StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics https://doi.org/10.1109/TVCG.2020.3030352
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StackGenVis/frontend/node_modules/simplicial-complex-contour/README.md

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simplicial-complex-contour
==========================
Finds a piecewise-linear isocontour on a simplicial complex using the marching simplex method.
# Example
```javascript
var extractContour = require('simplicial-complex-contour')
var bunny = require('bunny')
//Solve for the curve z=0 on the surface of the bunny
var zvalues = bunny.positions.map(function(p) {
return p[2]
})
var curve = extractContour(bunny.cells, zvalues, 0.0)
//Unpack edges and positions of curve
var curveEdges = curve.cells
var curvePositions = curve.vertexWeights.map(function(w,i) {
var a = bunny.positions[curve.vertexIds[i][0]]
var b = bunny.positions[curve.vertexIds[i][1]]
return [
w * a[0] + (1 - w) * b[0],
w * a[1] + (1 - w) * b[1],
w * a[2] + (1 - w) * b[2]
]
})
//Render the curve
console.log({
cells: curveEdges,
positions: curvePositions
})
```
# Install
```
npm install simplicial-complex-contour
```
# API
#### `require('simplicial-complex-contour')(cells, values[, level])`
Computes a piecewise linear solution to the solution `values=levels`
* `cells` is an array of simplices represented by tuples of vertex indices
* `values` is an array of values defined at each vertex of the cell complex
* `level` is the level at which the surface is extracted (Default 0)
**Returns** An object with 3 properties
* `cells` which are the cells of the extracted isosurface
* `vertexIds` which is an array of pairs of vertex ids encoding the crossing edges
* `vertexWeights` which are linear weights applied to each vertex
# Credits
(c) 2014 Mikola Lysenko. MIT License