标签归档:font-size

如何在Matplotlib图上更改字体大小

问题:如何在Matplotlib图上更改字体大小

如何更改matplotlib图上所有元素(刻度,标签,标题)的字体大小?

我知道如何更改刻度标签的大小,方法是:

import matplotlib 
matplotlib.rc('xtick', labelsize=20) 
matplotlib.rc('ytick', labelsize=20) 

但是如何改变其余的呢?

How does one change the font size for all elements (ticks, labels, title) on a matplotlib plot?

I know how to change the tick label sizes, this is done with:

import matplotlib 
matplotlib.rc('xtick', labelsize=20) 
matplotlib.rc('ytick', labelsize=20) 

But how does one change the rest?


回答 0

matplotlib文档中

font = {'family' : 'normal',
        'weight' : 'bold',
        'size'   : 22}

matplotlib.rc('font', **font)

这会将所有项目的字体设置为kwargs对象指定的字体font

另外,您也可以使用此答案中rcParams update建议的方法:

matplotlib.rcParams.update({'font.size': 22})

要么

import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 22})

您可以在“ 定制matplotlib”页面上找到可用属性的完整列表。

From the matplotlib documentation,

font = {'family' : 'normal',
        'weight' : 'bold',
        'size'   : 22}

matplotlib.rc('font', **font)

This sets the font of all items to the font specified by the kwargs object, font.

Alternatively, you could also use the rcParams update method as suggested in this answer:

matplotlib.rcParams.update({'font.size': 22})

or

import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 22})

You can find a full list of available properties on the Customizing matplotlib page.


回答 1

如果您是像我这样的控制狂,则可能需要显式设置所有字体大小:

import matplotlib.pyplot as plt

SMALL_SIZE = 8
MEDIUM_SIZE = 10
BIGGER_SIZE = 12

plt.rc('font', size=SMALL_SIZE)          # controls default text sizes
plt.rc('axes', titlesize=SMALL_SIZE)     # fontsize of the axes title
plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels
plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize
plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title

请注意,您还可以设置在以下位置调用rc方法的大小matplotlib

import matplotlib

SMALL_SIZE = 8
matplotlib.rc('font', size=SMALL_SIZE)
matplotlib.rc('axes', titlesize=SMALL_SIZE)

# and so on ...

If you are a control freak like me, you may want to explicitly set all your font sizes:

import matplotlib.pyplot as plt

SMALL_SIZE = 8
MEDIUM_SIZE = 10
BIGGER_SIZE = 12

plt.rc('font', size=SMALL_SIZE)          # controls default text sizes
plt.rc('axes', titlesize=SMALL_SIZE)     # fontsize of the axes title
plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels
plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels
plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize
plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title

Note that you can also set the sizes calling the rc method on matplotlib:

import matplotlib

SMALL_SIZE = 8
matplotlib.rc('font', size=SMALL_SIZE)
matplotlib.rc('axes', titlesize=SMALL_SIZE)

# and so on ...

回答 2

matplotlib.rcParams.update({'font.size': 22})
matplotlib.rcParams.update({'font.size': 22})

回答 3

如果要仅更改已创建的特定图的字体大小,请尝试以下操作:

import matplotlib.pyplot as plt

ax = plt.subplot(111, xlabel='x', ylabel='y', title='title')
for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] +
             ax.get_xticklabels() + ax.get_yticklabels()):
    item.set_fontsize(20)

If you want to change the fontsize for just a specific plot that has already been created, try this:

import matplotlib.pyplot as plt

ax = plt.subplot(111, xlabel='x', ylabel='y', title='title')
for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] +
             ax.get_xticklabels() + ax.get_yticklabels()):
    item.set_fontsize(20)

回答 4

更新:请参阅答案的底部以获取一种更好的方法。
更新#2:我也想出了更改图例标题字体。
更新#3:Matplotlib 2.0.0中存在一个错误,错误导致对数轴的刻度标签恢复为默认字体。应该在2.0.1中修复,但是我已经在答案的第二部分中包含了解决方法。

此答案适用于试图更改所有字体(包括图例)的任何人,以及适用于每件事使用不同字体和大小的任何人。它不使用rc(对我来说似乎不起作用)。这相当麻烦,但是我个人无法使用任何其他方法。它基本上将ryggyr的答案与SO的其他答案结合在一起。

