Creating python plots on background - python

With a single script, I have to produce dozens of figures with matplotlib using spyder. I would like spyder to create figures while I can work with other browsers or windows without interruption. Here were the methods I tried. Let us say that there are 40 plots to be created. Each plot contains multiple subplots
(1) From How do I get interactive plots again in Spyder/IPython/matplotlib?. I used %matplotlib inline. The plots will be created inline at the end of the program. However, the usage of computation memory keeps accumulating. At some point, python will show an error message due to lack of memory and then crash. The message is like: "More than 20 figures have been opened. Figures created through the pyplot interface (matplotlib.pyplot.figure) are retained until explicitly closed and may consume too much memory."
(2) Then, I use plt.close() to close each figure after saving it. The memory issue is resolved. However, even if the figure is not shown, every time python close a figure and open another one, all other browsers and windows will be affected. If I am typing on a window, after the interruption, I have to click the window again in order to continue typing.
Previously, when I used MATLAB, I could simply specify h=figure and then set(h,'visible','off') to avoid this issue. I wonder if I can do similar things with python.
Thank you for the help!

Related

How to save figures in a folder with Jupyter Notebook when the plots are produced with an external function that I don't want to modify?

I want to save figures plotted by a function that I don't want to have to touch (because it is an external function, and also because if tomorrow I don't want to save them and just display on the console, I don't want to have to edit the source code again and again). Is it possible to save the figures into a folder from ipython? Whether the figures are plotted in iPython or not is not a concern. I just want to be able to save them in a folder automatically, as they are a lot in number.
I have tried most of the solutions mentioned here, but they don't work - they just save a blank image file.
import matplotlib.pyplot as pl
fig = pl.figure()
external_function(parameters) # this function plots a figure
fig.savefig(r'path\to\folder\image.png') # saves a blank image.png into the folder
fig.savefig must be before show because when you close the figure, it is destroyed and only an empty (will appear blank) figure is saved.
There are several approaches, all of which require a modification of the external function that you don't want to change:
1 - modify the external function by adding a parameter to indicate if the figure must be saved or not, then using a conditional to save the figure or not.
def external function(params, dosave=False):
...
if dosave:
fig.savefig...
fig.show()
2 - modify the external function to return a figure that you can then choose to save prior to displaying it.
3 - Possibly decorate the external function so it saves the figure.
There may be a 'hacky way' to use ipython internals to keep a handle on the figures you are closing, but I don't know it.

how to stop plt.show() from making interface non-interactive

I'm writing an app that allows you to drag and drop datafiles unto a gui which then plots it. However using plt.show() causes the interface to become non-interactive, that means I need to first close the plot before dragging and dropping another file. I wanted to avoid doing this.
I've tried using plt.ion() but doing that causes the plot gui from updating when you resize it or try to manually close it.

Close a figure - PyCharm

I have spent over an hour searching, just to figure this simple thing. So, before considering this a duplicate question, please compare my question to any question out there.
This is my code:
import pandas
import matplotlib.pyplot as plt
dataset = pandas.read_csv('international-airline-passengers.csv', usecols=[1], engine='python', skipfooter=1)
print dataset, type(dataset)
plt.plot(dataset)
plt.show()
plt.close()
Firstly, plt.show() to my understanding is a blocking function. So what is the way to close the figure. There is no point in writing plt.close() after it. So where is the right way to put it.
Secondly, how can I make sure all the windows are closed when I execute a new process of the same python code. For example in MATLAB, one could easily say close all in the beginning of their file and it closes all the opened plots which were the result of previous MATLAB code execution. plt.close('all') is not working either.
I am using PyCharm. The results I found for the first situation, might work on IDLE but not in the PyCharm. How can I do it PyCharm.
plt.show(block=False) will do the trick- This is the way you can make this function non-blocking (both in run & debug mode). The main dis-advantage is that if the code ends, the figure is automatically closes...
I had the same problem.
I fix it making the python file in Pycharm to run in only one console. Go to: run---Edit configuration-- check that "single instance only" is activated
There are two ways to run matplotlib, non-interactive and interactive. In non-interactive mode, the default, you are right that plt.show() is blocking. In this case, calling plt.close() is pointless, the code won't stop as long as the figure is open. In interactive mode, however (which can be triggers by plt.ion()), this code will open then immediately close the figure. You would need to put something to wait for user input if you run code like this in a script. Interactive mode, as the name implies, is designed more for running interactively rather than in a script.
As for closing figures from multiple runs of a python script, this isn't possible. If you open multiple instances of MATLAB, close all in one instance won't close the figures in another instance. Running multiple processes of the same python code is the same as opening multiple instances of MATLAB, one run has no knowledge of the others.

