From 23ad7ae6d93099e1a6575efac2e7500ac10833dd Mon Sep 17 00:00:00 2001 From: Daniel McDonald Date: Sun, 10 Jul 2016 20:48:56 -0600 Subject: [PATCH 01/32] PERF: more direct use of numpy --- gneiss/balances.py | 134 ++++++++++++++++++++-------------- gneiss/tests/test_balances.py | 44 ++++++----- 2 files changed, 105 insertions(+), 73 deletions(-) diff --git a/gneiss/balances.py b/gneiss/balances.py index 516575d..82cb7b1 100644 --- a/gneiss/balances.py +++ b/gneiss/balances.py @@ -10,25 +10,37 @@ def _balance_basis(tree_node): """ Helper method for calculating balance basis """ - counts, n_tips = _count_matrix(tree_node) - counts = OrderedDict([(x, counts[x]) - for x in counts.keys() if not x.is_tip()]) - nds = counts.keys() - r = np.array([counts[n]['r'] for n in nds]) - s = np.array([counts[n]['l'] for n in nds]) - k = np.array([counts[n]['k'] for n in nds]) - t = np.array([counts[n]['t'] for n in nds]) + # TODO: use recarray + # col 0 -> right counts + # col 1 -> left counts + # col 2 -> k + # col 3 -> t + r_idx = 0 + l_idx = 1 + k_idx = 2 + t_idx = 3 + + counts, n_tips, n_nodes = _count_matrix(tree_node) + r = counts[:, r_idx] + s = counts[:, l_idx] + k = counts[:, k_idx] + t = counts[:, t_idx] a = np.sqrt(s / (r*(r+s))) b = -1*np.sqrt(r / (s*(r+s))) basis = np.zeros((n_tips-1, n_tips)) - for i in range(len(nds)): - basis[i, :] = np.array([0]*k[i] + [a[i]]*r[i] + [b[i]]*s[i] + [0]*t[i]) - # Make sure that the basis is in level order - basis = basis[:, ::-1] - nds = list(nds) - return basis, nds + for i in np.arange(n_nodes - n_tips, dtype=int): + v = basis[i] + + k_i = n_tips - k[i] + r_i = k_i - r[i] + s_i = r_i - s[i] + + v[r_i:k_i] = a[i] + v[s_i:r_i] = b[i] + + return basis, [n for n in tree_node.levelorder() if not n.is_tip()] def balance_basis(tree_node): @@ -90,51 +102,63 @@ def balance_basis(tree_node): def _count_matrix(treenode): - n_tips = 0 - nodes = list(treenode.levelorder(include_self=True)) - # fill in the Ordered dictionary. Note that the - # elements of this Ordered dictionary are - # dictionaries. - counts = OrderedDict() - columns = ['k', 'r', 'l', 't', 'tips'] - for n in nodes: - if n not in counts: - counts[n] = {} - for c in columns: - counts[n][c] = 0 - - # fill in r and l. This is done in reverse level order. - for n in nodes[::-1]: + node_count = 0 + for n in treenode.postorder(include_self=True): + node_count += 1 if n.is_tip(): - counts[n]['tips'] = 1 - n_tips += 1 - elif len(n.children) == 2: - lchild = n.children[0] - rchild = n.children[1] - counts[n]['r'] = counts[rchild]['tips'] - counts[n]['l'] = counts[lchild]['tips'] - counts[n]['tips'] = counts[n]['r'] + counts[n]['l'] + n._tip_count = 1 else: - raise ValueError("Not a strictly bifurcating tree!") - - # fill in k and t - for n in nodes: - if n.parent is None: - counts[n]['k'] = 0 - counts[n]['t'] = 0 - continue - elif n.is_tip(): + try: + left, right = n.children + except: + raise ValueError("Not a strictly bifurcating tree!") + n._tip_count = left._tip_count + right._tip_count + + # TODO: use recarray + # col 0 -> right counts + # col 1 -> left counts + # col 2 -> k + # col 3 -> t + r_idx = 0 + l_idx = 1 + k_idx = 2 + t_idx = 3 + counts = np.zeros((node_count, 4), dtype=int) + + for i, n in enumerate(treenode.levelorder(include_self=True)): + if n.is_tip(): continue - # left or right child - # left = 0, right = 1 - child_idx = 'l' if n.parent.children[0] != n else 'r' - if child_idx == 'l': - counts[n]['t'] = counts[n.parent]['t'] + counts[n.parent]['l'] - counts[n]['k'] = counts[n.parent]['k'] + + n._lo_idx = i + node_counts = counts[i] + + node_counts[r_idx] = 1 if n.is_tip() else n.children[1]._tip_count + node_counts[l_idx] = 1 if n.is_tip() else n.children[0]._tip_count + + if n.is_root(): + k = 0 + t = 0 else: - counts[n]['k'] = counts[n.parent]['k'] + counts[n.parent]['r'] - counts[n]['t'] = counts[n.parent]['t'] - return counts, n_tips + parent_counts = counts[n.parent._lo_idx] + if n is n.parent.children[0]: + #t = parent_counts[t_idx] + parent_counts[l_idx] + #k = parent_counts[k_idx] + + k = parent_counts[k_idx] + parent_counts[r_idx] + t = parent_counts[t_idx] + else: + #k = parent_counts[k_idx] + parent_counts[r_idx] + #t = parent_counts[t_idx] + + k = parent_counts[k_idx] + t = parent_counts[t_idx] + parent_counts[l_idx] + + node_counts[k_idx] = k + node_counts[t_idx] = t + + counts[i] = node_counts + + return counts, treenode._tip_count, node_count def _attach_balances(balances, tree): diff --git a/gneiss/tests/test_balances.py b/gneiss/tests/test_balances.py index 59f2435..9a8ff72 100644 --- a/gneiss/tests/test_balances.py +++ b/gneiss/tests/test_balances.py @@ -48,8 +48,8 @@ def test_balanceplot(self): tree = TreeNode.read([u"((a,b)c,d)r;"]) balances = np.array([10, -10]) tr, ts = balanceplot(balances, tree) - self.assertEquals(ts.mode, 'c') - self.assertEquals(ts.layout_fn[0], default_layout) + self.assertEqual(ts.mode, 'c') + self.assertEqual(ts.layout_fn[0], default_layout) class TestBalances(unittest.TestCase): @@ -57,30 +57,31 @@ class TestBalances(unittest.TestCase): def test_count_matrix_base_case(self): tree = u"(a,b);" t = TreeNode.read([tree]) - res, _ = _count_matrix(t) - exp = {'k': 0, 'l': 1, 'r': 1, 't': 0, 'tips': 2} - self.assertEqual(res[t], exp) + res, _, _ = _count_matrix(t) - exp = {'k': 0, 'l': 0, 'r': 0, 't': 0, 'tips': 1} - self.assertEqual(res[t[0]], exp) + exp = np.array([1, 1, 0, 0]) + npt.assert_equal(res[0], exp) - exp = {'k': 0, 'l': 0, 'r': 0, 't': 0, 'tips': 1} - self.assertEqual(res[t[1]], exp) + exp = np.array([0, 0, 0, 0]) + npt.assert_equal(res[1], exp) + + exp = np.array([0, 0, 0, 0]) + npt.assert_equal(res[2], exp) def test_count_matrix_unbalanced(self): tree = u"((a,b)c, d);" t = TreeNode.read([tree]) - res, _ = _count_matrix(t) + res, _, _ = _count_matrix(t) - exp = {'k': 0, 'l': 2, 'r': 1, 't': 0, 'tips': 3} - self.assertEqual(res[t], exp) - exp = {'k': 1, 'l': 1, 'r': 1, 't': 0, 'tips': 2} - self.assertEqual(res[t[0]], exp) + exp = np.array([1, 2, 0, 0]) + npt.assert_equal(res[0], exp) + exp = np.array([1, 1, 1, 0]) + npt.assert_equal(res[1], exp) - exp = {'k': 0, 'l': 0, 'r': 0, 't': 0, 'tips': 1} - self.assertEqual(res[t[1]], exp) - self.assertEqual(res[t[0][0]], exp) - self.assertEqual(res[t[0][1]], exp) + exp = np.array([0, 0, 0, 0]) + npt.assert_equal(res[2], exp) + npt.assert_equal(res[3], exp) + npt.assert_equal(res[4], exp) def test_count_matrix_singleton_error(self): with self.assertRaises(ValueError): @@ -150,6 +151,13 @@ def test_balance_basis_large1(self): get_data_path('large_tree_basis.txt', subfolder='data')) res_basis, res_keys = balance_basis(t) + + exp_basis = exp_basis[:, ::-1] + print(exp_basis.shape) + for i in range(len(res_basis)): + print(i) + npt.assert_allclose(exp_basis[i], res_basis[i]) + npt.assert_allclose(exp_basis[:, ::-1], res_basis) From 2a5d4fecd1a9a6b4529def286598c844b980da1e Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Sat, 16 Jul 2016 12:15:20 -0700 Subject: [PATCH 02/32] Adding license --- COPYING.txt | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) create mode 100644 COPYING.txt diff --git a/COPYING.txt b/COPYING.txt new file mode 100644 index 0000000..7e868c6 --- /dev/null +++ b/COPYING.txt @@ -0,0 +1,27 @@ +Copyright (c) 2013--, gneiss development team. +All rights reserved. + +Redistribution and use in source and binary forms, with or without modification, +are permitted provided that the following conditions are met: + +* Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + +* Redistributions in binary form must reproduce the above copyright notice, this + list of conditions and the following disclaimer in the documentation and/or + other materials provided with the distribution. + +* Neither the names gneiss, or biocore nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND +ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED +WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR +ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES +(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; +LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON +ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS +SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. From b979d41e4c5dce08f6f488144bbb44d42f85755b Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Sat, 16 Jul 2016 12:22:34 -0700 Subject: [PATCH 03/32] Last touches before release --- gneiss/__init__.py | 2 +- setup.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/gneiss/__init__.py b/gneiss/__init__.py index ccb3281..6d14325 100644 --- a/gneiss/__init__.py +++ b/gneiss/__init__.py @@ -9,4 +9,4 @@ from __future__ import absolute_import, division, print_function -__version__ = "0.0.1" +__version__ = "0.0.2" diff --git a/setup.py b/setup.py index 2d9f4f7..0f081de 100644 --- a/setup.py +++ b/setup.py @@ -40,8 +40,8 @@ def finalize_options(self): Topic :: Software Development :: Libraries Topic :: Scientific/Engineering Topic :: Scientific/Engineering :: Bio-Informatics - Programming Language :: Python :: 2 - Programming Language :: Python :: 2 :: Only + Programming Language :: Python :: 3 + Programming Language :: Python :: 3 :: Only Operating System :: Unix Operating System :: POSIX Operating System :: MacOS :: MacOS X From 362fe9e470f88c9b2b84d744863885033170d126 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 18 Jul 2016 17:43:13 -0700 Subject: [PATCH 04/32] ENH: Adding util functions Correcting documentation in setup.py --- gneiss/tests/test_util.py | 241 ++++++++++++++++++++++++++++++++++++++ gneiss/util.py | 121 +++++++++++++++++++ setup.py | 2 +- 3 files changed, 363 insertions(+), 1 deletion(-) create mode 100644 gneiss/tests/test_util.py create mode 100644 gneiss/util.py diff --git a/gneiss/tests/test_util.py b/gneiss/tests/test_util.py new file mode 100644 index 0000000..df6a6ee --- /dev/null +++ b/gneiss/tests/test_util.py @@ -0,0 +1,241 @@ +import unittest +import pandas as pd +import pandas.util.testing as pdt +from skbio import TreeNode +from gneiss.util