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import vtkPolyData from 'vtk.js/Sources/Common/DataModel/PolyData';
const { vtkErrorMacro } = macro;
// ----------------------------------------------------------------------------
// vtkImageStreamline methods
// ----------------------------------------------------------------------------
function vtkImageStreamline(publicAPI, model) {
// Set our className
model.classHierarchy.push('vtkImageStreamline');
const indices = new Int32Array(3);
const paramCoords = new Float32Array(3);
const weights = new Float32Array(8);
const voxelIndices = new Uint32Array(8);
const dimensions = new Uint32Array(3);
const velAt = new Float32Array(3);
const xtmp = new Float32Array(3);
publicAPI.interpolationFunctions = (pcoords, sf) => {
const r = pcoords[0];
const s = pcoords[1];
const t = pcoords[2];
const rm = 1.0 - r;
const sm = 1.0 - s;
const tm = 1.0 - t;
sf[0] = rm * sm * tm;
sf[1] = r * sm * tm;
sf[2] = rm * s * tm;
sf[3] = r * s * tm;
sf[4] = rm * sm * t;
sf[5] = r * sm * t;
sf[6] = rm * s * t;
sf[7] = r * s * t;
};
publicAPI.computeStructuredCoordinates = (
x,
ijk,
pcoords,
extent,
spacing,
origin,
bounds
) => {
// tolerance is needed for 2D data (this is squared tolerance)
const tol2 = 1e-12;
//
// Compute the ijk location
//
let isInBounds = true;
for (let i = 0; i < 3; i++) {
const d = x[i] - origin[i];
const doubleLoc = d / spacing[i];
// Floor for negative indexes.
ijk[i] = Math.floor(doubleLoc);
pcoords[i] = doubleLoc - ijk[i];
let tmpInBounds = false;
const minExt = extent[i * 2];
const maxExt = extent[i * 2 + 1];
// check if data is one pixel thick
Iif (minExt === maxExt) {
const dist = x[i] - bounds[2 * i];
if (dist * dist <= spacing[i] * spacing[i] * tol2) {
pcoords[i] = 0.0;
ijk[i] = minExt;
tmpInBounds = true;
}
} else Iif (ijk[i] < minExt) {
if (
(spacing[i] >= 0 && x[i] >= bounds[i * 2]) ||
(spacing[i] < 0 && x[i] <= bounds[i * 2 + 1])
) {
pcoords[i] = 0.0;
ijk[i] = minExt;
tmpInBounds = true;
}
} else if (ijk[i] >= maxExt) {
if (
(spacing[i] >= 0 && x[i] <= bounds[i * 2 + 1]) ||
(spacing[i] < 0 && x[i] >= bounds[i * 2])
) {
// make sure index is within the allowed cell index range
pcoords[i] = 1.0;
ijk[i] = maxExt - 1;
tmpInBounds = true;
}
} else {
tmpInBounds = true;
}
// clear isInBounds if out of bounds for this dimension
isInBounds = isInBounds && tmpInBounds;
}
return isInBounds;
};
publicAPI.getVoxelIndices = (ijk, dims, ids) => {
ids[0] = ijk[2] * dims[0] * dims[1] + ijk[1] * dims[0] + ijk[0];
ids[1] = ids[0] + 1; // i+1, j, k
ids[2] = ids[0] + dims[0]; // i, j+1, k
ids[3] = ids[2] + 1; // i+1, j+1, k
ids[4] = ids[0] + dims[0] * dims[1]; // i, j, k+1
ids[5] = ids[4] + 1; // i+1, j, k+1
ids[6] = ids[4] + dims[0]; // i, j+1, k+1
ids[7] = ids[6] + 1; // i+1, j+1, k+1
};
publicAPI.vectorAt = (xyz, velArray, image, velAtArg) => {
if (
!publicAPI.computeStructuredCoordinates(
xyz,
indices,
paramCoords,
image.getExtent(),
image.getSpacing(),
image.getOrigin(),
image.getBounds()
)
) {
return false;
}
publicAPI.interpolationFunctions(paramCoords, weights);
const extent = image.getExtent();
dimensions[0] = extent[1] - extent[0] + 1;
dimensions[1] = extent[3] - extent[2] + 1;
dimensions[2] = extent[5] - extent[4] + 1;
publicAPI.getVoxelIndices(indices, dimensions, voxelIndices);
velAtArg[0] = 0.0;
velAtArg[1] = 0.0;
velAtArg[2] = 0.0;
const vel = new Array(3);
for (let i = 0; i < 8; i++) {
velArray.getTuple(voxelIndices[i], vel);
for (let j = 0; j < 3; j++) {
velAtArg[j] += weights[i] * vel[j];
}
}
return true;
};
publicAPI.computeNextStep = (velArray, image, delT, xyz) => {
// This does Runge-Kutta 2
