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 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_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 shogun.Features import HashedWDFeatures, StringByteFeatures, RAWDNA
from shogun.IO 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
from shogun.Features import LongIntFeatures from numpy import array, int64, 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=int64) # ... of type LongInt a=LongIntFeatures(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=int64), 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()
