I'm working with matplotlib plotting and use ioff() to switch interactive mode off to suppress the automatic opening of the plotting window on figrue creation. I want to have full control over the figure and only see it when explicitely using the show() command.
Now apparently the built-in commands to clear figures and axes do not work properly anymore.
Example:
import numpy as np
import matplotlib.pyplot as mpp
class PlotTest:
def __init__(self,nx=1,ny=1):
# Switch off interactive mode:
mpp.ioff()
# Create Figure and Axes:
self.createFigure(nx, ny)
def createFigure(self,nx=1,ny=1):
self.fig, self.axes = mpp.subplots(nx,ny)
if nx*ny == 1:
self.axes = np.array([self.axes])
def linePlot(self):
X = np.linspace(0,20,21)
Y = np.random.rand(21)
self.axes[0].plot(X,Y)
P = PlotTest()
P.linePlot()
P.fig.show()
Now I was thinking I could use P.fig.clear() any time to simply clear P.fig, but apparently that's not the case.
Writing P.fig.clear() directly into the script and execute it together it works and all I see is an empty figure. However that's rather pointless as I never get to see the actual plot like that.
Doing P.fig.clear() manually in the console does not do anything, regardless if the plot window is open or not, all other possible commands fail as well:
P.fig.clf()
P.axes[0].clear()
P.axes[0].cla()
mpp.clf()
mpp.cla()
mpp.close(P.fig)
Wrapping the command into a class method doesn't work either:
def clearFig(self):
self.fig.clear()
EDIT ================
After a clear() fig.axes is empty, yet show() still shows the old plot with the axes still being plotted.
/EDIT ================
Is it because I switched off interactive mode?
If you add a call to plt.draw() after P.fig.clear() it clears the figure. From the docs,
This is used in interactive mode to update a figure that has been altered, but not automatically re-drawn. This should be only rarely needed, but there may be ways to modify the state of a figure with out marking it as stale. Please report these cases as bugs.
I guess this is not a bug as you have switched off interactive mode so it is now your responsibility to explicitly redraw when you want to.
You can also use P.fig.canvas.draw_idle() which could be wrapper in the class as clearFigure method.
Related
X = np.arange(20)
y = np.log(X**2)
# set title in Chinese
plt.title('你好')
sns.set_style({'axes.facecolor':'red','font.sans-serif':['SimSun']})
sns.lineplot(X,y,color="blue")
When I run this code first time in Jupyter,the title can be shown correctly, that means the font.sans-serif property worked well, but the backgroundcolor is not red.
But when I run the same code again for the second time, the axes.facecolor property works,the backgroundcolor changes to be red.
That makes me confused, why did this happend? And is there any other property like this?
According to the seaborn style aesthetics configuration tutorial, local style control should be done with (for instance):
with sns.axes_style("darkgrid"):
sns.lineplot(X,y,color="blue")
For global settings, use sns.set_style(...) before any plotting statement in order to it to be taken into account. This is why you have to launch it twice in Jupyter to take effect. Dedicating a cell to it right after the import could be a better solution.
I am new to Python, and somewhat new to object oriented programming. Can anyone explain what is going on and how things are typically done with a matplotlib GUI callback? I've taken the "event_handling example code" from the Matplotlib website and stripped it down for clarity. When you run this code it makes a plot, and if you press a key on the keyboard the press function is called. The press function is passed only event, but somehow every other variable from main program level appears inside the call to press but as a global variable, is this normal for functions? I can print the value of x, but if I try to change it then it makes a local variable version, worse yet now I have seemingly no way to access the global version anymore?
#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
x=np.random.rand(3)
y=np.random.rand(3)
def press(event):
print(x)
print('Local Var:', locals().keys())
print('Global Var:', globals().keys())
fig, ax = plt.subplots()
fig.canvas.mpl_connect('key_press_event', press)
ax.plot(x,y)
plt.show()
I have searched and had quite a hard time finding any reference that explains how to access or properly pass useful data in and out of the callback function so that a GUI event can do something useful, like update some data or feature of a plot?
So lets say I wanted to have the callback function modify y and re-plot the data. How is that typically done?
you have global access to x inside your callback, but can't modify it unless you specify it global.
def press(event):
global x
...
locals().keys() and globals().keys() are printing namespaces; I am unsure why you need to do that.
Your callback receives an event that you can use and manipulate inside the function.
Here is an example:
#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
x=np.random.rand(3)
y=np.random.rand(3)
def press(event):
print(event, event.key)
fig, ax = plt.subplots()
fig.canvas.mpl_connect('key_press_event', press)
ax.plot(x,y)
plt.show()
click on the plot window to set the focus.
pressing f should print the event object and set the plot full screen
pressing f again, will print f and restore the size of the window
pressing s will print s and will offer to save your figure
etc...
To learn more about how you can manipulate events, look up backend_bases in the very rich matplotlib web site. For example, you can set mouse_clicks events that allow you to capture canvas coordinates to add points or modify figures...
I am essentially writing a program that fits a spline to the points I click on a matplotlib window. I am using the LineBuilder class given as an example on the matplotlib website (code below, comments explain code that I have inserted). However, I want to exit the plot when I click on a certain region of the plotting window. The code I have works on one computer (matplotlib 1.2 I believe). On another computer (matplotlib 1.3) it does not continue the code that follows plt.show() after I click the appropriate part of the window. Instead, when I quit my GUI, it then decides to run the code that follows plt.show().