// Start with evaluating velocity @ initial point
Iif (!publicAPI.vectorAt(xyz, velArray, image, velAt)) {
return false;
}
// Now find the mid point
for (let i = 0; i < 3; i++) {
xtmp[i] = xyz[i] + (delT / 2.0) * velAt[i];
}
// Use the velocity @ that point to project
if (!publicAPI.vectorAt(xtmp, velArray, image, velAt)) {
return false;
}
for (let i = 0; i < 3; i++) {
xyz[i] += delT * velAt[i];
}
if (!publicAPI.vectorAt(xyz, velArray, image, velAt)) {
return false;
}
return true;
};
publicAPI.streamIntegrate = (velArray, image, seed, offset) => {
const retVal = [];
const maxSteps = model.maximumNumberOfSteps;
const delT = model.integrationStep;
const xyz = new Float32Array(3);
xyz[0] = seed[0];
xyz[1] = seed[1];
xyz[2] = seed[2];
const pointsBuffer = [];
let step = 0;
for (step = 0; step < maxSteps; step++) {
if (!publicAPI.computeNextStep(velArray, image, delT, xyz)) {
break;
}
for (let i = 0; i < 3; i++) {
pointsBuffer[3 * step + i] = xyz[i];
}
}
const pd = vtkPolyData.newInstance();
const points = new Float32Array(pointsBuffer);
retVal[0] = points;
pd.getPoints().setData(points, 3);
const npts = points.length / 3;
const line = new Uint32Array(npts + 1);
line[0] = npts;
for (let i = 0; i < npts; i++) {
line[i + 1] = i + offset;
}
retVal[1] = line;
pd.getLines().setData(line);
return retVal;
};
publicAPI.requestData = (inData, outData) => {
// implement requestData
const input = inData[0];
const seeds = inData[1];
Iif (!input) {
vtkErrorMacro('Invalid or missing input');
return;
}
Iif (!seeds) {
vtkErrorMacro('Invalid or missing seeds');
return;
}
const seedPts = seeds.getPoints();
const nSeeds = seedPts.getNumberOfPoints();
let offset = 0;
const datas = [];
const vectors = input.getPointData().getVectors();
const point = [];
for (let i = 0; i < nSeeds; i++) {
seedPts.getTuple(i, point);
const retVal = publicAPI.streamIntegrate(vectors, input, point, offset);
offset += retVal[0].length / 3;
datas.push(retVal);
}
let cellArrayLength = 0;
let pointArrayLength = 0;
datas.forEach((data) => {
cellArrayLength += data[1].length;
pointArrayLength += data[0].length;
});
offset = 0;
let offset2 = 0;
const cellArray = new Uint32Array(cellArrayLength);
const pointArray = new Float32Array(pointArrayLength);
datas.forEach((data) => {
cellArray.set(data[1], offset);
offset += data[1].length;
pointArray.set(data[0], offset2);
offset2 += data[0].length;
});
const output = vtkPolyData.newInstance();
output.getPoints().setData(pointArray, 3);
output.getLines().setData(cellArray);
outData[0] = output;
};
}
// ----------------------------------------------------------------------------
// Object factory
// ----------------------------------------------------------------------------
const DEFAULT_VALUES = {
integrationStep: 1,
maximumNumberOfSteps: 1000,
};
// ----------------------------------------------------------------------------
export function extend(publicAPI, model, initialValues = {}) {
Object.assign(model, DEFAULT_VALUES, initialValues);
// Make this a VTK object
macro.obj(publicAPI, model);
// Also make it an algorithm with one input and one output
macro.algo(publicAPI, model, 2, 1);
// Generate macros for properties
macro.setGet(publicAPI, model, ['integrationStep', 'maximumNumberOfSteps']);
// Object specific methods
vtkImageStreamline(publicAPI, model);
}
// ----------------------------------------------------------------------------
export const newInstance = macro.newInstance(extend, 'vtkImageStreamline');
// ----------------------------------------------------------------------------
export default { newInstance, extend };
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