I am using matplotlib with interactive mode on and am performing a computation, say an optimization with many steps where I plot the intermediate results at each step for debugging purposes. These plots often fill the screen and overlap to a large extent.
My problem is that during the calculation, figures that are partially or fully occluded don't refresh when I click on them. They are just a blank grey.
I would like to force a redraw if necessary when I click on a figure, otherwise it is not useful to display it. Currently, I insert pdb.set_trace()'s in the code so I can stop and click on all the figures to see what is going on
Is there a way to force matplotlib to redraw a figure whenever it gains mouse focus or is resized, even while it is busy doing something else?
Something like this might work for you:
import matplotlib.pyplot as plt
import numpy as np
plt.ion() # or leave this out and run with ipython --pylab
# draw sample data
fig = plt.figure()
ax = fig.add_subplot(111)
line, = ax.plot(np.random.rand(10))
class Refresher:
# look for mouse clicks
def __init__(self, fig):
self.canvas = fig.canvas
self.cid = fig.canvas.mpl_connect('button_press_event', self.onclick)
# when there is a mouse click, redraw the graph
def onclick(self, event):
self.canvas.draw()
# remove sample data from graph and plot new data. Graph will still display original trace
line.remove()
ax.plot([1,10],[1,10])
# connect the figure of interest to the event handler
refresher = Refresher(fig)
plt.show()
This will redraw the figure whenever you click on the graph.
You can also experiment with other event handling like
ResizeEvent - figure canvas is resized
LocationEvent - mouse enters a new figure
check more out here:
Have you tried to call plt.figure(fig.number) before plotting on figure fig and plt.show() after plotting a figure? It should update all the figures.
Related
I have two issues with my python plot that would be grateful if anyone could help me with:
1- I wonder if it is possible in python to have the option for the plots after display to add horizontal or vertical lines, so that these new lines could be added, moved or deleted without the need to run the code again.
to say it more clearly, I am looking for additional features that adding them does not need to change the code and they only enable me to manually draw on the already plotted image.
2- I want to plot a very large image in the real size, So that I need to add the horizontal and vertical slide bars to be able to scroll up/down or left/right in the plot?
I need to combine these two ability for my project, can someone help me with that?
1- You can't physically draw on it, but you can make a plot in matplotlib interactive as follows:
import matplotlib.pyplot as plt
plt.ion() # turns on interactive mode
fig = plt.figure()
ax = fig.add_subplot()
plt.ylim(-10, 10)
plt.xlim(0, 10)
while True:
plt.axhline(float(input("number")))
fig.canvas.draw()
fig.canvas.flush_events() # draws
This program allows you to create horizontal lines based on user input.
I think you can solve 2 with tkinter, but that would be pretty difficult. There might also an easier way. See this stack overflow question for an example of an interactive plot in tkinter. I believe this plot can be made bigger and scrollable, but I am not sure.
I am facing couple of issues. First, I wanted all the plots in a separate window. For this, I successfully changed the settings and I got the separate window. The problem is, I got all the plots in same figures, which is bad. Second issue is, how do I inscribe window pan to the Ipconsole? I donot want a separate window. I want this window inside the console?
For the first issue, you can have your plots in different figures by using figure this way:
import matplotlib.pyplot as plt
plt.figure()
# Plot your first graph(s)
plt.figure()
# Plot your other graph(s)
plt.show()
Each time you call figure, a new window is created. For more information on figure, you can check the doc
I'm using matplotlib to show a picture but I want to hide the window frame.
I tried the code frameon=False in plt.figure() but the window frame is still there. Just the background color turns to grey.
Here is the code and running result. The picture was showing with the window even I add the "frameon=False" in the code.
frameon suppresses the figure frame. What you want to do is show the figure canvas in a frameless window, which cannot be managed from within matplotlib, because the window is an element of the GUI that shows the canvas. Whether it is possible to suppress the frame and how to do that will depend on the operating system and the matplotlib backend in use.
Let's consider the tk backend.
import matplotlib
# make sure Tk backend is used
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
# turn navigation toolbar off
plt.rcParams['toolbar'] = 'None'
# create a figure and subplot
fig, ax = plt.subplots(figsize=(2,2))
#remove margins
fig.subplots_adjust(0,0,1,1)
# turn axes off
ax.axis("off")
# show image
im = plt.imread("https://upload.wikimedia.org/wikipedia/commons/8/87/QRCode.png")
ax.imshow(im)
# remove window frame
fig.canvas.manager.window.overrideredirect(1)
plt.show()
I'm using matplotlib to show a picture but I want to hide the window frame.
I tried the code frameon=False in plt.figure() but the window frame is still there. Just the background color turns to grey.
Here is the code and running result. The picture was showing with the window even I add the "frameon=False" in the code.
frameon suppresses the figure frame. What you want to do is show the figure canvas in a frameless window, which cannot be managed from within matplotlib, because the window is an element of the GUI that shows the canvas. Whether it is possible to suppress the frame and how to do that will depend on the operating system and the matplotlib backend in use.
Let's consider the tk backend.
import matplotlib
# make sure Tk backend is used
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
# turn navigation toolbar off
plt.rcParams['toolbar'] = 'None'
# create a figure and subplot
fig, ax = plt.subplots(figsize=(2,2))
#remove margins
fig.subplots_adjust(0,0,1,1)
# turn axes off
ax.axis("off")
# show image
im = plt.imread("https://upload.wikimedia.org/wikipedia/commons/8/87/QRCode.png")
ax.imshow(im)
# remove window frame
fig.canvas.manager.window.overrideredirect(1)
plt.show()
Using PyQt4 and matplotlib I have connected a button click to perform some calculation and render a graph. The tight_layout() only applies after clicking the button a second time.
When I'm done setting up the axes and putting data on the graph, I call
fig.tight_layout()
fig.canvas.draw()
I've tried to fake a second button press without success:
from PyQt4 import QtGui
QtGui.QApplication.processEvents()
fig.tight_layout()
fig.canvas.draw()
QtGui.QApplication.processEvents()
fig.tight_layout()
fig.canvas.draw()
My thought was that the Qt surface wasn't recognized as dirty, but resizing the window redraws the chart with the same loose layout. The tight layout does apply when I clear the axes and repopulate the chart.
How can I make tight_layout() apply the first time the graph is drawn?
Seems like there's no need to explicitly call draw or processEvents. Instead, I just needed a call to canvas.updateGeometry().