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Seaborn plotting distributions example on white background
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{
"metadata": {
"name": "",
"signature": "sha256:91492e3dcf474078736df21038285ec1b8ed70c7d94d86c0936819a69a070bde"
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"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Visualizing distributions of data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This notebook demonstrates different approaches to graphically representing distributions of data, specifically focusing on the tools provided by the [seaborn](https://github.com/mwaskom/seaborn) package."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"from numpy.random import randn\n",
"import pandas as pd\n",
"from scipy import stats\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.set_palette(\"deep\", desat=.6)\n",
"sns.set_context(rc={\"figure.figsize\": (8, 4)})\n",
"sns.set_style(\"white\")\n",
"np.random.seed(9221999)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Basic visualization with histograms"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The most basic and common way of representing a distributions is with a histogram. We can do this directly through the `hist` function that is part of matplotlib."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data = randn(75)\n",
"plt.hist(data);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10c506750>"
]
}
],
"prompt_number": 4
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By default, `hist` separates the data into 10 bins of equal widths and plots the number of observations in each bin. Thus, the main parameter is the number of bins, which we can change.\n",
"\n",
"The more bins you have, the more sensitive you will be to high-frequency patterns in the distribution. But, sometimes those high-frequency patterns will be noise. Often you want to try different values until you think you have best captured what you see in the data."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.hist(data, 6, color=sns.desaturate(\"indianred\", .75));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Twi/M8ZN9AHdGxGm0Ti92NnD7oOc4VD1sxz8BfxQRi4FjaL018exhHHEQRmItejAqa7EJ\n+BCt0+ldCDwy6/bK69Hp/PX/Dry3vf9sF6235D53+EfsyZzb0T6Q85n23/03gJ9m/j8cNm2U1uKg\nRm0dIuIE4CHgE5n58Kyb57Uewzio649pHZW8MSIAdmTmR9tHzW3OzAci4svAPwB7gNsz8ztDmONQ\n9bIdG4FHae03WFfwIKID9rf/A94+gnGU1uKATtsxCmtxM/DnEfEorSN8fxlGZj3edf76iPgl4LjM\nvCUiPg18ndbzf2tmbm1q0C66bce1wMO01ufvMvPBuT5REfsBRnQtDjjYNozSOqyj9Tb0+og4sC/5\nFuD75rsenstakqQCPDGIJEkFGGRJkgowyJIkFWCQJUkqwCBLklSAQZYkqQCDLElSAQZZkqQC/h9r\nbnxw41gbfQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x110b79cd0>"
]
}
],
"prompt_number": 5
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `normed` argument can also be useful if you want to compare two distributions that do not have the same number of observations. Note also that `bins` can be a sequence of where each bin starts."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data1 = stats.poisson(2).rvs(100)\n",
"data2 = stats.poisson(5).rvs(120)\n",
"max_data = np.r_[data1, data2].max()\n",
"bins = np.linspace(0, max_data, max_data + 1)\n",
"plt.hist(data1, bins, normed=True, color=\"#6495ED\", alpha=.5)\n",
"plt.hist(data2, bins, normed=True, color=\"#F08080\", alpha=.5);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10c506510>"
]
}
],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `hist` function has quite a few other options, which you can explore in its docstring. Here we'll just highlight one more that can be useful when plotting many observations (such as following a resampling procedure)."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = stats.gamma(3).rvs(5000)\n",
"plt.hist(x, 70, histtype=\"stepfilled\", alpha=.7);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x110b903d0>"
]
}
],
"prompt_number": 7
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can also represent a joint distribution with the histogram method, using a hexbin plot. This is similar to a histogram, except instead of coding the number of observations in each bin with a position on one of the axes, it uses a color-mapping to give the plot three quantitative dimensions.\n",
"\n",
"In `seaborn`, you can draw a hexbin plot using the `jointplot` function and setting `kind` to `\"hex\"`. This will also plot the marginal distribution of each variable on the sides of the plot using a histrogram:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"y = stats.gamma(5).rvs(5000)\n",
"with sns.axes_style(\"white\"):\n",
" sns.jointplot(x, y, kind=\"hex\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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3Wm/JbImuNfHgYbDUCuC5AsNRDKUNXEeg1fDg7ULkkGUAzqyfGAM8d2erJIIg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\nG7meSHxWU5cT+pXF1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"text": [
"<matplotlib.figure.Figure at 0x111432490>"
]
}
],
"prompt_number": 8
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Estimating the density of the observations: `kdeplot` and `rugplot`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A superior, if more computationally intensive, approach to estimating a distribution is known as a kernel density estimate, or KDE. To motivate the KDE, let's first think about rug plots. A rug plot is a very simple, but also perfectly legitimate, way of representing a distribution. To create one, simply draw a vertical line at each observed data point. Here, the height is totally arbitrary."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.set_palette(\"hls\", 1)\n",
"data = randn(30)\n",
"sns.rugplot(data)\n",
"plt.ylim(0, 1);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAeMAAAECCAYAAADNb78fAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x111432bd0>"
]
}
],
"prompt_number": 9
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can see where the density of the distribution is by how dense the tick-marks are. Before talking about kernel density plots, let's connect the rug plot to the histogram. The connection here is very direct: a histogram just creates bins along the range of the data and then draws a bar with height equal to the number of ticks in each bin"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.hist(data, alpha=.3)\n",
"sns.rugplot(data);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAdsAAAECCAYAAAC2S33TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ntQ3IZIi9uQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x111435310>"
]
}
],
"prompt_number": 10
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A kernel density plot is also a transformation from the tick marks to a height-encoded measure of density. However, the transformaiton is a bit more complicated. Instead of binning each tick mark, we will instead represent each tick with a gaussian basis function."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Draw the rug and set up the x-axis space\n",
"sns.rugplot(data);\n",
"xx = np.linspace(-4, 4, 100)\n",
"\n",
"# Compute the bandwidth of the kernel using a rule-of-thumb\n",
"bandwidth = ((4 * data.std() ** 5) / (3 * len(data))) ** .2\n",
"bandwidth = len(data) ** (-1. / 5)\n",
"\n",
"# We'll save the basis functions for the next step\n",
"kernels = []\n",
"\n",
"# Plot each basis function\n",
"for d in data:\n",
" \n",
" # Make the basis function as a gaussian PDF\n",
" kernel = stats.norm(d, bandwidth).pdf(xx)\n",
" kernels.append(kernel)\n",
" \n",
" # Scale for plotting\n",
" kernel /= kernel.max()\n",
" kernel *= .4\n",
" plt.plot(xx, kernel, \"#888888\", alpha=.5)\n",
"plt.ylim(0, 1);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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4FkWW5YH0P0sp53I52O12TE5O8srn08TjcbRaLYRCIT6DBY4HOPF4HPl8nhd5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DtIGo9qhKpBLraaeP77QnLO36+UUKtUIcbC2b5dy6UUlcqNejkomX3fZ3Z2lvPnz2sXq+rQVNnb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\n",
"text": [
"<matplotlib.figure.Figure at 0x1119ac850>"
]
}
],
"prompt_number": 11
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We then estimate the distribution that our samples came from from by summing these basis functions (and normalizing so, as a proper density, the function integrates to 1).\n",
"\n",
"There is also a function in the `scipy.stats` module that will perform a kernel density estimate (it actually returns an object that can be called on some values to return the density). We see that plotting the values from this object give us basically the same results as summing the gaussian basis functions."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Set up the plots\n",
"f, (ax1, ax2) = plt.subplots(2, 1, sharex=True)\n",
"c1, c2 = sns.color_palette(\"husl\", 3)[:2]\n",
"\n",
"# Plot the summed basis functions\n",
"summed_kde = np.sum(kernels, axis=0)\n",
"ax1.plot(xx, summed_kde, c=c1)\n",
"sns.rugplot(data, c=c1, ax=ax1)\n",
"ax1.set_yticks([])\n",
"ax1.set_title(\"summed basis functions\")\n",
"\n",
"# Use scipy to get the density estimate\n",
"scipy_kde = stats.gaussian_kde(data)(xx)\n",
"ax2.plot(xx, scipy_kde, c=c2)\n",
"sns.rugplot(data, c=c2, ax=ax2)\n",
"ax2.set_yticks([])\n",
"ax2.set_title(\"scipy gaussian_kde\")\n",
"f.tight_layout()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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jSPb709f89FjK0n5Ff35Lt3+wOo+27crGME2sts2x2jYncM6J3ikoEmEnPnsx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\n",
"text": [
"<matplotlib.figure.Figure at 0x1116edb50>"
]
}
],
"prompt_number": 12
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The seaborn package has a high-level function for plotting a kernel density estimate in one quick step, along with some additional nice features, such as shading in the density."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.kdeplot(data, shade=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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+8qDXceQk5SrohcA6AGvtVuDYnzwhMiVuu7w2DSgxxqw3xjxjjJnbU2FF8lXD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\n0rbTfubI2F9eQcScS3DoMIJ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"text": [
"<matplotlib.figure.Figure at 0x1116a7210>"
]
}
],
"prompt_number": 13
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Much like how the `bins` parameter controls the fit of the histogram to the data, you can adjust the bandwidth (`bw`) of the kernel to make the densisty estimate more or less sensitive to high-frequency structure."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pal = sns.blend_palette([sns.desaturate(\"royalblue\", 0), \"royalblue\"], 5)\n",
"bws = [.1, .25, .5, 1, 2]\n",
"\n",
"for bw, c in zip(bws, pal):\n",
" sns.kdeplot(data, bw=bw, color=c, lw=1.8, label=bw)\n",
"\n",
"plt.legend(title=\"kernel bandwidth\")\n",
"sns.rugplot(data, color=\"#333333\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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e8j6+s1NGRmw3KJkOJcYrCWMhJriu94whFo69VcZ79h4iarmwbAcLjs8/qoFb\ncV0rY4AZpZnkZjqJWm4qajrv0OR2u7Ftu9+dpeJfKFJSUjo9F2K8kTAWYoLrrTLuLeg+Ka9OdFF/\nav7QFvnoqqcwVhSFE+fEQrSq0SYcORKkAx1RHQ/f1NTUAZ0vxFglYSzEBNdTZexyuTBNs9siGZZl\ncaCyMTbC2QknzM4bljb0FMYA04tcKFiEoh70PVWJ1yWMxWQjYSzEBNd1ABf0fA8X4FB1E/6Qgo2D\nsileXM7h+RXR2+dhG6S5/dg4+MfGA4mXBxvGPp+v03MhxhsJYyEmuN4q4+RjcXv2VSW6qOfOyhy2\nNvRWGUejUbK9TQDsPuDHPFypDzaM3e7Y9CipjMV4JWEsxATX2z1j6F5J7tAriZhuVMXguLLsYWuD\noig4HI4ew9jnCuFzQyiqsnN3rKt6sGHscrlwu91SGYtxS8JYiAmut9HUyccgNqWpsiaAjYN0Tzup\nKb5hbYeqqj2GsaLACbMyAIW334t1VQ8ljKUyFuOZhLEQE1xPlXFPS2Lu3B2rigHS3e14vd5hbYeq\nqt26xeOf/5nTZgA2nxxsx7KsIVfGhmHIzk1iXJIwFmKCG8gALtu22bytnIjpxqlapLgCIxLGPVXG\nAEUFGWSlOYiaDjbtqBpwGMePxyvj5GsKMZ5IGAsxwcUDt6fKOH6s4lADh+piXdTZKWFU1dHp/OHQ\n09zm5AFYJ52QC8A76w8MOIzj14tXxgN5jxBjkYSxEBNcX5VxPAw3bP7kSBe1x4/X60VRFIZTfD3s\n5CUuY/eMFVRV5TNL56BgUV7ZgarG2jeYyljCWIxnEsZCTHD9TW0KhiJs+/gghuXBqTpwKy3D3kUN\nsS8Atm136qqORCK4XC4URSE/N52sNDAt0Pe3J473Jf5lwul0JsJYuqnFeCRhLMQE19/Ups3b9hGO\ngmE5OK4sC2xzRMK4p3u60Wi00/aJJ2qxruoPt9YBRzaC6I1hGDidThwOR+I6UhmL8ajPm0KapjmA\nR4AFQBi4Qdf1vUnH/xn4DmADz+m6/tMRbKsQYgj666besKUi0UV9/Mwsdn4EHo9n2NvR00IjhmEk\nlrIEOOPTM3n3ow84WBNkdrZjQN3U8etKZSzGs/4q44sAt67rS4HvAg/GD2iapgL3AecApwE3aZqW\nM1INFUIMTV8DuOob/dQ3tKI40wCYWRrbuCG+vORw6loZ27bdrTIuLsohzWtg29AeTh9QN3X8/VIZ\ni/GsvzC22L3KAAAgAElEQVReBrwKoOv6emBR/ICu6yZwvK7r7UA+oALyr0CIMaavyri8sgXTctAR\ntJkxJQOXGjt3sJWxP2Cg7/ez9qMm3v6wkQ+2tXCwOohlHRms1TWMk+cIxzkUBa0sC4C2SHafwRrf\nYrFrGEtlLMaj/uYuZABtSc9NTdMcuq5bALquW5qmXQI8DLwMBEammUKIoeqtMrZshdr6DlRXOoTg\nxOMLCIVi+woP5J5xJGqxZmMT6zY1sXOfn6RB0glpKSoLT8jkvGX53UZw9xTGACedUMJHH+sEoh78\ngc7zkpPFd52SMBYTQX9h3AakJz1PBHGcrusvapq2GngSuPrwn0KIMaK3yjhseLBscHkzoD3MiVo+\nzfX7gb7D2LJsXn+/gT+8XkNzWyz4phZ60crSKMx141QdBEIm+6sC7NrnZ83GJtZsbGJqfgp5akq/\nYTyrrAiPcyuBaCoN7b23o+v7e9v8QojxoL8wXgdcCPxO07QlwNb4AU3TMoA/Ayt0XY9omtYB9P41\nVggxKnoKY1VVCRlebBsaW6JkpnuYUphGdUWsMu6tm7qmIcwvnj/Ax+V+VFXhs0vyuODMAkoKeg5N\nw7TZsKOFV9bUoe/voIJTyFjn5xvT7EQXdHzgVVxmRirFeS72Vtu0hNITI6a7XTtpwQ/offMLIcaD\n/sJ4NbBC07R1h59fq2nalUCaruuPaZr2LLBG07QosAV4dgTbKoQYgp7mGTc0dWDaTjweD41Bi0/N\nz0VRlMRUop4q4492tvLQc+WEwhYnzknn65dOoyC373vLTlVhyYJsFp+Yxao/beYv/4jwzmaF+rY9\nXHZO7L1dwxjg+FlFHKytIWJ62V/RxOyygm7nJC/4kfynVMZiPOozjHVdt4Ebu7y8O+n4Y8BjI9Au\nIcQwMU0Th8OBw3FkvObufTWxY3YsCOfOyQPo9Z7xy2tqeebPh3AocN1FpXxuWf6gVuhSFIWT57ip\nLn+fOnMxO/f5eaiug1np3h7DeFZZEZ4PDhCNuNmwvbbHMO56L1wqYzGeyaIfQkxwhmF0qoot22bX\nnkOATXtIRVHg+JmxxTZ6CuPf/72ap186RKpP5ftfm8N5pxcMaalMl8uFW41y6ZkWF5xZQIvfZmvt\nApo7uofxjGmFuNUIYLNlV0OnJTSTfy44EsIygEuMZxLGQkxwpml2uudacaiBdn8Qp8MgEHZSVppF\nakosyLqG8R9er+aF16rJTHdyz03HMX92evcPGKB4WFqWwcoLp7D8ZIWo5ea3b8KhulCnc70eF9kZ\nLtxqhNb2KPsqWrtdr7cwlm5qMR5JGAsxwXWtjPfsqwLAVmL3bOfOyU0cC4VCiaUlX3+/gedfjQXx\nf31jDqVFR7cQSHI3sqIonKoZzMgqJxiGe3+5h4bmznOKC3JT8aixe9gbtlX3+HMlX1e6qcV4JmEs\nxATXtTL+ZF8s2CJmLFzj94shtha0x+Nh0642Hn/xID6Pgzu/OpvSwqNfkatrN3I4HKY04xBnf8pH\nY2uUHz7+CYHQkQkZRQXpuNUIDsXmo+21mGanWZW9hrFUxmI8kjAWYoIzTTNRGXcEQlTXNFFcmEN7\nyIOqGEwtinU927ZNKBQiSiYPPVuOAtx2zUyml6QMSzu6hnF8NPRFy7M481M5VNaG+Nmq/YlVuwrz\nMnEoFh5nlPaOCLvLmztdr2sYq6qKw+GQyliMSxLGQkxglmVhWVYisPbtr8EGcnJzMSwHqe4ObDtW\ncRqGQTgKGw5MIxS2uP6SaSw4LmPY2tJbGHs8Hr526TTmTEth485WXngtVrl7vR5cahSXIwh076ru\nbWUxqYzFeCRhLMQE1nXBj4OVDQCEjVgwpro6EuEYDAbZ0zgHf8jNZxbn8tkleT1cceh66qaGWBi7\nXQ6+/ZVZZGe4ePGNGjbrbXg8HlyOKC5HFLfLweaP64gaR7qqewpjp9MplbEYlySMhZjAuoXxoXoU\noKouVm2mujsSFerf32ugMZhHXobBdRdNHfa2dB3t3HUFruwMF7deNQNFgYdX7ScYUXGrERQFstIg\nGDLYsachcT2pjMVEImEsxASWHFjhSJTauhZycrKoqG4nMxWcDpNoNMrB6iB/eLMFVTH4p1PDuF3D\n/6sh/oUguZva4XB0CtO5s9L50opi2joMfvNaGwoWHrcDIxyb2rRxW02PP1tcvDLuaV6yEGOZhLEQ\nE1hyZXyoqhHLtvGmZGDbUJIX++cfDEb46apyDBNm5eylsJ8lLodKURRcLlenbmq3291tAZFLPlvE\n8WWpfLw/RF2gkIxUFcUOk+pzslWvIxSOhXDXtamTH8d/biHGCwljISaw5HWpK6oaAQiEYxVqaWGs\ne/iv/2jlYHWIeTMc5KfUD2j7xKHyeDyJe8WRSKTHpTAdDoUbL5uOy6lQ3lyGy+lEUSAnQyEatdim\n13f62bpWxiBzjcX4I2EsxAQWrxCdTifVtU3Ydux+sdfjpCTfS0ckhTc3BklPdbL8pCiKMrC9jIcq\nJSWFUCiEYRi9hjFAcb6XK84rxrSdbD+Uh8/rIRSITW36cGtsVHVPG2DIKlxivJIwFmICS+6mrq5t\nRnG46QganDArB5fLxZ6mOVhWbPMHB7ElKX2+o1/gozcpKbE5y21tbUDvWzUCnH9mIRmeduraUvGk\nT8UyQmSkufh4byMdgWif3dRSGYvxRsJYiAksHlg2Dppb/Lg8sQU+5s7JY8NuB/5IOnNKYenJ2QSD\nsRHWIxnG8Ws3N8eq3L7C2OFQWDClAodisXmfC8NykuoxME2bTTtr++ymlspYjDcSxkJMYPHKOBCM\nhVPIiIVVTnY6b28