def test_EstimateDistances_modify_lf(self):
"""tests modifying the lf"""
def constrain_fit(lf):
lf.set_param_rule("kappa", is_constant=True)
lf.optimise(local=True)
return lf
d = EstimateDistances(self.al, HKY85(), modify_lf=constrain_fit)
d.run(show_progress=False)
result = d.get_pairwise_distances().to_dict()
d = EstimateDistances(self.al, F81())
d.run(show_progress=False)
expect = d.get_pairwise_distances().to_dict()
self.assertDistsAlmostEqual(expect, result)
def test_get_param_matrix_coords(self):
"""return correct coords for continuous-time models"""
f81 = F81()
self.assertEqual(f81.get_param_matrix_coords(), {})
self.assertTrue(
len(f81.get_param_matrix_coords(include_ref_cell=True)["ref_cell"]) == 12
)
hky85 = HKY85()
coords = hky85.get_param_matrix_coords()
self.assertEqual(set(coords), set(["kappa"]))
coords = hky85.get_param_matrix_coords(include_ref_cell=True)
self.assertEqual(set(coords), set(["kappa", "ref_cell"]))
gn = GN()
coords = gn.get_param_matrix_coords(include_ref_cell=True)
self.assertTrue(len(coords) == 12)
self.assertTrue(len(coords["ref_cell"]) == 1)
def test_to_rich_dict(self):
"""returns complete dict of attributes"""
f81 = F81().to_rich_dict()
hky85 = HKY85().to_rich_dict()
gn = GN().to_rich_dict()
