使用散景的加權數據的直方圖

Question

如何使用散景生成加權數據的直方圖？

在matplotlib，可以做到以下幾點：

from pylab import hist 
x = randn(100); w = rand(100) 
hist(x, weights=w) 

如何做同樣的事情在背景虛化？

Answer 1

基本上，你將權重傳遞給你的numpy的直方圖函數。

import numpy as np 

from bokeh.layouts import gridplot 
from bokeh.plotting import figure, show, output_file 

p1 = figure(title="Normal Distribution (μ=50, σ=20) and normal weights",tools="save", 
     background_fill_color="#E8DDCB") 

measured = np.random.normal(50, 20, 1000) 

myweights = np.random.normal(0, 1, 1000) 
hist, edges = np.histogram(measured, density=True, bins=10,weights=myweights) 

x = np.linspace(-2, 2, 1000) 
p1.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:], 
    fill_color="#036564", line_color="#033649") 
p1.legend.location = "top_left" 
p1.xaxis.axis_label = 'x' 
p1.yaxis.axis_label = 'Pr(x)' 

show(p1)