python - Make reverse diagonals white in heatmap -

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i'm trying seen on image given below, enter image description here

just setting reverse diagonals white color left. couldn't set them white. chart takes integer values , don't know integer value corresponding of white color.

thank!

edited:

here code;

import math matplotlib import pyplot plt matplotlib import cm cm import pylab import numpy np matplotlib.collections import linecollection  class heatmap:     def __init__(self, selectedlines):         self.selectedlines = selectedlines       def getheapmap(self):         figure = plt.figure()          if len(self.selectedlines) != 0:              self.map = self.createtestmapdata(len(self.selectedlines),                len(self.selectedlines))               maxvalueinmap = self.findmaxvalueinmap(self.map)              x = np.arange(maxvalueinmap + 1)             ys = [x + in x]             ax = figure.add_subplot(111)             ax.imshow(self.map, cmap=cm.jet, interpolation='nearest')              '''             left side label of chart created according selected values             checkbox group.             '''             leftsidelabelsize = len(self.selectedlines)             sidelabels = []             line in self.selectedlines:                 sidelabels.append(line.text())             pos = np.arange(leftsidelabelsize)             '''             left side labels set code below.             '''             pylab.yticks(pos, sidelabels)             plt.xticks(pos, sidelabels)             self.numrows, self.numcols = self.map.shape             ax.format_coord = self.format_coord              line_segments = linecollection([zip(x, y) y in ys],                 linewidths=(0.5, 3, 1.5, 2),                 linestyles='solid')             line_segments.set_array(x)             axcb = figure.colorbar(line_segments)          return figure      def format_coord(self, x, y):         col = int(x + 0.5)         row = int(y + 0.5)         if col >= 0 , col < self.numcols , row >= 0 , row < self.numrows:             z = self.map[row, col]             return 'x=%1.4f, y=%1.4f, z=%1.4f' % (x, y, z)         else:             return 'x=%1.4f, y=%1.4f' % (x, y)      def createtestmapdata(self, xsize, ysize):         resultmap = 10 * np.random.rand(xsize, ysize)         #setting reverse diagonal here. set 0 gives blue.         # want set white         index in range(0, int(math.sqrt(resultmap.size))):             resultmap[index][((math.sqrt(resultmap.size) - 1) - index )] = 0          return  resultmap      def findmaxvalueinmap(self, map):         return np.amax(map)

the values generated randomly @ moment. code above gives gui like;

enter image description here

you can make own colormap, or adjust existing 1 :)

enter image description here

here's code above plot, explainations in comments:

import matplotlib pylab import * import numpy np  #create test data 0 valued diagonal: data = np.random.random_sample((25, 25)) rows, cols = np.indices((25,25)) data[np.diag(rows, k=0), np.diag(cols, k=0)] = 0  #create new colormap, white 0  #(can take rgb values, (255,255,255): colors = [('white')] + [(cm.jet(i)) in xrange(1,256)] new_map = matplotlib.colors.linearsegmentedcolormap.from_list('new_map', colors, n=256)  pcolor(data, cmap=new_map) colorbar() savefig('map.png') show()

alternatively, mask data, , set mask color:

#create test data: data = np.random.random_sample((25, 25)) #create diagonal mask: mask = np.diag(np.ones(25)) #apply mask data: masked_data = ma.masked_array(data, mask) #set mask color white: cm.jet.set_bad(color='white', alpha=none) #for work use pcolormesh instead of pcolor: pcolormesh(masked_data, cmap=cm.jet) colorbar() show()

this produces same result, may suit needs better can set cell white, , white doesn't show on colorbar (see bottom of above colorbar):

enter image description here


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