matplotlib.pyplot.semilogx()函数

数据可视化是分析数据的一个重要部分，因为绘制图表有助于提供更好的洞察力和对问题的理解。Matplotlib.pyplot是实现这一功能的最常用库之一。它有助于创建有吸引力的数据，而且超级容易使用。

Matplotlib.pyplot.semilogx()函数

该函数用于将数据可视化，X轴被转换为对数格式。当其中一个参数非常大，因此最初以紧凑的方式存储时，这个函数特别有用。它支持plot()和matplotlib.axes.axes.set_xscale()的所有关键字参数。其他参数是basex、subsx和nonposx。

语法:Matplotlib.pyplot.semilogx(x, y，)

参数:重要参数如下:

x: x轴上的值。

y: y轴上的值。

color:(可选)线条或符号的颜色。

linewidth:(可选)线路宽度。

label:可选参数，指定图形的标签

basex:(可选)x对数的底。标量应该大于1。

subsx:(可选)次要xticks的位置;None默认自动潜艇，这取决于几十年的情节。

nonposx:(可选)x中的非正数可以被屏蔽为无效，或者剪切为一个非常小的正数。

marker:(可选)将点显示为提到的符号。

markersize:(可选)改变所有标记的大小。

返回:x轴上的对数比例图。

示例1

简单图

#import required library
import matplotlib.pyplot as plt
 
# defining the values
# at X and Y axis
x = [1, 2, 3,
     4, 5, 6]
y = [100, 200, 300,
     400, 500, 600]
 
# plotting the given graph
plt.semilogx(x, y, marker = ".",
             markersize = 15,
             color = "green")
# plot with grid
plt.grid(True)
 
# show the plot
plt.show()

输出:

matplotlib.pyplot.semilogx()函数

示例2

在X和Y轴上使用负值和零值。由于对数函数涉及到x轴，很明显，负数或正值将被剪切或屏蔽，这由nonposx参数指定。默认情况下，负数或零值会被裁剪。

# importing required libraries
import matplotlib.pyplot as plt
 
 
# defining the values
# at X and Y axis
x = [-1, -2, 0]
y = [5, -2, 0]
 
# plotting the given graph
plt.semilogx(x,y)
 
# show the plot
plt.show()

输出:

matplotlib.pyplot.semilogx()函数

示例3

如果使用符号，则只删除负值或零值，只绘制正值。

#import required library
import matplotlib.pyplot as plt
 
# defining the values at X and Y axis
x = [-10, 30, 0, 20,
     -50, 25, 29, -3
     , 23, 25, 29, 31]
y = [-3, 30, -10, 0,
     -40, 3, 8, 0,
     -24, 40, 43, 25]
 
# plotting the graph
plt.semilogx(x,y,'g^', color = "red")
 
# plot with grid
plt.grid(True)
 
# set y axis label
plt.ylabel('---y---')
 
# set x axis label
plt.xlabel('---x---')
 
# show the plot
plt.show()

输出:

matplotlib.pyplot.semilogx()函数

示例4

如果使用了这些行，则会剪切这些值。对应于-3和-4的值被剪切

#import required library
import matplotlib.pyplot as plt
 
# defining the values
# at X and Y axis
x = [1, 2, -3,
     -4, 5, 6]
y = [100, 200, 300,
     400, 500, 600]
 
# plotting the graph
plt.semilogx(x, y, marker = ".",
             markersize = 15)
 
# plot with grid
plt.grid(True)
 
# show the plot
plt.show()

输出:

matplotlib.pyplot.semilogx()函数

示例5

下面的分图将使差异更加清晰。

#import required library
import matplotlib.pyplot as plt
 
# specifying the subplot
fig, axes = plt.subplots(nrows = 4,
                         ncols = 4,
                         figsize = (10,10))
 
# Or equivalently, 
# "plt.tight_layout()"
fig.tight_layout()
 
# subplot 1
plt.subplot(2, 2, 1)
x2 = [0.1, 10, -30]
y2 = [40, -10, 45]
 
# plotting the given graph
plt.semilogx(x2, y2,
             color = "blue",
             linewidth = 4)
# set the title
plt.title("USING LINE")
 
# set y axis label
plt.ylabel('-----------y-----------')
 
# set x axis label
plt.xlabel('-----------x-----------')
 
# plot with grid
plt.grid(True)
 
 
# subplot 2
plt.subplot(2, 2, 2)
x2 = [0.1, 10, -30]
y2 = [40, -10, 45]
 
# plotting the given graph
plt.semilogx(x2, y2,
             'g^',
             markersize = 20,
             color = "black")
# set the title
plt.title("USING SYMBOL")
 
# set y axis label
plt.ylabel('-----------y-----------')
 
# set x axis label
plt.xlabel('-----------x-----------')
 
# plot with grid
plt.grid(True)
 
# subplot 3
plt.subplot(2, 2, 3)
x2 = [0.1, 10, -30]
y2 = [40, -10 ,45]
 
# plotting the given graph
plt.semilogx(x2, y2,
             nonposx = "clip",
             color = "red",
             linewidth = 4)
# set the title
plt.title("CLIPPED")
 
