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Matplotlib: how to make the background transparent on Windows

I need the whole plot window to be transparent so that a chrome window, for example, on my desktop could be seen through the plot, so that I can add points to it while seeing what's behind it.
https://stackoverflow.com/a/45505906/13650485
The answer I've listed above is EXACTLY what I want to do, except my interactive system doesn't work with TK. I'd like to use Qt5Agg. When I run the code above, the system won't accept it -- it says QT5 is currently running. If I run it without QT already loaded, it creates a blank transparent window (yay!) but if I move it or click on the icon it turns opaque black without any plot. If I change tk to Qt5 it complains on lift. If I remove the "win" code, it has no transparency(obviously). I've tried adding everything I can think of to make the canvas transparent and I can change the color but not make it transparent.
import matplotlib
# make sure Tk backend is used
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
# create a figure and some subplots
fig, ax = plt.subplots(figsize=(4,2))
ax.plot([2,3,5,1])
fig.tight_layout()
win = plt.gcf().canvas.manager.window
win.lift()
win.attributes("-topmost", True)
win.attributes("-transparentcolor", "white")
plt.show()
When I made the changes suggested by: eyllanesc
I found within a vanilla Spyder 4.1.3 | Python 3.7.7 64-bit | Qt 5.9.6 | PyQt5 5.9.2 | Windows 10
In order to import QtCore I had to first
conda install pyqt
not enough, so then conda install pyqt5
and also conda update --all
When I did that, the code ran without errors. This is a better first result!, but I still only get the frozen mpl.fig window. This time, however, it is white. . . The console returns, but the mpl window hangs. Run again, a new frozen window. Restart and run again: same result.
I hope that this is a simple error; please teach this newby.
#eyllanesc
Revised: Python screen tracing application – needs a mostly transparent plot window.
I need the whole plot window to be transparent so that a chrome window, for example, on my desktop could be seen through the plot, so that I can add plot (x, y) points to it while seeing what's behind it.
Adding the command win.setWindowFlags(QtCore.Qt.FramelessWindowHint) did indeed make the window transparent, but it made the tool bar transparent, got rid of the title bar, and removed the ability to move or resize the window. It also made it so that the graph area was not sensitive to the mouse unless I was over the line. I added the facecolor attribute to the subplots command so I could see what was going on. As long as I put a non-zero value for either the fig-alpha or the ax-alpha, the graph is sensitive to the mouse over the whole area.
I need to be able to move and resize the window and would like to have the toolbar be opaque or at least sensitive to the mouse over the whole toolbar. Can you help with this? Thanks for past help!
## Python Code Fragment by Helen for Windows 10
## to test sequence creating plot with transparent
## background (to be used to trace and record xy pairs)
from PyQt5 import QtCore
import matplotlib
matplotlib.use("Qt5Agg") #define backend, must be before pyplot is imported
import matplotlib.pyplot as plt
# create a figure and a subplot
fig,ax = plt.subplots(figsize=(4, 2),facecolor=(1.,1.,0.,0.1)) #facecolor of figure
fig.patch.set_alpha(0.1)
ax.patch.set_alpha(0.1)
# plot some fixed points
ax.plot([2, 3, 5, 1])
fig.tight_layout()
#make window transparent to the desktop
win = plt.gcf().canvas.manager.window
win.setAttribute(QtCore.Qt.WA_NoSystemBackground, True)
win.setAttribute(QtCore.Qt.WA_TranslucentBackground, True)
win.setStyleSheet("background:transparent")
win.setWindowFlags(QtCore.Qt.FramelessWindowHint)
win.setWindowTitle("My App")
plt.show()

You have to use the Qt flags, tested on Linux:
from PyQt5 import QtCore
import matplotlib
# make sure Tk backend is used
matplotlib.use("Qt5Agg")
import matplotlib.pyplot as plt
# create a figure and some subplots
fig, ax = plt.subplots(figsize=(4, 2))
fig.patch.set_alpha(0.0)
ax.patch.set_alpha(0.0)
ax.plot([2, 3, 5, 1])
fig.tight_layout()
win = plt.gcf().canvas.manager.window
win.setAttribute(QtCore.Qt.WA_NoSystemBackground, True)
win.setAttribute(QtCore.Qt.WA_TranslucentBackground, True)
win.setStyleSheet("background:transparent")
plt.show()

