Welcome to weibull’s documentation!

• Installation
  • Using pip
  • Using setup.py
  • Using conda
  • Dependencies
• Analysis
  • Fitting
  • Plotting
  • Class Documentation
• Design
  • Class Documentation
• Weibayes
  • Class Documentation
• Examples
  • Determining \(\beta\) and \(\eta\) Values
  • Life Calculations
  • Basic Life Statistics
  • Plotting
  • Test Design
  • Weibayes Analysis
• Gallery
  • Example 1: Multiple-Censored Data
• Brief Introduction to Reliability Analysis
  • Weibull Distribution
  • Censoring Data
  • Determining \(\beta\) and \(\eta\)
  • B-Life
  • Confidence Levels

Introduction

The weibull package is a package designed for easy reliability analysis using the weibull distribution. This documentation will not make a high effort to explain Weibull analysis but will, instead, focus on the use of the package. Despite this, there are still some obligatory convention to establish in order to make the documentation and packaging readable. Conventions are established in Introduction to Reliability Analysis.

Installation

To install weibull into a Python 3 environment, simply pip3 install weibull. This package does not support Python 2.

Dependencies

The weibull package is built on pandas, numpy, matplotlib, and scipy libraries. If you are having trouble installing these libraries, particularly within windows, then you may wish to use the Anaconda distribution of Python.

Test Coverage

The weibull package contains testing for the algorithmic elements of the analysis, but no testing for graphic generation.

Classes

There are three primary classes available in weibull:

• Analysis - Used for analysis, you are probably wanting this
• Design - Used for reliability test design
• Weibayes - Used for analysis and design using some assumptions

Index