgjwGOBFAsDwJOPOn/b9gRQr8F4zyeB8TUAt2C9ewv45G4wxsCv/Tlw6Eaw5z5P\nHJ/mEabe7+ExZd1SEjC5nvbKAJqZrqtGv30DwI6nYX35I4h94PP0TDADxqX/DEwoZqsGA9S9QRDU\ntd5LsVBYcNb7lWvAd22nduWZnE0AsA4kitgJpwOXxMAG2lQ+eEE3b0wkAMuCde2V4D/5NnCsUNdM\n7YF1xbfATj2bzmlMELHJlNPVaGCIzHABt2JBrv2cO+VUUQmneMJJ+rkUC1qc1+wz1Bi54kEsyHH+\nkleDbTgS1pcuE595QLHQUTC1FMKvPY+E3Xc8YMH3M29UZV9pMhFCuaT4OmiZQ9uFNAHjHR8FSgWw\nPi1rH6BY4JwDe3eByQy7jpoZaPZiu9UntNufyYKXChQ0qx4LYYIgm1jQJjOd0BFBDrcsKoXoG+g4\no9kSZPAqO3oAohZeKhZCEgtVN7GAVBrGX74N/ImHwQ5rvjlguV6RNVYWNW3TAcBxrtYzmbkeZ9MK\nOJvOLisWjDPOA844r/0DqY63EurzphJcqkwtCux2k/GOlULwYp4MkVaudbJSusw+kXDKVewOJOJ7\n+3WFUFRXvCg8M0TQx8sld0ZCbW0pyzwAbQGT5o2KPFEEGqzBYyFkFlEqFsLME3I8FxZsRRCqle76\nXHipzDaeAHbxXwGMgZ1zfuPfY4ZbEaKSWgrZyOJxsC3/4DigS6iKBa9SCGnIlc44RkwAXfN0BuAA\nf+xBsCUhFmpgOe/gmsXj7jWhxQ2yUyMakVjQ1t8G5YOU9RZDGo8uNuri+0fxWKhWEakVntbi2f/4\nFYpDEklvxYIfsWCXQoQ0bwScuaUT5o3xhHushJXhu2Tj1Uaz3YbXR1O32ZnoZoalIWDdeQvY6rV0\nf7w2IZ0wbwyTUFEhx4QyNljLpRDa8yATKqm0085UgG99lOKyQ45wlLkDQ8D0JLhhAIzB+KeP2kSC\nTQKr93t41NlQAg4Rkutt02NBZLyv+i9wecxqFXx+BmzlGncpxEtfD/T0gf/02+Dzs4JsThHJHbU8\n2GXe6JEYKCyAja+mzx8ZB3/oXqBQaOya0iZYKkWlnt2A3llBqgx+8m36eWYKGF8NrF4Hft0vwKeE\n8aeqWBDEAusfhO0S5OoKocxHkliIukGPxyl2U89dPX/Arej2g94VouG14psMjwEHHaK874BiobNQ\nA6CwHgtBfgJqRlCFq29yGrC43fGAPtPdFcL2X4jHSeqa8CgFsE2XGuVM/M6bwf/9szA+/FVaZHQ0\nW/zqdTL20BZQlsmBT0+CpzPOOScStts8n9wN65P/B8YHvtDIRPrVztqtWhRiAaAHZH6mqbN116Fu\nOpLKhGWaTpePIIgJgZumc59EAMbGVjosaTPIiT2uKRb0xcH0Dn5YtsddUyYnw2yXSyE6Bd92k6Lr\nRDxBJqeAs+GL6tBtVinLZcTIkCvvkZ1rEfwn3wa/5dfACacidun76Jd6BiyRbGCuWTJFpQR+XSFU\nj4VSgbpvJJK0COpZvrrpyHj9FAt6u8l43OlOI5952eq07CGlVGDdej34Db8C5MIdxotFBoz5BSeA\nrZSi+2U0g09pG4vFXK1XG2DE3ONL7UiikXWGF7GmENW2Ika5PrxSBpJpkoarz225RBujlQeBP/5Q\n4FfrGoK6QgBEiBRrNG5aJYTsLhtN3teieWP9g5eCPf8lYEcc29r5LDYieixwyxJeRVGIhVTg9ebb\nngS/7TdOFizXC+zdBV5YcBNmvsQCbaBYKMWCLLNyKxbUQJ7ffRus63/Z8Fb2vBfBOOVs9y9Nk+ZD\ntY47bLbc5bFQDalYiKIgFWNe79oUAfwbn6btwwmnBigW2iQWSsUWiQUZ20UshfDy8VLj9R7y/uI1\nk+KArY9Ri3KVTBocoRasDED/kHssqj5NAmxsFXhPn0OKCxUgGx5rTzq+Yg2w/jDwpxTSIk5rOL/v\nTlIfqITHKWcTsfDwffT8tasWUO+9F7GQXwA2iGe6tx9YmAVKTbp+LDekpcm6iA2lWkmisEDlHm95\nL+qXfxy453a3OWcqRaaVABFSEnprbvt4eSoxCtP1xgtBigXZtaZlxYLHXCx8SJjo9GfjgGKhw4gr\nQXkzYqEdxUIq7bCuqQwNwPxCY21Og2IhoFwhnqBFwkuOLHrZ82e32cSCq71NM2JBylH1QECWQqis\nbcyp8eaP3A/MzYDfdavL7ZcUEJLA8S6FsDdSsj6qWgGfm11a40bAHbzKbIqUjoYqhZDSN61tUKsL\nRM7DvDGVdmczgUZDQPv9vcBdv8PU370cfNOpYMecRL9fyjKTVqB4KNioaYoFPbtVi0gs1EzvLiVt\nwFaLqG7OWimElPjORmcAACAASURBVOzZnyv/ZlbdrTZdRIDiXF4sANkeUviks43mjZpiQSqlGGMO\nyaqYBNmv6+1zeSywWIz+rZsK3n8n+B03gv3NP5Hk9Nc/p44gJ50BPjsNPHBX8wsl577CPD1j6QxQ\n6KLPhV/5WjNohlP8nttRv/U6qkk9/Ojm71clsfIZdpk3kuwc6QywW5G9VspAKgN22NHg1/wsuEtR\ntxDksQA4Y3h8NbXxavXYQMcUC6hWwZ99hmqVr74CbPV6+098fqaxxGWpIeORVuXqtsoqQpDYpE0i\nf+Au8N9cTR5DyRTY5gvBb/hvWJ99v2PsCgD3/R446vjGA7Ri3qiXQsg5XJlrrBv/B5jeC7bhSOcc\nH30A/A+3Ajqx4KFYYGE3tUp2l5tVML/Ws/brU9HWHOkpVch3rvNNteKtpuxAVwjyvmm9FIKNjIOv\nXkfntmJ1+PcLVR4vLAD1GljfoKPySKbB+vrBAVhf/DB1cJjaDfaCl7kOwYZGwacnwThIjaD+zYtY\nePHLwU45B9aH30q/kOTYX77V2exFABscRuz9jS3frTtuBP/m54A6XMQVGxiiFrIP30sESrv18KrK\n0Cuuyc87G+y+ASC/QMaY+xKxoJdC6M9rYd72JjK2/AP4728GG1/lrKPJFK3FyaRjWAnQHGIrFjRi\nIZmMvg6rSlW9PaSMM6R6vJlioRagWBCeEhgcdXdLWwKPhf28K0Qr5o0hFQseiw5jzNnApdL0wFYr\nxAaqn+nlseAD2jxkvOXIUmamtuBRe843y/6JrDfTg5RMVnSFqDp/UzY2TE4+z253v0/NxDWYN3qU\nQgDgd/wW2P4U2MASB35q8CoZ90QCqFXJJLBZKURMsI7qxrBSCt93WCIn5OhpRU7opVjQN6vytede\nCHb+xYiNrwK/+zZnPHTbvLFTaKJYcHWFkJN+1M2oqWycOtUVQp6bq0e7h3mjhF0KIQzB1IA1oWVb\nXNly8eynM77mjfYxXHMddx9bBk+JpOMArY6VVLph7rF+8h/gv78J2PooeQHs3AZ2wSthvOFSsE2n\nUFamWbZMXB+eXyDlVjoTPRMYBvUmm2Q/6JvaR+4HpvaC/dlrYVzyrubvl5LYur/HApNdIdQxI8hM\ndtDBdL9174bFQDPFgtgEshWr7RbNLR0bCHx2uWWRoi6MeaNZpQ0nAKxeT4SVPM5//xTWb/9nUTts\nWF/7VKDShNuKhVZNL+l66e2yQ6HZHFfM0/WenyViYWCIxrhKKojnWsqoVdg+PmGMRtNSDSV9coQK\nQ/zMLQt46jGwM18A42/+yf6PHX6MdymBHKvqWAnrD6DOC6p5Y5BiQSNorFt+DevK7xGx6gc51jtQ\nCmGjWvEeC22aN3LZHaMVjwWZROnpRezDX0HsE98AGxgOfo8KkZTjV3wL1re+QL+zO6claMMNkBn2\nyjVg572UuvKoGBwGZqbAp3aDDY83Hh9wEwvZHkrKiXstySiWznbEY0AHU6+n9pywjZvAH7zX8d1p\nB+pc51VGW8w7HeGkWnjbE5Tl3lcwMg72mkuAw46hn+XzKn0oqlVHFZLrhbH5Ane7VBkX5fo0dahC\nLKhJm1K+/RakXoqFRMJJ5hgxIhmC9g1KVwjuZaQrnzldTd5u69AI2L8VC4qM2GZA/epNmigWOOf+\nigWAGL/8