是否可以不依赖于数据集的长度和缩放，来改变比例尺上滴答的频率？

Question

当我用matplotlib绘制数据时，我的x轴上总是有5-9个滴答，与我绘制的范围无关，如果我放大x轴，滴答间距就会减小，所以我仍然会看到5-9个滴答。

不过，我想在我的x轴20-30滴答！

我可以做到以下几点：

from matplotlib import pyplot as plt
import numpy as np

x = [5, 10, 15, 20, 25, 30, 35, 40, 45, 50] 
y = [1, 4, 3, 2, 7, 6, 9, 8, 10, 5] 

number_of_ticks_on_x_axis = 20

plt.plot(x, y) 
plt.xticks(np.arange(min(x), max(x)+1, (max(x) - min(x))/number_of_ticks_on_x_axis))

plt.show() 

如果我现在放大x轴，在现有的轴之间不会出现新的刻度.不管我放大多远，我还是希望有20只蜱。

Answer 1

假设你想修正“不”。X轴上的蜱

...
from matplotlib.ticker import MaxNLocator
...
fig, ax = plt.subplots()
ax.xaxis.set_major_locator(MaxNLocator(15, min_n_ticks=15))
...

请看文档 for MaxNLocator

示例

In [36]: import numpy as np 
    ...: import matplotlib.pyplot as plt                                                  
In [37]: from matplotlib.ticker import MaxNLocator                                        
In [38]: fig, ax = plt.subplots(figsize=(10,4))                                           
In [39]: ax.grid()                                                                        
In [40]: ax.xaxis.set_major_locator(MaxNLocator(min_n_ticks=15))                          
In [41]: x = np.linspace(0, 1, 51)                                                        
In [42]: y = x*(1-x)                                                                      
In [43]: plt.plot(x, y)                                                                   
Out[43]: [<matplotlib.lines.Line2D at 0x7f9eab409e10>]

给出

​

​

当我放大到曲线的最大值时

​

​

Answer 2

可以将回调函数链接到画布中的事件。在这种情况下，您可以触发一个函数，该函数在重绘发生时更新轴。

from matplotlib import pyplot as plt
import numpy as np

x = [5, 10, 15, 20, 25, 30, 35, 40, 45, 50] 
y = [1, 4, 3, 2, 7, 6, 9, 8, 10, 5] 

n = 20

plt.plot(x, y) 
plt.xticks(np.arange(min(x), max(x)+1, (max(x) - min(x))/n), rotation=90)

def on_zoom(event):
    ax = plt.gca()
    fig = plt.gcf()
    x_min, x_max = ax.get_xlim()
    ax.set_xticks(np.linspace(x_min, x_max, n))
    # had to add flush_events to get the ticks to redraw on the last update.
    fig.canvas.flush_events()

fig = plt.gcf()
fig.canvas.mpl_disconnect(cid)
cid = fig.canvas.mpl_connect('draw_event', on_zoom)