yURWDzy60UBQlsUnEsaiMa2trAUhLS+vz/Ox0mxlZFYTCNq3GVIIdTUBsAZB4\n9dt1ahNIZSzGHwljISaweIXoDxhYtkJLu0lRfirPv1qLYUJZdjkeZ2y+b7wyHsl7xvGgr6urAyA9\nve9doNxuN8VpFZRN8dHQ7iFkeEn1KuzZ30wgFFsARAZwiYlAwliICSxeGbd3RImaLmwb0tOz2LnP\nz6xSF4WptZ1W4HK73Z0GRA23eGU8mDBWFPiX8wsBaAgWYxl+bBtqmmNrUTscR36NyQAuMV5JGAsx\ngR0J4wgR041tw45yA0WBy8/NQVGOVJGhUGhEq2I4EsbxLvH+uqnjo62nFaosPzWXUNRJIJoKQF2r\np1NVDNJNLcYvCWMhJjDDMLBtaGsPY9puwlYqbR0mK07LY9bU2CYQoVAI0zSJRCIjer8YjoRx3EAq\nY4jNSb7q8yWk+lRawnkoWAQibqJW5wFg8TCOL7UpxHghYSzEBGaaJpbtIGwohA0ngYiPVJ/K5Z8r\nSQRvIBA4JoO3ul5fURRSU1P7PD85jDPTXVz+uWJMCwwlC4BDzZmEQkeCVypjMV5JGAsxgRmGgWmr\nRE0XHdFULBsu+1wx6alOnE4nbrebQCBwTAZvQSyM4/d4bdvudL+3J8lhDLDitHymF/to7nATMZ10\nRLw8/cJbiUDuer4Q44WEsRATmGmamJaKP5JGxPRQlOdmxWn5ieM+n49gMHhM5hgDOBwOTj31VABK\nSkr6Pb9ruKqqwvWXxHaUCkRTMSwn+ytbePb372BaVuJ8qYzFeOPs/xQhxHhlmiZhw0VLKBOA6y+e\nilM9sjFDSkoKra2ttLe3AyNfGQMsXryY/Px8MjMz+z23p0r3+LI0lpyYyfvbWgkZXlLScjhYWc97\nH+poM2N7MEsYi/FGKmMhJjDDMKgLFGLaLopyHJykdQ7ArotwZGRkHJN2zZw5k9zc3H7Pi6/Q1bXb\n+Z8/mxsbxBVNoSPswe128ebarUSiVo/nCzHW9VkZa5rmAB4BFgBh4AZd1/cmHb8SuBUwgG3ATbqu\ny0aiQowRgZBJQyAfsLnknPxux+NhXF0d23zhWIXxQPV2Dzg73UFJehWH2kupanRw0fLZbNr8MVt2\nHOzxfCHGuv4q44sAt67rS4HvAg/GD2ia5gP+G1iu6/rpQCZwwUg1VAgxeB/oLixbxecMsuTkwm7H\n4/eIGxoaAAbUdXws9RbG0WiUqZkVuFSLoOGjqd2Fx+Ni07ZyLFuRbmox7vQXxsuAVwF0XV8PLEo6\nFgJO03U9dPi5EwgOewuFEENSVR9iZ0UKChbF2SG8nu4dYcnzfl0u14gP4Bqs3sLYMAycDpNFc0KA\nwrrNfhYumEk4YhA1PRLGYtzpL4wzgLak5+bhrmt0Xbd1PbbLt6Zp/wqk6rr++sg0UwgxWE+/VIlt\nK6S6O5hW3HPIJodvRkYGiqL0eN5o6asyBjh5tkWKF/xhNyEzNvc4Ynmlm1qMO/2FcRuQvESOQ9d1\nK/5E0zSHpmn/DzgH+OcRaJ8QYgg272rlo4/bcKsRPGqY42dm93he8nKU/S1NORr6qowBvB4X558e\nGwj2t/fbyMvNJGyohMKyNrUYX/oL43XA5wE0TVsCbO1y/JeAB7g4qbtaCDGKDNPmqZcqAUhxdaA6\nTLRZBT2eW1hYmBi0NdbuF0Pvy1smb5/4xXNK8TgNGttsUjNLAYX2gIwjFeNLf/OMVwMrNE1bd/j5\ntYdHUKcBG4DrgDXAm5qmAfxE1/U/jlRjhRD9+9s/6jlUF+bEOalUH2rA5YhQkJfV47kOh4Mrr7yS\nrVu3cvjf8JiiqipOp7PXytjlcuF2qSye52PNlijrd9oUeiBsOLEsq98VvoQYK/oM48PTlG7s8vLu\npMcjt9eaEGLQ2joMfve3atwuhRmFFtWHwOsM43L1/k/d4/EkVsUai9xud5+VMcBnl5awfrtOi9+L\nT8kmS2kkFAqTkjK2BqQJ0Rv52ijEBPLCq1V0BE0uOruIPeUNgE2KOzzazToqfYVxvBv7uLIcCrOi\ngE19Rx6G5WTfgZpj3VQhhkyWwxRigjhQFeDv7zeQl+Vm8YlpvPluEJcjitd99PdPLcumvsXkYE2U\nilqDumaDpjaTplYTf9AmHLUJRywsC5xOBZdTwetSyEx3kJ2ukpOhUpLvZGqhk9ICF9npjgGP3Ha7\n3bS0tHTqdo53U8crY4dDYfFJhdSvaSBopNAYzKX8QC3zTyg76p9diGNBwliICcC2bZ78UyW2Df9y\nwRR272sEwK1GcA/hX3l7wGLL7hA790fYVR5GPxghGO491F1O8LgUHA4FI2gRNWyifQxozslwoE33\ncPx0N/NneZg304Pb1XM4J4+ojq+d3bUyBjh1QTFvvFdBxPLSHMzmkwMNg/2xhRg1EsZCTAAfbG9h\nx14/J5SlcdpJWTz060+AWBh7Pf3fjbJtm10HIry3LciGj0PsPhDBSsre/CyVBbNdTCtyMbXQRVFu\nrNrNzVRJS3GgOroHqWHatLSbtLRbNLSaVNUbVNRFOVgTZc/B2Ge9ty22TpDHpbBgjodFJ3g54+QU\ninKP/GpKXp86HsbJA7jipk/JoDDXS6QugD+Sxs6DXqKGicspQ1vE2CdhLMQ4F4laPP3SIRQFvnJR\nKcGQwd6DLfg8oDosUrw9/zO3bZuP90d4c0OAdzcHqGs2E8dmlbpYqHmZP8vDCTPc5GUN/leFU1XI\ny3KSlwWzp3b/7EP1Bh+XR9iyJ8SGXSE+3Bn73y/+0MKcqS7OOiWFcz6dmgjjcPjIve+uA7gAFEVh\n0YnF1L29j7DDTWs4g/Wbqzl9Uemg2y7EsSZhLMQ49/KaOuqbI5yzOJeyKSls2FaNZdl4XQZYNl5P\n58qwocXgb+s7eO39DipqYxWm26Ww7CQfZ5zkY9FcHzkZI1tNKopCaYGL0gIXKxanJsL5H1uDrN0c\nYMe+CHsqWvm/P7dSVjCVbEcbbf4g+Yf3uuipmxpg0YIi/vrOPjI8bTQG8/j96/Us+9SUMbeymBBd\nSRgLMY41tUZY/UYNPq+DK84rAWBbbJVabDO24IfL5cK2bbZ+EuaP7/hZuzmAZYFDgcXzvKxYnMpp\n8334vKM3uSIezpd91sVln82gocXgrY0BXnuvg31VAIv41sM2XzizhQvPSOs2gCuuOD+N/Gw3dU1h\nvM4AVQ0pbNzZyqJ5Pc+zFmKskDAWYhxb9ZcqwhGLlRdMITPdhWla7NjTgM/rRCWKoljsrs3jqz+s\nYd+hWDVZnKtywRnpnLs4ldzMsXk/NS/LyZfOyeDSz6Tzlzd38Ic3GqnqmMGq19r47d/amJk/ldKU\n5m6VMcCC43N4470acnytVLWn8Owrhzjl+ExUVapjMXZJGAsxTu0q97NmYxPF+R7+6fRY/+3egy0E\nggazp2eyc18xVe0lhPb7gCinzvVy8VnpnDrP2+OAq7FIURRmlqicXLSFGxZnUhOYxeq32/mkLpdP\nOJu2X7ZwzeczOXG2N/GeU08s5o33alAUhQxPK1V1mbyxvoFzl3bfz1mIsULCWIhxyLJsnlhdAcC1\nF03F6Yx1MW/YVktzMIs3t+cTCKsoWJw4rZVvXq1RVuIezSYPWXwAl8MOccnZ6XzxrDR++NPX2HSw\nhI92ZfHRrjo+Pc/LdRdmcdw0N8WFWficAYJGCjneRjqimfzub9WcvjCHFO/Y7AkQQlbgEmIc+tt7\nDeyvCnLq/ExO1jIwTZu//sPP06+7qe0oIhRxUJRWzdkz3uTiJY3jNoiBbqOpVYfC1Kwazj3uPf73\nlnyOm+bmgx0hvnF/DXc/3kB1I2SndABgoXLCdGj1G7z0Vu2o/QxC9EcqYyHGmTZ/lOdfrcLlVFh5\nwRTe2tDBk6+0Hh4Z7WRmUZgTpxyisb6KNE9Ht0FO401vU5tcLienzvWx6AQvazcH+fWfW3jnowBr\nNwWYkTMbxfITVjzkpTSSllLAy2tqWXFaHrlZ4/eLiZi4pDIWYpxZ9ZfY+tNLTirg7sdb+O8nGqmo\nNZhdYlCWVc5Nl6QTDjTh8ThxKPaEDGPDMBKDtxRF4cxTUnj8zmK+e3UOBTkq+xqL2dc8ixp/EYdq\n2rn4M4VEojbPv1o1Kj+DEP2RMBZiHNlzoIO/v99MlExWrzXRD0b49Dwvv/xuIXneCtJ8BrOmZ+Lv\nCJGRFhvUpKrj+z5p1zC2bZtoNNrtS4bqUDh3SRpP/VcJZ889hOowaQzmseHQAsJRhYIcD+9sbGJ/\nVeCY/wxC9EfCWIhxIhAyufuxGppD2bQGXEwrdHL/zfncf3MBTiVIS1uYeXPy8PtjYZOWGuuO7Wn6\nz3jicrlQFCWxc1NPS2F2Ot+psGxukHPKXifb10zUcvHI6jABM4uoqfL0S4ew7aPfPEOI4TS++6+E\nmARs2+atjQEe+k0j/qALp2rzjUuy+cKZaTgPz539aEdscNIpcwtpaGwDIC3FTTvdF8YYbxRFwePx\nEAqFABKhHK+Ye1JSUoJv+3Zm5+yjviOH5lAO+6szgSze3xni7Q3NnH1qzrFovhADIpWxEEfp4MGD\niaAYbhU1YW7/aS33PtGIP2iT6gnxyzsKueTs9EQQ27bNpp21OJ0O5h+XT0NTO0BiTerx3k0NsZ2b\n4t3U8f/WfYXxzJkzAchwN+N1hpmRuY8bv2CRm6ESMnz88Kk2XnvPLxWyGDMkjIU4Cnv37uWPf/wj\nf//734f1ulHDZtWrrVx/bzUf6REyUkyyvC3c/M9ZlJV4O52790ALTS0h5s3Jw+d10tgUq4x9h+fU\njvfKGMDr9RKNRjFNMxHKfYWx2+3m+OOPJ83tx6FYhE0vWa4DPHNPCXOng2kp/O8zTXzn4XoO1UeP\n1Y8hRK8kjIU4Cjt27ACgvLx82Kqs7XvDfP2+Gh5/qRUFg5nZn+CymzmhzNvjKlLvbY6NEF5ycmxt\n6oamNhRFSewPPBHC2OfzAbGqeCBhDHDWWWfx5S9fSWmBB1DYtKMBr9vBfbeUUJzZhkuNsuHjENff\nW8OqV1uJGlIli9EjYSzEEAWDQQ4ePJh43tzcfFTXaw9YPPhcI//2YC37q6OcvsDJmdPfIRBNxaFY\n3HDxFBxdlrEMRww+2l5DWqqL+cflYdk2jU3tZGemYluxLREnUhgHg8EBh7HH4yE/P59T5hUAUNPs\nxDAM0lOdXH1BERnuVuaXmbid8PhLrXz9vhq27w33eU0hRoqEsRBD1NzcjGVZiefJwTwYtm3zxocd\nfOXuKl5Z10FxnpP/vSWfLy1rpNpfgmG5KM2oJMPXPSg276wjHDH59IJiVNVBW1uAqGGSm5vR685G\n49FQwjhuwQklqIpByPRRUdUIwGeX5DGjxEdNbTP/8S/pfGZRCvuro9z641p+8nwTHUGrn6sKMbwk\njIUYIr/fD0BZWRkATU1Ng77Gofoo//Gzev7n1420dVh8+XMZPHFnEafO9fH+lkbqOgrJ8EWZmllB\na2trt/e/v+lwF/UpUwCob4ydk5+TgWlOzMo4PoDL6/X29ZaEgrxMfK7Ye9Yf/u+lqgrXXlQKwO//\ndojvXJ3D/TfnU5Ct8qd3/Fz739Ws2yrzkcWxI2EsxBDFw7ikJHavtr29fcDvjRo2z73ayvX31rBx\nV4h5M9386ntF3PDFLDxuBy1tUdZsT0XB4uKzXDgUu1sYN7YE0cubKC1Kp7QoHYCauhYACguyiEZj\nA5PG+zxjOLrKWFUdFGQrgM3mXU2Je/tzZ6Vz5qdyqKoPs/qNGj49z8cTdxZz6WfSaWo1+c9HG7j7\n8QaaWs0R+ZmESCZhLMQQxcO4oKAAh8Mx4DDe9kmIr91Xw/+91IrbCf/+5Rx+8u+Fic0cbNvmFy8c\nIGyozMg+xMknFAJ0C+P18YFbp5QkXqurPxzG+VmJ+bgTKYwDgcCgwxhgSmEGbjVCW4fJvoMtidev\n/kIp6Skqq9+spbI2iM/r4KZLs3n49kJmTnHxzkcBvnJPFX9ZJ9OgxMgaUBhrmubQNO1RTdP+oWna\nW5qmzerhnBRN09ZpmqYNfzOFGHvi4Zuenk5aWhrt7e19/sJu6zB58LlGbv1xHQeqo5xzagpP/lcJ\nF5ye1mlg1t/fa2DTrjbSPe3Mm9ZOZmYm0DmMLcvmvU1VOBwKpy4oTrxeW9+Coijk52YkKmO3e/xv\njJCSkgIMrTIGmDolH48ae9/7m4+sT52R6uTqL5RimjaP/b4Cy4r9/3f8DA+PfreIG76QSThq8/+e\na+K2h+qorJNpUGJkDLQyvghw67q+FPgu8GDyQU3TFgFrgDJAvj6KSSFeGaelpZGenk40Gu20mUFc\nfIDWtfdUdxqg9f1r88jJ6LwgR1VdiKf/XInHpXBcjk5mRjqpqamoqtopjHfsaaCxOcjJcwtIP7zs\npWla1De2kZudjsvlJBKJoCjKhL1nPJgwLptRjFuN4FAsNm6vJRI90vV85qdyOHFOOh+X+3nzg8bE\n605V4cvnZfL494s5eY6HzXvCXH9vNatea8Uw5decGF4DDeNlwKsAuq6vBxZ1Oe4mFtj68DVNiLHN\n7/fj9XpxOp2kp8fu2Xbtqj5U13mA1lVJA7S6ihoWP1u1n0jU5uKzM/C5QqSnp6MoChkZGbS1tSUq\n73fWx0ZuL188LfH+xuZ2TNOiMD9WSUcikcS6zuNdchjHv2QMpuIvKszFodh4nGFCYYMtH9cljimK\nwlf/eSoup8Jzrxyipa1z9Tu10MWD3yzg21fl4HEpPP6nVm783xp27ZdpUGL4DDSMM4C2pOempmmJ\n9+q6/g9d1yuHtWVCjGGWZREIBEhLSwPoFsaRqM2zf23lunur2bgrxPxZHn71vSKuPzxAqye//mMl\neysDfHp+JvNnmJ2um56ejmVZBINBahs62PlJI6VF6cyalpV4f01tbJ5zQX7stUgkMiG6qCF231tV\n1URl7PF4BvUlQ3U48HnA7YgF6LsbOv+6KsrzcumKYjqCJv+3uqLb7QZFUfj8sjSevKuEsxamsLcy\nyi0P1PLI75sJhmUalDh6Aw3jNiA9+X26rsvfQDFpdXR0YNt2j2G8cVeIG/6nmif+3IrHpXDbVTk8\n9K2CxACtnrz5QQOvv99AcZ6Hmy6f0akLHCA1NRWIVeOvr9sPwPIl0zoF0qHqWBdraUkuANFodEIM\n3oJYGKakpNDR0UE4HB5UF3VceqoLl2qQl+1mz/5mquv9nY5fuLyQsik+1m9rYe1HPU9Ty8lU+a8b\n8vjvb+SRk6ny+zfbuf7eaj7cGRzSzyVE3EDDeB3weQBN05YAW0esRUKMA/GwjIdwWloawaiXJ151\nc/tP66isM/jcklSe+kEJ5y9L67ZyVrJ9lQH+78UKPC4Ht10zkxSf2u368TCurW9l/eYqMtM9nQZu\nAVQeDuOSohxM08Q0zQlTGQPk5OQQiUSIRqOJLymDen9WbBBYUXbs/4u1H3aujp2qwi1XzsDlVPi/\n1RXUN/XeDb1sQQq//s9ivnhmGrVNJt95uJ4f/rqBlnaZBiWGZqBhvBoIaZq2jtjgrW9pmnalpmlf\nHbmmCTF2JVeupmmzZpuHN8rPYduBVGYUu/j/vlXAd67OJTu97x2T2jsMHnxqH1HD5uuXTWNasa/b\n9ZP/fG9zHYZpc87S6bicR/75mqZFTW0z2VlppKZ4J9RI6riCgoLE46KiosG/Py8j9sD04/M6Wb+5\nikikc3hOLfLx5c9PIRiy+PlvDyRGV/ck1efg1iti09KmFzl5/cMAX7mnmr+t75BpUGLQBjTMUtd1\nG7ixy8u7ezjv7OFolBBjXTws69oz+Mb/1rC3MoqqKCydU8EP/m1pYnvDvhimzU+eK6e+OcLnz8jn\n9FOO7K/b0dEBHJnSk5qaimGpbNvTQarPxemLSjtdq66hlahhUloc66KeSHOM4/Lzj2ySMZQwzs3J\nQMGiscXP4pNm8vb6CjZsr2Hpwimdzvun0/PZuLOV7Z+088qaOi5cXtjndefP8vDLO4r5zd/aeO7V\nVu5/qpHXP+jgW1fmUJw3/keyi2NDFv0QYghqGwNsqj6ZB3/vY29llDNO9nHunLfQ8vYNKIht2+ZX\nvzvA1t3tnFCWxr9c0DlcOzo6cLlcico2NTWVxkAupgUrTp+B19P5l3xlVQMAJcWxQJfKuLu0tDRc\nanepXmsAACAASURBVJRo1GT+cdkArPmgott5DofCTVdMJ8Wr8pu/VnGgqv9lMd0uhWvOz+RX3ytm\n3kz34d2gqvndG22YMg1KDICEsRCDYJo2f1rTzk//XMyB1hkU5Sjcd3M+d38tn/ysI/d6+/P8a9W8\nvaGJKQVebr92ZqcAt22bQCCQuE8MEIqqtISycDttzlo8tdv19u6vAaBsWqyKm4iVcfz+OdDpv81A\npaam4nTENs8IdPiZMyObg1Vt7D/Ufc3vvCw3N1wyFcO0eejZcoKhgd0LnvH/t3fe8XWUV97/3rm9\nqfdiyyoedyQXbLANNsUGbAdMIJAQAsSQhCT7sptsdkl2IYTsZvd989kQNqQSQkIngGnG4IKxwb03\nSR7JsmT1Xm7R7XfeP+ZeWbKqqyx7vp/P/dy5Ux6dGd07vznnOc950vU8+4NUHrsnHkGA37/Tyfd+\n2UR5jf+M7VW5slDFWEVlhOwp8fDILxp59o0OAiEBMfEYf3w8hblTlX5eq9VKIBDoEcLBWL+9hdUb\nG4mP0fNvj+Rjs/T1cv1+P8FgsI/grNtai4xAdpIbo6Hv/uFwmBNVjVjMRtJS43vagMvLM9ZoNDz0\n0EOsWrXqrI632WzoBSViUFXT3DNGO5qdfjrzi+JZNCeRumYfv3vz5Ij7gQVBw+3X23nxiXSunWGm\nrNrPo//dyDOvt9PlUhO8VAZGFWMVlWGobgzwk98186/PtVDVEGDRTAtfmraDwqxK7LZTQ2yiSVbR\n/t6B2HO0kxfercFsEvjJw3kkxfcXy+jxUTE+VtHGodIWzHo/Mfr+Q27qGtvx+gLk5aQhRIY6XY5i\nDIp3fDZeMSj97zohiEYDVdXNzJiUTHKChQPFTbS09w9FazQaHr4zu2e404ebmwdodXCS43X8/NtJ\nPPVIEsnxWj78wsX9P63n3c1ONXSt0g9VjFVUBsHhDvHcWx2s+o8Gdh71Io4z8OwPUvj3byagCbb1\nG17TeyzwQOwt7uSZlysRBA0/ejCP8RmWAffrnbzl94d4/cMSAPLTPXg83T1TI0Ypr1BqLedNONWP\nejnN2HS+0Gq1WCxmjLoQDmc3Dmc3N80fjyzDp9tPDniMITLczGbR8uraOo6Wj3xmLlAE/boiCy8+\nmc4Dy2LxB+E3f+/gW//VyAHJez5OS+UyQRVjFZXT8HjDvPJxF/c9Wc/qz5zE2bU8/o0EfvsvqUzP\nN+HxeAiHw/3EeCjPeMehDv7nbyeQgX+6fwLT8u399onS2zP+cNNxWto9zJ+VSWaK4oV3d5/y4sKy\nzKHiKgRBw8S8U1nBl6tnfK5YrVYElPHDVdXNzCvMwG41sGN/HU73wN0LKQlGHrtPmbP6169U0tp5\n5v2/JoPAA8ti+euT6VxXZKayPsAPn23mqedbqFMnn1BBFWMVlR78AZnVnzn5+k/r+cuHXYTD8I3b\nYnjpp+ksmXeqcMfpY4CjRD3j08X4831t/PoVxSP+lwdzuXpaHEMRFduWLoFPt58k1m5k5ZKJA4r9\nyZpmOjpdiHmZ2KymnvWXYzb1+cBqtaIXFDGtqmlGr9eyeN44AsEwm3dWD3rcVWIM9yxNx+EO8ssX\nK/D6zq7vNy1Rx1OPJPM/j6UwIUPP5wc8PPh0A8++2U67Q+1PvpJRxVjliicUlvlkh4sHflbPc291\n4PKE+fINdl59OoMHl8dhNvX9mQwnxr3D1Bt3tvLbN05i0Ak8viqPosmxw9rjcrkIhHRs2NmORgMP\n3TUdi1k/oNjv2qsM9y+akdunjcsxm/p8EM2o1moFqmqUPuDrrs7GaNCyZXc1Xl9w0GPvuCGNeTPi\nqKzz8MzLlefU71skmvjTj9P44X0JxNm1vL/Fxdd/Ws9f13TS7VUrDV+JqGKscsUSDMms3+li1c8b\n+H8vt9PSEeK2a6289FQG37srnrhBqmcNJsa9PddwWOblD2v509vVmAwCP3kkn+kFMSOyq6PTRa0j\nC483xPLF+UycoIwdPl3sj1c2UFJWQ2pyHAV5GX3aUMPUA2O1WtFoIDnBRkeniy5HNxaznoVzsun2\nBAftOwYlS/r7X81BzLFy4JiD51dXn1OlLa1Ww7L5Nl7+WToP3x6LVoCX1jq4/6f1vLfFSSCoJnld\nSajlYVSuOPwBmY93uHhzg4PGNiU0eP1MCw+tiGVc6vCe5HCecUdnN//3LxUcOOYgMU7Pvz6UR07m\nwMla/Wzzh9hVKuMLmZg5NQVxgoWPNuzF3e1FIwfxBo3UNbSh0VWxZv0eAJYvmY1W6PtcHQ11Ryt4\nqShE/0cJcSYaWxxUVjdROG0CSxbmsG1fLRu3VbFwThYxtoEnojDoBX70UB5PPCexaVcbFpOW+5dn\nntM0lSaDwNeWxrJsvo3X1jl4b4uT/32zg9fXOfjq0hhuu9aGQT/2p8FUGRpVjFWuGLq9YT74wsXb\nnzpod4QRBFgy18q9S2LISR95ODcqxt3eMK+9vYXm1i5i7BbmzppIEDsbizNw+xyIOVZ++EAucfaR\nte3xBvjDawfpdOuxGT2YhS7++nrJaXvZ2XmwEQ42KtP63TSL8dkp/dqKinF0HmAVhagYx9qUW195\nRT2F0yZgsxhYunAC720oZ+3mE9y7fPKgbcRYdTzx7QKefK6MNVuaMRkE7l6Sfs7zRsfatDz65XhW\nLrLzysddrNvp5n/f7ODVTxx85SY7KxbaMA0y/abK2EcVY5XLnqb2IO9/7uKjrS6c3WH0OvjSQhv3\n3BxzVrWDnU4n3qCRN97bgSyDXq+lrcPFoXIvze5phGQti+Yk8MiXx/WZzGEomtvc/PG1gzS0uLHo\n3cSYPEgVbtJT41m8YDqJ8XYam9v56OONmC0xiGIBU8VxZGcmDdiex+NBp9OpYerTiEYz9NogFrOR\n8hP1hMJhtILAonnj2Lyrmq17a7nhmnGkJA4+njkpzsAT387np78r4+0NjYTDcM8t5y7IoCR5/fPX\nE/n6rbG8sd7Bxztc/P6dTl5f5+Dum2K4/TobFpMqypcbqhirXJbIsszBMh/vbnay/bCHsAxmo4av\n3GTn7htjSIwdejaloWhqdePy2zDoddyxbB7jstL5zWsVSGXdaAiTZa/hgeXiiIQ4HJbZtq+W1evK\n8PlDzJyaRMPJOvwBI5MKsrj79vnodYqtSYkxbNnkI84e4JYbZg7Zbnd3txqiHoCoZ9zd3U1BbjqH\niquoqWslJzsFg17Lihvyefm9Yt7fUM4j9xYO2VZ6somnvjuRp/9QzupPG/EFwty/PHPI6TLPhLRE\nHf/41QTuuzWGN9c7WLPNzfPvdfLaJ13ccq2NlYvsZKgTUVw2qP9JlcsKjy/Mxt1u3tviorJeGd6T\nlaLjjuvtLJ1nxWo+N4+ircNJc6cijvfdfT0dbhM/+tUxOhwBstOMmIMSAl4OFVdy7dXTBm1HlmWO\nlrXy0WcVVNc70OsF7l0+GZ+7kepKI3arnru/dG2PEINSQMJms+F0OpFleVAvLBgM4vf7iY+PP6dz\nvRyxWCxoNBpcLhfTi67iUHEVpWU15ERC/XMLM/h0x0kOlDRTcryVKfkDRx6iZCSbeOrRifz8j+V8\n9Hkznc4A371n/IgjIiMhOU7H97+SwNeWxvL2Jgdrtrp4Z5OT1Z85uWa6mTsX2ymaaDwvXrnK6KGK\nscqYJxyWOVLhY91ON1v2d+PxKVmoc6eaWLnIzuzJpvPirciyzLtrdiAjkBhv4a1PXewtrkOjgTtu\nSOUrS9LZ8GkzOw7U89nWEqZPycNuM/c5vqHFzb4jjew90thTgnHaxCTuunUSgibIb1/YBsjMnpGB\nXt//5xkXF4fD4eg3kURvPB4PoCZvDYQgCNjtdrq6uijITUev01J8rJqlN8xE0GgQBA33Lp/Mr17Y\nw+sflvLE967FYBg6ipKWZOTn35/If71QwbYDHbR3BvjhAxOIsZ3fYWUJsVq+tTKe+2+LZf0uN+9+\npkR9th/2MCFDz8pFdhbPspzzA6fK6KCKscqYpaE1yPpdbtbvdNEQyYqOswksm2/j9utsZKac35vh\nwSOVVNW20eFJoKw9mXC4iwmZZlatzGZijtIXmZWRhOXocdw+K6+t3sHMwknUNrqoaXBS2+jA5Va8\ndUHQMGNSMjfPzyFvfDyhcJg/v7yBUCiMzeAiLSVhQBtiY5Vxyl1dXYOKsZpJPTSxsbE4HA7CoSAT\n8zIolmqorm3p8Y7zx8ezYHYWW/fW8u6GMu5ZNngyV5SEWAM/e3Qiz7x8gkNlTh7/tcQ/P5hLbtb5\n/x+YjQK3X2dnxQIb+455Wf2Zk13FXn71Wju/fauDhUVmbplno3Ci8byFzFUuPKoYq4wpmtuDbD3k\nYcuBbo4cV8oa6rSw4CozS6+xMneqeUTzCZ8pbR3d/O39CpqceYTCOixG+PqKcdxwdSLPPvssf/cE\nWLTkq5SWeWh2p+ALmmg7HuTQ8aM9bdgseqbkJ1I4JZXCKSnYLKeSqz7fXkxdQxsJsQY0fl9PiPnZ\nZ58F4LHHHgP6inFGRt+xxVEGy6ReunQpAOvWrevXbpTo+pGyb98+AGbNmtWvvQULFhAIBPja177W\ns36gvxtdN1Bbg9l5us1r164lNTWVl156acDtvduIi4ujpqaGzs5Opk0eT7FUw+Hiqh4xBli5ZCKl\nx1vZsquGaQVJTJ2YPOy1sJi1PL4qn1fX1rFmSzP//huJ+1dkcsv85AsSQhYEDXOmmJkzxUxNU4CP\nt7tYv8vNxt3dbNzdTUqClqVzrSyZZyUzWS3+cqmjirHKJU9dc4DPD3r44mA3x6pO1QUuyNazdJ6N\nG+dYiLWdfULWUHi8IdZtb+GdDXX4AokIGpl0Wx1fuW0i3oCL516q4u3Va5CBeu9VkaPMmPRhIIBO\nE2TFzVcxfXI6sfaB+/XqGtrYsu0oFrORlLgQrS30iPHGjRuB/mLc2dk5uM2DhKnb2tp6lk9v9/T1\nI6W5Wali1dHR0a89r9fb02Z0/UB/N7puoLYGs/N0m9va2ga9JkNdw4kTRSxmI4eLq1iyuAiTUREt\ns0nHA1+ezjN/2cNfVx/l8W/PIzF++GFiWq2Gb6zIIj/bwh/fqubF92o5eMzBt+8eR0Lshctsz07V\n862V8az6Uhx7Sr18ssPFjiMeXv7YwcsfOxDHGVhYZGZhoYXsEYylV7n4qGKscsnhD8gcPeFjb6mX\n3Uc9nKg/VUh/Uo6B6wotLCg0k3Wew9C9qW30sH5HK1v2tuHxhdEgkxbrJjO+m4Y2eHXNqUpNGkGD\nXivw5aUTyc6IYf3at7BaDMycs4h31uzg0JES5s3MHlCI/YEg76zZQViWWbF0Dlu3fIzVasVoHLjo\nRFycUte6q6trUNvVMPXQ9L6Gep2Wohm5bNtVyuHiSq6eObFnv/zx8XzpxgLe31jOH18/yA9WzcFk\nHNkt89rCBHKzrPzmtUoOHHPwg1+Wct+yDG6cm3RBQ8darYZ508zMm2amyxVi095uNu52U1rlR6r2\n8+f3u5iQoWdhoSLMuZl6NfHrEkEVY5VRR5ZlTjYG2VvqYW+pl8PlPrx+JQlLo4EZ+UauK7Kw4Coz\nKQkX7ivr9YXYU9zFpztbKTmhFPawmrUk2ZwIYTfBgI6TzQJgYFJuAtMnJTO1IIlVB34DwI3zcwDY\nnxhLc3MzU8QsjlfmcKi4ig8+2c3K5df0zDcMyoxL767ZQWubg8JpE5gwLolPfT6SkwcPiY7EM44K\n9ekVwlQUomIcvYZzCvPZvquU7buPMaswv081syULc6htdLLvaCN/euMQj95XNOJM6bQkI09/T+Sj\nz5t5c109z79Tw8adrXxjRRZTh5i163wRa9OycpGdlYvsPd07Ww92c/i4j8r6AC+tdZCSoGX2JBOz\nJpmYOcl0wSJMKsOjirHKRccfkCmv8XO0wkfxCR/FlT46HKeK4yfHablhtonZk00UiRf2BuEPhDl4\nzMG2g+3sK+nCH1AeAnKzzIxPFSirqMbnlwmjIzPVRtB9gqxkDaseXDpom/Hx8TQ3N9PZ2cnyJXOo\nb2znUHEVWq3Asptno9frCASCvP/JboqlGtJT41m2ZDYtzU0AJCQMnLwFoNPpiIuLo7W1lWAwiE7X\n/yccDUcnJiaey6W5bImJiUEQBFpbWwFIiLczfcp4Dpec5NDRSmbOyOvZV6PR8I2VU3G4fByraOP5\nNw7y8D1XYdCP7Dup1Wr40uJUrp4ex98+qGVfSRc/+0M5U3Jt3LUknal5tovimaYk6LhzsZ07F9vp\ncIbYfljp9jlU5mPtdjdrt7vRaCA/S8+syWZmikYm5xjVzOyLiCrGKheUUFimpilIRa2f8ho/JZV+\npJM+Ar0mx7GZNcybZmL2ZDOzJ5vITtVd0BtUa6efA6Vd7C91cLTciS+gPAgkxOqZMdGGJtxNWUU9\nR9pDgIzdIvPQV+ZgM3hYvXov47OnDNl+VASbm5tJTk7mgXtv4C+vbWT/4RMcr2wkOyOR6rpWnC4P\nqclx3HfX9RgN+h4RHW58cHp6Op2dnbS0tJCent5nmyzLtLW1YbfbBw11X+nodDqSk5NpamrC4/Fg\nNptZNH86R0qr2fTFEaaK4zAaT3WB6PVavvO1Ip57eR9Hy1p57qX9PHLvVditI+8DTksy8q/fzONw\nmYO31jdQcsLF038oZ/IEG8uvT6FocuwFSTwciHi7lmXzbSybb+vTJbSv1MPx2gDlNQHeWK9EpSak\n65mSa2TKBANTco1kp1zY3+aVjCrGKucFWZbpcISpaQpQ1RigojbA8Vo/lXUBfIG+s89kJuuYmmtk\nWp6RqbkGxqfpL2g/WocjQEmFk5ITLkoqXNQ1e3u2JcTqWTApnpR4OFndwtHiBgAsJh12kxej4OXR\nB28iPS2BPXuUiRkGy2LuOb/MTABqa2uZOnUqMXYL33ngFj7ZdIDDxZUUSzVotQJzigq4eVFhT9JQ\ndXV1n+MHIy0tjdLSUhobG/uJscPhIBAIDNvGlU5GRgZNTU00NDSQm5tLUmIMc2dNZOdeiQ1bDrJ8\nyZw++5tNOv7PA7N4/o1DlBxv47//sJOHvjyd/JwzK6wyY2IM0wvsHD3u5K31DZRWuiitdBFr13H9\nrAQWX51EZopp+IbOEwa9hpmiiZmiCe6Io8sVYv8xL4fKfZRU+jhRF+BEfYA1W5X9Y6wCeVl6cjMN\n5Gbqycs0kJOuVyeyOA8MKcaiKArA74AZgA94WJKkil7bVwBPAEHgL5Ik/fkC2qoyykQFt7E9SFNb\nkLqWIDVNAWqag9Q0BnB7+0/5lpGsIz9LT16WgfwsA+J4AwkxFy7s7OoOUlXvoaLGTUVNNxU13bR0\nnMrA1gog5lgpmhzL+DQ91bWt7DxYySG3sk92up0501M4ePgoDoebZTfPIj1NCRs3NChCPZwYp6am\notfrqamp6amUZTIZuOO2udx600ycLg92mxmj4ZT3FQqFqK2txWKxDBteTktLA6C+vp6ioqI+26Kh\n16SkoStHXelkZGRw4MCBHjEGuPG6GRwrq2X3/nKyMpIonDahzzFGg45H7yvi/Y3lbNx2kmde3MOC\n2VksvyH/jLxkjUbD9IIYpuXbkarcbNrVyo5DnXywuZkPNjczPt1M0eQYZk6OpWCcFe1F8phB6Wde\nPNvK4tnKGHaPN8yxk35KKn2UVPoprfRxQFJeUQQBslN0jEvTk5miJytZR2ayjswUHYmxWtWTHiHD\necZ3AAZJkq4VRXEu8D+RdYiiqAd+BcwGuoFtoih+IElS84U0WOXCEAjKtDtCtHeFaOsK0RZddoRo\nbg/R2BakuSPU06d6OinxWibl6MlO1ZGdqicvS3lqvhB9TqGQTHuXn8Y2H7VNXuqavNQ1e6lt8tLl\n6js5vFEvMDnXxpRcG5MmWLGYZMor29hffIKNW5QkLYNeYP6sTObPzkKQ/fz9/a04nB6uvXoSc2eJ\ngJKhXFNTg9Vq7UmiGgxBEMjMzKSqqoqWlhZSUk6NXzUa9BgT+meBNzQ0EAgEyMvLG/bmlZiYiMVi\noaqqCq/Xi8l0ypOqqakBGDIJTEUJ9Ws0GsrLy7nmmmsQBAGjQc+9dy7khVc28N7anQD9BFmrFbhz\nqcikvERefb+EL/bUsudwA/NnZbFgdhapSYNPLnE6Go2GSRNsTJpg48E7Quw41MGWvW1IVW5ONnh4\nb1MTVrMWMcdKwXgrBeOs5GVbsJovXkDTbBIoEpXcDTj1QF5R51e85jo/J+oDnGwIcLIxCHj6HG8y\naEhP0pEcryUlPvquJTleR3Kclni7FqtZowo2w4vxfOATAEmSdomiOLvXtsnAcUmSugBEUdwKXAe8\nfSEMVRmaYEjG45Pp9obx+GQ8vsi7N4zbE6bLHcbZHcbhiry7wzjcIRyR9d0DeLW90esgNUFHWqLy\nSk3QkpaoPA1npegwG89ddMNhGac7iMMdpMsVxOEK4HAFaXcEaO3w09rpp6XDT3tXgIHmdLdbdUzO\ntZGdZiIvy0JakoFwyE9do5OqumZeWd2B26MMk9JooCAnnlnT05gzPR2fz8e2XaXsOVBOWJa5/tqp\n3LBwRk/bBw8eJBQKMWPGjBHdOERRpKqqij179rBs2bIh95Vlmd27dwOQn58/bNuCIDBt2jR2797N\nkSNHmDNHCan6/X5KS0sxGo3k5OQM286VjMVioaCggLKyMsrLyxFF5aErIy2Be1Yu5M13v2D1mh0c\nr2zomTWrN1Pyk3jyH65l0/ZqNm6v4tPtJ/l0+0kyUmwUTkmhICeBcRl2zKaRDb+zmLTcODeJG+cm\n4XQHOVTmYH9pF4ckJ/tLHewvdfTsmxinJzPFREayiYxkI8kJRhJj9STEGbBbLqwnqtFoSIjVkhCr\nFBuJEgzJNLQq0bK65gC1LUHqmpXPJxsDPXXiB0KnVTzyWJtAnE04tWxX3mMsAmaTgNWkwWISIi9l\nWa+7fER8ODGOARy9PodEURQkSQpHtvUe7OgEhnYZLgEaWoM0tgUH3DaoHA2yQUYRkLCseGvhMIRl\nZV0oDKFwZHtkfSikrA/LkXVhJcEp+h4MKZnGgaB86r1nmV7Lyrs/KOONCG9g4FMaFptZQ6xNS3aK\nQEKslsRYLQkxArFWAZ8/gN0iEGfXYDVrEDQaZDlyOWQZCOJyBSlxQiAYJhiSCQZlgiFZ+RyUCYRk\ngpFt/kCYbm8Yry+ExxtSHhii774Q3d7QgCLbG5NBQ3K8DrtFS4xVIM6uw2KU0etkQqEg7m43LU1t\nlJR68Pr6XhSrWU/RlBQm5SWSkqCnvqGF9pZ6/vZGMQ2N7ciA3WZmxdI5TCrI6jmupKSEvXv3otfr\nmT59+oiua0FBAXv37qWiooKtW7dSUFCA0WhEq1VC9LIsI8syXq+X0tJSamtrSU9PZ8KECcO0rDBt\n2jT279/Prl270Gq1JCYmcuTIEQKBAEVFRej1amGH4Zg5cyZlZWVs3LgRm83W088+MS+Db953E++s\n2cHh4ioOF1eRkZZAWkoccbE2ZkwZT0K8HaNBx62Lcll8zTh2H2pg39FGjp/soH6zCzgBQHKCmcQ4\nM/FxZmJtBkxGHUajFpNBR1yMkYKchH75EnarjgVFCSwoSkCWZRpbfZRXuzle001FtZvaZi+Hy5wc\nLnP2Oye9ToPNosNm1mK1aLGadVjNWmwWLUaDgF4nYNAJ6HQaDHpFzPQ6AYNeqctt1AuIE2xnnEym\n02rITtVHCor0LY4SCilRt5bOEM0dIVo6gj3vXa4wna4wDleIqvoA4WF+//3PF0WcjRoMBgG9Dgw6\nDQZ95BVZ1g+0TqtUMdNqQdBEloVT67SnrRMETm0XIDfTcE6zv/W7hsNsdwC9HwmjQgyKEPfeZgc6\nhmhLC9DY2HimNp43AkGZVf/ZQPAshetSQdAoPzqdToPJqCHBrMFkUF5mg4DJoMFoFDAZwWQQMBs1\n2M0CNkvkFVm2mjSRG0E48jp1YV7/uJ5tB4b6d56ncxGUWrsmo5Zkm4Ddqsdm0WK36LBZlfcYq46E\nWD2VNW18vOUEbh+422Cwb5IGiLUbSY03kZZkJT3FRkaKjdQkS4/X8MpbG2lpPfWcmZwUw9RJ45g2\naTx6vZJ8FeXYsWMEg0EWLFjQ0yfbm0BAeervfQwogrlx40Y2b97M5s2bh7wOVquVyZMnU1dXN6K2\nQRGTTZs2sXbt2p51iYmJpKenD7h/OBzuaWuwdqPrR0ooFBrUzujfCwQCPesH2i+6bqC2hjr/3sf3\nPreBtg+2rbCwkO3btyNJEvJpT4K3L5lBiVTD4ZIqystPUF6urC8/nsWtN/adwjI3Q0NuRjru7kSk\nyg7qmpzUNzqpr++guibMYDx89wzGZw3vw+SmQm6qBmbbkGUrTneIpjYfTW0+OhxBupx+OpxBOp0B\nuh0hWppDhAf/s0Ny181pLJpz/ofFxeghJgXyUwbeLssaXB4ZpzuMozuE0y3j7A7j8oTxRiN9EefD\n65Px+sN0+xSHpM0Zxh+UL+q9PTNFxy//YZCT6UUvzRtSuTWnfwF7I4rincAKSZIeEkVxHvCEJEnL\nItv0QDEwF3AD2yP7NgzS1gLgi2EtV1FRUVFRufxYKEnS1sE2DucZvwvcLIritsjnh0RR/CpgkyTp\neVEUfwCsAwTghcGEOMIeYCHQAIRGbL6KioqKisrYRQuko2jgoAzpGauoqKioqKhceNRaZyoqKioq\nKqOMKsYqKioqKiqjjCrGKioqKioqo4wqxioqKioqKqPMRaurJoriSuAuSZLui3yeB/waZXDrekmS\nnr5YtpwroihagNeBOMAPfF2SpKbRterMEEVRi1LOdBZgAJ6UJOmT0bXq7BFFcRKwE0iRJMk/3P6X\nGqIoxgKvoIzXNwA/kCRp5+haNTKGq2E/VogM1/wLMB4wAv8hSdKHo2vV2SGKYgqwD7hRkqSy0bbn\nbBBF8cfACkAPPCdJ0t9G2aQzIvK7+DMwEaWQwyOSJEmD7X9RPGNRFJ8FfoFSjyHK74GvSpK0cpEM\neQAAA8RJREFUAJgrimLhxbDlPPENoFSSpOuBN4EfjbI9Z8P9gC5y/e9AKW86JhFFMQalbrp3uH0v\nYf4J2CBJ0iLgQeC3o2rNmdFTwx54HOV/MRa5D2iRJOk64BbguVG256yIPFT8EaX+w5hEFMVFwDWR\n79QiIHdUDTo7lgDWyD32aeA/h9r5YoWptwGPEhHjyM3TKElSZWT7OuCmi2TL+cADREvUxKJ4x2ON\nJUCdKIprgOeB90fZnrNCFEUNyo3nx5xepX5s8Qzwp8iynrF1Ln1q2KNMHjMWeQt4MrIs0Lsk3dji\nlyjOzlB1Hy51lgBHRFF8D/gQ+GCU7TkbPEBs5B41rE6c1zC1KIqrgH88bfWDkiT9PfKkE+X0mtdO\nLtEnnwHOSQa+DzwuimIxEI8yQcYlyyD/lxbAI0nSclEUrwNeBK6/6MadAYOcx0ngDUmSDkeK/V/y\nleOH+J3sE0UxDXgZeOziW3bWDFXDfswgSZIbQBRFO4ow/9voWnTmiKL4IIp3vz4S5r3kfw+DkAxk\nA8tRtOEDYNKoWnTmbANMwDEU523FUDufVzGWJOkF4IUR7Hp6zesYoPN82nK+GOicRFH8E/CrSBWy\n6cA7wFWjYd9IGOQcXgc+imz/XBTFiaNh25kwyHmUA6siApeGEmVZdPGtGzmD/U4i36XXgR9KkjSW\nSscOVcN+TCGKYjawGvitJElvjLY9Z8FDgCyK4k1AIfA3URRvH2s5LUArSldgECgTRdErimKSJEn9\ni8NfuvwLsE2SpH8TRTEL2CSK4rTBclou3sSYvZAkySGKol8UxVygEiUk8dRo2HKWWDnlCbSgPEyM\nNbYCtwGrRVG8CsXDHHNIklQQXRZFMfpdGnOIojgFxRu7W5KkI6NtzxmyDeWp/61IYubhUbbnrBBF\nMRVYD3xXkqTPRtuesyGSxwKAKIqfAd8eg0IMyv3pMeBXoihmoNxz20bXpDOmt050oHQ/DTpZxMUU\nY5m+kxF+B3gVxbh1kiQNWbfzEuMnwPOiKH4P5Ro+PMr2nA3PA78XRXFH5PN3RtOY88RYru36C5Qs\n6v+NhNs7JUlaObomjZh+NexH05hz4CcofXtPiqIY7Tu+VZKksZwYOCaRJOkjURSvE0VxN0r//Xcl\nSRprv+9fAi+KovgFihD/WJKkQXNB1NrUKioqKioqo4xa9ENFRUVFRWWUUcVYRUVFRUVllFHFWEVF\nRUVFZZRRxVhFRUVFRWWUUcVYRUVFRUVllFHFWEVFRUVFZZRRxVhFRUVFRWWUUcVYRUVFRUVllPn/\nRNDcYc9vZLIAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x1114fbed0>"
]
}
],
"prompt_number": 14
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Although the gaussian kernel is the most common, and probably the most useful, there are a variety of kernels you can use to fit the density estimate. The kernel you choose generally has less influence on the resulting estimate thean the bandwidth size, but there may be situations where you want to experiment with different choices."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"kernels = [\"biw\", \"cos\", \"epa\", \"gau\", \"tri\", \"triw\"]\n",
"pal = sns.color_palette(\"hls\", len(kernels))\n",
"for k, c in zip(kernels, pal):\n",
" sns.kdeplot(data, kernel=k, color=c, label=k)\n",
"plt.legend();"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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6TsfoFDJn5R7y+OF2bbrhhhtYunQpd911F08++SRr1qzh8ccf56233qKuro4b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\n",
"text": [
"<matplotlib.figure.Figure at 0x1114df4d0>"
]
}
],
"prompt_number": 15
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `cut` and `clip` parameters allows you to control how far outside the range of the data the estimate extends: `cut` influences only the range of the support, while `clip` affects the fitting of the KDE as well."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"with sns.color_palette(\"Set2\"):\n",
" f, (ax1, ax2) = plt.subplots(2, 1, figsize=(8, 8), sharex=True)\n",
" for cut in [4, 3, 2]:\n",
" sns.kdeplot(data, cut=cut, label=cut, lw=cut * 1.5, ax=ax1)\n",
"\n",
" for clip in [1, 2, 3]:\n",
" sns.kdeplot(data, clip=(-clip, clip), label=clip, ax=ax2);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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V0bHskmejV1RkUAhR2aWEmTuw+2YBuG7eBK5o+psrGXNOG5xQbBTLFek9wDEA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\nAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x110b80a90>"
]
}
],
"prompt_number": 16
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As in the case of the histogram, plotting shaded density plots on top of each other can be a good way to ask whether two samples are from the same distribution. This also implements a simple classification operation. For a given `x` value with an unknown label, you should conclude it was drawn from the distribution with a greater density at that value.\n",
"\n",
"A legend can be helpful when overlaying several densities. This is done either by providing a `label` keyword to `kdeplot`, which explicitly assigns a value to the data, or by inferring the name if you pass an object (like a Pandas Series) with a `name` attribute."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"f, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(8, 6))\n",
"c1, c2, c3 = sns.color_palette(\"Set1\", 3)\n",
"\n",
"dist1, dist2, dist3 = stats.norm(0, 1).rvs((3, 100))\n",
"dist3 = pd.Series(dist3 + 2, name=\"dist3\")\n",
"\n",
"sns.kdeplot(dist1, shade=True, color=c1, ax=ax1)\n",
"sns.kdeplot(dist2, shade=True, color=c2, label=\"dist2\", ax=ax1)\n",
"\n",
"sns.kdeplot(dist1, shade=True, color=c2, ax=ax2)\n",
"sns.kdeplot(dist3, shade=True, color=c3, ax=ax2);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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T24ULURee/GwjXr/Jhf1a4rBVXmo++oWnAcgbf6msGhYixqTY2VLg5/v9Xhbs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\n",
"text": [
"<matplotlib.figure.Figure at 0x110b85550>"
]
}
],
"prompt_number": 17
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If you want to plot the density along the y axis, use the `vertical` keyword."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.figure(figsize=(4, 7))\n",
"data = stats.norm(0, 1).rvs((3, 100)) + np.arange(3)[:, None]\n",
"\n",
"with sns.color_palette(\"Set2\"):\n",
" for d, label in zip(data, list(\"ABC\")):\n",
" sns.kdeplot(d, vertical=True, shade=True, label=label)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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W1MKLuSDv5cJMFhJ81t6+qfdwrBshyDtryTtrSbTtBVXFFA9hXpq6+mYbfRfb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\nTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x110b7d690>"
]
}
],
"prompt_number": 18
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can also use `kdeplot` to estimate the cumulative distribution function (CDF) of the population from your data. This plot will tell you what proportion of the distribution falls at smaller values than a given point on the `x` axis:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"with sns.color_palette(\"Set1\"):\n",
" for d, label in zip(data, list(\"ABC\")):\n",
" sns.kdeplot(d, cumulative=True, label=label)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Bs6IonYCRlBZeACwWiw54G7hfUZSuwC+Ab//aLEQ5cufnk/fqa+iCg4kcM1rr\nOJft4zUpuFXo36W2z440XW4XUzdNIs+exwNNB1I7uo7WkYS4JBcqxp2BHwAURdkAtDnnufpAFjDM\nYrH8BkQriqJ4I6QQ/ih/xkzcGRmEP/mE3x2P+IfM/BK+336CGjEh9GhUVes4/+njfR+xN2svnap1\n5rpa12sdR4hLdqFiHAnknfPYdfbSNUAc0AmYBVwJ9LJYLD08H1EI/+M8epSC9+ZhqFGDiEcf0TrO\nZVu8/hgOl0q/TrUw6H1zVLzt9Fa+OPAZ8WHxPNlqsM+O3oU4nwsV4zwg4tzXK4riPvv3LOCQUspJ\n6Qi6zd8bEKIiso5/BRwOokaPQhfin3shFxQ7+HLTcWLCzVzXoprWcf5VVlEW0zdPxaAzMLzts4SZ\nfHv9sxD/5ULFeA1wHYDFYukA7DznuSNAuMVi+ePmTFdgt8cTCuFnSlavofiH5ZjbtSX4Bv+9ZPrl\npuPYSpzc2b4mQT54TKJLdTFt8xSsdiv3N32AepXqaR1JiMt23tnUwBLgKovFsubs4wEWi6UvEK4o\nyjsWi+VB4OOzk7nWKIqyzJthhfB1qstF7tiXQKcj6qWxfnvJtMThYvHZYxJv9dFjEj9TPmV35i7a\nJ3Tghto3ah1HiDI5bzFWFEUF/n7454Fznl8B+N/J6EJ4SeGixTj37SP0jtsxN2umdZzLtmzHSbIK\n7PTrnOyTxyTuydzN4n2fUDmkMoNbDfXbX3qE+INs+iGEh7jz8sibOAldaKjf7j8NfxyTmFJ6TGIH\n3zsmMa8kj6mbp4AOnm77DOHmcK0jCVFmUoyF8JD8WbNxZ2UR8eQTGOLjtY5z2X7fd5q07EJ6++Ax\niaqqMmvrTLKKMunbsB8NYxtpHUkIj5BiLIQHOFNSKHj3PQzVqxP+8ENax7lsqqqycLXvHpO49Mh3\nbEzfQNO4ZtxWv4/WcYTwGCnGQniAdfwrYLcTOep5v13KBLDl7DGJ3RpUoaaPHZN4JPcI83a/R6Q5\nkqfaPI1B53szvIW4XFKMhSijkjVrKV72A+a2bQm5yb9n9frqMYlFziKmbJqE0+1kSOuniA3x3T2y\nhbgcUoyFKAPV5cI69iUAol560a9n9Sqn8thwOItWyZVoXCNa6zh/8faOuZwoSON/dW+mTXxbreMI\n4XFSjIUog8LFn+LYu5fQ2/tgbt5c6zhl8qGPjop/O76CX1N/pk50Xe5tfJ/WcYTwCinGQlwmd35+\n6VKmkBAyA+jfAAAgAElEQVQiRz6rdZwyScsu5Jc96dSLj6BD3Tit4/zpVMFJ3tz+BsHGEJ5pOwKT\n3vfWPAvhCVKMhbhM+bNm487MJNzPlzIBfLy29JjEezon+8yldofbweRNkyh2FvF4iydICPfN/bGF\n8AQpxkJcBuexYxS88y6GatWIeORhreOUSXZBCd9vO0FCdAi9GvvOLxUL9yzgcO4heiZdSbfE7lrH\nEcKrpBgLcRms418tXco02r+XMgF8uiGVEqebfp2SMRp840fC5vRNfH3oK6qH1+Dh5v57BKUQF8s3\n3nlC+JGSdesoXroUc5s2hNx0k9ZxysRW4uSLjalEh5q4oWV1reMApcciztwyHZPexPC2Iwgx+vcv\nO0JcDCnGQlyC0qVMLwP+v5QJ4OstaeQXO7mjfU2CzdpvouFSXUzfPJU8ex4DmjxA7ejaWkcSolxI\nMRbiEhR++hmO3bsJ6dMHc4sWWscpE4fTzSfrUggxG7itnW8ck/jFgc/ZlbmT9gkduK72DVrHEaLc\nSDEW4iKdu5QpaqT/nsr0h+W7TpGRV8L/WtUgKtSsdRz2Z+3jk30fERsSx6BWQ/z+qoMQl0KKsRAX\nKX/WbNwZGYQ/8TiGhASt45SJ2116IIRBr6NvJ+2PSSx0FDJt8xRUVWVYm6eJMEdoHUmIciXFWIiL\n4ExJ+f+lTI/6/+ze1QcyOJZp45qmCVSN0n6C1Nwdb3K68DR9LHfQJK6p1nGEKHdSjIW4CNZXAmcp\n0x/HJALc4wNbX/52fAW/HV9B/UoW7mrQV+s4QmhCirEQF1Cydh3FS5edPZXJv5cyAexIzWXX8Vy6\nWCpTu0q4pllO29J56+x2l8PaDMeoN2qaRwitSDEW4jxUlwvri2OBwFjKBL5zTKLL7WLq5ikUOYt4\npPmjJIT79314IcpCirEQ51H4yaLSU5nuuN3vT2UCOHQ6nzUHMmiWFE3zpEqaZlmsLELJ3s8VNbrR\nI7GnplmE0JoUYyH+gzsvj7xJk9GFhhL5rP8vZQLfOSZxb+YePtu/mCqhVXi0xeMBccVBiLKQYizE\nf8if+TrurCwiBj3p96cyAZzKLeKn3enUqhxG53qVNctRYC9g2uYpAAxrM5wwU5hmWYTwFVKMhfgX\nziNHKXhvHobERMIffkjrOB7xydoUXG6Ve7rUQq/XZiSqqipvbp9DRlEGdzS4k4axjTTJIYSvkWIs\nxL+wjh8PDgdRo0ehCw7WOk6ZWQvtfLP1BFUig7m6iXYTpVak/srqE6toENOQOyx3aZZDCF8jxViI\nvyletZri5T9ibt+O4Ouv0zqOR3y6IZVih4u+HWtiMmrztj9VcJK5O98i1BjKsDbDMei1P5hCCF8h\nxViIc6hOJ9axY0GnI+rllwJiYpGtxMlnG44RFWrif61raJLB6XYydfNkip1FPNbiCaqGVdUkhxC+\nSoqxEOewffQxzv0KoXfdiblJE63jeMRXm9PIK3JyR/skQoO02VRj8f5POJhzkO6JPbgisZsmGYTw\nZVKMhTjLbbWSP3kKuvDwgFnKZD97TGKo2UCfdkmaZNiXtY/Plc+oElqVR5o/pkkGIXydFGMhzsqb\nPgN3Tg4RgwdhqKzd0h9PWrr9BJn5JdzSJlGTYxILHYXM2DIVFZWhrZ8i1BRa7hmE8AdSjIUAHIcO\nY3t/PoaaSYQPfFDrOB7hdLlZuPooJoOOvp2SNcnw3q53Sbelc2v922gcFxiX/YXwBinGQgDWl8eB\n00nUC6PRBQVpHccjftmTzomcIm5oWZ24iPL/N204uZ6fj/1Iraja9G3Yr9z7F8KfSDEWFV7xb79R\n8ssvmDt1Irh3b63jeITbrfLBqqPodXBP5/Lf+jK3OIc522Zh0psY1uZpTHpTuWcQwp9IMRYVmup0\nYn1pHOj1RI8NjFOZANYczODwmQKubJJA9ZjyvU+rqiqztr6O1W7lvsb3kxRZs1z7F8IfSTEWFZrt\ng4U4DxwgtG9fTI0DY2tGVVVZsPIIAP27lv+oeHnKD2w+vYnmlVtwfZ0by71/IfyRFGNRYbkyM8mb\nPAVdVBSRzz6jdRyP2ZqSw+40K10tlalbNaJc+z5ZcIJ5u94lzBTG4NZD0evkR4wQF0PeKaLCyntt\nAmpeHpHPDMcQG6t1HI/5YFXpqPi+rrXLtV+X28X0zdMocZXwWIsniAuJK9f+hfBn592Ox2Kx6IE3\ngGZACTBQUZTD//K6t4EsRVGe80pKITzMvm0bhYsWY2zYkLB779E6jsfsP2llw+EsWteKoUlidLn2\n/ZmymAM5Ct0Su9O1xhXl2rcQ/u5CI+ObAbOiKJ2AkcDUv7/AYrE8AjQBVM/HE8LzVLeb3FGjAYge\n/zI6ozZbRHrDglVHgfK/V6xkKyxWFhEXUpmHmz1arn0LEQguVIw7Az8AKIqyAWhz7pMWi6UT0A6Y\nCwTGNFQR8AoXLcaxYycht9xMUIcOWsfxmJSMAn7bd5qG1SJpV7v8LrsXO4uZsXkqqqoypPVThJvD\ny61vIQLFhYpxJJB3zmPX2UvXWCyWBGAM8CRSiIWfcOfmkvfaBHRhYUSNHqV1HI9auPooqgr9u9Yu\n1yVa83fP46TtJP+rezPNKjcrt36FCCQXKsZ5wLnTMfWKorjP/r0PEAcsBZ4F7rZYLP09H1EIz8mb\nMhV3djYRTw3FEB+vdRyPSc8t4oedp6gZF0a3BlXKrd+tp7ew7OhSakbWpF+je8utXyECzYVulq0B\nbgQ+s1gsHYCdfzyhKMosYBaAxWK5D2igKMoH3goqRFk59uzFtuADjHXqEP7gA1rH8aiP1qbgcqv0\n71oLvb58RsUF9gJmb30dg87A0NbDMBvK/yAKIQLFhYrxEuAqi8Wy5uzjARaLpS8QrijKO397rUzg\nEj5LVVVyR48Gt5uocS+hMwdO4cguKOGbLWnERwVzTdOEcuv33Z1vk1Wcxd0N+1E7uk659StEIDpv\nMVYURQX+fgDpgX953QJPhhLC04qWfIV94yaCr+1NcLfAOtx+8fpUSpxu+nVOxmgon60D1p9cx4rj\nv1I3uh631b+9XPoUIpDJph8i4LkLCrCOHw/BQUS9OEbrOB5VUOzg842pVAozc2OrGuXSp7XEyhvb\n52DSmxjS+imM+sBZGiaEVqQYi4CXP2Mm7tNniHjySYyJiVrH8agvNx3HVuLkrg41CTYZvN6fqqq8\ntf0NrCW53NPoXpIik7zepxAVgRRjEdAchw5R8M67GBITiXj0Ea3jeFSx3cUn644RFmTktnbl80vG\nqhMrWXtyDY1iG3Fj3f+VS59CVARSjEXAUlUV6wtjwOkk6qUX0YWEaB3Jo77ekkaOzU6fdkmEB3v/\nvODs4mzmbn+TIEMQg1s9hUHn/ZG4EBWFFGMRsIq++ZaSlasI6tGd4Kuv1jqOR5U4