def test_bimodal_open(self):
start_idx = bmutils.get_good_starting_point(self.cl, self.geom_smpl, strategy="bimodal_open")
# print(self.cl.clustercenters[start_idx])
#print(np.sort(self.cl.clustercenters.squeeze()))
assert 12 <= self.cl.clustercenters[start_idx] <= 18, "The coordinate distribution was created with pop " \
"maxima the values 1 (compact) and 15 (open)." \
" The found OPEN starting " \
"point should be in the interval [12,18] approx (see setUp)"
def test_most_pop_ordering(self):
order = np.random.permutation(np.arange(self.cl.n_clusters))
geom_smpl = [self.geom_smpl[ii] for ii in order]
start_idx = bmutils.get_good_starting_point(self.cl, geom_smpl,
cl_order=order, strategy='most_pop')
# Test might fail in some cases because it's not deterministi
# For the check to work via the clustercenter value, we have to re-order the clusters themselves
assert 12 <= self.cl.clustercenters[order][start_idx] <= 18, "The coordinate distribution was created with " \
"a max pop around the value 15. The found starting " \
"point should be in this interval (see the setUp)"
# However, for the geom_smpl object, start_idx can be used directly:
assert 12 <= geom_smpl[start_idx].xyz[:,-1,-1].mean() <= 18, "The coordinate distribution was created with " \
"a max pop around the value 15. The found starting " \
"point should be in this interval (see the setUp)"
def test_most_pop(self):
start_idx = bmutils.get_good_starting_point(self.cl, self.geom_smpl, strategy="most_pop")
#print(start_idx, self.cl.clustercenters[start_idx], np.sort(self.cl.clustercenters.squeeze()))
assert 12 <= self.cl.clustercenters[start_idx] <= 18, "The coordinate distribution was created with a max pop " \
"around the value 15. The found starting point should be" \
"in this interval (see the setUp)"
def _test_most_pop_x_rgyr(self):
start_idx = bmutils.get_good_starting_point(self.cl, self.geom_smpl, strategy="most_pop_x_smallest_Rgyr")
def test_smallest_rgyr(self):
start_idx = bmutils.get_good_starting_point(self.cl, self.geom_smpl)
# Should be the clustercenter with the smallest possible rgyr
assert self.cl.clustercenters[start_idx] == self.cl.clustercenters.squeeze().min()