From 875297b8b6e045c847e24d68448b7321797fbffc Mon Sep 17 00:00:00 2001 From: Natalia Polina Date: Tue, 20 Jun 2023 15:04:59 -0500 Subject: [PATCH] Added dtype parameter in np.cov() function call. --- dpbench/benchmarks/pca/pca_dpnp.py | 2 +- dpbench/benchmarks/pca/pca_numpy.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/dpbench/benchmarks/pca/pca_dpnp.py b/dpbench/benchmarks/pca/pca_dpnp.py index cbf51dd5..f163f6ea 100644 --- a/dpbench/benchmarks/pca/pca_dpnp.py +++ b/dpbench/benchmarks/pca/pca_dpnp.py @@ -10,7 +10,7 @@ def pca(data, dims_rescaled_data=2): data -= data.mean(axis=0) # calculate the covariance matrix - v = np.cov(data, rowvar=False) + v = np.cov(data, rowvar=False, dtype=data.dtype) # calculate eigenvectors & eigenvalues of the covariance matrix evalues, evectors = np.linalg.eigh(v) diff --git a/dpbench/benchmarks/pca/pca_numpy.py b/dpbench/benchmarks/pca/pca_numpy.py index 7c180a7a..6735216d 100644 --- a/dpbench/benchmarks/pca/pca_numpy.py +++ b/dpbench/benchmarks/pca/pca_numpy.py @@ -10,7 +10,7 @@ def pca(data, dims_rescaled_data=2): data -= data.mean(axis=0) # calculate the covariance matrix - v = np.cov(data, rowvar=False) + v = np.cov(data, rowvar=False, dtype=data.dtype) # calculate eigenvectors & eigenvalues of the covariance matrix evalues, evectors = np.linalg.eigh(v)