PG0MhUsynxQSYZtY0LtCNLnhqYx37aF8/97dzu8WlP7KzYJ0n80pMjkKZs2qM+DjCfA6\nPRSyBRXf9Yz38RgL8Fhw1xDxK74J9PSCeWVAFhNqoCof6kSKxo2UngeAyfZE8oHnXCgWWpASAmC5\nHhj/eJk7G5pM+RMLmj8GW7EG7KWvQ/re22Be/n+pZg9oTdK4lPBsN1lzBwU1kzxTZHDXjsdCp4kF\nL48RL8WChMtjoer6Lkwdk2o5l/RYAJwOLioU2T875kRg1Trnb70DZB4myUH1uq5ZD+Mdl7lNONMe\nc09PP4CdsH72n2D9Q1ROcrRYsNX50whYhO1SiHlqrdTbDy5bbnYDtYA5Owhe71mxGsb5rwj3flWx\nYJdCqOSjNG/MNAaD6QxlsQBg5zb3Bm8xEJaMGRceP5YV/hrbpRAB91tm8z0UC6S+EerAdIaUb/fd\nQX8sLDhlTSvWgN98jVDFpMFO3ew6Ds/Pg199BZmWXfTajqhCeLUCftet4BM7EPvwV7xfFNGboqGk\nsBU081iQ16xUcLLPx56E2LEnuV7GyyXvbH5LigVx/qrHwuAIIFusTu0lI+VDjnC/L5cDntXiDvn+\nhOaxEKUUomaG9FgwbRUR5xz8+/9G7xsc8fZqARSVVgeJhXKpO6UQkjRsJW6QCZmonQTEGsen91JL\nZcDOyDLDAO9zZN3Gy/8CbOVBjccYHKGubLVqo+GtTbZ7jN1kGqjlu6/szDjXU1ebso2bwH/9C2rt\n2S6xMCjUGl5xTbEAcA4mkliQvm7zs9SCeR8BY8ytmBbPFTv6BPBtT9AvA4gAuzNNT29j2akcKzLp\nUS6BFwrtlRMkkg6pqJYLqZ8H0LwTRGAklRi5WgHrcRvBsoteC/bcsxoUW0vhYfeno1gwq8Tm+rHR\nsWBiwZ6s/WRyUsqeyjgPrJwk7bICaRTYXLEAQAxsn37SAPgeRUKbV4mFZqUQPrWEmRy9t6g8SKoE\nXU5UO7e5s1Ty8zK5cOaNAuzCV4GdeHrwuXYbaimE3vJxYT7cxlxtWShb1LWqWABNjC4ViQicXTB9\nSCGB2Cqx6G57kjKfzdqOLheIDbZrXKmKhUSCnk11E9aOx4Ic+51qN2n3F1aJhbCKhap706kSELI+\ns16nxU6qldJZH8UC3W/j4r+Ccfq59p+M934axj9/Buw08TvFY4ExBrbxBPcC5KWW2b2TWPFdO8Af\nvg/s5LNtFZMdLDXxWbAJ3oLisRDVbT0MPNpNhoL63Mjv1lILNWU98TJvdLWbVLpCSEPLoVEglSGZ\n/2LDbKJYkJAZkjDeGhJ+Jr8qZCtGv/7nch3NivVmYietu3MztA5mcoh99F8Ru/ynFDxONao++HVX\ngV//S/Crf+RW/rWDWSpRhG7kqaIeVbGgEfStIJkCD1KIqLX/ARsbls54tz+Vm7IQzxkzYvQdKmXK\noNbrYKdtBiwL/L++Bn7D1RSn6a1CMz1uVaaEbN+nruOZkJtil2JBIXeDFAvccu6dSkYEjedqF4iF\n3Tu7Y95YjmD6LGOdqDXokiicnyXVgWXRnCjXyB6lXtxDMQOIunKzSm1YR9xELFPKAxvPXYz3bis7\n1ThSP4/DjqExt/XRtmXr7PRzYXzoy/T86AaskkDsUUohJBabvO4g2HHPBXvhy1xkQ6B6SppXrlnv\nHrOqYgFwYi2FcI0EtZy1QbGgxnq6ylSD7rGgvZbFE6R0XAbYvxULcUW6JhlQP/ZGbQ/mBbmA+LGy\neikEAEjFgpx4bY8FqVhosunzkCMDcCZ/tTY377jmNi2FsLPeugFglpi8+VmFDFGMdWx34wJN4LKW\nTR4vm7MHvvWL/6KMkLzeXq6nvR6mlYsNtTZTTK4skaTrsDAXTnkQVx942V6zA0qBZKoxa+znjyEQ\nE2w+3/bEvuOvAChtO2vOuNQVC6apOfUvH48Fp3Y8QLGgGnPKz5eLhWkKxVDB22NBtg+Vi10mC657\nLARkmtnwqLv21FBKIbygKRZ4MQ8szIFd8i4YXm7PzeZPCTn35ReArEWfI1pudgM8KrGgblSyOWB+\ntqXWrYwxh5StlGkebGg3mbLneNtLoVwEGx6jf686yDtL222EvGZ2z/Z6Df49mjXIzVsIxQLzWx9j\ncSBWJ2Jmag89cxtPAB69n8jgHmVjPzACTE/Cuu4qUvgMDAHxBPhN15AqZOc27w4IUSC8jwLrlZuY\nN3LOqYQy0+PexNuKhageC0GKBSUpESWAzrZQCgE4Kh1pRDy+GuxlbwD/6bepJOPI4xoz5tlcQCmE\nplgIK+NXz9dUu0L4EQtKa+l43K0Yk4rFqT3A0Kg7zuxQKQRXfTmqQe0m21cstFIKwZLCN6tNxQIW\n5pz/V6v2pp8pSRrmRzYOOmsbG9I2yR6lEDbksVsp/YgC9fi6YiGVAg47Gnj4PqfcOCIYY8Ca9UQm\nFvPgD9wN9PaDrdvgyPFlpluJv9k+pFjQwTJZsFf+tfv5CFBPGRe9FvyCi2nc3XWruyuEuu5lcgAm\niRBstxQCAGJxh+QSP7s7QySczlxeECWjnHOfrhBusL9+B/jtN0Q/7zaw5MTCww8/jKuuugpbt27F\n7Ows3v3ud+M5z3lOZw4+MERmg1Zd3IiAwdHMY0Gy1D4BF8v10ABNZ0i9wAyPUgjNvDGUYsGLWBC/\nm9wD6ztfBgDwvbucvzeTiPtlvWXgXFQeJFWxoGYw83MexEIPUC2DV8rg119ty9cBKKUQioeA6ly6\nVFDvp5xc5XcvFRxDxyCotZeSCIqgWGiAbMWnwqcrhATrG6D7uHMbsKqFXudLDNvZ16w6AZ9lOfcn\nJjfYTjDHzWo0M6xulELYigWPTgJ2KYT8LjGlBZaQt5lVmjdKBY+uEKbTPk+aTKUz4EoLLvq8FjbR\nsSbEQirjdK8BKCsMUVfveTxJBjWZe2QphMw+pjKetcsdQ9RSCKa2r+shsrXVrFYsATz2IJFhmZx7\nbZEGr+k0jXPZl15xe2ar1oI//iD4U4+B6RncbkLtte6Fw48RpSxSldFC9l0aAQfd74BSCAAis5QA\nkknwnUS8sEOPAn/oHvDdO53AGQCGRsAfuAu46X9JSaDUurLzLyZDtQ61OuUzk3QuuQACylYseG/+\n+G9+Bf6jbwDrD3ObwJnRiQWWTNlyYU+of4tCLLRSCgE4aihBDLNEAuyFLwOXGUevzWOWyjS5VXer\n8EwxVl0eCyHl5Oo8a1ad59OnRNVZo0wgDTfJbVbBi3lY738zjLd/yG1yaZs3ttkVwtRiUz9ioR3z\nRrm+Rmk3GUbl5IVYjIhleX2mJ2md0L/fplP9j7FmHdgZz6e5SCuj8TJvtCHj0W53z8r4eywAgLHl\n7dT+skPzPEumwO+6FdYDdwGxGIxP/4dDIApFFUskaG0r5vdpxYIEM2LOnqPJPCkVllyLtVxG1/Ke\nFfPk4RH1vOJi3tAVBmvWu5+ZeKK5x4JUTPl16FFgnLYZOG1z4Gu6hSUnFiqVCtavX4/Nmzfjc59r\ndFNtB2xkBWWsZqabMzzNukKI3/tmUbKOYoEZMaC3D5jcQ5kqO2MpDL2qIT0W0hlv46lyCRgaAUZX\ngk/scH6/6RTg3juaZ3L9ghQ1I2cTCwlF7lcmmSK3HFkV4Cx42Ryweyesyz9OmbcXvRz8f/+f3doP\ngPvB6VteigVII0m9HKEZkimFfBFBaicUC16KFR+1iQRjDBhbCWx7Yt8xbgTc2SCIcagqFqQjrhrM\nRS6FUDZOwk+D12puNrnlY1ZpkS4VnRpcvRQi7qHakWUANVNkOne7AyDpEyMDPkWxgK2PwrrpGvul\nfGJH+BpNtd2kF3TFgpxnfKSo9nGakZry+eCcFux0xmm52Q3U6+EzqSok8cKY29eiFaxcA/6HW2gM\nr1lHHSUkqqLdZDpDQYeUNqqdaA4/Brj1OliXfwKxz36n9e8QFU0Iqti7PwEA4H/8A/2iGZnkOnYI\nxYJN4gcoFjgoQH7sQQAA23AkXcdnn3GNUTY4DH7/nQAA4+Nfp+eDc9qATey0OxR1BNNELLh7n2lo\n1m