Building a Perspective Projection Matrix - flutter

my first post here but hopefully I can explain my dilemma with building a perspective projection matrix similar to the one in OpenGL. Being new to the 3D graphics space, I'm having trouble understanding what to do after multiplying my matrix after using a perspective projection multiplication. I'm attempting to create this in Flutter but it should be a moot point as I believe my conversion is off.
Here is what I have:
var center = {
'x': size.width / 2,
'y': size.height / 2
};
List points = [];
points.add(createVector(-50, -50, -50, center));
points.add(createVector(50, -50, -50, center));
points.add(createVector(50, 50, -50, center));
points.add(createVector(-50, 50, -50, center));
points.add(createVector(-50, -50, 50, center));
points.add(createVector(50, -50, 50, center));
points.add(createVector(50, 50, 50, center));
points.add(createVector(-50, 50, 50, center));
for (int i = 0; i < points.length; i++) {
var matrix = matmul(projection, points[i]);
var w = matrix[3][0];
projected.add(
Offset(
(matrix[0][0] / w),
(matrix[1][0] / w)
)
);
}
And these are the 2 custom functions I've created:
List createVector(x, y, z, center) {
return [
[center['x'] + x],
[center['y'] + y],
[z],
[0]
];
}
List matmul(a, b) {
int colsA = a[0].length;
int rowsA = a.length;
int colsB = b[0].length;
int rowsB = b.length;
if (colsA != rowsB) {
return null;
}
List result = [];
for (int j = 0; j < rowsA; j++) {
result.add([]);
for (int i = 0; i < colsB; i++) {
double sum = 0.0;
for (int n = 0; n < colsA; n++) {
sum += a[j][n] * b[n][i];
}
result[j].add(sum);
}
}
return result;
}
My projection matrix that I'm multiplying each point with is:
var aspect = size.width / size.height;
var fov = 100;
var near = 200;
var far = 300;
List projection = [
[1 / (aspect * tan(fov / 2)), 0, 0, 0],
[0, 1 / (tan(fov / 2)), 0, 0],
[0, 0, (near + far) / (near - far), (2 * near * far) / (near - far)],
[0, 0, -1, 0]
];
I believe I am using the correct projection matrix to multiply each vector point that I have. The only thing is, after I get the result from this multiplication, I'm not entirely sure what to do with the resultant vector. I've read about the perspective divide so I am dividing the x, y and z values by the 4th values but I could be incorrect.
Any insight or help is much appreciated. Have been stumped for a long time as I have been learning this online on my own.

In OpenGL the projection matrix turns from a right handed system to a left handed system. See Right-hand rule). This is accomplished by mirroring the z axis.
The terms in the 3rd column have to be inverted (- (near+far) / (near-far) respectively - (2*near*far) / (near-far)):
List projection = [
[1 / (aspect * tan(fov/2)), 0, 0, 0],
[0, 1 / (tan(fov/2)), 0, 0],
[0, 0, - (near+far) / (near-far), - (2*near*far) / (near-far)],
[0, 0, -1, 0]
];
The perspective projection matrix defines a Viewing frustum. It defines a 3 dimensional space (clip space) which is projected on the 2 dimensional viewport.
In OponGL all the geometry which is not in clip space is clipped. You have to ensure that the geometry is in between the near and far plane.

Related

is this correct to alter contrast of an image using matrices?

so I have been trying to alter an image's contrast with matrices and this is what I have come up with:
final defaultColorMatrix = const <double>[
1, 0, 0, 0, 0,
0, 1, 0, 0, 0,
0, 0, 1, 0, 0,
0, 0, 0, 1, 0,
];
List<double> calculateContrastMatrix(double contrast) {
final m = List<double>.from(defaultColorMatrix);
m[0] = contrast;
m[6] = contrast;
m[12] = contrast;
m[5] = (1 - contrast) / 2;
m[10] = (1 - contrast) / 2;
m[15] = (1 - contrast) / 2;
return m;
being contrast and adjustable value between 0 and 1
it is giving me sub optimal results
I just realized that the last column is not m[5], m[10], m[15] but m[4], m[9], m[14]. I forgot that dart's array index starts at 0.
I also forgot that the last column in flutter matrices is not normalized to it expects values between 0-255 so the correct solution is:
List<double> calculateContrastMatrix(double contrast) {
final m = List<double>.from(defaultColorMatrix);
m[0] = contrast;
m[6] = contrast;
m[12] = contrast;
m[4] = ((1 - contrast) / 2) * 255;
m[9] = ((1 - contrast) / 2) * 255;
m[14] = ((1 - contrast) / 2) * 255;
return m;

