.. _getting-started: Getting started =============== Installation ------------ The Chromophile color maps are distributed as a Python package. To install it, open a terminal and execute: .. code-block:: bash pip install chromophile Or, in IPython or Jupyter, use the :code:`%pip` magic command: .. code-block:: ipython %pip install chromophile The :mod:`chromophile` package has no required dependencies. To use the Chromophile color maps with `Matplotlib `_, the :mod:`matplotlib` package must be available at the time the :mod:`chromophile` package is imported. The tools used to develop the Chromophile color maps are in a separate package called `chromophile-dev `_. Most users will not need this package. Usage ----- To use the color maps, import the Chromophile package: >>> import chromophile as cp The Chromophile color maps are stored in two formats: * Matplotlib :class:`Colormap ` objects are stored in :data:`cp.cmap `. If Matplotlib is not available, :data:`cmap ` will equal :data:`None`. The color maps are also added to Matplotlib's color map registry. * `Bokeh `_ palettes are stored in :data:`cp.palette `. Individual color maps can be accessed either as dictionary items or as attributes of these objects. For example: >>> cp.cmap.cp_dawn >>> cp.palette['cp_peacock'] ('#06003c', '#06013d', '#06023e', '#07043e', ...) The same color map is returned regardless of how it is accessed: >>> cp.cmap.cp_lemon_lime is cp.cmap['cp_lemon_lime'] True >>> cp.palette.cp_blue is cp.palette['cp_blue'] True Most IDEs should support autocompletion for :data:`cmap ` and :data:`palette `. The available color maps can be listed using the :meth:`.keys() ` method of :data:`cmap ` or :data:`palette ` or by calling :func:`dir()` on either of these objects. They are also displayed in the :ref:`list-of-color-maps`.