import match, match_tips, rename_tips + + +class TestUtil(unittest.TestCase): + + def test_match(self): + table = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) + metadata = pd.DataFrame([['a', 'control'], + ['b', 'control'], + ['c', 'diseased'], + ['d', 'diseased']], + index=['s1', 's2', 's3', 's4'], + columns=['Barcode', 'Treatment']) + exp_table, exp_metadata = table, metadata + res_table, res_metadata = match(table, metadata) + pdt.assert_frame_equal(exp_table, res_table) + pdt.assert_frame_equal(exp_metadata, res_metadata) + + + def test_match_scrambled(self): + table = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) + metadata = pd.DataFrame([['a', 'control'], + ['c', 'diseased'], + ['b', 'control'], + ['d', 'diseased']], + index=['s1', 's3', 's2', 's4'], + columns=['Barcode', 'Treatment']) + exp_table = table + exp_metadata = pd.DataFrame([['a', 'control'], + ['b', 'control'], + ['c', 'diseased'], + ['d', 'diseased']], + index=['s1', 's2', 's3', 's4'], + columns=['Barcode', 'Treatment']) + + res_table, res_metadata = match(table, metadata) + pdt.assert_frame_equal(exp_table, res_table) + pdt.assert_frame_equal(exp_metadata, res_metadata) + + def test_match_intersect(self): + table = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) + metadata = pd.DataFrame([['a', 'control'], + ['c', 'diseased'], + ['b', 'control']], + index=['s1', 's3', 's2'], + columns=['Barcode', 'Treatment']) + + exp_table = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3]], + index=['s1', 's2', 's3'], + columns=['o1', 'o2', 'o3', 'o4']) + + exp_metadata = pd.DataFrame([['a', 'control'], + ['b', 'control'], + ['c', 'diseased']], + index=['s1', 's2', 's3'], + columns=['Barcode', 'Treatment']) + + res_table, res_metadata = match(table, metadata, intersect=True) + pdt.assert_frame_equal(exp_table, res_table) + pdt.assert_frame_equal(exp_metadata, res_metadata) + + def test_match_mismatch(self): + table = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) + metadata = pd.DataFrame([['a', 'control'], + ['c', 'diseased'], + ['b', 'control']], + index=['s1', 's3', 's2'], + columns=['Barcode', 'Treatment']) + + exp_table = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3]], + index=['s1', 's2', 's3'], + columns=['o1', 'o2', 'o3', 'o4']) + + exp_metadata = pd.DataFrame([['a', 'control'], + ['b', 'control'], + ['c', 'diseased']], + index=['s1', 's2', 's3'], + columns=['Barcode', 'Treatment']) + with self.assertRaises(ValueError): + match(table, metadata) + + def test_match_tips(self): + table = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['a', 'b', 'c', 'd']) + tree = TreeNode.read([u"(((a,b)f, c),d)r;"]) + exp_table, exp_tree = table, tree + res_table, res_tree = match_tips(table, tree) + pdt.assert_frame_equal(exp_table, res_table) + self.assertEqual(str(exp_tree), str(res_tree)) + + def test_match_tips_scrambled_tips(self): + table = pd.DataFrame([[0, 0, 1, 1], + [2, 3, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['a', 'b', 'c', 'd']) + tree = TreeNode.read([u"(((b,a)f, c),d)r;"]) + exp_tree = tree + exp_table = pd.DataFrame([[0, 0, 1, 1], + [3, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['b', 'a', 'c', 'd']) + + res_table, res_tree = match_tips(table, tree) + pdt.assert_frame_equal(exp_table, res_table) + self.assertEqual(str(exp_tree), str(res_tree)) + + def test_match_tips_scrambled_columns(self): + table = pd.DataFrame([[0, 0, 1, 1], + [3, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['b', 'a', 'c', 'd']) + tree = TreeNode.read([u"(((a,b)f, c),d)r;"]) + exp_tree = tree + exp_table = pd.DataFrame([[0, 0, 1, 1], + [2, 3, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['a', 'b', 'c', 'd']) + + res_table, res_tree = match_tips(table, tree) + pdt.assert_frame_equal(exp_table, res_table) + self.assertEqual(str(exp_tree), str(res_tree)) + + + def test_match_tips_intersect_tips(self): + # there are less tree tips than table columns + table = pd.DataFrame([[0, 0, 1, 1], + [2, 3, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['a', 'b', 'c', 'd']) + tree = TreeNode.read([u"((a,b)f,d)r;"]) + exp_table = pd.DataFrame([[0, 0, 1], + [2, 3, 4], + [5, 5, 3], + [0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['a', 'b', 'd']) + exp_tree = tree + res_table, res_tree = match_tips(table, tree, intersect=True) + pdt.assert_frame_equal(exp_table, res_table) + self.assertEqual(str(exp_tree), str(res_tree)) + + def test_match_tips_intersect_columns(self): + # table has less columns than tree tips + table = pd.DataFrame([[0, 0, 1], + [2, 3, 4], + [5, 5, 3], + [0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['a', 'b', 'd']) + tree = TreeNode.read([u"(((a,b)f, c),d)r;"]) + exp_table = pd.DataFrame([[1, 0, 0], + [4, 2, 3], + [3, 5, 5], + [1, 0, 0]], + index=['s1', 's2', 's3', 's4'], + columns=['d', 'a', 'b']) + exp_tree = TreeNode.read([u"(d,(a,b)f)r;"]) + res_table, res_tree = match_tips(table, tree, intersect=True) + pdt.assert_frame_equal(exp_table, res_table) + self.assertEqual(str(exp_tree), str(res_tree)) + + def test_match_tips_mismatch(self): + # table has less columns than tree tips + table = pd.DataFrame([[0, 0, 1], + [2, 3, 4], + [5, 5, 3], + [0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['a', 'b', 'd']) + tree = TreeNode.read([u"(((a,b)f, c),d)r;"]) + with self.assertRaises(ValueError): + match_tips(table, tree) + + table = pd.DataFrame([[0, 0, 1, 1], + [2, 3, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['a', 'b', 'c', 'd']) + tree = TreeNode.read([u"((a,b)f,d)r;"]) + with self.assertRaises(ValueError): + match_tips(table, tree) + + + def test_rename_tips(self): + tree = TreeNode.read([u"(((a,b), c),d)r;"]) + exp_tree = TreeNode.read([u"(((a,b)y2, c)y1,d)y0;"]) + res_tree = rename_tips(tree) + self.assertEqual(str(exp_tree), str(res_tree)) + + + def test_rename_tips_names(self): + tree = TreeNode.read([u"(((a,b), c),d)r;"]) + exp_tree = TreeNode.read([u"(((a,b)ab, c)abc,d)r;"]) + res_tree = rename_tips(tree, ['r', 'abc', 'ab']) + self.assertEqual(str(exp_tree), str(res_tree)) + +if __name__ == '__main__': + unittest.main() diff --git a/gneiss/util.py b/gneiss/util.py new file mode 100644 index 0000000..77cb390 --- /dev/null +++ b/gneiss/util.py @@ -0,0 +1,121 @@ +import pandas as pd +import numpy as np + + +def match(x, y, intersect=False): + """ Sorts samples in metadata and contingency table in the same order. + + Parameters + ---------- + x : pd.DataFrame + Contingency table where samples correspond to rows and + features correspond to columns. + y: pd.DataFrame + Metadata table where samples correspond to rows and + explanatory metadata variables correspond to columns. + intersect : bool, optional + Specifies if only the intersection of samples in the + contingency table and the metadata table will returned. + + Returns + ------- + _x : pd.DataFrame + Filtered dataframe + _y : pd.DataFrame + Filtered dataframe + """ + _x = x.sort_index() + _y = y.sort_index() + if intersect: + idx = set(_x.index) & set(_y.index) + idx = sorted(idx) + return _x.loc[idx], _y.loc[idx] + else: + if len(_x.index) != len(_y.index): + raise ValueError("`x` and `y` have incompatible sizes, " + "`x` has %d rows, `y` has %d rows. " + "Consider setting `intersect=True`." % + (len(_x.index), len(_y.index))) + return _x, _y + + +def match_tips(table, tree, intersect=False): + """ Returns the OTU table and tree with matched tips. + + Sorts the columns of the OTU table to match the tips in + the tree. If the tree is multi-furcating, then the + tree is reduced to a bifurcating tree by randomly inserting + internal nodes. + + + Parameters + ---------- + table : pd.DataFrame + Contingency table where samples correspond to rows and + features correspond to columns. + tree : skbio.TreeNode + Tree object where the leafs correspond to the features. + intersect : bool, optional + Specifies if only the intersection of samples in the + contingency table and the tree will returned. + + Returns + ------- + pd.DataFrame : + Subset of the original contingency table with the common features. + skbio.TreeNode : + Sub-tree with the common features. + """ + tips = [x.name for x in tree.tips()] + common_tips = list(set(tips) & set(table.columns)) + + if intersect: + _table = table.loc[:, common_tips] + _tree = tree.shear(names=common_tips) + else: + if len(tips) != len(table.columns): + raise ValueError("`table` and `tree` have incompatible sizes, " + "`table` has %d columns, `tree` has %d tips. " + "Consider setting `intersect=True`." % + (len(table.columns), len(tips))) + + _table = table + _tree = tree + + _tree.bifurcate() + _tree.prune() + sorted_features = [n.name for n in _tree.tips()] + _table = _table.reindex_axis(sorted_features, axis=1) + return _table, _tree + + +def rename_tips(tree, names=None): + """ Names the tree tips according to level ordering. + + The tree will be traversed from top-down, left to right. + If there `names` is not specified, the node with the smallest label (y0) + will be located at the root of the tree, and the node with the largest + label will be located at bottom right corner of the tree. + + Parameters + ---------- + tree : skbio.TreeNode + Tree object where the leafs correspond to the features. + names : list, optional + List of labels to rename the tip names. It is assumed that the + names are listed in level ordering. + + Returns + ------- + skbio.TreeNode + Tree with renamed internal nodes. + """ + i = 0 + for n in tree.levelorder(): + if not n.is_tip(): + if names is None: + n.name = 'y%i' % i + else: + n.name = names[i] + i+=1 + return tree diff --git a/setup.py b/setup.py index 0f081de..28a305e 100644 --- a/setup.py +++ b/setup.py @@ -35,7 +35,7 @@ def finalize_options(self): extensions = cythonize(extensions) classes = """ - Development Status :: 0 - pre-alpha + Development Status :: 2 - Pre-Alpha License :: OSI Approved :: BSD License Topic :: Software Development :: Libraries Topic :: Scientific/Engineering From a1b9cefd516537c97cb4c2e1ff6ccd1aa219efcb Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 