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// Copyright 2014 The Flutter Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
/// @docImport 'package:flutter/rendering.dart';
library;
import 'package:flutter/foundation.dart';
import 'package:vector_math/vector_math_64.dart';
import 'basic_types.dart';
/// Utility functions for working with matrices.
abstract final class MatrixUtils {
/// Returns the given [transform] matrix as an [Offset], if the matrix is
/// nothing but a 2D translation.
///
/// Otherwise, returns null.
static Offset? getAsTranslation(Matrix4 transform) {
// Values are stored in column-major order, so the appearance
// of dx is transposed from the top-right to the bottom-left.
if (transform.storage case [
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
final double dx,
final double dy,
0.0,
1.0,
]) {
return Offset(dx, dy);
}
return null;
}
/// Returns the given [transform] matrix as a [double] describing a uniform
/// scale, if the matrix is nothing but a symmetric 2D scale transform.
///
/// Otherwise, returns null.
static double? getAsScale(Matrix4 transform) {
// Values are stored in column-major order
// (but this symmetric matrix is unaffected).
if (transform.storage case [
final double diagonal1,
0.0,
0.0,
0.0,
0.0,
final double diagonal2,
0.0,
0.0,
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
0.0,
1.0,
] when diagonal1 == diagonal2) {
return diagonal1;
}
return null;
}
/// Computes the result of matrix multiplication `a x b` and stores the result
/// in `b`.
///
/// This function does not alter the argument `a`, and is thus useful when you
/// want to left-multiply in-place. For right-multiply in-place, see
/// [Matrix4.multiply].
static void multiplyInPlace(Matrix4 a, Matrix4 b) {
final Float64List aStorage = a.storage;
final double m00 = aStorage[0];
final double m01 = aStorage[4];
final double m02 = aStorage[8];
final double m03 = aStorage[12];
final double m10 = aStorage[1];
final double m11 = aStorage[5];
final double m12 = aStorage[9];
final double m13 = aStorage[13];
final double m20 = aStorage[2];
final double m21 = aStorage[6];
final double m22 = aStorage[10];
final double m23 = aStorage[14];
final double m30 = aStorage[3];
final double m31 = aStorage[7];
final double m32 = aStorage[11];
final double m33 = aStorage[15];
final Float64List bStorage = b.storage;
final double n00 = bStorage[0];
final double n01 = bStorage[4];
final double n02 = bStorage[8];
final double n03 = bStorage[12];
final double n10 = bStorage[1];
final double n11 = bStorage[5];
final double n12 = bStorage[9];
final double n13 = bStorage[13];
final double n20 = bStorage[2];
final double n21 = bStorage[6];
final double n22 = bStorage[10];
final double n23 = bStorage[14];
final double n30 = bStorage[3];
final double n31 = bStorage[7];
final double n32 = bStorage[11];
final double n33 = bStorage[15];
bStorage[0] = (m00 * n00) + (m01 * n10) + (m02 * n20) + (m03 * n30);
bStorage[4] = (m00 * n01) + (m01 * n11) + (m02 * n21) + (m03 * n31);
bStorage[8] = (m00 * n02) + (m01 * n12) + (m02 * n22) + (m03 * n32);
bStorage[12] = (m00 * n03) + (m01 * n13) + (m02 * n23) + (m03 * n33);
bStorage[1] = (m10 * n00) + (m11 * n10) + (m12 * n20) + (m13 * n30);
bStorage[5] = (m10 * n01) + (m11 * n11) + (m12 * n21) + (m13 * n31);
bStorage[9] = (m10 * n02) + (m11 * n12) + (m12 * n22) + (m13 * n32);
bStorage[13] = (m10 * n03) + (m11 * n13) + (m12 * n23) + (m13 * n33);
bStorage[2] = (m20 * n00) + (m21 * n10) + (m22 * n20) + (m23 * n30);
bStorage[6] = (m20 * n01) + (m21 * n11) + (m22 * n21) + (m23 * n31);
bStorage[10] = (m20 * n02) + (m21 * n12) + (m22 * n22) + (m23 * n32);
bStorage[14] = (m20 * n03) + (m21 * n13) + (m22 * n23) + (m23 * n33);
bStorage[3] = (m30 * n00) + (m31 * n10) + (m32 * n20) + (m33 * n30);
bStorage[7] = (m30 * n01) + (m31 * n11) + (m32 * n21) + (m33 * n31);
bStorage[11] = (m30 * n02) + (m31 * n12) + (m32 * n22) + (m33 * n32);
bStorage[15] = (m30 * n03) + (m31 * n13) + (m32 * n23) + (m33 * n33);
}
/// Returns true if the given matrices are exactly equal, and false
/// otherwise. Null values are assumed to be the identity matrix.
