check_ripser

Topological data analysis is a powerful tool for finding non-linear global structure
in whole datasets. The main tool of topological data analysis is persistent homology, which computes
a topological shape descriptor of a dataset called a persistence diagram. 'TDApplied' provides
useful and efficient methods for analyzing groups of persistence diagrams with machine learning and statistical inference,
and these functions can also interface with other data science packages to form flexible and integrated
topological data analysis pipelines.

Shael Brown

TDApplied

Machine Learning and Inference for Topological Data Analysis

Dr. Reza Farivar

check_ripser function

<dl><dt>ripser</dt>
<dd>the ripser module object.</dd></dl>

Arguments

Shael Brown - <a href="/link/shaelebrown%40gmail.com?package=TDApplied&version=3.0.3" data-mini-rdoc="TDApplied::shaelebrown@gmail.com">shaelebrown@gmail.com</a>

Author

Verify an imported ripser module. — check_ripser

<dl>

<dt>ripser</dt>
<dd>the ripser module object.</dd>

</dl>

Shael Brown - <a href='mailto:shaelebrown@gmail.com'>shaelebrown@gmail.com</a>

check_ripser: Verify an imported ripser module.

Description

Usage

Arguments

Author