I can embed a matplotlib figure in a GTK application by following some of the examples, like this one in the matplotlib documentation. However, when I resize the application window, there is a flicker of white as the figure is being redrawn.
This isn't that much of a problem if the figure I am going to show also has a white background. But if I am using a dark figure style (i.e. to match the appearance of the rest of my application), there is always a white flicker until the figure is drawn in the correct style. This is somewhat jarring if the rest of the application is using a darker theme.
Is there a way I can control the background that is shown by a matplotlib backend while the figure is being drawn?
If I could set the color that appears while drawing, there would still be a flickering effect of the data and axes of the plot being redrawn, but at least the background would stay the same color before and after the figure is drawn.
To illustrate the unwanted effect, if I add a dark plot style to the example linked above, each time I resize the window I can see the white flicker.
import gi
gi.require_version('Gtk', '3.0')
from gi.repository import Gtk
from matplotlib.backends.backend_gtk3agg import (
FigureCanvasGTK3Agg as FigureCanvas)
from matplotlib.figure import Figure
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('dark_background') # use the dark style so flicker is more apparent
win = Gtk.Window()
win.connect("delete-event", Gtk.main_quit)
win.set_default_size(400, 300)
win.set_title("Embedding in GTK")
fig = Figure(figsize=(5, 4), dpi=100)
ax = fig.add_subplot()
t = np.arange(0.0, 3.0, 0.01)
s = np.sin(2*np.pi*t)
ax.plot(t, s)
sw = Gtk.ScrolledWindow()
win.add(sw)
# A scrolled window border goes outside the scrollbars and viewport
sw.set_border_width(10)
canvas = FigureCanvas(fig) # a Gtk.DrawingArea
canvas.set_size_request(800, 600)
sw.add(canvas)
win.show_all()
Gtk.main()
(Resizing the window to very small sizes doesn't cause the flickering, presumably because once the figure is drawn at the smallest size, it does not get redrawn, just clipped.)
I'm using GTK 3, matplotlib 3.4.3, and Python 3.8.10 on Ubuntu.
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I have a Python custom visual inside a PowerBI report. Normally, this automatically fills the available space - and set the aspect ratio accordingly. However, when I set a facecolor background color (say None for a transparent visual, but also any other color), then the visual does not fill the space anymore, just keep the default matplotlib aspect ratio. Any ideas on how to force the chart to autofill?
This renders correctly with autofill:
import matplotlib.pyplot as plt
plt.plot(dataset['Column1'],dataset['Column2'])
plt.show()
But this has the aspect ratio problem:
import matplotlib.pyplot as plt
plt.figure(facecolor='red')
plt.plot(dataset['Column1'],dataset['Column2'])
plt.show()
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plt.imshow(G,interpolation='nearest')
I assume its some interpolation problem... maybe also there is a 0.5 shift, so that gridpoints 1 -> 1.5 and are then interpolated.
First switching back to matplotlib 1.5.1 and then
mpl.use('Agg')
solved it
see here:
Generating a PNG with matplotlib when DISPLAY is undefined
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I tried using the onscroll method which uses mouse scroll event and we can mpl_connect it on the canvas (Matplotlib). This seems to work fine but when I put this canvas on PyQt5 canvas, the scrolling stops. Is there any way I can implement this in PyQt5?
I have tried to keep this question simple because I want a generic answer, but if someone is interested, I am ready to share the (non-working) code.
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The entire code is fairly large to post here. But I am using
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When I launch qtconsole with the --colors=linux option and plot something the frame of the plot is blackened so I cannot see the axes because the qtconsole background is also black.
I used to launch this before without problem but have this problem after a recent update of pandas. I am not sure about what changed but I thought there might be a setting I can change to fix this anyway without worrying about what the update modified that broke this.
It looks like the axes are set to transparent by default (this was not happening before).
The following plots as desired, showing the white axes on black background:
import pandas as pd
import matplotlib.pylab as plt
fig = plt.figure()
fig.patch.set_alpha(1)
temp = pd.Series(range(100))
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I would also like to set this behavior as the default one. I have not been able to do that yet. This seemed like a good lead,
http://matplotlib.org/users/customizing.html
but I could not find an option for exactly that yet.
Any suggestion is welcome. Thank you.