def test_expr_errors(self, obj):
with pytest.raises(TypeError):
exprl2alignment(obj)
with pytest.raises(TypeError):
PairwiseAlignment(obj, Dw, Gw)
with pytest.raises(TypeError):
Alignment(obj)
def test_Alignment(filtered_peak_list):
#Alignment(Experiment("ELEY_1_SUBTRACT", filtered_peak_list))
#Alignment(None)
for obj in [test_string, *test_numbers, *test_lists, test_dict]:
with pytest.raises(TypeError):
Alignment(obj)
def merge_alignments(A1: Alignment, A2: Alignment, traces) -> Alignment:
"""
Merges two alignments with gaps added in from DP traceback.
:param A1: First alignment.
:param A2: Second alignment.
:param traces: DP traceback.
:return: A single alignment from ``A1`` and ``A2``.
:authors: Woon Wai Keen, Vladimir Likic, Qiao Wang
"""
# Create object to hold new merged alignment and fill in its expr_codes
ma = Alignment(None)
ma.expr_code = A1.expr_code + A2.expr_code
# create empty lists of dimension |A1| + |A2|
dimension = len(A1.peakpos) + len(A2.peakpos)
merged: List[List[Peak]] = [[] for _ in range(dimension)]
idx1 = idx2 = 0
# trace can either be 0, 1, or 2
# if it is 0, there are no gaps. otherwise, if it is 1 or 2,
# there is a gap in A2 or A1 respectively.
for trace in traces:
if trace in {0, 1}:
for i, _ in enumerate(A1.peakpos):
merged[i].append(A1.peakpos[i][idx1])
idx1 = idx1 + 1
elif trace == 2:
for i, _ in enumerate(A1.peakpos):
merged[i].append(None) # type: ignore
# ---
if trace in {0, 2}:
for j, peak in enumerate(A2.peakpos):
merged[1 + i + j].append(peak[idx2])
idx2 = idx2 + 1
elif trace == 1:
for j, _ in enumerate(A2.peakpos):
merged[1 + i + j].append(None) # type: ignore
ma.peakalgt = numpy.transpose(merged)
# sort according to average peak
ma.peakalgt = list(ma.peakalgt)
ma.peakalgt.sort(key=functools.cmp_to_key(alignment_compare))
ma.peakpos = numpy.transpose(ma.peakalgt)
return ma