static bool matrixEquals(Matrix4? a, Matrix4? b) {
if (identical(a, b)) {
return true;
}
assert(a != null || b != null);
if (a == null) {
return isIdentity(b!);
}
if (b == null) {
return isIdentity(a);
}
return a.storage[0] == b.storage[0] &&
a.storage[1] == b.storage[1] &&
a.storage[2] == b.storage[2] &&
a.storage[3] == b.storage[3] &&
a.storage[4] == b.storage[4] &&
a.storage[5] == b.storage[5] &&
a.storage[6] == b.storage[6] &&
a.storage[7] == b.storage[7] &&
a.storage[8] == b.storage[8] &&
a.storage[9] == b.storage[9] &&
a.storage[10] == b.storage[10] &&
a.storage[11] == b.storage[11] &&
a.storage[12] == b.storage[12] &&
a.storage[13] == b.storage[13] &&
a.storage[14] == b.storage[14] &&
a.storage[15] == b.storage[15];
}
/// Whether the given matrix is the identity matrix.
static bool isIdentity(Matrix4 a) {
return a.storage[0] ==
1.0 // col 1
&&
a.storage[1] == 0.0 &&
a.storage[2] == 0.0 &&
a.storage[3] == 0.0 &&
a.storage[4] ==
0.0 // col 2
&&
a.storage[5] == 1.0 &&
a.storage[6] == 0.0 &&
a.storage[7] == 0.0 &&
a.storage[8] ==
0.0 // col 3
&&
a.storage[9] == 0.0 &&
a.storage[10] == 1.0 &&
a.storage[11] == 0.0 &&
a.storage[12] ==
0.0 // col 4
&&
a.storage[13] == 0.0 &&
a.storage[14] == 0.0 &&
a.storage[15] == 1.0;
}
/// Applies the given matrix as a perspective transform to the given point.
///
/// This function assumes the given point has a z-coordinate of 0.0. The
/// z-coordinate of the result is ignored.
///
/// While not common, this method may return (NaN, NaN), iff the given `point`
/// results in a "point at infinity" in homogeneous coordinates after applying
/// the `transform`. For example, a [RenderObject] may set its transform to
/// the zero matrix to indicate its content is currently not visible. Trying
/// to convert an `Offset` to its coordinate space always results in
/// (NaN, NaN).
static Offset transformPoint(Matrix4 transform, Offset point) {
final Float64List storage = transform.storage;
final double x = point.dx;
final double y = point.dy;
// Directly simulate the transform of the vector (x, y, 0, 1),
// dropping the resulting Z coordinate, and normalizing only
// if needed.
final double rx = storage[0] * x + storage[4] * y + storage[12];
final double ry = storage[1] * x + storage[5] * y + storage[13];
final double rw = storage[3] * x + storage[7] * y + storage[15];
if (rw == 1.0) {
return Offset(rx, ry);
} else {
return Offset(rx / rw, ry / rw);
}
}
/// Returns a rect that bounds the result of applying the given matrix as a
/// perspective transform to the given rect.
///
/// This version of the operation is slower than the regular transformRect
/// method, but it avoids creating infinite values from large finite values
/// if it can.