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

# Set the font dictionaries (for plot title and axis titles)
title_font = {'fontname':'Arial', 'size':'16', 'color':'black', 'weight':'normal',
              'verticalalignment':'bottom'} # Bottom vertical alignment for more space
axis_font = {'fontname':'Arial', 'size':'14'}

# Set the font properties (for use in legend)   
font_path = 'C:\Windows\Fonts\Arial.ttf'
font_prop = font_manager.FontProperties(fname=font_path, size=14)

ax = plt.subplot() # Defines ax variable by creating an empty plot

# Set the tick labels font
for label in (ax.get_xticklabels() + ax.get_yticklabels()):
    label.set_fontname('Arial')
    label.set_fontsize(13)

x = np.linspace(0, 10)
y = x + np.random.normal(x) # Just simulates some data

plt.plot(x, y, 'b+', label='Data points')
plt.xlabel("x axis", **axis_font)
plt.ylabel("y axis", **axis_font)
plt.title("Misc graph", **title_font)
plt.legend(loc='lower right', prop=font_prop, numpoints=1)
plt.text(0, 0, "Misc text", **title_font)
plt.show()

这种方法的好处是,通过使用多个字体字典,您可以为各种标题选择不同的字体/大小/粗细/颜色,为刻度标签选择字体,并为图例选择字体,所有这些都是独立的。


更新:

我已经设计出一种略有不同,不太混乱的方法,该方法消除了字体词典,并允许系统上的任何字体,甚至.otf字体。有单独字体的每一件事情,只写更多font_pathfont_prop变量一样。

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import matplotlib.ticker
# Workaround for Matplotlib 2.0.0 log axes bug https://github.com/matplotlib/matplotlib/issues/8017 :
matplotlib.ticker._mathdefault = lambda x: '\\mathdefault{%s}'%x 

# Set the font properties (can use more variables for more fonts)
font_path = 'C:\Windows\Fonts\AGaramondPro-Regular.otf'
font_prop = font_manager.FontProperties(fname=font_path, size=14)

ax = plt.subplot() # Defines ax variable by creating an empty plot

# Define the data to be plotted
x = np.linspace(0, 10)
y = x + np.random.normal(x)
plt.plot(x, y, 'b+', label='Data points')

for label in (ax.get_xticklabels() + ax.get_yticklabels()):
    label.set_fontproperties(font_prop)
    label.set_fontsize(13) # Size here overrides font_prop

plt.title("Exponentially decaying oscillations", fontproperties=font_prop,
          size=16, verticalalignment='bottom') # Size here overrides font_prop
plt.xlabel("Time", fontproperties=font_prop)
plt.ylabel("Amplitude", fontproperties=font_prop)
plt.text(0, 0, "Misc text", fontproperties=font_prop)

lgd = plt.legend(loc='lower right', prop=font_prop) # NB different 'prop' argument for legend
lgd.set_title("Legend", prop=font_prop)

plt.show()

希望这是一个全面的答案

Update: See the bottom of the answer for a slightly better way of doing it.
Update #2: I’ve figured out changing legend title fonts too.
Update #3: There is a bug in Matplotlib 2.0.0 that’s causing tick labels for logarithmic axes to revert to the default font. Should be fixed in 2.0.1 but I’ve included the workaround in the 2nd part of the answer.

This answer is for anyone trying to change all the fonts, including for the legend, and for anyone trying to use different fonts and sizes for each thing. It does not use rc (which doesn’t seem to work for me). It is rather cumbersome but I could not get to grips with any other method personally. It basically combines ryggyr’s answer here with other answers on SO.