18 Jul 2016 17:45:16 -0700 Subject: [PATCH 05/32] STY: pep8 --- gneiss/tests/test_util.py | 36 ++++++++++++++++-------------------- gneiss/util.py | 2 +- 2 files changed, 17 insertions(+), 21 deletions(-) diff --git a/gneiss/tests/test_util.py b/gneiss/tests/test_util.py index df6a6ee..542805b 100644 --- a/gneiss/tests/test_util.py +++ b/gneiss/tests/test_util.py @@ -25,7 +25,6 @@ def test_match(self): pdt.assert_frame_equal(exp_table, res_table) pdt.assert_frame_equal(exp_metadata, res_metadata) - def test_match_scrambled(self): table = pd.DataFrame([[0, 0, 1, 1], [2, 2, 4, 4], @@ -40,12 +39,12 @@ def test_match_scrambled(self): index=['s1', 's3', 's2', 's4'], columns=['Barcode', 'Treatment']) exp_table = table - exp_metadata = pd.DataFrame([['a', 'control'], - ['b', 'control'], - ['c', 'diseased'], - ['d', 'diseased']], - index=['s1', 's2', 's3', 's4'], - columns=['Barcode', 'Treatment']) + exp_metadata = pd.DataFrame([['a', 'control'], + ['b', 'control'], + ['c', 'diseased'], + ['d', 'diseased']], + index=['s1', 's2', 's3', 's4'], + columns=['Barcode', 'Treatment']) res_table, res_metadata = match(table, metadata) pdt.assert_frame_equal(exp_table, res_table) @@ -70,11 +69,11 @@ def test_match_intersect(self): index=['s1', 's2', 's3'], columns=['o1', 'o2', 'o3', 'o4']) - exp_metadata = pd.DataFrame([['a', 'control'], - ['b', 'control'], - ['c', 'diseased']], - index=['s1', 's2', 's3'], - columns=['Barcode', 'Treatment']) + exp_metadata = pd.DataFrame([['a', 'control'], + ['b', 'control'], + ['c', 'diseased']], + index=['s1', 's2', 's3'], + columns=['Barcode', 'Treatment']) res_table, res_metadata = match(table, metadata, intersect=True) pdt.assert_frame_equal(exp_table, res_table) @@ -99,11 +98,11 @@ def test_match_mismatch(self): index=['s1', 's2', 's3'], columns=['o1', 'o2', 'o3', 'o4']) - exp_metadata = pd.DataFrame([['a', 'control'], - ['b', 'control'], - ['c', 'diseased']], - index=['s1', 's2', 's3'], - columns=['Barcode', 'Treatment']) + exp_metadata = pd.DataFrame([['a', 'control'], + ['b', 'control'], + ['c', 'diseased']], + index=['s1', 's2', 's3'], + columns=['Barcode', 'Treatment']) with self.assertRaises(ValueError): match(table, metadata) @@ -160,7 +159,6 @@ def test_match_tips_scrambled_columns(self): pdt.assert_frame_equal(exp_table, res_table) self.assertEqual(str(exp_tree), str(res_tree)) - def test_match_tips_intersect_tips(self): # there are less tree tips than table columns table = pd.DataFrame([[0, 0, 1, 1], @@ -223,14 +221,12 @@ def test_match_tips_mismatch(self): with self.assertRaises(ValueError): match_tips(table, tree) - def test_rename_tips(self): tree = TreeNode.read([u"(((a,b), c),d)r;"]) exp_tree = TreeNode.read([u"(((a,b)y2, c)y1,d)y0;"]) res_tree = rename_tips(tree) self.assertEqual(str(exp_tree), str(res_tree)) - def test_rename_tips_names(self): tree = TreeNode.read([u"(((a,b), c),d)r;"]) exp_tree = TreeNode.read([u"(((a,b)ab, c)abc,d)r;"]) diff --git a/gneiss/util.py b/gneiss/util.py index 77cb390..c9ee63f 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -117,5 +117,5 @@ def rename_tips(tree, names=None): n.name = 'y%i' % i else: n.name = names[i] - i+=1 + i += 1 return tree From 2908c93714b75171ebbf9a9ee2f30f36bbd052d2 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 18 Jul 2016 17:48:14 -0700 Subject: [PATCH 06/32] STY: Flake8 to the rescue --- gneiss/tests/test_util.py | 12 ------------ gneiss/util.py | 4 ---- 2 files changed, 16 deletions(-) diff --git a/gneiss/tests/test_util.py b/gneiss/tests/test_util.py index 542805b..4db5eba 100644 --- a/gneiss/tests/test_util.py +++ b/gneiss/tests/test_util.py @@ -91,18 +91,6 @@ def test_match_mismatch(self): ['b', 'control']], index=['s1', 's3', 's2'], columns=['Barcode', 'Treatment']) - - exp_table = pd.DataFrame([[0, 0, 1, 1], - [2, 2, 4, 4], - [5, 5, 3, 3]], - index=['s1', 's2', 's3'], - columns=['o1', 'o2', 'o3', 'o4']) - - exp_metadata = pd.DataFrame([['a', 'control'], - ['b', 'control'], - ['c', 'diseased']], - index=['s1', 's2', 's3'], - columns=['Barcode', 'Treatment']) with self.assertRaises(ValueError): match(table, metadata) diff --git a/gneiss/util.py b/gneiss/util.py index c9ee63f..bda70d5 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -1,7 +1,3 @@ -import pandas as pd -import numpy as np - - def match(x, y, intersect=False): """ Sorts samples in metadata and contingency table in the same order. From e2e2e635ed43420020f7af799a85af7d111a2418 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Tue, 19 Jul 2016 10:13:23 -0700 Subject: [PATCH 07/32] STY: Addressing @antgonza and @josenavas comments Adding tests for duplicate ids, updating documentation. Adding headers for copyright --- gneiss/balances.py | 8 ++++ gneiss/layouts.py | 8 ++++ gneiss/tests/test_balances.py | 8 ++++ gneiss/tests/test_util.py | 46 +++++++++++++++++++ gneiss/util.py | 86 +++++++++++++++++++++++++---------- 5 files changed, 132 insertions(+), 24 deletions(-) diff --git a/gneiss/balances.py b/gneiss/balances.py index 516575d..3f44749 100644 --- a/gneiss/balances.py +++ b/gneiss/balances.py @@ -1,3 +1,11 @@ +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the Modified BSD License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- + from __future__ import division import numpy as np import pandas as pd diff --git a/gneiss/layouts.py b/gneiss/layouts.py index 56d88ad..a831cba 100644 --- a/gneiss/layouts.py +++ b/gneiss/layouts.py @@ -1,3 +1,11 @@ +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the Modified BSD License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- + from ete3 import faces, AttrFace, CircleFace, BarChartFace diff --git a/gneiss/tests/test_balances.py b/gneiss/tests/test_balances.py index 59f2435..3af8262 100644 --- a/gneiss/tests/test_balances.py +++ b/gneiss/tests/test_balances.py @@ -1,3 +1,11 @@ +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the Modified BSD License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- + from __future__ import absolute_import, division, print_function import unittest import numpy as np diff --git a/gneiss/tests/test_util.py b/gneiss/tests/test_util.py index 4db5eba..597651a 100644 --- a/gneiss/tests/test_util.py +++ b/gneiss/tests/test_util.py @@ -1,3 +1,11 @@ +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the Modified BSD License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- + import unittest import pandas as pd import pandas.util.testing as pdt @@ -25,6 +33,38 @@ def test_match(self): pdt.assert_frame_equal(exp_table, res_table) pdt.assert_frame_equal(exp_metadata, res_metadata) + def test_match_duplicate(self): + table1 = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s2', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) + metadata1 = pd.DataFrame([['a', 'control'], + ['b', 'control'], + ['c', 'diseased'], + ['d', 'diseased']], + index=['s1', 's2', 's3', 's4'], + columns=['Barcode', 'Treatment']) + + table2 = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) + metadata2 = pd.DataFrame([['a', 'control'], + ['b', 'control'], + ['c', 'diseased'], + ['d', 'diseased']], + index=['s1', 's1', 's3', 's4'], + columns=['Barcode', 'Treatment']) + + with self.assertRaises(ValueError): + match(table1, metadata1) + with self.assertRaises(ValueError): + match(table2, metadata2) + def test_match_scrambled(self): table = pd.DataFrame([[0, 0, 1, 1], [2, 2, 4, 4], @@ -221,5 +261,11 @@ def test_rename_tips_names(self): res_tree = rename_tips(tree, ['r', 'abc', 'ab']) self.assertEqual(str(exp_tree), str(res_tree)) + def test_rename_tips_names_mismatch(self): + tree = TreeNode.read([u"(((a,b), c),d)r;"]) + exp_tree = TreeNode.read([u"(((a,b)ab, c)abc,d)r;"]) + with self.assertRaises(IndexError): + rename_tips(tree, ['r', 'abc']) + if __name__ == '__main__': unittest.main() diff --git a/gneiss/util.py b/gneiss/util.py index bda70d5..fed5e20 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -1,48 +1,74 @@ -def match(x, y, intersect=False): +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the Modified BSD License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- + +def match(table, metadata, intersect=False): """ Sorts samples in metadata and contingency table in the same order. Parameters ---------- - x : pd.DataFrame + table : pd.DataFrame Contingency table where samples correspond to rows and features correspond to columns. - y: pd.DataFrame + metadata: pd.DataFrame Metadata table where samples correspond to rows and explanatory metadata variables correspond to columns. intersect : bool, optional Specifies if only the intersection of samples in the contingency table and the metadata table will returned. + By default, this is False. Returns ------- - _x : pd.DataFrame - Filtered dataframe - _y : pd.DataFrame - Filtered dataframe + pd.DataFrame : + Filtered contingency table. + pd.DataFrame : + Filtered metadata table + + Raises + ------ + ValueError: + Raised if duplicate sample ids are present in `table`. + ValueError: + Raised if duplicate sample ids are present in `metadata`. + ValueError: + Raised if `table` and `metadata` have incompatible sizes. """ - _x = x.sort_index() - _y = y.sort_index() + subtableids = set(table.index) + submetadataids = set(metadata.index) + if len(subtableids) != len(table.index): + raise ValueError("`table` has duplicate sample ids.") + if len(submetadataids) != len(metadata.index): + raise ValueError("`metadata` has duplicate sample ids.") + if intersect: - idx = set(_x.index) & set(_y.index) + idx = subtableids & submetadataids idx = sorted(idx) - return _x.loc[idx], _y.loc[idx] + return table.loc[idx], metadata.loc[idx] else: - if len(_x.index) != len(_y.index): - raise ValueError("`x` and `y` have incompatible sizes, " - "`x` has %d rows, `y` has %d rows. " + subtable = table.sort_index() + submetadata = metadata.sort_index() + + if len(subtable.index) != len(submetadata.index): + raise ValueError("`table` and `metadata` have incompatible sizes, " + "`table` has %d rows, `metadata` has %d