问题:Matplotlib不同大小的子图
我需要在图中添加两个子图。一个子图的宽度大约是第二个子图的三倍(相同的高度)。我使用GridSpec
和colspan
参数完成了此操作,但是我想使用来完成此操作,figure
因此可以保存为PDF。我可以使用figsize
构造函数中的参数调整第一个图形,但是如何更改第二个图形的大小?
I need to add two subplots to a figure. One subplot needs to be about three times as wide as the second (same height). I accomplished this using GridSpec
and the colspan
argument but I would like to do this using figure
so I can save to PDF. I can adjust the first figure using the figsize
argument in the constructor, but how do I change the size of the second plot?
回答 0
另一种方法是使用该subplots
函数并通过以下参数传递宽度比gridspec_kw
:
import numpy as np
import matplotlib . pyplot as plt
# generate some data
x = np . arange ( 0 , 10 , 0.2 )
y = np . sin ( x )
# plot it
f , ( a0 , a1 ) = plt . subplots ( 1 , 2 , gridspec_kw ={ 'width_ratios' : [ 3 , 1 ]})
a0 . plot ( x , y )
a1 . plot ( y , x )
f . tight_layout ()
f . savefig ( 'grid_figure.pdf' )
Another way is to use the subplots
function and pass the width ratio with gridspec_kw
:
import numpy as np
import matplotlib.pyplot as plt
# generate some data
x = np.arange(0, 10, 0.2)
y = np.sin(x)
# plot it
f, (a0, a1) = plt.subplots(1, 2, gridspec_kw={'width_ratios': [3, 1]})
a0.plot(x, y)
a1.plot(y, x)
f.tight_layout()
f.savefig('grid_figure.pdf')
回答 1
您可以使用gridspec
和figure
:
import numpy as np
import matplotlib . pyplot as plt
from matplotlib import gridspec
# generate some data
x = np . arange ( 0 , 10 , 0.2 )
y = np . sin ( x )
# plot it
fig = plt . figure ( figsize =( 8 , 6 ))
gs = gridspec . GridSpec ( 1 , 2 , width_ratios =[ 3 , 1 ])
ax0 = plt . subplot ( gs [ 0 ])
ax0 . plot ( x , y )
ax1 = plt . subplot ( gs [ 1 ])
ax1 . plot ( y , x )
plt . tight_layout ()
plt . savefig ( 'grid_figure.pdf' )
You can use gridspec
and figure
:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import gridspec
# generate some data
x = np.arange(0, 10, 0.2)
y = np.sin(x)
# plot it
fig = plt.figure(figsize=(8, 6))
gs = gridspec.GridSpec(1, 2, width_ratios=[3, 1])
ax0 = plt.subplot(gs[0])
ax0.plot(x, y)
ax1 = plt.subplot(gs[1])
ax1.plot(y, x)
plt.tight_layout()
plt.savefig('grid_figure.pdf')
回答 2
可能最简单的方法是使用subplot2grid
,如使用GridSpec自定义子图的位置中所述 。
ax = plt . subplot2grid (( 2 , 2 ), ( 0 , 0 ))
等于
import matplotlib . gridspec as gridspec
gs = gridspec . GridSpec ( 2 , 2 )
ax = plt . subplot ( gs [ 0 , 0 ])
因此bmu的示例变为:
import numpy as np
import matplotlib . pyplot as plt
# generate some data
x = np . arange ( 0 , 10 , 0.2 )
y = np . sin ( x )
# plot it
fig = plt . figure ( figsize =( 8 , 6 ))
ax0 = plt . subplot2grid (( 1 , 3 ), ( 0 , 0 ), colspan = 2 )
ax0 . plot ( x , y )
ax1 = plt . subplot2grid (( 1 , 3 ), ( 0 , 2 ))
ax1 . plot ( y , x )
plt . tight_layout ()
plt . savefig ( 'grid_figure.pdf' )
Probably the simplest way is using subplot2grid
, described in Customizing Location of Subplot Using GridSpec .
ax = plt.subplot2grid((2, 2), (0, 0))
is equal to
import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(2, 2)
ax = plt.subplot(gs[0, 0])
so bmu’s example becomes:
import numpy as np
import matplotlib.pyplot as plt
# generate some data
x = np.arange(0, 10, 0.2)
y = np.sin(x)
# plot it
fig = plt.figure(figsize=(8, 6))
ax0 = plt.subplot2grid((1, 3), (0, 0), colspan=2)
ax0.plot(x, y)
ax1 = plt.subplot2grid((1, 3), (0, 2))
ax1.plot(y, x)
plt.tight_layout()
plt.savefig('grid_figure.pdf')
回答 3
我使用pyplot
的axes
对象来手动调整尺寸,而无需使用GridSpec
:
import matplotlib . pyplot as plt
import numpy as np
x = np . arange ( 0 , 10 , 0.2 )
y = np . sin ( x )
# definitions for the axes
left , width = 0.07 , 0.65
bottom , height = 0.1 , . 8
bottom_h = left_h = left + width + 0.02
rect_cones = [ left , bottom , width , height ]
rect_box = [ left_h , bottom , 0.17 , height ]
fig = plt . figure ()
cones = plt . axes ( rect_cones )
box = plt . axes ( rect_box )
cones . plot ( x , y )
box . plot ( y , x )
plt . show ()
I used pyplot
‘s axes
object to manually adjust the sizes without using GridSpec
:
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(0, 10, 0.2)
y = np.sin(x)
# definitions for the axes
left, width = 0.07, 0.65
bottom, height = 0.1, .8
bottom_h = left_h = left+width+0.02
rect_cones = [left, bottom, width, height]
rect_box = [left_h, bottom, 0.17, height]
fig = plt.figure()
cones = plt.axes(rect_cones)
box = plt.axes(rect_box)
cones.plot(x, y)
box.plot(y, x)
plt.show()