In this link, they explain how to use subplots and save the result as an .mp4 file. It works great. However, it saves the video as if the window were not maximized. here, they explain how to automatically maximize when displaying, that is, when using plt.show(), which works. But again, when saving automatically by using .save, it does not save the maximized the version. Does anyone know how to do that (if it is not too complicated)?
Thanks!
You can obtain the dimensions you want by adjusting figsize using:
fig, ax = plt.subplots(figsize=(20, 10))
where 20 and 10 are respectively width and height of the figure in inches
and you can also provide a dpi option (defaults to 100) :
fig, ax = plt.subplots(figsize=(20, 10), dpi=80)
When you save the figure, dpi option is still available:
plt.savefig("test.png", dpi=80)
For animations, it's the same:
ani.save("test.mp4", dpi=80)
Related
Using the Spyder IDE, I have created a matplotlib plot and changed the face (background) color of both the figure object and the axes object to black. When I try to save the figure using plt.savefig(...) the axes, title, and axes label are not included.
I have tried implementing the standard advice of adding bbox_inches='tight' to the plt.savefig() function for when the axes are cut off:
plt.savefig("my_fig_name.png", bbox_inches='tight')
To no avail. Others suggested that I change the plotting method to "inline" from "automatic" within either Jupyter Notebook or Spyder. This had no effect. I also tried to make sure there was enough room in the figure for my axes using:
fig.add_axes([0.1,0.1,0.75,0.75])
This does not work either. Below is enough to reproduce my experience.
import matplotlib.pyplot as plt
xs, ys = [0,1], [0,1]
fig = plt.figure(figsize=(6, 6)) # Adding tight_layout=True has no effect
ax = fig.add_subplot(1, 1, 1)
# When the following block is commented out, the color of the
# plot is unchanged and the plt.savefig function works perfectly
fig.patch.set_facecolor("#121111")
ax.set_facecolor("#121111")
ax.spines['top'].set_color("#121111")
ax.spines['right'].set_color("#121111")
ax.spines['bottom'].set_color('white')
ax.spines['left'].set_color('white')
ax.xaxis.label.set_color('white')
ax.tick_params(axis='x', colors='white')
ax.yaxis.label.set_color('white')
ax.tick_params(axis='y', colors='white')
ax.set_title("My Graph's Title", color="white")
plt.plot(xs, ys)
plt.xlabel("x-label")
plt.ylabel("y-label")
plt.savefig("my_fig_name.png", bbox_inches="tight")
I am expecting to get an image like this:
What I Expect to Get
However, plt.savefig(...) gives me the following result:
What I Actually Get
Curiously, there seems to be white space around the plot which does not disappear even when I add the tight_layout=True parameter to the matplotlib figure constructor.
fig = plt.figure(figsize=(6, 6), tight_layout=True)
And, when I comment out the code which changes the face color of the plot, the figure is saved correctly with all the axes and labels displayed correctly.
In order to solve your problem, you just have to specify the facecolor keyword argument to your plt.savefig call, in this case :
plt.savefig("my_fig_name.png", bbox_inches="tight", facecolor="#121111")
which gives the intended .png output :
For more information, see plt.savefig documentation.
Updated MRE with subplots
I'm not sure of the usefulness of the original question and MRE. The margin padding seems to be properly adjusted for large x and y labels.
The issue is reproducible with subplots.
Using matplotlib 3.4.2
fig, axes = plt.subplots(ncols=2, nrows=2, figsize=(8, 6))
axes = axes.flatten()
for ax in axes:
ax.set_ylabel(r'$\ln\left(\frac{x_a-x_b}{x_a-x_c}\right)$')
ax.set_xlabel(r'$\ln\left(\frac{x_a-x_d}{x_a-x_e}\right)$')
plt.show()
Original
I am plotting a dataset using matplotlib where I have an xlabel that is quite "tall" (it's a formula rendered in TeX that contains a fraction and is therefore has the height equivalent of a couple of lines of text).
