utils_color_breaks

Auto Breaks for Matrix Plotting Functions

Fast C++ implementation of Dynamic Time Warping for time series dissimilarity analysis, with applications in environmental monitoring and sensor data analysis, climate science, signal processing and pattern recognition, and financial data analysis. Built upon the ideas presented in Benito and Birks (2020) <doi:10.1111/ecog.04895>, provides tools for analyzing time series of varying lengths and structures, including irregular multivariate time series. Key features include individual variable contribution analysis, restricted permutation tests for statistical significance, and imputation of missing data via GAMs. Additionally, the package provides an ample set of tools to prepare and manage time series data.

Blas M. Benito

distantia

Advanced Toolset for Efficient Time Series Dissimilarity
Analysis

utils_color_breaks function

<dl><dt>m</dt>
<dd>(required, numeric matrix) distance or cost matrix generated by <code>psi_distance_matrix()</code> or <code>psi_cost_matrix()</code>, but any numeric matrix will work. Default: NULL</dd>
<dt>n</dt>
<dd>(required, integer) number of colors to compute the breaks for. Default: 100</dd></dl>

Arguments

Auto Breaks for Matrix Plotting Functions — utils_color_breaks

<dl>

<dt>m</dt>
<dd>(required, numeric matrix) distance or cost matrix generated by <code>psi_distance_matrix()</code> or <code>psi_cost_matrix()</code>, but any numeric matrix will work. Default: NULL</dd>


<dt>n</dt>
<dd>(required, integer) number of colors to compute the breaks for. Default: 100</dd>

</dl>

utils_color_breaks: Auto Breaks for Matrix Plotting Functions

Description

Usage

Value

Arguments

See Also