Matplotlib swordsman line - layout guide and multi map implementation (Updated)

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Layout guide

A simple example

stay Matplotlib in , Axis （ Including subgraphs ） The position of is in the standardized graphic coordinates , Your axis label or title （ Sometimes even scale labels ） Beyond the graphic area , So you need to edit .

To prevent this , The position of the shaft needs to be adjusted .

• By adjusting the subgraph parameters Figure.subplots_adjust. To manually complete however , use constrained_layout=True Keyword parameters will be adjusted automatically .
• This Figure.tight_layout It's auto filled
  • tight_layout() The subgraph spacing will also be adjusted to minimize overlap
  • tight_layout() You can use keyword parameters pad , w_pad and h_pad , Controls the additional padding around the graph boundary and between subgraphs

fig, ax = plt.subplots(constrained_layout=True)
example_plot(ax, fontsize=24)

When you have multiple subgraphs , You usually see that different label axes overlap each other

fig, axs = plt.subplots(2, 2, constrained_layout=False)
for ax in axs.flat:
    example_plot(ax)

• Output image ：

• Calling plt.subplots Appoint constrained_layout=True, Make the layout properly constrained
• tight_layout The function can adjust the relative size of the subgraph so that the characters do not overlap

fig, axs = plt.subplots(2, 2, constrained_layout=True)
for ax in axs.flat:
    example_plot(ax)

• Output image ：

subtitle —— title

• constrained_layout You can also make room to set the title suptitle.

fig, axs = plt.subplots(2, 2, figsize=(4, 4), constrained_layout=True)
fig.suptitle('Big Suptitle')
plt.show()

• Output image ：

Legend has it that —— legend

The legend can be placed outside its parent axis . Constrained layout is designed to deal with this problem Axes.legend(). however , Constrained layouts do not handle legends created by Figure.legend().

fig, ax = plt.subplots(constrained_layout=True)
ax.plot(np.arange(10), label='This is a plot')
ax.legend(loc='center left', bbox_to_anchor=(0.8, 0.5))

• Output image ：

however , When there are multiple subgraphs, this will compress the space of the subgraph layout

A better way to solve this embarrassment is to simply use the provided legend method Figure.legend:

Filling and spacing

• Filling between shafts , Horizontal by w_pad and wspace And vertical by h_pad and hspace
  • This can be done by set_constrained_layout_pads( w/h_pad, w/hspace) edit
  • The spacing between subgraphs is determined by wspace and hspace Set up
• It can also be done through plt.subplots_adjust(wspace=0,hspace=0) Set up
  • wspace,hspace： Used to control the percentage of width and height , such as subplot The gap between

Multi graph implementation

More pictures ——plt.subplots

subplots Parameters

• plt.subplots(nrows, ncols, index, sharex, sharey)

  • nrows Row number of subgraphs
  • ncols Number of columns in a subgraph
  • index Take the index of the subgraph
  • sharex All subgraphs use the same x Axis scale
  • sharey All subgraphs use the same y Axis scale
    • sharex,sharey： Share or not x,y scale
  • figsize Parameter can specify the size of the entire canvas

• When we call plot when , If you set plt.figure(), Will be called automatically figure() Generate a figure, Strictly speaking , Is to generate subplots(111)

• First create a chart figure, Then generate subgraphs ,(2,2,1) For creating 2*2 Matrix table of , Then choose the first , The order is from left to right, from top to bottom

Calling subplot Generally, you need to pass in three digits , Respectively represent the total number of head offices , The total number of columns , Of the current subgraph index
2*2 Four subgraphs index:1 The first sub graph is selected
ax1 = plt.subplot(221)
ax2 = plt.subplot(222)
ax3 = plt.subplot(223)
ax4 = plt.subplot(224) When all three digits are less than 10 when , You can omit the comma in the middle , This command is equivalent to plt.subplot(2,2,4)

beyond , May be an error
plt.subplot(225)

Two ways of implementation

OO style

import matplotlib.pyplot as plt

x = [" Shenzhen ", " Guangzhou ", " Beijing ", " Shanghai "]
y = [1, 3, 2, 5]
fig, axs = plt.subplots(2, 2)

#  Subscript [nrows][ncols]
#  First subgraph 
axs[0][0].bar(x, y)
#  Second subgraph 
axs[0][1].pie(y, labels=x)
#  The third subgraph 
axs[1][0].plot(x, y)
#  The fourth subgraph 
axs[1][1].barh(x, y)
plt.show()

• Output image ：
  

plplot style

import matplotlib.pyplot as plt

plt.rcParams['font.sans-serif'] = 'Microsoft YaHei'
x = [" Shenzhen ", " Guangzhou ", " Beijing ", " Shanghai "]
y = [1, 3, 2, 5]

#  First subgraph 
plt.subplot(2, 2, 1)
plt.bar(x, y)
#  Second subgraph 
plt.subplot(2, 2, 2)
plt.pie(y, labels=x)
#  The third subgraph 
plt.subplot(2, 2, 3)
plt.plot(x, y)
#  The fourth subgraph 
plt.subplot(2, 2, 4)
plt.barh(x, y)
plt.show()