Jupyter Notebook: duplicated scatter plot using when using ipywidgets

I'm trying to control the display of a scatter plot with a checkbox. When I built it using the interact function it worked as expected. The plot was shown or hidden based on the value in the checkbox.
import matplotlib.pyplot as plt
from ipywidgets import interact, widgets
%matplotlib inline
def on_change(Display):
if Display == True:
plt.scatter(x,y)
plt.show()
return Display
interact(on_change, Display=False);
When I tried to do the same thing using the observe function every time I clicked on the checkbox I get an additional plot displayed below. What do I need to do to get it to redraw the same plot so it works like the example above?
I suppose something in the interact example is clearing the display but it's not clear how to do this manually.
import matplotlib.pyplot as plt
from ipywidgets import interact, widgets
%matplotlib inline
x = [1,2,3,4,5,6,7,8]
y = [5,2,4,2,1,4,5,2]
def on_change(change):
if change['new'] == True:
scat = plt.scatter(x,y)
plt.show()
cb = widgets.Checkbox(False, description = "Display")
cb.observe(on_change, names='value')
display(cb)

A couple of alterations I made to your example to hopefully demonstrate what you want. I have taken a more object-oriented route, not sure if you specifically wanted to avoid it but it helps achieve your desired outcome, it seems like you are moving towards a simple GUI here.
1) Include an Output widget (out) - basically a cell output which you can display like a normal widget. You can use a context manager block (with out:) when you want to print to that specific output widget. You can also clear the widget with out.clear_output()
2) Use the object oriented interface in matplotlib rather than using plt. I find this easier to control which plots are displayed and in which location at the right times.
temporarily suspend the interactive matplotlib with plt.ioff()
Create your figure and axis with fig, ax = plt.subplots(). NB figures can have multiple axes/subplots but we only need one.
'plot' the scatter data to your axis using ax.scatter(x,y), but this won't cause it to appear.
Explicitly display the figure with display(fig).
I'm assuming you want your figure to be replotted each time you check the box, so I have included it in the observe function. If your figure doesn't change, it would make sense to move it outside of the loop.
import matplotlib.pyplot as plt
from ipywidgets import interact, widgets
%matplotlib inline
out = widgets.Output()
x = [1,2,3,4,5,6,7,8]
y = [5,2,4,2,1,4,5,2]
def on_change(change):
if change['new'] == True:
with out:
plt.ioff()
fig,ax = plt.subplots()
ax.scatter(x,y)
display(fig)
else:
out.clear_output()
cb = widgets.Checkbox(False, description = "Display")
cb.observe(on_change, names='value')
display(cb)
display(out)

Matplotlib figure not updating on data change

I'm implementing an image viewer using matplotlib. The idea is that changes being made to the image (such as filter application) will update automatically.
I create a Figure to show the inital image and have added a button using pyQt to update the data. The data does change, I have checked, but the Figure does not. However, if after I've pressed the filter application button, I move the image using matplotlib's standard tool bar, the image is then updated.
I assume I'm doing something wrong when updating the image, but since the fact of moving it actually forces the update, it then shows the data change. I would like for this to happen when I press the button, though.
Below is some of the code. This is the initial figure initialization, which shows the original image:
self.observableFig = Figure((4.0, 4.0), dpi=100)
self.canvas = FigureCanvas(self.observableFig)
self.canvas.setParent(self.observableWindow)
self.canvas.setFocusPolicy(Qt.StrongFocus)
self.canvas.setFocus()
self.canvas.mpl_connect('button_press_event', self.on_click)
# Showing initial data on Window
self.observableFig.clear()
self.observableAxes = self.observableFig.add_subplot(1, 1, 1)
min, max = self.min, self.max
self.observableAxes.imshow(
self.data,
vmin=min,
vmax=max,
origin='lower'
)
And this is the event for when the button that changes the data is pressed:
self.observableAxes.imshow(self.data/2, origin='lower')
# plt.clf()
# plt.draw()
# plt.show()
I have tried draw(), show(), basically anything I've found on pyplot about this. I have also tried both with and without plt.ion() at the beginning, but it hasn't made a difference in this.
Thanks in advance.

The reason that nothing is updating is that you're trying to use pyplot methods for a figure that's not a part of the pyplot state machine. plt.draw() won't draw this figure, as plt doesn't know the figure exists.
Use fig.canvas.draw() instead.
Regardless, it's better to use fig.canvas.draw() that plt.draw(), as it's clear which figure you're drawing (the former draws one, the latter draws all, but only if they're tracked by pyplot).
Try something along these lines:
import numpy as np
import matplotlib.pyplot as plt
data = np.random.random((10,10))
# To make a standalone example, I'm skipping initializing the
# `Figure` and `FigureCanvas` and using `plt.figure()` instead...
# `plt.draw()` would work for this figure, but the rest is identical.
fig, ax = plt.subplots()
ax.set(title='Click to update the data')
im = ax.imshow(data)
def update(event):
im.set_data(np.random.random((10,10)))
fig.canvas.draw()
fig.canvas.mpl_connect('button_press_event', update)
plt.show()

