Style: viscid-colorblind
========================

.. image:: _images/viscid-colorblind.png
   :scale: 75 %

Style Sheet
~~~~~~~~~~~

Note that this is not the same syntax as the original style sheet.

.. code-block:: text

   axes.prop_cycle: cycler(color, [#004358, #FD7400, #3DA88E, #83522B,
                    #00D4FD, #E2D893])
   image.cmap: viridis
   lines.linewidth: 2.275
   lines.markeredgewidth: 0.0
   lines.markersize: 9.1
   patch.linewidth: 0.39
   viscid.symmetric_cmap: RdBu_r
   

Example Source Code
~~~~~~~~~~~~~~~~~~~

.. code-block:: python

   import matplotlib
   from matplotlib.colors import ListedColormap
   import numpy as np
   import viscid
   from viscid.plot import vpyplot as vlt
   import matplotlib.pyplot as plt
   
   matplotlib.rcParams.update(matplotlib.rcParamsDefault)
   
   fld = viscid.empty((np.linspace(1, 5, 64), np.linspace(1, 5, 64)),
                      name="F", pretty_name="Generic Field")
   X, Y = fld.get_crds(shaped=True)
   fld[:, :] = 1e-4 * (np.sin(X)**10 + np.cos(10 + X * Y) * np.cos(X))
   
   with plt.style.context(("viscid-colorblind",)):
       fig = plt.figure(figsize=(11, 7))
   
       ax = plt.subplot2grid((2, 9), (0, 0), rowspan=2)
       pal = vlt.get_current_colorcycle()
       size = 1
       n = len(pal)
       ax.imshow(np.arange(n).reshape(n, 1), cmap=ListedColormap(list(pal)),
                 interpolation="nearest", aspect="auto")
       ax.set_xticks([])
       ax.set_yticks([])
       ax.set_xticklabels([])
       ax.set_yticklabels([])
       ax.set_ylabel("Color Cycle")
   
       plt.subplot2grid((2, 9), (0, 1), rowspan=2, colspan=4)
       x = np.linspace(0, 2 * np.pi)
       for phase in np.linspace(0, np.pi / 4, n):
           plt.plot(x, (1 + np.sqrt(phase)) * np.sin(x - phase),
                        label=r"$\phi = {0:.2g}$".format(phase))
       plt.legend(loc=0)
   
       plt.subplot2grid((2, 9), (0, 5), colspan=4)
       vlt.plot(fld)
       plt.title("Sequential")
   
       plt.subplot2grid((2, 9), (1, 5), colspan=4)
       vlt.plot(fld, lin=0)
       plt.title("Symmetric")
   
       vlt.auto_adjust_subplots(subplot_params=dict(top=0.93, bottom=0.1))
       txt = ("Matplotlib Version: {0}\nViscid Version: {1}"
              "".format(matplotlib.__version__, viscid.__version__))
       fig.text(0.05, 0.01, txt, color='grey', size='small')