def test_pca(app_inst: ArrayApplication):
real_X, _ = BimodalGaussian.get_dataset(2345, 9)
X = app_inst.array(real_X, block_shape=(123, 4))
# Covariance matrix test.
C = app_inst.cov(X, rowvar=False)
V, _, VT = linalg.svd(app_inst, C)
assert app_inst.allclose(V, VT.T)
pc = X @ V
assert app_inst.allclose(pc, linalg.pca(app_inst, X))
def pca(app: ArrayApplication, X: BlockArray):
C = app.cov(X, rowvar=False)
U, _, _ = svd(app, C)
return X @ U