chroptiks 0.1.7

A set of helper functions for quickly making matplotlib plots with a high number of built-in options.

Description

chroptiks is a Python package that offers advanced plotting utilities, making it easier to create complex and informative visualizations. It extends the functionality of libraries like matplotlib and scipy, providing a user-friendly interface for a variety of plotting needs.

Requirements

Python libraries: matplotlib, numpy, scipy

Installation

To install chroptiks, run:

pip install chroptiks

or if you want to install from source:

git clone https://github.com/cagostino/chroptiks.git
cd chroptiks
python setup.py install

Features

—2D Histograms (hist2d): Easily create 2D histograms for data analysis.

—1D Histograms (hist1d): Simplify the process of creating and customizing 1D histograms.

—Scatter Plots (scatter): Enhanced functionality for scatter plot creation.

—3D Plots (plot3d): Intuitive tools for 3D data visualization.

—Bar Charts (plotbar): Quick and customizable bar chart creation.

Example usage

hist2d, hist1d, scatter, plot3d, plotbar are now ready to be used as per their defined functionalities and plots are generated through each of their plot methods. For example:

import numpy as np
from chroptiks.plotting_utils import hist2d

x = np.linspace(-1,1, 100000)+np.random.normal(0,.1, size=100000)
y = x**(3)+np.random.normal(0, 0.3, size=100000)
z =  np.random.normal(size=100000)

hist2d.plot(x,y,nx=200,ny=200)

hist2d.plot(x,y,nx=40, ny=40, ccode = z, ccodename='Z', xlabel='X', ylabel='Y')

hist2d.plot(x,y,nx=200,ny=200,bin_y=True, size_y_bin=0.1, xlabel='X', ylabel='Y', percentiles=False)

from chroptiks.plotting_utils import hist1d

hist1d.plot(z, range=(-2,2), bins=100, xlabel='Z', ylabel='Counts')

hist1d.plot(z, range=(-2,2), bins=100, xlabel='Z', ylabel='Counts', normed=True)

hist1d.plot(z, range=(-4,4), bins=100, xlabel='Z', ylabel='Cumulative Count', cumulative=True)



from chroptiks.plotting_utils import scat

#scat
scat.plot(x,z)

#scat with color-code
scat.plot(x,y, ccode=z, color=None, edgecolor=None, vmin=-0.5, vmax=0.5)
#note if you use ccode to color the points, you must set color to None, and I would advise you to set edgecolor to None as well or else each will have outlines.

#scat with y-binning
scat.plot(x, y, bin_y=True, size_y_bin=0.1, percentiles=True, xlabel='X', ylabel='Z', aspect='auto')