在热图中使反向对角线为白色

Question

我正试着做一些如下图所示的事情，

只需设置反向对角线白色就可以了。我不能把它们设成白色。图表采用整数值，我不知道什么整数值对应白色。

谢谢！

编辑：

这是密码

import math
from matplotlib import pyplot as plt
from matplotlib import cm as cm
import pylab
import numpy as np
from 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 + i for i in x]
            ax = figure.add_subplot(111)
            ax.imshow(self.map, cmap=cm.jet, interpolation='nearest')

            '''
            Left side label of the chart is created according to selected values
            from a checkbox group.
            '''
            leftSideLabelSize = len(self.selectedLines)
            sideLabels = []
            for line in self.selectedLines:
                sideLabels.append(line.text())
            pos = np.arange(leftSideLabelSize)
            '''
            Left side labels are set with the 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) for 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 and col < self.numcols and row >= 0 and 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 is here. Now it is set with zero but it gives blue.
        # I want it to be set as white
        for 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)

此时，这些值是随机生成的。上面的代码提供了一个类似于gui的界面

Answer 1

您可以创建自己的颜色映射，或调整现有的颜色映射：）

以下是上述情节的代码，注释中有解释：

import matplotlib
from pylab import *
import numpy as np

#Create test data with zero 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, with white for zero 
#(can also take RGB values, like (255,255,255):
colors = [('white')] + [(cm.jet(i)) for 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()

或者，可以屏蔽数据，并设置遮罩颜色：

#Create test data:
data = np.random.random_sample((25, 25))
#Create a diagonal mask:
mask = np.diag(np.ones(25))
#Apply mask to data:
masked_data = ma.masked_array(data, mask)
#Set mask color to white:
cm.jet.set_bad(color='white', alpha=None)
#for this to work we use pcolormesh instead of pcolor:
pcolormesh(masked_data, cmap=cm.jet)
colorbar()
show()

这会产生基本相同的结果，但可能更适合您的需要，因为您可以将任何单元格设置为白色，而且白色不会显示在颜色栏上（请参见上面颜色栏的底部）：

Answer 2

colormap由ax.imshow()中的cmap参数定义。您已经使用了jet颜色映射，所以您有cmap=cm.jet，这只是matplotlib中许多built-in color maps之一。你可以选择一个或定义自己的适合你的口味。