smartplot 0.1.2

A helper tool for matplotlib. Provides a contextmanager which automatically saves data used to make plots and automatically generates a script to re-load and re-plot this data at a later stage.

Smartplot

This package provides a simple contextmanager which automatically saves data used to make matplotlib plots and automatically generates a script to reproduce the plot at a later stage.

Install

pip install smartplot

Basic Usage

A SmartPlotContext contextmanager can be used in conjunction with a with block as shown below.

from smartplot import SmartPlotContext


with SmartPlotContext("./data-save-dir", locals(), overwrite=True) as spl:
    spl.plot( ... )
    ...
    spl.title( ... )
    spl.show()

The resulting context manager spl support all matplotlib.pyplot function calls. All calls made to spl are passed onto matplotlib.pyplot as-is and recorded. The data save directory is dynamically created if it does not exist and is populated with pickle files containing the data used to make the plot. The automatically generated make_plot.py script contains code which reloads all data and contains the necessary calls to matplotlib.pyplot used to create the original plot. This script may then be modified to adjust the plot. If the data save directory is not empty an exception is raised unless overwrite=True. Passing in locals() allows SmartPlotContext to infer the original variable names for the objects used for re-use in make_plot.py.

Note that only calls directly to spl are recorded, if you use figures and axes directly, you're on your own for now.

Example Usage

import numpy as np
import matplotlib.pyplot as plt
from smartplot import SmartPlotContext


x_data = np.linspace(0, 2 * np.pi, 1000)
y_data = np.sin(x_data)
with SmartPlotContext("./data-save-dir", locals(), overwrite=True) as spl:
    spl.plot(x_data, y_data, c='k', label='sin')
    spl.plot(x_data, np.cos(x_data), c='b', label='cos')
    spl.xlabel('xaxis')
    spl.ylabel('yaxis')
    spl.title('Title')
    spl.legend()
    spl.savefig('plot.pdf')
    spl.show()

This will generate the following directory structure

data-save-dir/
  make_plot.py
  unnamed_arg.pkl
  x_data.pkl
  y_data.pkl

The contents of make_plot.py would be

import numpy as np
import matplotlib.pyplot as plt
from smartplot import load_pickle


x_data = load_pickle('x_data.pkl')
y_data = load_pickle('y_data.pkl')
unnamed_arg = load_pickle('unnamed_arg.pkl')

plt.plot(x_data, y_data, c='k', label='sin')
plt.plot(x_data, unnamed_arg, c='b', label='cos')
plt.xlabel('xaxis')
plt.ylabel('yaxis')
plt.title('Title')
plt.legend()
plt.savefig('plot.pdf')
plt.show()

which should perfectly reproduce the original plot. Note that the variable names x_data and y_data are arbitrary and were inferred by the SmartPlotContext using the locals() dict. Good code structure will always allow SmartPlotContext to infer the correct variable names. Anonymous arguments, such as the y data of the np.cos plot are simply saved and named "unnamed_arg" with an integer postfix if multiple unnamed arguments are present.

Misc

Please report any bugs or feature requests to [e-mail].