Attempting to automatically crop to data within a List and convert that to Image

I have an image that I initialized to be all 0 values.
img.Image onlyDog = img.Image.from(decodedImage); // decodedImage is of size 720, 1080
// reset all pixels to 0.
img.fill(onlyDog, img.Color.fromRgba(0, 0, 0, 0));
The full size of the onlyDog image is 720 x 1080. But a small portion of this image has been give values based on an if condition.
To get to the pixel level I had to do:
// get pixel level information for this image via getBytes()
var pixels = decodedImage.getBytes();
// do same for the dog image
var dogPixels = onlyDog.getBytes();
The pixels I need are given values in the following loop:
// get pixel level information for this image via getBytes()
var pixels = decodedImage.getBytes();
// do same for the dog image
var dogPixels = onlyDog.getBytes();
for (int i = 0; i < pixels.length - 4; i += 4) {
//pixels are in format RGBA
var pixelColor = [pixels[i], pixels[i + 1], pixels[i + 2], pixels[i + 3]];
var dogColor = [44, 232, 128, 255];
if (listEquals(pixelColor, dogColor)){
dogPixels[i] = pixels[i]; // R
dogPixels[i + 1] = pixels[i + 1]; // G
dogPixels[i + 2] = pixels[i + 2]; // B
dogPixels[i + 3] = 255; // A - keep this at max as this is the effect I want
}
}
Now, unlike python and other languages, images are not stored in clean [row x column] format but rather as a List so this makes it even more difficult to get the exact coordinates of the pixels set. What I want to do is to crop to the content and not return the massive space of emty [0,0,0,0] data.
What I tried:
I created a dynamic list and added any pixels that are not zero, this would basically extract only the meaningful content from onlyDog:
List<int> contentPixelList = [];
// below for loop to look for cropping to content
for (int i = 0; i < dogPixels.length - 4; i += 4) {
var pixelColor = [dogPixels[i], dogPixels[i + 1], dogPixels[i + 2], dogPixels[i + 3]];
if (!listEquals(pixelColor, [0, 0, 0, 0])){
contentPixelList.add(dogPixels[i]);
contentPixelList.add(dogPixels[i+1]);
contentPixelList.add(dogPixels[i+2]);
contentPixelList.add(dogPixels[i+3]);
//print(dogPixels[i]);
}
}
I then converted this to a fixed List as we get an error if an Image is created from a growableList.
List<int> fixedListContent = new List<int>.from(contentPixelList, growable: false);
And an Image is created from this:
Uint8List dogCropList = new Uint8List.fromList(fixedListContent);
//no image from above list
img.Image dogCropImage = img.decodeImage(dogCropList);
The dogCropImage returned is null, then I realized that I should have been using fromBytes as the data I have is of type List<int> But the problem here is that Image.fromBytes() requires a height and width argument as well which I cannot know from the above list I populated,.
Any help would be appreciated?
All images store their pixel data in a list/array format. Libraries just exist to translate x and y coordinates into array indices. The conversion is pretty straightforward:
int stride = width * bytesPerPixel;
int index = (y * stride) + (x * bytesPerPixel);
Using this, it's pretty simple to modify pixels in a list of bytes. For example:
for (int y = startY; y <= endY; y++) {
int yStride = y * stride;
for (int x = startX; x <= endX; x++) {
int index = yStride + (x * bytesPerPixel);
// Assuming an ARGB format
pixelData[index] = aValue;
pixelData[index+1] = rValue;
pixelData[index+2] = gValue;
pixelData[index+3] = bValue;
}
}

