从指定的x/y值填充直方图

2024-09-28 22:28:40 发布

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我有以下柱状图:

BPT Diagnostic Diagram

现在,我相信你们中的很多人都会给我指出matplotlib库和其他资源的方向,但是出于某种原因,我想到的,以及随后从各种不同来源读取的内容与我的轴柱状图不太相符。(如果我错了,请纠正我!)在

我的问题是:

如何从(2,2,1)和(2,2,4)图中直方图上叠加的行分割的位置填充直方图。在

x直方图(位置2,2,1)在x = -0.222处绘制了vline,而y直方图在y = 0.49处绘制了hline。在

示例工作代码(仅针对原始数组中的任何数组进行了修改),如下所示:

import numpy as np
import scipy
import matplotlib as mpl
import matplotlib.pyplot as plt
import pylab

X = 0.32, 0.41, 0.45, 0.53, -0.23,  0.34,  0.35, 0.47, 0.48, 0.33, 0.49, -0.10, -0.23,       0.45, 0.19
Y = 0.56, 0.67, 0.49, 0.61,  0.00, -0.02, -0.12, 0.12, 0.23, 0.44, 0.56,  0.13,  0.56, 0.67, 0.28

binsize = 0.1

min_x_data, max_x_data   = np.min(X), np.max(X)
num_x_bins               = np.floor((max_x_data - min_x_data) / binsize)

min_y_data, max_y_data   = np.min(Y), np.max(Y)
num_y_bins               = np.floor((max_y_data - min_y_data) / bin size)

fig = plt.figure(221)

axScatter = fig.add_subplot(223)
axScatter.scatter(X, Y)
axScatter.set_xlim(-2.0, 1.5)
axScatter.set_ylim(-2.0, 2.5)

axHistX = fig.add_subplot(221)
axHistX.set_xlim(-2.0, 1.5)
axHistX.set_ylim(0, 10)

axHistY = fig.add_subplot(224)
axHistY.set_xlim(0, 10)
axHistY.set_ylim(-2.0, 2.5)

axHistX.hist(X, num_x_bins, ec='0.3', fc='none', histtype='step')
axHistY.hist(Y, num_y_bins, ec='0.3', fc='none', histtype='step', orientation='horizontal')

axScatter.axhline(y=0.49, xmin=0, xmax=1, linestyle='-.',c='k')
axScatter.axvline(x=-0.222, ymin=0, ymax=1, linestyle='-.',c='k')
axHistX.axvline(x=-0.222, ymin=0, ymax=1, linestyle='-.',c='k')
axHistY.axhline(y=0.49, xmin=0, xmax=1, linestyle='-.',c='k')

plt.show()

Tags: importdatamatplotlibnpfig直方图minnum
1条回答
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1楼 · 发布于 2024-09-28 22:28:40

所以在这里我最后一次尝试,但强烈建议您学习python和 matplotlib。在

def step_hist(ax, X, num_x_bins=10,               
              hatch_from= -2, hatch_till=0.5,
              orientation='h'):
    #make histogram by hand.
    hist, edges = np.histogram(X, bins=num_x_bins)
    #generate (x,y) points for a step-plot
    edges = np.repeat(edges, 2)
    hist = np.hstack((0, np.repeat(hist, 2), 0))
    #plot step_hist
    #indices where we want the  plot hatached
    fill_region  =(hatch_from<edges)&(edges<hatch_till) 
    #apply hatching my using fill_between.
    if orientation == 'h':    
        ax.fill_between(edges[fill_region], 
                        hist[fill_region], 0, 
                        color='none', edgecolor='k',
                        hatch='xxx')
        ax.plot(edges, hist, 'k')
    elif orientation == 'v':
        ax.fill_betweenx(edges[fill_region], 
                        hist[fill_region], 0, 
                        color='none', edgecolor='k',
                        hatch='xxx')
        ax.plot(hist, edges, 'k')

a, b = np.random.randn(500), np.random.randn(500)

ax_top = plt.subplot(221)
ax_right = plt.subplot(224)
ax_cent = plt.subplot(223)

ax_cent.scatter(a, b, c='k')
step_hist(ax_top, a)
step_hist(ax_right, a, orientation='v')

resulting picture

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