static Rect _safeTransformRect(Matrix4 transform, Rect rect) {
final Float64List storage = transform.storage;
final bool isAffine = storage[3] == 0.0 && storage[7] == 0.0 && storage[15] == 1.0;
_accumulate(storage, rect.left, rect.top, true, isAffine);
_accumulate(storage, rect.right, rect.top, false, isAffine);
_accumulate(storage, rect.left, rect.bottom, false, isAffine);
_accumulate(storage, rect.right, rect.bottom, false, isAffine);
return Rect.fromLTRB(_minMax[0], _minMax[1], _minMax[2], _minMax[3]);
}
static final Float64List _minMax = Float64List(4);
static void _accumulate(Float64List m, double x, double y, bool first, bool isAffine) {
final double w = isAffine ? 1.0 : 1.0 / (m[3] * x + m[7] * y + m[15]);
final double tx = (m[0] * x + m[4] * y + m[12]) * w;
final double ty = (m[1] * x + m[5] * y + m[13]) * w;
if (first) {
_minMax[0] = _minMax[2] = tx;
_minMax[1] = _minMax[3] = ty;
} else {
if (tx < _minMax[0]) {
_minMax[0] = tx;
}
if (ty < _minMax[1]) {
_minMax[1] = ty;
}
if (tx > _minMax[2]) {
_minMax[2] = tx;
}
if (ty > _minMax[3]) {
_minMax[3] = ty;
}
}
}
/// Returns a rect that bounds the result of applying the given matrix as a
/// perspective transform to the given rect.
///
/// This function assumes the given rect is in the plane with z equals 0.0.
/// The transformed rect is then projected back into the plane with z equals
/// 0.0 before computing its bounding rect.
static Rect transformRect(Matrix4 transform, Rect rect) {
final Float64List storage = transform.storage;
final double x = rect.left;
final double y = rect.top;
final double w = rect.right - x;
final double h = rect.bottom - y;
// We want to avoid turning a finite rect into an infinite one if we can.
if (!w.isFinite || !h.isFinite) {
return _safeTransformRect(transform, rect);
}
// Transforming the 4 corners of a rectangle the straightforward way
// incurs the cost of transforming 4 points using vector math which
// involves 48 multiplications and 48 adds and then normalizing
// the points using 4 inversions of the homogeneous weight factor
// and then 12 multiplies. Once we have transformed all of the points
// we then need to turn them into a bounding box using 4 min/max
// operations each on 4 values yielding 12 total comparisons.
//
// On top of all of those operations, using the vector_math package to
// do the work for us involves allocating several objects in order to
// communicate the values back and forth - 4 allocating getters to extract
// the [Offset] objects for the corners of the [Rect], 4 conversions to
// a [Vector3] to use [Matrix4.perspectiveTransform()], and then 4 new
// [Offset] objects allocated to hold those results, yielding 8 [Offset]
// and 4 [Vector3] object allocations per rectangle transformed.
//
// But the math we really need to get our answer is actually much less
// than that.
//
// First, consider that a full point transform using the vector math
// package involves expanding it out into a vector3 with a Z coordinate
// of 0.0 and then performing 3 multiplies and 3 adds per coordinate:
//
// xt = x*m00 + y*m10 + z*m20 + m30;
// yt = x*m01 + y*m11 + z*m21 + m31;
// zt = x*m02 + y*m12 + z*m22 + m32;
// wt = x*m03 + y*m13 + z*m23 + m33;
//
// Immediately we see that we can get rid of the 3rd column of multiplies
// since we know that Z=0.0. We can also get rid of the 3rd row because
// we ignore the resulting Z coordinate. Finally we can get rid of the
// last row if we don't have a perspective transform since we can verify
// that the results are 1.0 for all points. This gets us down to 16
// multiplies and 16 adds in the non-perspective case and 24 of each for
// the perspective case. (Plus the 12 comparisons to turn them back into
// a bounding box.)
//
// But we can do even better than that.
//
// Under optimal conditions of no perspective transformation,
// which is actually a very common condition, we can transform
// a rectangle in as little as 3 operations:
//
// (rx,ry) = transform of upper left corner of rectangle
// (wx,wy) = delta transform of the (w, 0) width relative vector
// (hx,hy) = delta transform of the (0, h) height relative vector
//
// A delta transform is a transform of all elements of the matrix except
// for the translation components. The translation components are added
// in at the end of each transform computation so they represent a
// constant offset for each point transformed. A delta transform of
// a horizontal or vertical vector involves a single multiplication due
// to the fact that it only has one non-zero coordinate and no addition
// of the translation component.
//
// In the absence of a perspective transform, the transformed
// rectangle will be mapped into a parallelogram with corners at:
// corner1 = (rx, ry)
// corner2 = corner1 + dTransformed width vector = (rx+wx, ry+wy)
// corner3 = corner1 + dTransformed height vector = (rx+hx, ry+hy)
// corner4 = corner1 + both dTransformed vectors = (rx+wx+hx, ry+wy+hy)
// In all, this method of transforming the rectangle requires only
// 8 multiplies and 12 additions (which we can reduce to 8 additions if
// we only need a bounding box, see below).
