该matlab代码对应的matplotlib代码是什么

Question

我试图摆脱 matlab 并使用 python + matplotlib 代替。然而，我还没有真正弄清楚 matplotlib 等价于 matlab 'handles' 的是什么。这里有一些 matlab 代码，我在其中返回句柄，以便我可以更改某些属性。使用 matplotlib 的这段代码的等价物是什么？我经常在 matlab 中使用句柄的“Tag”属性，并使用“findobj”。这也可以用 matplotlib 来完成吗？

% create figure and return figure handle
h = figure();
% add a plot and tag it so we can find the handle later
plot(1:10, 1:10, 'Tag', 'dummy')
% add a legend
my_legend = legend('a line')
% change figure name
set(h, 'name', 'myfigure')
% find current axes
my_axis = gca();
% change xlimits
set(my_axis, 'XLim', [0 5])
% find the plot object generated above and modify YData
set(findobj('Tag', 'dummy'), 'YData', repmat(10, 1, 10))

Answer 1

有一个 findobj 方法也是 matplotlib ：

import matplotlib.pyplot as plt
import numpy as np

h = plt.figure()
plt.plot(range(1,11), range(1,11), gid='dummy')
my_legend = plt.legend(['a line'])
plt.title('myfigure')  # not sure if this is the same as set(h, 'name', 'myfigure')
my_axis = plt.gca()
my_axis.set_xlim(0,5)
for p in set(h.findobj(lambda x: x.get_gid()=='dummy')):
    p.set_ydata(np.ones(10)*10.0)
plt.show()

请注意plt.plot 中的 gid 参数通常由 matplotlib 使用（仅）当后端设置为“svg”时。它使用 gid 作为某些分组元素的 id 属性（例如 line2d、patch、text ）。

Answer 2

我没有使用过matlab，但我认为这就是你想要的

import matplotlib
import matplotlib.pyplot as plt

x = [1,3,4,5,6]
y = [1,9,16,25,36]
fig = plt.figure()
ax = fig.add_subplot(111)  # add a plot
ax.set_title('y = x^2')
line1, = ax.plot(x, y, 'o-')       #x1,y1 are lists(equal size)
line1.set_ydata(y2)                #Use this to modify Ydata
plt.show()

当然，这只是一个基本图，还有更多内容。尽管 this 找到您想要的图表并查看其源代码。

Answer 3

# create figure and return figure handle
h = figure()

# add a plot but tagging like matlab is not available here. But you can
# set one of the attributes to find it later. url seems harmless to modify.
# plot() returns a list of Line2D instances which you can store in a variable  
p = plot(arange(1,11), arange(1,11), url='my_tag')

# add a legend
my_legend = legend(p,('a line',)) 
# you could also do 
# p = plot(arange(1,11), arange(1,11), label='a line', url='my_tag')
# legend()
# or
# p[0].set_label('a line')
# legend()

# change figure name: not sure what this is for.
# set(h, 'name', 'myfigure') 

# find current axes
my_axis = gca()
# change xlimits
my_axis.set_xlim(0, 5)
# You could compress the above two lines of code into:
# xlim(start, end)

# find the plot object generated above and modify YData
# findobj in matplotlib needs you to write a boolean function to 
# match selection criteria. 
# Here we use a lambda function to return only Line2D objects 
# with the url property set to 'my_tag'
q = h.findobj(lambda x: isinstance(x, Line2D) and x.get_url() == 'my_tag')

# findobj returns duplicate objects in the list. We can take the first entry.
q[0].set_ydata(ones(10)*10.0) 

# now refresh the figure
draw()