5y+5P0f1lGKdEGsdCUPFU2vCwKsZCOQCyUS85coXaj8QHLisRNqeSUnQLeXSFClv/ZAT9AxECz\ndpNy/pb3Qo3NZAlpvQY+M+UmvKuK0rMdqEmawVGwQzw2oW2aNzqlEFE8FiKun/EElTHJMsiZvQ3x\nuvHVHweOL5ZIgm15u8/xlXJKHTIe7ba6M6gUAqKUo5MGijIOSGXIm+rOW51zUBVdfQN0z3XDv30V\nqXRzYlyFugdTO5DVa86YKBUopo4KeS4aaWC86k2Nr2tWCgHQXBNCsbCUWHJiYdOmTdi0aVPzF0bB\nqHCHnZxofiOaeSzYwY7PgLVrn8XD2zcA7HjaXX4hB245XCkES6XtLIgKXi4Baw5G7G0f1H5fhPW2\n14CbZnAmt+aT9XaxqopiwVQ2zcOjwORu8Py88xmyBeLxJ9NCbVlg578S7LCNRCyoC516D/qWg2LB\nyY7YAYmqbAlVCqHUiHdcsVAFtyxHAuhnvKmArT0EfNsT+5a8zW7bqWxS9K4QNVML5toxb9Ta+6i+\nC5GOWaOAt5h3yjn0QNWrHMhWLJjASI/79fLf9boT/MvFbvU64OZrwb93ufs8jjg23PkaAfJQiLlH\nrT2fmQJ6+vwds5vNnxK6b0M6435+Oo16rTUjMgE2PE5z2fgq5360GHyqGWfr2ivBtz8NQHQGqNdF\nKQSdm/X1T8P4h39xzBsBGKefC6tSAv/Rvy9u28mwgZlcv1pRLLRp3kifKwxKDz+a+r/39juB394J\nV5tCDIpgvX8ILOeWGXPbSNDDxygKZClE0PGaeCxwacisE8p26+qIxILP9eacu4iFKMEqi8eB0RVU\nbhUG0ldEnlMYQiKrqCmV+8i9SiHCQiVpXKUQAeaNgLPuyFI02Z5aEgia942tzmlXsSDWE+Nv3wN2\n/HO9X2PE2usKEaEUoqHrWauIxch4UZ7D9GRDRratTg1BioVUhnyG2pG6h0E80djyuZuQc9tB64Fc\nL/j1V1HWPZVxm0f2DVAXuKj3brkhlaLnLOw11rtCAM76Ikz4USp2phSiydxqvGILMOpPYLhUvdVK\nZ/YYXcKSEwtdhZD38DtuBG9mjNKux4KsjZIToMzGq58pJ7hqmeTQfvViEgHmjXarGBWSUS8WwJ94\nGBgZ827747c5zSqBswxgVFf6SpmCuNlpt2JBEgtHHQ/jvIvsX3M1Q2efY8LxXdBcTZcEXgGJGlSH\nWWCTSp9wGVQm21gIJeRYqlYcwioMsfC6vwN70cs7y4B3G3o2CPDuCiGDOcOI7rFgOlI5uz60WmlP\n4WFWnWe+WhHEQs2l1rEXBl2xwMmsih18BLDyIPpPgPUPUYeZR+6jX4hn1Dj3JcC5L7Ffxyd2wvrg\nW6glVxiE8VjQ2yAGXR/5zDTzWKhWXHXALJ0Bl+RKN6B0ymgF7NiTYPzbzwDDgPXFD9Ev2xkfsYST\n2ReKNZZKAwcfBnbqZqqFnNhB11klM3v6ydju5mth/foXzvmd/DwYf/aa6OfjA855+JKasGSSCqlu\nC1QsSKPkAPNGYTjKf/EDYHQFoK6H6roiiYVVB6EB8jmUUvVKmYiJNeubfw8PyCRAQ8tlFc0UC5MT\n9F1ECadNdtuKhQjBZJDHQqngT/y3AOPjXw9PfIkyKyavRRgSS8ZXeta/ZtI5+42VINimrDlHNcaY\nv2moTX5rioXefifYBxq79diKhTbNG306QrnQCfNGxlrrTtAJ88YZQWLHE2Tg2MGMLGumWFgELypq\nSZ+huHkxiAURf7LhMbAzXwDrim8ChTzYyWe5z2t0HLydjgfLDXbL+JDfSe/ABTjxgtd+KArkuFsT\nbKzINp3S5DhKjFwpd2aP0SXs18QCSySBgWHwm6+l1oaqa6gOMah4rebK9vNHHwCfnwHmRT2zD7HA\nxlaB9w04G5a+gcZNhNoVIgxD6NduslzyliTHYuTtcPUV4LNTwNoNiH3wC42v81ug0lmn1CGp1M2p\nxnSpNEmpVOmy32bXI4PBGKNrkkwti44FnuSOYrLHQnksaG6tQPg6z6Bzk21xlCxms64QgKgfk63g\n9hXo2SBAUyyIzP29t9PPud7IWW7u8lgQn9uuHNo0HTf4aoWyaurnAD6KBfHvUgHo6YXx529wH/fo\nTcDYKvBrxabSJwhiK8gADb0hybogQyuAxq869+gb3objtaBYGBmnVrncoqC8WTu8dlCvR86kNbiJ\ntxOAqvOoLAdJpqm/+cVbiFiY3ut+1gGwnl4ilu64kQjl554J/sj94PfeAXSBWLAz6WGC32a+RB6w\n5eZB9zuMYsHgwPpDgWwP2Mg4rfXSQ0EhFtjQCDjIr6IBYvPEK2UwUAtkfvO1MC7/SbSSAKlYCOx4\nQdfKZTQmwE2TjnHUJpKGl8t2cGuTFVEVC35lY7r3QsQsWEtqmnS6PcWCCtMkw7sosYT83FwPXR9B\nqPl+l6Sb/OZSmSCyvg6xoJEfSilEg0dEKwix9oOxNj0WqBSrpfspPWGizrOxOLg85zXrqXzMrLpb\nb7cDcV56m0cAYMk0+GKVjKazRCwEEUOdgiSGhsfBjjwOsQ992fNl7NWXgHnMRfss5PcOXQoRa/w3\nE3sCZVwEmio2gUywGqc/P/IxADjfqVwi8vBAKcQSQiwG7OK/hnFGwI318FjghTysz73fqf2Kxf1r\nkU44FcZxz3Em5H7xOjVINGjjj0qlub+CfK+XrFKtw1XAGKPBJ9te+UnvfIgAFovBeMt7wWcmHfZM\n8VjgNrHQBxTU9pY+XSb8Bn4yRRuK5QR109Db52xkB0Nk/ROOqz3vpGJBXr9nngQfGgXAHEPQxVic\nFhN6NghwKRbYijXgmRxtqNYf5jhHR4FpOs+PnbVsU4pfMx0DVxlIqiUXgPMd1ZarCaXO1yvwMWJg\nf/Zq8G99AVixOjB4My58VfjzFXOaZ/s4gEgEXbEQVFIQ2mOhDAyOwPj799N1Wnco8MBdzTvZREUr\nhpZ+ENdI7w/dEuJxUh5Y9cZyqd5+IBZ3FF5qtlCSVbu2AxuOhPGqN8G68vvgt/8m+rkEoVmduYoo\n5o1hSiHqIcwbQc+G8ZdvtU13jTe9A/zZ7WCnnO28Vqq2vIiFhJtU5NLX4JkngUM3Nv0qrlP+zPvo\nfcrxvF8YUAoxtYf6zB+0Hvyhe+hZkRvqtjwWAog7qTyUysRFCFZZKg0+P9fad7KJBQ/Fgmre2MqG\nWK6huV4yAq41UTd5eSwwA+jpA69WwWxiQUsGmVWKmfLzdP5RlZoh1Iod6QrRaoeEnj5qPTsyHu0z\n5b1LJsFe8FLw238LAN7dhyIg0LxxfFX7JSphIdfPxVAsyHE8EmzK2Naathxhd+ALWwqh+VkBYMec\nCP7I/WAbjgKXrVDbUCywEVFWefQJkY8BwJknxZzdVnlQl7HP7U5uueUW3Hrrra7fjY+PY8uWLejr\n6yMpp4LJ/Dw4gKHNL4IRMKHzeh2TAHrSKaSHiBSozU9jhnP0f/hLSBx6FJUvhFx4rVdtQWXD4Yiv\n24DEkENG7E3EYZgV8EQCQ0PBhinFwSEUK6WG101VykgPDiHn8f7JZNLObjCz6vkZ5VQKCwCGRsdd\nrXwAAM+/wPVjqa8f+VoNQ0NDmLXqMPoGYNVrMKoV9IljVzJpzAMYHB2DoZVoyA7i6nlMZbKIDY9i\noMn3XyxMr1iD7GveZN93DA3B+o+rAcuCESIDPJ/rgZWfx8DQEEqJOPIAhlasbF7q0gS1g9ZhBoD1\n5Y+4/5BIYmhshafZYCLEuFqOqJULmAGQndqN9Enk/jxpWcj19SMzNAScciZwimNUOP0Pr0cyFkNP\nhO86yziMXA59Q0OozY9iBkBfJuV6TlsBr9cxWa8hNTSMMoD+dArxoSEUkgmUkin7fpjDI5gFkMjm\n7LFfHRqG7O2QGxig76rjgleAv+ilADPaHlMStVIeMwCSPb32c6yiNDyCvDL3zFk1oLcP/T7XqF4p\nYhpAbzaDZMB1nOMW0NOL/mMcX51CXz/K9Zr9WdbMFAo//U87kI6tXofsRZSdr21/CpXbbkDiiGOR\n9KszhvMcTIMjketBbxvPxHwmiwqA3vEVgd8tCOX+AZpze/tQm96NWQD9K1cjLo43NTyKxNRu+pzR\nMaTE7+uWiWkAWJhDenQcvUNDKK5YiUJ+HoODgx33XbAW5jEFoHdg0D4HP9TmhujZyWVDPzuzDDAB\nGLWa7zxVK8zRcQcHPY87k04DYBgcGgLOc8qBcPYLG17L+/tRePkbkd384oa1CQD2JlPIxmPIDg1h\nfnQcFQCZie3InnxmqO9jH+eZJ5E68zzAMFB76nHf7zZpWeAAkobR8CxVtz2GOQA9RxyDhWuutOcR\nALSuxBMYHmmtvC2RSCA3MIi8TyxQ3cYxByA2ugL1iR0YGBtHrMvrx0L/AGoTO5DLZjAHoH94xP6e\nfuD9/ZgEkGVwzZEz3EI814vs0DCmQcF22PWv0NuHIoDEwCAAjmQygaIyX+uo16s0x6XTSA4NociA\nYjaLRK4HvFxEJpnEPIBk3XTNqdP1Gtj4KtTy8+g30PS7+sGc3kPzRsD1KvX0Is+5/R1qz2zFzHsu\nsYklY3QFhi6/wpegzsNCNdfTegzxrV80f40PFrI5lAEYA8MYfvHLgBe/LPKxvFAUm8LewaHG+fuN\nb+7oZwVhprcPNXjHyZ1Gvl5DCUDf+g2R16x9EXO5XlRB97rZ+gUAtfwsZsS/h0ZGaD1954ftv099\n/19hzU4h3dsXKdYEAP7WfwZ/09thtGlWX1ugWNX4+fdgAegZHg71HQFHUfad73wHu3fvdv3tjDPO\nwJlntrbeNcM+RyyceeaZvhdhfn4eppYxY5e+D9i+FbPVGjA97fk+G4aB/NwciuJ1/JmnAAAL6R6w\nkszeteDse8Lp9H/1c40YLCErnm5yPpbFwcslTE1OujYUVqmAEgcqHu/nihKCVyqen2GJerbphQWw\nQvD3saoVoGZiamoKVn4BrG+QaiSnJ+1jc3G8mYU8WF2zxBYSYPU8rFgcPJ1t+v0XDR/9VxQB+767\nEOIcLc7BiwVMT0/Dmp4EkinMzM62fVo81w/jI5c70idAyMcHMDPv7aI/NDS0fK5rC+B1C4jFkP/G\nZ1HM9gJHHAMAKJTLKHl8n3oshnJ+HtUI37VeKoFZHNPT0+AlCrjm9+4FG4qWceFC2l6JUQAzt3cP\nWP8wrPl5cCPmPCcik2Wqv1M8VAqVqud37QZ4KgN2zvkwL3il9xxRt4BqFVN79oDF46gvzIPlen3H\nFhfzyMLMa9IQmQAAIABJREFUDFjAd6jnF8B6+93zgVkHL5ft31k3XgN+zZWkZsjPA9dfjdJpzye/\ngy9/DNj6KLB6HWIf/orv58jnoF6pwDJrMNu4rpZFc9qCWQ/8bkGQ93l67x5g17MAgLmaZR/PGhhG\n5WnKeOerNRTk+DCd7GMllYU5PQ3LiAPVKqZ37aRSig6Cz9Ln5stl+xx8Xyvu+fz0dOjrUi+SfNyq\nlP3HklhP5vMFz+PWOQCG8PPc+a9Etc695/JkEsXZGZSnp1GfJqVf4Y/3oHzmi8IdG6KEoVxC9bBj\ngIkd4KWi/3cT8Um1XHK9hj/xMKz/+AIQi6HQR5uOud27wDLkLWDNzgKJRMtz+9DQEApmjdbwyb22\nDJ/n58Gvuwp85zYAQH1oFJjYgdliKfIYDwsLBnh+AQtTdL3nisVwn5nJojC52zVH1stl1Ot1VBdo\nPeSJZOhrZAm/j1qSjGpr8/PghhEwx9HYXZieAhNrPU+lYXIOXiyiJrqCVOZmXceol4pgonR17pmn\nwbLRFAtcHD/oelnlEmDVnfXlsYeAagXs1X8D7NoO66ZrMD2xyzNTzZ/ZCuv+PwAtXMNOwBLSc6tv\noCufmxTHXyiXuz62g1AXihfPOLnDsIQJ7IKRWNLvvNioi31Svlxpun4BAM+L/U8shpmZmYa/W2vW\nA7NTKFtWpFjThTbfz4sUP9aeeBgAkK+Yob4jQATz6OgotmzZ0tY5hMWSEwvlchkTExP2z7t378bT\nTz+Nnp4ejLTIznuBHXEsWFin9FjcVS/KZ6ZIWtdJdjEeBwoFx4woCB7mfSSlLfvLklVpc7Xi7SYu\nawnDZD/jCZJNW5bjsZBIAHuetV9i18169ef97Hcb6q7Z0Sd4S1P3VSRS7s4ZHZIoMcZcRn77M1iu\nF8Zn/hPWR/8R/MG7wQ49iv7gJ/1XfS1ahep6b3s7tFHjL8e/dCu3SyE0aa3dblKR1SXUsojFM1Fi\nRgzs9W/x//v4anAA1kfeTm3NyqXgXtfNzG8lKuXG4ySTbiPOPc8CI+OIvf9z4PfdCeurHyWCYWIH\nkQprN1ApTBhENG90QY6VdkshxPnY/ewVd3s2NAJ+9+/oB7V8LpVyxrrIeLDefpJWLsy3LltuBtsZ\nv0ulELbHQpvmjZ3y50mmnZIfOabuuQ31L/wLYu/4iP/7VIi6f5brAU+lg7tC1LxLIfgf7wLyC2Cv\nvsQZZ+pxzGp0Z3K13EvGEXfeDP7fPyWp9NEngPUNevZa7wrkNQoj7VeRyXmXQqhdIVo5/7gooUhn\ngElTlN4FjHtx/e2uW7JsQHbd8OkKgWqFDEYB8PnZ4I5dQQjjsaCVQnBhJMnOuQB48G7wm66htc6L\nWLjmZ8CuHWAv6KxioBnYha+iGH31uu4cP6gUYhFhtxaO0v641c867yLw7Vvba5O4D4Il061dY7nO\n+XnnrdsA/sBd0UxzOw3ZJvSYE4Gtj0UvPVoELDmxsHXrVlx22WX2z9/97ncBAGeffTYuvfTSxT2Z\neNzdk3t2Gujtb6+/vY5YnLLOISY5ls7SQ6LWN8sMp19AKYOPTJbcib3a2+imcs3OF6CAqFKmGiYj\n5u4KIRc8j0VZb/EFAMar/ybcZ+8rSGjtJpdx7dNyBuvtAzvqePCH7wN7yavpd749xRPteSzI8S9N\nNr1MUhXwB++B9fVPORuCgw+H8Y6PkKRU3nvVvBHwMG8Utfp6VwiJJQ58VLBDj4Lxzo/C+tWPwW+9\nnsgAtY2fDqmUauaVUPUg3hIJwDTBqxXwO28B3/2sExD1C/ng3Az5awyPgZ3yPPCrfhTui6idRaJC\n3pdsG+aN9vWpkWFeMukeB0OjznjWSeNcLzA7BSavhfSnWZizNywdQ5jNi4TdbrIFf4yaSe8LIvLC\nmDd2ak1OppzndWEO7IzzwEsF4OH7wx9DJYrU43lBXiudjNm7CzjoYBibLwCfE5kzV2vd6MQCSyYd\n7xc5tp5+AjjoYNvc2frRv1MSZTHITWHeyG1vppCfme1pNG+UJHEEYoEd9xx6/9wMXZtKOXjcN3SF\nKNL1lF03fLtCVIVJbQqYb8yKhoYkpYLID2YAnDsJpVKBjLLjcXB5bSre45PPzYBtOqXRQLjLYD19\nQDNH/Hagm/AuFeSz167nTwiwgw5G7F++1PXPWXZItdgVwiYWvO8JW3cozZ06obkEYLleGF+5IlL7\n7MXGkhMLGzduxBVXXLHUp0GIxYFnt5NxEjOAyd1kStPpzwDCBUZyAOkmaoD/4JLH7R+kBa5a8SYW\nQpr/sbgwl6uZdKxkms5rfhb8iYfAn30G/Pv/Rq/tUP33PockZRSt398Efst1TtvBA2gdGzcBv7se\n1ne/Sj/7bQqTKScwbRWqYkFm8MqlwEwSf+xB8li56HVAuQj+ix+A33kT2Kmb7UBTmjfyaoWOFcK8\n0bUALkImoxWwo46HUa/DevSPwPRkKPNGXjODM3KSnHS9N0nB8B9uBf/Ol6iv+FlCii5k4ZifIXO9\n8dW0waiUwOv15k7k9Xr7m1CbhOqAYqFm0kY02+v+u2oSqxMvPUQs2POK9H1Z8C6Hagv1EJsXiXgE\nxYJp0v1bmKMOTF73Rh7P797GE53bJKTSzkZrYQ5Ysw4sngS/5w5wzsF/9xvwq71JLPail8M453xn\ns5vrpbHtoxTknDvfTVPx8cndYLIlptecVK1GVxPI9ykKL77tCTCVKMzmaAPaYc8OT0hj2JK4bmHv\nZZYUC9ZtNwBCDoz8vKM8AFoi9dmKNWAXvBLWT78N7NxG9+CUc/zfEIsT+VKTXSGEYkEqiiQxqBAL\nnHMi0ZIp0Ua0jRLJAGWoDUmwWFRaiFLJMaa2zUp9CPn5WSBiq9XlDHuNWGpiIZMNrxQ+gGho1bxR\nEv5+a83aDQAAvndXmyfWGewLpAKwDIiFZYX+QfBbrwO/9Trnd8ef3NnPkAM4TODmlU2VjuIZv1II\nsXj0DwETO4kM0MsuzBYUC3bwaDoy/55eoF6D9an30kJ76FFgBx8e7nj7I9JZyqh+/18p63TuS5q/\n5wA8wY49Cfyo44G7hCzc7zlJJKK3KFTGPzNiNKZ1+aqOPc8Cq9fDOO8iAED9qcfBf30VcOpmJ5OU\n9SqFUBUJHu0me/pEKUDNv+PMUkJuYrkVvLGW3zNMu0mtY4qdUd36CP2iVnPapfZRdp7PzQLTk2Br\nDwHLiu4bJW+Hdetn/4mZxx5EvVajzWK7GaJ4AkilI7dTA+Bux1nIu8ogAMowcWYAuZyjfJGQP0uS\nRXxnnp+LLqv2gxzLrbSbbHbPXcc3aaOzILoCeBELTRQLxkWv7WApBGWbeaVMz23vAI11btH5PfpH\noF4HO/Uc19v43beRRPac852WjbkeGtuc03t1IsCy6G+JpIdiYQI4TpiRJlO0rlZUxUIlupogoZRC\nQHjCPLsdUNYpdsSxpNBcBMjnl3/vX+n+hyX+sjnwYgH45Q/pXg0MA6vWgR12NJUAAA3PVSjIsT44\nAvbKLf7nLbtuSUK7VKI4LJGk33kpFuo1pzVc3wCpIyKCh3k25XWwiYWCU/Zgl8T4rJsLs8uvW1cn\nIMfXUnfSSmWWXfJgv4OMLVouhfAZG0MjYM//M7DnhffcOYADxIILxj9/hhhwANb3LgcevAesv8PB\nfrwJQ6ZC9o2vlMCn9oJfe6XTEsvXY0G01+wbEPJHD3a6lVII+TqzBlTLlNU45Ejww4+Bcf4rgLUb\nwP7EM/TsrBdR7+XpSRhv+WeS9h1AJLBsD4y//wCst76SfuFX+xZPgue920TxXdvBZUYL5OnBREs6\nAJRxUsd/OtPYIkw/5u6dLvKMbTgS/Nc/px9kJjCZdGSxgEcpRCOxwHI9MD7/XwC3licb3aMEmkHn\nZxgim9dkk+lZCiFql5981P4VGyNigcUTRGTOzwDTe0kyq7ae83jW+O03UkCw7lDg4MPATjgt+Jya\nYWQMWLGmvWPIQKdWI8WCRh6wDUfCuPzH1PlD32jZxILwWIgn6BrMh/SZaAWt1L3LZ7PZPVdhVp3N\ni0+tt9Nu0juz11ESO5kihdE8ZZJZbz9QLdsliLxcBFavhfHyv3C9zSrkwZ9+DAAcz4xsD1gy5ZQd\n6MSCvE7JlEOeQNTB5+ftshbGmCA7FaVitRq95Zk4D+vbX3RaWHOLng+Blryo2sVxz6W21rUa2NBo\naJUEy/aA794JFBbAzr8Yxotf4f77q94EFqFFITvjPGBgCOy0c5u3cEuknJiqXAQbHBKKRaUUolwE\ntyzKTMsOXckkeN8AeMhSCOuOGwEAhto6NWy7ScDxWSgVG4kFjzIkXqtReWuXuxUsCZaLx8LG4xev\nteWfKiKXQvjEmYyBveaSDpzYnxYOEAsKWCptD0x24ungD97TeYbRlmWFuPRiQbC++jEKyDI5Cj6O\nOREY9TFlsUshBCHixU6bZusPXrlI2ZZUCmxsJWLv/kS49/8JgPX2wXjvp4FS8QCp0AG4WqD6MclJ\nf/NG6ztfJpM/iVPPAXvTO52fTU1JkM4GKhY458CeXYAqkxWyXC6zkwA9U2qNdYN5o/i3tuFoaPm6\nnKCO5wBigTEmzG9N8IfuBZfqAx3VSmMphJxjdzxF89bcNDCuzG99g5TRXZgjLwJJLJQa6x4550B+\nHqk/fz3Kpz0/zDdsCuOsFwJnNbYybAlKdp97KBYAf/NO1tMLnkq7iaeefiDfDWKhFfNGum+8Xg+v\nnKiZirLHR5ItN0XtemOEQSpNhLk0buzrBxbEtymXgHLJe04fHAbuoa4GKORJ0RJPkHkjQOo+/RZL\nZUcq5VYsTJKDO1PNuFIZ8IfvgyUkuPzJh4PNU4Owcg1l3GQmvacPWH/YksneWSIBnHh662qbbI42\nZkVv82vjBS+Ndj6jK8jcMAxUPyW1FKKqmDdyTmMqnXXGeDIF1j8I/oTPvKiAF/Pg3/wc/eBJLAQ8\nm5JY4GJ8eRELXjGhGP/7Y5Jo2Zg3HroR7NCNS3oO+z1aLoUQa0ynFHAHAOAAseALdtxzKfPQaWlY\nC5Mc6x8E2/IPVPuWSICd9nxPM0QXZHA6IJhnr82XXvsd5nwF08qSB4wJvcCSqcVx1P5TgTQf9e0K\noUhSFfByEXj6cbA3XArj7BfD+sHXwR++1/n77BRQKYENKTXt6Uyj4ZaKuRmgUgaT8nyASD7LEu7m\nNeecFGKBa4oFxhh9r0wbJoCLDJZKCbl4tbmiQrSWtX7wdZJVe71+cARszcHa+5wNNXv5X9CcpRKn\n/YPgTz1Ofx8ec66fl6FSpQyYVRh9y0zSq3bNKCyAteKAPr66UTHR2we++1nwSrl5lrUVRFEstFgK\nwbI5Wlv9uro0M2/sIFgyBZ6fd4iF3gEiHgHaOBYL3u7bgyPkE2FWyWNBrstBmzd5nZJpIpgW5sCv\nuZLMSgG3g3s6AzxwF3gmS89COgsmSyUifEf2xr+P9N5lhUwOmNoLgIzMlgSJJLBrO5XBLMzRfZIk\nt2qKWCwKYqHivK9vkMoNAsDvvxPWL4Wnh67mEXFbkMKDGQY9W4Kc4y5iQXoseIxNodjZL/2hlot5\n4wF0Hy2WQjAjRmTcIhhq/inhwNX0ARsYgnHZVzvfrqVZTY8G44zzWjo8S4h6ZVmP67WItFQKIc5T\nGlQd6HhwAIuBgWFBLPh5LGgtCiWeeASwLLAjjqGf1x8K3PAr8FIRLJMFf/wh+v1hRzvvyWRJ9jw/\n29gqrloh5RLg1P3DMWpEMe9skOKCWKgopRDa82L808ddx9kn0NNPZQhNiQWRzZvcDfbqN8HYfGG4\n4w+PUtDLYmAbN4FpXhOsbwD84fvoh6ERJ1vpRSyIUjajd5kFyC5iwVux4Ad23kVg57qvJRseA//9\nTeDf/SrYJe/q3Hm2pFhorRSC1D2m0zar7NOWsZl5YyeRJPNGPjdDpTw9fc5aVykTueBRrsEGh+n5\nn512m3HKjFnV47uppRCFBfAH7qYWfysPIi8nVRkhlZPPORPGX7y1M991X0eux5lr2+nQ0g76h8D/\ncAuVPgKkIonFyXy2VBDGlCWHqDYdxQL6B4D5OerAMTIG47xGhYX1u+uBqT10XF2RFcYbi+mlEAWw\nwWHnHADwarVRLWITC/tfKQST1+yAv8F+D7b+UPCjT2gteROPL85a8yeEA8RCANiqtZ0/aCtdIaJA\nmtL1Dzq1njpUV/yQx+MyiF/Osu0D2H8wOAzs2h7gDJ8E5mZh/fz7rl/zJx+hOtHx1QAAtu4weg6e\neRI44ljg8QeBsVVgai1pOkvdTd61hUzbvJDNASNKaz81a15TSyGSrlIIlnM/Z2zdhubffbmhpy8k\nsRCnoLhec8u6m4ANj8H4yo/p31519fJeMUaZYoPCYl7MNwbIglhYdpJe6T5dN4Fio8dCEJhhNPgN\nsDdeCl6rgU/s7ORZtqRYsMtfwnaFqNdJJi5JH49SFgCLqliwFUZ7nqVWprEYuPQ2KpdES0EPHwjZ\nxWNm0k0UST+Dr3zUrXSIJ2C87PXOa+ZngMI8kEwh9pHLG48vjZtXrO7Al9xPoG4Wopg0dgDGOz/i\ndGMxGJVu3XUrrTEF4VGwpwR+3x3AxHbwPRP02lQKbMNG8LWHUNvcqT3gp2wG69XKbOZmwY4+ETjy\nWPDvfJm67MhnMUxCyNNjQe8K4eGxYBMLy0zp1QEkTz4Lxlve61tqdgD7D9iqtYj942WtvSmWOEAs\ndBgHiIXFht0VoksDWRIGMhj3qmNtpSuEZLm/LXrittNy7QAOICTYgMgI+lTiskMOB7/jt+C33dD4\nt7Ne6MhFV64GkilYP/su2Pgq8AfvATv2Oe7XZzLgu7aTodlf/aOT4QHoeRoaA