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_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 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_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
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
from shogun.Features import ByteFeatures from numpy import array, uint8, all # create dense matrix A A=array([[1,2,3],[4,0,0],[0,0,0],[0,5,0],[0,0,6],[9,9,9]], dtype=uint8) # ... 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(array([1,4,0,0,0,9], dtype=uint8), 0) # get matrix a_out = a.get_feature_matrix() print type(a_out), a_out.dtype print a_out assert(all(a_out==A))
from shogun.Features import RealFeatures, LongIntFeatures, ByteFeatures from numpy import array, float64, int64, uint8, all # create dense matrices A,B,C A=array([[1,2,3],[4,0,0],[0,0,0],[0,5,0],[0,0,6],[9,9,9]], dtype=float64) B=array([[1,2,3],[4,0,0],[0,0,0],[0,5,0],[0,0,6],[9,9,9]], dtype=int64) C=array([[1,2,3],[4,0,0],[0,0,0],[0,5,0],[0,0,6],[9,9,9]], dtype=uint8) # ... of type Real, LongInt and Byte 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 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(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()
