hamhelper 1.12

Some helpful tools I use in research and fun. Primarily targeted to data visualization and pretty colours.

hamHelper

Description

This repository contains the HamHelper package written in Python3 for scientific plotting and analysis tools geared towards speeding up common workflows in my experience. This is mainly a wrapper of matplotlib with some script and numpy for common physics use cases.

Usage

Installing

In order to use this package you will need to have installed:

• Python3.XX,
• matplotlib,
• numpy.

Install as you normally would with pip: pip install hamhelper

Submodules

HamHelper.    # package root
|- plotting   # plotting helpers
|- colours    # colourmap definitions, helper functions, and custom colour class HamColour 

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Purpose

This package contains a set of helper functions and methods I use. Primarily geared towards physics, experimental analysis, and data visualization. The goal is to simplify common procedures around generating pretty plots with minimal chart-junk as well as getting the values that matter (ie. curve fit routine that also computes standard error and chi squared). In general, there are three parts:

plotting

hamhelper.plotting.despine()
Simple matplotlib wrapper to despine. Offers offset axis as well as trimmed axis like in Seaborn.

despine(axis = None, trim = False, drop = 0, noLine = False, bottom = True, left = True, top = False, right = False):  

axis: None or mpl.axes object (opt.)
The axes object to act on, default plt.gca().
trim: bool (opt.)
If true trims axes to the limiting ticks, default False.
drop: float (opt.)
Distance to space spine from axes in pixels. Default 0.
noLine: bool (opt.)
If true removes the spine but keeps the axis ticks, default False.
bottom, left, top, right: bool (opt.)
Enable or disable the corresponding axes spine, default keeps bottom and left, removes top and right.

hamhelper.plotting.errorbands()
Wrapper of matplotlib.pyplot.errorbar producing continuous bands instead of stems. You can additionally enable the caps still.

errorbands(x, y, yerr, capsize = 0, ax = None, color = None, *args, **kwargs):  

x: np.array like
The x dimension of pairwise data.
y: np.array like
The y dimension of pairwise data.
yerr: np.array like
The error in the y dimension of pairwise data.
capsize: float (opt.)
The width of caps to be added above each data point at the same location as the error band.
ax: None or plt.axes object (opt.)
Can specify to plot on another axis, defaults to plt.gca()
color: tuple or string (opt.)
Facecolor of the error band. If tuple provided, expects a tuple of RGB or RGBA values. If string provided expects a hex '#RRGGBB' or matplotlib named color. Defaults None for no fill color.
*args & **kwargs: (opt.)
Passed to plt.ax.fill_between().

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colours

A suite of colour sets and colour maps I use with a custom HamColor class to easily import and play with the colours. Just stuff I like to use!