def downScale(self, factor):
""" Cube data zoomed out """
newdata = np.zeros([
self.data.shape[0], self.data.shape[1] /
(2**factor), self.data.shape[2] / (2**factor)
],
dtype=np.uint32)
ocplib.zoomOutData_ctype(self.data, newdata, int(factor))
self.data = newdata
def downScale ( self, factor ):
""" Cube data zoomed out """
#KLTODO write an optimize version in cython
newdata = np.zeros ( [self.data.shape[0], self.data.shape[1]/(2**factor), self.data.shape[2]/(2**factor)], dtype=np.uint32)
#test = np.zeros ( [self.data.shape[0], self.data.shape[1]/(2**factor), self.data.shape[2]/(2**factor)], dtype=np.uint32)
import time
start = time.time()
ocplib.zoomOutData_ctype ( self.data, newdata, int(factor) )
print "Ctype", time.time()-start
#start = time.time()
#ocplib.zoomOutData_ctype_OMP ( self.data, test, int(factor) )
#print "OMP", time.time()-start
self.data = newdata
def downScale ( self, factor ):
""" Cube data zoomed out """
newdata = np.zeros ( [self.data.shape[0], self.data.shape[1]/(2**factor), self.data.shape[2]/(2**factor)], dtype=np.uint32)
ocplib.zoomOutData_ctype ( self.data, newdata, int(factor) )
self.data = newdata
