@acransac/vtk.js
Version:
Visualization Toolkit for the Web
263 lines (142 loc) • 4.02 kB
Markdown
## Pi() : Math.PI;
Return PI.
## radiansFromDegrees(degree) : radian
Convert degrees to radians.
## degreesFromRadians(radian) : degree
Convert radians to degrees.
## round(float): int
Same as Math.round().
## floor(float) : int
Same as Math.floor().
## ceil(float) : int
Same as Math.ceil().
## ceilLog2()
NOT IMPLEMENTED
## min(a, b)
Same as Math.min().
## max(a, b)
Same as Math.max().
## arrayMin(array)
Minimum of the array.
## arrayMax(a, b)
Maximum of the array.
## factorial(n) : number
NOT IMPLEMENTED
## binomial(m, n) : int
## beginCombination(m, n) : Array or null
## nextCombination(m, n, r) : Boolean
## randomSeed()
NOT IMPLEMENTED
## getSeed()
NOT IMPLEMENTED
## random(minValue = 0, maxValue = 1) : Number
## gaussian()
NOT IMPLEMENTED
## add(a, b, out)
```js
a[3] + b[3] => out[3]
```
Returns out.
## subtract(a, b, out)
```js
a[3] - b[3] => out[3]
```
Returns out.
## multiplyScalar(vec, scalar) {
```js
vec[3] * scalar => vec[3]
```
Returns vec.
## multiplyScalar2D(vec, scalar)
```js
vec[2] * scalar => vec[2]
```
Returns vec.
## multiplyAccumulate(a, b, scalar, out)
```js
a[3] + b[3] * scalar => out[3]
```
Returns out.
## multiplyAccumulate2D(a, b, scalar, out)
```js
a[2] + b[2] * scalar => out[2]
```
Returns out.
## dot(x, y)
## outer(x, y, out_3x3)
## cross(x, y, out)
Computes cross product of 3D vectors x and y.
Returns out.
It is safe to x or y as out.
## norm(x, n = 3)
## normalize(x)
Normalize in place. Returns norm.
## perpendiculars(x, y, z, theta)
## projectVector(a, b, projection)
## dot2D(x, y)
## projectVector2D(a, b, projection)
## distance2BetweenPoints(x, y)
## angleBetweenVectors(v1, v2)
angle between 3D vectors
## signedAngleBetweenVectors(v1, v2, vN)
Signed angle between v1 and v2 with regards to plane defined by normal vN.
## gaussianAmplitude(mean, variance, position)
## gaussianWeight(mean, variance, position)
## outer2D(x, y, out_2x2)
## norm2D(x2D)
## normalize2D(x)
## determinant2x2(c1, c2)
## LUFactor3x3(mat_3x3, index_3)
## LUSolve3x3(mat_3x3, index_3, x_3)
## linearSolve3x3(mat_3x3, x_3, y_3)
## multiply3x3_vect3(mat_3x3, in_3, out_3)
## multiply3x3_mat3(a_3x3, b_3x3, out_3x3)
## multiplyMatrix(a, b, rowA, colA, rowB, colB, out_rowXcol)
## transpose3x3(in_3x3, outT_3x3)
## invert3x3(in_3x3, outI_3x3)
## identity3x3(mat_3x3)
## determinant3x3(mat_3x3)
## quaternionToMatrix3x3(quat_4, mat_3x3)
## jacobiN(a, n, w, v)
## matrix3x3ToQuaternion(mat_3x3, quat_4)
## multiplyQuaternion(quat_1, quat_2, quat_out)
## orthogonalize3x3(a_3x3, out_3x3)
## diagonalize3x3(a_3x3, w_3, v_3x3)
## singularValueDecomposition3x3(a_3x3, u_3x3, w_3, vT_3x3)
## luFactorLinearSystem(A, index, size)
## luSolveLinearSystem(A, index, x, size)
## solveLinearSystem(A, x, size)
## invertMatrix(A, AI, size, index = null, column = null)
## estimateMatrixCondition(A, size)
## jacobi(a_3x3, w, v)
```js
jacobiN(a_3x3, 3, w, v);
```
## solveHomogeneousLeastSquares(numberOfSamples, xt, xOrder, mt)
## solveLeastSquares(numberOfSamples, xt, xOrder, yt, yOrder, mt, checkHomogeneous = true)
## rgb2hsv(rgb, hsv)
## hsv2rgb(hsv, rgb)
## lab2xyz(lab, xyz)
## xyz2lab(xyz, lab)
## xyz2rgb(xyz, rgb)
## rgb2xyz(rgb, xyz)
## rgb2lab(rgb, lab)
## LabToRGB(lab, rgb)
## uninitializeBounds(bounds)
## areBoundsInitialized(bounds)
## clampValue(value, minValue, maxValue)
## clampAndNormalizeValue(value, range)
## getScalarTypeFittingRange
NOT IMPLEMENTED
## getAdjustedScalarRange
NOT IMPLEMENTED
## extentIsWithinOtherExtent(extent1, extent2)
## boundsIsWithinOtherBounds(bounds1_6, bounds2_6, delta_3)
## pointIsWithinBounds(point_3, bounds_6, delta_3)
## solve3PointCircle(p1, p2, p3, center)
## inf()
## negInf()
## isInf(number) : Boolean
## isNan(?) : Boolean
## isFinite(number) : Boolean
## createUninitializedBouds() : new [6]