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Adding hex2rgb and rgb2hex function. Adding dvips colors (#14)
* Adding hex2rgb and rgb2hex function. * Adding dvips colors. * Switching off oldest gcc in CI.
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‎.travis.yml‎

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@@ -7,14 +7,6 @@ env:
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matrix:
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fast_finish: true
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include:
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- os: linux
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addons:
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apt:
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sources:
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- ubuntu-toolchain-r-test
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packages:
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- g++-4.9
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env: COMPILER=gcc GCC=4.9
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- os: linux
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addons:
2012
apt:

‎README.md‎

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@@ -24,6 +24,14 @@ C++ and Python library specifying colormaps.
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<img src="./examples/overview/monocolor.png">
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</p>
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<p align="center">
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<img src="./examples/overview/monocolor_dvips_1.png">
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</p>
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<p align="center">
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<img src="./examples/overview/monocolor_dvips_2.png">
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</p>
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<p align="center">
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<img src="./examples/overview/Qualitative.png">
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</p>
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- [Example](#example)
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- [Available colormaps](#available-colormaps)
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- [ColorBrewer](#colorbrewer)
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- [Matplotlib](#matplotlib)
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- [Monochromatic colormaps](#monochromatic-colormaps)
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- [Available color-cycles](#available-color-cycles)
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- [matplotlib](#matplotlib)
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- [monocolor](#monocolor)
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- [Available colorcycles](#available-colorcycles)
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- [Xterm](#xterm)
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- [Eindhoven University of Technology](#eindhoven-university-of-technology)
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}
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```
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Note that the colorcycles are not interpolatable. Consequently the functions do have a size option. Note also that the colormaps can also be called directly, e.g.
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Note that the colorcycles are not interpolatable. Consequently the functions do have a size option. Note also that the colormaps and colorcycles can also be called directly, e.g.
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```cpp
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#include <cppcolormap.h>
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# specify the colormap as string
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cols = cm.colormap("Reds", N)
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cols = cm.colorcycle("tue", N)
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cols = cm.colorcycle("tue")
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# or call the functions directly
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cols = cm.Reds(N)
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cols = cm.tue(N)
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cols = cm.tue()
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```
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(see lists of [colormaps](#available-colormaps) and [color-cycles](#available-color-cycles) below).
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np.linspace(0, 1, 100),
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np.linspace(0, 1, 100))
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d = np.sqrt(x**2 + y**2)
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d = np.sqrt(x ** 2.0 + y ** 2.0)
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C = cm.Reds(256)
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C = np.c_[C, np.ones(C.shape[0])]
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>
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> [colorbrewer2.org](http://colorbrewer2.org)
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## Matplotlib
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## matplotlib
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| Name | Inverse colormap |
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|----------|------------------|
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>
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> [GitHub](https://github.com/BIDS/colormap)
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## Monochromatic colormaps
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| Name | Inverse colormap |
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|----------|------------------|
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| White | - |
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| Grey | - |
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| Black | - |
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| Red | - |
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| Blue | - |
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# Available color-cycles
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## monocolor
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| Name | Inverse colormap | Source |
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|----------------|------------------|--------|
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| White | - | - |
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| Grey | - | - |
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| Black | - | - |
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| Red | - | - |
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| Blue | - | - |
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| tuedarkblue | - | 1 |
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| tueblue | - | 1 |
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| tuelightblue | - | 1 |
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| tuewarmred | - | 1 |
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| Apricot | - | 2 |
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| Aquamarine | - | 2 |
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| Bittersweet | - | 2 |
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| Black | - | 2 |
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| Blue | - | 2 |
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| BlueGreen | - | 2 |
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| BlueViolet | - | 2 |
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| BrickRed | - | 2 |
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| Brown | - | 2 |
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| BurntOrange | - | 2 |
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| CadetBlue | - | 2 |
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| CarnationPink | - | 2 |
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| Cerulean | - | 2 |
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| CornflowerBlue | - | 2 |
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| Cyan | - | 2 |
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| Dandelion | - | 2 |
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| DarkOrchid | - | 2 |
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| Emerald | - | 2 |
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| ForestGreen | - | 2 |
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| Fuchsia | - | 2 |
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| Goldenrod | - | 2 |
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| Gray | - | 2 |
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| Green | - | 2 |
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| GreenYellow | - | 2 |
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| JungleGreen | - | 2 |
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| Lavender | - | 2 |
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| LimeGreen | - | 2 |
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| Magenta | - | 2 |
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| Mahogany | - | 2 |
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| Maroon | - | 2 |
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| Melon | - | 2 |
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| MidnightBlue | - | 2 |
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| Mulberry | - | 2 |
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| NavyBlue | - | 2 |
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| OliveGreen | - | 2 |
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| Orange | - | 2 |
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| OrangeRed | - | 2 |
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| Orchid | - | 2 |
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| Peach | - | 2 |
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| Periwinkle | - | 2 |
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| PineGreen | - | 2 |
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| Plum | - | 2 |
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| ProcessBlue | - | 2 |
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| Purple | - | 2 |
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| RawSienna | - | 2 |
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| Red | - | 2 |
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| RedOrange | - | 2 |
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| RedViolet | - | 2 |
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| Rhodamine | - | 2 |
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| RoyalBlue | - | 2 |
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| RoyalPurple | - | 2 |
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| RubineRed | - | 2 |
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| Salmon | - | 2 |
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| SeaGreen | - | 2 |
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| Sepia | - | 2 |
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| SkyBlue | - | 2 |
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| SpringGreen | - | 2 |
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| Tan | - | 2 |
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| TealBlue | - | 2 |
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| Thistle | - | 2 |
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| Turquoise | - | 2 |
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| Violet | - | 2 |
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| VioletRed | - | 2 |
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| White | - | 2 |
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| WildStrawberry | - | 2 |
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| Yellow | - | 2 |
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| YellowGreen | - | 2 |
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| YellowOrange | - | 2 |
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1. [Eindhoven University of Technology](http://www.tue.nl)
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2. [LaTeX xcolor (dvipsnames)](https://en.wikibooks.org/wiki/LaTeX/Colors)
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# Available colorcycles
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## Xterm
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| Name | Inverse colormap |
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|----------|------------------|
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| xterm | xterm_r |
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| Name | Inverse colormap |
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|-------|------------------|
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| xterm | xterm_r |
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> See [this site](https://jonasjacek.github.io/colors/)
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## Eindhoven University of Technology
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| Name | Inverse colormap |
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|--------------|------------------|
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| tue | tue_r |
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| tuedarkblue | - |
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| tueblue | - |
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| tuelightblue | - |
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| tuewarmred | - |
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| Name | Inverse colormap |
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|------|------------------|
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| tue | tue_r |
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> Based on the corporate color scheme of the
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> [Eindhoven University of Technology](http://www.tue.nl).