//
// In the presence of a perspective transform, the above conditions
// continue to hold with respect to the non-normalized coordinates so
// we can still save a lot of multiplications by computing the 4
// non-normalized coordinates using relative additions before we normalize
// them and they lose their "pseudo-parallelogram" relationships. We still
// have to do the normalization divisions and min/max all 4 points to
// get the resulting transformed bounding box, but we save a lot of
// calculations over blindly transforming all 4 coordinates independently.
// In all, we need 12 multiplies and 22 additions to construct the
// non-normalized vectors and then 8 divisions (or 4 inversions and 8
// multiplies) for normalization (plus the standard set of 12 comparisons
// for the min/max bounds operations).
//
// Back to the non-perspective case, the optimization that lets us get
// away with fewer additions if we only need a bounding box comes from
// analyzing the impact of the relative vectors on expanding the
// bounding box of the parallelogram. First, the bounding box always
// contains the transformed upper-left corner of the rectangle. Next,
// each relative vector either pushes on the left or right side of the
// bounding box and also either the top or bottom side, depending on
// whether it is positive or negative. Finally, you can consider the
// impact of each vector on the bounding box independently. If, say,
// wx and hx have the same sign, then the limiting point in the bounding
// box will be the one that involves adding both of them to the origin
// point. If they have opposite signs, then one will push one wall one
// way and the other will push the opposite wall the other way and when
// you combine both of them, the resulting "opposite corner" will
// actually be between the limits they established by pushing the walls
// away from each other, as below:
//
// +---------(originx,originy)--------------+
// | -----^---- |
// | ----- ---- |
// | ----- ---- |
// (+hx,+hy)< ---- |
// | ---- ---- |
// | ---- >(+wx,+wy)
// | ---- ----- |
// | ---- ----- |
// | ---- ----- |
// | v |
// +---------------(+wx+hx,+wy+hy)----------+
//
// In this diagram, consider that:
//
// * wx would be a positive number
// * hx would be a negative number
// * wy and hy would both be positive numbers
//
// As a result, wx pushes out the right wall, hx pushes out the left wall,
// and both wy and hy push down the bottom wall of the bounding box. The
// wx,hx pair (of opposite signs) worked on opposite walls and the final
// opposite corner had an X coordinate between the limits they established.
// The wy,hy pair (of the same sign) both worked together to push the
// bottom wall down by their sum.
//
// This relationship allows us to simply start with the point computed by
// transforming the upper left corner of the rectangle, and then
// conditionally adding wx, wy, hx, and hy to either the left or top
// or right or bottom of the bounding box independently depending on sign.
// In that case we only need 4 comparisons and 4 additions total to
// compute the bounding box, combined with the 8 multiplications and
// 4 additions to compute the transformed point and relative vectors
// for a total of 8 multiplies, 8 adds, and 4 comparisons.
//
// An astute observer will note that we do need to do 2 subtractions at
// the top of the method to compute the width and height. Add those to
// all of the relative solutions listed above. The test for perspective
// also adds 3 compares to the affine case and up to 3 compares to the
// perspective case (depending on which test fails, the rest are omitted).