In any case, the bottom of the formula is always cut off when I draw the figures. Changing figure size doesn't seem to help this, and I haven't been able to figure out how to shift the x-axis "up" to make room for the xlabel. Something like that would be a reasonable temporary solution, but what would be nice would be to have a way to make matplotlib recognize automatically that the label is cut off and resize accordingly.
Here's an example of what I mean:
import matplotlib.pyplot as plt
plt.figure()
plt.ylabel(r'$\ln\left(\frac{x_a-x_b}{x_a-x_c}\right)$')
plt.xlabel(r'$\ln\left(\frac{x_a-x_d}{x_a-x_e}\right)$', fontsize=50)
plt.title('Example with matplotlib 3.4.2\nMRE no longer an issue')
plt.show()
The entire ylabel is visible, however, the xlabel is cut off at the bottom.
In the case this is a machine-specific problem, I am running this on OSX 10.6.8 with matplotlib 1.0.0
Use:
import matplotlib.pyplot as plt
plt.gcf().subplots_adjust(bottom=0.15)
# alternate option without .gcf
plt.subplots_adjust(bottom=0.15)
to make room for the label, where plt.gcf() means get the current figure. plt.gca(), which gets the current Axes, can also be used.
Edit:
Since I gave the answer, matplotlib has added the plt.tight_layout() function.
See matplotlib Tutorials: Tight Layout Guide
So I suggest using it:
fig, axes = plt.subplots(ncols=2, nrows=2, figsize=(8, 6))
axes = axes.flatten()
for ax in axes:
ax.set_ylabel(r'$\ln\left(\frac{x_a-x_b}{x_a-x_c}\right)$')
ax.set_xlabel(r'$\ln\left(\frac{x_a-x_d}{x_a-x_e}\right)$')
plt.tight_layout()
plt.show()
In case you want to store it to a file, you solve it using bbox_inches="tight" argument:
plt.savefig('myfile.png', bbox_inches="tight")
An easy option is to configure matplotlib to automatically adjust the plot size. It works perfectly for me and I'm not sure why it's not activated by default.
Method 1
Set this in your matplotlibrc file
figure.autolayout : True
See here for more information on customizing the matplotlibrc file: http://matplotlib.org/users/customizing.html
Method 2
Update the rcParams during runtime like this
from matplotlib import rcParams
rcParams.update({'figure.autolayout': True})
The advantage of using this approach is that your code will produce the same graphs on differently-configured machines.
plt.autoscale() worked for me.
You can also set custom padding as defaults in your $HOME/.matplotlib/matplotlib_rc as follows. In the example below I have modified both the bottom and left out-of-the-box padding:
# The figure subplot parameters. All dimensions are a fraction of the
# figure width or height
figure.subplot.left : 0.1 #left side of the subplots of the figure
#figure.subplot.right : 0.9
figure.subplot.bottom : 0.15
...
There is also a way to do this using the OOP interface, applying tight_layout directly to a figure:
fig, ax = plt.subplots()
fig.set_tight_layout(True)
https://matplotlib.org/stable/api/figure_api.html
for some reason sharex was set to True so I turned it back to False and it worked fine.
df.plot(........,sharex=False)
You need to use sizzors to modify the axis-range:
import sizzors as sizzors_module
sizzors_module.reshape_the_axis(plt).save("literlymylief.tiff")
I want to extent the python plots I am plotting using mpld3 to full screen. I wish to use mpld3 due to the following reasons
I wish to have around 4 plots and have the zoom option for each plot.
All plots must be displayed in the same window.
Here, I tried using tight_layout option to extend the plots to occupy full screen but it does not work as shown in the link at the end.I guess tight_layout does not work with mpld3. Is there any other way to make it stretch to full screen?
