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Make centering optional #9

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15 changes: 9 additions & 6 deletions pyopls/opls.py
Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
from sklearn.utils.validation import check_consistent_length


def _center_scale_xy(X, Y, scale=True):
def _center_scale_xy(X, Y, scale=False, center = False):
""" Center X, Y and scale if the scale parameter==True

Returns
Expand All @@ -17,9 +17,12 @@ def _center_scale_xy(X, Y, scale=True):
"""
# center
x_mean = X.mean(axis=0)
X -= x_mean
y_mean = Y.mean(axis=0)
Y -= y_mean

if center:
X -= x_mean
Y -= y_mean

# scale
if scale:
x_std = X.std(axis=0, ddof=1)
Expand Down Expand Up @@ -64,10 +67,10 @@ class OPLS(BaseEstimator, TransformerMixin):
Johan Trygg and Svante Wold. Orthogonal projections to latent structures (O-PLS).
J. Chemometrics 2002; 16: 119-128. DOI: 10.1002/cem.695
"""
def __init__(self, n_components=5, scale=True):
def __init__(self, n_components=5, scale=True, center = False):
self.n_components = n_components
self.scale = scale

self.center = center
self.W_ortho_ = None
self.P_ortho_ = None
self.T_ortho_ = None
Expand Down Expand Up @@ -99,7 +102,7 @@ def fit(self, X, Y):
if Y.ndim == 1:
Y = Y.reshape(-1, 1)

X, Y, self.x_mean_, self.y_mean_, self.x_std_, self.y_std_ = _center_scale_xy(X, Y, self.scale)
X, Y, self.x_mean_, self.y_mean_, self.x_std_, self.y_std_ = _center_scale_xy(X, Y, self.scale, self.center )

Z = X.copy()
w = np.dot(X.T, Y) # calculate weight vector
Expand Down