molstar
Version:
A comprehensive macromolecular library.
61 lines (60 loc) • 2.48 kB
JavaScript
/**
* Copyright (c) 2020 mol* contributors, licensed under MIT, See LICENSE file for more info.
*
* @author David Sehnal <david.sehnal@gmail.com>
*/
import { Mat4, Tensor, Vec3 } from '../../mol-math/linear-algebra';
import { Box3D } from '../../mol-math/geometry';
import { arrayMin, arrayMax, arrayRms, arrayMean } from '../../mol-util/array';
// eslint-disable-next-line
export function CubeGridFormat(grid) {
return { name: 'custom grid', kind: 'cube-grid', data: grid };
}
export function isCubeGridData(f) {
return f.kind === 'cube-grid';
}
export function initCubeGrid(params) {
const geometry = params.basis.atoms.map(a => a.center);
const { gridSpacing: spacing, boxExpand: expand } = params;
const count = geometry.length;
const box = Box3D.expand(Box3D(), Box3D.fromVec3Array(Box3D(), geometry), Vec3.create(expand, expand, expand));
const size = Box3D.size(Vec3(), box);
const spacingThresholds = typeof spacing === 'number' ? [[0, spacing]] : [...spacing];
spacingThresholds.sort((a, b) => b[0] - a[0]);
let s = 0.4;
for (let i = 0; i <= spacingThresholds.length; i++) {
s = spacingThresholds[i][1];
if (spacingThresholds[i][0] <= count)
break;
}
const dimensions = Vec3.ceil(Vec3(), Vec3.scale(Vec3(), size, 1 / s));
return {
params,
box,
dimensions,
size,
npoints: dimensions[0] * dimensions[1] * dimensions[2],
delta: Vec3.div(Vec3(), size, Vec3.subScalar(Vec3(), dimensions, 1)),
};
}
const BohrToAngstromFactor = 0.529177210859;
export function createGrid(gridInfo, values, axisOrder) {
const boxSize = Box3D.size(Vec3(), gridInfo.box);
const boxOrigin = Vec3.clone(gridInfo.box.min);
Vec3.scale(boxSize, boxSize, BohrToAngstromFactor);
Vec3.scale(boxOrigin, boxOrigin, BohrToAngstromFactor);
const scale = Mat4.fromScaling(Mat4(), Vec3.div(Vec3(), boxSize, Vec3.sub(Vec3(), gridInfo.dimensions, Vec3.create(1, 1, 1))));
const translate = Mat4.fromTranslation(Mat4(), boxOrigin);
const matrix = Mat4.mul(Mat4(), translate, scale);
const grid = {
transform: { kind: 'matrix', matrix },
cells: Tensor.create(Tensor.Space(gridInfo.dimensions, axisOrder, Float32Array), values),
stats: {
min: arrayMin(values),
max: arrayMax(values),
mean: arrayMean(values),
sigma: arrayRms(values),
},
};
return grid;
}