def kernel_linear_byte_modular(fm_train_byte=traindat,fm_test_byte=testdat): from shogun.Kernel import LinearKernel from shogun.Features import ByteFeatures feats_train=ByteFeatures(fm_train_byte) feats_test=ByteFeatures(fm_test_byte) kernel=LinearKernel(feats_train, feats_train) km_train=kernel.get_kernel_matrix() kernel.init(feats_train, feats_test) km_test=kernel.get_kernel_matrix() return kernel
def features_simple_modular(A=matrixA, B=matrixB, C=matrixC):
a = RealFeatures(A)
b = LongIntFeatures(B)
c = ByteFeatures(C)
# or 16bit wide ...
#feat1 = f.ShortFeatures(N.zeros((10,5),N.short))
#feat2 = f.WordFeatures(N.zeros((10,5),N.uint16))
# print some statistics about a
# get first feature vector and set it
a.set_feature_vector(array([1, 4, 0, 0, 0, 9], dtype=float64), 0)
# get matrices
a_out = a.get_feature_matrix()
b_out = b.get_feature_matrix()
c_out = c.get_feature_matrix()
assert (all(a_out == A))
assert (all(b_out == B))
assert (all(c_out == C))
return a_out, b_out, c_out, a, b, c
def features_simple_byte_modular(A):
from shogun.Features import ByteFeatures
# create dense features a
# ... of type Byte
a = ByteFeatures(A)
# print some statistics about a
#print a.get_num_vectors()
#print a.get_num_features()
# get first feature vector and set it
#print a.get_feature_vector(0)
a.set_feature_vector(numpy.array([1, 4, 0, 0, 0, 9], dtype=numpy.uint8), 0)
# get matrix
a_out = a.get_feature_matrix()
#print type(a_out), a_out.dtype
#print a_out
assert (numpy.all(a_out == A))
return a_out, a