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 <v...@it.uu.se
<mailto:v...@it.uu.se>> 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
------------------------------------------------------------------------------
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Find What Matters Most in Your Big Data with HPCC Systems
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