更改网格间隔并在Matplotlib中指定刻度标签 [英] Change grid interval and specify tick labels in Matplotlib

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问题描述

我试图在网格图中绘制计数,但我无法弄清楚我是如何去做的。我想要:


  1. 以5为间隔点缀网格


  2. 只有每20个主要的刻度标签


  3. 我希望刻度在图之外。

  4. $ b
  5. 在这些网格中有计数


我检查了潜在的重复项,例如此处这里,但我一直无法弄清楚。



这是我的代码。 p>

  import matplotlib.pyplot as plt 
from matplotlib.ticker import MultipleLocator,FormatStrFormatter

for key ,sort(data.items())中的值:
x = value [0] [2]
y = value [0] [3]
count = value [0] [4]

fig = plt.figure()
ax = fig.add_subplot(111)

ax.annotate(count,xy =(x,y),size = 5)
#覆盖我只得到最后一个数据点

plt.close()
#没有这个,我得到未能分配位图错误

plt.suptitle( 'count count',fontsize = 12)
ax.set_xlabel('x')
ax.set_ylabel('y')
plt.axes()。set_aspect('equal')

plt.axis([0,1000,0,1000])
#这个间隔为200

majorLocator = MultipleLocator(20)
majorFormatter = FormatStrFormatter('%d')
minorLocator = MultipleLocator(5)
#我希望小网格为5,主网格为20
plt.grid()

filename ='C:\Users\Owl\Desktop\Plot.png'
plt.savefig(文件名,dpi = 150)
plt.close()

这就是我得到的。



我也有问题覆盖数据点,我也遇到了麻烦...任何人都可以请帮助我是否有问题?

解决方案

您的代码有几个问题。 >首先是大的:


  1. 您在循环的每次迭代中创建一个新图形和一个新坐标轴→
    fig = plt.figure ax = fig.add_subplot(1,1,1)外部循环。


  2. 不要使用定位器。使用正确的关键字调用函数 ax.set_xticks() ax.grid()


  3. 使用 plt.axes(),您可以再次创建新的轴。使用 ax.set_aspect('equal')


次要的东西:
您不应该将类似MATLAB的语法(如 plt.axis())与目标语法混合使用。
使用 ax.set_xlim(a,b) ax.set_ylim(a,b)



这应该是一个最小的例子:

  import numpy as np 
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.add_subplot(1,1,1)

#Major每20个小刻度,每5个小元刻度b $ b major_ticks = np.arange(0,101,20)
minor_ticks = np.arange(0,101,5)

ax。 set_xticks(major_ticks)
ax.set_xticks(minor_ticks,minor = True)
ax.set_yticks(major_ticks)
ax.set_yticks(minor_ticks,minor = True)

#和一个相应的网格
ax.grid(which ='both')

#或者如果你想为网格设置不同的设置:
ax.grid(which ='minor ',alpha = 0.2)
ax.grid(which ='major',alpha = 0.5)

plt.show()
pre>

输出是这样的:


I am trying to plot counts in gridded plots, but I am not being able to figure out how I go about it. I want to:

  1. Have dotted grids at an interval of 5

  2. Have major tick labels only every 20

  3. I want the ticks to be outside the plot.

  4. Have "counts" inside those grids

I have checked for potential duplicates such as here and here, but I have not been able to figure it out.

This is my code.

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, FormatStrFormatter

for key, value in sorted(data.items()):
    x = value[0][2]
    y = value[0][3]
    count = value[0][4]

    fig = plt.figure()
    ax = fig.add_subplot(111)

    ax.annotate(count, xy = (x, y), size = 5)
    # Overwrites and I only get the last data point

    plt.close()
    # Without this, I get "fail to allocate bitmap" error

plt.suptitle('Number of counts', fontsize = 12)
ax.set_xlabel('x')
ax.set_ylabel('y')
plt.axes().set_aspect('equal')

plt.axis([0, 1000, 0, 1000])
# This gives an interval of 200

majorLocator   = MultipleLocator(20)
majorFormatter = FormatStrFormatter('%d')
minorLocator   = MultipleLocator(5)
# I want minor grid to be 5 and major grid to be 20
plt.grid()

filename = 'C:\Users\Owl\Desktop\Plot.png'
plt.savefig(filename, dpi = 150)
plt.close()

This is what I get.

I also have a problem of overwriting the data points, which I am also having trouble with... Could anybody PLEASE help me with this problem?

解决方案

There are several problems in your code.

First the big ones:

  1. You are creating a new figure and a new axes in every iteration of your loop → put fig = plt.figure and ax = fig.add_subplot(1,1,1) outside of the loop.

  2. Don't use the Locators. Call the functions ax.set_xticks() and ax.grid() with the correct keywords.

  3. With plt.axes() you are creating a new axes again. Use ax.set_aspect('equal').

The minor things: You should not mix the MATLAB-like syntax like plt.axis() with the objective syntax. Use ax.set_xlim(a,b) and ax.set_ylim(a,b)

This should be a working minimal example:

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)

# Major ticks every 20, minor ticks every 5
major_ticks = np.arange(0, 101, 20)
minor_ticks = np.arange(0, 101, 5)

ax.set_xticks(major_ticks)
ax.set_xticks(minor_ticks, minor=True)
ax.set_yticks(major_ticks)
ax.set_yticks(minor_ticks, minor=True)

# And a corresponding grid
ax.grid(which='both')

# Or if you want different settings for the grids:
ax.grid(which='minor', alpha=0.2)
ax.grid(which='major', alpha=0.5)

plt.show()

Output is this:

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