具有不同限制的轴的 Matplotlib 方形大/小网格 [英] Matplotlib square major/minor grid for axes with different limits

问题描述

我有一个带有背景网格的图.即使 X 轴和 Y 轴的限制不同，我也需要网格单元是方形的(主网格和次网格单元).

I have a plot with a background grid. I need grid cells to be square (both major grid and minor grid cells) even though the limits of X and Y axes are different.

我目前的代码如下:

import matplotlib.pyplot as plt
import matplotlib.ticker as plticker
import numpy as np

data = [0.014,  0.84,  0.95, -0.42, -0.79,  0.84, 0.98,  1.10,   0.56, -0.49]


fig, ax = plt.subplots(figsize=(20, 5))
ax.minorticks_on()

# Set major and minor grid lines on X
ax.set_xticks(np.arange(0, 10, 0.2))
ax.xaxis.set_minor_locator(plticker.MultipleLocator(base=0.2 / 5.))
for xmaj in ax.xaxis.get_majorticklocs():
        ax.axvline(x=xmaj, ls='-', color='red', linewidth=0.8)
for xmin in ax.xaxis.get_minorticklocs():
    ax.axvline(x=xmin, ls=':', color='red', linewidth=0.6)

# Set major and minor grid lines on Y
ylim = int(np.ceil(max(abs(min(data)), max(data))))
yticks = np.arange(-ylim, ylim + 0.5, 0.5)
ax.set_yticks(yticks)
ax.yaxis.set_minor_locator(plticker.MultipleLocator(base=0.5 / 5.))
for ymaj in ax.yaxis.get_majorticklocs():
        ax.axhline(y=ymaj, ls='-', color='red', linewidth=0.8)
for ymin in ax.yaxis.get_minorticklocs():
    ax.axhline(y=ymin, ls=':', color='red', linewidth=0.6)

ax.axis([0, 10, -ylim, ylim])
fig.tight_layout()

# Plot
ax.plot(data)

# Set equal aspect ratio NOT WORKING
plt.gca().set_aspect('equal', adjustable='box')
plt.show()

将生成以下图:

大网格单元格每个包含 5 个较小的单元格.但是，大网格的纵横比不是 1.问题:如何确保大网格是方形的?

Large grid cells contain 5 smaller cells each. However, the aspect ratio of large grid is not 1. Question: How can I make sure that large grid is square?

编辑当前方法是设置与@ImportanceOfBeingErnest建议的相同的刻度位置，但更改Y标签:

EDIT Current approach is to set same tick locations as suggested by @ImportanceOfBeingErnest, but change Y labels:

ylim = int(np.ceil(max(abs(min(data)), max(data))))
yticks = np.arange(-ylim, ylim + 0.2, 0.2)

ax.set_yticks(yticks)

labels = ['{:.1f}'.format(v if abs(v) < 1e-3 else (1 if v > 0 else -1)*((0.5 - abs(v)%0.5) + abs(v))) 
          if i%2==0 else "" for i, v in enumerate(np.arange(-ylim, ylim, 0.2))]
ax.set_yticklabels(labels)

结果:似乎太过分了.

推荐答案

使用相等的纵横比并瞄准正方形网格时，两个轴都需要使用相同的刻度间距.这可以通过 MultipleLocator 实现，其中 x 轴和 y 轴的间隔需要相同.

When using equal aspect ratio and aiming for a square grid you would need to use the same tickspacing for both axes. This can be achieved with a MultipleLocator where the interval needs to be the same for x and y axis.

通常，可以使用 grid 命令创建网格.

In general, grids can be created with the grid command.

import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import numpy as np

data = [0.014,  0.84,  0.95, -0.42, -0.79,  0.84, 0.98,  1.10,   0.56, -0.49]


fig, ax = plt.subplots(figsize=(20, 5))
ax.minorticks_on()

# Set major and minor grid lines on X
ax.xaxis.set_major_locator(mticker.MultipleLocator(base=.5))
ax.xaxis.set_minor_locator(mticker.MultipleLocator(base=0.5 / 5.))

ax.yaxis.set_major_locator(mticker.MultipleLocator(base=.5))
ax.yaxis.set_minor_locator(mticker.MultipleLocator(base=0.5 / 5.))

ax.grid(ls='-', color='red', linewidth=0.8)
ax.grid(which="minor", ls=':', color='red', linewidth=0.6)

## Set limits
ylim = int(np.ceil(max(abs(min(data)), max(data))))
ax.axis([0, 10, -ylim, ylim])
plt.gca().set_aspect('equal', adjustable='box')
fig.tight_layout()

# Plot
ax.plot(data)

plt.show()

如果您想在网格中的方形主要单元格上具有不同的刻度间距，则需要放弃相等的长宽比，而是将其设置为刻度间距的商.

If you instead want to have different tick spacings with square major cells in the grid, you would need to give up the equal aspect ratio and instead set it to the quotient of the tick spacings.

import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import numpy as np

data = [0.014,  0.84,  0.95, -0.42, -0.79,  0.84, 0.98,  1.10,   0.56, -0.49]


fig, ax = plt.subplots(figsize=(20, 5))
ax.minorticks_on()

xm = 0.2
ym = 0.25

# Set major and minor grid lines on X
ax.xaxis.set_major_locator(mticker.MultipleLocator(base=xm))
ax.xaxis.set_minor_locator(mticker.MultipleLocator(base=xm / 5.))

ax.yaxis.set_major_locator(mticker.MultipleLocator(base=ym))
ax.yaxis.set_minor_locator(mticker.MultipleLocator(base=ym / 5.))

ax.grid(ls='-', color='red', linewidth=0.8)
ax.grid(which="minor", ls=':', color='red', linewidth=0.6)

## Set limits
ylim = int(np.ceil(max(abs(min(data)), max(data))))
ax.axis([0, 10, -ylim, ylim])
plt.gca().set_aspect(xm/ym, adjustable='box')
fig.tight_layout()


# Plot
ax.plot(data)

plt.show()

要摆脱第二个刻度标签，可以使用

To then get rid of every second ticklabel, an option is

fmt = lambda x,p: "%.2f" % x if not x%(2*ym) else ""
ax.yaxis.set_major_formatter(mticker.FuncFormatter(fmt))

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