def features_dense_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_dense_longint_modular (A=matrix): a=LongIntFeatures(A) # get first feature vector and set it a.set_feature_vector(array([1,4,0,0,0,9], dtype=int64), 0) # get matrix a_out = a.get_feature_matrix() assert(all(a_out==A)) return a_out
def features_string_hashed_wd_modular(A=matrix,
order=3,
start_order=1,
hash_bits=2):
a = LongIntFeatures(A)
from numpy import array, uint8
from modshogun import HashedWDFeatures, StringByteFeatures, RAWDNA
from modshogun import MSG_DEBUG
x = [array([0, 1, 2, 3, 0, 1, 2, 3, 3, 2, 2, 1, 1], dtype=uint8)]
from_order = order
f = StringByteFeatures(RAWDNA)
#f.io.set_loglevel(MSG_DEBUG)
f.set_features(x)
y = HashedWDFeatures(f, start_order, order, from_order, hash_bits)
fm = y.get_computed_dot_feature_matrix()
return fm