Also,how do I add text to the screen where am plotting? Like the 4 plots occupying 90% of the screen from top to bottom and the text occupying remaining 10% at the bottom?
import matplotlib.pyplot as plt
import mpld3
x = [1,2,3]
y = [1,4,9]
fig = plt.figure()
ax = fig.add_subplot(411)
ax.plot(x,y)
ax = fig.add_subplot(412)
ax.plot(x,y)
ax = fig.add_subplot(413)
ax.plot(x,y)
ax = fig.add_subplot(414)
ax.plot(x,y)
fig.tight_layout()
mpld3.show()
Check this link for output of the code http://i.stack.imgur.com/4mBRI.png
I think the size is defined by matplotlib, this means that adjusting this would result in a fullscreen plot.
From this topic: How to maximize a plt.show() window using Python
mng = plt.get_current_fig_manager()
mng.frame.Maximize(True)
Something like this might work.
fig.set_size_inches(x_val,y_val)
helped me resize the plot to fit the screen
Use window.state option to get a zoomed version:
plt.get_current_fig_manager().window.state('zoomed')
I'm using Windows XP v3/Python 2.7 with Canopy and Anaconda package managers/editors.
I am using Python/Matplotlib to produce some Bland-Altman plots (statistical scatter plots) for publication.
After processing the data, the plt.show() command opens a new "Figure" window containing the plot, which looks fine.
I want to be able to use the dynamic pan and zoom commands in this window to interactively optimise the appearance of my plot, then save it as it appears in the window as a high resolution press-quality png image (400-600 dpi, 7 x 5 inches).
The default setting for saving images from the "Figure" window appears to be set to screen resolution (800 x 600 pixels), and I cannot find any options in this window which allow me to change these settings.
I've read other posts on this forum which explain how to directly save a plot from Python in higher resolution by using the following commands to manipulate dpi and image size, e.g.:
plt.figure(figsize=(18, 12), dpi=400)
plt.savefig("myplot.png", dpi = 400)
However, this is not the solution that I'm looking for; as I want to be able to modify the plot using the dynamic pan and zoom features of the "Figure" window before saving in a higher resolution than the default screen resolution.
I'd be grateful for your help.
Many thanks in anticipation & Happy New Year.
Dave
(UK)
Try this:
Determine how to set width and height using a pixels-to-inches converter, like in the following matplotlib documentation. Then try:
import matplotlib.pyplot as plt
fig = plt.figure(frameon=False)
fig.set_size_inches(width,height)
I had this issue in spyder and found changing the value in Preferences > iPython Console > Inline Backend > Resolution changes the resolution when I save figures from the built in window viewing application.
One may register an event upon a key press that would save the figure with some previously given size and dpi. The following uses a class that stores some figsize and dpi and upon pressing t wll change the figure size and dpi of the figure. It will then save this figure and restore the old size and dpi such that the figure on screen remains unchanged.
import matplotlib
matplotlib.use("TkAgg")
import matplotlib.pyplot as plt
fig,ax=plt.subplots()
ax.plot([1,3,1])
class AnySizeSaver():
def __init__(self, fig=None, figsize=None, dpi=None, filename=None):
if not fig: fig=plt.gcf()
self.fig = fig
if not figsize: figsize=self.fig.get_size_inches()
self.figsize=figsize
if not dpi: dpi=self.fig.dpi
self.dpi=dpi
if not filename: filename="myplot.png"
self.filename=filename
self.cid = self.fig.canvas.mpl_connect("key_press_event", self.key_press)
def key_press(self, event):
if event.key == "t":
self.save()
def save(self):
oldfigsize = self.fig.get_size_inches()
olddpi=self.fig.dpi
self.fig.set_size_inches(self.figsize)
self.fig.set_dpi(self.dpi)
self.fig.savefig(self.filename, dpi=self.dpi)
self.fig.set_size_inches(oldfigsize, forward=True)
self.fig.set_dpi(olddpi)
self.fig.canvas.draw_idle()
print(fig.get_size_inches())
ass = AnySizeSaver(fig=fig, figsize=(3,3), dpi=600)
plt.show()
I am using pylab in matplotlib to create a plot and save the plot to an image file. However, when I save the image using pylab.savefig( image_name ), I find that the SIZE image saved is the same as the image that is shown when I use pylab.show().