3I9VBsskXOy5tz0\nLoVAzdw/JHYyk5pqQizE4uC7dtC/VRImBAJbcK08yP6/bWyYyXorFkTQv2xLIUwTKBTa3hixdBZs\n7SHgj/2xAyfngIep41YRi4UvhZDH7gsmFnhdeiwsQlu2VAqolImgkeUmSrtHV426ikFS1fCZKXBX\nKYQgBOZmgA1HgYn38jt+C37HTc5n1uuCkPAhmGRb6fEDxIKEXUIDtETMdfQcEklSTSngsutGfoEU\nrrNT4Fd+zznXeALoGwTrG0DsA58Hn9gB64OXkqfMUce7P2B+BthwhGO+PT/nfF4UYqHsjF/GmJv4\n1j832+OQGPsRjGwO7MTTl/o0DmC5Ih7fP+K0ZYQDV3ORwYbHwAG3S30nYbebJGKBVysNWzO99jsQ\noyvA/vb/UM/pVAZopTb4AA4gKtZuAH53va+CgB1/MmIhWsEyIwb2wpeBP/L/27v7qKjqfX/g7++e\ngYFBHkXi2XFA0BTFpChFMNRS83g72klX3nOMzHuIe7x27NdppddOdnV1luehzq9fq1Uq2s3yoVZ4\nSY7PebyJFOUzYiKhIqGC0vBMArN/f2xmmJFBBhwYGN6vtVjCnr33fGfc35m9P/vz/XzPQq68AQSH\nQUy6o6ifh9Z8IibiH4KwURisA/PMBB2HQsgFx9H61mtAealL9Bfh7aOc5NozFOL6VeX3wB4WmrNB\nSpoBOT7ROrDh6WUzsCBbDoWo7+SOuDO0XajL3+UqASxHXBgNHQbU1Xa7zoJc/ZP1VIaWfrqp/Gvv\niZZKbX9goa0mivD2VaYbbKi3HTZ0RsbCtbL2GgambIGGOuUxW0MhPNpqpdyqAOpqISLaLv4s/h+k\nf3vZPEVp6083lTvVpudsbVUuRDs7DkxTPzKw0M7yc9mez+i+Ygo419dCjLwf4u2PreuHqN2UGkwm\nQSGAxgNyaQnEnYGFaoMSeDPV9qq9I7DQVaaprYwFrcXx666xapt8Ig/GrI+U5+lvWV5EfUHFoRCO\nxsBCHxO//neIX6X1XgE3tZvy5eLlraQO25haCM3NyvzLdhBCQDyY5OBGEt2deHQ2xH0hVlOi9ZT0\nL4uAuxUMN104qN3s75eeyomtbBoK0ZYWLiU/rlw8AsD9EyAenNLzhvcXpowFe4ZC1NUCfkMdnnba\noTK/dogS7LxTXY1SoV+j6V+BBY0nEBQC+USu0vbgiHvepQhQgtSoqmzP6uiCXHENxv98ofMhP4By\n8WHviVZbwU67mDIW3DVtxVnb/3/kWxWQv9oP8S+LLKab7KNZIRrqlJ+QtuFTkkq5s9t2cS86y9Ib\nOgxy1kfK76YLRMupZC3eQxE3EXKhUkRWaDwgt7a2TTvayQWyKTW9G0OKXJ4pmCtJXX8W9SVTUcT6\nWsDNXfnsu8vnn5BUyowcV0uslss/NykBPx//9uFClsUe75zNyBbzrBBG5Rj7uck6y9Qyow6AfDpf\nKUw8eRrESM5YQIMQayw4HAMLfUxIUu9G293clQrSQnT4EjHm/y/k47lA4UnXuOAhlyUkCRg7sW+e\nzHTi5etv/5zqbm7KCWVjPQChzNoiBJCQBJHgYoG4IT5K4KSru+Kmk96+uBjS2s5YQG21dRG8fkKo\n1VCte9+xOx3alvV2qxuBhe/PAACkF9d0PtzBN8DuftDZUAhZliF/9C7kyuvtC82ZPeoOQ1nkE3mQ\nc3ZCTJxskbHQB0Mh3DXt2UqWM29oPAFD23SSnQThped+D/lqCQABEdf2WdX2nopF6VbrivGJkHds\nUvpQwLC2aUdr2wtZ3ik2Drhwtn3oD7UHFrRD7D8++4JpKITRaPfMUCJihDIDxMFsiOAwiLETzcEk\n4etvrnUg1xjas3rsmc3LsnijaTiNZbD8zsBC5TWI6NGQfvWcXe0mcjkcCuFwfDddjHjgEcBUEMii\nQr18qxLylv/bnlo50CrTE/UW04VDd1NBPYe0zWGvcemprMTo8cCtiq5P5ttOWEVffLZovZTp+lpb\nre4Mo66mXwYWeoXfUEBIkKsqOqlEYkNxIRAxAmLMBMe0obPijdVVkL/aD8TGWRfSDA4Hhkd1HMpS\noUy5KJ87oVxACunudTccxfJC0DKw4OGpTE0LdJrFJCJGQERYT50qhIBqQ3bHdYcFQ/rgfwAA8pG9\nSvCkvq7TIqfSstdszywxmJluyDhrqsnOuFtkJ9gbWBjzAOSv/wk567+VWRqmPNb+ueXjr2Q9eGrb\np0EF7Kyx0PZZaDS2ZwRZDuVxu6PGQuV1YORYu9pM5JI4FMLhGFhwMVYnO27K/Mryj1dgzHwL8NRC\neuVNQOPZvyL+RM5kkbHQLVov5eRNEndNfR3oRNQoiKhRXa/YNkOBeOLpXm5R2zj9r/bD+O46qP7j\nNfNyua6mPbDq4oRKpRQRvHGtfdaeLsgXCyHsqE1it85qLFy9DACQFi+DGGajkKfWq31KPgDyDVNg\n4aRSaK0vCjcCEGMfAJ54WslWsgyAaDzb6xw4qGCx6TtXVqmUC7+6mk4vkoVGwxmY7qTxULJYnDXV\nZGcsL/btDSzEJ0L1zg4lsydnJ+SD2cpQCkCZlhJQ6izU3BlY6OKU3bLGwq0byu+edw6FUDKH5Ns/\nK8d4UPcK7RK5FLUbMxYcjO+mK2tLezP+z8dAfR2kjJWdjxclGqSEp1YpqNrdOby1XkrGgruHS2cs\n2Et6aS2gVtu+kHQw8eS/Ap5ayAeyYTx6ACi5oDxQUgQxelyvP3+/MSwE8v4syPuz7N5ExDjwDqVK\nZbPGglx2WRkHP7STIp7aIZAtZ4WouKZcSF0sBCL1fVNfAYDw8laOpTt5eLYXIrWzHpHdTCexNYb+\nd/e9HxNCKJ+5/e09swwm2BlYMBFCQMxZAHncgzD+14vKQlNmho9fe60NwL7ZvEzBq7JLkD/4c9t+\nLL7XLIdCVCqBh774vCbqt1QqZiw4GAMLrsxdyVjAzRsQYx+w764j0WBjKgTm282hEG0XR8Lbp+tq\n3YOAiO27lFrh4wfMfArywWzIH76jDPHSegEBgRDxiX3WDmeTfvM7oPQH+zdwc3ds7RJ1J0Mhyi4D\nYcM7Hc4gPLWQb1UAAOTm20BVJcSC55W7t/t3OT9Q5+GpFCIFHD/Fsukktvl25zUWyDZPL/tm7elL\nbt0fCtGBxZAaU58RAUGQK6+Zl8ut3SjeeEX5TJBWvw0x1GIGMneNkqkAAKZ9DwvpWZuJXIFaDcGM\nBYfiu+nKTDUWblUALNZIZJvpwqGbGQtC6wX5p1vKBYLadYdC9FfC2wcYNR64eQPSa29bT+k2SIig\nEGX6OmdRqSGXXYbxyN62Bilp3vKPlyGiR3e+nafFUIjK64AsQ0TogafSIG9+2+nTtAoPT2XGDSF1\nXbS0u/tWqZR9AxCdzQpBNomoUcpUxP2Ju8Y87FT0MFAkhADGPwRcvdS+MFwHnMmHbDQqwYaW5q4D\nF22BBfl6mVKENVJv/TzuGsh1NZB/+B7Gz/9baXd3hwASuRAxdTYzuR2MgQVX5q6BXPOTUiSrs5RU\nosGuLdVZdLd4o3YIcDwXcukPdlflJ8eSlr6kXJQOwqBCfyBCIyF/fRhyyffKAqMRuFYGXC8Dps7u\nfEOtF1B2Ga3/sbA9NTs4FFLMGMiPPNr7De+KKZjg2Qv1iCzvjnkNjnogjiItWeHsJnQg1GpIr7+j\n1NuJ0He9QSekf19lvd8IHeSmRuXG0LBgoLm562wNU8bCtTLbBbrdleKN8ne5QHUVxJOL+qZIKlE/\nJfGmq8MxsODK3NzNEXDBwAKRbYHBEPMXA/fHd2szMXUW4OEByICIjeulxtHdiMEyA0Q/JaUtB9KW\nm/9u/X9rIX93FGhthQjXdb6haaYFowyx4HkIX39zjZN+UVjYNDyqN+5kWY7nZcaCSxAOyBrqcNyH\ntw2PuHpJCSzYNStEW5Cgotz20DQ3JYtVvvEjEDUa0mO/vOd2ExFZYmDBhQl3DeSqSuUPBhaIbBKS\nBDFzfve3C42EmLe4F1pENDCJcB3k0/nKH+F3Gc5gquyvj4H06BO937DuiowCPDwh9LGO37flrAZM\nQ6fO+PoD3r6QT36tBAxuVQBhurtvIyyCVjYzFjTK0L3rZYOqFg0R9R0GFlyZKT1Y7aZUGCYiIuol\nIlxdWyJ3AAATr0lEQVSn1A8YFnz3cattj4muLpScRJqUCkxK7Z2dR42G9J9vAe7uEP1thgPqN4QQ\nwMj7laFGXx9uW9jFRhbDGkRngYWGOqUwaXCY4xpLRNSGgQVXFhKu/NvSzHF0RETUu0zDH7oKGDTf\nVv4d3vMx6QOVEAIY3s8KEFK/JP3bH5RAQHMz5K8PQ3Q1XM9/KBAzRpma0la2jbsGqK0GAIj7wnuh\nxUQ02DGw4MLEjCcBWbaeDomIiKg3BIUAGg8Ii+nzbBEJk4HaaogEFs4i6oxQqQBvX+X32b/qen0P\nT6hefrPzFdwtzgWZsUBEvYCBBRfW07HjRERE3SUkFaT/sw4IspGGbbmeuwbicRaOI+pL4r4wyJKk\n9E8OjyWiXsDAAhERETmE0I10dhOIyAYx9gGo3t/l7GYQkQvjwHsiIiIiIiIi6rF+kbGwd+9efPHF\nFzAYDNDpdEhLS0N0dLSzm0VEREREREREXXB6xsKxY8fw0Ucf4emnn8b69esxfPhwrFu3DjU1Nc5u\nGhERERERERF1wemBhZycHEyfPh0pKSkICwvD0qVLodFocPjwYWc3jYiIiIiIiIi64NTAQktLC0pK\nShAXF2deJoRAXFwcioqKnNgyIiIiIiIiIrKHU2ss1NbWwmg0wtfX12q5r68vysvLu70/tbpflIwg\nchohBNzc3JzdDCKnYj8gYj8gYh+gwa6vr4377ZW4EMLm8qNHjyI3N9dq2ejRozF37lz4+/v3RdOI\n+rVhw4Y5uwlETsd+QMR+QMQ+QARkZ2fj/PnzVssmT56MpKQkhz6PUwML3t7ekCQJ1dXVVsurq6s7\nZDGYJCUl2XwTsrOzMXfu3F5pJ9FAsWXLFjz77LPObgaRU7EfELEfELEPELVfI/fFdbJTayyo1Wro\n9XqcPXvWvEyWZRQUFCA2NrZb+7ozCkM0GN24ccPZTSByOvYDIvYDIvYBor69Rnb6UIgnnngC7777\nLvR6PaKjo5GTk4Off/4ZU6dOdXbTiIiIiIiIiKgLTg8sTJo0CbW1tdi5cycMBgN0Oh1WrVoFHx8f\nZzeNiIiIiIiIiLrg9MACADz++ON4/PHHnd0MIiIiIiIiIuom1euvv/66sxvhKJGRkc5uApHTsR8Q\nsR8QAewHROwDRH3XD4Qsy3KfPBMRERERERERuRynzgpBRERERERERAMbAwtERERERERE1GMMLBAR\nERERERFRjzGwQEREREREREQ9xsACEREREREREfWY2tkNcIS9e/fiiy++gMFggE6nQ1paGqKjo53d\nLKJ7lpWVhfz8fJSXl8Pd3R0xMTFYtGgRQkNDzes0Nzfjww8/RF5eHpqbmzF+/Hg8//zz8PX1Na9z\n8+ZNbNiwAYWFhfDw8EBKSgqeeeYZSBJjizSwZGVlYfv27Zg9ezYWL14MgH2ABoeqqip8/PHHOHXq\nFH7++WeEhITghRdegF6vN6+zY8cOfPnll6ivr0dsbCyWLl2K4OBg8+N1dXXIzMzE8ePHIUkSEhMT\n8eyzz8LDw8MZL4moW4xGI3bu3ImjR4/CYDDA398fU6dOxfz5863WYz8gV3L+/HlkZ2ejpKQEBoMB\nL7/8MhISEqzWccQxf+XKFWRmZqK4uBi+vr6YOXMm5s6d2622ql5//fXX7+nVOtmxY8ewceNG/OY3\nv8GCBQtQUVGBTz75BKmpqdBoNM5uHtE92bVrF1JTU/HUU08hOTkZZ86cwe7duzFjxgyoVCoAQGZm\nJk6dOoXly5djxowZOHbsGL7++ms8+uijAJQv4tdeew0eHh74/e9/j7i4OOzcuRONjY0YO3asM18e\nUbcUFxdj27ZtGDZsGIKCghAfHw+AfYBcX319PVauXImQkBCkpaVh7ty50Ov1CAgIgJeXFwDl+yIn\nJwfp6emYO3cuvv/+e+zevRuPPfaYOYD2l7/8BZWVlVixYgUmTZqEPXv24NKlS0hMTHTmyyOyS1ZW\nFvbt24f09HQ8/fTTiIiIwNatW+Hp6Wm+och+QK7mxx9/RGtrK1JTU5GXl4fJkydb3WB0xDHf2NiI\nlStXQq/XY9myZRg+fDg+/PBD+Pr6WgWvuzLgb9Xk5ORg+vTpSElJQVhYGJYuXQqNRoPDhw87u2lE\n9+zVV19FcnIywsPDERkZiYyMDNy8eRMlJSUAgIaGBhw+fBiLFy/G/fffjxEjRiAjIwMXLlxAcXEx\nAOD06dMoLy/HsmXLEBkZifj4eCxYsAD79u1Da2urM18ekd2amprwzjvvID093XwhBbAP0OCwa9cu\nBAYGIj09HXq9HsOGDcO4ceMQFBRkXmfPnj2YP38+EhISEBkZid/97neoqqpCfn4+AKCsrAynT59G\neno6oqKiEBsbi7S0NBw7dgwGg8FZL43IbkVFRUhISEB8fDwCAwORmJiIcePGmT/rAfYDcj2mc5aH\nHnrI5uOOOOa/+uortLa24oUXXkB4eDgmTZqEWbNmYffu3d1q64AOLLS0tKCkpARxcXHmZUIIxMXF\noaioyIktI+odDQ0NAIAhQ4YAAEpKStDa2mp11zU0NBSBgYHmPnDx4kVERkbCx8fHvM748ePR0NCA\nq1ev9mHriXpu48aNmDhxYocMA/YBGgyOHz+OqKgo/O1vf8PSpUvxyiuv4NChQ+bHKyoqYDAYrM6H\ntFotRo4cadUPvLy8MGLECPM648aNgxACFy9e7LsXQ9RDsbGxKCgowLVr1wAAly9fxoULFzBhwgQA\n7Ac0+DjqmC8qKsLo0aPN2dCAcp5UXl5uvvawx4CusVBbWwuj0Wg1jhYAfH19UV5e7qRWEfUOWZax\nZcsWjBo1CuHh4QAAg8EAtVoNrVZrta6vr685CmkwGDr0ET8/P/NjRP1dbm4urly5gjfffLPDY+wD\nNBjcuHED+/fvx5w5czBv3jwUFxdj8+bNcHNzQ3Jysvk4tnU+dLd+IEkShgwZwn5AA8KTTz6JxsZG\nvPjii5AkCbIsY+HChZg8eTIAsB/QoOOoY766utoqA85ynwaDocM5VmcGdGDhboQQzm4CkUNt3LgR\nZWVleOONN7pcV5Zlu/bJfkL93a1bt7BlyxasXr0aarX9X1nsA+RKZFlGVFQUFi5cCADQ6XS4evUq\nDhw4gOTk5Ltu11WBUlmW2Q9oQDh27BiOHj2KF198EeHh4bh8+TK2bNmCgIAA9gMiC8465gd0YMHb\n2xuSJKG6utpqeXV1dYfIDNFAtmnTJpw8eRJvvPEGAgICzMv9/PzQ0tKChoYGq2hiTU2N+Y6sn58f\nfvjhB6v9dRbhJOpvSkpKUFNTg1deecW8zGg0orCwEHv37sWqVavYB8jl+fv7IywszGpZWFiYeQyt\n6Vivrq42/w4o/UCn05nXufN8yWg0or6+nv2ABoStW7fil7/8JR555BEAQEREBCorK5GVlYXk5GT2\nAxp07vWYN23j6+tr83ra8jnsMaBrLKjVauj1epw9e9a8TJZlFBQUIDY21oktI3KcTZs24bvvvsMf\n//hHBAYGWj2m1+uhUqlQUFBgXlZeXo6bN28iJiYGABATE4PS0lLU1NSY1zlz5gy0Wq15SAVRfxUX\nF4e//vWv+POf/2z+0ev1mDJlivl39gFydbGxsR2GeJaXl5u/E4KCguDn52d1PtTQ0ICLFy+az4di\nYmJQX1+PS5cumdc5e/YsZFnGyJEj++BVEN2b27dvd7jDKoQwZ6ixH9Bgc6/HvGk2lZiYGJw/fx5G\no9G8zunTpxEaGmr3MAjABaab9PT0xI4dOxAYGAg3Nzds374dV65cQXp6OqebpAFv48aNyM3NxYoV\nK+Dn54empiY0NTVBkiSoVCq4ubnhp59+wt69e6HT6VBXV4cNGzYgMDDQPK9zUFAQ8vPzcfbsWURG\nRuLy5cvYvHkzZsyYgXHjxjn5FRLdnVqtho+Pj9VPbm4u7rvvPiQnJ7MP0KAQGBiIzz77DJIkwd/f\nH6dOncJnn32GhQsXIjIyEoByB2rXrl0ICwtDS0sLMjMz0dLSgueeew6SJMHHxwfFxcXIzc2FTqdD\nRUUFNmzYgPj4eKSkpDj5FRJ17ccff8SRI0cQGhoKtVqNc+fOYfv27UhKSjIXr2M/IFfT1NSEsrIy\nGAwGHDx4ENHR0XB3d0dLSwu0Wq1DjvmQkBAcOHAApaWlCA0NRUFBAbZt24YFCxZYFX3sipDtHYja\nj+3btw/Z2dkwGAzQ6XR47rnnEBUV5exmEd2zBQsW2FyekZFh/jBobm7GRx99hNzcXDQ3NyM+Ph5L\nliyxSum7efMmNm7ciHPnzsHDwwMpKSl45plnuhx/RdQfrVmzBjqdDosXLwbAPkCDw4kTJ/DJJ5/g\n+vXrCAoKwpw5c5Cammq1zs6dO3Ho0CHU19dj9OjRWLJkCYKDg82P19fXY9OmTTh+/DgkSUJiYiLS\n0tJ4I4YGhKamJuzYsQP5+fmoqamBv78/kpKSMH/+fKtq9uwH5EoKCwuxZs2aDstTUlKQkZEBwDHH\nfGlpKTZt2oQffvgB3t7emDVrFubOnduttrpEYIGIiIiIiIiInIO3aoiIiIiIiIioxxhYICIiIiIi\nIqIeY2CBiIiIiIiIiHqMgQUiIiIiIiIi6jEGFoiIiIiIiIioxxhYICIiIiIiIqIeY2CBiIiIiIiI\niHqMgQUiIiIiIiIi6jEGFoiIiIiIiIioxxhYICIiIiIiIqIeUzu7AUREROQ8paWl+PTTT1FSUgKD\nwQBvb2+Eh4cjISEBM2fOBABkZWUhPDwcDz74oJNbS0RERP0RMxaIiIgGqQsXLuDVV19FaWkppk2b\nhiVLlmDatGmQJAl79uwxr5eVlYVvv/3WiS0lIiKi/owZC0RERIPU559/Dq1Wiz/96U/w9PS0eqym\npsZJrSIiIqKBhoEFIiKiQaqiogIREREdggoA4OPjAwBYsGABAODIkSM4cuQIACAlJQUZGRkAgKqq\nKmzfvh0nT55EQ0MDgoOD8cQTTyA1NdW8r8LCQqxZswbLly/H5cuX8c9//hONjY2Ii4vDkiVLMHTo\nUPO6169fx9atW1FUVIT6+nr4+PggNjYWv/3tb222k4iIiJyPgQUiIqJBKjAwEBcvXsTVq1cRERFh\nc51ly5bhvffew8iRIzF9+nQAwH333QcAqK6uxqpVqyBJEmbNmgUfHx+cPHkS77//PpqamjB79myr\nfWVlZUEIgSeffBLV1dXIycnB2rVrsX79eri5uaGlpQVr165Fa2srZs2aBT8/P1RVVeHEiROor69n\nYIGIiKifYmCBiIhokPrFL36BN998E3/4wx8QHR2NUaNGIS4uDmPGjIFKpQIAJCUl4YMPPkBQUBCS\nkpKstt+2bRtkWcb69evh5eUFAJg+fTr+/ve/49NPP8WMGTPg5uZmXr+urg5vv/02NBoNAGDEiBF4\n6623cOjQIcycORNlZWWorKzESy+9hIceesi83fz583v7rSAiIqJ7wOKNREREg9S4ceOwdu1aJCQk\n4MqVK8jOzsa6deuQnp6O7777rsvtv/nmG0ycOBFGoxG1tbXmn/Hjx6OhoQGXLl2yWj8lJcUcVACA\nhx9+GH5+fjh58iQAQKvVAgBOnTqF27dvO/CVEhERUW9ixgIREdEgFhUVhZdeegmtra24cuUK8vPz\nkZOTg7feegvr169HWFiYze1qamrQ0NCAgwcP4uDBgzbXqa6utvo7ODi4wzrBwcGorKwEAAQFBWHO\nnDnYvXs3vvrqK4waNQoJCQmYMmWKOehARERE/Q8DC0RERASVSgW9Xg+9Xo/g4GC89957yMvLw1NP\nPWVzfaPRCACYMmUKpk6danOdyMjIbrfj17/+NaZOnYpvv/0WZ86cwebNm7Fr1y6sW7cOAQEB3d4f\nERER9T4GFoiIiMhKVFQUAMBgMAAAhBAd1vHx8YGHhweMRiPGjh1r136vX79uc5lOp7NaFhERgYiI\nCMybNw9FRUVYvXo1Dhw4YJ6hgoiIiPoX1lggIiIapM6dO2dz+YkTJwAAoaGhAACNRoOGhgardSRJ\nQmJiIr755htcvXq1wz5qamo6LDty5AiamprMf+fl5cFgMGDChAkAgMbGRnMmhElERASEEGhubu7G\nKyMiIqK+xIwFIiKiQSozMxO3b9/Ggw8+iLCwMLS0tODChQvIy8tDUFCQeYiDXq/H2bNnsXv3bgQE\nBCAoKAjR0dFYtGgRCgsLsXLlSkybNg3h4eGoq6tDSUkJzp07h02bNlk935AhQ7B69Wo8+uijMBgM\n+Mc//oGQkBCkpqYCAAoKCpCZmYmHH34YISEhMBqNOHLkCFQqFR5++OG+fnuIiIjITkKWZdnZjSAi\nIqK+d/r0aeTl5aGoqAi3bt1CS0sLAgMDMWHCBMybNw8+Pj4AgPLycmzYsAHFxcW4ffs2UlJSkJGR\nAUDJTPjss89w/PhxGAwGDBkyBBEREZg0aZI5YFBYWIg1a9Zg+fLlKC0txZdffonGxkbExcVhyZIl\nGDp0KACgoqICn3/+Oc6fP4+qqiq4u7tDp9Nh3rx5GDNmjHPeJCIiIuoSAwtERETUq0yBhRUrViAx\nMdHZzSEiIiIHY40FIiIiIiIiIuoxBhaIiIiIiIiIqMcYWCAiIiIiIiKiHmONBSIiIiIiIiLqMWYs\nEBEREREREVGPMbBARERERERERD3GwAIRERERERER9RgDC0RERERERETUYwwsEBEREREREVGPMbBA\nRERERERERD3GwAIRERERERER9RgDC0RERERERETUY/8fnzuwFxp9Cw4AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10c6b7f50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mcmc = MCMC(model)\n",
"mcmc.sample(1000)\n",
"\n",
"mean_1_samples = mcmc.trace('mean1')[:]\n",
"mean_2_samples = mcmc.trace('mean2')[:]\n",
"p_samples = mcmc.trace('p')[:]\n",
"precision_samples = mcmc.trace('precision')[:]\n",
"\n",
"figsize(12.5, 9)\n",
"plt.subplot(311)\n",
"lw = 1\n",
"\n",
"plt.subplot(311)\n",
"plt.plot(mean_1_samples, label=\"trace of mean 1\",\n",
" color=\"#348ABD\", lw=lw)\n",
"plt.xlabel(\"Steps\")\n",
"plt.legend();\n",
"\n",
"plt.subplot(311)\n",
"plt.plot(mean_2_samples, label=\"trace of mean 2\",\n",
" color=\"#A60628\", lw=lw)\n",
"plt.xlabel(\"Steps\")\n",
"plt.ylim(-15, 15)\n",
"plt.legend();\n",
"\n",
"plt.subplot(312)\n",
"plt.plot(p_samples, label=\"trace of p\", lw=lw)\n",
"plt.xlabel(\"Steps\")\n",
"plt.ylim(0, 1)\n",
"plt.legend();\n",
"\n",
"plt.subplot(313)\n",
"plt.plot(precision_samples, label=\"trace of precision\", lw=lw)\n",
"plt.xlabel(\"Steps\")\n",
"# plt.ylim(0, 1)\n",
"\n",
"plt.legend();"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.12"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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