def test_sparsealleles_copyspan():
a = SparseAlleles(np.array([1, 1, 1, 1, 1, 1, 1], dtype=np.int), refcode=1)
b = SparseAlleles(np.array([2, 2, 2, 2, 2, 2, 2], dtype=np.int), refcode=1)
a.copy_span(b, 2, 6)
assert all(a.todense() == np.array([1, 1, 2, 2, 2, 2, 1]))
c = SparseAlleles(np.array([1, 1, 1, 1, 1, 1, 1], dtype=np.int), refcode=1)
a.copy_span(c, 2, 6)
assert all(a.todense() == np.array([1, 1, 1, 1, 1, 1, 1]))
def test_sparsealleles_meaninglesscomparisions():
# Comparsions like >, <, >=, <= aren't meaningful for genotypes
a = SparseAlleles([1, 2, 3, -1])
b = SparseAlleles([1, 3, 2, -1])
# Can't test an expression so we make a throwaway function to test
assert_raises(NotMeaningfulError, lambda x, y: x < y, a, b)
assert_raises(NotMeaningfulError, lambda x, y: x > y, a, b)
assert_raises(NotMeaningfulError, lambda x, y: x >= y, a, b)
assert_raises(NotMeaningfulError, lambda x, y: x <= y, a, b)
def test_sparsealleles():
a = SparseAlleles([1, 2, 3, -1], refcode=1)
b = SparseAlleles([1, 3, 2, -1], refcode=1)
assert a.nmark() == b.nmark() == 4
assert (a.missing == np.array([False, False, False, True])).all()
assert (a.missing == b.missing).all()
# Test todense
assert (a.todense() == [1, 2, 3, -1]).all()
assert isinstance(a.todense(), Alleles)
a = SparseAlleles([0, 0, 1, 0, -1, 1], refcode=0)
a[0] = a.missingcode
assert list(a.missing) == [True, False, False, False, True, False]
def test_sparsealleles_copyspan():
a = SparseAlleles(np.array([1,1,1,1,1,1,1], dtype=np.int), refcode=1)
b = SparseAlleles(np.array([2,2,2,2,2,2,2], dtype=np.int), refcode=1)
a.copy_span(b, 2, 6)
assert all(a.todense() == np.array([1,1,2,2,2,2,1]))
c = SparseAlleles(np.array([1,1,1,1,1,1,1], dtype=np.int), refcode=1)
a.copy_span(c, 2, 6)
assert all(a.todense() == np.array([1,1,1,1,1,1,1]))
def test_sparsealleles():
a = SparseAlleles([1,2,3,-1], refcode=1)
b = SparseAlleles([1,3,2,-1], refcode=1)
assert a.nmark() == b.nmark() == 4
assert (a.missing == np.array([False, False, False, True])).all()
assert (a.missing == b.missing).all()
# Test todense
assert (a.todense() == [1, 2, 3, -1]).all()
assert isinstance(a.todense(), Alleles)
a = SparseAlleles([0,0,1, 0,-1, 1], refcode=0)
a[0] = a.missingcode
assert list(a.missing) == [True, False, False, False, True, False]
def empty_chromosome(self, dtype=np.uint8, sparse=False, refcode=None):
"""
Produces a completely empty chromosome associated with this template.
:param sparse: Should a SparseAlleles object be returned
:type sparse: bool
:param refcode: if sparse, what should the refcode be?
:type refcode: int8_t
:returns: empty alleles container
"""
if sparse:
return SparseAlleles(size=self.nmark(),
template=self,
refcode=refcode)
else:
return Alleles(np.zeros(self.nmark(), dtype=dtype), template=self)
def linkageequilibrium_chromosome(self, sparse=False):
"""
Returns a randomly generated chromosome in linage equilibrium
:param sparse: Should the output be sparse
:type sparse: bool
:returns: random chromosome
:rtype: Alleles or SparseAlleles
"""
if (self.frequencies < 0).any():
raise ValueError('Not all frequencies are specified')
r = np.random.random(self.nmark())
r = np.array(r < self.frequencies, dtype=np.int8) + 1
if sparse:
return SparseAlleles(r - 1, refcode=0, template=self)
else:
return Alleles(r, template=self)
def test_sparsealleles_emptylike():
a = SparseAlleles([1,2,3,4])
e = a.empty_like()
assert ((not e.container.any()) and
(e.refcode == a.refcode) and
(a.nmark() == e.nmark()))
def test_sparsealleles_emptylike():
a = SparseAlleles([1,2,3,4])
e = a.empty_like()
assert (e.container == e.refcode).all()
def test_sparsealleles_emptylike():
a = SparseAlleles([1, 2, 3, 4])
e = a.empty_like()
assert ((not e.container.any()) and (e.refcode == a.refcode)
and (a.nmark() == e.nmark()))