As it happens, I have a lot of data in the plot and when I am using pylab.show(), I have to maximize the window before I can see all of the plot correctly, and the xlabel tickers don't superimpose on each other.
Is there anyway that I can programmatically 'maximize' the window before saving the image to file? - at the moment, I am only getting the 'default' window size image, which results in the x axis labels being superimposed on one another.
There are two major options in matplotlib (pylab) to control the image size:
You can set the size of the resulting image in inches
You can define the DPI (dots per inch) for output file (basically, it is a resolution)
Normally, you would like to do both, because this way you will have full control over the resulting image size in pixels. For example, if you want to render exactly 800x600 image, you can use DPI=100, and set the size as 8 x 6 in inches:
import matplotlib.pyplot as plt
# plot whatever you need...
# now, before saving to file:
figure = plt.gcf() # get current figure
figure.set_size_inches(8, 6)
# when saving, specify the DPI
plt.savefig("myplot.png", dpi = 100)
One can use any DPI. In fact, you might want to play with various DPI and size values to get the result you like the most. Beware, however, that using very small DPI is not a good idea, because matplotlib may not find a good font to render legend and other text. For example, you cannot set the DPI=1, because there are no fonts with characters rendered with 1 pixel :)
From other comments I understood that other issue you have is proper text rendering. For this, you can also change the font size. For example, you may use 6 pixels per character, instead of 12 pixels per character used by default (effectively, making all text twice smaller).
import matplotlib
#...
matplotlib.rc('font', size=6)
Finally, some references to the original documentation:
http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.savefig, http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.gcf, http://matplotlib.sourceforge.net/api/figure_api.html#matplotlib.figure.Figure.set_size_inches, http://matplotlib.sourceforge.net/users/customizing.html#dynamic-rc-settings
P.S. Sorry, I didn't use pylab, but as far as I'm aware, all the code above will work same way in pylab - just replace plt in my code with the pylab (or whatever name you assigned when importing pylab). Same for matplotlib - use pylab instead.
You set the size on initialization:
fig2 = matplotlib.pyplot.figure(figsize=(8.0, 5.0)) # in inches!
Edit:
If the problem is with x-axis ticks - You can set them "manually":
fig2.add_subplot(111).set_xticks(arange(1,3,0.5)) # You can actually compute the interval You need - and substitute here
And so on with other aspects of Your plot. You can configure it all. Here's an example:
from numpy import arange
import matplotlib
# import matplotlib as mpl
import matplotlib.pyplot
# import matplotlib.pyplot as plt
x1 = [1,2,3]
y1 = [4,5,6]
x2 = [1,2,3]
y2 = [5,5,5]
# initialization
fig2 = matplotlib.pyplot.figure(figsize=(8.0, 5.0)) # The size of the figure is specified as (width, height) in inches
# lines:
l1 = fig2.add_subplot(111).plot(x1,y1, label=r"Text $formula$", "r-", lw=2)
l2 = fig2.add_subplot(111).plot(x2,y2, label=r"$legend2$" ,"g--", lw=3)
fig2.add_subplot(111).legend((l1,l2), loc=0)
# axes:
fig2.add_subplot(111).grid(True)
fig2.add_subplot(111).set_xticks(arange(1,3,0.5))
fig2.add_subplot(111).axis(xmin=3, xmax=6) # there're also ymin, ymax
fig2.add_subplot(111).axis([0,4,3,6]) # all!
fig2.add_subplot(111).set_xlim([0,4])
fig2.add_subplot(111).set_ylim([3,6])
# labels:
fig2.add_subplot(111).set_xlabel(r"x $2^2$", fontsize=15, color = "r")
fig2.add_subplot(111).set_ylabel(r"y $2^2$")
fig2.add_subplot(111).set_title(r"title $6^4$")
fig2.add_subplot(111).text(2, 5.5, r"an equation: $E=mc^2$", fontsize=15, color = "y")
fig2.add_subplot(111).text(3, 2, unicode('f\374r', 'latin-1'))
# saving:
fig2.savefig("fig2.png")
So - what exactly do You want to be configured?
