scatterscale 1.0.1

Automatically determine the best scaling for your scatterplot's colorbar.

ScatterScale

Automate the normalizing scale for your scatterplot's colorbar. Scaling options are Log, SymLog, Asinh, or no normalization, as defined by matplotlib.

To Install

pip install scatterscale

Quick Start

Scatterscale's get_scatterscale() function can be used to generate the matplotlib.color.Norm used for matplotlib plotting.

import scatterscale 
optimal_norm = get_scatterscale(data_for_colorbar)
plt.scatter(x_data, y_data, c=data_for_colorbar, norm=optimal_norm)
plt.show()

If you'd like to remove outliers from your data first, you can do so with handle_outliers() before running get_scatterscale().

data_for_colorbar_no_outliers = handle_outliers(data_for_colorbar, sigma_value=5, treatment="mask_out")
optimal_norm_no_outliers = get_scatterscale(data_for_colorbar)
plt.scatter(x_data, y_data, c=data_for_colorbar_no_outliers, norm=optimal_norm_no_outliers)
plt.show()

Tutorial

A tutorial notebook is provided in docs/tutorials/full_demo.ipynb, showing how scatterscale works for photometric test data.