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

# Set the font dictionaries (for plot title and axis titles)
title_font = {'fontname':'Arial', 'size':'16', 'color':'black', 'weight':'normal',
              'verticalalignment':'bottom'} # Bottom vertical alignment for more space
axis_font = {'fontname':'Arial', 'size':'14'}

# Set the font properties (for use in legend)   
font_path = 'C:\Windows\Fonts\Arial.ttf'
font_prop = font_manager.FontProperties(fname=font_path, size=14)

ax = plt.subplot() # Defines ax variable by creating an empty plot

# Set the tick labels font
for label in (ax.get_xticklabels() + ax.get_yticklabels()):
    label.set_fontname('Arial')
    label.set_fontsize(13)

x = np.linspace(0, 10)
y = x + np.random.normal(x) # Just simulates some data

plt.plot(x, y, 'b+', label='Data points')
plt.xlabel("x axis", **axis_font)
plt.ylabel("y axis", **axis_font)
plt.title("Misc graph", **title_font)
plt.legend(loc='lower right', prop=font_prop, numpoints=1)
plt.text(0, 0, "Misc text", **title_font)
plt.show()

The benefit of this method is that, by having several font dictionaries, you can choose different fonts/sizes/weights/colours for the various titles, choose the font for the tick labels, and choose the font for the legend, all independently.


UPDATE:

I have worked out a slightly different, less cluttered approach that does away with font dictionaries, and allows any font on your system, even .otf fonts. To have separate fonts for each thing, just write more font_path and font_prop like variables.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import matplotlib.ticker
# Workaround for Matplotlib 2.0.0 log axes bug https://github.com/matplotlib/matplotlib/issues/8017 :
matplotlib.ticker._mathdefault = lambda x: '\\mathdefault{%s}'%x 

# Set the font properties (can use more variables for more fonts)
font_path = 'C:\Windows\Fonts\AGaramondPro-Regular.otf'
font_prop = font_manager.FontProperties(fname=font_path, size=14)

ax = plt.subplot() # Defines ax variable by creating an empty plot

# Define the data to be plotted
x = np.linspace(0, 10)
y = x + np.random.normal(x)
plt.plot(x, y, 'b+', label='Data points')

for label in (ax.get_xticklabels() + ax.get_yticklabels()):
    label.set_fontproperties(font_prop)
    label.set_fontsize(13) # Size here overrides font_prop

plt.title("Exponentially decaying oscillations", fontproperties=font_prop,
          size=16, verticalalignment='bottom') # Size here overrides font_prop
plt.xlabel("Time", fontproperties=font_prop)
plt.ylabel("Amplitude", fontproperties=font_prop)
plt.text(0, 0, "Misc text", fontproperties=font_prop)

lgd = plt.legend(loc='lower right', prop=font_prop) # NB different 'prop' argument for legend
lgd.set_title("Legend", prop=font_prop)

plt.show()

Hopefully this is a comprehensive answer


回答 5

这是一种完全不同的方法,可以很好地更改字体大小:

更改图形大小

我通常使用这样的代码:

import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure(figsize=(4,3))
ax = fig.add_subplot(111)
x = np.linspace(0,6.28,21)
ax.plot(x, np.sin(x), '-^', label="1 Hz")
ax.set_title("Oscillator Output")
ax.set_xlabel("Time (s)")
ax.set_ylabel("Output (V)")
ax.grid(True)
ax.legend(loc=1)
fig.savefig('Basic.png', dpi=300)

较小你做图的大小,更大的字体是相对于情节。这也会放大标记。注意我还设置了dpi每英寸或点。我是从张贴AMTA(美国美国建模老师)论坛上学到的。上面的代码示例:

Here is a totally different approach that works surprisingly well to change the font sizes:

Change the figure size!

I usually use code like this:

import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure(figsize=(4,3))
ax = fig.add_subplot(111)
x = np.linspace(0,6.28,21)
ax.plot(x, np.sin(x), '-^', label="1 Hz")
ax.set_title("Oscillator Output")
ax.set_xlabel("Time (s)")
ax.set_ylabel("Output (V)")
ax.grid(True)
ax.legend(loc=1)
fig.savefig('Basic.png', dpi=300)

The smaller you make the figure size, the larger the font is relative to the plot. This also upscales the markers. Note I also set the dpi or dot per inch. I learned this from a posting the AMTA (American Modeling Teacher of America) forum. Example from above code:


回答 6

采用 plt.tick_params(labelsize=14)

Use plt.tick_params(labelsize=14)