Snap Matrix4 rotation to 90, 180, 270, 360 degrees, Flutter

I'm currently using the matrix_gesture_detector package to scale, transform and rotate a Transform widget.
Everything works fine but to improve UX I would like to snap the widget at 90, 180, 270 or 360 degrees once the user rotates the widget close enough to said angles.
Edit: To clarify I would like the user to be able to freely rotate the widget, but snap into the nearest 90 degree rotation within whichever quadrant it is, once it gets close enough.
Hence, the solution should detect that "closeness" and then act accordingly. Please visit this link to see a GIF which shows the desired effect
How can I achieve this?
Below is the code snippet
Widget transformContainer() {
Matrix4 matrix;
GlobalKey matrixDetectorKey = GlobalKey();
return MatrixGestureDetector(
key: matrixDetectorKey,
onMatrixUpdate: (m, tm, sm, rm) {
setState(() {
matrix = MatrixGestureDetector.compose(matrix, tm, sm, rm);
});
},
child: Transform(
transform: matrix,
child: Container(
padding: EdgeInsets.all(24.0),
width: 100.0,
height: 200.0,
color: Colors.teal,
),
),
);}
For this to work, you have to check if the rotation of the matrix is closing in on a snapping point and rotate the Z-Axis to that point. I was able to write this code which works for this scenario. You may have to tune the threshold to adjust the "snappiness" to your taste.
import vector_math and use the following code:
import 'package:vector_math/vector_math_64.dart' as vec;
onMatrixUpdate: (Matrix4 m, Matrix4 tm, Matrix4 sm, Matrix4 rm) {
Matrix4 ogRm = rm.clone();
double radian = MatrixGestureDetector.decomposeToValues(m).rotation;
double degrees = vec.degrees(radian);
double delta_0 = vec.absoluteError(degrees, 0);
double delta_90 = vec.absoluteError(degrees, 90);
double delta_180 = vec.absoluteError(degrees, 180);
double delta_270 = vec.absoluteError(degrees, -90);
double threshold = 4;
if (delta_0 <= threshold) {
rm.rotateZ(vec.radians(0) - radian);
} else if (delta_90 <= threshold) {
rm.rotateZ(vec.radians(90) - radian);
} else if (delta_180 <= threshold) {
rm.rotateZ(vec.radians(180) - radian);
} else if (delta_270 <= threshold) {
rm.rotateZ(vec.radians(270) - radian);
}
// update gesture matrix
if (ogRm != rm) m = m * rm;
setState(() {
//transform your widget using this matrix
matrix = m;
});
}
Note that 360 is the same as 0, so there's no need to check for it.
MatrixGestureDetector(
onMatrixUpdate: (m, tm, sm, rm) {
setState(() {
//270 is the angle
m.rotate(m.getTranslation(), 270);
matrix4 = m;
});
},
child: Transform(
transform: matrix4,
child: Container(
padding: EdgeInsets.all(24.0),
width: 100,
height: 200,
color: Colors.teal,
),
),
),
You will have the rotate function inside the library. this code will work for snapping to 0 degrees. Basically what I am doing is if the difference in rotation and x-axis is less than 0.2 radians, I snap to 0 degrees while keeping the rotation in a separate variable. When the user moves beyond this, I add this value again and keep rotating normally.
Matrix4 _rotate(double angle, Offset focalPoint) {
double toBeRotated = 0;
var array = matrix.applyToVector3Array([0, 0, 0, 1, 0, 0]);
Offset delta = Offset(array[3] - array[0], array[4] - array[1]);
double rotation = delta.direction;
deltaAngle = deltaAngle + angle;
if ((rotation + deltaAngle).abs() > 0.2) {
toBeRotated = deltaAngle;
deltaAngle = 0;
} else if (rotation != 0 && (rotation + deltaAngle).abs() <= 0.2) {
toBeRotated = -rotation;
deltaAngle = deltaAngle + rotation;
} else {
toBeRotated = 0;
}
var c = cos(toBeRotated);
var s = sin(toBeRotated);
var dx = (1 - c) * focalPoint.dx + s * focalPoint.dy;
var dy = (1 - c) * focalPoint.dy - s * focalPoint.dx;
// ..[0] = c # x scale
// ..[1] = s # y skew
// ..[4] = -s # x skew
// ..[5] = c # y scale
// ..[10] = 1 # diagonal "one"
// ..[12] = dx # x translation
// ..[13] = dy # y translation
// ..[15] = 1 # diagonal "one"
return Matrix4(c, s, 0, 0, -s, c, 0, 0, 0, 0, 1, 0, dx, dy, 0, 1);
}

How to convert a location on football pitch to coordinates on rectangle?

