将 matplotlib 直方图除以最大 bin 值

Question

I want to plot multiple histograms on the same plot and I need to compare the spread of the data. I want to do this by dividing each histogram by its maximum value so all the distributions have the same scale. However, the way matplotlib's histogram function works, I have not found an easy way to do this.

This is because n in

n, bins, patches = ax1.hist(y, bins = 20, histtype = 'step', color = 'k')

Is the number of counts in each bin but I can not repass this to hist since it will recalculate.

I have attempted the norm and density functions but these normalise the area of the distributions, rather than the height of the distribution. I could duplicate n and then repeat the bin edges using the bins output but this is tedious. Surely the hist function must allow for the bins values to be divided by a constant?

Example code is below, demonstrating the problem.

y1 = np.random.randn(100)
y2 = 2*np.random.randn(50)
x1 = np.linspace(1,101,100)
x2 = np.linspace(1,51,50)
gs = plt.GridSpec(1,2, wspace = 0, width_ratios = [3,1])
ax = plt.subplot(gs[0])
ax1 = plt.subplot(gs[1])
ax1.yaxis.set_ticklabels([])   # remove the major ticks

ax.scatter(x1, y1, marker='+',color = 'k')#, c=SNR, cmap=plt.cm.Greys)
ax.scatter(x2, y2, marker='o',color = 'k')#, c=SNR, cmap=plt.cm.Greys)
n1, bins1, patches1 = ax1.hist(y1, bins = 20, histtype = 'step', color = 'k',linewidth = 2, orientation = 'horizontal')
n2, bins2, patched2 = ax1.hist(y2, bins = 20, histtype = 'step', linestyle = 'dashed', color = 'k', orientation = 'horizontal')

Answer 1

我不知道 matplotlib 默认情况下是否允许这种标准化，但我自己编写了一个函数来完成此操作。

它获取 plt.hist 的输出n（bins如上所述），然后将其传递给下面的函数。

def hist_norm_height(n,bins,const):
    ''' Function to normalise bin height by a constant. 
        Needs n and bins from np.histogram or ax.hist.'''

    n = np.repeat(n,2)
    n = float32(n) / const
    new_bins = [bins[0]]
    new_bins.extend(np.repeat(bins[1:],2))
    return n,new_bins[:-1]

现在要绘制图（我喜欢步进直方图），请将其传递给 plt.step。

例如plt.step(new_bins,n)。这将为您提供一个高度由常数标准化的直方图。