def generateBTMatrix(factory, training, verbose=False):
from pysgpp import DataVector, DataMatrix
storage = factory.getStorage()
b = factory.createOperationB()
alpha = DataVector(storage.size())
temp = DataVector(training.getNrows())
# create BT matrix
m = DataMatrix(training.getNrows(), storage.size())
for i in xrange(storage.size()):
# apply unit vectors
temp.setAll(0.0)
alpha.setAll(0.0)
alpha[i] = 1.0
b.multTranspose(alpha, training, temp)
#Sets the column in m
m.setColumn(i, temp)
return m
def generateBBTMatrix(factory, training, verbose=False):
from pysgpp import DataVector, DataMatrix
storage = factory.getStorage()
b = createOperationMultipleEval(factory, training)
alpha = DataVector(storage.size())
erg = DataVector(len(alpha))
temp = DataVector(training.getNrows())
# create B matrix
m = DataMatrix(storage.size(), storage.size())
for i in xrange(storage.size()):
# apply unit vectors
temp.setAll(0.0)
erg.setAll(0.0)
alpha.setAll(0.0)
alpha[i] = 1.0
b.mult(alpha, temp)
b.multTranspose(temp, erg)
# Sets the column in m
m.setColumn(i, erg)
return m
def generateBBTMatrix(factory, training, verbose=False):
from pysgpp import DataVector, DataMatrix
storage = factory.getStorage()
b = createOperationMultipleEval(factory, training)
alpha = DataVector(storage.getSize())
erg = DataVector(len(alpha))
temp = DataVector(training.getNrows())
# create B matrix
m = DataMatrix(storage.getSize(), storage.getSize())
for i in range(storage.getSize()):
# apply unit vectors
temp.setAll(0.0)
erg.setAll(0.0)
alpha.setAll(0.0)
alpha[i] = 1.0
b.mult(alpha, temp)
b.multTranspose(temp, erg)
# Sets the column in m
m.setColumn(i, erg)
return m
