我正在尝试绘制散点矩阵。我正在建立这个线程中给出的示例matplotlib中有制作散点图矩阵的函数吗?。在这里,我只是稍微修改了代码,使轴对所有子图都可见。修改后的代码如下
import itertools
import numpy as np
import matplotlib.pyplot as plt
def main():
np.random.seed(1977)
numvars, numdata = 4, 10
data = 10 * np.random.random((numvars, numdata))
fig = scatterplot_matrix(data, ['mpg', 'disp', 'drat', 'wt'],
linestyle='none', marker='o', color='black', mfc='none')
fig.suptitle('Simple Scatterplot Matrix')
plt.show()
def scatterplot_matrix(data, names, **kwargs):
"""Plots a scatterplot matrix of subplots. Each row of "data" is plotted
against other rows, resulting in a nrows by nrows grid of subplots with the
diagonal subplots labeled with "names". Additional keyword arguments are
passed on to matplotlib's "plot" command. Returns the matplotlib figure
object containg the subplot grid."""
numvars, numdata = data.shape
fig, axes = plt.subplots(nrows=numvars, ncols=numvars, figsize=(8,8))
fig.subplots_adjust(hspace=0.05, wspace=0.05)
for ax in axes.flat:
# Hide all ticks and labels
ax.xaxis.set_visible(True)
ax.yaxis.set_visible(True)
# # Set up ticks only on one side for the "edge" subplots...
# if ax.is_first_col():
# ax.yaxis.set_ticks_position('left')
# if ax.is_last_col():
# ax.yaxis.set_ticks_position('right')
# if ax.is_first_row():
# ax.xaxis.set_ticks_position('top')
# if ax.is_last_row():
# ax.xaxis.set_ticks_position('bottom')
# Plot the data.
for i, j in zip(*np.triu_indices_from(axes, k=1)):
for x, y in [(i,j), (j,i)]:
axes[x,y].plot(data[x], data[y], **kwargs)
# Label the diagonal subplots...
for i, label in enumerate(names):
axes[i,i].annotate(label, (0.5, 0.5), xycoords='axes fraction',
ha='center', va='center')
# Turn on the proper x or y axes ticks.
for i, j in zip(range(numvars), itertools.cycle((-1, 0))):
axes[j,i].xaxis.set_visible(True)
axes[i,j].yaxis.set_visible(True)
fig.tight_layout()
plt.xticks(rotation=45)
fig.show()
return fig
main()
我似乎无法旋转所有子图的 x 轴文本。可以看出,我尝试了 plt.xticks(rotation=45) 技巧。但这似乎仅对最后一个子图进行旋转。