lkluft/discrete_colormap.ipynb

## discrete_colormap.ipynb
{
  "cells": [
    {
      "metadata": {
        "trusted": true,
        "ExecuteTime": {
          "end_time": "2016-06-08T09:03:11.579735",
          "start_time": "2016-06-08T09:03:11.174627"
        },
        "collapsed": false
      },
      "cell_type": "code",
      "source": "%matplotlib inline\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import colors\n\nM = np.random.randn(50, 50)\n\n# Define a list of colors\n# http://matplotlib.org/examples/color/named_colors.html\ncolor_list = ['white', 'orange', 'blue', 'black']\n\n# Convert list of colornames into list of RGB tuples.\ncmap_data = [colors.cnames[c] for c in color_list]\n\n# Create a colormap from list of RGB tuples.\ncmap_name = 'OwnColormap'  # colormap name\nown_cmap = colors.LinearSegmentedColormap.from_list(cmap_name, cmap_data)\n\n# Register the colormap to make it callable via its name.\nplt.register_cmap(cmap_name, own_cmap)\n\n\n# pcolormesh plot to demonstrate the use of our newly created colormap.\nfig, ax = plt.subplots(figsize=(8, 8))\npcm = ax.pcolormesh(M, cmap=plt.get_cmap(cmap_name, lut=4))\nfig.colorbar(pcm, orientation='horizontal')",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 1,
          "metadata": {},
          "data": {
            "text/plain": "<matplotlib.colorbar.Colorbar at 0x7fc63abe19b0>"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": "<matplotlib.figure.Figure at 0x7fc63d7ab518>"
          },
          "metadata": {}
        }
      ]
    }
  ],
  "metadata": {
    "_draft": {
      "nbviewer_url": "https://gist.github.com/cf5863d97e32df08c2a92cd2f2bf1da1"
    },
    "gist": {
      "id": "cf5863d97e32df08c2a92cd2f2bf1da1",
      "data": {
        "description": "Create a colormap with discrete colors.",
        "public": true
      }
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3",
      "language": "python"
    },
    "language_info": {
      "pygments_lexer": "ipython3",
      "version": "3.5.1",
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "codemirror_mode": {
        "version": 3,
        "name": "ipython"
      },
      "name": "python",
      "nbconvert_exporter": "python"
    },
    "toc": {
      "toc_threshold": 6,
      "toc_number_sections": true,
      "toc_cell": false,
      "toc_window_display": false
    },
    "widgets": {
      "state": {},
      "version": "1.1.2"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}
	{
	"cells": [
	{
	"metadata": {
	"trusted": true,
	"ExecuteTime": {
	"end_time": "2016-06-08T09:03:11.579735",
	"start_time": "2016-06-08T09:03:11.174627"
	},
	"collapsed": false
	},
	"cell_type": "code",
	"source": "%matplotlib inline\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import colors\n\nM = np.random.randn(50, 50)\n\n# Define a list of colors\n# http://matplotlib.org/examples/color/named_colors.html\ncolor_list = ['white', 'orange', 'blue', 'black']\n\n# Convert list of colornames into list of RGB tuples.\ncmap_data = [colors.cnames[c] for c in color_list]\n\n# Create a colormap from list of RGB tuples.\ncmap_name = 'OwnColormap' # colormap name\nown_cmap = colors.LinearSegmentedColormap.from_list(cmap_name, cmap_data)\n\n# Register the colormap to make it callable via its name.\nplt.register_cmap(cmap_name, own_cmap)\n\n\n# pcolormesh plot to demonstrate the use of our newly created colormap.\nfig, ax = plt.subplots(figsize=(8, 8))\npcm = ax.pcolormesh(M, cmap=plt.get_cmap(cmap_name, lut=4))\nfig.colorbar(pcm, orientation='horizontal')",
	"execution_count": 1,
	"outputs": [
	{
	"output_type": "execute_result",
	"execution_count": 1,
	"metadata": {},
	"data": {
	"text/plain": "<matplotlib.colorbar.Colorbar at 0x7fc63abe19b0>"
	}
	},
	{
	"output_type": "display_data",
	"data": {
	"image/png": 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	"text/plain": "<matplotlib.figure.Figure at 0x7fc63d7ab518>"
	},
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	]
	}
	],
	"metadata": {
	"_draft": {
	"nbviewer_url": "https://gist.github.com/cf5863d97e32df08c2a92cd2f2bf1da1"
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	"gist": {
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	"data": {
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	}
	},
	"kernelspec": {
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	"language": "python"
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	"language_info": {
	"pygments_lexer": "ipython3",
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	"name": "python",
	"nbconvert_exporter": "python"
	},
	"toc": {
	"toc_threshold": 6,
	"toc_number_sections": true,
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	"toc_window_display": false
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	"widgets": {
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