README.md

In gabysbrain/hypersliceplorer: A library for computing 1D and 2D slices through multi-dimensional datasets

Please use MdSlicing.jl now.

Multi-dimensional Slicing

A library for computing 1D and 2D slices through multi-dimensional datasets.

Installation

Installation is via devtools

install_github("gabysbrain/multid-slicing")

1D slice example

1. If your data is a set of samples in a table, rather than a function then build a regression model on your dataset so you have a function to visualize. Divide your data into X which is a table of all independent variables and Y which is a vector of a single dependent variable. For this example, the regression is done using a Gaussian process model via the mlegp library. ``` library(mlegp)

m = mlegp(X, Y) f = function(x) {predict(m, x)} 2. You will also need to create a `problemSpec` instance to keep track of the names and limits of each dimension. library(multidslicing) lims = createProblemSpec(x1=c(-1, 1), x2=c(-1, 1), x3=c(-1, 1)) 3. Create a set of slices from the function you have. Here, we create 50 slices of the function for each dimension. slices = sliceplorer(f, lims, 50) 4. Now plot the slices plot(slices) ```

License

This project is licensed under a BSD License --- see the LICENSE.md file for details.

gabysbrain/hypersliceplorer documentation built on Nov. 17, 2022, 1:42 p.m.