Matplotlib - force display within a script

This is highly related to an earlier question by another person a couple of years ago: Matplotlib - Force plot display and then return to main code
I am using Canopy 1.5.5 on MacOSX 10.8.5, with matplotlib 1.4.3.
I will need to load data, look at it, press enter to approve and move to the next dataset (and do that a few thousand times, so it's kind of critical to get this functionality). Here is my MWE:
import numpy as np
from matplotlib import pyplot as plt
plt.ion()
plt.figure()
ind=np.arange(5)
for i in ind:
plt.clf()
plt.scatter(ind,ind+i)
plt.title('this is plot number %i' % i)
plt.show()
u=raw_input("Press any button")
The code seems to do everything EXCEPT actually showing me the plot. If I finish the script (or interrupt it), then I see the current figure.
I have tried everything from the previous answer: with and without interactive mode, with and without plt.show(block=False), every permutation of plt.draw and plt.show, and every backend on my available list.
This seems like a very basic functionality! Please tell me that this can be done. I find it weird that matplolib says here http://matplotlib.org/users/shell.html that "by default the drawing is deferred until the end of the script", but does not have suggestions on how to override the default. Please help!
Your example works for me (my backend is osx), although the figure window appears behind other windows at first. I needed to use alt-tab to raise it to the front.
Try starting your script with the --matplotlib option of IPython. You can select a backend or let it be auto-detected like so: ipython --matplotlib auto yourscript.py
Not sure if you now, but the raw_input function waits for you to press the return key, not just any key.
Edit:
About your last remark: this section explains how to force drawing before the end of the script. This can be done with the draw function. In interactive mode every pyplot command calls draw as well. Drawing in this context means rendering the figure by the backend.

What's wrong with Pandas plot?

I'm following a book by Wes McKinney and in the section introducing pandas, he's given a simple example of plotting a pandas Data Frame. Here're the lines I wrote:
tz_counts = frame['tz'].value_counts() # frame is a Data Frame
tz_counts[:10] # works fine till here. I can see the key-value I wanted
tz_counts[:10].plot(kind='barh', rot=0)
It just prints a line on screen that says
<matplotlib.axes.AxesSubplot object at 0x3d14ed0>
rather than displaying a plot window as I'd expect with matplotlib's plot function. What's wrong here? How can I make it work?
Matplotlib doesn't show the plot until you tell it to, unless you're in "interactive" mode.
Short Answer: Call plt.show() when you're ready to display the plot.
This starts the gui mainloop of whatever backend you're using, so it is blocking. (i.e. execution will stop until you close the window)
If you want it to show up automatically without stopping execution, you can turn on interactive mode either with plt.ion() or by using ipython --pylab.
However, using --pylab mode in ipython will import all of numpy, matplotlib.pyplot, and a few other things into the global namespace. This is convenient for interactive use, but teaches very bad habits and overwrites functions in the standard library (e.g. min, max, etc).
You can still use matplotlib's interactive mode in ipython without using "pylab" mode to avoid the global import. Just call plt.ion()
Matplotlib's default TkAgg backend will work in interactive mode with any python shell (not just ipython). However, other backends can't avoid blocking further execution without the gui mainloop being run in a separate thread. If you're using a different backend, then you'll need to tell ipython this with the --gui=<backend> option.
Try using:
%matplotlib
tz_counts = frame['tz'].value_counts()
tz_counts[:10].plot(kind='barh', rot=0)
Using % matplotlib prevents importing * from pylab and numpy which in turn prevents variable clobbering.

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