XHy45ighZgN9\nO3r/vGBVVZmzdRYFjgIGNHmQhPDym7UtREUgxVgEJHdeHtaxL0FwENHjx5XrjlTl4bttJ8jIL+HW\nNolEh3l/mdYvx35i8+lNtKjSkt61rvV6f0JUNFKMRUDKmzQZ95kzRA4ejDE5Wes4HuVwuvlg9VGC\njHru7pzs9f7OFJ7h3V3vEGoM5cmWgwPuFxshfIEUYxFw7Dt2YJu/oHSnrQCbtAWwdMdJTluLublN\nDWLDg7zal1t1M2vrDIqcRTzU7BEqh1b2an9CVFRSjEVAUV0ucp99DlSV6NdeRRfk3WJV3pwuNx+s\nOoLJoKNfZ+8fk7jsyPfszNhJu/j29Ejq6fX+hKiopBiLgGJb8AGOXbsIue02gjp30jqOx/246xQn\ncoq4sVUNqkQGe7WvkwUnmL9nPhHmSB5v+aRcnhbCi6QYi4DhSk8nb+IkdFFRRI0ZrXUcj3O5Veav\nPIJBr+PeLt4dFbtUFzO2TMfuKuHR5o9RKbiSV/sToqKTYiwChvWll1ELCoh6/jkMcXFax/G4X/ek\nk5pVyPUtqpEQ7d01018fXIKSvZ8u1bvSpUZXr/YlhJBiLAJE8W+/UfTNt5hatSL07r5ax/E4t1vl\n/bOj4vu61vZqX8fyUvho34dEB0XzSPO/nxMjhPAGKcbC76lFReSOGg0GA5UmvIZOH3jf1r/tP82R\nMwVc0zSB6jGhXuvH6XYyY/N0nG4nT7QcRGRQpNf6EkL8v8D7qSUqnPzZc3ClHCN84IOYGjfSOo7H\nqarK/N+PoNPBfVd4d1T8mbKYI9bD9Eq6knYJ7b3alxDi/0kxFn7NcegQ+XPewJCQQMTTw7SO4xWr\nD2RwID2fKxvHUzMuzGv9HMo5xGfKp8SFVObBZg95rR8hxD9JMRZ+S1VVcp8bBQ4HUeNfRh/mvUKl\nFVVVeWfFIXQ6GNCtjtf6sbvszNwyDZfqYlCrIYSZAu9rKYQvk2Is/FbRF19iX7uW4KuuJPiaa7SO\n4xW/7TvDgVOlo+LaVcK91s/H+z4kNT+Va2tdT4sqLbzWjxDi30kxFn7JlZlJ7otj0YWEEDXu5YDc\nkMLtVnl3xSH0OhjYo67X+tmbuYevDi4hISyB+5sM8Fo/Qoj/JsVY+CXri2NRc3OJfHYExsREreN4\nxS970zl8poDezap57V5xkbOImVuno0PHkNbDCDZ6d1cvIcS/k2Is/E7xz79Q9NXXmFq2IOyBwBzJ\nudwq7644jEGv44Hu3rtXPH/3PNJt6dxc71Yaxjb0Wj9CiPOTYiz8iruggNznngejkUqTJ6EzGLSO\n5BU/7jrFsUwb17eoRg0vrSveenoLPxxdRs3ImtzdsJ9X+hBCXBwpxsKv5E2YiOvkSSKefAJTw8Ac\nyTldbt777RBGg85rM6gL7AXM3vo6Bp2Boa2HYTKYvNKPEOLiSDEWfqNk0+bSc4rr1iVi8CCt43jN\n0u0nScsu4qZWNby2B/U7O+eSVZzFXQ36Ujvae5fBhRAXR4qx8AtqSQm5z4woPad4yqSAO6f4DyUO\nF/N+P4zZqOd+L+1Bve7EWn47voJ6lepxW/3bvdKHEOLSSDEWfiF/1mycBw8Sdl9/gtq21TqO13yx\n6Tjp1mL6tEuiSpTnZzbnluTy5vY5mPVmhrYehkEfmPfchfA3UoyFz3Ps20f+7DkYEhKIfG6k1nG8\nJr/IwfyVRwgPNnJfV8+fV6yqKm9sm43VbuXexvdRIyIwl4QJ4Y+kGAufpjoc5AwdBg4H0RNeQx8R\noXUkr/lwzVHyihz071KLqFCzx9tfcfxXNpxaT5O4JtxQ50aPty+EuHxSjIVPy589B8fu3YTeeQfB\nV/bSOo7XnMkrZtH6Y1SODOKODjU93n5GYQbv7nybYGMIg1sNRa+Tt74QvkTekcJn2XfvIX/GTAwJ\nCUS9OEbrOF717opDlDjcPNS9LsEmz97HVVWV2dtex+aw8WDTgVQNi/do+0KIspNiLHySareTM/Qp\ncDqJnjIJfVSU1pG85mhGAd9tO0Fy5TCua1HN4+0vPfo9289so3XV1lxV82qPty+EKDspxsIn5b8+\nC+e+fYTe3Zfg7t21juNVb/18ELcKj19ZH6PBs2/J1LxjzN81jwhzJE+0HByQB2oIEQikGAufY9+1\ni/zXZ2GoVo2oMS9oHcertqZk8/v+MzRLiqarpbJH27a77EzdNBm7286TLQcRGxLr0faFEJ4jxVj4\nFLWkpPTytMtF9NQpAT172ulyM23pPgCGXGPx+Kh14Z4FpOSlcE1ybzpU6+jRtoUQniXFWPiUvOkz\ncO5XCLv3HoKv6Kp1HK/6eksah04XcH2LajSuEe3Rtred3so3h7+mengNHmg60KNtCyE8T4qx8Bkl\nmzZRMOcNDImJRI4epXUcr7IW2pn76yFCgww8fmV9z7ZdYmXmlukYdUaebjtczigWwg9IMRY+wZ2X\nR86gIQBUen0G+vBwjRN51zsrDpNX5ODBbnWIjfDcPtuqqjJ76+vklOTQr9E91Imu67G2hRDeYzzf\nkxaLRQ+8ATQDSoCBiqIcPuf5vsAQwAnsAh5XFEX1XlwRqHJHvYDr+HEihgwmqF07reN41eHT+SzZ\nfJyk2FDuaO/ZDT6Wp/zAxvQNNI1rxs31bvVo20II77nQyPhmwKwoSidgJDD1jycsFksIMA7orihK\nFyAKuMFbQUXgKlyyhKIvv8TUsgURTw3VOo5XqarK9GX7cblVhvZugMnouYtTafnHeW/Xu4Sbwhna\nZpjssiWEH7nQu7Uz8AOAoigbgDbnPFcMdFQUpfjsYyNQ5PGEIqA5jx8n97lR6EJDiZn1OjpTYB9y\nv2LvaTYfzaZTvTg61ffcUiaHy8HUTVOwu0p4ouUg4kLiPNa2EML7znuZGogE8s557LJYLHpFUdxn\nL0dnAFgslkFAmKIoP3sppwhAqstFzuAhqPn5RE+bgrGW508q8iX5RQ6mLt2H2ahn6LUNPNr2wr0L\nOGI9zJU1r6JT9c4ebVsI4X0XKsZ5wLkLPfWKorj/eHD2nvIkoC5wm+fjiUBWMHsO9o2bCL7+ekLv\nuEPrOF43+6cDZBXYeaxXPZJiwzzW7oaT6/n60FdUD6/BwGYPe6xdIUT5udBl6jXAdQAWi6UDsPNv\nz88FgoBbzrlcLcQF2bduI2/qNPTx8VSa+FrAb9O45Wg2X29Jo27VcPp1TvZYu6dt6czcOh2zIYgR\n7UYSYgzxWNtCiPJzoZHxEuAqi8Wy5uzjAWdnUIcDm4EHgJXArxaLBWCmoihfeSusCAyu7ByyH3sc\n3G5iZs5AX6mS1pG8qtjhYsK3e9Dr4LmbGnts/2mH28HkTROxOWwMajmY5Khkj7QrhCh/5y3GZ+8L\nP/a3Dx845++ePetNBDzV7SZnyFBcaWlEDHuKoC6Bf3/z/d+PcDyrkLs61vToTlvzd8/jYM5BeiT2\npFfNqzzWrhCi/MnaB1GuCmbPoeTXXwnqdgURQ4doHcfrDqbn8eGao8RHB/NwD89twLHuxFq+O/wt\niRFJPNri8YC/zC9EoJNiLMpN8arV5E2egiEhgUqzZ6EzBPaFFbvTzbglu3G5VZ69oRGhQRe6K3Rx\nThWcZNa2mQSdvU8s210K4f+kGIty4Tp1ipwnB4FeT8zctzDExGgdyeve+uUgB9LzubFVdTrW88ya\n4kJHIa+uH4/NYeOxFk+QFJnkkXaFENqSYiy8TnU4yH7sCdyZmUSNeQFz61ZaR/K6DYcz+XhtComx\noTzV2zNrilVV5fWtM0jNT+WGOjfSI6mnR9oVQmhPirHwurzXJmDftImQG28g7IEBWsfxulybnXFL\ndmPQ63j5tmYeuzz92YFPWXdyLU3imjKgyYMeaVMI4RukGAuvKvzmWwrmvo2xTh2ip0wO+IlGqqry\n6jd7yMwv4ZGedWlYPcoj7W46tZGP935I5ZDKjGg3EqPeMwVeCOEbpBgLr7Hv3EnOU0+hCw8n5t23\nA/5YRICvNqexcv8ZWteK4Z7OntneMy0/jWmbp2DSm3iuwyiigjxT4IUQvkOKsfAK1+nTZA14EErs\nxMyZjal+fa0jed3+k3nM+GE/kSFGXrylKXp92a8CFNgLeHX9eAqdhTzRapCcTyxEgJJiLDxOLSoi\n68GHcKenE/n8cwRf2UvrSF6XY7MzctE27C43L9zSlCpRZV9u5HA5eG3DeE4UpHFz3VvpntjDA0mF\nEL5IirHwKNXtJnvwUBzbthFy222EP/ao1pG8zuly8/yn20m3FvNQj7p0tVQpc5tu1c3rW2ewO3M3\nHat14r4m95c9qBDCZ0kxFh6VN248xUuXYu7YkUqTJwb8hC2AmcsVtqXk0KNRVQZcUdsjbX6090NW\npv2OJaYBT7V5Gr1O3qpCBDJ5hwuPKXhvHgVvv4Oxfn1i330bXVCQ1pG87rttJ/hsQyp1qoTzws1N\nPPLLx/KjP/D5gU9JCEtgdIcXCDIE/tdRiIpOirHwiMKvvsL64lj0VaoQu3AB+mjPHYjgq7Yfy2Hi\nt3uIDDEysW9Lj6wn3pK+mbd2vEGEOZIXO71EpMycFqJCkGIsyqzop5/JGfIUuogI4j5ciLFGDa0j\ned3B9HyGf7wVtwrjbm9OjZjQMre5O3MXEza+hkFnYFSHF0gIr+aBpEIIfyDFWJRJybp1ZD/6KDqj\nkdgP5mNq3EjrSF53IruQoQs3U1DsZMwtTWhfJ67Mbe7P2se4tS/hdrsY2f55GsY29EBSIYS/kG18\nxGUr2bCBrP73g8tNzPx5BLVtq3Ukr8vKL2HIws1kFdgZdm0DrmlW9tHr4dxDvLxuLHa3nRFtR9Im\nPvC/jkKIv5KRsbgsJevXk3VPf1S7nZi33iC4e3etI3ldfpGDoR9uIS27iAe61eaODjXL3OaxvBRe\nXP0ChY5ChrYeRsfqnTyQVAjhb6QYi0tWsnZdaSF2OIh5+y1CevfWOpLXWQvtDFm4hYPp+dzSJpGH\nepR9J6zjeccZs3o0+Y58nmw1mG6J3cseVAjhl6QYi0tStHw5mffci+p0lhbia67ROpLXZRWU8Pj8\nTew9YeW6FtUYfn3DMi9hOpCt8NyqZ8ktyeWR5o9xZc2rPJRWCOGP5J6xuGi2RYvIfeZZdMHBxLz/\nHsHdumkdyetOW4sYtGAzqVmF9GmXyLBrG5Z5z+kdZ7bz6vrx2F12nmw5mKuSr/ZQWiGEv5JiLC5I\nVVXyZ75O/uQp6KKjiVv4AeZWLbWO5XVp2YU8uWAT6bnF3NulFo9fWa/MI+J1J9YyZfMkAEa0H0nH\nanKPWAghxVhcgFpcTM7wZyha8hWG6tWJ/Wghpnr1tI7ldTtTc3h20XZybHYe6VmX+6+oXeZC/GPK\nct7cNgezMYhRHUbTrHJzD6UVQvg7KcbiP7nS08ka+DCObdswt25NzHvvYKhcWetYXvfdthNM/HYP\nbhWGX9+QPu2SytSeS3WxcM8Clhz8kkhzJGM6vUS9SoH/C40Q4uJJMRb/qnjVanKeHIQ7M5OQW28t\nPfQhuOzHAvoyl1tlzk8H+HhtChHBRl65owXt6sSWqc18ez5TNk1i+5ltVAuvzqgOL1AjIvB3KBNC\nXBopxuIvVJeL/NdnkT91GhiNRL38EmEPDAj405eshXbGfrmLdQczqRkXxuS+LUmKCytTmynWFF7b\nMJ50WzptqrZlWNvhhJnK1qYQIjBJMRZ/ch45Ss7Qp7Bv2YKhenVi3nqzQkzU2ng4i3FLdpGRX0KH\nurGM69OciBBTmdpcc2I1r2+ZQbGrmNstd3J3w35yDKIQ4j9JMRaoLhe2DxaS98qrqEVFhNx0I1Gv\nvIIhppLW0bzK7nQz95eDfLQ2BYNex+NX1qNf51oYyrB0qdhZzLxd77I85QeCDcGMaDeSztW7eDC1\nECIQSTGu4Ow7d5L73PM4tu9AFx1NpalTCP3fTVrH8rqD6fmMW7KLA+n5JMaG8vJtzWhYvWzHFSrZ\nCjO3TOdEQRrJkck83XYESZFlm/wlhKgYpBhXUK4zZ8ibOp3Cjz4CVSXk1luIemE0hipVtI7mVbYS\nJ++uOMSnG1JxuVVualWdob0blOks4hJXCR/v/YhvDn2FGzc31rmJ/o3vx2wwezC5ECKQSTGuYNz5\n+RS8NZeCuW+jFhVhrFeP6FfGE9Q5sDefUFWVX/eeZsay/WTkl1AjJoRh1zWkU72yLdXadGoj7+yc\ny+nC08SHJTCo1WCaxDX1UGohREUhxbiCcGVnY3tvHgXvz0e1WtFXqULUi2MIvetOdKayTVbydTtT\nc5j76yG2HM3GbNTzYPc69O9SiyCT4bLbPJ53nAV75rEpfRMGnYGb695K34Z3E2wM7OVfQgjvkGIc\n4ByKgm3BBxR++hlqURH6mBginh1B2MAH0YeGah3Pq/aftDL310OsO5gJQKd6cQy9tgFJsZe/vCij\n8AyfKZ/y07EfcatumsQ14ZHmj5EUWfbjFIUQFZcU4wDkttkoXroM2+LF2NetB8BQrRrhz40k9O6+\n6ENCNE7oPaqqsjUlh0XrUlilZADQulYMD/esS/Oky58dnpqXypKDX/D78d9wqS5qhNegf5MBtItv\nF/BrsIUQ3ifFOEC4i4oo+f13ir5fSvGyH1CLigAI6tqVsPv7E3zlleiMgfu/u8juZPnOU3y2IZXD\nZwoAaJoYzSM969Km9uXtoqWqKvuz97Pk4BdsOFX6S01iRBK31r+NbjW6Y9Bf/mVuIYQ4V+D+dA5w\nqqriPHyEktWrS//89vufBdiQXJPQW28l9NZbMNaqpXFS73G7Vban5vDjzlP8sied/GInBr2Oq5rE\nc3v7JJomRl/WqDWrKJMVqStYkfoLaQVpANSvZKFP/dtpm9BONu8QQnicFGM/oaoqrtRUStZvoGTN\nWkrWrMGdnv7n88Y6dQi+tjchva/B1KJFwF46dbrc7D1h5bd9Z/hp9yky8koAiA0380C32tzSJpHK\nkZc+iSqnOIetp7ewMu13dp7ZgRs3Jr2JLtW70rvWtTSJaxqwX1MhhPbOW4wtFoseeANoBpQAAxVF\nOXzO8zcCLwBOYJ6iKO96MWuFobrduI4fx7FzF/Zdu87+dydqrvXP1+hjYwm56UaCunQhqHMnjMnJ\n2gX2IlVVOZVbzKYjWWw4lMmmI1nkFzsBiAg2cmOr6lzTNIGWyTGXtHOW0+3kUM5BtpzewpbTmzmc\ne+jP5ywxDeiZ1Isu1bsSbg73+L9JCCH+7kIj45sBs6IonSwWS3tg6tmPYbFYTMA0oA1QCKyxWCzf\nKIpyxpuBA4Wqqqi5uThPnMB5+DDOw0dwHjpU+t/Dh/+85PwHQ3Iy5iuuwNyqFUFdOmO0WNDpA+9y\naa7NzuEzBexJy2VPmpXdablkFdj/fD4hOoQrmyTQqX4c7evEYTZe+GvgVt2cKTzDwZwDHMhWOJBz\ngCO5h7G7S9s16ow0q9yc1lVb0za+PdUjqnvt3yeEEP/mQsW4M/ADgKIoGywWS5tznmsIHFIUxQpg\nsVhWA1cAn3sjqD9xFxbizsjAnZmFKzMDd0YmrowMXOmncZ1Iw3XiJK4TJ1Bttn98ri44GGPt2hjr\n1VtXYiYAAAXDSURBVMXUtCnmpk0xNW2CPqpsWzX6ClVVybHZSbcWk55bxKncYk7mFHI0o4CjGTZy\nbPa/vL5yRBA9GlWlRVIlOtaLIzE29F8vFxc6CskuziKrKIus4ixOFZziREEaJ/LTOGk7hd1V8udr\n9To9NSOTscRYaFWlNU0rNyPUFNjLvIQQvu1CxTgS+L/27ifEjTKM4/g3m+3G7TbdzdI/290uBbf6\niCB41IO14B8UFPHgQXqpeBAKYq0X/4An0YOoIC2iovgPFAoqFQ9WtAgWqm1B2otPRaRV2moVbZLd\nJpPsjId3um5tk61tdqeNvw+Efd+ZN8mTyZIn82bmmfKs/rSZ9bh7nK47OWtdBZi3jBFXKiT1OsQx\nJEm4xQlJkkAye1loJ3HaP2tdmAYOjXTZdEwS1UmiiKQeQRTN9KlHYXkUheePIuJqlbhcIalWwt9K\nhbhSJilXiKtViKK2ryU3OEjvmjXkx0bJj42F5Lt2gt6JCfKjo/Oyx1uLppmKmulmS0gIiXFmMyVJ\nWJ5AAv+0Z8aceZ/GdEy9EVNvTlNrTFOuVZlq1Kg3p6k3mtSbTSq1iPKpBuVaRKXWoHIqolKPiOMY\ncoT3gARyCblcwvJiL2vGF7FyaBGrSr2MDPXRX6gRxUeoNQ/xxbEqk0eqTDYmqTbC38nGJOX6Saaa\nU+d83YV8gdVLVjNWHGNiaC1Xl65mYmitinOIyCVlrmRcBoqz+qcTMYREPHtdEfizzWPlAY7POujo\nfNX37uOvRzaHxHkJyvX3w5IBegYHyY2O0rO0SE+pRM/wMD2lEvnhYXLDJfLLlpEfGSE3MEDLdH30\naMfj++1kjYff2UfUnJ/t11f8maXjX7Yf1AsUYaDYesgp4PBUuHEem6GQ76O/dzFL+oqsvmKcoUKJ\nUqHEUGGIZYuXMzIwQqlQOnNPuga/H//9PF6ViMjFm5Xz2p4LOVcy3g3cDWw3sxuAA7PWfQ9cZWYl\nYJIwRf18m8daBbBhw4Y5nrKF/sKF3W+hTE2G24msA8mG0puISFurgB9brZwrGX8E3GZmu9P+A2Z2\nP7DE3V83sy3AZ0AP8Ia7H2vzWHuBm4BjwPT5Ri8iInIZyxMS8d52g3JJkixMOCIiInJO3XdujIiI\nyGVGyVhERCRjSsYiIiIZUzIWERHJWCYXijCza4A9wAp3b18hQ/4TMxsE3iOc990HbHH3PdlG1T3m\nqtcuFy8ttfsmsAYoAM+4+yfZRtWdzGwFsB+4xd0PZR1PtzGzJwinBy8Ctrr7263GLviesZktJdS4\nri30c/9PPAp87u7rgY3Atkyj6T4z9dqBxwn/y9JZG4AT7r4OuAPYmnE8XSn90vMqoU6EdJiZrQdu\nTD8r1gNXthu/oMnYzHKEN/8JQsEl6byXgNfS9iK0nTvtjHrthAulSGdtB55O2z2Eq8JJ5z0PvEKo\n/SCddztw0Mw+Bj4BdrQbPG/T1Gb2ILD5X4sPAx+4+wEzg7RCsVyYFtt4o7vvN7MR4F3gkYWPrKu1\nq9cuHeDukwBmViQk5qeyjaj7mNlGwuzDznQqVZ/FnbccGAfuIuwV7wCuaTV4QYt+mNkPwC9p9wbg\nm3Q6VTrIzK4D3gcec/fPso6nm5jZC8Aed9+e9n929/GMw+o6ZjYOfAhsc/e3Mg6n65jZV8xcqYXr\nAQfucfdfMw2si5jZc4QvPC+m/e+AW939nNWDF/QALne/6nTbzH4i7MZLB5nZtYS9ifvc/WDW8XSh\ndvXapQPMbCWwE9jk7ruyjqcbufvNp9tmtgt4SIm4474mzEy+aGajwADwR6vBmRxNnVIdzvnxLOEo\n6pfTnwL+cvd7sw2pq5xVrz3LYLrUk4TLsT5tZqd/O77T3XXQp1w23P1TM1tnZt8Sjn3Y5O4t855q\nU4uIiGRMRT9EREQypmQsIiKSMSVjERGRjCkZi4iIZEzJWEREJGNKxiIiIhlTMhYREcmYkrGIiEjG\n/gYna/HIl5rktgAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x110bc1850>"
]
}
],
"prompt_number": 19
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Multivariate density estimation with `kdeplot`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can also use the kernel density method with multidimensional data. For visualization, we are mostly concerned with plotting joint bivariate distributions. As with the hexbin plot, we will color-encode the density estimate over a 2D space. The `kdeplot` function tries to infer whether it should draw a univariate or bivariate plot based on the type and shape of the `data` argument. If using a 2d array or a DataFrame, the array is assumed to be shaped (`n_units`, `n_variables`)."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data = np.random.multivariate_normal([0, 0], [[1, 2], [2, 20]], size=1000)\n",
"data = pd.DataFrame(data, columns=[\"X\", \"Y\"])\n",
"mpl.rc(\"figure\", figsize=(6, 6))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.kdeplot(data);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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w3ezbtw8vLy/KlSvHmDFjsvwfNyU1hRlL57J66wYKmFmwbt7yTIO5JEl4eu1k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HaLJQc3GrVPWpR2LMaSzt9QzVnh4HVfuv8+lg3nfNI8D/0v9Rj9Nn6Lf/hN3Ms3ZVSDXi8F7aFL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\nSKALIYSZkEAXQggzIYEuhBBm4n9r+Pp0Y8d6gAAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x110b90950>"
]
}
],
"prompt_number": 21
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can also pass in two vectors as the first positional arguments, which will also draw a bivariate density."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.kdeplot(data.X, data.Y, shade=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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ddZK+7e6fkSR3/77WztL2KTN7RtaWATUxgQwAoDIAABAGAAARBgAAEQYAABEG\nAAARBgAAEQYAABEGAABJ/w/jZETJVwScSQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1119ea210>"
]
}
],
"prompt_number": 22
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As in the univariate case, you can also set the kernel bandwidth and choose different points at which to clip the data or cut the estimate. However, only the gaussian kernel is availible for the multidimensional kde.\n",
"\n",
"When specifying the colormap, the multivariate `kdeplot` accepts a special token where colormaps that end with `_d` are plotted in a way that maintains the overall color palette but that uses darker colors at one extreme so the contour lines are fully visible."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.kdeplot(data, bw=\"silverman\", gridsize=50, cut=2, clip=(-11, 11), cmap=\"BuGn_d\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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ep8+ogdy8J/tCk8D3jyDoAoVOSkoKU6dOJTk5mTlz5lC9uuyJQfJ4FBbK5Pmu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\nxrQiY206y+3GmFt01DUZXrMdLcrU5lV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FF/cuJsi/ed/BA9feTsbRvXyxdjmTh4yld5J3\nCXNv0aUdEfrFjE5Cvwhw+vRpvvzyS3755RfMZjORkZHMmTOH8ePH079//1Y7Pb2BIAi8+PYrVNZU\ncd8td9I/ra/H9W8t/xitQc+TN91BkJtxcYcKT1KlruWqoVPwa9H1uTbb3hI/o1cjUZmsFt7YtxwJ\nEh4ddl2DRa7JaubNAz9RoqlmeGwvbug9iWh5qMfnqzVoyK0rJ6+uguO1xRitdkkhOSSaoTGpDIjs\n1uFt/2Pje3OouoCDVfluCb13RCJJITHsKz9Fla7O7eeQ+fjy7OhbuHfD67x7cCVdFJEMi3Odl5oY\nGsuiS+9h/q9v8OTad/hszkIim1xzZI90bhp7JcsyVvHams/499X3NTtfHhDI07c8zANvPM2iz15n\n6TNvIRPp0G0vnBF6W0sX4eLU0DsJ/QJGbm4uH3/8Mb///juCINC1a1duvvlmLr/8cvz9vR8r5g1+\n+O1nNu/cxpD+g7jl2r95XLvn+EHW7dlM3+ReXDV+utt1647a5ZZpA8TlFn9fPyZ3H9rws7X5uymq\nr+TKHmPpG5nU8PPl2dso0VRzSbdB3NpPXNNXG3Xk1lWQW1dObl05yiae5KF+csZ2SWNITHeiAkM8\nfrYzQVdFJFEBwRyvLcJktYiag0kkEmYkD+PDI2v44/RBbug9ye31YoLCeW7sbTyx5UOe37GUty55\nSHQe6uhuA7h35LW8t3sFz6x/n3eufKLZGL97LrmBffmZ/HpwM+N6DWFKv+bDo0f0Hczs8TP4adta\nvli7gjsuv7H9v4QWcGroZW0g9E4NvRMXFGw2G6+88gorVqxAEATS0tKYN28eU6ZMaWi66EgcyDzM\nax+9TWhIKM8teNrjPVT1dfzn09fw8fHhnzfdj4+H2u7dOYcJCVQwOLl5tK/Uqymqq2Bs0kCCmszY\n3F12AoAbezfWquvNRjYVHSEyIIQbRcjPJtj4IWcX+ysbZ1AG+vrRNyKR1NBYUkPjiJGHeixb7ChI\nJBK6BIVTbajHYDWJEjrAgKhkAKp0rQ9w6B/dnX+OvJEXdn7Jczs+551LHm72O3Pi5sGXcawyjy35\nB/ju6Ab+NrBxo5X5+vL8nIe48d0FvLP+K8anDXMpH31o7p1sObSTZet/YPaEGUSGnLkMBRAZbu9L\nqFXVen2O2ZGg7Yg3z/MNnVUuFyDeeustli9fTkpKCq+//jrLli3j0ksvPStkfizrBPOfexJBEHj5\nyf8QFy0+Bg7skdPzS9+kuq6We666mT5J4q6LAKXKSspUVQxJ7usy9DmvthSA1CayhNVmI7M6n3hF\nFFFNJIOdZScwWc1MTkx36fK0CQIrHGQeJw/jsuQhPDhwJs+OmMMtfSYyNr43cUFh54TMndA7xsvJ\nfd2/QZkcgy08TV1qiomJg7gubTLF9VUs2fONqOuiRCLhyYm3Eh4QzIe7f6BQ2XzsXLeoeK4edikl\nygpWHXDtWFUEyrl91o1o9Tpe//ZDr57LG/j6+BIcpECl9n76kF5vNz6Ty70vH71Q0EnoFxiWLVvG\nV199RUpKCv/3f//HhAkTzpqWmJV3igf//Rh6o4EXHn+WYelDPK5fsfkXth3ezbDeA7l5untfF4D9\n+ccAGJrSz+VYvtI+piylCaHn15WhMxtIj25ebbK56AhSiYTxXQc0+7lNEPgpdzcHKu1t+vcMmMaE\nhL4kKCLddneeC2gtRvykvh67Us02e924uwheDLcPmMngmJ7sKD3GN24sBMIDQ3h8ws0YrWZe2PSJ\nSwPTbROvIdDPn082r0Bvch12MWfyLPqnpLFh79Z2TzgSQ1hIaLsIPSCg7SWk5zs6Cf0Cwpo1a3jz\nzTeJiYnh7bffbjD6PxvILczngWcWoNFpWfjov5g6brLn9SUFvPX9x4QqQnjujsdaLYk8UGAn9CEi\nhJ5Xayf01IiuDT87WmWXTAY0IfT8unIK1BUMjkklvIl3iyAIrM7by56KHOKDwrmt35QOT3C2Fzqz\nsdUuU6dJl0zqPaH7SH14atRNRMvDWJq5lr3lJ0XXTUkdztQeIzhakcvK482dGSMVYdw4+nJqNCq+\n2fGr6D2evvURfH18WfzVu2j0ru6P7UFoSCh19WqvtXGDwb7ZeOMEeqGhk9AvEOzatYvnnnsOhULB\n//73vzY3A7UFp0uKuf+Z+ajUdTz1wGNcNlm8E9MJg8nI0x8txmQx8+ytjxAdJm6h64QgCOzPP0ao\nPJju0V1djufVliCVSEgKazQIO1rtIPSoRkLfXGR3FZyUOLDZtX8tOMDO8mzi5GHc0W+qR3njXENv\nMSFvZXNxDoj2awOhg91DfeGYefhKfXhp1zLKNDWi6+aP/TtyWQAf7/0JTQtL3r+PvYLwoBC+zFiF\nUqt2OTc1IYl5l11HpbKa9378rE3P5/a5Q0KxWCxovdwgdDr7uk5C78R5iePHj/P444/j4+PD66+/\n7rV5VntQUl7GvU8/Qo2ylsf/8TCzp1/e6jn/W/4xeaWFzJk0iwmDRrW6/vDpLCrqahiROsAlkhcE\ngbzaEhJCYhq8WwRB4GhVHlGBocQF2ZNoeouJnaUniAwIaUgiCoLA+tOH2V56gujAEO7sN5UgN9Gw\n3mIiW1XO70XH+KXgMBuLT7CrPJejNcXk1lVSpq1DbdKL6tHthcVmxWSztLrBmBySi7caelOkRSTy\n4JBrqDfpeW7H5xgsruZaEfIQbh0yC5VBw9KDzSNxRYCcOybNQWfU8+lm14EZAPNmXk9Kl0RWbP6V\nwznH2vyMLREabK8sqlO7biBicEounYTeifMOZWVlPPLIIxiNRl544QWGDPGsY58JikqLufepR6is\nruKh2+7huiuuafWcX3f8wYrNv5KakMRDc+/06j7f7rSTyNXDXEsMa/Vq1EYt3Zvo5yWaalRGDf2j\nUhryBfvKszFYzUxMHNCgiR+qymdTcSaRAcHc1W8qCr/mGqtNEMhXV/NLwWE+Pr6NtaczOa4sI09d\nRWZtCXsq89lUcpJfC4+wPHcvn5/M4LMT2zlYdRqz7cy9tzWOodCtSS5qkz0CbYvk0hQzu49kVvdR\n5KpK+eq4uNf49enTiAkK57sj61HqmxPp7KFT6RoRyw97N1Cldq0+8ZPJePrWR5BIJCz56v12PWNT\nOAldpfZuRmin5NKJ8xI6nY758+dTW1vLggULmDJlylm716FjR7jziQcpqyznvlvu5OZrW6813rB3\nK89//gbBcgUv3v0vFx9zMRwrzmHT8d30TUhlSLJrc1KB0l7hkhTWKCkV1dv9T1LDGkk+r85epTEo\n2t4uLggCW0tPIEXC7f2mNDPQ0ltM7CrP5fOT21ldcIg8dRVRAQpGx6VyQ48R3N13Ijf1Gs3V3Ycw\nPbE/47r0ZEh0Er3CYjHZrGwry2bpyQwOVBWeEbFnOz5bQpCrhbATVpuNVTk7kdBYvtge3DtoNv4+\nsoZSz5YI8PXj2v5TMFkt7Ctuvkbm68ucETOw2qzsynEdlgGQntqH8ekjOVWcR1FlabufE2hIznpb\nhlhba99kvBnAcqHh4ivUvEAgCALPP/88p06dYs6cOVx/vfhgiDOF2Wzm/775nKUrvgbg8Xse4brL\nr271vM0Hd/Dvj5cQ6O/P24+8IDojtCUEQeCd9csAeHDazaLVOc7BDGnRyQ0/c2rBXRSN2nyJpgYJ\n0EVhJ8ciTQ1lWiX9IhKJDGh0dRQEgdUFhynX1SGT+jAgIoF+EQnEyJs3EAX4yojA1cpAbzFxqPo0\nh6qL2F52iv2VBQyJTmJAZNc2VaEAHKu1T7nvH+X+d/XH6YMUa6qZ2DWd5FD3Lpatwd9XRp/IJA5V\n5qA2agnxd/1swxL6Aj+wv/QEl/Yc2ezYiFR71dC+vKNcMUQ8IT42fThbD+9ix9F9XH/JlaJrvIHT\naVEh987ts7ra7vMeHR3dysoLD50R+nmKtWvXsmHDBtLT03nsscfOyj0Kigq54/H7+ez7ZcRFx/LR\n4re9IvOMo3t56sOX8ZP58dbDz9M3pZdX98vIPsCBguOMTxvKkBRx64CsqkIA0qIaO0HLtPaIrEuT\nyLakvppoeViDV8thx0YwIq557XtOXSXlujqSg6O4s+8EJnft40LmnhDo68fouB7c1nscI2JSsAoC\nGeU5fH4ygyKN980wBouJHFU5XYLCm204TaE2avnxVAZyX3/m9nI/MMRbOEs8nQnllkiLTiLIL5B9\nJa5RfPeYRCIUoezNy3RbfTKm/zAAdmTuPaPndA6lDvbSvrmqqorAwECCgtx7CV2o6CT08xDl5eUs\nXryYwMBAFi1a1OEdcYIgsGLNT9z0yF2cyMniiqkz+ertTxjYp3+r5+45fpB/vvcCPj4+vPHgc6T3\n8Ozp4oTFauWd9V8hlUi471LxIdEAWdWFKPwCSQhpjL7KW0ToaqOWerOeBEXjvNB8dQU+Eindm0S1\nVsHGzvJcpEgYH98TmYfa79YQ4CtjVFwqt/UZy6jY7hitZraXnvK61C5LWYpVsNEvItHtmu+zt6Gz\nGLmm57g2ea67Q7pDjjpSKU7ovlIfBndJo7iukvL65hUxEomEYSn9qdGoyK8qET0/NiKaHgnJHMg6\nisHoWrfuLeo19gg9KNC7z1xTU3NRRufQSejnHWw2G4sWLUKj0TB//ny6dnUt6zsT1ChrefS5J1n8\n3hsE+Pmz+F+L+PcjT3p0TnTiQPZRFry7CIBX73+WIWkDWjmjEb8e2kx+VTFXDJlM9xjxz6Q16Tmt\nqqBXVFIzOaZMW4NCFkiwn/0LX+wg+AQHwRssJsq0KhKDI5uR9rGaElQmHf0iEwgXkRzaA38fGSNi\nu9M9JJoqQz3lXrTn25/FLrf0ixQn9FxVGVuLj5IYHMUl3QZ1yLP2jkhCJvXhSFWu2zVDE3oDsF8k\nSh/evVF2cYfR/YdhNJvYn+1+TWvQ6DQEBcq96nS2WCzU1tYSFeV5+PeFik5CP8/w/fffs2fPHsaN\nG8fs2bM77Lo2m42f1v3CDffPI2PfLkYOHsY373zGlLETvTr/SO4J5v/vP1itVl665ylG9vW+2kZv\nMvDRxu/xl/lx1+Tr3K47VVOEgEBadKPcIggCZdqaFvq5XUN1EnphfTUCAskhjbYEJquF3RV5yKQ+\njIxJ8fpZvUV6lJ2YD1cXtbrWbLNyUllCRICCOLl4Iu+H7G0A3NxnqosVQnvh7yujd0QSuapStCa9\n6JphCfZBzftLXRuRhnW3v7Ht9UDoYwcMB2DH0fbLLhqtxutpWbW1tQiCcNESemdS9DxCQUFBQwfo\nM88802Et/YUlRbzw1mIOHT9KYEAgC+5+kOsuv8brARcb9m7lhaVvYjKb+O8/nmL8wJGtn+SAIAi8\n8dvnVNcruW3iNUSHuK/wyCy3R5JN9fMagxqT1dJQfw72hCjQILkUqqsASA5uJPRjtaXorWZGxnb3\nav5nW9E1KJwI/yBy6iox26we5Zy8ugpMNgt9IxJF/6ZVOhWZNYX0Ck+gt5sIvr3oHdmNo9V5nFKV\nMCjGtX8hNbIrwX5yjpbnuByLD4+hS1g0h0+LD7gGe7VLoH8A+7PaF6HbbDbq1Gq6xHrXKFdZaa94\n6iT0TvylYbFYWLhwIUajkUWLFnXI/7BWq5Wvf/qeD7/6FKPJxJQxE1lw94PERHmnP1qsVt798TO+\nWv8jcv9AXrrnKSYNdh2k4AmfbvmBn/dvJK1LCreM8/zGsSFnNz4SKSMTG+0ACuvs05a6hTRq41U6\ne71yrGPwRJXeLnt0CWqMfp0Jy34R8W7vJwgChRoVNgRSFOFt2kAlEglx8lBqjVo0ZoNHSSfP8Rl6\nNel8bYotxZkATEpM9/r+3sJZ8hkfJN69K5VIsSG4GJs54S/zQyfi6+KEr6/vGfmjFxSfRqvX0TPF\nu2lF+fn5ACQlJbWy8sJEJ6GfJ1i6dCnHjh1j5syZXHLJJa2f0ApyC/N5/q3FHMs+QURYOM/Nf5pL\nxk3y+vxatYqnP3qZ/VlHSIrrypL7niGlS+uliU2xct/vfLTxe7qERfP6TU8i93dvplSgLCOrupAx\n3dIJb+JJXuAgw5QmPt+VujqCZYEEOlroqw31yKQ+DRq7TRAo1SoJ85OjcDMDVBAEDivLOaW2R/u1\nRj1DIuPb5Lwol9nvr7OYWiH0SqRISApx3UitNhvbio8i9/VnuMiAijOB1WblSFUe8YooYtxMXTJY\nTGhN+mZDL5pCbzIg93P/dxMEAa1BR1Jc+3I9h44dAWBQP+82s7w8e4I3NfXiHFfXSejnAU6ePMlH\nH31ETEwMjz/++BldSxAEvvjhGz5c9ilmi5kZky5lwV0PEBbqfRPGsfws/vn+i1Qqq5k4aDQLb1+A\nwssKBIA6nYbX1nzKuiPbCQkM4s2bnyIq2LN/9rpT9glF03s2tw7IdzQQJYfao1ubYKNGr6abgxwF\nQaBaryYqMKSBjKv19ZhsVnoqxD+zVbCxt7qEIm0dwTJ/fCQS8jVKDFYLo6IT8fVSinJ6sujMru31\nThitZko0NSQoIkXH4R2pzkdp1HBJt0FejctrC04pS9CZDUxOdJ9krdXZu0Qj3JRy6owGYkPde/OY\nLGasVity//Z1bR50EPpgLwk9N9cuy3USeif+kjCZTCxcuBCr1cqzzz5LSEj7J+bYbDaWvP8GP/y2\niqiISJ68fwETR45t0zV+3raOJV+/i8Vq5b6rb+WWGXPbNEx6R/ZBXvz5A6rrlfTr2pOF19xPUpR7\n2QMcHiyndhHo68+ElObJ1gJ1OTKpT4NerjRosAhWoh3JRbVJj9lmJapJbXexVglAgkhUarZZ2VF5\nmkqDlkh/OeNiuiGRSNhZWUSZvp4t5fmMjU0iwIumIacni07EL8WJQnUVNoRm5ZRNsaXITmgTu3a8\n3HKo8hSAqHbuRK1DrooQmdQkCAI6kx65yMAMJ5yGWt6WHLo847EjhIaEktzVOwklNzeXmJgYgoPF\na/kvdHQS+l8c77//Prm5uVx77bWMHj269RPcwGK18Pybi1mzaT09U3rw9qJXGqbBeAOj2cTr337I\nyq2/ESJX8Pxd/2R0/6Gtn+iA1qjnrbVf8PP+P/D18eHeqTdy09gr8fWiFO1YRR4l6iqm9xxFYJME\npk2wUVhXQWJIbIN/uFMvjw60SwTVDh+SpqPjijXihG6wWthWUYDKZCA+MJhR0YkNFSXjYpPYV11C\noVbFxrI8JsQmoWglmRrkjNAtRrdr8tV2Dbt7qOtgEJVBw6GqXJJDYs+oK9QdDlbaE50DPRG6o+xS\nTHIxWsxYbTYCPUguWoOD0N3MjfWE8soKyqsqmDhqnFf5C41GQ0VFBaNGtW4Ad6Gik9D/wti/fz/L\nli0jMTGRhx9+uN3XMZvNPP3KIjbt2Er/tL689dwSQhTeRzCnK0p46sOXyC7Ko1didxbf+wwJ0d7b\n8+7Ly+TFnz+gVFlJz7gkFl7zAD3jvE9arW2QW5pvaOXaWgxWEykhjc/iHMvmHJ5cbagHICrQ/nnt\n+rmKUL9AgpsQkcZsYmtFAVqLiRRFuIteLpVIGB6VgNxXxom6Kv4oy2N8bBIRHhp8GiQXDxF6Xl0F\nEiQkBbvq59tKMrEJAhO7el/P7y2K66s4WHGKlNAuhLvpTAW7GRpARKAroeuMjslAHnIfDRF6QNsl\nlx377UMyhg4Y7NX6i11ugU5C/8tCr9fz3HPPIZFIWLRo0RmN0/r426Vs2rGVYemDefWZ/xLUhmvt\nOnaApz58CY1ey1Xjp7Pg+n8Q4OEL3BTFteW8ufYLtp3ch1Qi4bYJ13DHpDku8yg9oc6gYV32TsID\nghnRtXnXaZbD+ySlSXVIhc4efccE2iWXKmeEHmCP0GsNWkw2Cz2CGglUEAT2VBehtZjoExpNv7AY\n0YhQIpHQPzwWua+M/TWl7K4qZkZCT7fRozMpq7eYRY9bBRvFmhrig8JFB2zsLjuJTOrD6Hjvum09\nQW82crgql33lJ9lfkU1xvb2Us7VE6ylHHX2MwlWeKlXa3y5CAt3XiDuNuULbEECAw2Pn998AGD/S\nu8qpU6fsElInoXfiL4f33nuP0tJSbr31VgYMaH+Edio/l6UrviYuOpbXnv0vci+1TEEQWL7pF974\n7kOkUikLb1vArDHeVdcYTEY+37aSrzJWY7KYGZTUh0dm3EKfhLZ/0T7bv5p6k46HxtyAbwvdenfp\ncQCGxjaSUqFDwkh0RLwNEowjqVdrtLeROyN2gAq9hhqjnvjAYPqHty5tdA+OoNqgo1CrosqgJcYD\noXlCnVGHVbA1PFtTGCwmiuqr6Rke73WdvN5iRGmop9ZQj9LxT41eTWZ1PsdrCrA4nCADff0ZHd+P\nobG9mJYy3O31NEYdv2XvIDoonIFxrvNffzu8FYAJvd1fY9X29QBMGty2XM3W3RlkZh1n8pgJdI3z\nnGNx4tgxu/d6375nvgGer+gk9L8gjh49yrfffku3bt2466672n0dq9XKC/9bgtVq5cn753tN5haL\nhVe//YAft6whIjiMJfc/S3pqn1bPEwSBjcd28da6L6ioqyE6JIKHp9/C1P6j29UEVVRXwYrMq+0r\nkQAAIABJREFUP0gIiWZO/+bWwFablT3lJ4gODCU1rPELf1pdSbi/osHrpEJXR7AsoCFBWWOwGz1F\nNCkjzK131KSHuR9w3RLdg8Mp1Koo0KjcErqA3cfF3SevNWgcz+IavRaoKxAQ6B4qXpvecA9B4O0D\nP/J74X70brR6CRJ6hndlWFwaQ+N60SciyavhGL+c3I7ObODWIbNcNlOj2cS6I9uJCg5nVI+BoueX\nVJWz+/gBBvboS2qC9xKb1WrlvS8+RiqVcu/Nd3h93tGjRwkKCiIlpeM7f88XdBL6Xwwmk4lFixYh\nCALPPvvsGQ26/e6XHzl+6iTTJ05l7DDvEkUqjZp/ffBf9mcdoWfX7rz2wL+Ji2yd6PIqi3jt18/Y\nl5+JzMeXW8fPZt6Eazzqq63h/V0rsNis3Ddqrktjy7GaAupNeiamDmrYLNRGLUqjpsED3WS1oDJq\nm1WQNJBokxmjdWYD/lIfwtpQWhfpL8df6kOVUet2jdOWy91mpjS6PosTeSp7OWaqm2YjJ/aUnWB1\n7g4iA0PoH5VCeEAwEQHBhDf5JyU0jlD/tr1FWG02lmf+jr+PjNl9J7kc33pyH/UGLVcPm+o2sf3z\ntrUAzB4/s033Xrt5A3mn87li6kxSEpO9Oqe+vp6CggKGDx/ulefLhYpOQv+L4dNPPyU/P5+5c+cy\neLB3ySAxlFaU8cGXnxAaEsqCux/06pzymkruf/0piipLmThoNM/d8RjyVpJZFquFjzet4IvtP2G1\n2RjbawiPzpxHYuSZzTQ9Un6KjXn76B+bypTuw1yO73LILaPim3SNOuSWJIdnS6VDboltktCrNWrx\n9/FtqECx2mxoLWai2uheKJFICPcPpFyvwWi14C8S8TqdFiVuYnSxzcUJZ/eopwjdYrPyweFVSCVS\nXp7wD5JDO26ObEbhYUrUVVzZZwKhIs/3y0H7AOnL3XihWywWVmVsIESu4JJh47y+r9ls5qOvP0Pm\nK+Puv93m9XlOuaV//9YdQS9kdBL6XwinTp3is88+IzY2lgceeKDd1xEEgcXvvYHeoOfJ+x4l3Ium\noeq62gYyv3XmXO6dfWur9eUFVSUs/OFtTpbm0SUsmsdm3cG4tDMfgWcwG3kz4xsAHhpzvWiEu6v0\nOAE+fgxuUnKXrbTbuHZ3EJuz4iXGUfFisdlQGfXEyUMarlnvkClC2uHnEu5nJ3SlSU9coKts0hih\ni59f66jAESP0XFUZwX7yZuWWLbEqJ4Pi+iqu7DG2Q8kc4Puj9tF01w2Y6nKsoq6a3blHSE9Mc9tD\nsPXwLmrVSm645CqvJlU5sXLtakoryrnxqrnExXhfqpmZabdH6CT0TvwlYLFYeP7557FarTz11FNn\nZM6/Zdd2duzfzYhBQ5k5eVqr6+t1Gh5842mKKkuZN/M67rtmnsf1giDw494NvLXuC4xmE7MGT2L+\nzHko2lFr3BIqfT0L1rzJ8cp8pvccRbpIMq6kvpqi+krGxPdrJsUcrylEKpHQ2+EpXumocIlxROh1\nJh0CQjMCVZschN4G0nEiwiHRKI1uCN2LCN1HIiWkRWOOyqihxqBmUHSqW7lGbdTy5bH1KGSB3NKv\n9b9xW5BdfZp9JScYltCHHiJmYGsObUUQBC4fMsntNVZutVeozJ7gvdyi0+v45LsvkQcGctt1N7Xp\nmY8etZt/dRJ6J/4S+O677zh+/DgzZ85k7Ni2VQS0xLKV3yGRSHj8Hw97lYz8bM135JYUMnfy5dx7\n9a0e1+pNBl5a9ZGjbV/Bc9c+yOS+3rsreoJSr+aBVa+QW1vMzF5jeGqS+Cv3lqJDAIxuIrfUm3Tk\n1pWREhrX0HxU5ugIdUboNQ1JyMbNUuOoEVf4tp3QQx0+MGqzeDKyISnq5m9QZ9IT6idvGGLtRLmj\n8SlRxNvFie3FR9GY9dyZPqvN+rgn1OjqeHLtOwD8fZArGddq6vh6xy/I/QK4pJ94o9umAzvYffwg\nQ3oN8Gr0INg3v5ffe51aVS133TjPq7fKpuceO3aM+Ph4IiPd2xBcDOgk9L8AysrKeP/99wkNDWXB\nggVndK3q2hqOnMhkUL90khNbryyoUStZvukXYsIieWjunR43gMLqUp789jXyKosYkNiLF6971KOP\nR1tQq1Pz4Ool5NaWMKf/FBaMu0n0WQRBYEPhPvx8fBnfpB1+X8UpbILACEddtSAIFGtqCPWTE+yI\ngGsdFS6RAY2E7qwRl7fDEdDPkXwzO4YYt4TNEaFL3UToFpuFQD/Xtxqjzf5MAT6utelOZCvt9eHD\n4np7/8CtQGvSM//XNyitr+KOoVcyuptruexba5ei1muYf5n4G1mVqob/fvk//GV+PPH3+72+98p1\nq/lt0wb6p/Vtc3ReUlKCSqVi+HD35ZMXCzoJ/U+GIAgsWbIEg8HAk08+ecaTyjfttL8OTxkzwav1\nX/y2HKPJyLy5d+Ivc08ghwtP8siyl9AZ9Vw3cgYPTb+lTQ1CnlCjq+OBVUvIV5Yyd8BU5o/9m9uN\nZW/5SYrrq5iUOIigJlLFnjK7J/fwOPv80jqTDo3Z0GwCUEOE3pTQrRYAAtthfOXriKyd9d0t0UDo\nbj6L3SfdNU9hdjyTpyHTWbVF+Pn4khTSMZYAFquFp9e/R1Z1IVf0Hs+dw12tjHfnHGHtke30TUhl\nzogZLsdtNhuLPnuDOo2ax/92r9fR+cmcbF778G1Cg0N46Z//QSZr29+iUz9vRCeh/8nYtGkT27Zt\nY9iwYcyaNeuMr7cxw97sMdkLQq9S1fDjljXERURz5Vj3OmypspJ/fvsqRrORRXMeYnq691ULraFa\nq+L+VUsoVJVxQ/o0Hh5zg1syN1stfHDoZ6QSCTf2aWxyUht1HK85TWpoF6IcerlzDF1ik0lGtUYt\nflJfgprIK3qrGR+JRJRYW4NEIsFXIsUstBKhu3nTsNis+Epdv4JmxwbhbiiGyWomv66MXhGJDR42\nZwJBEPjvls/ZVZTJmG7p/HPCLS5/A4PJyOLV/4ePVMq/rvyH6NSk5ZtWs/v4AcYOGM6cSZd7de+6\nejX/fOnfmMwmljz9fJsSoU50EnojOkfQ/YnQaDS88soryGQynnzyyTOeQKSqU3Ew8zD90/oSG9V6\n7fjS35ZjNJu4fdaN+LmJinRGA49/vQSlVs2Cy27vUDKv0iq57+fFFKrK+NvA6R7JHOCnnO0U1Vdx\neeoYujdpJtpXkY2AwIgujR2jRY6hxl0dhO6scIkMCGp2D73FTKCPrN2/e5lU2kDALWFzEL0YoVsF\nGwLipG1yROgyEbIHe426VbDRK7xj5sl+uOdH1mRl0DcmhRen3efSRAT2QSQlygpuGD2LXl2SXY5X\nqWp4f+UXhCpCeGbeI179Pi1WC08t/g+lFWXcfv0tXvdKtERmZiY+Pj6kpXWsX/z5iM4I/U/EBx98\nQFVVFXfffTfJyclnfL0tuzOw2qxeyS0VtdWs3LqG+Kg4Lh/jWpoG9lfohT/8j5yK08wZMZ1rR3RM\nNUWlRskPxzay8tgm1EYtfx80kwdGzfVIArV6NcuOrSfYT86t/Zq/7u8pd8otjV9oZ4TuJHSV0bXC\nxSrYMNqshHhwC2wNvlIfjA4CbgkbzghdRFZxbAJiEbbZ5llycernvSLOfBzdD5kb+fzAL3QNjeHV\nmY80c7N0IqfiNMsyVtMlLJq7Js8Vvc7bKz5FZ9Tz1HV3ERni2dveif99+gF7Du1n/Igx/OPv3tec\nN4XJZCIrK4tevXqdURPehYJOQv+TkJmZyXfffUe3bt2YN29eh1xzY8YWACZ7Mdj5i7XfY7ZYuOPy\nG/B1o4V/snkFW0/uY3j3ATw603P1izdQ6tW8u2s5v2XvxGqzEhqg4MHR1/O3gdNbjeg+y/wNncXI\nQ0OubWjrB3v53omaInqExTfUbNsEgRJNDdGBIQ2mV04Pl6YVLgaLnTjlZzA4QiaRom1HUtTiQVZx\nErq7CN1pStYr/MwIfWv+AV7dtozwgGDenLVAdIiF1Wbj5VUfYbVZefzyO0StcvdnHWHt7k30SerJ\nFeMu9ereK9eu5pufl5OSmMSix55pk6d+U2RnZ2M2mzvlFgc6Cf1PgEaj4ZlnnkEQBJ566in8/Nwn\nI9uCEzlZJMTFe2VmtP3IXsIUIcwcJW64pTHoWJaxmpiQSF687lHR13Bv4RxQ8XrG19QZNKSEx3N9\n+jRm9Bot6jLYEkpDPRsK9tEtJJbLujd/LT9YmYuA0JAMBajRqzFYzfRRNEoSzgqX5glRZzVJ+z+b\nr9Q+c9MmCC7SSmPZout5jTXq7mFzo81XOhwlnUM92oO9xcdZ+PtH+PvKeH3Wo3QV8WMH+CpjFUeL\nspnafwxje7k2janq61j48StIJVKe+Pt9+Hih6a9cu5qX3n2N0OAQXn3mvyjk7e+5OHnyJAB9+rTu\nNXQxoJPQzzEEQeDll1+muLiYefPmMWyYa1t7e2Cz2airV9MtofWozWA0UF5byZBeA9z6cKw5tAWD\n2cjtE68lVN7+OueiugrezPiGjMLDBPj68ciYG5k7YKpoUs0d1uXvxSrYuDJ1jMt5ByvtHthNO0ZP\nOxOiwY2EpzTafbmbRejOCpczGGLs45BTrIINqaT579LZUCS4nEWDOZaY/q6Q2at3tGbx4cvOyL+9\nCdFfTm7npS2fI0XCi9PupU+MuJlVdlkBH278jqjgcJ643NUky2az8Z9PX6NSVcN9V99Kv5TWNezl\nv65kyftvEhYSyrsvvE63hDPLAzg90Hv2dG1AuxjRSejnGKtXr2bt2rUMGDCAe+65p8Ouq9bUY7PZ\nCAsRH+bbFKcrShAEgeQu4uQvCAI/7F2Pr48PV7jx6vAEndnAxtx9/HpyOwcd5YTDEvrwr0nzSAjx\n3tEQ7FHqb/m78PeRcUlS8wlJJquFzJpCugRFENdk+lBxfTXQvMJFZdThK5E2mzLkLFk8kwjdxxF+\nWwWBltuCM/oWRBjdKbWIErqjHFNj1ove0ypYkUokbU7kCoLAx3t/4pP9qwjxD2LJjIcYFN9LdK3R\nbGLhD29jsVp5Zva9hMpdO2G/XLeCHZn7GN1/KLfMENfWm+Lrn5fzxv+9Q0RYBO++8Bo9kru36fnF\nkJubi0QiuagdFpuik9DPIfLz81myZAkKhYIXX3zRrXbdHqjqVABeEXpBeTEAyW4msR8oOE5BVQnT\nBowlQtH69cBOvAdLs/k1azubcvc1WLkOje/N7L6TmNpjRLsqSQ5V5lCqqeHS5GENROfEidrTmKxm\nBsU091kv0tTgI5HSxUHygiCgMukI85c3ewaDQ3IJPCNCd0ToNhu0CJgb7+XK6D4SKVIkDRUtTaFw\ndKBqTO4jdLFEqyeYrRb+u/kzfsveQUJINK9f9ihJ4e6Nvz7441vyKouYM2I6o3u6DpE+mJ3JBz99\nQUxYJP+5/bFWNfCvVn7Hm5+8R1REJO+/+IZXTW+tQRAEcnJySExM7EyIOtBJ6OcIRqORp556CoPB\nwMsvv0x8vHem/d5C6SB0b1qmC8rtSTV3EfqPe+1DCa4Z7l1Vy+6iTBZv+YJSxxSc+OBobuo9lpm9\nxhIf0n6dF2BN3i4AZnV3LWlrkFuiGwndYrNSplXSJSi8QZLQWoyYbVbCWjgq6i3OCP1MJBdnhO6q\nd3uK0CUSCTIf34YEaFO0FqHbBFvDRuIN1EYtT659hwOlJ+kX051XZj4smgB1YuepQ3y94xeSouJ5\ncJpr16ayvo5n/m8xAC/c/SThwZ43/Q3bNvLmJ+8RExXN+y++ecYyixPV1dWo1WqGDvV+tu2Fjk5C\nP0d4//33OXXqFNdccw1Tp4qXCZ4JlGq7s6A3hF7YEKG7EnpNvYpNx/fQPSaRQUmtt5UfKsvmid/+\nh4DArLRxXN57HAO79GxzBCkGlUFDRkkmySFx9I1MbnZMEAQOVeYSJAugZ3hCw89LtUqsgq2Z3OLU\nz8NbEHqHRugirN2ooYup6HbZxZOG7lZysdm8/v2WqquZv+YNCpSlTEoZyn+m3u0xEZ1XWczT37+B\nn6+M5+Y85OKUaLPZWPjJq1Sparj/mtsY1LOfmyvZkZl1nOfeeImgQDlv/WdJh5E5QE6Ofch1jx7u\nh1xfbOhQQk9LS5MC7wHpgBG4MysrK7cj73E+4tChQ3z11Vd069aNRx999KzcQ6V2SC7eROhlxQT6\nBxAd5urD8svBzVhtVq4ZfmmrEkl5fQ2PrXkTi2DjlRkPMiZJfHJNe/F74X4sNiuXdR/l8ixF9VXU\nGuoZ3aVPs0RpkUM/79okIapyELpLhG61IJNK25SgbQkfqfsI3RmieyJ0McklSOaPBE+Si82tnUBT\naIw6/vHTi1RpVfxt4HQeGH2dx41Aa9Tz2FeL0Rr1LJrzEH3iXTXurzesZNex/YwdMJybp1/r8f7F\nZSUseP5pzBYLi596vkM086boHArtio7uFJ0N+GVlZY0BngRe6+Drn3ewWq288sorCILAv//9bwID\n2z793BvYHLXQ3lQ+1GnVhAeHieqeJ0rtX5JJfUa0ep1vDq9DY9Izf+zfOpzMATKr8wAYn5jucsw5\nAKJPZHO/kEqHB3qXJklStcke6Yb6tYzQLWckt4CXEbo4nyOTiksuUokUuSzAbZWLVbB59XdefXIb\nVVoVNw++jIfG3NBqVP/+799Qoqzg5nFXinYEl9dU8tGqZYQHh7LwtvkedfOK6krue3o+tapaFtz9\nULu7QD0hPz8foDMh2gQdTehjgbUAWVlZu4GOqck7j7F69WqysrKYOXMmgwa5Jpc6Cs7JQnqjOAk0\nhSAIbqPSclU1fr4yIhWeI321UcuqE1uJCQrnqj7eGYG1Ffl15YT4yYkMcNV7GypZgptbzFY7hkZE\nBTRWZWgc9rbBssbEmU0QMNmsBJyhF0qjQZeYhu5ZcvHz8RWN0AHkvv7o3MwItdisrWroVpuNFZl/\n4O8j4yYRG9yWOHo6mxV71pEUFc9dk68TXfPG9x9hMBl5cM4dhHnQzWtVSu5/ZgFlleXcc9MdXHf5\n1a3evz04ffo0EomExMQz75i9UNDRhB4CqJv8t9Uhw1yU0Gg0vPfeewQEBPDgg96NgWsvAh2ErtOL\n665NYRNsbuWU8rpqYkIiW61a+OnYZvQWI9enX3pGTUfuoLcYKdPUkBzaRfRZizX2BGyCorlsVK1X\nE+onb9Y2X++IdOVN3CSd7fpio+PaAufGaBFLijZILuLwk/piEWyiDURymT86DxF6aw08O04foURd\nxfReo0VHyDWF2WLhv6s+RBAE/nXlP0RdN3dm7mPTgR0M7NGPWaPFm9HAXj77wLOPUVh8mpuvuYHb\nr7/Z473PBKdPnyY+Pr7DGvMuBHQ02aqBpgWr0qysLPF2t4sAn376KbW1tcybN4+YmLbVX7cVcoeU\noze0TuiCTbzszWA2odTW0SXM/WAFsLv9fX/0d+SyAK7q07rNQHtwWl2JgECKm9FqJfXVRAeGNkvw\nmawW6kw6IltMD9KYjQT5+jeLag0dUIMOjRG6eJWLk9HdR+gAZqtrYlTuG4DBaha15rXarPhKPBO6\nc4TcXJERci3x5fafyass4uphUxmc7NpxaTSbePWbD/CR2rtB3QUDWp2ORxY+wan8HK6deSUP3nbP\nGRvOuYNGo6GmpoakpDMvf7yQ0NGEngFcBpCWljYKONLB1z9vUFxczDfffENcXBw33dQ2w/72IKAD\nIvRKtb3DsrWhFetP7aZap2J234ko2jhc2Vvk19mn3ieLDElWG3XUmXTNEp/QOKMzuolEIwgCGrMB\nRYtqDWMHE7q45OJ4Bjfn+jm8WkwiOnqQowFKLyK7WAQbvh7eoPJqS9hbfJwh8b3pKTJCrikKq0v5\ndMsPRAWH84BIiSLAsnU/UFRZytwpV9Kzq7heLQgCz776PEezjjNz8qU8ce+jZ43MAQoLCwHo1s07\nz/WLBR39rrwSuDQtLS3D8d/ts1C7APDmm29iNpt56KGHzknTQ4OGbtC1utZmsyGVun7ZqtV2j5Do\nkAi35wqCwNeH1uIj9eH6dO+MmNqDAkfSUyxCL9Y4KllaeJlU6e2E3jRC11lM2AShmX4OYLB1lORi\n/z2KSy6tlC067i2mo8sdz6szGwlukcy12KweJZflR38HaPXvY7PZeOnnDzFbLTw263bRCUSl1RV8\nvuY7IkPDufuKv7u91o+/rWLbnh0MHziUfz/yZLvNtryFMyHaSejN0aGEnpWVJQD3duQ1z0dkZmay\nefNmBg0axKWXnj3Sawpn9YzOC8nFJghIRCQXpdZRyx7kvunkYFkWecoSpvccRazi7M1vLHBG6CGu\nhF7iIPSW5lSVevvzO4dCQ2NCVNGC0Ds6QhctW3TAXZWLn4OUxSL0QIeUpBWJ0K0ekqI6s4HfsncQ\nFxzJuCTPSfj1RzM4WHiCiX2Gu50L+/aKTzCaTTw992G3JlrF5aW88cm7hCiC+c+j/zorOZWWOHLE\n/vLft2/fs36v8wkXbcLybGLLFruN7S23uE5+OVtwftm0utYjdJmvLxaLK4k4SUlsio4ThUo70Y4S\nmTfZkajRqwn2C2w2Zs6JWkckHi1vXmmhNjkaiAKaGnA5m4ealyc6JRJ3U4G8hZOrJSK+icZWRsk1\nTiZyPe7cBFpa75qtFnQW16jdiQMlJzFYTEzvOdpjfb0gCHyVsRofqZRHZ84TXVNUWcrGAxn0TurB\n9BGT3F7n1Q/ewmg08tg/HiYmynP+pSMgCAIZGRmEhITQu3fHzVS9ENBJ6GcBu3fvxsfH55y2JCuC\n7CRWr9G0ujbALwCDSNNKgwOgm1I6AKWDTCMCvfN4aS9URg1hbqbZqxze5mH+zSNGZyNO02i8wVu8\nhauks27cmwYdT3Bugj4i13GWHQa56cx0Rt9BIkMljFYT0BipO6F05AkiAlzNsgB2Fx8DYFSiZ3/w\nPblHyS4vYFKfEW6T4N/+/hOCIHDTtGvdBiZbdm0nY98uhqUPYcakju+AFsPJkyepqKhg3LhxHeqH\ndCGgk9A7GHV1dZw4cYL09HSCgtrv89xW+Pr4Ig8MRKP1htD90ZtcX+W9IfRah6wREShOKB0Bq81K\nnVFLmL/4PeqMdm/z0JaEbjYgQUJgk5mhJkcFiV+LKNhJ6GJE3LZndV7H9aukNdtJWe5m+LbObESK\nRLS5SW+xn+vfwtq3toHQxWWxPUWZyGUB9I913z0pCAL/t+l7AG6dIF4jXqetZ3XGBuIiopkyVHzs\noN6g57WP3sbX15d/3uvd2LmOwObNmwGYNGnSObnf+YROQu9g7N27F0EQGDlSXJM8m1AEKaj3ktAN\nIoTu1D4t3kTo8rMXoVfqVAgIxASJjzKrM2mR+/rj14IItWYDQTL/ZlF34/Sf5hG6rSGyPrOvQEOE\nLiJvOCN0ua9rBO58XrnMX5QIjQ3DN5pvBrUGe5tHRKAroZfVV1OoKmdIfO+GzVkMu3IOc7Qom0l9\nRpDWRbxq5cfNazCYjFx/yVVuPfM/+fZLyqsquOnq6zvEPdFbbN68GX9/f0aPHn3O7nm+oJPQOxi7\nd+8G+FMIPThI4VWEHugfgNFkbLALcMJJkCaL2e25tXo7obTWrHImKG1IeoonXVUGrUt0DvYIvWXy\n0+TQqVvq2B0nubiP9HWOKNud5KKzGN2SvcFxbstNq8bx+xeTXPYU2eWWkYnuDbMEQeCjjd8BcKeb\n+aAms5nvN60iKFDOVeNniK7JLypg2cpv6RITxx3X3+L2fh2NoqIicnNzGTFixFmz0Tif0UnoHYw9\ne/agUCj+lJFYwY4IXXBXVuGA00HP6JAEnJB5EaHX6tSEBijaPS3HG5Q6Jg7Fi4xYs9is1Jv1Lvq5\n2WbFYDW7EnqD5NJSQ+/gCF1McrE4JRdX0rYJNvQWk6h+DmCwmgjwkblsOA0RuojksqfYSeju9fOM\n7AMcL8llSr9R9IwTj6rX7dlETZ2S2eNnoAh0Tb4KgsCS99/EarWy4B/npizXCWfBwcSJZ6eh7XxH\nJ6F3IFQqFSUlJQwcOPBPSdYoghTYbLZWm4uchN7S90XmeGajhwhdbdAQdhajc4Bih696FxFCd6ef\nO42sgloQunvJpfWZnt7A+QbgK0LoaqPerUauNukRRJ7XCa3ZKGpzW+3MYbSI0C02K3uLjxMXHEli\naKzb5/1sy49IJBLunDTH7Zpvfv8ZHx8fbrjkKtHjm3ZuY9+Rg4wfMYaJI8e6vU5HQxAE1q5di0Qi\nYcKEs+MfdL6jk9A7EE5PidYi5LN2f0fyzdwi8m6JQH9xI69gR7lfvcG9bBMoC0BnFjeN6ijkqEqQ\nICFFpAa9Qme3CY5uUWXTSOjNI153cz0DHMlGg4e3EW9Q5Rg+He7f/PVfadRSZainqyJCVNbJrLEP\nGUkVId96k55qfZ1L4xRArqoUmdTX5e0lsyIXtVHLmG7pbpOT2eUFZBafYnSPQaTGijfknCrOJ6c4\nn/HpI4mNcK1+sVqtfLjsU3ykPjxyx/2i1zhb2LVrFydPnmTSpElERLhvfruY0UnoHQi5XI5cLqe6\nuvpPub9M5qhSEakxbwq54xVZb2weyYc5GopU2nq354YFBqPS15+1Tcsm2MhRFpMYEkOgiBxR1iDH\nNNfXtW4aiJxk2tIAS+EgdI3F8+bnCWablSqDjjC/AJcGpZOOev0+bsa8Ha4qQIqEAZGuskeeyn5u\naljzqVYmq5k8VSmpYfEuSc+MwsMAjPVgY/zTPnsH6dXD3Te7rd21CYAZIyeJHv8jYwt5p/O5bMq0\nDh1W0RoEQeDjjz8G4I47XAdWd8KOTkLvYERHR1NZWfmn3NvXQVJmD5IJNI3Qm0facr8A/HxlqHRq\nsdMACA8MxmyzoDW13pHaHpRqatBZjPQMFyeLUm0tAF1aELrGjeTiNCGztdiAnIlKbStvM55QadAi\nINClRQmnIAicVJYjk/rQPdQ1yq0x1FOkqSY1LA6Fn6vkkqMqBaBHeHNCz1OVYRVs9IohRkx9AAAg\nAElEQVRw9WfZUXgYf18/hiaI5270JgNrD28jOiSCMT0Hi66x2Wys37sFRWAQY9PF/fB/WvcLALdd\nd/b9iZpi//79HD58mPHjx3c2E3lAJ6F3MGJiYlCpVBiNZ1eWEINTA28tQg/0F4/QJRIJofJgVDr3\nEXq4g7ycDS4djWylXYroGZYgetyZMO0S1PyV253k0jjzU5zQzyRCL3f8nuICm+cUynR11JsN9AyN\nEe1EPVJlN5YaGJUsel0noae2MCZz/m56tdjsStXV5NaWMCyhj9vxchsyd6A16rlyyBS3ZYiHTh2j\noraKyUPGilroVtfWsO/IAdL79Ccx/txF5wCffPIJ0Bmdt4ZOQu9gOG1yq6qqzvm9/WSOCN3cWoTu\nMH4yukbZ4fIQVFpPEbpdllHq3a85E+QoSwDoGeEmQtfUEBEQ7NJB2WbJReb0SmkfoQuCQLleg0wq\nJaKF42Se2v63F9PHAQ5XF+AjkdJPxAnRJtjIVZXRJSiiYVi0E1m1dkJPi2iuf+847Y3c8gdSiYQr\nh0xxu+a33RsBmDlqsujx9ds2IggC0yeem45QJw4fPszevXsZOXIk/ft77oC92NFJ6B0MJ6H/GbKL\nt5KL3E1SFCBMHozOZHApaWw47qiuUOnPToR+SlmMBAk9RCJ0vcWE0qghPsg1IdYgubSo63Ynucik\nPvhJfdotuVQatOisZroEBrskPfPVVfhKpCQqXBujKnQqynUq0sITXDYlsG9YBquJHi30c7BH6AG+\nfiQGN/fWb9TPXUf1gT0Zeqz4FKN7DiYuzDXRCvba8437M4gJi2RIL3GfnvVb/sBH6sPUcZNEj58t\nOKPzO++885ze93xEJ6F3MOLi7JUZ2dnZ5/zezldpMeOtpmiI0EWcGRsSo25kF2eHYo1jdmdHwmqz\nkq0spmtwdIN9bFMU1ds3yZYJUYB6s/2ztIxqnb7hZpFBEcEyPzQWU5uj9Hqzkb3VxQD0DGn+LLl1\nlSiNOpKCI11q9W2CjV/zDwAwKDpZ9NqHq+xzVFsSusqg4bS6gp7hXZt1pRotZg6WZpESHu/W/XLF\n7nUAzB7mPrLefmQ39ToN00ZMErW+LS4r4Vj2CYYPGkpEmHgH79nAzp072bFjB0OGDGHwYHHtvxON\n6HS26WBMnDiRJUuW8NNPP3H99defM38LaCRyma/nwccB/uKNRdCU0NWigy5iHFFnlVZ1Rs8qhmxl\nMTqzgcmJ4l/c49WnAUgTSQpW6dUoZAEuUW+IzE7wdSJJ3NTgSGqMxRxXVTI8yjtNWGUysLW8AKPN\nQnp4bDO5RWs28kfxCXwkUkbFuXqprD99mGxVKb3C4ukvIrdYbFY2FB7Ez0fGiC5pzY5llBzFJgiM\njm/eBbq/5AQGi4nRbtwvazQqfju8la4RsYztNcTt51qdYZ9wNGuM+Hi537dvBmDaBPeSjTsYDAbe\neustTpw4QVhYGOHh4YSFhREaGtrw7zabjfr6eurr69FoNA3/vmvXLnx8fFiwYEGb73sxopPQOxhR\nUVFMnDiRjRs3cvToUdLTxV+DzwacLfutNTX5OxKHRpMroUcE2eu7lRrxCDza4a9Soalt93O6w8GK\nUwAMju0pevxYTSESoG9kcw3ZZLWgNGhICXHVrMMdhKt0NCQ1RbegUE7WVVGgUZEWEk2In3jXphO1\nRh1bKwox26wMiehCapPoXBAENhQdx2A1MzE+jcgWzVdHqgvZXHyMyAAFN6SNFR0BuKcsi1pDPVOT\nBrtU62w8fRCACV2b//+0vfAQAOOSxb3Pl+9ei8li5sYxl7u1061S1bAzcz99k3uRmpAsumbDto34\n+voycZS4UZc7lJeXs2DBArKyspBIJG0ud5VIJDz44IOkpaW1vrgTnYR+NnDNNdewceNGfvzxx3NK\n6M5kqJ8bdz8nnJ2iYha6zghd6aZ0MUZh168rtWeB0CvthD4oxjW6NVhM5KhKSQmNcyG7Kn0dAhAj\nYhgW4heIBAkqo6tPvEQioX9YLDuqTpNRWciULt3dTjCqMmjZXlGIRbAxPCqB5Bb6+JGaYk5rakgK\njiQ9snm0X6ZVsvzUDvykvtzSZ5Kof4vaqOPrk5vwlfgwPam57XJJfTVHqnIZFNOD2Cb5A0EQyCg8\nTLCfnPTYHi7XNJpN/LBnPaHyYC4fNEn0cwGs2bkRm2DjirHi9emFJUVk5+UwbvhoQhTeu2weOnSI\nxx9/HKVSyezZs3niiScwmUyoVKqGf5RKJSqVCh8fH4KDgwkODkahUDT8e0hICArF2e1MvpDQSehn\nASNGjCAhIYENGzYwf/58QkLcTwDqSDgJ3dlg5A7+jo5WMcfFCCeha8QJPcDXj9AABZUdHKEbLWaO\nVRfQPSyeUBEf9JO1RVgFG/1EGnEqHXp+rAih+0ilhPgFoBQhdIB4eTDJijAKNCpWFZ0k3C+QLoEK\n4gKDifAPRCKRUK6rJ6PqNIIAo6MT6RrU/D41Bg3by04R4CNjate+zWQ2ndnIlye2YLZZuan3BGLl\nYS7PIAgCnx1bh9qk48bek4ht4TK5Nn8PADNSmteG59QUUaGpZVqPkaJTgrae3Idar+GWcVc1bOJi\n916dsR5/mR/TRoj7o/y+zd5s1JZk6MqVK1m8eDGCIPDEE08wd+5cJBIJfn5+KBQKunY9t2WPFws6\nk6JnAVKplKuvvhqj0ciaNWvO2X3N3mrobsy5AMLkniN0gFhFBJUaZYd2ix6rycdsszA4xr3cAtAv\nypXQK5yj59xY+ob7B2GwmjGIVP9IJBKGRSYwIDyWaH85KpOe43VVbCzPY1XRSXZUnmZ7pV27HxfT\nzYXMrTYb605nYhVsXNK1T7M6eKtg45vs7dQaNUzp2p/+keLt9ttKMtlfkUOfiG5MTx7W4vpW1hfs\nRSELZFxC87e9ba3ILb8e3AzArMGTRI8DHM09wemKEiYNHkOwXDwS/n37JmS+Mq/kFovFwuLFi3nx\nxRcJCgrinXfe4brrrjunuaSLGZ2EfpZw5ZVX4uvry48//njOvF2cHi4ymWdCd2roYhG6c56oc76o\nGKKDwtFbjNSbWh935y0OVeYAHvTz6kJkUl/RcsaGCD3QNfoFCGvQ0cWfVyKR0Ds0mkldunNVtz6M\njk4kRRGOj0RCiU6Nj0TChNhk4uSuHaE7ynOoNmjoGx5PamhjOaG9omU/p1Rl9A5PYGo38RrxUk0N\ny47/QaCvH3elz3QpgdxTfpJag5opSUNchl1sLzhsT8CKJESr1LXszj1Mv649SY4Wb9ICWJWxHoAr\nxk0TPZ5fVEBOQR6jh45AEeRZ+lAqlTzwwAMsX76c1NRUli5dyvDhwz2e04mORafkcpYQERHBlClT\nWL9+PVu2bDkn01WcZYj+rST3nJKLUYTQWytbBIgOshNnja6OEBFf8vbgcGUuUomUAVGuAxdq9GqK\nNdX0j0oW8TW3UVhfRbAswK0VbZQjQVmkqaFLkOfBHDKpD12DQukaFIogCKjNRnwlUoJa5CVMVgtb\nS7M4riwj1C+QCfG9Go7VGXV88//snXdcFPT/x5937L2XIBtBhlvcI1eK5sxMLUfZ0nbftt8sG1bf\nsn6lOZqWe2tuxQkqCCoIshGRvTcct35/HEcCBxyIQnXPx6NHj+4+n8994OJ1n3t/3u/XO/ECaWX5\n2BiY8niPYSoNuiJzk9gYfYQaqZjnegVh3ahpRa1UzM/RhwEIch/c4LnbxdnczEtlgGNPle/Bnisn\nkMnlTOnbvM1sQUkRx8PO4mBlxwBv1Xc9B08eBWD8CNXFRnezfPlyIiIiGD16NB999NED7dilQYHm\nhH4fefbZZxEKhaxZs6bV3PCOIL+wAFNjk/q0xOb4qzNR09xso7rTbGVN86dvo7pUwI7yc6mVSkgq\nvoOHeTeV+edX607v/WybXvylluZSKRbhZ+Xc7Nd6j7oS/Ii8NJX56M0hEAgw09VvIuappflsTrzE\nzeJsbPRNmOnev/6DJr08nzVRR0gryyfAypnnAyY0KceXymTsiD/H/13dj1Qm47leQQxzbNqUYlPM\nMW6X5TLVc1gTo66dNxRGWzP9mgptRU0Vu8OOY2FkSlDv5gX992O7EIlrWThptsrc86rqKvYfP4Sl\nuSVjhrXsPx4XF0dYWBj9+vXjyy+/1Ih5J6ER9PuIq6sr06ZNIy0tjUOHDt3318srLFCr63p9AZIK\n61gtoRBDXX0qWhL0uuKdKnHTLJn2kFR8B7FMip+Vq8rnI+vSGfupyOS4np8GNO+LAqCnpc0gO3ck\nchlbEi+T0c4L3UqxiCO3ozl0O4oqSS2Btm7M9hyISZ3BVmReChtunKRCLGKKW3/meY9ompFTVcoX\nV3Zy+FY4doYWrBj6hEoxjym4xa6Ec3QztmJJr8kNnisXVXEkIRR7YytGujXNLd8fcYrymkrmDA5q\n9jI0t6iAveeO4GBl22x2y+HTx6morGDWpKmtZk79/vvvADz11FMqPxw0PBg0IZf7zLPPPsuRI0fY\nsGEDEydOvG/dXSqrqqisqsTGSnVp9920dEIHMNI3pKKZeDNQf4quUpH22B5iC9IA8FUhyhW11cQX\n3cHdzEFlU4fYwnTMdA1xMW35g6yPdXfKaquJLsxgb+pVfCwcGO7ghWEzZlZ3I5fLiS3KIiQ7iVqZ\nBAdDM8Y49azPNZfKZRxNu0pIVjwG2rrM8x6Bl3lDY61aqYQjt8L5MyUMsUzCADsvngmYpNIiuFoi\n4n/h2wF4M3Bug6bXAAfjzlMtEfGU/9Qm1ai1EjHbLh3GUFefWYGq4+IAa/f+Sq1EzNNT5qm8RJfJ\nZOz4cy/a2trMDJra4u8nIyOD4OBgevTo0SmtFzX8hUbQ7zM2NjbMmzePX3/9lW3btrF48eL78jr5\nhQpDKFurezuhAxjrGVJY0XwlqGHdibSjQi43C9MA8FMh6FH5qcjkcvqrOJ0nFmdRIxUz0M6z1d6g\nQoGQ0Y4+9LRw4HRGPPHF2dwqy2eYvRd+lt2aadQsobCmgos5yWRVlqAj1GJ0N28CrJzqx1dJRGxL\nCCGpJBtbAzMW9ByNdSM73et5KWyOO01eVQlmekY87j2Bod18mw0R/Rx9mKyKAmZ7j8a/0Z2CVCZj\nd0wwetq6TO3ZtGvPkevnKCgv5olhUzE1UH2JGZ0Sx7GwM/i4eDJlqGo7gMvXrnA7I52ghyZgbaHa\nUkDJli1bkMlkLFiwQJPN0sloBP0BsHDhQvbu3ctvv/3GjBkzMDdXnY1xL+QVKppqqCPoWkItBAJB\nsyd0Y31D0guzkMvlKv9AOzLkIpfLiS1Iw8bADFvDph4hEXXhlv4qsl+iClq2oVWFnaEZc7wGEl2Y\nwaWcFE5nxhFXnEU/GxcqxCKKRZUUiSoprqmiUvLXpbG7qQ2junnXh1dAkV2zKe4shTXl+Fg48niP\nYQ3i5XlVJWyJO821vBSEAgEPu/ZnpucwladyJVdzEzmQHIqzqR2L/Js2aL6Qdo3s8gJm+I5u0qhb\nKpPxR8hBdLS0eXxIkMr1ZTIZq7dvAOCNx59rNjyy/eBuAB6f1nyrOlBkthw8eBAHBwfGjXuwLowa\nmqIR9AeAsbExS5Ys4euvv2bjxo289dZbHf4a9Sd0NWLooDilS1s4oUtlMmrEIgxUNGCoD7l0gKBn\nVRRSIqpgdPemudS1UjE3CtJwMLJsYshVK5Vws+gOVvrGOBq3rR2ZUCCkj7Uznma2nMtKJKU0j8O3\noxuMMdHRx9nYCkt9Q5yNrXA1/SuUJZFJuZSdwMn0aGplEkY7+THBuXd9OX+luIY/Uy5z8vZVxDIp\nPpbdWeA7FieTlt+b3Moivr6yE6FAyFuBc9FV0Yt0R7TCc+WxgKbieTr2MhlFOUwfMA4bU9W/kyOX\ngrmZlsiEwFH09mwauwdIu3ObS5Hh9PENoKdnyyX3O3fuRCQSMX/+/E7po6uhIZp34AExa9Ysdu7c\nyb59+3jqqaewtm491t0WEm+lANDdofmc47sRIGhiKaukvol0rWpBVwpNbSs2veqQUqLwP1fVhSeh\nKINaqVilFcDlnETEMil9bdzb/TXfWEefyS69uF1eSE5VKWa6BljqGWGhb6SyMQVAfFEmh25FUFBT\njqG2Lo96jaBXXbGTXC4nJDOW7QnnKK+twkLPmLk+oxnk4NPiHhOK7rA38Rzn7kQhlctY4DdBpQHZ\nxdvRXMtOYHD3ANwsG77PEqmUn87sQkso5IlhqmPeRWUlfLvrJ/R19Xhp1lPN7uf73xQn+HnTH2t2\nDEBBQQFbtmzB3NycqVNbjrNreDBoBP0Boaury5NPPslnn33Gjh07WLasYxvsXr1xHR1tHfy8fdUa\nL5VJm+1cUx9jbybFT9ksQqsZ0WsLGeWKbxaNPb4B4uoaOjQu96+VSjiXGYuelg5Du927aZOLiRUu\nJi3HifOqSjmcFklCcRYCBAyx78E45971ue93yvPZFHuSxOJMdLV0mN1jJA+79m+SN69EKpNxOTuW\nPQnnuVGgsMx1NbXnUe9RTHBtWowjkUr47tIOhAIBLw6Z3eT5I1HnSCvIZFr/sXS3atpcG+Dr7esp\nqyznjcefU9kAGuBiZBjnw0Lp59+H0UNGtPg7WbduHVVVVbz88ssYGhq2OFbDg0Ej6A+QoKAg1q1b\nx+7du1m0aFGH5eqWVZSTkJpEH79ereagg+IkKZXJVPp/AGgLFY9LmxF05ePNufe1hcwKRexfVTji\nZmE6WgIhPSwankYvZSdQKRYxtnuASqOrjqRaUkvwnWguZicgk8vxNLNnilt/7Ov8VqoltexLCuXE\n7ci6y1sv5vcc06RISElxTTln06+zP/lCfTu9gfY+zOwxkv52PZo9ye+KCSatOIvpvqPwbGS9KxLX\n8uPpXehp6/D0aNUx73PXL3HyynkCPHry6ENTVI4Ri8Ws/nENQqGQ/zz3csvfKhISOHjwIO7u7kyf\nPr3ZcRoeLBpBf4Do6+szZ84c1q9fz8GDB5k7d26HrHstNhq5XM6AAPUaACizW1o9oTdzaao8oauy\ngG0rGeX5CAVC7Bt1IaoSi7hVmoOnuUODi0bF6fwm+lo6DO+muiFyR5BfVcrFnESu5qUikoqx1Ddm\nsmt/fC2d6m1gw3MS2Bp3hmJRBbYGZjzpO47etu5N1sqqKCA0M4aLmTHEFqQhR46OUJsg98HM9BqB\ni5nqE7WS0ylX+P7SDkz1jHhm4Iwmz++9coK8skKeGDZVpYd9eVUFX2xei462NssXvtLsN6sdf+7l\ndkY6syfPwMutaZhLiVwuZ/Xq1cjlcl5//XVN7LwLoXknHjCPPvoov/76K1u3bmX27Nkd8scQGa3w\nyu4foNqkqTHSOqHWakbQlX/wEpnqS1OJrONCLlkVBdgbWTbJp04ozkCOnJ6Nwi3xxZlUSUSMdvJT\n2cLtXpDJZSQUZ3ExO4GkkmwATHUNGePkz7BuPvV7zKwo5I+bp7hZmI6OUIvpnkOZ4h7Y4BIzpSSL\nCxnRhGbeIK00B1DcW/hZuzLU0Z/xLgMw12/dFvZC2nX+e2oD+tp6rJ78GlaNDMgqRdX8dn4fRnoG\nLBgxTeUa3+3+mYLSIp6fvgA3B9UGYQXFhfy07TfMTEx57onm4+sA586dIzIykuHDhzN48OAWx2p4\nsGgE/QGjvEDatWsXp06dYuLEpqlpbSUi+hq6Orr4+6gXP1eevJsPubR8QpfK6z4Q7jHnuLy2ihJR\nhcoL0bhChcOhb6PwQnyR4hK1OefC9lAtqSUiN5lLOYkU1VQA4Gpqy1AHb/wsu9eHlqoltexPvsiJ\ntEikchm9bdx5oueYBna3GeX5/BR9mNDMGwDoCLUZ7ODLUEd/BnfzxUJffT/xsDsxvHd8LTpCLVZP\nfg1/u6an5p2Xj1JSVc4zDz2GmWHTtcPjrnPgwnE8ndxY8HDzKYhrN22ksrqKd5a+jplJ83bPtbW1\nfPvtt2hpafHqq6+q/bNoeDBoBL0TmD9/Pnv27GHr1q33LOglpSUkp6XQz793q6ZcStQOuTR7KarI\njrnXkEtmuSJ+7mjcNOMnrkhx+r27t6ZMLiehOBNTXQMcVTSKbg/X8m6xLyWMWpkEbaEWA2w9GNrN\nh26NPMmv5SbzW+xJikUV2BiY8UTPMfSx9aiPMxdVl7El7hSHUy4hlcvwtXJlVo+RDLT3aTHvvDmC\nU66w8vRPCATwv0mv0MehR5MxpVXlbAn9E1MDY5V55yJxLav++A6hQMh/F73a7LfBqJs3OHTqGF5u\nnkx/WHV8XcmuXbvIyMjg8ccfx9XVtc0/l4b7i0bQOwEnJycCAwO5fPkyBQUF95TCeOzcKeRyOcMG\nDlF7TmWdK6O+ipREUIQGAGgmrVH5/L2aApfWKtrCNS7pl8vlZFcU4Whs3SCMUV5bTaVEREALRlxt\nISI3hT3Jl9DT0mGSS18G2nli2Eh8K8U1bL4ZTGjWTbQFTcMrFbXV7Ew4w77EC9RIa+u8V6Yw3DGg\nXXsUScT838Vt7I09g4G2Hp8+/BIDnVR/8/rm6CbKayp55eEFGOs3zTLZfuoAmfk5zB03nZ4uqm2J\nK6oq+eDrTxEIBLz9wqvNhuEAKioq+OWXXzAyMmLJkiVt/tk03H80gt5JDBw4kMuXLxMZGcnDDz/c\nrjXkcjn7jx9CW1ubyWPUX6Okrl+ohYlqK1m5UqqbESSdulCNuJnCJHWplda1zGtUQFMhrqFWJmki\n9CV1fUEt1Ig9t0Z4ThJ7U8Iw1Nbjab+xKouT4ovusD7qMEU15biZ2fNMwCScTBQfvlKZlH1JIWyN\nO0l5bTWW+qY82/sRJrkPanIf0BJyuZyi6jLulOSSXprD7phgEgvS8bB04tMJS3G1cFA572LiNY5G\nnadnNw8eGzypyfNFZSX8dmQ7ZsamLHlkXrOv/79135KVm81Tc56kt6/qRtNKNm3aRGlpKcuWLbsv\n1c4a7h2NoHcS/fsr+kbei6DHJsaRcvsWY4eNwtK8adl8c5TUtZdrVtCVet7MfJ1WLk3VRSnoeo0E\nvahGsT/LRp4oxSJFfNviHj3YL2UncCD1CkbaeizxH4dDo/CKTC7jYPJl9iVfRCCAWV7DmeI+qD6W\nnl6Wy//CtxNflI6xjgFPB0xmutfwJja5d1NZW82d0lzulORyp1Qh3uklin8qGnniTOs5iteGz2t2\nvUpRNZ//uREtoRbvT39eZejsxz+3UFlTzX/mLmq2E9Hxc6c4cuYEvl4+PDN3UUu/MvLz89m6dSs2\nNjYdlp2loePRCHon4ePjg5GREREREe1e48AJRfOD6Q8/0qZ5xeWKE7qZserLL+UJvbmQgfKE3lyM\nXV1q6074jU/oRdWK5hqWeo0Fve6Efg+CHpIVz6FbERjr6POM/7gmPT6LasrZEHWYuKI7WOmbsrTP\nFLzq8uClMhn7ki7wa8wRaqUSxjr3Y2nfGZjqNQx3lNZUcDThIilFGQrxLsmhqLppSz8doTZOZrb0\nd+yJs7k9zmZ2eFk742Pj2uLP8MPJreSWFvLUqFl42TdtyZeSeZt9547iYu/EzJFNT+8AOfl5fP7D\nNxjoG/DJm/9tNdtq48aNiEQinnvuufvmGKrh3tEIeiehra1Nnz59CA0NJT8/Hxsb9TxYlEikEs5c\nuoC1pRWBffq3PuEuSls5oSuP6IJmzujKwqN7DbmImgm5FNXUCXrjE3pdBkp7Qy7nM29yJO0qJjoG\nPOM/rkkP0ut5KfwYfZRycTX97Tx52n8ixnVGZJnlBXx1ZTsxBbcw1zPm3UGPMtypYYgiq6yA7dHH\nORh3nhqJoh2gUCDA3tiawd39cTKzw9ncnu5mdjib22FvbN3m4qxraXHsDj+Oq40ji0fNVDnm+90/\nI5PLePnRp1UKtVwu59Pv/0dFZQXLX36L7t1abticlpbGwYMHcXV1ZcqUli9NNXQuGkHvRPr3709o\naCiRkZFtznaJir1BaVkpsyZNbXNDAeUJ3bzZE7qC5k/oiq/4ben+owpxvaA3/N9QKehW+g33pzyh\nm7fjhB6Wk8iRtKuY6RryjP+4BpWcEpmUnQnnOZYWgbZAiwW+Yxnr3BeBQFAXfrnIz9GHqZHWMsKp\nFy/3m9UghzypIJ0/rh8lODkcqVyGrZEFzwbOZIhzAI6mNipNttqDSFzLZwfWIxAIWD7tBXRV+Jhf\njr3KxZgIBvbsw/BegSrXOXjyCJevhjOkfyBTx6t2ZbybtWvXIpVKefHFFzVFRF0czbvTidwdR2+r\noJ8LCwVg9JCmntit8Zegt9xfs1lBrzuhi+pOoe2lti4Gr1xPSZFI9Um8VFSFgbZuk5h7axTWlPPn\nrUgMtfV41n88Vned/OVyOWuvHyQyNxl7IwuW9XkEF1M7QBFi+ezyZs5nRGGia8jrAx9jdPc+9b+X\n9JIcfri8m7O3IgHwsHTkiT5BjPcMbDbH/17YcHoH6YXZzBkcRIBz0zRGiVTK/+36EYFAwCuzl6h8\n//ILC/jmp7UYGRrx3otvtpqJc+XKFc6cOUOvXr0YNarlNnQaOh+NoHciXl5eCIVC0tLS2jw38oai\nmKhfgOpu8i2RVaCoXGzOoKk1HOoyPdKKs9o1X4myN2lZXfqiEt06ga9tFNLR09KmsEaCTC5rUw78\nkbSrSGRSHvUc3EDMAS5lxxGZm4y3hRNvDJhVfxEpl8v54fp+zmdEEWDjzvLBT2J516n+bGokK05t\nQCQV42/nwVP9pzLEuX2piuoQHHuZLaF/0t3KgefHPq5yzJ+hJ0jJvM0jwybQo3tTCwKArzd+R2VV\nJe+++Ab2Nk0N0e6mrKyMDz/8EC0tLd544w1N84q/ARpB70R0dXWxt7fnzp07bZpXUVlB0q0U+vj1\narXXoyru5GZib2nTbL9JJfJm8tCN9QxxMXfgZt4tpDJZu026lP4teZXFDR5XnsyLa8rr0wQBrPRN\nuFNRSImoCks14+gppTnEFt7BxcSmSSOMMlEVm2+eRldLh2d6TWqQVbIr4SwHk+fOLAkAACAASURB\nVENxM3Pg42FP1Tf1AEWD5m9CtqKvrcvH459nnEfgfRO7pJzbrD2xhUvJ19HR0uaT2a9gqNf0UrKi\nuooN+//AQE+fF6YvULnWhfCLBIeeo7dvANMntBwLl8vlrFq1itzcXJ5//nn8/FR7p2voWmgEvZNx\ncnIiPDyc6upqDAwMWp8ARMXFIJfL6dNK3rAqistLySspZJBv0+bCSpTSJG+hdMjPzp0jCaHcLsnG\n3VI9D/bG2NV1KMqtaijoyvxzZZqiEuXpurCmXC1Bl8llHKoLhzziNqCJ6G6OC6ZCXM08n4ewvSvb\n5Uz6NX6MPoS1gRmfjlhSL+YyuYw1l3ayNeo4VoZmfB30aqsZKe0lt7SADcE7OBJ1XmG85ubPSw8/\ngU831Sfv34/upKi8hOemPYm1edOc+uqaar5cpyjZf3fZG63euxw9epSTJ0/Sq1cvFi1a1BE/koYH\ngEbQOxlnZ2fCw8PJyMjAy0t1NV9jrscquuv08evV5te7HKsQuAE+LYRqlMLXQimon61C0GNzU9ot\n6LZ1+d+5jU/oegqxVl6OKrGuE/rC6vImTZhVEZGbQnZlMf1s3XFq5Hd+NTeZy9nxeJg7MMH1rw+3\nqLwU/he+DUMdfT4b8Qw2dUIvkohZefpHglOu4GrRjdVBr9HNVHWFr0QqJeJWDJU1VQgEArSEQgQC\nIUKBoO6/tTDRN8LM0BhTA2OM9QzrBba8upJNF/ax4/JRaiViPO2ceXHCEwz27N3st4Csgly2ntyH\nrYU188c3dWME2Lj1N3Lyc1n82BN4uLipHFO/XlYWX3zxBUZGRqxcuVJzEfo3QvNOdTJOToqUsTt3\n7rRJ0IVCIb16+rf59S7eUOS9Dw0Y0OyY5tIV78bPTnFSjM1L5REVzYrVwUhHHxNdgyYndKWBlTJN\nUYnyhF7QSOhVUSOp5Xj6dXSF2kx0buhCWSmuYVPsSbQFWizxn1gfj79dmsOHob8iB1YMXYhb3YdG\naU0Fbx/7nuvZifR18OaLSS9hqiLTpkZcy+FrZ9kcepCs4jz1fgkoUhtNDIwxMzCmuLKM8ppKbE2t\neH7sHCb2HtlqSGvNnl+olYh5ceZi9FWEYxJSk9i2fxdODo48NUd1OEaJTCbjww8/pLKykhUrVtT/\n/6nh74FG0DuZ7t0VboLp6elqjRfViohNjMfLzQNjw7al70llUi7fvIqtuRWejq6tjm8p5OJp6YSe\nlg438261aQ+NsTW0ILO8oEFDamXIpfEJ3Ur/r5BLa5zOiKFSLGKCc+8mhT/b489RLKpgltdwHOti\n9IXVZbx34ScqxNW8FTiXfnaKLJKssgJeO7ya2yXZjPUYyAdjnkGvUbpgRU0Vu8OPs/3SEYorS9HV\n1mH6gHF42jkjk8uQyeTI5XJkchlyuRyJTEpZdQVl1RWUVldQVlVBaXU5ZdUV6OnosnDEdGYPnoS+\nGvcjJ6+c51TEBfzdfZgQ2DQLRSqV8tn3XyGVSXln6WutNkDZsWMHV69eZfTo0Zqc878hGkHvZJQn\noMzMTLXGJ6YmI5aI2xU/j0mNp7SijKnDJ7R4iVcfcWnmUhQU1rveNq7E5qaQV1GMrbH61gN3Y29k\nSUpJFoXVZVjXFfoYaOuir6VLTmVRA6E31NbDQFuX7MpiZHI5wmZ+hryqUkKz4jHXM2JEoyYYqaU5\nnMuIpruJDZPdA+t/zi/CtpJXVcwi/4mMd1V8exFJxLxy6CvulOYyv/dElg2Z3SS75nx8BF/++SP5\n5cUY6RmwcMR05gwOwsrk/nud5BYV8MXmNejr6rFi8esq4+IHThzmZlI8E0ePZ1Dfpq3t7ubOnTus\nWbMGc3Nz3nvvPU1Wy9+Qe285o+GesLJSxHaLi4tbGakgOy8XAOduTT3EW+NY2FkAxvYf3uI4pWgp\nOxM1x2TvYUjlMjZdPdTmvSgJsFaEbsKz4+ofEwgE9LJxI7eqhNS65hDKx30tu1MiqmRbwgXKG3mg\nKPYsZ19KGFK5jEfcBtTbFCg5khoOwFyf0fUmWhezYriWl8RAex/m9RxXP3Zb1HHulObyqP8YXho6\np4GYS2UyVu5dy5tbv6zzI5/NwTfWsXT8vAci5jKZjJW/raasqoJXH3sGF/umoZGq6io2bPkFA30D\nXnn6hRbXU2a1iEQi3nrrLSwtO8aeWMODRSPonYyJiQkCgYDS0lK1xucXKpoq21i1zXJXLBFz8sp5\nLE0tGNiz5VZ1SqGTyloXdCdTWw7EnSO7ztu8rQx1VNwDXMqKbfD4yLqy+vMZNxo+7tgTN1NbbhSm\n8+mVPayJOsqp9GgyKgqRyeVE5qVwqywPX8vu+DVqjpFbWcyVnERcTG3rG09LZTJ+jj6ClkDIC32m\n1Z9KcysK+e3qn1jom/Bc4Kwm+14fvJ3D18/h082d31/4giUPzVZpYXu/2B58gCtx1xneK5AZzfi1\n7D68n6KSYubPeAxri5abYB86dIjw8HBGjBjB+PHj78eWNTwANILeyWhpaWFqaqq+oBcpGgu3VdAv\nxkRQVlnOw4Gjmm1soUT51b01QdfW0ubpAdOQyKT8Gvlnm/ajxMHYClcze67mJVItEdU/7m/tgqW+\nCZez4+o9XwDsDM15zGsoQa79cDezI6uyiFN3olkTdZRVV/Zw6FYkukJtprk3vfQ9lhaBHDmT3f7K\nGz+XcZ075XlMcB1Id9O/Cm2+v7STGkktSwc/ikmjGPyZm2H8fmE/TpZ2rFn4X9xt2/5t6V5IzrjF\nD3t/w9LEnOULX1UZGqmqruKPvdsxNjJm3rTZLa5XWFjIN998g6GhIW+//bYm1PI3RiPoXQAzMzNK\nSkrUGtveE/rRS6cBmDR4TKtjlb1CZa0IOsAEr8G4mDtwOD6E/55cz9GEixSrcBZsiSHd/KiVSojM\nSax/TCgQMtzRX9Ee7q7HQVF4NNLRl2f9x/NB4GzmeY+gn407MuSIpGImufbFrFEWSpmoivMZMVgb\nmDHQ3htQfGBtjj2JlkDI3J5j68dGZsZzKjkcX1t3Jvs0DE+l5Weycu9a9HX0+GLum5gY3JuVb1up\nFYv54Kf/USsR8/7CV7A0VR3e2XV4PyVlpcybPhsT45bb3n399deUlZWxdOlS7O1bblitoWujuRTt\nApiZmZGZmdngArA58gsLEAqFWFmoH+Msr6rgQnQYbg7OeDs3381diTJWLFXDfEtLKOSdUQv5KPhH\nTiaHcTI5DAECetq6MdQ5gKEuvfCxcW2xVH9oN3+2xQVzKSu2gYPhSCd/DqZc4nzGDYY5qq5U1NfW\npZe1C72sXZDJZZTVVqs07zqUGoZYJmGS24D6NMDzGVHcKc9jolsgDsaKkIREJmV1yBYECPjPiPkN\n9l0pqubtbV9RVVvDx7NfwdOu4/qaqsv6/b+TnJnGjJGTGNF7kMoxlVWK07mJkTFzpzbfRxQgJCSE\nEydOEBAQwOzZLZ/kNXR9NILeBTA3N0cqlVJZWYmxccsVkPlFhViaW7TJ/Ck4IgSxRELQkDFqfZ3W\nVoZcWrkUVdK3mzf7nvgft4qzCL0dxcX0aKKzk7iZl8pPEQdwMXdg44z3MGumurOHpROW+qaEZd9s\nYCVga2hOT0tn4orSya0sbtCMWRVCgVClmKeW5nA8LRJbA7P62LxUJmPzzZMIBcIGF6F7Y8+QUpTB\nIz4j8LX9qypTLpezct9a0goymTd0ChMChqn1u+lIrsRdZ8vJvXS37carjz3T7Lhdh/dRWlbKc/Of\nwtio+f+fKisrWbVqFdra2rz//vsttp/T8PdAE3LpApiYKL4Sl5W1HqooKilqU3cigDPXFM6MDweO\nVmu8MoauTshFiUAgwN3SkSf7BrFu2jscX/w9n01YyuDu/twuyeb9Ez/Udyhq8noCIUMd/SgVVXI5\nu/HlqOLSdF/yRbX3cjfVklo2RB1GjpynAh6ud2q8mBVDelku413615/Oa8Qifok4gLGuAS8Maniy\nPRp1gbM3w+nn6suy8fPbtZd7QSSu5bM/vkMoELByyZsYqCggAqipqWHLvh2YGBnz+NSml7l388cf\nf5Cbm8vChQvx9PS8H9vW8IDRCHoXQFlarY6ASiTSNhlySWVSopNv4mLvhL1Vy+56SmR1+efN5Xmr\ng7GeIWM8BvJ10GuMcutHRGYcHwX/2Gwq5HSvEQgFAn6POd5gzGCHnriZ2XMx6ybX8lLatAe5XM4v\nMcfJrixiousAfK3+6u6zO+EcAI/5PFT/2KGEEEpqKngsYDyWhn85K1bUVPH9iT/Q09FlxcwXW71U\nvh/8fGgbmfk5PDZmKn5u3s2OO3T6GCVlpcyeMqPF03lZWRnbtm3D0tJS49XyD0Ij6F2A+qwSaesx\na5lc1qYshJSMNCprqunlobpzvMrXqPtgEbTBorY5tIRCVo57nj4OPQhOucI3odtUFiy5mNrxkHM/\nUkuzuXBXqqKWUMgzARPRFmjxW8wJKsU1ar92cPo1wrLj8TLvxmPef9kT3Cy8zc3CNAY59MS5zvtc\nIpOy9fpx9LR0eNR/bIN1fjyzk6KKUhaPnIm9edsuo+8VuVzOd7t/5rcjO7C1sG6x4bNUKmXrvp3o\naOvw2BTV3YyUHDlyhMrKSubNm6e2KZyGro9G0LsASoFuqTJTiVwmb1OHoqiUmwD08WqDoNfto722\nuI3R09bhf5NewcPSkV03TvH7tcMqxz3pOwGhQMjvsccbpEw6mdgw3XMIxaIKtsadUes1U0uy2RJ3\nBhMdA5b1mVqfWw+wp+50/qj36PrHzqZGklWeT5D38Aan8+TcdHaFHcPJ0p75w9rWu/VekUgkrPz1\nGzYf34OznSMb3/pfsw2fAc6HhXInO5OgMRNavDSXy+UcOHAALS0tpk6dej+2rqGT0Ah6F0B5GaXu\nCb0toZCoJIWg9/ZU389aGfLoyHxkEz1Dvpn8BvbGVqwL28Oh+AtNxjiaWDPBdQDpZbmcvXOtwXNB\n7oG4mtpxITOGqPzUFl+roraaNdcPIpPLeL735Aa9SbMrCgnJjMbT3JHeNoqMH7lczubrRxEgYG7v\nCQ3W+r+jm5DKZLwetEhly7f7RY2ohjd/+JjDl07h59aDn97+im7Wdi3O+WPvdgCemDGnxXHx8fEk\nJSUxcuRITUXoPwyNoHcB1D2hy+XyutRG9d42uVzO9aQYLE3M6W7bTe39KAW9LV2B1MHW2IJvp7yB\nqZ4Rq87+Rkja9SZj5vuOR0sg5I/YEw3SJrWFWiwJmIiWQMgvN45TKqpsMlexdzkbo49SUF3GNM+h\nBNg0tIrdl3QBmVzOLO9R9b/3yMw44vPTGO3eH2fzv/Kwk3PTCU+9wQA3f4b1aN4/vqMprSxn2Tfv\nE3rjCoP9+rP29VWYN9fQu46ouBhuxMcyInAort1dWhx74MABAKZNm9Zhe9bQNdAIehdA3Ri6Mrat\nbsglpyiPvJJCenn6tum0Xf8696Fi0NXCgdVBr6Gtpc37J9cRlZ3U4Hl7I0smug0is6KAk7cjGzzn\nbGrLNA9F6OWl0z/w2pkNrI7Yy66E81zMvMntslz2J1/ken4KflYuTPcc0mB+RW01x26FY21gxuju\nf1nqbo06DsD8Pg37uu69cgKAxwa3rd/rvVBQWsSzX/yHGylxTBz0EF+/+AGG+q3HuDfv2QbAEzNV\nt6dTUlNTw7Fjx7CxsWHw4MEdsmcNXQdNHvrfCKUoq5tOmJadAdBsf8nmUMavtYT3J5vD396DzyYs\n5a2j3/HOse/ZPf+LBi3e5vuO4+TtK2yMOkhvG4/6tEKAKR6DEAqFJBTd4U55PtfzU7ie3zD7xULP\nmBd6T27yDeNgcijVEhHzfcfVx9QzSvO4mB5NgL0n/nZ/FV3VSsQcjw7BxsSCYT36349fg0rW7PmV\nW9l3eHzsNF597Bm1PrzzCws4H36Rnl7e9G2l6cnly5epqKhg1qxZmsYV/0A072gXQCRSeJjo66vO\nLVYiFAox0Degslp1uKEx7U2vq5XUAqCrc/9ixsNcevPUgKn8eGU/26KOs2Tg9PrnbAzNebHvTFZH\n7OTjS7/z7ZgX0a3LH9cWajHVYzB4KE6XZaIqMioKyKwoILOiEC/zbria2TdpQFEtEbE36TzGOgZM\n8Rha//jeWIUlwuxGmS3hKdFU1FQxtd+YB5ammJCewtHLp/FycldbzAGOnTuFTCZj6vigVr+JXbig\nuLsYNaqpd7qGvz+akEsXoKZGkYrXmqADGBsaUVGpnqDr1F3iiSWqC3qaQ1Q3/u6myfeDub0fxsLA\nlK1Rx5v4v0xyH8REt0CSijP4/ureZtcw1TPE18qZ8S79WOQ3nmGOfjgaN3UW3BYXTKmokhleIzDS\nUfyeayS1HIoPwcLAlNHuDU/hJ2MUhUxj/YY0Wet+cCriAs9/9TZyuZwXZy1SW8zlcjmHg4+hra3N\nuOEPtTo2NDQUc3NzTdPnfygaQe8CtEnQjYyoqFJX0BVfwMRSSZv2U1sn6Lr3WdANdfRZ3P8RqsQ1\nbLraNJXxpX4z8bJw4titcI6kXm736xy7Fc62uGDsjSyZ0WNE/eOnksMoE1UytefI+m8AoKjKPB8f\ngYO5DX5O97eCsqZWxKo/vue9DauQSqV8sOg1hvg33x6wMTfiY0m5fYtRg4ZhbtryxWlCQgIFBQUM\nGTJEU+b/D0Uj6F0AZchFr5X2YKA8oVeolbOubO4gkbRN0EXKkMsDSNOb7jsKBxNr9sScJqe8sMFz\nulo6fDB0ISa6hqy5uo/EojttXv9KTjzfROzCRNeQz0Y8g4nuX1a4e2JOIxQImOE7usGcy8nXqRJV\nM85/yH21kk3NSmfxZ6+y7/xRPJ3c+H35d0wZ1jYv8r1HDwIwc1LrGSshISEAjBgxopWRGv6uaAS9\nC6A8oasj6EZGxkil0voPgZbQVoZc2npCFysEXa8NFgPtRVdLh2cHzkAsk/BTxP4mz9sbWfLuoPlI\nZFJWXtxEWTPpiqpIKs7g44u/oy0UsnL4Uw38zm/mpRKXn8Zwlz7YmzQM0dSHW/yH0h6Kykp46Zv3\n+eiX1QRHhlBRXdXgeblczsGQEyz89BVSMm8za/Rkfnl3Na4ObfNVLy0v4+SFMzh3c2JAr5abloBC\n0LW0tBgy5MGEkTQ8eDSXol2Ampoa9PX11ToNGhspLvsqqipbDdHUh1zaGUNv3Az5fjHBazCbrx/h\nSEIoc3s9jIdVw3ZqAx18eNJvPL/HnuCzy5v5ZMSSBpWfqsgoz2f5hZ+okdTy36EL8LdumI+++0Yw\nALP8G/rD19SKCEmIxMnSDh+HhnPUQS6X882OjYTdVBRGHb50Cm0tbfp4+dGvRwC9PX05GHKC4+Fn\nMTYw4qPn32BMKy0Bm+Pw6ePUimuZMXFqqzH34uJiYmNj6du3b70ZnIZ/Hh0m6N7e3gIgA1B2I7iU\nkJDwXket/09GIpGonUJmUdfQoLC4EGvLltuKmRkp/nCzC/PatB9lyb9EKm2TTW970RIKWTZ4Nq8f\n+ZaPTv/ITzOXN4hpg6LgKKHoDmHZcXwVvp23Bs1ttvApuTiDd8//SImogmV9ZzDCqWEqX1pxNseT\nLuNi7sBAp4aWCKdiL1FdK2J8wLB2hVv2XzjG8fCz+Lr24K15Swm5EU5IdDgR8VFExEfVj/N0cuOr\nZR+0Wv3ZEmcvnkcgEDB57MOtjr1y5QpyuVxzOv+H05F/rR5AZEJCgsYcoh2oKx6O9g4AZObm4O3R\no8WxpkYmuDl0JyY1vk6c1bsIszJR2PMWVBTjZPlgOtgMdenNIz4j+DP+AuvD9vDy0IYFMkKBkPeH\nPMk75zYQnH6V4PSrBFi742Jmh4upPa5m9riY2nGnPI//hvxCtVjEy/1m8Yhn07DJ2ss7kcplLBv8\naJMPhX1XTiIQCJjWf2yTea0RkxrPV9vWYWZsyqrn38XByg5ftx48O/UJistLiU65SVTSTW7nZvDy\no0/fk5hXVVcRHR9LT09vLMxab0p99epVAPr3f3A59RoePB0p6P0BR29v79NANfBaQkJCYitzNNSh\nziUngKO9ooQ/MztTrfG9Pf24deEYyRm38HFRL2PDpk7Q88senKADvDZ8HlHZSWyNOs6g7gEM6t4w\ntc5AW49PRizhTPo19iaeJ7bwFjcKmvq6aAmEvDd4PqOdm8aVr2bFcyHtOn0cejDCteHzidlpxGQk\nMaxHPxzMbdq098KyYt5Z9ylSqYxPnnkLB6uGYm1hYsaoPkMY1adjTshXY6KQSqUM6qteRszVq1fR\n19fH11d9kzYNfz/aJeje3t5PA682engp8FlCQsIeb2/vYcBmIPAe9/evoC1f7Z0c6gQ9J0ut8b08\nfdl/4RhRybFqC7q18oReXqz2vjoCQx19Vo5/jiV7P2Hl6R/Z/NhKLAxMG4wx0TVkqucwpnoOQyQR\nc6c8j9tlOaSV5nK7LIdSUSVP+I1noL1Pk/VlchnfX9wBwEtD5jT5ve+LOAnAzIFtyzSRSKUs3/gF\neSWFLJu5iEG+99/3JexaBACD+rQu6MXFxaSmpjJo0CBNdeg/nHa9uwkJCT8DP9/9mLe3twEgqXs+\n1NvbW303KA1qn9C72dWFXHKy1Rrf21NxIotKvsmcseqZMf0l6EVqje9IfGxceS5wJmsv7+KDUxtY\nHfRaffplY/S0dfC0cMTTwlGttU8lhxOXn8Y4z0D87BraIVSKqjkWdQE7MyuGeLWeMXI3a/f+SmRC\nNKP7DmXBxAfTlzP8eiT6evoE9Gy9QOjaNcUFbb9+D85gTEPn0JFpix9Qd2r39vbuDaR34Noa6jA0\nMMTS3JIMNU/oTjYOWJpaEJV8U+0Pjb8EvaTd+7wX5veZyDCX3lzJuMnHp39qtstRW6iVilkXtgcd\noTZLBzVtnHw8OoSq2hqm9x/XJh/4k1fOseXEXlzsnfhg8ev3NW9dSX5hAanpt+jr30ut7lWa+Pm/\nh44U9M+Bkd7e3meAr4BFHbi2hrtwtHcgOy9HrYIhgUBAb8+e5JcUklWQo9b6NiYKj+zcsoJ72md7\nEQqEfDr+BQLsPTmRHMaqs78hkbXuFd8cIomYL8//TnZ5AY8GjKWbacP4uFwuZ++VE2gJhUztP6aZ\nVZqy7/xRVv76DYZ6Bny5dDnGBoatT+oArkQpXCjVCbeAQtD19PQ08fN/AR0m6AkJCaUJCQmPJCQk\nPJSQkDBecyGqPiYmJlRVVVFbW6vWeC9XD6RSKQkpSa0PBob6DwTg8MVgtcbbmFpiZWzOpaTrVNeq\n3/KtI9HX0eProFfpYe3Mn/EXePPo/1FZW93mddJLcliy92MOxYfgYenI4v5Nuw6FJESSlHObh3wH\n1387aY1b2ems+uN7pDIZK5e8iZuDc5v31l6ibsYA0C+gTysjobS0lKSkJAICAtDVvf+FYho6F02l\naBegW7duyOVycnLUO0H3r/tDjrhxrZWRCiYEjsLE0Jh9F46qVWSkJRQyY8A4KmqqOBYdotZr3A9M\n9YxYN+0dBncP4FL6DV448Dl5Fepf1B5NvMjCXR+SVHiHaT1H8fPM/zZxYZTKZKwP3oFAIODp0bPU\nXvvABYWH+orFrzOyz4P1Fb+RcBM9XV28XD1aHXvt2jXkcrkmfv4vQSPoXQAHB8VFZ1aWenHxfr3q\nBD1aPUE30NNnytBxFJYWc+bqRbXmTB8wDi2hFrvDjqkde78fGOka8FXQK0z3HUViQTpL9n5MUmHL\nni7VYhGfnPmZj4J/RCAQ8PG453l39CL0dZpaKxy+dpbk3NsE9RmFu616pfe1YjFHLgVjbmzKQ/2G\ntevnai/VNdWk3E6lp6e3Whkryvi5RtD/HWhymLoASkHPzlYvc8Xawgo3Z1eibt5ALBajo4Zv+azR\nk9l2aj+7zhxiQmDrXtg2ppY85BvIqZhLXL8dR1/Xzou/agu1eHvkQhxNbVl7eRdP7vyAsR4D8bB0\nwtbYAhsjS2yNLbA1siC7vIDlJ9eTVpyFt7ULn0x4ge5mqgt4qkQ1rA/ejr6OHs+PbbnTz92cu36J\nkooy5k+YeV8941VxMykBmUyGn7d678fVq1fR1dUlICDgPu9MQ1dAI+hdACsrRQl/cbH64YQBAX3Z\ndXgfN5Pi6e3b+h+rs50jg/36czk2ksQ7qWp1MXo08GFOxVxid/jxThV0UFzuPtk3CAcTa3bdOEVw\nyhWCU640O35OwHiWDZndxELgbv4IOUBhRQlLRj+Kran6zZIPXDgGwNThE1oZ2fHEJiiafvt792x1\nbFVVFQkJCfTp00ct4zcNf380gt4FsLBQXMS1SdB7KQQ9IvqaWoIOMPuhKVyOjWT3mUO8t+DlVsf3\ncemJp50zZ26Gk1dW1CbRu1+M8wxkuEtvsssLyKssJr+ymLyKYvIqi8irKKZaLGJu7wmMdGs5xJBb\nWsiWi39ibWLBE8PVd6vIzM8mPO46vT39HuhFqJKYxDgA/L1bzz9PSUlBLpfj49O0yErDPxONoHcB\nzM0VXhxtEfR+/r0BRYHJ048vUGvO0IABOFjZcTTsDM9MnY+NecvmXgKBgEcHTeTzgxvZdH4fb055\nWu39qUIul1NQXkxKbjrJuemk5t3BwdyGJ0dMR78NVr36Onq4WTriZqleQVFjpDIZX/75IyJxLW9O\nfhoD3dYbiyj5/dhuAKaPeHCNo5XI5XJuxMdibWmFnXXr1gRJSYosKE/P+9ukQ0PXQSPoXQAbGxv0\n9PS4deuW2nPMzczp7RvAtdgo0jMzcHZ0anWOllCLxUFz+OyP7/h6+wY+f751M8xJvUaw/eJhdocf\np49LT8YHtM0jPCI1hrNx4fUiXlZd0WTMyZiLfDBjGf7dvdq0dnuQy+V8c/Q3QhKvMsDNn6A+6vfW\nPHIpmH3nj+LezYVxAx98k4jbmXcoKCpk3IiH1CpgUgp6jx4tm7hp+OegyXLpAmhra+Ph4UFqaipi\nsfre5XMemYlcLuf3PVvVnjN1+AR6efTkdGQI4XHXWx2vr6vH53PfwFBXvevu9AAAIABJREFUn08P\nrGNfxCmqRK3npt9IT2Tprx+x7LeV7Ao7xrXbcZgaGDGq50CeHv0on815nW0vfs3jQ4K4XZDFMz8t\nZ92pbYjb2F2prWy9eIhdYcdwt+3O54+/oXZVaEJ6Cqv++B4jA0O+XLr8gTT/aIyyoGhgb/UyVhIS\nEtDS0sLdvfX7Eg3/DDSC3kXw9vZGLBaTlpam9pwxQ0fh3M2Jw6ePk1eQr9YcoVDIf+a+gEAg4Ott\n69WqNnWzceKDmcuolUj4/OBGJn/1HF/8+SOJ2U33mpB9i9f+WMWSn5YTeSuWIZ59+GHxCs68v4k9\nr37Pl3Pf5NkxjzHWbzDutt15bdIifli8Ajsza347v49FG94lMUf930FbOBVzke+O/4GNiQXfPvku\nJgZGrU8CSivLeeuHTxCJa1n59Js427Uv1HOvREQp0lQH9mpd0GUyGUlJSbi4uGguRP9FaAS9i+Dl\npQg3JCaqX2CrpaXFk7PmIpFI2Hpgl9rzfFw8mT5iIrey09l19pBacx7yHcT+19fyzEOPYaxnyN4r\nJ3ly3Vs8tfF9/rx6hvisVN7Z/jUL1r3NxaRr9HXpyfqnPuLbBe/R382vxTh1fzc/tiz7imn9x5Kc\ne5vFG97l13N7kUjbX+5/NxKphINXT/PhnjUY6hmw+sl3sTOzVmuuVKZwUswuzGXJlHmM6D2oQ/bU\nVmQyGZE3rmFvY4eTQ+sfKBkZGVRXV+Pt7f0Adqehq6CJoXcRlHHOxMREJk+erPa8oDET2LjlV/Ye\nPcjix57AzMS09UnACzMWEhxxgY0HNzMhcBRWpq2XvNuaWrLkoUdZNHIGl5KusS/iFBeTrhGb8ZcF\ngZ+jJ8+Pe5yB7gFtMqoy0jPgvWnPMbpnIJ8eWM/64O0cunaGGQPGM6XvaMyN1Pu57qamVsSBq8Fs\nCf2T3NJCdLV1WDXndXrYu6q9xo8HtxB28yrDAgay5JF5bd5DR5GYmkxpeRkjB6nXSUl5MNDEz/9d\naAS9i9CeEzqAro4u82c8xrc//8DOQ3t5Zu4iteaZG5vy/PQFfLn1B37Y+xv/XfSa2q+praXFCJ8B\njPAZQE5JAQcig0nOvc3UfmMY7t3/nhwHh/boy9ZlX/PDqa0cvX6O709sZn3wdsb6DWb6gHH0dvZp\ntX9mWXUFu8OOs+PyEUqqytHT0WXO4CDmDZ2Cvbl6J3OArIJcfj+2GwcrWz56+j+tvu795K/4uXqO\niRpB/3eiEfQugpGREd27dyc+Ph6pVIqWmu3iAGZMfIRfd25m2/5dPDIuCHsb29YnATNGTWLf+WP8\nGXqSUX2GtMuTxN7cmufGzmnzvJYwMzTm3anPsmz8PI5cP8++Kyc5Fh3CsegQLI3N6NnNA59uqi/6\nCsqLOB4dSo1YhIm+EYtHzWTO4CAs2njCl0gkrPrjOyRSCS9MX4ipUec1Vq6uqebPU0eBtl2IgkbQ\n/21oBL0LMWDAAPbt20dsbCy9evVqfUIdhgaGLF34DKvWfM2Hqz9l7Ser1fpA0BJqsWLxayz54j/8\n96cv+emdr/Fyanun+/uFqYExjw8JYs7gSVxLi+NI1DlCEiKJuBVDaOLVZufZm1kze9Bspg8Yh7F+\n2y1t5XI5n29ZQ9jNawzvFcj4wJH38mPcE3K5nM/XrubWndvMnjyj1cbgyjkxMTE4ODjUF61p+Heg\nEfQuxLBhw9i3bx8hISFtEnSAGQ8/wsWIMM5dDuGPvdtZNHu+WvN6OHvw0dP/4e11n/LG9x/y6/vf\nqhVPf5AIBAL6ufnSz80XqUxGZlFOs803dLS06enooXZDbFX8emQHB0NO4OPiyafPvoOWsP1r3Sv7\njv/JkTMn8OvRk1eXLFVrTmZmJqWlpQQGajpA/tvQZLl0IQIDA9HR0SEkpO2WtQKBgOUvvYm1pRXr\nN/9MbF2JuDo81G8Yz09fQE5RPm//8Am1bciFf9BoCYU4W3erF/jG/wQ497gnMT92+Qzr9/+OvaUN\nq1/8EAM99atIO5q45AS+Wv8dZiamrHrnQ7W6EwHExCj80v38WrcH0PDPQiPoXQhDQ0P69etHYmIi\neXl5bZ5vbmbOh6+/h1Qq5YOvPqGqukrtuYuD5vBw4GiiU+JY/uMXavmm/9OITIhm5W/fYGxgxDcv\nr8TavPO8a8oqynln1QdIpBJW/mc5Drb2as+NjY0FwN/f/35tT0MXRSPoXYzhw4cDEBoa2q75g/oM\n4ImZj5OelcFXG75Te55AIOD9ha/Q37sXZ69d5O11nyISq9dB6Z/Arex03vrhEwC+XLocD0eXTtuL\nTCZjxdefkpWbw1NznmRo/7blvsfExKClpaUx5foXohH0Lsa9CjrA0ieX0NPTmz9PHWXPkQNqz9PX\n1eOblz5kkG8/QqLD+c+aldSoUeb/d6egpIhX/+8DyqsqWL7wFQb49O7U/WzavYWQK5cI7NNf7TRU\nJWKxmISEBDw9PdHX77xwkYbOQSPoXYzu3bvj4uLCpUuXKCsra9caOjo6fPHeSsxNzfhy/bccOXNC\n7bn6evp89eIHDO8VSNjNq7z07XJKK8vbtY+ujkQqZfeZQzy+4nmyC/N4btoTBA0Z22n7qais4Juf\n1vLD7z9ha2XDJ29+0Kb0VYC4uDhqa2s1DS3+pWgEvQsyY8YMRCIR+/fvb/caDrb2fPvhFxgZGPLh\n6s84eOKw2nP1dHT54oX3mRA4iqjkmzz35VvkFhW0ey9dkasJN1jwyct8ufUHpHIZr895lqcmz30g\nry2TyUjPzOB06DnWb/6ZNz5+j2lPz+GhOZPZun8nrk7OrP10NRZm5m1eOywsDICBAwd29LY1/A0Q\ndEa/SG9vb1fgVnBwME5Ordu+/tsoLy8nKCgIU1NTDhw4oFbvyOZISElk2fI3KC0v452lrzMraJra\nc2UyGd/u/JHtwQews7Thu1c/7pSmDh1JblE+3+/+hRNXzgHwyLDxLJ256L6masrlctIybnP5agRh\n165wLTaKqurqBmMszS3wcvPAr4cvC2bNxciw7fnzAEuWLCE6OppTp05hatp2uwQNXZuMjAzGjh0L\n4JaQkJDW+HlNHnoXxMTEhClTprBr1y7Onj3LuHHj2r2Wt0cP1q/6lqXvv87nP6xGLBHz+NRH1Zor\nFAp5bc6zWJlZsHbvbzzzxZu8PX8p4waMvKfy/s6gtLKcPWcP89uRHdTUivBz68F/5r6An9v9Ma8q\nKS0h7HoEYdcU/+QV/uWG6ezYHV8vH3q4eeDl5omXmwdWFveeUVNRUcGNGzfw9fXViPm/FI2gd1Hm\nzJnDrl272LZt2z0JOoCnqwfrV/0fS99/ja83fo9YIuHJmeo1RRYIBCyc9BiWpuZ8vnkN72/8gu3B\nB3ll9hJ6ebTe17KzKK+q4FpiDBEJ0UTGR5OceQu5XI6liTlvzVtK0JCx98WbRSKV8Pvubfy0bVN9\n6qeZqRnjR4xhcN8BBPYdqLY1Q1uJjIxEKpUyeHDbLRw0/DPQCHoXxdXVlWHDhhEaGkpsbOw9F4m4\nO7uy4fPvWPrea3z3yzqkUqna1aQAjwybQF+vANbs/ZXTkSEs+fwNxg8cydIZi3C0UT9HuiORy+WU\nVJSRV1xAXnEBucUFZORlcTXxBonpqcjkMgB0tXXo1yOAQb59eXT0FIwN1fNBbyspt2/x0beriEtK\nwNrSisemzGRwv4F4u3s9EGOvy5cvAzBoUOdY/GrofDSC3oWZO3cuoaGhbN++nY8//vie13Nx7M6G\nL77jhXdfZe2mjejp6jF3mnrhFwAnWwc+f/49rifF8n+7fuTklfOcvXaROWOnsThoDiaGxve8x7up\nqqkmuzCPnKI8sgtyyS7MU4h3SUG9iKvqcKStpU0vz54M8O5Nf59e+Lv73NcOQzKZjM17t7N+8y+I\nJWImj3mY1599CVPjB2voFRYWhqGhoSbD5V+MRtC7MIMGDcLd3Z0TJ06wYMGCeovde8HJvhs/fLqa\nZ995mdU/fo+2thazJ89o0xp9vPz4+Z3VnLxynrV7f2Xz8T1sPr6Hof4D8Hf3IcDDBz9Xb7VPwtWi\nGlKzbpOckUZK1m1SMtNIybxNUZnqptkCgQBrM0t6dHfHxtwaWwtrbC2ssLWwxt7SFh9nD/QfUMl+\naXkZK77+lNCIy1hbWvHusjcYOWjYA3ntu0lOTiY9PZ3Ro0ff0yW6hr83mne+CyMQCHj11Vd5+eWX\nWbFiBZs2bUJHR+ee1+3ezYkfPl3N8+++xpfrvkVLqMXMSVPbtIZQKOThQaMZ1XcIO08fJCQ6nIsx\nEVyMiajfu6t9dwI8fOhu64ioVkSVqJpqUQ1VNYp/V9ZUkVOUR1ZBLo2zrRys7Bjk249u1nbYW9ri\nYG2Lg5Ut9pa2WJladAnRupkUzzurVpCdl8PgvgP5+D/LMW9HqmFHcPDgQYA2NUfR8M9Dk7b4N+CT\nTz5h//79LF68mGXLlnXYuqnpaTz/7isUl5bw/ktvMv3hKfe0XmFZMbGpCcSkxnMjNZ6baYlUt1Jp\nam5sioejKx6OrnjW/dvd0RmjdtjePkjOXrrA+1+uRCwRs+TxhTz9+II2FwF1FGKxmEmTJiEQCDhy\n5EiHfOhr6Jpo0hb/Abz22muEh4ezadMmRo4c2WExUndnV3749BteeO9VPlvzFUKhkKnjg9q9npWp\nBSP7DK5vlCGRSknNuk1uUT6G+gYY6OljqGeAgZ4Bhvr6GOgZ3JMzYmex58gBvlz/LXq6enzx3kqG\nDxzSqfu5cOECJSUlzJs3TyPm/3I0laJ/A4yMjFixYgVyuZwVK1ZQU9Nx/iqeru6s/WQ1psYmfPLd\nlxwOPtZha2tradGjuzsjeg+iv3cvfF174OrQHTtLa0wMjf92Yi6Xy9mw5Rc+/2E1ZiamrPvsm04X\nc4ADBxR+PVOnti1spuGfh0bQ/yb079+fefPmkZ6ezvfff9+ha/dw92Ttp6sxMTLmo28/5+DJIx26\n/j8BiVTCZ2u+4qdtm+hm58BPX67Fr0fn5+HHxMQQGhpKr1698PT07OztaOhkNIL+N2Lp0qW4ubmx\nY8eOdjXBaAlvd6/6k/rH//cFG7b8gkwm69DX+LtSXVPN2599wP7jh/D28OLnr9bi7Nj5dz9SqZRv\nv/0WgBdffLGTd6OhK6AR9L8Renp6rFy5El1dXd5++22uXLnSoev7ePb4//buParKOt/j+Bs2GAYS\nHBnxPkTmD9HRbBQ0FXNsXFrjzDHBvERSekKXHnFCRTOQQaIhw8LLeAvRKM2pJXgsNWecStMBFMeh\ntPmVKdqgIiaMgKjtvTl/gCzLvAAbHvbm+1prL3j2huf5iPjx2c/l9+PNJSur90A3b+TF5Hgqr1Te\n+Rsd2IWS74hcEMXenP307/NLVr+Sio/3nef1bApr167lyJEjDBs2jIcfvrvJo4Vjk0K3Mz169GDJ\nkiVYrVZmz55NXl6eTdfv17krG5aupm+vPuzZ/ylT583k3Pkim27DHly9dpV3MrcwfsazfPm1ZvRj\no0iNT260u0zr6uOPPyYtLY1OnToRGxtrdBzRTEih26FBgwbx6quvYrFYmDVrFllZWTddx90Q3vd5\nsXJxCmNGjuarE8eZ/EIk//zyC5utvzmzWCz83192MDbyad5I+xNms5nf/89MYqNims0VJCdPnmTR\nokW4ubmRkpIiA3GJWlLodmrIkCGkpKTQqlUrEhMTWbhwIeXl5TZbv6urKwtmRDM3Mor/XLrE9AWz\n2f7XnTZbf3NTVVXFp9mfMeF/n2NxajIlpaU8/eR4st7czMTfhTWb0SXLy8uJjo7m8uXLxMXFyYlQ\n8QNyHbodGzRoEJs2bWLhwoXs3r2bY8eOkZSURGBgoE3W7+TkxLjRT/LzLl158Y/xJLzxR977MJPf\n/GokI0J+ZdhdkbZUXlFOzj8O8U7Wn/n8X0dxdnbmdyOeYOqEiEYbFbG+rFYrsbGxnD59mvDwcEaM\nGGF0JNHMyJ2iDsBsNrN69Wo2bNiAi4sLs2bNYsKECTbdqzxd+G9ef3MFf8/LxWK14OLiwuB+A3hi\n+EgG9RvQbA5H3Mn1ySY+O5jNgUPZ/ONoPhaLBYBhj4QwPXwK93fxMzbkLaxbt441a9YQFBTEsmXL\nmsXwB6Jp3elOUSl0B5KdnU1cXBwXL15kyJAhxMXF4e1t25l4LpR8x0ef/JUP93zE1wXfANXjfQc/\n9EuCH+qHeuBB/Lve36wKvuQ/pfzz2Occyj/Mvty/c6bobO1rgQ8GMKjfAB4dOITu/s3z8EVpaSlZ\nWVmsWLGCDh06kJGRgZeX/b87EnUnhd7CXLhwgbi4OHJzc/H19SU1NbXRjrPqE1/z4Z6P+OjTv1JW\nXl47oYOLiwsP/Px+lP+DKP8H6Xb/A3Ru3xGf/2rb6OOCV1VVcarwW/557PPqx5dfcLrw29rX3e91\nZ+DD/RnUfyADHw6yyUxBjcFsNnPgwAG2b9/Ovn37MJvNuLu7s2bNGgICAoyOJwwihd4CWa1W0tPT\nWbVqFR4eHrz22mv069ev0bZnsVg4XvANR7/6F/qbr9EnvuZ4wTdcvXbtB1/XyrUVHX3b06l9Rzq1\n70Cn9h35WVsf2ri3oY2HB23c2+Dp4YGHhwcuplsfTrBYLBRf/I7Cc2dqHmcpPHeGM0VnOV34Lf8p\nu1T7te73uvOLgJ706dGLvj1707tHL8PePZw/f57c3FyOHj1K69at8fb2xsvLq/ajl5cXFRUV7Nix\ng507d3Lx4kUA/P39+e1vf8uoUaNo27Z5XAMvjCGDc7VAzs7OTJkyhU6dOhEfH8/MmTOJj49n5MiR\njbI9k8mEeqA76oHutc+ZLWYKvj3NVye+5pvTBZwpqindc2cp+PfpO67z3tatMTmbsFZVYbVasVot\nWKzWms9/+g5Wk8lEx3btGfBwEH0Ce/FQYG/8u/oZNgpiRUUFhw8fJicnh9zcXE6cOHHX33vfffcx\nbtw4Ro8eTUBAQLO5ykY0b1LoDmzkyJH4+PgQHR3NSy+9RFFREc8880yTlIOLyYVufv508/O/6bWy\n8jLOFJ3l32fP8F1pCWXlZVwqL6O8opxL5WU1y+VYrRacnU2YnJ1xdnau/mgyYXI28bO2benUviMd\nfTv8YG//dnv2TaWgoIBXX321do5PqL7L95FHHiEoKIi+fftiNpspLS2lpKSE0tLS2s+tVivDhg1j\n8ODBtGrVeLMsCcdk/G+/aFT9+vUjLS2NqKgoli9fzrlz55gzZ45he60AbTzaoDza/GCP3lHs3LmT\npKQkKisrCQwMJDg4mODgYHr37i0FLRqdFHoL0K1bN9avX09UVBTvvfcexcXFJCYm4ubWNNO0tQRX\nrlwhJSWFzMxM3N3dSUpKkuvERZOTO0VbCF9fX9588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"text": [
