如何在python中启用对辅助轴(twiny)的共享 [英] How to to enable sharing for the secondary axis (twiny) in python

问题描述

我正在尝试为主轴和次轴启用共享.下面的代码说明了示例图.该图包含两个水平轴，主轴网格显示为绿色，而另一个轴显示为红色网格.

I'm trying to enable sharing for both primary and secondary axis. The example plot is illustrated by the code below. The plot contains two horizontal axes, the primary axis grid is shown in green, while the other axis has red grid.

#!/usr/bin/python

# -*- coding: utf-8 -*-

import numpy as np
import matplotlib.pyplot as plt

FIRST = 0.0
LAST  = 2.0
STEP  = 0.01

t = np.arange(FIRST, LAST, STEP)

s1 = np.sin(2*np.pi*t)
s2 = np.exp(-t)
s3 = s1*s2

###############################################################################

plt.rc('axes', grid=True)
plt.rc('grid', color='0.75', linestyle='-', linewidth=0.5)

fig3 = plt.figure()
ax1primary = plt.subplot2grid((4,3), (0,0), colspan=3, rowspan=2)
ax2primary = plt.subplot2grid((4,3), (2,0), colspan=3, sharex=ax1primary)
ax3primary = plt.subplot2grid((4,3), (3,0), colspan=3, sharex=ax1primary)

ax1primary.plot(t,s1)
ax1primary.set_yticks(np.arange(-0.9, 1.0, 0.3))
ax1primary.xaxis.grid(color='green')

ax2primary.plot(t[:150],s2[:150])
ax2primary.set_yticks(np.arange(0.3, 1, 0.2))
ax2primary.xaxis.grid(color='green')

ax3primary.plot(t[30:],s3[30:])
ax3primary.plot([0,2],[0.2,0.2],'m')
ax3primary.set_yticks(np.arange(-0.4, 0.7, 0.2))
ax3primary.xaxis.grid(color='green')

INDEX = t[np.where(abs(s3-0.2) < 0.005)[0]]
INDEX = np.append(INDEX, LAST)
INDEX = np.insert(INDEX, 0, FIRST)

ax1secondary = ax1primary.twiny()
ax1secondary.set_xticks(INDEX)
ax1secondary.xaxis.grid(color='red')

ax2secondary = ax2primary.twiny()
ax2secondary.set_xticks(INDEX)
ax2secondary.xaxis.grid(color='red')

ax3secondary = ax3primary.twiny()
ax3secondary.set_xticks(INDEX)
ax3secondary.xaxis.grid(color='red')

plt.tight_layout()
plt.subplots_adjust(hspace=0)

for ax in [ax1primary, ax2primary, ax2secondary, ax3secondary]:
    plt.setp(ax.get_xticklabels(), visible=False)

###############################################################################

plt.show()

在静态图上没有问题.该问题在以下情况时变得很明显您开始平移(或缩放)其中一个子图.主轴(绿色)完美地保持同步并在所有子图内移动，而次级(红色)轴未对准且仅在活动子图中移动.

On a static figure there is no issue. The problem becomes obvious when you start panning (or zooming) one of the subplots. The primary (green) axis stays perfectly in sync and moves within all subplots, but the secondary (red) axis gets misaligned and moves only within the active subplot.

有没有办法解决这个问题?

Is there a way to fix this?

我要实现的行为如下:

我需要一个通用的主要"x 轴(对于所有三个子图)，其底部带有刻度，另一个常见的次要"x 轴(对于所有三个子图)带有顶部的刻度图.主轴是标准的规则间隔轴，而次级轴则显示自定义的刻度线(例如零交叉点).以上示例均满足此要求.现在，在平移和缩放子图时，还需要使它满足.

I need one common "primary" x-axis (for all three subplots) with the ticks on the bottom of the figure and another common "secondary" x-axis (for all three subplots) with the ticks on the top of the figure. The primary axis is a standard regularly spaced axis, while the secondary axis shows the customized ticks (for example zero crossings) This is all satisfied in the example above. Now I need it to be satisfied also while panning and zooming subplots.

推荐答案

不幸的是，提出的回调解决方案不够健壮.大多数时候平移工作正常，但缩放是一场灾难.尽管如此，网格仍然经常会错位.

Unfortunately the proposed callback solution is not robust enough. Most of the time panning works fine, but zooming is a disaster. Still, too often the grids get misaligned.

在我找到如何改进回调解决方案之前，我决定编写一个自定义网格并注释图中的值.

Until I find out how to improve the callback solution, I decided to code a custom grid and annotate the values within the plot.

#!/usr/bin/python

# -*- coding: utf-8 -*-

import numpy as np
import matplotlib.pyplot as plt

FIRST = 0.0
LAST  = 2.0
STEP  = 0.01

t = np.arange(FIRST, LAST, STEP)

s1 = np.sin(2*np.pi*t)
s2 = np.exp(-t)
s3 = s1*s2

###############################################################################

plt.rc('axes', grid=True)
plt.rc('grid', color='0.75', linestyle='-', linewidth=0.5)

fig3 = plt.figure()
ax1primary = plt.subplot2grid((4,3), (0,0), colspan=3, rowspan=2)
ax2primary = plt.subplot2grid((4,3), (2,0), colspan=3, sharex=ax1primary)
ax3primary = plt.subplot2grid((4,3), (3,0), colspan=3, sharex=ax1primary)

ax1primary.plot(t,s1)
ax1primary.set_yticks(np.arange(-0.9, 1.0, 0.3))
ax1primary.xaxis.grid(color='green')
ax1primary.set_ylim(-1, 1)

ax2primary.plot(t[:150],s2[:150])
ax2primary.set_yticks(np.arange(0.3, 1, 0.2))
ax2primary.xaxis.grid(color='green')
ax2primary.set_ylim(0.2, 1)

ax3primary.plot(t[30:],s3[30:])
ax3primary.plot([0,2],[0.2,0.2],'m')
ax3primary.set_yticks(np.arange(-0.4, 0.7, 0.2))
ax3primary.xaxis.grid(color='green')
ax3primary.set_ylim(-0.6, 0.8)

INDEX = np.where(abs(s3-0.2) < 0.005)[0]

for i in range(0, len(INDEX)):
    ax1primary.annotate(t[INDEX[i]], xy=(t[INDEX[i]], 0))

ax1primary.plot([t[INDEX], t[INDEX]], [-1e9 * np.ones(len(INDEX)), 1e9 * np.ones(len(INDEX))], 'r')
ax2primary.plot([t[INDEX], t[INDEX]], [-1e9 * np.ones(len(INDEX)), 1e9 * np.ones(len(INDEX))], 'r')
ax3primary.plot([t[INDEX], t[INDEX]], [-1e9 * np.ones(len(INDEX)), 1e9 * np.ones(len(INDEX))], 'r')

plt.tight_layout()
plt.subplots_adjust(hspace=0)

for ax in [ax1primary, ax2primary]:
    plt.setp(ax.get_xticklabels(), visible=False)

###############################################################################

plt.show()

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