Does anybody know what might cause this? I'm not sure the exact nature of this problem. I do know that if I turn block=False in plt.show(), the code will run but I cannot build my line, so I have a feeling it might be related to this. But I can't find if that has changed. Code:
from matplotlib import pyplot as plt
class LineBuilder:
def __init__(self, line):
self.line = line
self.xs = list(line.get_xdata())
self.ys = list(line.get_ydata())
self.cid = line.figure.canvas.mpl_connect('button_press_event', self)
def __call__(self, event):
print 'click', event
if event.inaxes!=self.line.axes: return
self.xs.append(event.xdata)
self.ys.append(event.ydata)
self.line.set_data(self.xs, self.ys)
self.line.figure.canvas.draw()
#If x.data < previous, plt.close ('all')
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_title('click to build line segments')
line, = ax.plot([0], [0])
linebuilder = LineBuilder(line)
plt.show ()
#Code that follows does not run in newer (?) version
Matplotlib has an interactive and a non-interactive mode, and I've found as well that depending on system configuration or even how you launch your scipt (system shell, interactive shell, dedicated shell, IDLE shell...) this may be different.
If you call matplotlib.interactive(True) somewhere at the beginning of your code, this should be avoided. It worked for me in Matplotlib 0.99 and 1.3.1, on python 2.65 and 2.75 respectively. plt.ion() is also supposed to switch modes though I haven't tested it.
I've been struggling to achieve something that is trivial in Octave: to produce a series of plots, that change when I hit a key. Here's my octave code sample.
x = [1:10];
for c=1:3
plot(x,c.*x);
hold off;
input('a');
end
When I try to do the same in python, I realized that python matplotlib has the save function, which puts it in non-blocking mode, and so I have to close the figure using a mouse, for the next figure to be produced. And the next figure is at a random other location on the screen. How can I get python to imitate the above behavior? I've tried various combinations of ion(), ioff(), plt.show(), plt.draw(), but haven't succeeded.
You can do something fancier if you want, using mpl_connect
First import pylab
from pylab import *
Then define an updateData function that can be connected to the figure canvas.
i = 1
def updateData(event):
global i,x
i +=1
y = i*x
data.set_data(x,y)
ylim(y[0],y[-1])
draw()
i and x are global variables in this case. (This could be treated in better way, this is just an example!)
Then, create you plot and connect with your defined function.
f = figure()
data, = plot(x,x)
i=1
f.canvas.mpl_connect("key_press_event",updateData)
show()
Whenever you hit any key in the keyboard (When the figure window is selected) the function updateData is called, i is incremented and the plot updated.
Have fun!
Is there a way to close a pyplot figure in OS X using the keyboard (as far as I can see you can only close it by clicking the window close button)?
I tried many key combinations like command-Q, command-W, and similar, but none of them appear to work on my system.
I also tried this code posted here:
#!/usr/bin/env python
import matplotlib.pyplot as plt
plt.plot(range(10))
def quit_figure(event):
if event.key == 'q':
plt.close(event.canvas.figure)
cid = plt.gcf().canvas.mpl_connect('key_press_event', quit_figure)
plt.show()
However, the above doesn't work on OS X either. I tried adding print statements to quit_figure, but it seems like it's never called.
I'm trying this on the latest public OS X, matplotlib version 1.1.1, and the standard Python that comes with OS X (2.7.3). Any ideas on how to fix this? It's very annoying to have to reach for the mouse every time.
This is definitely a bug in the default OS X backend used by pyplot. Adding the following two lines at the top of the file switches to a different backend that works for me, if this helps anyone else.
import matplotlib
matplotlib.use('TKAgg')
I got around this by replacing
plt.show()
with
plt.show(block=False)
input("Hit Enter To Close")
plt.close()
A hack at its best, but I hope that helps someone
use interactive mode:
import matplotlib.pyplot as plt
# Enable interactive mode:
plt.ion()
# Make your plot: No need to call plt.show() in interactive mode
plt.plot(range(10))
# Close the active plot:
plt.close()
# Plots can also be closed via plt.close('all') to close all open plots or
# plt.close(figure_name) for named figures.
Checkout the "What is interactive mode?" section in this documentation
Interactive mode can be turned off at any point with plt.ioff()
When you have focus in the matplotlib window, the official keyboard shortcut is ctrl-W by this:
http://matplotlib.org/1.2.1/users/navigation_toolbar.html
As this is a very un-Mac way to do things, it is actually cmd-W. Not so easy to guess, is it?
If you are using an interactive shell, you can also close the window programmatically. See:
When to use cla(), clf() or close() for clearing a plot in matplotlib?
So, if you use pylab or equivalent (everything in the same namespace), it is just close(fig). If you are loading the libraries manually, you need to take close from the right namespace, for example:
import matplotlib.pyplot as plt
fig = plt.figure()
plt.plot([0,1,2],[0,1,0],'r')
fig.show()
plt.close(fig)
The only catch here is that there is no such thing as fig.close even though one would expect. On the other hand, you can use plt.close('all') to regain your desktop.