在matplotlib中制作log2缩放的热图 [英] making log2 scaled heatmap in matplotlib

问题描述

我想绘制matplotlib中倍数变化的热图，其中颜色以log2比例绘制，并自定义在色条中显示哪些刻度.我尝试了以下方法:

I want to plot a heatmap of fold changes in matplotlib, where the colors are plotted on a log2 scale, and customize which ticks are shown in the colorbar. I tried the following:

import matplotlib.pylab as plt
import numpy as np
import matplotlib.colors
from matplotlib.colors import SymLogNorm, LogNorm

mat1 = np.clip(np.random.normal(20, 10, [20, 20]), a_min=0, a_max=500)
mat2 = np.clip(np.random.normal(10, 5, [20, 20]), a_min=0, a_max=500)
mat = np.clip(mat1 / mat2, a_min=0, a_max=500)
plt.figure()
print mat
cmap = plt.cm.get_cmap("seismic")
ticks = np.array([1/float(50), 1/float(20), 1, 20, 50])
# how to make these ticks spaced out on a log2 and not log10 scale?
plt.pcolormesh(mat, cmap=cmap, norm=SymLogNorm(linthresh=0.01, vmin=1/50., vmax=50.))
p = plt.colorbar(ticks=ticks)
plt.show()

我希望将1的倍数变化显示为白色，所以我使用了地震色图.

I want fold change of 1 to appear as white so I used the seismic colormap.

问题:如何使颜色以log2的比例而不是log10的比例?刻度线是否也显示为log2值而不是未记录的值?

Question: How can I make the colors spaced in log2 scale, and not log10? And also have the ticks show up as log2 values rather than the unlogged values?

如果我尝试使用LogNorm而不是SymLogNorm，则刻度标签和我的刻度不会显示:

If I try to use LogNorm instead of SymLogNorm then the tick labels and my ticks do not show up:

# This does not work -- ticks do not show
plt.pcolormesh(mat, cmap=cmap, norm=LogNorm(vmin=1/50., vmax=50.))
p = plt.colorbar(ticks=ticks)

我知道SymLogNorm用于负数据(我没有).我之所以只使用它，是因为LogNorm

I know SymLogNorm is meant for negative data (which I don't have). I only used it because of this tick issue with LogNorm

推荐答案

您可以将colorbar对象的locator设置为以2为底的LogLocator.然后，您需要调用p.update_ticks().

You could set the locator of the colorbar object to a LogLocator with a base of 2. You then need to call p.update_ticks().

plt.pcolormesh(mat, cmap=cmap, norm=SymLogNorm(linthresh=0.01, vmin=1/50., vmax=50.))

p = plt.colorbar()
p.locator=ticker.LogLocator(base=2)
p.update_ticks()

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