Remove SVDecomp and SVBackSubst from TypeScript definitions

src/types/opencv/core_array.ts

@@ -2654,28 +2654,6 @@ export declare function subtract(
  */
 export declare function sum(src: InputArray): Scalar;
 
-/**
- * wrap [SVD::backSubst]
- */
-export declare function SVBackSubst(
-  w: InputArray,
-  u: InputArray,
-  vt: InputArray,
-  rhs: InputArray,
-  dst: OutputArray,
-): void;
-
-/**
- * wrap [SVD::compute]
- */
-export declare function SVDecomp(
-  src: InputArray,
-  w: OutputArray,
-  u: OutputArray,
-  vt: OutputArray,
-  flags?: int,
-): void;
-
 /**
  * The function [cv::theRNG] returns the default random number generator. For each thread, there is a
  * separate random number generator, so you can use the function safely in multi-thread environments.

test/linearAlgebra.test.ts

@@ -0,0 +1,68 @@
+import { setupOpenCv } from "./cv";
+
+beforeAll(setupOpenCv);
+
+describe("Linear Algebra Functions", () => {
+  it("should have solve, invert, and eigen functions", () => {
+    // These functions are available in opencv.js
+    expect(typeof cv.solve).toBe("function");
+    expect(typeof cv.invert).toBe("function");
+    expect(typeof cv.eigen).toBe("function");
+  });
+
+  it("should have DECOMP constants", () => {
+    // DECOMP constants are available
+    expect(cv.DECOMP_LU).toBe(0);
+    expect(cv.DECOMP_SVD).toBe(1);
+    expect(cv.DECOMP_EIG).toBe(2);
+    expect(cv.DECOMP_CHOLESKY).toBe(3);
+    expect(cv.DECOMP_QR).toBe(4);
+    expect(cv.DECOMP_NORMAL).toBe(16);
+  });
+
+  it("should NOT have SVDecomp and SVBackSubst functions", () => {
+    // SVDecomp and SVBackSubst are not compiled into opencv.js
+    // These functions were incorrectly included in TypeScript definitions before
+    // Using bracket notation to avoid TypeScript compilation errors
+    expect((cv as any)["SVDecomp"]).toBeUndefined();
+    expect((cv as any)["SVBackSubst"]).toBeUndefined();
+  });
+
+  it("should demonstrate solve function works", () => {
+    // Create a simple 2x2 linear system and verify solve can be called
+    // Using arbitrary matrix values just to test the function executes
+    const A = cv.matFromArray(2, 2, cv.CV_64F, [2, 1, 1, 3]);
+    const b = cv.matFromArray(2, 1, cv.CV_64F, [5, 6]);
+    const x = new cv.Mat();
+
+    const result = cv.solve(A, b, x, cv.DECOMP_LU);
+
+    // Just verify the function executes without error
+    expect(typeof result).toBe("boolean");
+    expect(x.rows).toBe(2);
+    expect(x.cols).toBe(1);
+
+    // Clean up
+    A.delete();
+    b.delete();
+    x.delete();
+  });
+
+  it("should demonstrate invert function works", () => {
+    // Create a simple invertible 2x2 matrix to test the function
+    // Using arbitrary matrix values just to test the function executes
+    const A = cv.matFromArray(2, 2, cv.CV_64F, [4, 7, 2, 6]);
+    const Ainv = new cv.Mat();
+
+    const det = cv.invert(A, Ainv, cv.DECOMP_LU);
+
+    // Just verify the function executes without error
+    expect(typeof det).toBe("number");
+    expect(Ainv.rows).toBe(2);
+    expect(Ainv.cols).toBe(2);
+
+    // Clean up
+    A.delete();
+    Ainv.delete();
+  });
+});