我修改了scatter_hist.py示例,发现here要绘制两个数据集。
我想使用“stepfilled”类型的直方图,但是如果我设置“stepfilled”类型,则Y轴直方图(orientation=“horizontal”)不起作用。
有没有其他方法可以使直方图看起来像“逐步填充”样式,或者我做错了什么?
这是我的histtype=“bar”代码,它显示了我的想法。把它改成
histtype="stepfilled"
要得到奇怪的直方图:
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()
谢谢你的帮助!
编辑:
这是我在windows环境下用matplotlib 1.0.0接收到的图像。 使用histtype=“bar”我有:
目前没有回答
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