matplotlib scatter_hist，在直方图中具有逐步填充的直型 [英] matplotlib scatter_hist with stepfilled histtype in histogram

问题描述

我修改了scatter_hist.py示例，发现了此处有两个数据集密谋.

I modified scatter_hist.py example found here to have two data sets to be plotted.

我想使用"stepfilled"类型的直方图，但是如果我将类型设置为"stepfilled"，则Y轴直方图(方向=水平")不起作用.

I'd like to have histograms with "stepfilled" type, but somehow if I set the type "stepfilled" the Y-axis histogram (orientation = "horizontal") is not working.

还有其他方法可以使直方图看起来像阶梯填充"样式吗?还是我做错了什么?

Is there any other way to do the histogram to look like "stepfilled"-style or am I doing something wrong?

这是我的带有histt​​ype ="bar"的代码，以说明我尝试执行的操作.更改为

Here is my code with histtype = "bar" to show the idea what I try to do. Change it to

histtype="stepfilled"

获取奇怪的直方图:

import numpy as np
import matplotlib.pyplot as plt

# the random data
x = np.random.randn(1000)
y = np.random.randn(1000)

x_vals = [x]
y_vals = [y]
x_vals.append( np.random.randn( 300 ) )
y_vals.append( np.random.randn( 300 ) )

fig = plt.figure(1, figsize=(5.5,5.5))

from mpl_toolkits.axes_grid1 import make_axes_locatable

colour_LUT = ['#0000FF',
              '#00FF00']

# the scatter plot:
xymax = np.max(np.fabs(x))
colors = []
axScatter = plt.subplot(111)
for i in range( len(x_vals ) ):
    colour = colour_LUT[i]
    xymax = np.max( [np.max(np.fabs(x)), np.max(np.fabs(y)), xymax ] )
    axScatter.scatter( x_vals[i], y_vals[i], color = colour )
    colors.append(colour)

axScatter.set_aspect(1.)

# create new axes on the right and on the top of the current axes
# The first argument of the new_vertical(new_horizontal) method is
# the height (width) of the axes to be created in inches.
divider = make_axes_locatable(axScatter)
axHistx = divider.append_axes("top", 1.2, pad=0.1, sharex=axScatter)
axHisty = divider.append_axes("right", 1.2, pad=0.1, sharey=axScatter)

# make some labels invisible
plt.setp(axHistx.get_xticklabels() + axHisty.get_yticklabels(),
         visible=False)

# now determine nice limits by hand:
binwidth = 0.25

lim = ( int(xymax/binwidth) + 1) * binwidth

bins = np.arange(-lim, lim + binwidth, binwidth)
histtype = "bar"
axHistx.hist(x_vals, bins=bins, histtype= histtype, color=colors)
axHisty.hist(y_vals, bins=bins, orientation='horizontal',histtype= histtype, color=colors)

# the xaxis of axHistx and yaxis of axHisty are shared with axScatter,
# thus there is no need to manually adjust the xlim and ylim of these
# axis.

#axHistx.axis["bottom"].major_ticklabels.set_visible(False)
for tl in axHistx.get_xticklabels():
    tl.set_visible(False)
axHistx.set_yticks([0, 50, 100])

#axHisty.axis["left"].major_ticklabels.set_visible(False)
for tl in axHisty.get_yticklabels():
    tl.set_visible(False)
axHisty.set_xticks([0, 50, 100])

plt.draw()
plt.show()

谢谢您的帮助！

这是我在Windows环境中使用matplotlib 1.0.0收到的图像. 使用histt​​ype ="bar"我有这个:

Here is the images which I receive in windows environment with matplotlib 1.0.0. With histtype="bar" I have this:

并使用histt​​ype ="stepfilled"，我有这个:

and with histtype="stepfilled" I have this:

推荐答案

文档仅在使用'bar'和'barstacked'时提到了多个数据的特殊情况，我认为这意味着对于其他两种类型而言，这没有正确实现.更改您的代码以添加多个直方图，而不是只对我有用:

The documentation only mentions special cases for multiple data when using 'bar' and 'barstacked', which I would assume means that this isn't properly implemented for the other two types. Changing your code to add multiple histograms instead of just one worked for me:

histtype = "stepfilled"
for i in xrange(len(x_vals)):
    axHistx.hist(x_vals[i], bins=bins, histtype= histtype, color=colors[i])
    axHisty.hist(y_vals[i], bins=bins, orientation='horizontal',histtype= histtype, color=colors[i])

这篇关于matplotlib scatter_hist，在直方图中具有逐步填充的直型的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！