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https://github.com/stsievert/python-drawnow

MATLAB-like drawnow to easily update a figure
https://github.com/stsievert/python-drawnow

python visualization

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MATLAB-like drawnow to easily update a figure

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README

          

`drawnow` for matplotlib
========================

The scientific community often runs iterative code, often in the form of
simulation. It's often useful to see the results after each iteration.
Accordingly, MATLAB® has a nice feature that allows you to update the
figure, `drawnow`. This repo brings the same feature to Python's
matplotlib, with some extras.

Example:

![image0](test-data/test.gif)

This is shown with `imshow`, but python-drawnow allows updates of any
figure.

Usage:

``` python
# complete implementation of script found in test/test.py
from pylab import *
from drawnow import drawnow, figure
# if global namespace, import plt.figure before drawnow.figure

def approx(x, k):
"""Approximate x with k singular values"""
...

figure(figsize=(7, 7/2))
def draw_fig():
subplot(1, 2, 1)
imshow(x)

subplot(1, 2, 2)
imshow(x_hat)
#show()

x = imread('test-data/mandrill.png').mean(axis=2)
k_values = around(logspace(0, 2, num=10))
for k in k_values:
x_hat = approx(x, k)
drawnow(draw_fig)
```

Documentation
=============

If you want to wait for confirmation after update or the option to drop
into a debugger, call `drawnow(function_to_draw_figure, confirm=True)`.

If you only want to show the figure once, call
`drawnow(function_to_draw_figure, show_once=True)`. The full
documentation is included in the doc strings. Use `drawnow?` or
`help(drawnow)` to see these docs.

Jupyter/Spyder
==============

Try running the folloowing code in a Jupyter input cell/in the
console/etc:

```
%matplotlib
```

This will disable the Matplotlin inline mode and use the default
plotting backend. For more detail, see the [IPython plotting
documentation](https://ipython.readthedocs.io/en/stable/interactive/plotting.html#id1).

Installation
============

Two options:

1. Run `pip install drawnow`.
2. Download this repository and run `python setup.py install`.

Option 2 assumes a working Python installation with `pip`. I suggest
Anaconda's distribution: For
other options, see .

Changes to code
---------------

This does require *small* changes to your code. All it should really
amount to is moving `figure(); plot(...); show()` inside a function; not
much.