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multivariate_gaussian_interact_1.ipynb
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{ | |
"cells": [ | |
{ | |
"metadata": {}, | |
"cell_type": "markdown", | |
"source": "# Plot a Bivariate Gaussian (Normal)\n\nProvides interactive controls to allow the variances and correlation coefficient to be changed." | |
}, | |
{ | |
"metadata": { | |
"collapsed": true, | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "%matplotlib inline\nfrom __future__ import print_function\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pylab as plt\nimport seaborn as sns\nfrom ipywidgets import IntSlider, FloatSlider, fixed, interact", | |
"execution_count": 1, | |
"outputs": [] | |
}, | |
{ | |
"metadata": { | |
"collapsed": true, | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "def show1(varx=1.0, vary=1.0, cor_coef=0.0, num_points=3000):\n mean = [0.0, 0.0]\n cov_xy = cor_coef * np.sqrt(varx * vary)\n cov = np.matrix([[varx, cov_xy], \n [cov_xy, vary]])\n data = np.random.multivariate_normal(mean, cov, num_points)\n df = pd.DataFrame(data, columns=[\"x\", \"y\"])\n sns.jointplot(x=\"x\", y=\"y\", data=df, xlim=(-5,5), ylim=(-5,5))", | |
"execution_count": 2, | |
"outputs": [] | |
}, | |
{ | |
"metadata": { | |
"collapsed": false, | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "interact(show1,\n varx=FloatSlider(min=0.0, max=3.0, value=1.0, step=0.02, continuous_update=False),\n vary=FloatSlider(min=0.0, max=3.0, value=1.0, step=0.02, continuous_update=False),\n cor_coef=FloatSlider(min=-1.0, max=1.0, value=0.0, step=0.02, continuous_update=False),\n num_points=IntSlider(min=1, max=10000, value=3000, continuous_update=False),\n);", | |
"execution_count": 3, | |
"outputs": [ | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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CwJBERAUh0UhRssv9x4vSeZeXFo3zmaRmT2sfvL7opebJthEgylWcbiOigqCm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II=\n", 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"text/plain": "<matplotlib.figure.Figure at 0x7f09fb839750>" | |
}, | |
"metadata": {} | |
} | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"name": "conda-root-py", | |
"display_name": "Python [conda root]", | |
"language": "python" | |
}, | |
"toc": { | |
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"number_sections": false, | |
"toc_cell": false, | |
"toc_window_display": true, | |
"toc_section_display": "block", | |
"sideBar": true, | |
"navigate_menu": true, | |
"moveMenuLeft": true, | |
"colors": { | |
"hover_highlight": "#DAA520", | |
"selected_highlight": "#FFD700", | |
"running_highlight": "#FF0000" | |
}, | |
"nav_menu": { | |
"width": "252px", | |
"height": "30px" | |
} | |
}, | |
"language_info": { | |
"mimetype": "text/x-python", | |
"nbconvert_exporter": "python", | |
"name": "python", | |
"pygments_lexer": "ipython2", | |
"version": "2.7.12", | |
"file_extension": ".py", | |
"codemirror_mode": { | |
"version": 2, | |
"name": "ipython" | |
} | |
}, | |
"anaconda-cloud": {}, | |
"widgets": { | |
"state": { | |
"167765f8b8b34720b800c87ead5d9265": { | |
"views": [ | |
{ | |
"cell_index": 3 | |
} | |
] | |
} | |
}, | |
"version": "1.2.0" | |
}, | |
"gist": { | |
"id": "e0e7afda066d9ea09f565335b6c7eadb", | |
"data": { | |
"description": "multivariate_gaussian_interact_1.ipynb", | |
"public": true | |
} | |
}, | |
"_draft": { | |
"nbviewer_url": "https://gist.github.com/e0e7afda066d9ea09f565335b6c7eadb" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 1 | |
} |
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