‎examples/overview/monocolor.png‎

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‎examples/overview/monocolor_dvips_1.png‎

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‎examples/overview/monocolor_dvips_2.png‎

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‎examples/overview/order_dvips.py‎

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import cppcolormap as cm
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import numpy as np
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names = (
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"Apricot",
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"Aquamarine",
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"Bittersweet",
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"Black",
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"Blue",
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"BlueGreen",
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"BlueViolet",
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"BrickRed",
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"Brown",
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"BurntOrange",
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"CadetBlue",
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"CarnationPink",
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"Cerulean",
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"CornflowerBlue",
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"Cyan",
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"Dandelion",
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"DarkOrchid",
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"Emerald",
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"ForestGreen",
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"Fuchsia",
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"Goldenrod",
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"Gray",
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"Green",
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"GreenYellow",
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"JungleGreen",
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"Lavender",
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"LimeGreen",
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"Magenta",
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"Mahogany",
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"Maroon",
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"Melon",
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"MidnightBlue",
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"Mulberry",
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"NavyBlue",
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"OliveGreen",
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"Orange",
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"OrangeRed",
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"Orchid",
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"Peach",
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"Periwinkle",
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"PineGreen",
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"Plum",
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"ProcessBlue",
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"Purple",
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"RawSienna",
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"Red",
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"RedOrange",
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"RedViolet",
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"Rhodamine",
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"RoyalBlue",
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"RoyalPurple",
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"RubineRed",
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"Salmon",
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"SeaGreen",
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"Sepia",
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"SkyBlue",
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"SpringGreen",
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"Tan",
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"TealBlue",
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"Thistle",
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"Turquoise",
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"Violet",
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"VioletRed",
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"WildStrawberry",
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"Yellow",
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"YellowGreen",
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"YellowOrange")
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dvips = np.array([list(cm.colormap(name, 1)[0, :]) for name in names])
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jet = cm.jet(256)
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idx = cm.match(dvips, jet, cm.metric.perceptual)
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jdx = np.argsort(idx)
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print('\n'.join([names[i] for i in jdx]))

‎examples/overview/overview.py‎

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"jet"),
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'monocolor' : (
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"White",
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"Gray",
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"Grey",
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"Black",
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"Red",
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"Blue",
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"Green",
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"Yellow",
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"Purple",
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"Cyan",
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"Orange",
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"tuewarmred",
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"tuedarkblue",
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"tueblue",
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"tuelightblue")}
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"tuelightblue"),
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'monocolor - dvips (1)' : (
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"Plum",
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"Fuchsia",
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"BlueViolet",
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"Violet",
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"RoyalPurple",
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"MidnightBlue",
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"NavyBlue",
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"RoyalBlue",
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"CadetBlue",
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"Periwinkle",
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"PineGreen",
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"Cerulean",
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"JungleGreen",
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"Emerald",
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"TealBlue",
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"CornflowerBlue",
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"ProcessBlue",
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"Aquamarine",
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"BlueGreen",
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"Turquoise",
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"SkyBlue",
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"SeaGreen",
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"ForestGreen",
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"OliveGreen",
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"YellowGreen",
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"LimeGreen",
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"SpringGreen",
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"GreenYellow"),
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'monocolor - dvips (2)' : (
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"Goldenrod",
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"Dandelion",
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"Apricot",
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"YellowOrange",
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"Lavender",
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"Melon",
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"Tan",
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"Peach",
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"BurntOrange",
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"Salmon",
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"Thistle",
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"CarnationPink",
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"Orchid",
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"RedOrange",
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"VioletRed",
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"Rhodamine",
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"DarkOrchid",
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"Bittersweet",
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"WildStrawberry",
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"OrangeRed",
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"Magenta",
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"RubineRed",
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"BrickRed",
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"Maroon",
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"Mulberry",
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"Mahogany",
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"RedViolet",
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"RawSienna",
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"Sepia",
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"Brown")}
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nrows = max(len(cmap_list) for cmap_category, cmap_list in cmaps.items())
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gradient = np.linspace(0, 1, 256)
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for ax in axes:
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ax.set_axis_off()
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plt.savefig(cmap_category + '.png')
152+
plt.savefig(cmap_category.replace(' ', '_').replace('(','').replace(')','').replace('_-_', '_') + '.png')
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plt.close()
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for cmap_category, cmap_list in cmaps.items():
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for ax in axes:
117183
ax.set_axis_off()
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plt.savefig(cmap_category + '.png')
185+
plt.savefig(cmap_category.replace(' ', '_').replace('(','').replace(')','').replace('_-_', '_') + '.png')
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plt.close()
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plot_color_gradients('Colorcycles', cmaps, nrows)

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