# set y axis label
plt.ylabel('-----------y-----------')
 
# set x axis label
plt.xlabel('-----------x-----------')
 
# plot with grid
plt.grid(True)
 
# subplot 4
plt.subplot(2, 2, 4)
x2 = [0.1, 10, -30]
y2 = [40, -10, 45]
 
# plotting the given graph
plt.semilogx(x2, y2,
             nonposx = "mask",
             color = "green",
             linewidth = 4)
 
# set the title
plt.title("MASKED")
 
# set y axis label
plt.ylabel('-----------y-----------')
 
# set x axis label
plt.xlabel('-----------x-----------')
 
# plot with grid
plt.grid(True)
 
# show the plot
plt.show()

输出:

matplotlib.pyplot.semilogx()函数

示例6

使用nonposx参数。屏蔽删除无效值，而剪切将它们设置为一个非常低的可能值。

在下面的图中，剪裁和遮蔽之间的区别将更加清楚。

# import required library
import matplotlib.pyplot as plt
 
fig, axes = plt.subplots(nrows = 1,
                         ncols = 2,
                         figsize = (15,9))
# Or equivalently,  "plt.tight_layout()"
fig.tight_layout()
 
 
# subplot 1
x1 = [-1, 2, 0,
      -3, 5, 9,
      10, -3, -8,
      15, 12, 0.1,0.9]
 
y1 = [5, -2, 0,
      10, 20, 30,
      25, 28, 16,
      25, 28, 3, 5]
 
plt.subplot(1,2,1)
 
# plotting the graph
plt.semilogx(x1, y1,
             marker = ".",
             markersize = 20,
             nonposx = "clip",
             color = "green" )
 
# set the y-axis label
plt.ylabel('---y---')
 
# set the x-axis label
plt.xlabel('---x---')
 
# set the title
plt.title('CLIP')
 
# plot with grid
plt.grid(True)
 
 
# subplot 2
x2 = [-1, 2, 0,
      -3, 5, 9,
      10, -3, -8,
      15, 12, 0.1, 0.9]
 
y2 = [5, -2, 0,
      10, 20, 30,
      25, 28, 16,
      25, 28, 3, 5]
 
plt.subplot(1,2,2)
plt.semilogx(x2, y2,
             nonposx = "mask",
             color ="green",
             linewidth = 4,
             marker = ".",
             markersize = 20)
 
# set the title
plt.title('MASK')
 
# set the y-axis label
plt.ylabel('---y---')
 
# set the x-axis label
plt.xlabel('---x---')
 
# plot with grid
plt.grid(True)
 
# show the plot
plt.show()

输出:

matplotlib.pyplot.semilogx()函数

示例7

改变底数，根据方便可以设置底数，底数应大于1，以满足对数性质。

# importing the required libraries
import numpy as np
import matplotlib.pyplot as plt
 
# function that will
# output the values
def function(t):
    return np.exp(-t)*np.sin(2*np.pi.t)/2 + np.tan(t)
 
# define the x-axis values
t1 = np.arange(-0.01, 1.0, 0.08)
t2 = np.arange(0.0, 5.0, 0.02)
 
 
# subplot 1
plt.figure(figsize = (10,10))
plt.subplot(211)
 
# plot the graph
plt.semilogx(t1, f(t1),
             'bo', t2, f(t2),
             'k', color = "blue",
             basex = 3)
# set the title
plt.title("BASE: 3")
 
# subplot 2
plt.subplot(212)
 
# plot the graph
plt.semilogx(t2, np.cos(2*np.pi*t2),
             'r--', color = "brown",
             linewidth = 2, basex = 4)
 
# set the title
plt.title("BASE: 4")
 
# show the plot
plt.show()

输出:

matplotlib.pyplot.semilogx()函数

示例8

指定X轴上的次要xticks。默认情况下，它取决于图中几十年的数量。

# import required library
import matplotlib.pyplot as plt
 
fig, axes = plt.subplots(nrows = 2,
                         ncols = 2,
                         figsize = (10,7))
 
# Or equivalently,  "plt.tight_layout()"
fig.tight_layout()
 
# subplot 1
plt.subplot(2, 2, 1)
x = [1, 11]
y = [4, 6]
 
# plot the graph
plt.semilogx(x, y, marker = ".",
             markersize = 20,
             color = "green")
 
# set the title
plt.title("Without subsx - line ")
 
# plot with grid
plt.grid(True)
 
 
# subplot 2
plt.subplot(2, 2, 2)
x = [1, 11]
y = [4, 6]
 
# plot the graph
plt.semilogx(x, y, subsx = [2, 3, 9, 10],
             marker = ".", markersize = 20,
             color = "green")
 
# set the title
plt.title("With subsx - line ")
plt.grid(True)
 
 
# subplot 3
plt.subplot(2, 2, 3)
x = [1, 11]
y = [4, 6]
plt.semilogx(x, y, 'g^', marker = ".",
             markersize = 20,
             color = "blue")
plt.title("Without subsx - symbol ")
plt.grid(True)
 
 
# subplot 4
plt.subplot(2, 2, 4)
x = [1, 11]
y = [4, 6]
plt.semilogx(x, y, 'g^', subsx=[2, 3, 9, 10],
             marker = ".", markersize = 20,
             color = "blue")
plt.title("With subsx - symbol ")
plt.grid(True)
 
plt.show()

输出 :

matplotlib.pyplot.semilogx()函数