I think you need to specify a different resolution when saving the figure to a file:
fig = matplotlib.pyplot.figure()
# generate your plot
fig.savefig("myfig.png",dpi=600)
Specifying a large dpi value should have a similar effect as maximizing the GUI window.
Check this:
How to maximize a plt.show() window using Python
The command is different depending on which backend you use. I find that this is the best way to make sure the saved pictures have the same scaling as what I view on my screen.
Since I use Canopy with the QT backend:
pylab.get_current_fig_manager().window.showMaximized()
I then call savefig() as required with an increased DPI per silvado's answer.
You can look in a saved figure it's size, like 1920x983 px (size when i saved a maximized window), then I set the dpi as 100 and the size as 19.20x9.83 and it worked fine. Saved exactly equal to the maximized figure.
import numpy as np
import matplotlib.pyplot as plt
x, y = np.genfromtxt('fname.dat', usecols=(0,1), unpack=True)
a = plt.figure(figsize=(19.20,9.83))
a = plt.plot(x, y, '-')
plt.savefig('file.png',format='png',dpi=100)
I had this exact problem and this worked:
plt.savefig(output_dir + '/xyz.png', bbox_inches='tight')
Here is the documentation:
[https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.savefig.html][1]
I did the same search time ago, it seems that he exact solution depends on the backend.
I have read a bunch of sources and probably the most useful was the answer by Pythonio here How to maximize a plt.show() window using Python
I adjusted the code and ended up with the function below.
It works decently for me on windows, I mostly use Qt, where I use it quite often, while it is minimally tested with other backends.
Basically it consists in identifying the backend and calling the appropriate function. Note that I added a pause afterwards because I was having issues with some windows getting maximized and others not, it seems this solved for me.
def maximize(backend=None,fullscreen=False):
"""Maximize window independently on backend.
Fullscreen sets fullscreen mode, that is same as maximized, but it doesn't have title bar (press key F to toggle full screen mode)."""
if backend is None:
backend=matplotlib.get_backend()
mng = plt.get_current_fig_manager()
if fullscreen:
mng.full_screen_toggle()
else:
if backend == 'wxAgg':
mng.frame.Maximize(True)
elif backend == 'Qt4Agg' or backend == 'Qt5Agg':
mng.window.showMaximized()
elif backend == 'TkAgg':
mng.window.state('zoomed') #works fine on Windows!
else:
print ("Unrecognized backend: ",backend) #not tested on different backends (only Qt)
plt.show()
plt.pause(0.1) #this is needed to make sure following processing gets applied (e.g. tight_layout)
Old question but to anyone in need, Here's what had worked for me a while ago:
You have to have a general idea of the aspect ratio that would maximise your plot fitting. This will take some trial and error to get right, but generally 1920x1080 would be a good aspect ratio for most modern monitors. I would still suggest playing around with the aspect ratios to best suit your plot.
Steps:
Before initiating the plot, set the size for the plot, use:
plt.figure(19.20, 10.80)
**notice how I have multiplied my aspect ratio by '0.01'.
At the end of the plot, when using plt.savefig, save it as follows:
plt.savefig('name.jpg', bbox_inches='tight', dpi=1000)
If I understand correctly what you want to do, you can create your figure and set the size of the window. Afterwards, you can save your graph with the matplotlib toolbox button. Here an example:
from pylab import get_current_fig_manager,show,plt,imshow
plt.Figure()
thismanager = get_current_fig_manager()
thismanager.window.wm_geometry("500x500+0+0")
#in this case 500 is the size (in pixel) of the figure window. In your case you want to maximise to the size of your screen or whatever
imshow(your_data)
show()