Tkinter keeps creating embedded plots instead of updating the current plot

I am aware that there are couple of questions on this around the web but unfortunately none of those helped me with this. My relevant matplotlib imports are:
import matplotlib
matplotlib.use("TkAgg")
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib.figure import Figure
Below is how I call for new plots:
self.myFig1 = Figure(figsize = (10, 4), tight_layout = True)
self.myPlot1 = self.myFig1.add_subplot(111)
self.myPlot1.plot([blah],[blah])
canvas1 = FigureCanvasTkAgg(self.myFig1, self.myFrame)
canvas1.show()
canvas1.get_tk_widget().grid()
I have a refresh button that sort of keeps calling the function that ends up creating this plot, but I need one embedded plot which is updated after every button click, not recreated. I have tried things like Figure.close(), Figure.clf() but none worked. I'd appreciate your help with this.
Additional info: The reason it keeps creating a new plot is because I keep .grid-ing it over and over again. So I deleted the .grid() part of the code and I tried something like this below which did not work:
self.myFig1.clf()
self.myFig1 = Figure(figsize = (10, 4), tight_layout = True)
self.myPlot1 = self.myFig1.add_subplot(111)
self.myPlot1.plot([blah],[blah])
canvas1 = FigureCanvasTkAgg(self.myFig1, self.myFrame)
canvas1.draw()
This just destroys the figure, canvas, everything and doesn't plot anything.

self.myFig.clear()
self.myPlot = self.myFig.add_subplot(111, **self.nadalkwArgs)
self.myPlot.plot([series1], [series2])
self.myFig.canvas.draw()
Is what solved my problem. Your "refresh plot" button or method should have this in order to keep the canvas, clear the old plot, make the new plot and keep plot style elements such as xlabel, ylabel etc. So basically, first you clear the figure(not the subplot, self.myPlot.clear() would clear the plot but you can't have your kwargs that way), and then you recreate the subplot with kwargs and then you plot, and finally you .canvas.draw()

There is no need to recreate a new canvas or fig.
After grid your FigureCanvasTkAgg, you can reset line in button callback only by:
self.myPlot1.set_data(xdata,ydata)
self.myFig.canvas.draw()

Print variable in large font in python figure

I have borrowed some code from another source and I want to edit the figure produced. Here is the relevant (i think) code from the script.
import gtk #the gui toolkit we'll use:
from matplotlib.figure import Figure
from Tkinter import *
from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg as FigureCanvas
#create a window to put the plot in
win = gtk.Window()
#connect the destroy signal (clicking the x in the corner)
win.connect("destroy", quit_app)
win.set_default_size(600,500)
#create a plot:
fig = Figure()
ax = fig.add_subplot(111,xlabel='Time Step', ylabel='Temp (deg C)', axisbg='black')
ax.set_ylim(0,100) # set limits of y axis.
canvas = FigureCanvas(fig) #put the plot onto a canvas
win.add(canvas) #put the canvas in the window
#show the window
win.show_all()
win.set_title("ready to receive data");
line, = ax.plot(times,yvals, color='red')
while(1):
line.set_ydata(yvals) # draw the line
fig.canvas.draw() # update the Canvas
win.set_title("Temp: "+str(yvals[49])+" deg C")
I don't know whether or not all the code above is necessary - but that is all the 'plot' related code I could find.
So anyway the code works in my program perfectly.
There are TWO tasks I would like to create:
(1) What I want is to include that 'str(yvals[49])' variable, which is currently being displayed in the title of the window, to be displayed in large font underneath the plot. So I think I need to make the window size a little bigger to accompany the text but not sure how to print it.
(2) I manged to change the background of the plot itself to black that plots a red line. But how can I change the background of the window itself to all black and the x/y axis to red as well.
Thanks!!

(1) What you are most probably looking for it the matplotlib text command. Have a look at http://matplotlib.org/users/pyplot_tutorial.html section working with text. It might be convenient to create two separate axes, so you can truly put the text below the whole figure. Maybe it is enough to place the text at xlabel position?
import matplotlib.pyplot as plt
plt.xlabel('yourtext')
(2) There are already good answers out there that might help you: e.g. How to change the pylab window background color?
As for the color of the axis Changing the color of the axis, ticks and labels for a plot in matplotlib
Have also a look at Matplotlib figure facecolor (background color) in case you want to save the figure.