def construct_oa(al):
""" Transform one Hadamard matrix into several OAs """
oalist = []
nfactors = al.n_columns
altwo = al * 2 - 1
for ii in range(nfactors):
Hadmat = altwo.getarray()
norm_col = Hadmat[:, ii]
OAtwo = np.multiply(norm_col.reshape((-1, 1)), Hadmat)
OAtwo = np.delete(OAtwo, ii, 1)
A = oapackage.makearraylink((OAtwo + 1) / 2)
oalist.append(oapackage.makearraylink(A))
return (oalist)
def _get_array(f, N=32, k=32, verbose=1):
""" Return array from file """
A = np.zeros((N, k), dtype=int)
row = 0
al = None
while True:
l = f.readline()
if verbose >= 2:
print(l)
print('len(l) %d' % len(l))
if len(l) == 0:
break
if l == '\n':
continue
if 0:
for c in l:
print(c)
if len(l) == (k / 4) + 1:
l = l.strip()
if verbose:
print(f'row {row}: {l}')
x = bin(int(l, 16))[2:]
A[row, :] = [int(y) for y in list(x)]
row = row + 1
if row == N:
break
al = oapackage.makearraylink(A[:row, :])
return al
def test_numpy_interface(verbose=0):
A = np.eye(3, 4).astype(int)
A[0, :] = [10, 20, 30, 50]
A[2, :] = [-3, -4, -5, -6]
if verbose:
print('makearraylink')
al = oapackage.makearraylink(A)
np.testing.assert_array_equal(np.array(al), A)
if verbose:
al.showarray()
if verbose:
print('direct')
al = oapackage.array_link(A)
if verbose:
al.showarray()
Ax = np.array(al)
if verbose:
print(A)
print(Ax)
with np.testing.assert_raises(TypeError):
# not possible right now...
if verbose:
print('direct float')
A = np.eye(3).astype(float)
al = oapackage.array_link(A)
if verbose:
al.showarray()
def selectIsomorphismClasses(sols, verbose=1):
""" Select isomorphism classes from a list of designs
Args:
sols (list of arrays)
verbose (int)
Return:
indices (list of integers): indices of the isomorphism classes
mm (list of arrays): the arrays in normal form
Example:
>>> sols=[oapackage.exampleArray(i) for i in [26,26,27,26]]
>>> idx, mm = selectIsomorphismClasses(sols)
To select one representative array from each isomorphism class one can use:
>>> _, ui = np.unique(idx, return_index=True)
>>> representatives = [sols[i] for i in ui]
"""
# perform check on array data type
mm = []
for ii, al in enumerate(sols):
if verbose:
oapackage.tprint('selectIsomorphismClasses: process aray %d/%d' %
(ii, len(sols)))
al = oapackage.makearraylink(al)
tt = oapackage.reduceOAnauty(al, verbose >= 2)
#pp, tt = reduceBliss(al, arrayclass, verbose >= 2)
#tt = graph2arrayTransformation(pp, arrayclass)
alx = tt.apply(al)
mm.append(np.array(alx))
pass
# perform uniqueness check
nn = len(mm)
qq = np.array([None] * nn, dtype=object)
for ii in range(nn):
qq[ii] = mm[ii].flatten()
# Trick to make unique work...
nx = qq[0].size
dt = qq[0].dtype.descr * nx
qqq = np.array(qq, dtype=dt)
a, indices = np.unique(qqq, return_inverse=True)
if verbose >= 1:
print('selectIsomorphismClasses: reduce %d to %d' %
(len(sols), np.unique(indices).size))
return indices, mm
def selectIsomorphismClasses(sols, verbose=1):
""" Select isomorphism classes from a list of designs
Args:
sols (list of arrays)
verbose (int)
Return:
indices (list of integers): indices of the isomorphism classes
mm (list of arrays): the arrays in normal form
"""
# perform check on array data type
mm = []
for ii, al in enumerate(sols):
if verbose:
oapackage.tprint('selectIsomorphismClasses: process aray %d/%d' %
(ii, len(sols)),
dt=4)
al = oapackage.makearraylink(al)
tt = oapackage.reduceOAnauty(al, verbose >= 2)
#pp, tt = reduceBliss(al, arrayclass, verbose >= 2)
#tt = graph2arrayTransformation(pp, arrayclass)
alx = tt.apply(al)
mm.append(np.array(alx))
pass
# perform uniqueness check
nn = len(mm)
qq = np.array([None] * nn, dtype=object)
for ii in range(nn):
qq[ii] = mm[ii].flatten()
if 0:
# Trick to make unique work...
# old code
nx = qq[0].size
dt = qq[0].dtype.descr * nx
qqq = [np.array(q, dtype=dt) for q in qq]
qqq = np.array(qq, dtype=dt)
a, indices = np.unique(qqq, return_inverse=True)
# Trick to make unique work...
a, indices = np.unique(np.vstack(qq), axis=0, return_inverse=True)
if verbose >= 1:
print('selectIsomorphismClasses: %d reduced to %d' %
(len(sols), np.unique(indices).size))
return indices, mm
def test_arraylink_slicing(self):
numpy_array = np.arange(0, 6 * 10).reshape((6, 10))
al = oapackage.makearraylink(numpy_array)
self.assertTrue(al[0] == numpy_array.flatten()[0])
self.assertTrue(al[0, 1] == numpy_array[0, 1])
self.assertTrue(al[4, 2] == numpy_array[4, 2])
np.testing.assert_equal(al[0:4, 1:5], np.array(al)[0:4, 1:5])
np.testing.assert_equal(al[0:1, 0:10:2], np.array(al)[0:1, 0:10:2])
np.testing.assert_equal(al[3, 3::], np.array(al)[3:4, 3::])
np.testing.assert_equal(al[2, :8:2], np.array(al)[2:3, :8:2])
np.testing.assert_equal(al[2:3, :8:2], np.array(al)[2:3, :8:2])
with self.assertRaises(IndexError):
_ = al[-1, 1]
def selectIsomorphismClasses(sols, verbose=1):
""" Select isomorphism classes from a list of designs
Args:
sols (list of arrays): list of arrays from which to determine the unique ones
verbose (int): verbosity level
Return:
indices (list of integers): indices of the isomorphism classes
mm (list of arrays): the arrays in normal form
Example:
>>> import oapackage.graphtools; import numpy as np
>>> sols=[oapackage.exampleArray(idx) for idx in [26,26,27,26]]
>>> idx, mm = oapackage.graphtools.selectIsomorphismClasses(sols, verbose=0)
>>> _, unique_indices = np.unique(idx, return_index=True)
>>> print('found %d isomorphism classes from %d arrays' % (len(unique_indices), len(sols)) )
found 2 isomorphism classes from 4 arrays
>>> representatives = [sols[idx] for idx in unique_indices]
"""
mm = []
for ii, al in enumerate(sols):
if verbose:
oapackage.tprint(
'selectIsomorphismClasses: process aray %d/%d' % (ii, len(sols)))
al = oapackage.makearraylink(al)
tt = oapackage.reduceOAnauty(al, verbose >= 2)
alx = tt.apply(al)
mm.append(np.array(alx))
# perform uniqueness check
nn = len(mm)
qq = np.array([None] * nn, dtype=object)
for ii in range(nn):
qq[ii] = mm[ii].flatten()
# Trick to make unique work...
_, indices = np.unique(np.vstack(qq), axis=0, return_inverse=True)
if verbose >= 1:
print('selectIsomorphismClasses: reduce %d to %d' %
(len(sols), np.unique(indices).size))
return indices, mm
def selectIsomorphismClasses(sols, verbose=1):
""" Select isomorphism classes from a list of designs
Args:
sols (list of arrays): list of arrays from which to determine the unique ones
verbose (int): verbosity level
Return:
indices (list of integers): indices of the isomorphism classes
mm (list of arrays): the arrays in normal form
Example:
>>> import oapackage.graphtools; import numpy as np
>>> sols=[oapackage.exampleArray(idx) for idx in [26,26,27,26]]
>>> idx, mm = oapackage.graphtools.selectIsomorphismClasses(sols, verbose=0)
>>> _, unique_indices = np.unique(idx, return_index=True)
>>> print('found %d isomorphism classes from %d arrays' % (len(unique_indices), len(sols)) )
found 2 isomorphism classes from 4 arrays
>>> representatives = [sols[idx] for idx in unique_indices]
"""
mm = []
for ii, al in enumerate(sols):
if verbose:
oapackage.tprint('selectIsomorphismClasses: process aray %d/%d' %
(ii, len(sols)))
al = oapackage.makearraylink(al)
tt = oapackage.reduceOAnauty(al, verbose >= 2)
alx = tt.apply(al)
mm.append(np.array(alx))
# perform uniqueness check
nn = len(mm)
qq = np.array([None] * nn, dtype=object)
for ii in range(nn):
qq[ii] = mm[ii].flatten()
# Trick to make unique work...
_, indices = np.unique(np.vstack(qq), axis=0, return_inverse=True)
if verbose >= 1:
print('selectIsomorphismClasses: reduce %d to %d' %
(len(sols), np.unique(indices).size))
return indices, mm