| Name | cmcrameri JSON |
| Version |
1.9
JSON |
| download |
| home_page | None |
| Summary | Perceptually uniform colormaps by Fabio Crameri |
| upload_time | 2024-04-22 08:23:54 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.6 |
| license | MIT License Colormaps in cmcrameri/cm/cmaps: Copyright (c) 2020 Fabio Crameri Python scripts and packaging: Copyright (c) 2020 Callum Rollo Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# cmcrameri
[](https://www.repostatus.org/#active)
 [](https://pepy.tech/project/cmcrameri)
 [](https://anaconda.org/conda-forge/cmcrameri)
This is a Python wrapper around Fabio Crameri's perceptually uniform colormaps.
<https://www.fabiocrameri.ch/colourmaps/>
All credit for creating the colormaps to Fabio.
Any errors in the Python implementation of colormaps are my own.
This version is based on _Scientific colour maps_ [version 8.0](https://doi.org/10.5281/zenodo.8035877) (2023-06-14).
## Install
With `pip`:
```sh
python -m pip install cmcrameri
```
With `conda`:
```sh
conda install -c conda-forge cmcrameri
```
## Usage example
```python
import cmcrameri.cm as cmc
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 1, 100)[np.newaxis, :]
plt.imshow(x, aspect='auto', cmap=cmc.batlow)
plt.axis('off')
plt.show()
```
Alternatively, the registered name string can be used.
```python
import cmcrameri # required in order to register the colormaps with Matplotlib
...
plt.imshow(x, aspect='auto', cmap='cmc.batlow')
```
## Extra instructions
You can access all the core colormaps from Fabio Crameri's list by `cmcrameri.cm.<colormapname>`.
You can use tab autocompletion on `cmcrameri.cm` if your editor supports it.
For a reversed colormap, append `_r` to the colormap name.
Categorical colormaps have the suffix `S`.
For an image of all the available colormaps without leaving the comfort of your Python session:
```python
from cmcrameri import show_cmaps
show_cmaps()
```
The original colormap text files are shipped as part of the package.
Find them on your system with:
```python
from cmcrameri.cm import paths
paths
```
## License
This work is licensed under an [MIT license](https://mit-license.org/).
Raw data
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"description": "# cmcrameri\n\n\n[](https://www.repostatus.org/#active)\n\n\n\n [](https://pepy.tech/project/cmcrameri)\n\n [](https://anaconda.org/conda-forge/cmcrameri)\n\n\nThis is a Python wrapper around Fabio Crameri's perceptually uniform colormaps.\n\n<https://www.fabiocrameri.ch/colourmaps/>\n\nAll credit for creating the colormaps to Fabio.\nAny errors in the Python implementation of colormaps are my own.\n\nThis version is based on _Scientific colour maps_ [version 8.0](https://doi.org/10.5281/zenodo.8035877) (2023-06-14).\n\n## Install\n\nWith `pip`:\n\n```sh\npython -m pip install cmcrameri\n```\n\nWith `conda`:\n\n```sh\nconda install -c conda-forge cmcrameri\n```\n\n## Usage example\n\n```python\nimport cmcrameri.cm as cmc\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nx = np.linspace(0, 1, 100)[np.newaxis, :]\n\nplt.imshow(x, aspect='auto', cmap=cmc.batlow)\nplt.axis('off')\nplt.show()\n```\n\nAlternatively, the registered name string can be used.\n\n```python\nimport cmcrameri # required in order to register the colormaps with Matplotlib\n...\nplt.imshow(x, aspect='auto', cmap='cmc.batlow')\n```\n\n## Extra instructions\n\nYou can access all the core colormaps from Fabio Crameri's list by `cmcrameri.cm.<colormapname>`.\n\nYou can use tab autocompletion on `cmcrameri.cm` if your editor supports it.\n\nFor a reversed colormap, append `_r` to the colormap name.\n\nCategorical colormaps have the suffix `S`.\n\nFor an image of all the available colormaps without leaving the comfort of your Python session:\n\n```python\nfrom cmcrameri import show_cmaps\n\nshow_cmaps()\n```\n\n\n\nThe original colormap text files are shipped as part of the package.\nFind them on your system with:\n\n```python\nfrom cmcrameri.cm import paths\n\npaths\n```\n\n## License\n\nThis work is licensed under an [MIT license](https://mit-license.org/).\n",
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