如何在 matplotlib 中使用不同的 xlimit 和 x 轴的大小绘制子图? [英] How can I do subplots in matplotlib with differents xlimit and size of axis-x?

问题描述

我该如何解决这个问题?我想用 matplotlib 做 4 个子图，我使用了 subplot 选项，但结果只是一个大图.我不知道有什么问题.我想看到四个子图，每个子图都有标题，以及它们的副标题.

How can I solve this? I want to do 4 subplots with matplotlib, I have used the subplot option but the result is just a big plot. I don't have idea what is the problem. I want to see four subplots, each one with title, and a suptitle for them.

我不知道如何解决?

你能帮我解决一下吗?非常感谢

Can you help me please to fix it? Thanks a lot

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from __future__ import unicode_literals
from matplotlib.collections import LineCollection
import matplotlib.patches as mpatches
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.ticker as tkr
from pylab import text


with open("file1.txt") as f:
         m1 = map(float,f)

with open ("file2.txt") as f:
         m2 = map(float, f)

fig, ax = plt.subplots(sharey='row')
fig.set_figwidth(18)  #Width figure
fig.set_figheight(12) #Height figure

plt.rcParams['figure.dpi'] = 300
plt.subplots_adjust(wspace=0.18, hspace=0.2)

fig.suptitle('PLOTS', y=0.93, fontsize=15)

# Plot
plt.subplot(421)
y = np.array(m1)
x = np.arange(len(y))
threshold = 0.5
segments_x = np.r_[x[0], x[1:-1].repeat(2), x[-1]].reshape(-1, 2)
segments_y = np.r_[y[0], y[1:-1].repeat(2), y[-1]].reshape(-1, 2)
linecolors = ['red' if y_[0] > threshold and y_[1] > threshold else 'blue'
              for y_ in segments_y]
segments = [zip(x_, y_) for x_, y_ in zip(segments_x, segments_y)]
ax = plt.axes()
ax.add_collection(LineCollection(segments, colors=linecolors))
ax.set_ylim(-0.06, 1.07)
ax.set_xlim(0,268)
blue_patch = mpatches.Patch(color='blue', label='ordenada')
red_patch = mpatches.Patch(color='red', label='desordenada')
plt.legend(handles=[blue_patch, red_patch], loc='lower left', fontsize=12)
plt.axhline(y=0.5, color='black', linestyle='--')
plt.title(r'Protein', fontsize=18)
plt.xlabel(r'# Residue', fontsize=16)
plt.ylabel(r'(%)', fontsize=16)
plt.xticks(size=12)
plt.yticks(size=12)
plt.xticks(np.arange(min(x), max(x)+1, 10))
plt.grid()
plt.tight_layout()

# Plot
plt.subplot(423)
p = np.array(m2)
o = np.arange(len(p))
threshold = 0.5
segments_o = np.r_[o[0], o[1:-1].repeat(2), o[-1]].reshape(-1, 2)
segments_p = np.r_[p[0], p[1:-1].repeat(2), p[-1]].reshape(-1, 2)
linecolors = ['red' if p_[0] > threshold and p_[1] > threshold else 'blue'
              for p_ in segments_p]
segments = [zip(o_, p_) for o_, p_ in zip(segments_o, segments_p)]
ax = plt.axes()
ax.add_collection(LineCollection(segments, colors=linecolors))
ax.set_ylim(-0.06, 1.07)
ax.set_xlim(0,383)
blue_patch = mpatches.Patch(color='blue', label='ordenada')
red_patch = mpatches.Patch(color='red', label='desordenada')
plt.legend(handles=[blue_patch, red_patch], loc='lower left', fontsize=12)
plt.axhline(y=0.5, color='black', linestyle='--')
plt.title(r'Protein', fontsize=18)
plt.xlabel(r'# Residue', fontsize=16)
plt.ylabel(r'(%)', fontsize=16)
plt.xticks(size=12)
plt.yticks(size=12)
plt.xticks(np.arange(min(o), max(o)+1, 10))
plt.grid()
plt.tight_layout()
plt.show()

#plt.savefig('figure.png', format='png', bbox_inches="tight", dpi=300)

我该如何解决这个问题?问题出在哪里?

How can I solve this? where is the problem?

推荐答案

您需要通过 matplotlib.pyplot.subplots,

You need to specify the number of plots you want to be created by matplotlib.pyplot.subplots,

nrows = 2
ncols = 2
fig, ax = plt.subplots(nrows, ncols, sharey='row')

这将创建一个形状为 (nrows, ncols) 的 axes 实例数组.然后您可以通过

which will create an array of axes instances with shape (nrows, ncols). You can then plot to individual axes via

ax[0,0].plot(...)

尽管为了为 axes 设置刻度属性、标签等，您需要使用函数的 axes 版本而不是 pyplot 版本.即

Although in order to set tick properties, labels, etc for the axes you need to use the axes versions of the functions instead of the pyplot versions. I.e.

ax[0, 0].set_xticks(...)
# instead of 
plt.xticks(...)

ax[0, 0].set_title(...)
# instead of 
plt.title(...)

ax[0, 0].set_xlabel(...)
# instead of
plt.set_xlabel(...)

这篇关于如何在 matplotlib 中使用不同的 xlimit 和 x 轴的大小绘制子图?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！