I have 4 points of football pitch (corner points):
P1(lat, lon, alt), P2(lat, lon, alt), P3(lat, lon, alt), P4(lat, lon, alt).
and a location on the pitch:
L(lat, lon, alt)
I want to convert L(lat, lon, alt) to L(x, y) on a rectangle with size of (W, H).
How to implement this conversion function? (I preferred C# language but implementation language is not important)
The following image describes my problem (I don't know how to implement the Function box):
First off, because output coordinates are 2D, I'm going to assume that we can get rid of altitude information from input coordinates. So input data consist of four points defining the input rectangle:
P1(lat, lon), P2(lat, lon), P3(lat, lon), P4(lat, lon)
and dimensions of the output rectangle: w, h.
I'm also going to ignore the curvature of the Earth (football pitch is small enough). With those assumptions we can implement the conversion function, by performing affine transformation. It would be wasteful to create transformation matrix each time we want to perform a transformation. For that reason we need two functions: first one to create the transformation matrix (called only once), and the second one that will use that matrix to perform transformation itself (called possibly many times, one time for each point we want to transform), something like:
tm = createTransformationMatrix(P1, P2, P4, w, h)
inPoint = (200, 50)
outPoint = transform(inPoint, tm)
Note that we only need three of four input points to unambiguously define a rotated rectangle in 2D euclidean space.
Here is the implementation of createTransformationMatrix and transform functions:
const run = function() {
// Creates transformation matrix to transform
// from rectangle somewhere in 2D space with coordinates p0, px, pi, py
// to rectangle with coordinates (x=0, y=0), (x=w, y=0), (x=w, y=h), (x=0, y=h).
// Note that: p0 is mapped to (x=0, y=0)
// px is mapped to (x=w, y=0)
// py is mapped to (x=0, y=h)
const createTransformationMatrix = function(p0, px, py, w, h) {
// Translate px and py by p0 - pxt and pyt are px and py vectors in coordinate system in which p0 is at the origin
const pxt = {
x: px.x - p0.x,
y: px.y - p0.y,
};
const pyt = {
x: py.x - p0.x,
y: py.y - p0.y,
};
// Create transformation matrix, which is inverse of transformation matrix that:
// 1. Transforms (x=0, y=0) to (x=p0.x, y=p0.y)
// 2. Transforms (x=1, y=0) to (x=p0.x + pxt.x / w, y=p0.y + pxt.y / w)
// 3. Transforms (x=0, y=1) to (x=p0.x + pyt.x / h, y=p0.y + pyt.y / h)
return Matrix.invert3([
[pxt.x / w, pyt.x / h, p0.x],
[pxt.y / w, pyt.y / h, p0.y],
[0 , 0 , 1 ],
]);
};
const transform = function(point, transformationMatrix) {
// Convert point to homogeneous coordinates
const inputVector = [
[point.x],
[point.y],
[1],
];
// Transform inputVector
const outputVector = Matrix.multiply(transformationMatrix, inputVector);
// Convert outputVector back to cartesian coordinates and return
return {
x: outputVector[0][0] / outputVector[2][0],
y: outputVector[1][0] / outputVector[2][0],
};
};
const w = 220;
const h = 115;
const p1 = {x:-79, y:80 };
const p2 = {x:9, y:-96};
const p3 = {x:55, y:-72};
const p4 = {x:-34, y:105};
const tm = createTransformationMatrix(p1, p2, p4, w, h);
const inPoint = {x: 200, y: 50};
const outPoint = transform(inPoint, tm);
console.log(`(${inPoint.x}, ${inPoint.y}) --[transform]--> (${outPoint.x}, ${outPoint.y})`);
}
//// Matrix ////
const Matrix = {};
Matrix.scale = (s, m) => m.map(x => Array.isArray(x) ? Matrix.scale(s, x) : s * x);
Matrix.multiply = function(a, b) {
const aNumRows = a.length, aNumCols = a[0].length;
const bNumRows = b.length, bNumCols = b[0].length;
const m = new Array(aNumRows);
for (let r = 0; r < aNumRows; ++r) {
m[r] = new Array(bNumCols);
for (let c = 0; c < bNumCols; ++c) {
m[r][c] = 0;
for (let i = 0; i < aNumCols; ++i)
m[r][c] += a[r][i] * b[i][c];
}
}
return m;
};
Matrix.invert3 = function(m) {
const [[a, b, c],
[d, e, f],
[g, h, i]] = m;
const det = a*(e*i - f*h) - b*(d*i - f*g) + c*(d*h - e*g);
return Matrix.scale(1/det, [
[e*i - f*h, c*h - b*i, b*f - c*e],
[f*g - d*i, a*i - c*g, c*d - a*f],
[d*h - e*g, b*g - a*h, a*e - b*d],
]);
};
//////////////
run();
I've included all the matrix processing logic, so that this code snippet is self contained, but I would suggest you to instead use some linear algebra library for matrix processing.
I've also made a more visual demo.

