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src/c/o/cogent-1.5.3/tests/test_maths/test_unifrac/test_fast_tree.py   cogent(Download)
from cogent.util.unit_test import TestCase, main
from cogent.parse.tree import DndParser
from cogent.maths.unifrac.fast_tree import (count_envs, sum_env_dict, 
    index_envs, get_branch_lengths, index_tree, bind_to_array, 
    bind_to_parent_array, _is_parent_empty, delete_empty_parents,
            if not n.Children:
                tips.append(n._leaf_index)
        tip_distances(bl, bindings, tips)
        self.assertEqual(bl, array([5,6,6,6,6,0,0,0,0])[:,newaxis])
 
        tip_bindings = bind_to_parent_array(self.t, td)
        tips = [n._leaf_index for n in self.t.tips()]
        tip_distances(td, tip_bindings, tips)
        result = weighted_unifrac_matrix(bl, envs, tip_indices, bl_correct=True,
            tip_distances=td)
        tip_bindings = bind_to_parent_array(self.t, td)
        tips = [n._leaf_index for n in self.t.tips()]
        tip_distances(td, tip_bindings, tips)
        result = weighted_unifrac_matrix(bl, envs, tip_indices, bl_correct=True,
            tip_distances=td)

src/p/y/pycogent-HEAD/tests/test_maths/test_unifrac/test_fast_tree.py   pycogent(Download)
from cogent.util.unit_test import TestCase, main
from cogent.parse.tree import DndParser
from cogent.maths.unifrac.fast_tree import (count_envs, sum_env_dict, 
    index_envs, get_branch_lengths, index_tree, bind_to_array, 
    bind_to_parent_array, _is_parent_empty, delete_empty_parents,
            if not n.Children:
                tips.append(n._leaf_index)
        tip_distances(bl, bindings, tips)
        self.assertEqual(bl, array([5,6,6,6,6,0,0,0,0])[:,newaxis])
 
        tip_bindings = bind_to_parent_array(self.t, td)
        tips = [n._leaf_index for n in self.t.tips()]
        tip_distances(td, tip_bindings, tips)
        result = weighted_unifrac_matrix(bl, envs, tip_indices, bl_correct=True,
            tip_distances=td)
        tip_bindings = bind_to_parent_array(self.t, td)
        tips = [n._leaf_index for n in self.t.tips()]
        tip_distances(td, tip_bindings, tips)
        result = weighted_unifrac_matrix(bl, envs, tip_indices, bl_correct=True,
            tip_distances=td)