回答 7

您可以使用plt.rcParams["font.size"]设置font_sizematplotlib,你也可以使用plt.rcParams["font.family"]设置font_familymatplotlib。试试这个例子:

import matplotlib.pyplot as plt
plt.style.use('seaborn-whitegrid')

label = [1,2,3,4,5,6,7,8]
x = [0.001906,0.000571308,0.0020305,0.0037422,0.0047095,0.000846667,0.000819,0.000907]
y = [0.2943301,0.047778308,0.048003167,0.1770876,0.532489833,0.024611333,0.157498667,0.0272095]


plt.ylabel('eigen centrality')
plt.xlabel('betweenness centrality')
plt.text(0.001906, 0.2943301, '1 ', ha='right', va='center')
plt.text(0.000571308, 0.047778308, '2 ', ha='right', va='center')
plt.text(0.0020305, 0.048003167, '3 ', ha='right', va='center')
plt.text(0.0037422, 0.1770876, '4 ', ha='right', va='center')
plt.text(0.0047095, 0.532489833, '5 ', ha='right', va='center')
plt.text(0.000846667, 0.024611333, '6 ', ha='right', va='center')
plt.text(0.000819, 0.157498667, '7 ', ha='right', va='center')
plt.text(0.000907, 0.0272095, '8 ', ha='right', va='center')
plt.rcParams["font.family"] = "Times New Roman"
plt.rcParams["font.size"] = "50"
plt.plot(x, y, 'o', color='blue')

You can use plt.rcParams["font.size"] for setting font_size in matplotlib and also you can use plt.rcParams["font.family"] for setting font_family in matplotlib. Try this example:

import matplotlib.pyplot as plt
plt.style.use('seaborn-whitegrid')

label = [1,2,3,4,5,6,7,8]
x = [0.001906,0.000571308,0.0020305,0.0037422,0.0047095,0.000846667,0.000819,0.000907]
y = [0.2943301,0.047778308,0.048003167,0.1770876,0.532489833,0.024611333,0.157498667,0.0272095]


plt.ylabel('eigen centrality')
plt.xlabel('betweenness centrality')
plt.text(0.001906, 0.2943301, '1 ', ha='right', va='center')
plt.text(0.000571308, 0.047778308, '2 ', ha='right', va='center')
plt.text(0.0020305, 0.048003167, '3 ', ha='right', va='center')
plt.text(0.0037422, 0.1770876, '4 ', ha='right', va='center')
plt.text(0.0047095, 0.532489833, '5 ', ha='right', va='center')
plt.text(0.000846667, 0.024611333, '6 ', ha='right', va='center')
plt.text(0.000819, 0.157498667, '7 ', ha='right', va='center')
plt.text(0.000907, 0.0272095, '8 ', ha='right', va='center')
plt.rcParams["font.family"] = "Times New Roman"
plt.rcParams["font.size"] = "50"
plt.plot(x, y, 'o', color='blue')

回答 8

这是我在Jupyter Notebook中通常使用的内容:

# Jupyter Notebook settings

from IPython.core.display import display, HTML
display(HTML("<style>.container { width:95% !important; }</style>"))
%autosave 0
%matplotlib inline
%load_ext autoreload
%autoreload 2

from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"


# Imports for data analysis
import pandas as pd
import matplotlib.pyplot as plt
pd.set_option('display.max_rows', 2500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.max_colwidth', 2000)
pd.set_option('display.width', 2000)
pd.set_option('display.float_format', lambda x: '%.3f' % x)

#size=25
size=15
params = {'legend.fontsize': 'large',
          'figure.figsize': (20,8),
          'axes.labelsize': size,
          'axes.titlesize': size,
          'xtick.labelsize': size*0.75,
          'ytick.labelsize': size*0.75,
          'axes.titlepad': 25}
plt.rcParams.update(params)

Here is what I generally use in Jupyter Notebook:

# Jupyter Notebook settings

from IPython.core.display import display, HTML
display(HTML("<style>.container { width:95% !important; }</style>"))
%autosave 0
%matplotlib inline
%load_ext autoreload
%autoreload 2

from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"


# Imports for data analysis
import pandas as pd
import matplotlib.pyplot as plt
pd.set_option('display.max_rows', 2500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.max_colwidth', 2000)
pd.set_option('display.width', 2000)
pd.set_option('display.float_format', lambda x: '%.3f' % x)

#size=25
size=15
params = {'legend.fontsize': 'large',
          'figure.figsize': (20,8),
          'axes.labelsize': size,
          'axes.titlesize': size,
          'xtick.labelsize': size*0.75,
          'ytick.labelsize': size*0.75,
          'axes.titlepad': 25}
plt.rcParams.update(params)

