class LocfitEstimator(BaseEstimator):
"""
An R locfit estimator that pretends to work like a sklearn estimator.
"""
def __init__(self):
rfile = "/net/noble/vol2/home/katecook/proj/2015HiC-differential/src/call_locfit.R"
rfh = open(rfile, 'r')
string = ''.join(rfh.readlines())
self.locfit = SignatureTranslatedAnonymousPackage(string, "locfit")
def fit(self, X, y):
X_robj = robjects.FloatVector(X)
y_robj = robjects.FloatVector(y)
self.fit_ = self.locfit.do_fit(X_robj, y_robj)
def predict(self, X):
check_is_fitted(self, "fit_")
shape = X.shape
flat = X.flatten().T
#logging.debug(flat.shape)
#logging.debug(flat)
X_robj = robjects.FloatVector(flat)
#logging.debug(X_robj)
y_robj = self.locfit.safepredict(self.fit_, X_robj)
y_ = np.array(y_robj).T.reshape(shape)
logging.debug(y_)
np.savetxt("y.txt", y_, delimiter='\t')
return y_
def score(self, X, y):
yest = self.safepredict(X)
return r2_score(y, yest, sample_weight=None)