Generate random movement for a point in 3D space

I want to simulate a point that moves with random vibration around a mean position (let's say around the position [X, Y, Z] = [0,0,0]). The first solution that I found is to sum a couple of sinusoids for each axis based on the following equation:
<img src="https://latex.codecogs.com/gif.latex?\sum_{i&space;=&space;1}^n&space;A_i&space;\sin(\omega_i&space;t&plus;\phi)" title="\sum_{i = 1}^n A_i \sin(\omega_i t+\phi)" />
where A_i is a normal random amplitude, and omega_i is a normal random frequency. I have not tested the phase yet, so I leave it to zero for now. I generated figures of the expect normal distribution and equation results with the following approach. I tried multiple values of N and I'm not sure that the equation is giving a normally distributed results. Is my approach correct? Is there a better way to generate random vibration?
For such a task, you may find useful Perlin Noise or even Fractal Brownian Motion noise. See this implementation in JavaScript:
class Utils {
static Lerp(a, b, t) {
return (1 - t) * a + t * b;
}
static Fade(t) {
return t * t * t * (t * (t * 6 - 15) + 10);
}
}
class Noise {
constructor() {
this.p = [];
this.permutationTable = [];
this.grad3 = [[1, 1, 0], [-1, 1, 0], [1, -1, 0],
[-1, -1, 0], [1, 0, 1], [-1, 0, 1],
[1, 0, -1], [-1, 0, -1], [0, 1, 1],
[0, -1, 1], [0, 1, -1], [0, -1, -1]];
for (let i = 0; i < 256; i++)
this.p[i] = Math.floor(Math.random() * 256);
for (let i = 0; i < 512; i++)
this.permutationTable[i] = this.p[i & 255];
}
PerlinDot(g, x, y, z) {
return g[0] * x + g[1] * y + g[2] * z;
}
PerlinNoise(x, y, z) {
let a = Math.floor(x);
let b = Math.floor(y);
let c = Math.floor(z);
x = x - a;
y = y - b;
z = z - c;
a &= 255;
b &= 255;
c &= 255;
let gi000 = this.permutationTable[a + this.permutationTable[b + this.permutationTable[c]]] % 12;
let gi001 = this.permutationTable[a + this.permutationTable[b + this.permutationTable[c + 1]]] % 12;
let gi010 = this.permutationTable[a + this.permutationTable[b + 1 + this.permutationTable[c]]] % 12;
let gi011 = this.permutationTable[a + this.permutationTable[b + 1 + this.permutationTable[c + 1]]] % 12;
let gi100 = this.permutationTable[a + 1 + this.permutationTable[b + this.permutationTable[c]]] % 12;
let gi101 = this.permutationTable[a + 1 + this.permutationTable[b + this.permutationTable[c + 1]]] % 12;
let gi110 = this.permutationTable[a + 1 + this.permutationTable[b + 1 + this.permutationTable[c]]] % 12;
let gi111 = this.permutationTable[a + 1 + this.permutationTable[b + 1 + this.permutationTable[c + 1]]] % 12;
let n000 = this.PerlinDot(this.grad3[gi000], x, y, z);
let n100 = this.PerlinDot(this.grad3[gi100], x - 1, y, z);
let n010 = this.PerlinDot(this.grad3[gi010], x, y - 1, z);
let n110 = this.PerlinDot(this.grad3[gi110], x - 1, y - 1, z);
let n001 = this.PerlinDot(this.grad3[gi001], x, y, z - 1);
let n101 = this.PerlinDot(this.grad3[gi101], x - 1, y, z - 1);
let n011 = this.PerlinDot(this.grad3[gi011], x, y - 1, z - 1);
let n111 = this.PerlinDot(this.grad3[gi111], x - 1, y - 1, z - 1);
let u = Utils.Fade(x);
let v = Utils.Fade(y);
let w = Utils.Fade(z);
let nx00 = Utils.Lerp(n000, n100, u);
let nx01 = Utils.Lerp(n001, n101, u);
let nx10 = Utils.Lerp(n010, n110, u);
let nx11 = Utils.Lerp(n011, n111, u);
let nxy0 = Utils.Lerp(nx00, nx10, v);
let nxy1 = Utils.Lerp(nx01, nx11, v);
return Utils.Lerp(nxy0, nxy1, w);
}
FractalBrownianMotion(x, y, z, octaves, persistence) {
let total = 0;
let frequency = 1;
let amplitude = 1;
let maxValue = 0;
for(let i = 0; i < octaves; i++) {