回答 9

基于以上内容:

import matplotlib.pyplot as plt
import matplotlib.font_manager as fm

fontPath = "/usr/share/fonts/abc.ttf"
font = fm.FontProperties(fname=fontPath, size=10)
font2 = fm.FontProperties(fname=fontPath, size=24)

fig = plt.figure(figsize=(32, 24))
fig.text(0.5, 0.93, "This is my Title", horizontalalignment='center', fontproperties=font2)

plot = fig.add_subplot(1, 1, 1)

plot.xaxis.get_label().set_fontproperties(font)
plot.yaxis.get_label().set_fontproperties(font)
plot.legend(loc='upper right', prop=font)

for label in (plot.get_xticklabels() + plot.get_yticklabels()):
    label.set_fontproperties(font)

Based on the above stuff:

import matplotlib.pyplot as plt
import matplotlib.font_manager as fm

fontPath = "/usr/share/fonts/abc.ttf"
font = fm.FontProperties(fname=fontPath, size=10)
font2 = fm.FontProperties(fname=fontPath, size=24)

fig = plt.figure(figsize=(32, 24))
fig.text(0.5, 0.93, "This is my Title", horizontalalignment='center', fontproperties=font2)

plot = fig.add_subplot(1, 1, 1)

plot.xaxis.get_label().set_fontproperties(font)
plot.yaxis.get_label().set_fontproperties(font)
plot.legend(loc='upper right', prop=font)

for label in (plot.get_xticklabels() + plot.get_yticklabels()):
    label.set_fontproperties(font)

回答 10

这是Marius Retegan 答案的扩展。您可以对所有修改内容制作一个单独的JSON文件,然后通过rcParams.update加载它。所做的更改仅适用于当前脚本。所以

import json
from matplotlib import pyplot as plt, rcParams

s = json.load(open("example_file.json")
rcParams.update(s)

并将此“ example_file.json”保存在同一文件夹中。

{
  "lines.linewidth": 2.0,
  "axes.edgecolor": "#bcbcbc",
  "patch.linewidth": 0.5,
  "legend.fancybox": true,
  "axes.color_cycle": [
    "#348ABD",
    "#A60628",
    "#7A68A6",
    "#467821",
    "#CF4457",
    "#188487",
    "#E24A33"
  ],
  "axes.facecolor": "#eeeeee",
  "axes.labelsize": "large",
  "axes.grid": true,
  "patch.edgecolor": "#eeeeee",
  "axes.titlesize": "x-large",
  "svg.fonttype": "path",
  "examples.directory": ""
}

This is an extension to Marius Retegan answer. You can make a separate JSON file with all your modifications and than load it with rcParams.update. The changes will only apply to the current script. So

import json
from matplotlib import pyplot as plt, rcParams

s = json.load(open("example_file.json")
rcParams.update(s)

and save this ‘example_file.json’ in the same folder.

{
  "lines.linewidth": 2.0,
  "axes.edgecolor": "#bcbcbc",
  "patch.linewidth": 0.5,
  "legend.fancybox": true,
  "axes.color_cycle": [
    "#348ABD",
    "#A60628",
    "#7A68A6",
    "#467821",
    "#CF4457",
    "#188487",
    "#E24A33"
  ],
  "axes.facecolor": "#eeeeee",
  "axes.labelsize": "large",
  "axes.grid": true,
  "patch.edgecolor": "#eeeeee",
  "axes.titlesize": "x-large",
  "svg.fonttype": "path",
  "examples.directory": ""
}

回答 11

我完全同意Huster教授的观点,最简单的方法是更改​​图形的大小,从而可以保留默认字体。当将图形另存为pdf时,我只需要用bbox_inches选项对此进行补充,因为轴标签被切掉了。

import matplotlib.pyplot as plt
plt.figure(figsize=(4,3))
plt.savefig('Basic.pdf', bbox_inches='tight')

I totally agree with Prof Huster that the simplest way to proceed is to change the size of the figure, which allows keeping the default fonts. I just had to complement this with a bbox_inches option when saving the figure as a pdf because the axis labels were cut.

import matplotlib.pyplot as plt
plt.figure(figsize=(4,3))
plt.savefig('Basic.pdf', bbox_inches='tight')