//
// The final tally:
// basic method = 60 mul + 48 add + 12 compare
// optimized perspective = 12 mul + 22 add + 15 compare + 2 sub
// optimized affine = 8 mul + 8 add + 7 compare + 2 sub
//
// Since compares are essentially subtractions and subtractions are
// the same cost as adds, we end up with:
// basic method = 60 mul + 60 add/sub/compare
// optimized perspective = 12 mul + 39 add/sub/compare
// optimized affine = 8 mul + 17 add/sub/compare
final double wx = storage[0] * w;
final double hx = storage[4] * h;
final double rx = storage[0] * x + storage[4] * y + storage[12];
final double wy = storage[1] * w;
final double hy = storage[5] * h;
final double ry = storage[1] * x + storage[5] * y + storage[13];
if (storage[3] == 0.0 && storage[7] == 0.0 && storage[15] == 1.0) {
var left = rx;
var right = rx;
if (wx < 0) {
left += wx;
} else {
right += wx;
}
if (hx < 0) {
left += hx;
} else {
right += hx;
}
var top = ry;
var bottom = ry;
if (wy < 0) {
top += wy;
} else {
bottom += wy;
}
if (hy < 0) {
top += hy;
} else {
bottom += hy;
}
return Rect.fromLTRB(left, top, right, bottom);
} else {
final double ww = storage[3] * w;
final double hw = storage[7] * h;
final double rw = storage[3] * x + storage[7] * y + storage[15];
final double ulx = rx / rw;
final double uly = ry / rw;
final double urx = (rx + wx) / (rw + ww);
final double ury = (ry + wy) / (rw + ww);
final double llx = (rx + hx) / (rw + hw);
final double lly = (ry + hy) / (rw + hw);
final double lrx = (rx + wx + hx) / (rw + ww + hw);
final double lry = (ry + wy + hy) / (rw + ww + hw);
return Rect.fromLTRB(
_min4(ulx, urx, llx, lrx),
_min4(uly, ury, lly, lry),
_max4(ulx, urx, llx, lrx),
_max4(uly, ury, lly, lry),
);
}
}
static double _min4(double a, double b, double c, double d) {
final e = (a < b) ? a : b;
final f = (c < d) ? c : d;
return (e < f) ? e : f;
}
static double _max4(double a, double b, double c, double d) {
final e = (a > b) ? a : b;
final f = (c > d) ? c : d;
return (e > f) ? e : f;
}
/// Returns a rect that bounds the result of applying the inverse of the given
/// matrix as a perspective transform to the given rect.
///
/// This function assumes the given rect is in the plane with z equals 0.0.
/// The transformed rect is then projected back into the plane with z equals
/// 0.0 before computing its bounding rect.
static Rect inverseTransformRect(Matrix4 transform, Rect rect) {
// As exposed by `unrelated_type_equality_checks`, this assert was a no-op.
// Fixing it introduces a bunch of runtime failures; for more context see:
// https://github.com/flutter/flutter/pull/31568
// assert(transform.determinant != 0.0);
if (isIdentity(transform)) {
return rect;
}
transform = Matrix4.copy(transform)..invert();
return transformRect(transform, rect);
}
/// Create a transformation matrix which mimics the effects of tangentially
/// wrapping the plane on which this transform is applied around a cylinder
/// and then looking at the cylinder from a point outside the cylinder.
///
/// The `radius` simulates the radius of the cylinder the plane is being
/// wrapped onto. If the transformation is applied to a 0-dimensional dot
/// instead of a plane, the dot would translate by ± `radius` pixels
/// along the `orientation` [Axis] when rotating from 0 to ±90 degrees.
///
/// A positive radius means the object is closest at 0 `angle` and a negative
/// radius means the object is closest at π `angle` or 180 degrees.
///
/// The `angle` argument is the difference in angle in radians between the
/// object and the viewing point. A positive `angle` on a positive `radius`
/// moves the object up when `orientation` is vertical and right when
/// horizontal.
///
/// The transformation is always done such that a 0 `angle` keeps the
/// transformed object at exactly the same size as before regardless of
/// `radius` and `perspective` when `radius` is positive.
///
/// The `perspective` argument is a number between 0 and 1 where 0 means
/// looking at the object from infinitely far with an infinitely narrow field
/// of view and 1 means looking at the object from infinitely close with an
/// infinitely wide field of view. Defaults to a sane but arbitrary 0.001.
///
/// The `orientation` is the direction of the rotation axis.
///
/// Because the viewing position is a point, it's never possible to see the
/// outer side of the cylinder at or past ±π/2 or 90 degrees and it's
/// almost always possible to end up seeing the inner side of the cylinder
/// or the back side of the transformed plane before π / 2 when perspective > 0.
static Matrix4 createCylindricalProjectionTransform({
required double radius,
required double angle,
double perspective = 0.001,
Axis orientation = Axis.vertical,
}) {
assert(perspective >= 0 && perspective <= 1.0);
// Pre-multiplied matrix of a projection matrix and a view matrix.
//
// Projection matrix is a simplified perspective matrix
// http://web.iitd.ac.in/~hegde/cad/lecture/L9_persproj.pdf
// in the form of
// [[1.0, 0.0, 0.0, 0.0],
// [0.0, 1.0, 0.0, 0.0],
// [0.0, 0.0, 1.0, 0.0],
// [0.0, 0.0, -perspective, 1.0]]
//
// View matrix is a simplified camera view matrix.
