在 matplotlib 中保存子图

发布于 2024-10-05 09:10:50 字数 303 浏览 3 评论 0原文

是否可以将 matplotlib 图中的单个子图保存(保存为 png)?假设我有

import pyplot.matplotlib as plt
ax1 = plt.subplot(121)
ax2 = plt.subplot(122)
ax1.plot([1,2,3],[4,5,6])    
ax2.plot([3,4,5],[7,8,9])

是否可以将两个子图保存到不同的文件中,或者至少将它们单独复制到一个新的图形中以保存它们?

我在 RHEL 5 上使用 matplotlib 1.0.0 版本。

Is it possible to save (to a png) an individual subplot in a matplotlib figure? Let's say I have

import pyplot.matplotlib as plt
ax1 = plt.subplot(121)
ax2 = plt.subplot(122)
ax1.plot([1,2,3],[4,5,6])    
ax2.plot([3,4,5],[7,8,9])

Is it possible to save each of the two subplots to different files or at least copy them separately to a new figure to save them?

I am using version 1.0.0 of matplotlib on RHEL 5.

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评论(2

尴尬癌患者 2024-10-12 09:10:50

虽然@Eli 说得非常正确,通常不需要太多这样做,但这是可能的。 savefig 采用 bbox_inches 参数,可用于有选择地将图形的一部分保存到图像中。

这是一个简单的例子:

import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np

# Make an example plot with two subplots...
fig = plt.figure()
ax1 = fig.add_subplot(2,1,1)
ax1.plot(range(10), 'b-')

ax2 = fig.add_subplot(2,1,2)
ax2.plot(range(20), 'r^')

# Save the full figure...
fig.savefig('full_figure.png')

# Save just the portion _inside_ the second axis's boundaries
extent = ax2.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
fig.savefig('ax2_figure.png', bbox_inches=extent)

# Pad the saved area by 10% in the x-direction and 20% in the y-direction
fig.savefig('ax2_figure_expanded.png', bbox_inches=extent.expanded(1.1, 1.2))

完整的图:
完整示例图


第二个子图内的区域:
Inside secondary subplot


第二个子图周围的区域在 x 方向上填充 10%,在 y 方向上填充 20%:
完整的第二个子图

While @Eli is quite correct that there usually isn't much of a need to do it, it is possible. savefig takes a bbox_inches argument that can be used to selectively save only a portion of a figure to an image.

Here's a quick example:

import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np

# Make an example plot with two subplots...
fig = plt.figure()
ax1 = fig.add_subplot(2,1,1)
ax1.plot(range(10), 'b-')

ax2 = fig.add_subplot(2,1,2)
ax2.plot(range(20), 'r^')

# Save the full figure...
fig.savefig('full_figure.png')

# Save just the portion _inside_ the second axis's boundaries
extent = ax2.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
fig.savefig('ax2_figure.png', bbox_inches=extent)

# Pad the saved area by 10% in the x-direction and 20% in the y-direction
fig.savefig('ax2_figure_expanded.png', bbox_inches=extent.expanded(1.1, 1.2))

The full figure:
Full Example Figure


Area inside the second subplot:
Inside second subplot


Area around the second subplot padded by 10% in the x-direction and 20% in the y-direction:
Full second subplot

旧梦荧光笔 2024-10-12 09:10:50

应用 3 年后 @Joe 的答案中的 full_extent() 函数,您可以得到正是OP正在寻找的东西。或者,您可以使用 Axes.get_tightbbox() ,它提供了更紧密的边界框

import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
from matplotlib.transforms import Bbox

def full_extent(ax, pad=0.0):
    """Get the full extent of an axes, including axes labels, tick labels, and
    titles."""
    # For text objects, we need to draw the figure first, otherwise the extents
    # are undefined.
    ax.figure.canvas.draw()
    items = ax.get_xticklabels() + ax.get_yticklabels() 
#    items += [ax, ax.title, ax.xaxis.label, ax.yaxis.label]
    items += [ax, ax.title]
    bbox = Bbox.union([item.get_window_extent() for item in items])

    return bbox.expanded(1.0 + pad, 1.0 + pad)

# Make an example plot with two subplots...
fig = plt.figure()
ax1 = fig.add_subplot(2,1,1)
ax1.plot(range(10), 'b-')

ax2 = fig.add_subplot(2,1,2)
ax2.plot(range(20), 'r^')

# Save the full figure...
fig.savefig('full_figure.png')

# Save just the portion _inside_ the second axis's boundaries
extent = full_extent(ax2).transformed(fig.dpi_scale_trans.inverted())
# Alternatively,
# extent = ax.get_tightbbox(fig.canvas.renderer).transformed(fig.dpi_scale_trans.inverted())
fig.savefig('ax2_figure.png', bbox_inches=extent)

我会发布图片但我缺乏声誉点

Applying the full_extent() function in an answer by @Joe 3 years later from here, you can get exactly what the OP was looking for. Alternatively, you can use Axes.get_tightbbox() which gives a little tighter bounding box

import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
from matplotlib.transforms import Bbox

def full_extent(ax, pad=0.0):
    """Get the full extent of an axes, including axes labels, tick labels, and
    titles."""
    # For text objects, we need to draw the figure first, otherwise the extents
    # are undefined.
    ax.figure.canvas.draw()
    items = ax.get_xticklabels() + ax.get_yticklabels() 
#    items += [ax, ax.title, ax.xaxis.label, ax.yaxis.label]
    items += [ax, ax.title]
    bbox = Bbox.union([item.get_window_extent() for item in items])

    return bbox.expanded(1.0 + pad, 1.0 + pad)

# Make an example plot with two subplots...
fig = plt.figure()
ax1 = fig.add_subplot(2,1,1)
ax1.plot(range(10), 'b-')

ax2 = fig.add_subplot(2,1,2)
ax2.plot(range(20), 'r^')

# Save the full figure...
fig.savefig('full_figure.png')

# Save just the portion _inside_ the second axis's boundaries
extent = full_extent(ax2).transformed(fig.dpi_scale_trans.inverted())
# Alternatively,
# extent = ax.get_tightbbox(fig.canvas.renderer).transformed(fig.dpi_scale_trans.inverted())
fig.savefig('ax2_figure.png', bbox_inches=extent)

I'd post a pic but I lack the reputation points

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