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Commit 0567e53b authored by Danilo Ferreira de Lima's avatar Danilo Ferreira de Lima
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Reset PCA comps.

parent 90e6b8ee
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1 merge request!17Make Torch optional and allow for backwards compatibility on autocovariance calculation
...@@ -289,14 +289,14 @@ def main(): ...@@ -289,14 +289,14 @@ def main():
pca = PCA(None, whiten=True) pca = PCA(None, whiten=True)
pca.fit(pes_raw_select) pca.fit(pes_raw_select)
df = pd.DataFrame(dict(variance_ratio=pca.explained_variance_ratio_, df = pd.DataFrame(dict(variance_ratio=pca.explained_variance_ratio_,
n_comp=1000*np.ones_like(pca.explained_variance_ratio_), n_comp=600*np.ones_like(pca.explained_variance_ratio_),
)) ))
df.to_csv(os.path.join(args.directory, "pca_pes.csv")) df.to_csv(os.path.join(args.directory, "pca_pes.csv"))
pca_spec = PCA(None, whiten=True) pca_spec = PCA(None, whiten=True)
pca_spec.fit(spec_raw_int[train_idx]) pca_spec.fit(spec_raw_int[train_idx])
df = pd.DataFrame(dict(variance_ratio=pca_spec.explained_variance_ratio_, df = pd.DataFrame(dict(variance_ratio=pca_spec.explained_variance_ratio_,
n_comp=40*np.ones_like(pca_spec.explained_variance_ratio_), n_comp=20*np.ones_like(pca_spec.explained_variance_ratio_),
)) ))
df.to_csv(os.path.join(args.directory, "pca_spec.csv")) df.to_csv(os.path.join(args.directory, "pca_spec.csv"))
......
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