// Basically re-scales to keep object at original size at angle = 0 at
// any radius in the form of
// [[1.0, 0.0, 0.0, 0.0],
// [0.0, 1.0, 0.0, 0.0],
// [0.0, 0.0, 1.0, -radius],
// [0.0, 0.0, 0.0, 1.0]]
var result = Matrix4.identity()
..setEntry(3, 2, -perspective)
..setEntry(2, 3, -radius)
..setEntry(3, 3, perspective * radius + 1.0);
// Model matrix by first translating the object from the origin of the world
// by radius in the z axis and then rotating against the world.
result =
result *
(switch (orientation) {
Axis.horizontal => Matrix4.rotationY(angle),
Axis.vertical => Matrix4.rotationX(angle),
} *
Matrix4.translationValues(0.0, 0.0, radius))
as Matrix4;
// Essentially perspective * view * model.
return result;
}
/// Returns a matrix that transforms every point to [offset].
static Matrix4 forceToPoint(Offset offset) {
final result = Matrix4.zero();
final Float64List storage = result.storage;
// Matrix4 is column-major.
// The first two columns (indices 0, 1, 4, 5) are zero, so x and y are ignored.
storage[10] = 1; // Row 2, Column 2: z' = z
storage[12] = offset.dx; // Row 0, Column 3: x' = offset.dx
storage[13] = offset.dy; // Row 1, Column 3: y' = offset.dy
storage[15] = 1; // Row 3, Column 3: w' = w
return result;
}
}
/// Returns a list of strings representing the given transform in a format
/// useful for [TransformProperty].
///
/// If the argument is null, returns a list with the single string "null".
List<String> debugDescribeTransform(Matrix4? transform) {
if (transform == null) {
return const <String>['null'];
}
return <String>[
'[0] ${debugFormatDouble(transform.entry(0, 0))},${debugFormatDouble(transform.entry(0, 1))},${debugFormatDouble(transform.entry(0, 2))},${debugFormatDouble(transform.entry(0, 3))}',
'[1] ${debugFormatDouble(transform.entry(1, 0))},${debugFormatDouble(transform.entry(1, 1))},${debugFormatDouble(transform.entry(1, 2))},${debugFormatDouble(transform.entry(1, 3))}',
'[2] ${debugFormatDouble(transform.entry(2, 0))},${debugFormatDouble(transform.entry(2, 1))},${debugFormatDouble(transform.entry(2, 2))},${debugFormatDouble(transform.entry(2, 3))}',
'[3] ${debugFormatDouble(transform.entry(3, 0))},${debugFormatDouble(transform.entry(3, 1))},${debugFormatDouble(transform.entry(3, 2))},${debugFormatDouble(transform.entry(3, 3))}',
];
}
/// Property which handles [Matrix4] that represent transforms.
class TransformProperty extends DiagnosticsProperty<Matrix4> {
/// Create a diagnostics property for [Matrix4] objects.
TransformProperty(
String super.name,
super.value, {
super.showName,
super.defaultValue,
super.level,
});
@override
String valueToString({TextTreeConfiguration? parentConfiguration}) {
if (parentConfiguration != null && !parentConfiguration.lineBreakProperties) {
// Format the value on a single line to be compatible with the parent's
// style.
final values = <String>[
'${debugFormatDouble(value!.entry(0, 0))},${debugFormatDouble(value!.entry(0, 1))},${debugFormatDouble(value!.entry(0, 2))},${debugFormatDouble(value!.entry(0, 3))}',
'${debugFormatDouble(value!.entry(1, 0))},${debugFormatDouble(value!.entry(1, 1))},${debugFormatDouble(value!.entry(1, 2))},${debugFormatDouble(value!.entry(1, 3))}',
'${debugFormatDouble(value!.entry(2, 0))},${debugFormatDouble(value!.entry(2, 1))},${debugFormatDouble(value!.entry(2, 2))},${debugFormatDouble(value!.entry(2, 3))}',
'${debugFormatDouble(value!.entry(3, 0))},${debugFormatDouble(value!.entry(3, 1))},${debugFormatDouble(value!.entry(3, 2))},${debugFormatDouble(value!.entry(3, 3))}',
];
return '[${values.join('; ')}]';
}
return debugDescribeTransform(value).join('\n');
}
}