• Output image ：
  

All in one display ——plt.subplot

Graph in uniform graph

• Use plt.figure Create an image window . Use plt.subplot To create a thumbnail
• plt.subplot(2,2,1) Indicates that the entire image window is divided into 2 That's ok 2 Column , The current position is 1. Use plt.plot([0,1],[0,1]) In the 1 Create a small diagram at one location .
• plt.subplot(2,2,2) Indicates that the entire image window is divided into 2 That's ok 2 Column , The current position is 2. Use plt.plot([0,1],[0,2]) In the 2 Create a small diagram at one location .
• plt.subplot(2,2,3) Indicates that the entire image window is divided into 2 That's ok 2 Column , The current position is 3. plt.subplot(2,2,3) It can be abbreviated as plt.subplot(223). Use plt.plot([0,1],[0,3]) In the 3 Create a small diagram at one location .
• plt.subplot(224) Indicates that the entire image window is divided into 2 That's ok 2 Column , The current position is 4. Use plt.plot([0,1],[0,4]) In the 4 Create a small diagram at one location .

plt.figure()

plt.subplot(2,2,1)
plt.plot([0,1],[0,1])

plt.subplot(2,2,2)
plt.plot([0,1],[0,2])

plt.subplot(223)
plt.plot([0,1],[0,3])

plt.subplot(224)
plt.plot([0,1],[0,4])

Uneven graph in graph

• Use plt.subplot(2,1,1) Divide the entire image window into 2 That's ok 1 Column , The current position is 1. Use plt.plot([0,1],[0,1]) In the 1 Create a small diagram at one location .
• Use plt.subplot(2,3,4) Divide the entire image window into 2 That's ok 3 Column , The current position is 4. Use plt.plot([0,1],[0,2]) In the 4 Create a small diagram at one location .
  • Used in the previous step plt.subplot(2,1,1) Divide the entire image window into 2 That's ok 1 Column , The first 1 A small picture occupies the 1 A place , That is, the whole second 1 That's ok .
  • In this step plt.subplot(2,3,4) Divide the entire image window into 2 That's ok 3 Column , So the first... Of the entire image window 1 OK, it becomes 3 Column , That is to say 3 A place , To be the first 2 OK, No 1 The first position is the... Of the entire image window 4 A place .

plt.subplot(2,1,1)
plt.plot([0,1],[0,1])

plt.subplot(2,3,4)
plt.plot([0,1],[0,2])

• And so on , Create the first 5、6 Subgraph on position

plt.subplot(235)
plt.plot([0,1],[0,3])

plt.subplot(236)
plt.plot([0,1],[0,4])

Uneven subgraph ——add_gridspec

Area cutting

• Use GridSpec Draw a non-uniform subgraph
• utilize add_gridspec You can specify the relative width scale width_ratios And relative height scale parameters height_ratios

spec = fig.add_gridspec(nrows=2, ncols=2, width_ratios=[1,3],height_ratios=[1,2])
It means cutting the whole canvas to 2 That's ok 2 Column area ,width_ratios=[1, 3] It means that the width of the two columns is divided into 1:3 Tailoring , Empathy height_ratios=[1,2] Indicates that the vertical direction is in accordance with 1:2 Tailoring

x = [" Shenzhen ", " Guangzhou ", " Beijing ", " Shanghai "]
y = [1, 3, 2, 5]
fig = plt.figure(figsize=(10, 8))

spec = fig.add_gridspec(nrows=2, ncols=2, width_ratios=[1, 3], height_ratios=[1, 2])
ax = fig.add_subplot(spec[0, 0])
ax.bar(x, y)

ax = fig.add_subplot(spec[0, 1])
ax.plot(x, y)

ax = fig.add_subplot(spec[1, 0])
ax.pie(y, labels=x)

ax = fig.add_subplot(spec[1, 1])
ax.barh(x, y)
plt.show()

• Output image ：
  
• spec It also supports slicing , For example, we will show the second line as the whole bar graph

x = [" Shenzhen ", " Guangzhou ", " Beijing ", " Shanghai "]
y = [1, 3, 2, 5]
fig = plt.figure(figsize=(10, 8))

spec = fig.add_gridspec(nrows=2, ncols=2, width_ratios=[1, 3], height_ratios=[1, 2])
ax = fig.add_subplot(spec[0, 0])
ax.bar(x, y)

ax = fig.add_subplot(spec[0, 1])
ax.plot(x, y)

#  The second line shows a bar chart in the whole area 
ax = fig.add_subplot(spec[1, :])
ax.barh(x, y)

#  Adjust the distance between areas 
plt.subplots_adjust(hspace=0.3, wspace=0.2)
plt.show()

• Output image ：
  

Additive elements

• ax Subgraphs can also be passed set_title、set_xlable And so on , Axis title, etc
• If you need to add a headline, you can use fig.suptitle() To complete .