Python:直方图的面积归一化为除1以外的值 [英] Python: Histogram with area normalized to something other than 1
问题描述
有没有办法告诉matplotlib对直方图进行规范化",以使其面积等于指定值(而不是1)?
Is there a way to tell matplotlib to "normalize" a histogram such that its area equals a specified value (other than 1)?
其中的标准= 0"选项
The option "normed = 0" in
n, bins, patches = plt.hist(x, 50, normed=0, histtype='stepfilled')
只是将其恢复为频率分布.
just brings it back to a frequency distribution.
推荐答案
只需将其计算并归一化为您想要的任何值,然后使用bar
绘制直方图即可.
Just calculate it and normalize it to any value you'd like, then use bar
to plot the histogram.
在旁注中,这将使所有条形图的区域标准化为normed_value
.原始金额不是为normed_value
(尽管很容易做到这一点,如果您愿意的话).
On a side note, this will normalize things such that the area of all the bars is normed_value
. The raw sum will not be normed_value
(though it's easy to have that be the case, if you'd like).
例如
import numpy as np
import matplotlib.pyplot as plt
x = np.random.random(100)
normed_value = 2
hist, bins = np.histogram(x, bins=20, density=True)
widths = np.diff(bins)
hist *= normed_value
plt.bar(bins[:-1], hist, widths)
plt.show()
因此,在这种情况下,如果我们要集成(将高度乘以宽度乘以宽度)垃圾箱,我们将得到2.0而不是1.0. (即(hist * widths).sum()
将产生2.0
)
So, in this case, if we were to integrate (sum the height multiplied by the width) the bins, we'd get 2.0 instead of 1.0. (i.e. (hist * widths).sum()
will yield 2.0
)
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