total = this.PerlinNoise(x * frequency, y * frequency, z * frequency) * amplitude;
maxValue += amplitude;
amplitude *= persistence;
frequency *= 2;
}
return total / maxValue;
}
}
With Fractal Brownian Motion can have huge control about the randomness of distribution. You can set the scale, initial offset and its increment for each axis, octaves, and persistence. You can generate as many positions you like by incrementing the offsets, like this:
const NUMBER_OF_POSITIONS = 1000;
const X_OFFSET = 0;
const Y_OFFSET = 0;
const Z_OFFSET = 0;
const X_SCALE = 0.01;
const Y_SCALE = 0.01;
const Z_SCALE = 0.01;
const OCTAVES = 8;
const PERSISTENCE = 2;
const T_INCREMENT = 0.1;
const U_INCREMENT = 0.01;
const V_INCREMENT = 1;
let noise = new Noise();
let positions = [];
let i = 0, t = 0, u = 0, v = 0;
while(i <= NUMBER_OF_POSITIONS) {
let position = {x:0, y:0, z:0};
position.x = noise.FractalBrownianMotion((X_OFFSET + t) * X_SCALE, (Y_OFFSET + t) * Y_SCALE, (Z_OFFSET + t) * Z_SCALE, OCTAVES, PERSISTENCE);
position.y = noise.FractalBrownianMotion((X_OFFSET + u) * X_SCALE, (Y_OFFSET + u) * Y_SCALE, (Z_OFFSET + u) * Z_SCALE, OCTAVES, PERSISTENCE);
position.z = noise.FractalBrownianMotion((X_OFFSET + v) * X_SCALE, (Y_OFFSET + v) * Y_SCALE, (Z_OFFSET + v) * Z_SCALE, OCTAVES, PERSISTENCE);
positions.push(position);
t += T_INCREMENT;
u += U_INCREMENT;
v += V_INCREMENT;
i++;
}
Positions you get with these options would look similar to these:
...
501: {x: 0.0037344935483775883, y: 0.1477509219864437, z: 0.2434570202517206}
502: {x: -0.008955635460317357, y: 0.14436114483299245, z: -0.20921147024725012}
503: {x: -0.06021806450587406, y: 0.14101769272762685, z: 0.17093922757597568}
504: {x: -0.05796055906294283, y: 0.13772732578136435, z: 0.0018755951606465138}
505: {x: 0.02243901814464688, y: 0.13448621540816477, z: 0.013341084536334057}
506: {x: 0.05074194554980439, y: 0.1312810723109357, z: 0.15821600463130164}
507: {x: 0.011075140752144507, y: 0.12809058766450473, z: 0.04006055269090941}
508: {x: -0.0000031848272303249632, y: 0.12488712875549206, z: -0.003957905411646261}
509: {x: -0.0029798194097060307, y: 0.12163862278870072, z: -0.1988934273517602}
510: {x: -0.008762098499026483, y: 0.11831055728747841, z: 0.02222898347134993}
511: {x: 0.01980289423585394, y: 0.11486802263767962, z: -0.0792283303765883}
512: {x: 0.0776034130079849, y: 0.11127772191732693, z: -0.14141576745502138}
513: {x: 0.08695806478169149, y: 0.10750987521108693, z: 0.049654228704645}
514: {x: 0.036915612100698, y: 0.10353995005320946, z: 0.00033977899920740567}
515: {x: 0.0025923223158845687, y: 0.09935015632822117, z: -0.00952549797548823}
516: {x: 0.0015456084571764527, y: 0.09493065267319889, z: 0.12609905321632175}
517: {x: 0.0582996941155056, y: 0.09028042189611517, z: -0.27532974820612816}
518: {x: 0.19186052966982514, y: 0.08540778482478142, z: -0.00035058098387404606}
519: {x: 0.27063961068049447, y: 0.08033053495775729, z: -0.07737309686568927}
520: {x: 0.20318957178662056, y: 0.07507568989311474, z: -0.14633819135757353}
...
Note: for efficiency, it's a good idea generate all positions only once into an array of positions like in this example, and then in some animation loop just assigning positions to your point from this array one by one.
Bonus: Here you can see how those values affect the distribution of multiple points by playing around with real-time response control panel:
https://marianpekar.github.io/fbm-space/
References:
https://en.wikipedia.org/wiki/Fractional_Brownian_motion
https://en.wikipedia.org/wiki/Perlin_noise