"<matplotlib.figure.Figure at 0x111971b50>"
]
}
],
"prompt_number": 23
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.kdeplot(data, bw=1, clip=[(-4, 4), (-11, 11)], cmap=\"PuRd_d\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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s5csuSv3SJbBuXQvLZtUxqmiLOB+XTCZ9iiD07iuCrnoQ5fkBAImWOnZdG2A/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\nTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x111423890>"
]
}
],
"prompt_number": 24
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.kdeplot(data.values, shade=True, bw=(.5, 1), cmap=\"Purples\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x111f08f50>"
]
}
],
"prompt_number": 25
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Bivariate and univariate plots using `jointplot`:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `jointplot` function allows you to simultaneously visualize the joint distribution of two variables and the marginal distribution of each. Above, we showed how to use it to draw a hexbin plot. You can also use it to draw a kernel density estimate:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"with sns.axes_style(\"white\"):\n",
" sns.jointplot(\"X\", \"Y\", data, kind=\"kde\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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6dDyxwnQpeaHAEiF4XdVwTISWwsrfquYthHCY9hWP4Lru6G/wOc0SlJIX1K6q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\nBZaIiASCAktERALh/wOoid22m1r+HAAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x111f26f10>"
]
}
],
"prompt_number": 26
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Combining plot styles: `distplot`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Each of these styles has advantages and disadvantages. Fortunately, it is easy to combine multiple styles using the `distplot` function in seaborn. `distplot` provides one interface for plotting histograms, kernel density plots, rug plots, and plotting fitted probability distributions.\n",
"\n",
"By default, you'll get a kernel density over a histogram. Unlike the default matplotlib `hist` function, `distplot` tries to use a good number of bins for the dataset you have, although all of the options for specifying bins in `hist` can be used."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.set_palette(\"hls\")\n",
"mpl.rc(\"figure\", figsize=(8, 4))\n",
"data = randn(200)\n",
"sns.distplot(data);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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45Giv40gFCU26kODQYbS/vhYn3eV1HClzxUp6NXArgDFmDrCpD8e8l/y1a4wx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\nkhYRESlTKmkREZEypZIWEREpU/8/en125ycNHcUAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x1119ea190>"
]
}
],
"prompt_number": 27
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`hist`, `kde`, and `rug` are boolean arguments to turn those features on and off."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.distplot(data, rug=True, hist=False);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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oH7ykRN2upB94AwEKp80gWl1F82uvuB1H0oyKtEgXovV11D+zDv+QoRRMmOR2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\nEUlTKtIiIiJpSkVaREQkTf1/uxlqLbLGKOUAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x110bc22d0>"
]
}
],
"prompt_number": 28
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can also pass a distribution family from `scipy.stats`, and `distplot` will fit the parameters using maximum likelihood and plot the resulting function."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.distplot(data, kde=False, fit=stats.norm);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x111f327d0>"
]
}
],
"prompt_number": 29
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To control any of the underlying plots, pass keyword arguments to the `[plot]_kws` argument."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.distplot(data,\n",
" kde_kws={\"color\": \"seagreen\", \"lw\": 3, \"label\": \"KDE\"},\n",
" hist_kws={\"histtype\": \"stepfilled\", \"color\": \"slategray\"});"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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7k31JjG4z0OVEUpdM4440TEwDIK/sJNtO7HU5kcQqFWmRGhYMBpm2bb7THtm6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\ngg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1112803d0>"
]
}
],
"prompt_number": 30
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can also draw the distribution vertically, if for example you wanted to plot marginal distributions on a scatterplot (as in the `jointplot` function):"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.figure(figsize=(4, 7))\n",
"sns.distplot(data, color=\"dodgerblue\", vertical=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x1112ac4d0>"
]
}
],
"prompt_number": 31
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If the data has a `name` attribute (e.g. it is a pandas `Series`), the name will become the label for the dimension on which the distributio is plotted, unless you use `axlabel=False`. You can also provide a string, which will override this behavior and label nameless data."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.distplot(pd.Series(data, name=\"score\"), color=\"mediumpurple\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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DMxcFOXVwgJ7ODM2TdctEhqYBXSKX4dShAdqPpJh3TYjJs9SKlit3zbpia3rv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\nhbSIiEiVUkiLiIhUKYW0iIhIlfr/AazbyqY0picLAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x111601810>"
]
}
],
"prompt_number": 32
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Comparing distributions: `boxplot` and `violinplot`"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.set(rc={\"figure.figsize\": (6, 6)})\n",
"sns.set_style(\"white\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 33
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Frequently, you will want to compare two or more distributions. Although above we showed one method to do this above, it's generally better to plot them separately but in the way that allows for easy comparisons.\n",
"\n",
"The traditional approach in this case is to use a boxplot. There is a `boxplot` function in matplotlib we could use..."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data = [randn(100), randn(100) + 1]\n",
"plt.boxplot(data);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAAFxCAYAAABTIkLBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x1112ac2d0>"
]
}
],
"prompt_number": 34
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"...but, it is quite ugly by default. To get more aesthetically pleasing plots, use the `seaborn.boxplot` function:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.boxplot(data);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAAFxCAYAAABTIkLBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n3ADFCDdAMcINUIxwAxQj3ADF/C8XbiPOPdXgUgAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1119e1e50>"
]
}
],
"prompt_number": 35
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The default rules for a boxplot are that the box encompasses the inter-quartile range with the median marked. The \"whiskers\" extend to 1.5 * IQR past the closest quartile, and any observations outside this range are marked as outliers.\n",
"\n",
"This is quite a mouthfull though, and the outliers can be distracting, so you can just make the whiskers extend all the way out. Let's also tweak the aesthetics a bit."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.boxplot(data, names=[\"group1\", \"group1\"], whis=np.inf, color=\"PaleGreen\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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j05yRvcm5OftcVTKcf0vykdbaO5PsT/ILExzr/NUQTMq5OeOsuAGKsccNUIxwAxQj3ADF\nCDdAMcINUIxwAxTzfwN+6VgLxM9rAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x11191cf90>"
]
}
],
"prompt_number": 36
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If fits better with the plot you are drawing, the boxplot can be horiztonal. This just uses the matplotlib parameter, which is awkwardly named `vert`:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.boxplot(data, names=[\"group1\", \"group1\"], linewidth=2, widths=.5, color=\"skyblue\", vert=False);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAFtCAYAAADlKgbgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x110ba2ed0>"
]
}
],
"prompt_number": 37
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In some cases, you may want to plot repeated-measures data. In this case, a subtle effect that is consistent across subjects can be masked and look non-consequential.\n",
"\n",
"To show such an effect, use the `join_rm` argument."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pre = randn(25)\n",
"post = pre + np.random.rand(25)\n",
"sns.boxplot([pre, post], names=[\"pre\", \"post\"], color=\"coral\", join_rm=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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OGrLnfq/uUrSh7IA3CXYkot3I56kbUeLeZXithtfxD+S6LsvLy8zNzbG8vPxe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\nhA/9fzjgUD6wptzBAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x110b90950>"
]
}
],
"prompt_number": 38
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The boxplot is more informative than a bar plot, but it still compresses the a distribution to about five points. Just as the kernel density plot is a modern alternative to the histogram, we can use our computing power to bring more information using a kernel density estimate to these comparative plots.\n",
"\n",
"These plots are known as \"violin\" (apparently, sometimes \"viola\") plots. They essentially combine a boxplot with a kernel density estimate.\n",
"\n",
"Let's create a toy case that demonstrates why we might prefer the increased information in the violin plot."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"d1 = stats.norm(0, 5).rvs(100)\n",
"d2 = np.concatenate([stats.gamma(4).rvs(50),\n",
" -1 * stats.gamma(4).rvs(50)])\n",
"data = pd.DataFrame(dict(d1=d1, d2=d2))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 39
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First, draw a boxplot. Note that the `color` argument can take anything that can be used as a palette in addition to any single valid matplotlib color, and that the function is Pandas-aware and will try to label the axes appropriately."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.boxplot(data, color=\"pastel\", widths=.5);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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wtvKcQ9+6FpJ8srV2X5KDSf77pJ/7UJRZOPl9+T9JPpbkG0nubq0lyb299/fPasDKXPoP\nUIRTLgBFCDpAEYIOUISgAxQh6ABFCDpAEYIOUISgAxTxfwvQkf0yHeK3AAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x110b905d0>"
]
}
],
"prompt_number": 40
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Based on this plot, it looks like we basically have two samples from the same distribution.\n",
"\n",
"But, let's just see what the violin plot looks like:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.violinplot(data, color=\"pastel\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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CgwmKkrlYBKRPH4Tdbmfvvn1u3Y9Oi18gRVFygbI9e/aQmZnp8f1fYzKZWLdu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\nJCYU6CIiMfF/3DAhgv6khbEAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x11195a850>"
]
}
],
"prompt_number": 41
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Woah! Now it looks like the distribution on the left is roughly normal, but the distribution on the right is bimodal with peaks at $+/-$ 5.\n",
"\n",
"It may be rare to run into such data, but more information doesn't hurt even in non-pathological cases, and might catch problems that otherwise could slip through.\n",
"\n",
"(Of course, if you looked at each distribution with a histogram/KDE plot as above, you might have caught this before making any comparisons.)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Both the boxplot and violin functions can take a Pandas Series object as the data and an object that can be used to perform a `groupby` on the data to group it into the boxes/violins."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"y = np.random.randn(200)\n",
"g = np.random.choice(list(\"abcdef\"), 200)\n",
"for i, l in enumerate(\"abcdef\"):\n",
" y[g == l] += i // 2\n",
"df = pd.DataFrame(dict(score=y, group=g))\n",
"sns.boxplot(df.score, df.group);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAGACAYAAABBdbKWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n0OvOmg9xRQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x111954390>"
]
}
],
"prompt_number": 42
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Much like the `kdeplot`, you can tune the bandwidth of the kernel used to fit the density estimate in the violin."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.violinplot(df.score, df.group, color=\"Paired\", bw=1);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAGACAYAAABBdbKWAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n8YyPjwPpG9MPkSyin3BP3+l0rgNeUFV1LbAOWJBoG0xMTJKHkOiHPP50
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