Re: [Matplotlib-users] Adding a colorbar --- how?

[Virgil S. <vs...@it...>]

On 16-Jun-14 00:46, Raymond Smith wrote:
> Hi Virgil,
>
> I did something very much like this recently by simply adding an axes 
> to my figure and using it to show a linspace of the data range off 
> which the line color was based. See 
> http://matplotlib.org/examples/color/colormaps_reference.html.
>
> Best,
> Ray
>
>
> On Sun, Jun 15, 2014 at 6:17 PM, Virgil Stokes <vs...@it... 
> <mailto:vs...@it...>> wrote:
>
>     There are some rather nice and useful matplotlib examples for
>     colormaps that are shown at:
>
>     http://nbviewer.ipython.org/github/dpsanders/matplotlib-examples/blob/master/colorline.ipynb
>
>     In*Example 1.  Sine wave colored by time (uses the defaults for
>     colorline)*, how can one add a colorbar?
>
>     --V
>
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Thanks for your response to my request, Ray. I had looked at this 
approach earlier; but, what I really need is something like is produced 
by the following code for the cax object:

"""Produce custom labelling for a colorbar.

  Original Script:  Scott Sinclair
     Modification:  V. Stokes
"""

import matplotlib.pyplot as plt
import numpy             as np
import matplotlib.colors as col
from matplotlib   import cm
from numpy.random import randn

def register_cmap():
     """
      Purpose: define colormap using the from_List() method as a
               segmented list and register it.
     """
     cmap_Name  = 'reyegr'    # my colormap name
     startcolor = '#00AF33'   # truegreen
     midcolor   = '#FFE600'   # yolk (a medium dark yellow)
     endcolor   = '#FF0033'   # bright red
     cmap2 = col.LinearSegmentedColormap.from_list(cmap_Name,
[startcolor,midcolor,endcolor])
     cm.register_cmap(cmap=cmap2)
     return cm.get_cmap(cmap_Name)  # my new cmap for 'reylgr'

#-----------------------------------------------------------------------------
my_cmap = register_cmap()

## Vertical colorbar-1
fig, ax = plt.subplots()

data = np.clip(randn(250, 250), -1, 1)

cax = ax.imshow(data, interpolation='nearest', cmap=my_cmap)
ax.set_title('Gaussian noise with vertical colorbar')
# Add colorbar, make sure to specify tick locations to match desired 
ticklabels
cbar = fig.colorbar(cax, ticks=[-1, 0, 1])
cbar.ax.set_yticklabels(['<-1', '0', '> 1'])# vertically oriented colorbar

## Vertical colorbar-2
fig, ax = plt.subplots()

data = np.clip(randn(50, 50), -1, 1)

#cax = ax.imshow(data, interpolation='nearest', cmap=cm.coolwarm)
cax = ax.imshow(data, interpolation='nearest', cmap=my_cmap)
ax.set_title('Gaussian noise with vertical colorbar')

# Add colorbar, make sure to specify tick locations to match desired 
ticklabels
cbar = fig.colorbar(cax, ticks=[-1, 0, 1])
# Vertically oriented (by default) colorbar
cbar.ax.set_yticklabels(['Low', 'Medium', 'High'])

## Horizontal colorbar
fig, ax = plt.subplots()
#
cax = ax.imshow(data, interpolation='nearest', cmap=my_cmap)
ax.set_title('Gaussian noise with horizontal colorbar')

cbar = fig.colorbar(cax, ticks=[-1, 0, 1], orientation='horizontal')
cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])# horizontal colorbar

plt.show()

But, for a colorline object, which was referenced in the link given in 
my earlier email.

--V