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fix tests and bugs revealed by new tests

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This commit is contained in:
Adrian Mariano 2021-10-01 23:57:07 -04:00
parent a5ae4879be
commit d66c1929a5
2 changed files with 16 additions and 4 deletions
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9
math.scad
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@ -545,10 +545,12 @@ function gaussian_rands(N=1, mean=0, cov=1, seed=undef) =
rdata = [for (i = count(dim*N,0,2)) sqrt(-2*ln(nums[i]))*cos(360*nums[i+1])] rdata = [for (i = count(dim*N,0,2)) sqrt(-2*ln(nums[i]))*cos(360*nums[i+1])]
) )
dim==1 ? add_scalar(sqrt(cov)*rdata,mean) : dim==1 ? add_scalar(sqrt(cov)*rdata,mean) :
assert(is_matrix_symmetric(cov),"Supplied covariance matrix is not symmetric")
let( let(
L = cholesky(cov) L = cholesky(cov)
) )
array_group(rdata,dim)*transpose(L); assert(is_def(L), "Supplied covariance matrix is not positive definite")
move(mean,array_group(rdata,dim)*transpose(L));
// Function: spherical_random_points() // Function: spherical_random_points()
@ -1092,14 +1094,13 @@ function _back_substitute(R, b, x=[]) =
function cholesky(A) = function cholesky(A) =
assert(is_matrix(A,square=true),"A must be a square matrix") assert(is_matrix(A,square=true),"A must be a square matrix")
assert(is_matrix_symmetric(A),"Cholesky factorization requires a symmetric matrix") assert(is_matrix_symmetric(A),"Cholesky factorization requires a symmetric matrix")
echo(A=A,len=len(A))
_cholesky(A,ident(len(A)), len(A)); _cholesky(A,ident(len(A)), len(A));
function _cholesky(A,L,n) = let(ffee=echo(insideA=A,L,n)) function _cholesky(A,L,n) =
A[0][0]<0 ? undef : // Matrix not positive definite A[0][0]<0 ? undef : // Matrix not positive definite
len(A) == 1 ? submatrix_set(L,[[sqrt(A[0][0])]], n-1,n-1): len(A) == 1 ? submatrix_set(L,[[sqrt(A[0][0])]], n-1,n-1):
let( let(
i = n+1-len(A),ff=echo(i=i,lenA=len(A)) i = n+1-len(A)
) )
let( let(
sqrtAii = sqrt(A[0][0]), sqrtAii = sqrt(A[0][0]),

11
tests/test_math.scad
View File

@ -368,6 +368,17 @@ module test_gaussian_rands() {
assert_equal(len(nums3), 1000); assert_equal(len(nums3), 1000);
assert_equal(nums1, nums3); assert_equal(nums1, nums3);
assert(nums1!=nums2); assert(nums1!=nums2);
R = [[4,2],[2,17]];
data = gaussian_rands(100000,[0,0],R,seed=49);
assert(approx(mean(data), [0,0], eps=1e-2));
assert(approx(transpose(data)*data/len(data), R, eps=2e-2));
R2 = [[4,2,-1],[2,17,4],[-1,4,11]];
data3 = gaussian_rands(100000,[1,2,3],R2,seed=97);
assert(approx(mean(data3),[1,2,3], eps=1e-2));
cdata = move(-mean(data3),data3);
assert(approx(transpose(cdata)*cdata/len(cdata),R2,eps=.1));
} }
test_gaussian_rands(); test_gaussian_rands();