molstar
Version:
A comprehensive macromolecular library.
58 lines (57 loc) • 3.13 kB
JavaScript
/**
* Copyright (c) 2018 mol* contributors, licensed under MIT, See LICENSE file for more info.
*
* @author David Sehnal <david.sehnal@gmail.com>
*/
import { __awaiter, __generator } from "tslib";
import { Task } from '../../mol-task';
import { SpacegroupCell, Box3D } from '../../mol-math/geometry';
import { Tensor, Vec3 } from '../../mol-math/linear-algebra';
import { CustomProperties } from '../../mol-model/custom-property';
export function volumeFromDensityServerData(source, params) {
var _this = this;
return Task.create('Create Volume', function (ctx) { return __awaiter(_this, void 0, void 0, function () {
var info, values, cell, axis_order_fast_to_slow, normalizeOrder, sample_count, tensorSpace, data, origin, dimensions;
return __generator(this, function (_a) {
info = source.volume_data_3d_info, values = source.volume_data_3d;
cell = SpacegroupCell.create(info.spacegroup_number.value(0), Vec3.ofArray(info.spacegroup_cell_size.value(0)), Vec3.scale(Vec3.zero(), Vec3.ofArray(info.spacegroup_cell_angles.value(0)), Math.PI / 180));
axis_order_fast_to_slow = info.axis_order.value(0);
normalizeOrder = Tensor.convertToCanonicalAxisIndicesFastToSlow(axis_order_fast_to_slow);
sample_count = normalizeOrder(info.sample_count.value(0));
tensorSpace = Tensor.Space(sample_count, Tensor.invertAxisOrder(axis_order_fast_to_slow), Float32Array);
data = Tensor.create(tensorSpace, Tensor.Data1(values.values.toArray({ array: Float32Array })));
origin = Vec3.ofArray(normalizeOrder(info.origin.value(0)));
dimensions = Vec3.ofArray(normalizeOrder(info.dimensions.value(0)));
return [2 /*return*/, {
label: params === null || params === void 0 ? void 0 : params.label,
entryId: params === null || params === void 0 ? void 0 : params.entryId,
grid: {
transform: { kind: 'spacegroup', cell: cell, fractionalBox: Box3D.create(origin, Vec3.add(Vec3.zero(), origin, dimensions)) },
cells: data,
stats: {
min: info.min_sampled.value(0),
max: info.max_sampled.value(0),
mean: info.mean_sampled.value(0),
sigma: info.sigma_sampled.value(0)
},
},
sourceData: DscifFormat.create(source),
customProperties: new CustomProperties(),
_propertyData: Object.create(null),
}];
});
}); });
}
//
export { DscifFormat };
var DscifFormat;
(function (DscifFormat) {
function is(x) {
return (x === null || x === void 0 ? void 0 : x.kind) === 'dscif';
}
DscifFormat.is = is;
function create(dscif) {
return { kind: 'dscif', name: dscif._name, data: dscif };
}
DscifFormat.create = create;
})(DscifFormat || (DscifFormat = {}));