def test_deserialise_likelihood_function(self):
"""correctly deserialise data into likelihood function"""
# tests multiple alignments
data = load_aligned_seqs(
filename=os.path.join(os.getcwd(), "data", "brca1_5.paml")
)
half = len(data) // 2
aln1 = data[:half]
aln2 = data[half:]
loci_names = ["1st-half", "2nd-half"]
loci = [aln1, aln2]
tree = make_tree(tip_names=data.names)
model = get_model("HKY85")
lf = model.make_likelihood_function(tree, loci=loci_names)
lf.set_alignment(loci)
lf_rich_dict = lf.to_rich_dict()
got = deserialise_likelihood_function(lf_rich_dict)
self.assertEqual(str(lf.defn_for["mprobs"]), str(got.defn_for["mprobs"]))
self.assertEqual(
str(lf.defn_for["alignment"].assignments),
str(got.defn_for["alignment"].assignments),
)
# tests single alignment
model = get_model("HKY85")
lf = model.make_likelihood_function(tree)
lf.set_alignment(aln1)
lf_rich_dict = lf.to_rich_dict()
got = deserialise_likelihood_function(lf_rich_dict)
self.assertEqual(str(lf.defn_for["mprobs"]), str(got.defn_for["mprobs"]))
self.assertEqual(
str(lf.defn_for["alignment"].assignments),
str(got.defn_for["alignment"].assignments),
)
def lf(self):
result = list(self.values())
if type(result[0]) == dict:
from cogent3.util import deserialise
# we reset the stat attributes to None
for attr in self._stat_attrs:
setattr(self, attr, None)
for k, v in self.items():
v = deserialise.deserialise_likelihood_function(v)
self[k] = v
if len(self) == 1:
result = list(self.values())[0]
else:
result = OrderedDict()
for k in sorted(self):
v = self[k]
if type(k) == str and k.isdigit():
k = int(k)
result[k] = v
return result