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