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gschivley/Luminance comparison.ipynb

Created June 8, 2018 18:07
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Luminance comparison
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Luminance comparison.ipynb
{
"cells": [
{
"metadata": {},
"cell_type": "markdown",
"source": "# Compare the luminance of Jet and Viridis against linear data\nI'm using the [colorspacious package](https://colorspacious.readthedocs.io/en/latest/index.html) to convert jet and viridis to sequences of 256 values representing . This is similar to what is done in the [matplotlib documentation](https://matplotlib.org/users/colormaps.html). These are normalized so they range from 0 to 1 and plotted against a linear sequence of 256 values from 0 to 1."
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2018-06-08T17:40:01.156327Z",
"start_time": "2018-06-08T17:40:00.311930Z"
},
"trusted": true
},
"cell_type": "code",
"source": "import pandas as pd\nimport altair as alt\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom colorspacious import cspace_convert\nfrom matplotlib import cm",
"execution_count": 1,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "def get_lightness(cmap):\n 'Return an array of 256 values representing the lightness of a colormap'\n x = np.linspace(0.0, 1.0, 256)\n rgb = cm.get_cmap(cmap)(x)[np.newaxis, :, :3]\n \n light = cspace_convert(rgb, \"sRGB1\", \"CAM02-UCS\")[0, :, 0]\n light -= light.min()\n light /= light.max()\n \n return light",
"execution_count": 2,
"outputs": []
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "data = pd.DataFrame({'Count': range(256),\n 'Linear values': np.linspace(0, 1, num=256) + 0.01, # include a slight offset\n 'Jet': get_lightness('jet'),\n 'Viridis': get_lightness('viridis')})\ndata.head()",
"execution_count": 3,
"outputs": [
{
"data": {
"text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Count</th>\n <th>Linear values</th>\n <th>Jet</th>\n <th>Viridis</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>0</td>\n <td>0.010000</td>\n <td>0.000000</td>\n <td>0.000000</td>\n </tr>\n <tr>\n <th>1</th>\n <td>1</td>\n <td>0.013922</td>\n <td>0.007086</td>\n <td>0.003893</td>\n </tr>\n <tr>\n <th>2</th>\n <td>2</td>\n <td>0.017843</td>\n <td>0.014209</td>\n <td>0.007786</td>\n </tr>\n <tr>\n <th>3</th>\n <td>3</td>\n <td>0.021765</td>\n <td>0.021367</td>\n <td>0.011679</td>\n </tr>\n <tr>\n <th>4</th>\n <td>4</td>\n <td>0.025686</td>\n <td>0.028558</td>\n <td>0.015573</td>\n </tr>\n </tbody>\n</table>\n</div>",
"text/plain": " Count Linear values Jet Viridis\n0 0 0.010000 0.000000 0.000000\n1 1 0.013922 0.007086 0.003893\n2 2 0.017843 0.014209 0.007786\n3 3 0.021765 0.021367 0.011679\n4 4 0.025686 0.028558 0.015573"
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
]
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "tidy_data = pd.melt(data, id_vars='Count', value_vars=['Linear values', 'Jet', 'Viridis'], var_name='Colormap')",
"execution_count": 4,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## If your real data was the linear values which line would you rather show someone?\nI've offset the linear values slightly because otherwise they would be hidden by the `viridis` line. "
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "alt.Chart(tidy_data).mark_line().encode(\n x='Count',\n y='value',\n color='Colormap:N'\n)",
"execution_count": 5,
"outputs": [
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"text/plain": "<VegaLite 2 object>\n\nIf you see this message, it means the renderer has not been properly enabled\nfor the frontend that you are using. For more information, see\nhttps://altair-viz.github.io/user_guide/troubleshooting.html\n"
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
]
}
],
"metadata": {
"kernelspec": {
"name": "conda-env-pydata-issst-py",
"display_name": "Python [conda env:pydata-issst]",
"language": "python"
},
"language_info": {
"name": "python",
"version": "3.6.5",
"mimetype": "text/x-python",
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"pygments_lexer": "ipython3",
"nbconvert_exporter": "python",
"file_extension": ".py"
},
"varInspector": {
"window_display": false,
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"library": "var_list.py",
"delete_cmd_prefix": "del ",
"delete_cmd_postfix": "",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"library": "var_list.r",
"delete_cmd_prefix": "rm(",
"delete_cmd_postfix": ") ",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
]
},
"gist": {
"id": "",
"data": {
"description": "Luminance comparison",
"public": true
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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