rows. " "Consider setting `intersect=True`." % - (len(_x.index), len(_y.index))) - return _x, _y + (len(subtable.index), len(submetadata.index))) + return subtable, submetadata def match_tips(table, tree, intersect=False): - """ Returns the OTU table and tree with matched tips. + """ Returns the contingency table and tree with matched tips. - Sorts the columns of the OTU table to match the tips in - the tree. If the tree is multi-furcating, then the - tree is reduced to a bifurcating tree by randomly inserting - internal nodes. + Sorts the columns of the contingency table to match the tips in + the tree. The ordering of the tips is in post-traversal order. + If the tree is multi-furcating, then the tree is reduced to a + bifurcating tree by randomly inserting internal nodes. Parameters ---------- @@ -54,6 +80,7 @@ def match_tips(table, tree, intersect=False): intersect : bool, optional Specifies if only the intersection of samples in the contingency table and the tree will returned. + By default, this is False. Returns ------- @@ -61,6 +88,16 @@ def match_tips(table, tree, intersect=False): Subset of the original contingency table with the common features. skbio.TreeNode : Sub-tree with the common features. + + Raises + ------ + ValueError: + Raised if `table` and `tree` have incompatible sizes. + + See Also + -------- + skbio.TreeNode.bifurcate + skbio.TreeNode.tips """ tips = [x.name for x in tree.tips()] common_tips = list(set(tips) & set(table.columns)) @@ -88,8 +125,8 @@ def match_tips(table, tree, intersect=False): def rename_tips(tree, names=None): """ Names the tree tips according to level ordering. - The tree will be traversed from top-down, left to right. - If there `names` is not specified, the node with the smallest label (y0) + The tree will be traversed in level order (i.e. top-down, left to right). + If `names` is not specified, the node with the smallest label (y0) will be located at the root of the tree, and the node with the largest label will be located at bottom right corner of the tree. @@ -99,7 +136,8 @@ def rename_tips(tree, names=None): Tree object where the leafs correspond to the features. names : list, optional List of labels to rename the tip names. It is assumed that the - names are listed in level ordering. + names are listed in level ordering, and the length of the list + is at least as long as the number of internal nodes. Returns ------- From d6a037b3addde15ae19176ff10f8edd799adedc4 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Tue, 19 Jul 2016 10:15:27 -0700 Subject: [PATCH 08/32] STY: pep8 flake8 --- gneiss/tests/test_util.py | 17 ++++++++--------- gneiss/util.py | 3 ++- 2 files changed, 10 insertions(+), 10 deletions(-) diff --git a/gneiss/tests/test_util.py b/gneiss/tests/test_util.py index 597651a..08da7e6 100644 --- a/gneiss/tests/test_util.py +++ b/gneiss/tests/test_util.py @@ -38,27 +38,27 @@ def test_match_duplicate(self): [2, 2, 4, 4], [5, 5, 3, 3], [0, 0, 0, 1]], - index=['s2', 's2', 's3', 's4'], - columns=['o1', 'o2', 'o3', 'o4']) + index=['s2', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) metadata1 = pd.DataFrame([['a', 'control'], ['b', 'control'], ['c', 'diseased'], ['d', 'diseased']], - index=['s1', 's2', 's3', 's4'], - columns=['Barcode', 'Treatment']) + index=['s1', 's2', 's3', 's4'], + columns=['Barcode', 'Treatment']) table2 = pd.DataFrame([[0, 0, 1, 1], [2, 2, 4, 4], [5, 5, 3, 3], [0, 0, 0, 1]], - index=['s1', 's2', 's3', 's4'], - columns=['o1', 'o2', 'o3', 'o4']) + index=['s1', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) metadata2 = pd.DataFrame([['a', 'control'], ['b', 'control'], ['c', 'diseased'], ['d', 'diseased']], - index=['s1', 's1', 's3', 's4'], - columns=['Barcode', 'Treatment']) + index=['s1', 's1', 's3', 's4'], + columns=['Barcode', 'Treatment']) with self.assertRaises(ValueError): match(table1, metadata1) @@ -263,7 +263,6 @@ def test_rename_tips_names(self): def test_rename_tips_names_mismatch(self): tree = TreeNode.read([u"(((a,b), c),d)r;"]) - exp_tree = TreeNode.read([u"(((a,b)ab, c)abc,d)r;"]) with self.assertRaises(IndexError): rename_tips(tree, ['r', 'abc']) diff --git a/gneiss/util.py b/gneiss/util.py index fed5e20..85a2106 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -6,6 +6,7 @@ # The full license is in the file COPYING.txt, distributed with this software. # ---------------------------------------------------------------------------- + def match(table, metadata, intersect=False): """ Sorts samples in metadata and contingency table in the same order. @@ -46,7 +47,7 @@ def match(table, metadata, intersect=False): raise ValueError("`metadata` has duplicate sample ids.") if intersect: - idx = subtableids & submetadataids + idx = subtableids & submetadataids idx = sorted(idx) return table.loc[idx], metadata.loc[idx] else: From 38b64c856f6e186f67cb1aa0854dcdb44dc9d801 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Tue, 19 Jul 2016 10:29:48 -0700 Subject: [PATCH 09/32] GPL license --- COPYING.txt | 701 ++++++++++++++++++++++++++++++++-- gneiss/__init__.py | 2 +- gneiss/balances.py | 8 + gneiss/layouts.py | 8 + gneiss/tests/test_balances.py | 8 + 5 files changed, 699 insertions(+), 28 deletions(-) diff --git a/COPYING.txt b/COPYING.txt index 7e868c6..94a9ed0 100644 --- a/COPYING.txt +++ b/COPYING.txt @@ -1,27 +1,674 @@ -Copyright (c) 2013--, gneiss development team. -All rights reserved. - -Redistribution and use in source and binary forms, with or without modification, -are permitted provided that the following conditions are met: - -* Redistributions of source code must retain the above copyright notice, this - list of conditions and the following disclaimer. - -* Redistributions in binary form must reproduce the above copyright notice, this - list of conditions and the following disclaimer in the documentation and/or - other materials provided with the distribution. - -* Neither the names gneiss, or biocore nor the names of its - contributors may be used to endorse or promote products derived from - this software without specific prior written permission. - -THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND -ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED -WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE -DISCLAIMED. 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But first, please read +. diff --git a/gneiss/__init__.py b/gneiss/__init__.py index 6d14325..a27c03f 100644 --- a/gneiss/__init__.py +++ b/gneiss/__init__.py @@ -1,7 +1,7 @@ # ---------------------------------------------------------------------------- # Copyright (c) 2016--, gneiss development team. # -# Distributed under the terms of the Modified BSD License. +# Distributed under the terms of the GPLv3 License. # # The full license is in the file COPYING.txt, distributed with this software. # ---------------------------------------------------------------------------- diff --git a/gneiss/balances.py b/gneiss/balances.py index 516575d..db0fd6f 100644 --- a/gneiss/balances.py +++ b/gneiss/balances.py @@ -1,3 +1,11 @@ +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the GPLv3 License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- + from __future__ import division import numpy as np import pandas as pd diff --git a/gneiss/layouts.py b/gneiss/layouts.py index 56d88ad..a831cba 100644 --- a/gneiss/layouts.py +++ b/gneiss/layouts.py @@ -1,3 +1,11 @@ +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the Modified BSD License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- + from ete3 import faces, AttrFace, CircleFace, BarChartFace diff --git a/gneiss/tests/test_balances.py b/gneiss/tests/test_balances.py index 59f2435..3af8262 100644 --- a/gneiss/tests/test_balances.py +++ b/gneiss/tests/test_balances.py @@ -1,3 +1,11 @@ +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the Modified BSD License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- + from __future__ import absolute_import, division, print_function import unittest import numpy as np From 1cbc6adb535963d9f2196aa0f20c9be742eb06ff Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Tue, 19 Jul 2016 10:41:20 -0700 Subject: [PATCH 10/32] Adding changelog --- CHANGELOG.md | 8 ++++++++ 1 file changed, 8 insertions(+) create mode 100644 CHANGELOG.md diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..27164b8 --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,8 @@ +# gneiss changelog + +## Version 0.0.2 (changes since 0.0.2 go here) + +### Features +* Adding GPL license. + +### Bug fixes From d19760519392180a31a34c6875458e1765d98d18 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Tue, 19 Jul 2016 15:43:46 -0700 Subject: [PATCH 11/32] DOC: Changing method name Adding some mutability tests Adding warning about replacing internal node names --- gneiss/tests/test_util.py | 71 ++++++++++++++++++++++++++++++++++----- gneiss/util.py | 31 +++++++++++++---- 2 files changed, 86 insertions(+), 16 deletions(-) diff --git a/gneiss/tests/test_util.py b/gneiss/tests/test_util.py index 08da7e6..1255de1 100644 --- a/gneiss/tests/test_util.py +++ b/gneiss/tests/test_util.py @@ -1,7 +1,7 @@ # ---------------------------------------------------------------------------- # Copyright (c) 2016--, gneiss development team. # -# Distributed under the terms of the Modified BSD License. +# Distributed under the terms of the GPLv3 License. # # The full license is in the file COPYING.txt, distributed with this software. # ---------------------------------------------------------------------------- @@ -10,7 +10,7 @@ import pandas as pd import pandas.util.testing as pdt from skbio import TreeNode -from gneiss.util import match, match_tips, rename_tips +from gneiss.util import match, match_tips, rename_internal_nodes class TestUtil(unittest.TestCase): @@ -33,6 +33,35 @@ def test_match(self): pdt.assert_frame_equal(exp_table, res_table) pdt.assert_frame_equal(exp_metadata, res_metadata) + def test_match_immutable(self): + # tests to make sure that the original tables don't change. + table = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) + metadata = pd.DataFrame([['a', 'control'], + ['c', 'diseased'], + ['b', 'control']], + index=['s1', 's3', 's2'], + columns=['Barcode', 'Treatment']) + + exp_table = pd.DataFrame([[0, 0, 1, 1], + [2, 2, 4, 4], + [5, 5, 3, 3], + [0, 0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['o1', 'o2', 'o3', 'o4']) + exp_metadata = pd.DataFrame([['a', 'control'], + ['c', 'diseased'], + ['b', 'control']], + index=['s1', 's3', 's2'], + columns=['Barcode', 'Treatment']) + match(table, metadata, intersect=True) + pdt.assert_frame_equal(table, exp_table) + pdt.assert_frame_equal(metadata, exp_metadata) + def test_match_duplicate(self): table1 = pd.DataFrame([[0, 0, 1, 1], [2, 2, 4, 4], @@ -227,6 +256,19 @@ def test_match_tips_intersect_columns(self): pdt.assert_frame_equal(exp_table, res_table) self.assertEqual(str(exp_tree), str(res_tree)) + def test_match_tips_intersect_tree_immutable(self): + # tests to see if tree chnages. + table = pd.DataFrame([[0, 0, 1], + [2, 3, 4], + [5, 5, 3], + [0, 0, 1]], + index=['s1', 's2', 's3', 's4'], + columns=['a', 'b', 'd']) + tree = TreeNode.read([u"(((a,b)f, c),d)r;"]) + match_tips(table, tree, intersect=True) + self.assertEqual(str(tree), u"(((a,b)f,c),d)r;\n") + + def test_match_tips_mismatch(self): # table has less columns than tree tips table = pd.DataFrame([[0, 0, 1], @@ -249,22 +291,33 @@ def test_match_tips_mismatch(self): with self.assertRaises(ValueError): match_tips(table, tree) - def test_rename_tips(self): + def test_rename_internal_nodes(self): tree = TreeNode.read([u"(((a,b), c),d)r;"]) exp_tree = TreeNode.read([u"(((a,b)y2, c)y1,d)y0;"]) - res_tree = rename_tips(tree) + res_tree = rename_internal_nodes(tree) self.assertEqual(str(exp_tree), str(res_tree)) - def test_rename_tips_names(self): + def test_rename_internal_nodes_names(self): tree = TreeNode.read([u"(((a,b), c),d)r;"]) exp_tree = TreeNode.read([u"(((a,b)ab, c)abc,d)r;"]) - res_tree = rename_tips(tree, ['r', 'abc', 'ab']) + res_tree = rename_internal_nodes(tree, ['r', 'abc', 'ab']) self.assertEqual(str(exp_tree), str(res_tree)) - def test_rename_tips_names_mismatch(self): + def test_rename_internal_nodes_names_mismatch(self): tree = TreeNode.read([u"(((a,b), c),d)r;"]) - with self.assertRaises(IndexError): - rename_tips(tree, ['r', 'abc']) + with self.assertRaises(ValueError): + rename_internal_nodes(tree, ['r', 'abc']) + + def test_rename_internal_nodes(self): + tree = TreeNode.read([u"(((a,b)y2, c),d)r;"]) + with self.assertWarns(Warning): + rename_internal_nodes(tree) + + def test_rename_internal_nodes_immutable(self): + tree = TreeNode.read([u"(((a,b)y2, c),d)r;"]) + rename_internal_nodes(tree) + self.assertEqual(str(tree), "(((a,b)y2,c),d)r;\n") + if __name__ == '__main__': unittest.main() diff --git a/gneiss/util.py b/gneiss/util.py index 85a2106..5674aa1 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -1,10 +1,12 @@ # ---------------------------------------------------------------------------- # Copyright (c) 2016--, gneiss development team. # -# Distributed under the terms of the Modified BSD License. +# Distributed under the terms of the GPLv3 License. # # The full license is in the file COPYING.txt, distributed with this software. # ---------------------------------------------------------------------------- +import warnings +import copy def match(table, metadata, intersect=False): @@ -123,8 +125,8 @@ def match_tips(table, tree, intersect=False): return _table, _tree -def rename_tips(tree, names=None): - """ Names the tree tips according to level ordering. +def rename_internal_nodes(tree, names=None): + """ Names the internal according to level ordering. The tree will be traversed in level order (i.e. top-down, left to right). If `names` is not specified, the node with the smallest label (y0) @@ -144,13 +146,28 @@ def rename_tips(tree, names=None): ------- skbio.TreeNode Tree with renamed internal nodes. + + ValueError: + Raised if `tree` and `name` have incompatible sizes. """ + _tree = tree.copy() + non_tips = [n for n in _tree.levelorder() if not n.is_tip()] + if not names is None and len(non_tips) != len(names): + raise ValueError("`_tree` and `names` have incompatible sizes, " + "`_tree` has %d tips, `names` has %d elements." % + (len(non_tips), len(names))) + i = 0 - for n in tree.levelorder(): + for n in _tree.levelorder(): if not n.is_tip(): if names is None: - n.name = 'y%i' % i + label = 'y%i' % i else: - n.name = names[i] + label = names[i] + if not n.name is None and label == n.name: + warnings.warn("Warning. Internal node (%s) has been replaced " + "with (%s)" % (n.name, label)) + + n.name = label i += 1 - return tree + return _tree From 2ded931959028e69ef3f19e9b30ac6b9fc75c524 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Tue, 19 Jul 2016 15:45:58 -0700 Subject: [PATCH 12/32] STY: clean up pep8/flake8 --- gneiss/tests/test_util.py | 3 +-- gneiss/util.py | 4 ++-- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/gneiss/tests/test_util.py b/gneiss/tests/test_util.py index 1255de1..ce815fe 100644 --- a/gneiss/tests/test_util.py +++ b/gneiss/tests/test_util.py @@ -268,7 +268,6 @@ def test_match_tips_intersect_tree_immutable(self): match_tips(table, tree, intersect=True) self.assertEqual(str(tree), u"(((a,b)f,c),d)r;\n") - def test_match_tips_mismatch(self): # table has less columns than tree tips table = pd.DataFrame([[0, 0, 1], @@ -308,7 +307,7 @@ def test_rename_internal_nodes_names_mismatch(self): with self.assertRaises(ValueError): rename_internal_nodes(tree, ['r', 'abc']) - def test_rename_internal_nodes(self): + def test_rename_internal_nodes_warning(self): tree = TreeNode.read([u"(((a,b)y2, c),d)r;"]) with self.assertWarns(Warning): rename_internal_nodes(tree) diff --git a/gneiss/util.py b/gneiss/util.py index 5674aa1..4aabb3c 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -152,7 +152,7 @@ def rename_internal_nodes(tree, names=None): """ _tree = tree.copy() non_tips = [n for n in _tree.levelorder() if not n.is_tip()] - if not names is None and len(non_tips) != len(names): + if names is not None and len(non_tips) != len(names): raise ValueError("`_tree` and `names` have incompatible sizes, " "`_tree` has %d tips, `names` has %d elements." % (len(non_tips), len(names))) @@ -164,7 +164,7 @@ def rename_internal_nodes(tree, names=None): label = 'y%i' % i else: label = names[i] - if not n.name is None and label == n.name: + if n.name is not None and label == n.name: warnings.warn("Warning. Internal node (%s) has been replaced " "with (%s)" % (n.name, label)) From 477d1967bb7ee99eb0d4d40d5225e0a62951388a Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Wed, 20 Jul 2016 10:21:08 -0700 Subject: [PATCH 13/32] DOC: Updating changelog --- CHANGELOG.md | 1 + gneiss/util.py | 1 - 2 files changed, 1 insertion(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 27164b8..08e45ee 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,7 @@ ## Version 0.0.2 (changes since 0.0.2 go here) ### Features +* Adding in utility functions for handing feature tables, metadata, and trees. [#12](https://github.com/biocore/gneiss/pull/12) * Adding GPL license. ### Bug fixes diff --git a/gneiss/util.py b/gneiss/util.py index 4aabb3c..47d1aa3 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -6,7 +6,6 @@ # The full license is in the file COPYING.txt, distributed with this software. # ---------------------------------------------------------------------------- import warnings -import copy def match(table, metadata, intersect=False): From e0c75050935ded07c69e5cf32875c9a5cc563e28 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 25 Jul 2016 15:37:15 -0700 Subject: [PATCH 14/32] ENH: Adding in niche sorting algorithm --- gneiss/sort.py | 80 +++++++++++++++++++++++++++++ gneiss/tests/test_sort.py | 105 ++++++++++++++++++++++++++++++++++++++ 2 files changed, 185 insertions(+) create mode 100644 gneiss/sort.py create mode 100644 gneiss/tests/test_sort.py diff --git a/gneiss/sort.py b/gneiss/sort.py new file mode 100644 index 0000000..e1382e5 --- /dev/null +++ b/gneiss/sort.py @@ -0,0 +1,80 @@ +import numpy as np +import pandas as pd +from functools import partial +from gneiss.util import match + + +def mean_niche_estimator(abundances, gradient): + """ Estimates the mean niche of an organism. + + Calculates the mean niche or an organism along a gradient. + This is done by calculating the expected value of an organism + across the gradient. + + Parameters + ---------- + abundances : pd.Series, np.float + Vector of fraction abundances of an organism over + a list of samples. + gradient : pd.Series, np.float + Vector of numerical gradient values. + + Returns + ------- + np.float : + The mean gradient that the organism lives in. + """ + if len(abundances) != len(gradient): + raise ValueError("Length of abundances (%d) doesn't match the length" + " of the gradient (%d)" % (len(abundances), + len(gradient))) + if np.any(pd.isnull(gradient)): + raise ValueError("`gradient` cannot have any missing values.") + + # normalizes the proportions of the organism across all of the + # samples to add to 1. + v = abundances / abundances.sum() + return np.dot(gradient, v) + + +def nichesort(table, gradient, niche_estimator=None): + """ Sort the table according to estimated niches. + + Sorts the table by samples along the gradient + and otus by their estimated niche along the gradient. + + Parameters + ---------- + table : pd.DataFrame + Contingency table where samples are rows and + features (i.e. OTUs) are columns. + gradient : pd.Series + Vector of numerical gradient values. + niche_estimator : function + A function that takes in two pandas series and returns an ordered + object. The ability for the object to be ordered is critical, since + this will allow the table to be sorted according to this sorting. + + Returns + ------- + pd.DataFrame : + Sorted table according to the gradient of the samples, and the niches + of the organisms along that gradient. + """ + + if niche_estimator is None: + niche_estimator = mean_niche_estimator + + niche_estimator = partial(niche_estimator, + gradient=gradient) + + _table, _gradient = match(table, gradient, intersect=True) + norm_table = _table.apply(lambda x: x/x.sum(), axis=1) + est_niche = norm_table.apply(niche_estimator, axis=0) + + _gradient = _gradient.sort_values() + est_niche = est_niche.sort_values() + + _table = _table.reindex(index=_gradient.index) + _table = _table.reindex(columns=est_niche.index) + return _table diff --git a/gneiss/tests/test_sort.py b/gneiss/tests/test_sort.py new file mode 100644 index 0000000..c04c223 --- /dev/null +++ b/gneiss/tests/test_sort.py @@ -0,0 +1,105 @@ +import numpy as np +import pandas as pd +import unittest +from gneiss.sort import nichesort, mean_niche_estimator +import pandas.util.testing as pdt + + +class TestSort(unittest.TestCase): + def setUp(self): + pass + + def test_mean_niche_estimator1(self): + gradient = pd.Series( + [1, 2, 3, 4, 5], + index=['s1', 's2', 's3', 's4', 's5']) + values = pd.Series( + [1, 1, 0, 0, 0], + index=['s1', 's2', 's3', 's4', 's5']) + m = mean_niche_estimator(values, gradient) + self.assertEqual(m, 1.5) + + def test_mean_niche_estimator2(self): + gradient = pd.Series( + [1, 2, 3, 4, 5], + index=['s1', 's2', 's3', 's4', 's5']) + values = pd.Series( + [1, 3, 0, 0, 0], + index=['s1', 's2', 's3', 's4', 's5']) + m = mean_niche_estimator(values, gradient) + self.assertEqual(m, 1.75) + + def test_mean_niche_estimator_bad_length(self): + pass + + def test_basic_nichesort(self): + table = pd.DataFrame( + [[1, 1, 0, 0, 0], + [0, 1, 1, 0, 0], + [0, 0, 1, 1, 0], + [0, 0, 0, 1, 1]], + columns=['s1', 's2', 's3', 's4', 's5'], + index=['o1', 'o2', 'o3', 'o4']).T + gradient = pd.Series( + [1, 2, 3, 4, 5], + index=['s1', 's2', 's3', 's4', 's5']) + res_table = nichesort(table, gradient) + pdt.assert_frame_equal(table, res_table) + + def test_basic_nichesort_scrambled(self): + + table = pd.DataFrame( + [[1, 0, 1, 0, 0], + [1, 1, 0, 0, 0], + [0, 0, 1, 1, 0], + [0, 0, 0, 1, 1]], + columns=['s2', 's1', 's3', 's4', 's5'], + index=['o2', 'o1', 'o3', 'o4']).T + + gradient = pd.Series( + [2, 1, 3, 4, 5], + index=['s2', 's1', 's3', 's4', 's5']) + + exp_table = pd.DataFrame( + [[1, 1, 0, 0, 0], + [0, 1, 1, 0, 0], + [0, 0, 1, 1, 0], + [0, 0, 0, 1, 1]], + columns=['s1', 's2', 's3', 's4', 's5'], + index=['o1', 'o2', 'o3', 'o4']).T + + res_table = nichesort(table, gradient) + + pdt.assert_frame_equal(exp_table, res_table) + + def test_basic_nichesort_lambda(self): + table = pd.DataFrame( + [[1, 1, 0, 0, 0], + [0, 0, 1, 1, 0], + [0, 1, 1, 0, 0], + [0, 0, 0, 1, 1]], + columns=['s1', 's2', 's3', 's4', 's5'], + index=['o1', 'o3', 'o2', 'o4']).T + gradient = pd.Series( + [1, 2, 3, 4, 5], + index=['s1', 's2', 's3', 's4', 's5']) + + exp_table = pd.DataFrame( + [[1, 1, 0, 0, 0], + [0, 1, 1, 0, 0], + [0, 0, 1, 1, 0], + [0, 0, 0, 1, 1]], + columns=['s1', 's2', 's3', 's4', 's5'], + index=['o1', 'o2', 'o3', 'o4']).T + + def _dumb_estimator(v, gradient): + v[v > 0] = 1 + values = v / v.sum() + return np.dot(gradient, values) + + res_table = nichesort(table, gradient, niche_estimator=_dumb_estimator) + pdt.assert_frame_equal(exp_table, res_table) + + +if __name__ == '__main__': + unittest.main() From 3d9ded69f924b8c91db7f9ba720dcafb34536bf8 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 25 Jul 2016 15:38:57 -0700 Subject: [PATCH 15/32] TST: Adding in length and nan tests --- gneiss/tests/test_sort.py | 21 ++++++++++++++++++++- 1 file changed, 20 insertions(+), 1 deletion(-) diff --git a/gneiss/tests/test_sort.py b/gneiss/tests/test_sort.py index c04c223..64ce24d 100644 --- a/gneiss/tests/test_sort.py +++ b/gneiss/tests/test_sort.py @@ -30,7 +30,26 @@ def test_mean_niche_estimator2(self): self.assertEqual(m, 1.75) def test_mean_niche_estimator_bad_length(self): - pass + gradient = pd.Series( + [1, 2, 3, 4, 5], + index=['s1', 's2', 's3', 's4', 's5']) + values = pd.Series( + [1, 3, 0, 0, 0, 0], + index=['s1', 's2', 's3', 's4', 's5', 's6']) + + with self.assertRaises(ValueError): + mean_niche_estimator(values, gradient) + + def test_mean_niche_estimator_missing(self): + gradient = pd.Series( + [1, 2, 3, 4, np.nan], + index=['s1', 's2', 's3', 's4', 's5']) + values = pd.Series( + [1, 3, 0, 0, 0], + index=['s1', 's2', 's3', 's4', 's5']) + + with self.assertRaises(ValueError): + mean_niche_estimator(values, gradient) def test_basic_nichesort(self): table = pd.DataFrame( From 4c8d41d74180cbbbad894a7f8cf66fe9f69291af Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 25 Jul 2016 16:14:19 -0700 Subject: [PATCH 16/32] DOC: typo --- gneiss/sort.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/gneiss/sort.py b/gneiss/sort.py index e1382e5..c45fec1 100644 --- a/gneiss/sort.py +++ b/gneiss/sort.py @@ -53,7 +53,7 @@ def nichesort(table, gradient, niche_estimator=None): niche_estimator : function A function that takes in two pandas series and returns an ordered object. The ability for the object to be ordered is critical, since - this will allow the table to be sorted according to this sorting. + this will allow the table to be sorted according to this ordering. Returns ------- From 371cc16d6dd6c7b2b8cd4b984b9ad11745f3c83f Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 25 Jul 2016 16:31:44 -0700 Subject: [PATCH 17/32] ENH: Adding inplace option --- gneiss/tests/test_util.py | 9 +++++++++ gneiss/util.py | 16 +++++++++++++--- 2 files changed, 22 insertions(+), 3 deletions(-) diff --git a/gneiss/tests/test_util.py b/gneiss/tests/test_util.py index ce815fe..0076d90 100644 --- a/gneiss/tests/test_util.py +++ b/gneiss/tests/test_util.py @@ -145,6 +145,10 @@ def test_match_intersect(self): columns=['Barcode', 'Treatment']) res_table, res_metadata = match(table, metadata, intersect=True) + # sort for comparison, since the match function + # scrambles the names due to hashing. + res_table = res_table.sort_index() + res_metadata = res_metadata.sort_index() pdt.assert_frame_equal(exp_table, res_table) pdt.assert_frame_equal(exp_metadata, res_metadata) @@ -317,6 +321,11 @@ def test_rename_internal_nodes_immutable(self): rename_internal_nodes(tree) self.assertEqual(str(tree), "(((a,b)y2,c),d)r;\n") + def test_rename_internal_nodes_mutable(self): + tree = TreeNode.read([u"(((a,b)y2, c),d)r;"]) + rename_internal_nodes(tree, inplace=True) + self.assertEqual(str(tree), "(((a,b)y2,c)y1,d)y0;\n") + if __name__ == '__main__': unittest.main() diff --git a/gneiss/util.py b/gneiss/util.py index 47d1aa3..a645ee3 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -39,6 +39,11 @@ def match(table, metadata, intersect=False): Raised if duplicate sample ids are present in `metadata`. ValueError: Raised if `table` and `metadata` have incompatible sizes. + + Note + ---- + If `intersect=True` is specified, then the rows for `table` and + `metadata` will be matched, but they will be in a random order. """ subtableids = set(table.index) submetadataids = set(metadata.index) @@ -49,7 +54,6 @@ def match(table, metadata, intersect=False): if intersect: idx = subtableids & submetadataids - idx = sorted(idx) return table.loc[idx], metadata.loc[idx] else: subtable = table.sort_index() @@ -124,7 +128,7 @@ def match_tips(table, tree, intersect=False): return _table, _tree -def rename_internal_nodes(tree, names=None): +def rename_internal_nodes(tree, names=None, inplace=False): """ Names the internal according to level ordering. The tree will be traversed in level order (i.e. top-down, left to right). @@ -140,6 +144,8 @@ def rename_internal_nodes(tree, names=None): List of labels to rename the tip names. It is assumed that the names are listed in level ordering, and the length of the list is at least as long as the number of internal nodes. + inplace : bool, optional + Specifies if the operation should be done on the original tree or not. Returns ------- @@ -149,7 +155,11 @@ def rename_internal_nodes(tree, names=None): ValueError: Raised if `tree` and `name` have incompatible sizes. """ - _tree = tree.copy() + if inplace: + _tree = tree + else: + _tree = tree.copy() + non_tips = [n for n in _tree.levelorder() if not n.is_tip()] if names is not None and len(non_tips) != len(names): raise ValueError("`_tree` and `names` have incompatible sizes, " From 6d70cf9f754097fc9da49e7400ac7114e831affa Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 25 Jul 2016 18:02:02 -0700 Subject: [PATCH 18/32] STY: Code dereplication --- gneiss/tests/test_util.py | 66 ++++++++++++++------------------------- gneiss/util.py | 50 +++++++++-------------------- 2 files changed, 39 insertions(+), 77 deletions(-) diff --git a/gneiss/tests/test_util.py b/gneiss/tests/test_util.py index 0076d90..fecf40f 100644 --- a/gneiss/tests/test_util.py +++ b/gneiss/tests/test_util.py @@ -30,6 +30,16 @@ def test_match(self): columns=['Barcode', 'Treatment']) exp_table, exp_metadata = table, metadata res_table, res_metadata = match(table, metadata) + + # make sure that the metadata and table indeces match + pdt.assert_index_equal(res_table.index, res_metadata.index) + + res_table = res_table.sort_index() + exp_table = exp_table.sort_index() + + res_metadata = res_metadata.sort_index() + exp_metadata = exp_metadata.sort_index() + pdt.assert_frame_equal(exp_table, res_table) pdt.assert_frame_equal(exp_metadata, res_metadata) @@ -58,7 +68,7 @@ def test_match_immutable(self): ['b', 'control']], index=['s1', 's3', 's2'], columns=['Barcode', 'Treatment']) - match(table, metadata, intersect=True) + match(table, metadata) pdt.assert_frame_equal(table, exp_table) pdt.assert_frame_equal(metadata, exp_metadata) @@ -116,6 +126,15 @@ def test_match_scrambled(self): columns=['Barcode', 'Treatment']) res_table, res_metadata = match(table, metadata) + # make sure that the metadata and table indeces match + pdt.assert_index_equal(res_table.index, res_metadata.index) + + res_table = res_table.sort_index() + exp_table = exp_table.sort_index() + + res_metadata = res_metadata.sort_index() + exp_metadata = exp_metadata.sort_index() + pdt.assert_frame_equal(exp_table, res_table) pdt.assert_frame_equal(exp_metadata, res_metadata) @@ -144,7 +163,7 @@ def test_match_intersect(self): index=['s1', 's2', 's3'], columns=['Barcode', 'Treatment']) - res_table, res_metadata = match(table, metadata, intersect=True) + res_table, res_metadata = match(table, metadata) # sort for comparison, since the match function # scrambles the names due to hashing. res_table = res_table.sort_index() @@ -152,21 +171,6 @@ def test_match_intersect(self): pdt.assert_frame_equal(exp_table, res_table) pdt.assert_frame_equal(exp_metadata, res_metadata) - def test_match_mismatch(self): - table = pd.DataFrame([[0, 0, 1, 1], - [2, 2, 4, 4], - [5, 5, 3, 3], - [0, 0, 0, 1]], - index=['s1', 's2', 's3', 's4'], - columns=['o1', 'o2', 'o3', 'o4']) - metadata = pd.DataFrame([['a', 'control'], - ['c', 'diseased'], - ['b', 'control']], - index=['s1', 's3', 's2'], - columns=['Barcode', 'Treatment']) - with self.assertRaises(ValueError): - match(table, metadata) - def test_match_tips(self): table = pd.DataFrame([[0, 0, 1, 1], [2, 2, 4, 4], @@ -236,7 +240,7 @@ def test_match_tips_intersect_tips(self): index=['s1', 's2', 's3', 's4'], columns=['a', 'b', 'd']) exp_tree = tree - res_table, res_tree = match_tips(table, tree, intersect=True) + res_table, res_tree = match_tips(table, tree) pdt.assert_frame_equal(exp_table, res_table) self.assertEqual(str(exp_tree), str(res_tree)) @@ -256,7 +260,7 @@ def test_match_tips_intersect_columns(self): index=['s1', 's2', 's3', 's4'], columns=['d', 'a', 'b']) exp_tree = TreeNode.read([u"(d,(a,b)f)r;"]) - res_table, res_tree = match_tips(table, tree, intersect=True) + res_table, res_tree = match_tips(table, tree) pdt.assert_frame_equal(exp_table, res_table) self.assertEqual(str(exp_tree), str(res_tree)) @@ -269,31 +273,9 @@ def test_match_tips_intersect_tree_immutable(self): index=['s1', 's2', 's3', 's4'], columns=['a', 'b', 'd']) tree = TreeNode.read([u"(((a,b)f, c),d)r;"]) - match_tips(table, tree, intersect=True) + match_tips(table, tree) self.assertEqual(str(tree), u"(((a,b)f,c),d)r;\n") - def test_match_tips_mismatch(self): - # table has less columns than tree tips - table = pd.DataFrame([[0, 0, 1], - [2, 3, 4], - [5, 5, 3], - [0, 0, 1]], - index=['s1', 's2', 's3', 's4'], - columns=['a', 'b', 'd']) - tree = TreeNode.read([u"(((a,b)f, c),d)r;"]) - with self.assertRaises(ValueError): - match_tips(table, tree) - - table = pd.DataFrame([[0, 0, 1, 1], - [2, 3, 4, 4], - [5, 5, 3, 3], - [0, 0, 0, 1]], - index=['s1', 's2', 's3', 's4'], - columns=['a', 'b', 'c', 'd']) - tree = TreeNode.read([u"((a,b)f,d)r;"]) - with self.assertRaises(ValueError): - match_tips(table, tree) - def test_rename_internal_nodes(self): tree = TreeNode.read([u"(((a,b), c),d)r;"]) exp_tree = TreeNode.read([u"(((a,b)y2, c)y1,d)y0;"]) diff --git a/gneiss/util.py b/gneiss/util.py index a645ee3..6958ab7 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -8,9 +8,12 @@ import warnings -def match(table, metadata, intersect=False): +def match(table, metadata): """ Sorts samples in metadata and contingency table in the same order. + The intersection of samples in the contingency table and the metadata table + will returned. + Parameters ---------- table : pd.DataFrame @@ -19,10 +22,6 @@ def match(table, metadata, intersect=False): metadata: pd.DataFrame Metadata table where samples correspond to rows and explanatory metadata variables correspond to columns. - intersect : bool, optional - Specifies if only the intersection of samples in the - contingency table and the metadata table will returned. - By default, this is False. Returns ------- @@ -52,22 +51,13 @@ def match(table, metadata, intersect=False): if len(submetadataids) != len(metadata.index): raise ValueError("`metadata` has duplicate sample ids.") - if intersect: - idx = subtableids & submetadataids - return table.loc[idx], metadata.loc[idx] - else: - subtable = table.sort_index() - submetadata = metadata.sort_index() - - if len(subtable.index) != len(submetadata.index): - raise ValueError("`table` and `metadata` have incompatible sizes, " - "`table` has %d rows, `metadata` has %d rows. " - "Consider setting `intersect=True`." % - (len(subtable.index), len(submetadata.index))) - return subtable, submetadata + idx = subtableids & submetadataids + subtable = table.loc[idx] + submetadata = metadata.loc[idx] + return subtable, submetadata -def match_tips(table, tree, intersect=False): +def match_tips(table, tree): """ Returns the contingency table and tree with matched tips. Sorts the columns of the contingency table to match the tips in @@ -76,6 +66,9 @@ def match_tips(table, tree, intersect=False): If the tree is multi-furcating, then the tree is reduced to a bifurcating tree by randomly inserting internal nodes. + The intersection of samples in the contingency table and the + tree will returned. + Parameters ---------- table : pd.DataFrame @@ -83,10 +76,6 @@ def match_tips(table, tree, intersect=False): features correspond to columns. tree : skbio.TreeNode Tree object where the leafs correspond to the features. - intersect : bool, optional - Specifies if only the intersection of samples in the - contingency table and the tree will returned. - By default, this is False. Returns ------- @@ -108,23 +97,14 @@ def match_tips(table, tree, intersect=False): tips = [x.name for x in tree.tips()] common_tips = list(set(tips) & set(table.columns)) - if intersect: - _table = table.loc[:, common_tips] - _tree = tree.shear(names=common_tips) - else: - if len(tips) != len(table.columns): - raise ValueError("`table` and `tree` have incompatible sizes, " - "`table` has %d columns, `tree` has %d tips. " - "Consider setting `intersect=True`." % - (len(table.columns), len(tips))) - - _table = table - _tree = tree + _table = table.loc[:, common_tips] + _tree = tree.shear(names=common_tips) _tree.bifurcate() _tree.prune() sorted_features = [n.name for n in _tree.tips()] _table = _table.reindex_axis(sorted_features, axis=1) + return _table, _tree From 9003db813f82b0106ac847c4e2acb12542cdefd8 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 25 Jul 2016 18:09:14 -0700 Subject: [PATCH 19/32] DOC: cleaning up docstrings --- gneiss/util.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/gneiss/util.py b/gneiss/util.py index 6958ab7..6df83cf 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -9,10 +9,12 @@ def match(table, metadata): - """ Sorts samples in metadata and contingency table in the same order. + """ Matches samples between a contingency table and a metadata table. - The intersection of samples in the contingency table and the metadata table - will returned. + Sorts samples in metadata and contingency table in the same order. + If there are sames contained in the contigency table, but not in metadata or + vice versa, the intersection of samples in the contingency table and the + metadata table will returned. Parameters ---------- @@ -39,10 +41,6 @@ def match(table, metadata): ValueError: Raised if `table` and `metadata` have incompatible sizes. - Note - ---- - If `intersect=True` is specified, then the rows for `table` and - `metadata` will be matched, but they will be in a random order. """ subtableids = set(table.index) submetadataids = set(metadata.index) @@ -132,6 +130,8 @@ def rename_internal_nodes(tree, names=None, inplace=False): skbio.TreeNode Tree with renamed internal nodes. + Raises + ------ ValueError: Raised if `tree` and `name` have incompatible sizes. """ From b049ced42527af99e485de6d2098768aaee5779e Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Mon, 25 Jul 2016 18:24:57 -0700 Subject: [PATCH 20/32] pep8 --- gneiss/util.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/gneiss/util.py b/gneiss/util.py index 6df83cf..98e7031 100644 --- a/gneiss/util.py +++ b/gneiss/util.py @@ -12,8 +12,8 @@ def match(table, metadata): """ Matches samples between a contingency table and a metadata table. Sorts samples in metadata and contingency table in the same order. - If there are sames contained in the contigency table, but not in metadata or - vice versa, the intersection of samples in the contingency table and the + If there are sames contained in the contigency table, but not in metadata + or vice versa, the intersection of samples in the contingency table and the metadata table will returned. Parameters From ac1832dbad814d999336098c17dcb3258e15e962 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Tue, 26 Jul 2016 11:43:06 -0700 Subject: [PATCH 21/32] FIX: Fixing ordering --- gneiss/sort.py | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/gneiss/sort.py b/gneiss/sort.py index c45fec1..f709f7a 100644 --- a/gneiss/sort.py +++ b/gneiss/sort.py @@ -34,7 +34,8 @@ def mean_niche_estimator(abundances, gradient): # normalizes the proportions of the organism across all of the # samples to add to 1. v = abundances / abundances.sum() - return np.dot(gradient, v) + m = np.dot(gradient, v) + return m def nichesort(table, gradient, niche_estimator=None): @@ -65,13 +66,14 @@ def nichesort(table, gradient, niche_estimator=None): if niche_estimator is None: niche_estimator = mean_niche_estimator + + _table, _gradient = match(table, gradient) + niche_estimator = partial(niche_estimator, - gradient=gradient) + gradient=_gradient) - _table, _gradient = match(table, gradient, intersect=True) norm_table = _table.apply(lambda x: x/x.sum(), axis=1) est_niche = norm_table.apply(niche_estimator, axis=0) - _gradient = _gradient.sort_values() est_niche = est_niche.sort_values() From 42221f5d51538bd636d85129a7a1b30cf4298c9b Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Tue, 26 Jul 2016 11:47:31 -0700 Subject: [PATCH 22/32] pep8 --- gneiss/sort.py | 1 - 1 file changed, 1 deletion(-) diff --git a/gneiss/sort.py b/gneiss/sort.py index f709f7a..14a8dd6 100644 --- a/gneiss/sort.py +++ b/gneiss/sort.py @@ -66,7 +66,6 @@ def nichesort(table, gradient, niche_estimator=None): if niche_estimator is None: niche_estimator = mean_niche_estimator - _table, _gradient = match(table, gradient) niche_estimator = partial(niche_estimator, From 23acedfd2291c0b3716023c9867c2629b1c16dc4 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Wed, 27 Jul 2016 10:40:39 -0700 Subject: [PATCH 23/32] Adding @josenavas and @antgonza comments --- gneiss/sort.py | 66 ++++++++++++++++++++++++++++----------- gneiss/tests/test_sort.py | 56 ++++++++++++++++++++++++++++----- 2 files changed, 95 insertions(+), 27 deletions(-) diff --git a/gneiss/sort.py b/gneiss/sort.py index 14a8dd6..c9909b2 100644 --- a/gneiss/sort.py +++ b/gneiss/sort.py @@ -1,3 +1,10 @@ +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the GPLv3 License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- import numpy as np import pandas as pd from functools import partial @@ -7,10 +14,20 @@ def mean_niche_estimator(abundances, gradient): """ Estimates the mean niche of an organism. - Calculates the mean niche or an organism along a gradient. + Calculates the mean niche of an organism along a gradient. This is done by calculating the expected value of an organism across the gradient. + Specifically, this module calculates the following + + .. math:: + E[g | x] = + \frac{1}{\sum\limits_{j=1}^N x_j} \sum\limits_{i=1}^N x_i g_i + + Where :math:`N` is the number of samples, :math:`x_i` is the proportion of + species :math:`x` in sample :math:`i`, :math:`g_i` is the gradient value + at sample `i`. + Parameters ---------- abundances : pd.Series, np.float @@ -23,13 +40,22 @@ def mean_niche_estimator(abundances, gradient): ------- np.float : The mean gradient that the organism lives in. + + Raises + ------ + ValueError: + If the length of `abundances` is not the same length as `gradient`. + ValueError: + If the length of `gradient` contains nans. """ - if len(abundances) != len(gradient): - raise ValueError("Length of abundances (%d) doesn't match the length" - " of the gradient (%d)" % (len(abundances), - len(gradient))) + len_abundances = len(abundances) + len_gradient = len(gradient) + if len_abundances != len_gradient: + raise ValueError("Length of `abundances` (%d) doesn't match the length" + " of the `gradient` (%d)" % (len_abundances, + len_gradient)) if np.any(pd.isnull(gradient)): - raise ValueError("`gradient` cannot have any missing values.") + raise ValueError("`gradient` cannot have any nans.") # normalizes the proportions of the organism across all of the # samples to add to 1. @@ -38,7 +64,7 @@ def mean_niche_estimator(abundances, gradient): return m -def nichesort(table, gradient, niche_estimator=None): +def niche_sort(table, gradient, niche_estimator=mean_niche_estimator): """ Sort the table according to estimated niches. Sorts the table by samples along the gradient @@ -51,10 +77,11 @@ def nichesort(table, gradient, niche_estimator=None): features (i.e. OTUs) are columns. gradient : pd.Series Vector of numerical gradient values. - niche_estimator : function + niche_estimator : function, optional A function that takes in two pandas series and returns an ordered object. The ability for the object to be ordered is critical, since this will allow the table to be sorted according to this ordering. + By default, `mean_niche_estimator` will be used. Returns ------- @@ -63,19 +90,20 @@ def nichesort(table, gradient, niche_estimator=None): of the organisms along that gradient. """ - if niche_estimator is None: - niche_estimator = mean_niche_estimator - - _table, _gradient = match(table, gradient) + table, gradient = match(table, gradient) niche_estimator = partial(niche_estimator, - gradient=_gradient) + gradient=gradient) + + # normalizes feature abundances to sum to 1, for each sample. + # (i.e. scales values in each row to sum to 1). + normtable = table.apply(lambda x: x/x.sum(), axis=1) - norm_table = _table.apply(lambda x: x/x.sum(), axis=1) - est_niche = norm_table.apply(niche_estimator, axis=0) - _gradient = _gradient.sort_values() + # calculates estimated niche for each feature + est_niche = normtable.apply(niche_estimator, axis=0) + gradient = gradient.sort_values() est_niche = est_niche.sort_values() - _table = _table.reindex(index=_gradient.index) - _table = _table.reindex(columns=est_niche.index) - return _table + table = table.reindex(index=gradient.index, + columns=est_niche.index) + return table diff --git a/gneiss/tests/test_sort.py b/gneiss/tests/test_sort.py index 64ce24d..d3a8f37 100644 --- a/gneiss/tests/test_sort.py +++ b/gneiss/tests/test_sort.py @@ -1,7 +1,14 @@ +# ---------------------------------------------------------------------------- +# Copyright (c) 2016--, gneiss development team. +# +# Distributed under the terms of the GPLv3 License. +# +# The full license is in the file COPYING.txt, distributed with this software. +# ---------------------------------------------------------------------------- import numpy as np import pandas as pd import unittest -from gneiss.sort import nichesort, mean_niche_estimator +from gneiss.sort import niche_sort, mean_niche_estimator import pandas.util.testing as pdt @@ -51,7 +58,7 @@ def test_mean_niche_estimator_missing(self): with self.assertRaises(ValueError): mean_niche_estimator(values, gradient) - def test_basic_nichesort(self): + def test_basic_niche_sort(self): table = pd.DataFrame( [[1, 1, 0, 0, 0], [0, 1, 1, 0, 0], @@ -62,11 +69,12 @@ def test_basic_nichesort(self): gradient = pd.Series( [1, 2, 3, 4, 5], index=['s1', 's2', 's3', 's4', 's5']) - res_table = nichesort(table, gradient) + res_table = niche_sort(table, gradient) pdt.assert_frame_equal(table, res_table) - def test_basic_nichesort_scrambled(self): - + def test_basic_niche_sort_scrambled(self): + # Swap samples s1 and s2 and features o1 and o2 to see if this can + # obtain the original table structure. table = pd.DataFrame( [[1, 0, 1, 0, 0], [1, 1, 0, 0, 0], @@ -87,11 +95,11 @@ def test_basic_nichesort_scrambled(self): columns=['s1', 's2', 's3', 's4', 's5'], index=['o1', 'o2', 'o3', 'o4']).T - res_table = nichesort(table, gradient) + res_table = niche_sort(table, gradient) pdt.assert_frame_equal(exp_table, res_table) - def test_basic_nichesort_lambda(self): + def test_basic_niche_sort_lambda(self): table = pd.DataFrame( [[1, 1, 0, 0, 0], [0, 0, 1, 1, 0], @@ -116,9 +124,41 @@ def _dumb_estimator(v, gradient): values = v / v.sum() return np.dot(gradient, values) - res_table = nichesort(table, gradient, niche_estimator=_dumb_estimator) + res_table = niche_sort(table, gradient, + niche_estimator=_dumb_estimator) pdt.assert_frame_equal(exp_table, res_table) + def test_basic_niche_sort_immutable(self): + # Swap samples s1 and s2 and features o1 and o2 to see if this can + # obtain the original table structure. + table = pd.DataFrame( + [[1, 0, 1, 0, 0], + [1, 1, 0, 0, 0], + [0, 0, 1, 1, 0], + [0, 0, 0, 1, 1]], + columns=['s2', 's1', 's3', 's4', 's5'], + index=['o2', 'o1', 'o3', 'o4']).T + + gradient = pd.Series( + [2, 1, 3, 4, 5], + index=['s2', 's1', 's3', 's4', 's5']) + + exp_table = pd.DataFrame( + [[1, 0, 1, 0, 0], + [1, 1, 0, 0, 0], + [0, 0, 1, 1, 0], + [0, 0, 0, 1, 1]], + columns=['s2', 's1', 's3', 's4', 's5'], + index=['o2', 'o1', 'o3', 'o4']).T + + exp_gradient = pd.Series( + [2, 1, 3, 4, 5], + index=['s2', 's1', 's3', 's4', 's5']) + + niche_sort(table, gradient) + pdt.assert_frame_equal(exp_table, table) + pdt.assert_series_equal(exp_gradient, gradient) + if __name__ == '__main__': unittest.main() From 940d7e8cca0a8f76e87e7d21529d270453bbe33d Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Wed, 27 Jul 2016 12:41:50 -0700 Subject: [PATCH 24/32] TST: Adding callable error --- gneiss/sort.py | 2 ++ gneiss/tests/test_sort.py | 14 ++++++++++++++ 2 files changed, 16 insertions(+) diff --git a/gneiss/sort.py b/gneiss/sort.py index c9909b2..901b426 100644 --- a/gneiss/sort.py +++ b/gneiss/sort.py @@ -89,6 +89,8 @@ def niche_sort(table, gradient, niche_estimator=mean_niche_estimator): Sorted table according to the gradient of the samples, and the niches of the organisms along that gradient. """ + if not callable(niche_estimator): + raise ValueError("`niche_estimator` is not a function.") table, gradient = match(table, gradient) diff --git a/gneiss/tests/test_sort.py b/gneiss/tests/test_sort.py index d3a8f37..1288b75 100644 --- a/gneiss/tests/test_sort.py +++ b/gneiss/tests/test_sort.py @@ -72,6 +72,20 @@ def test_basic_niche_sort(self): res_table = niche_sort(table, gradient) pdt.assert_frame_equal(table, res_table) + def test_basic_niche_sort_error(self): + table = pd.DataFrame( + [[1, 1, 0, 0, 0], + [0, 1, 1, 0, 0], + [0, 0, 1, 1, 0], + [0, 0, 0, 1, 1]], + columns=['s1', 's2', 's3', 's4', 's5'], + index=['o1', 'o2', 'o3', 'o4']).T + gradient = pd.Series( + [1, 2, 3, 4, 5], + index=['s1', 's2', 's3', 's4', 's5']) + with self.assertRaises(ValueError): + niche_sort(table, gradient, niche_estimator='rawr') + def test_basic_niche_sort_scrambled(self): # Swap samples s1 and s2 and features o1 and o2 to see if this can # obtain the original table structure. From 7ee169cb712abb69a42ecc5e9da802b329912013 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Wed, 27 Jul 2016 14:10:32 -0700 Subject: [PATCH 25/32] DOC: Adding raises section --- gneiss/sort.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/gneiss/sort.py b/gneiss/sort.py index 901b426..aa64d16 100644 --- a/gneiss/sort.py +++ b/gneiss/sort.py @@ -88,6 +88,11 @@ def niche_sort(table, gradient, niche_estimator=mean_niche_estimator): pd.DataFrame : Sorted table according to the gradient of the samples, and the niches of the organisms along that gradient. + + Raises + ------ + ValueError : + Raised if `niche_estimator` is not a function. """ if not callable(niche_estimator): raise ValueError("`niche_estimator` is not a function.") From 0168b42737be8d1454bb0b41133d48f7a9642829 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Wed, 27 Jul 2016 16:17:19 -0700 Subject: [PATCH 26/32] DOC: Clarifying formulat in `mean_niche_estimator` --- gneiss/sort.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/gneiss/sort.py b/gneiss/sort.py index aa64d16..3751df4 100644 --- a/gneiss/sort.py +++ b/gneiss/sort.py @@ -22,7 +22,7 @@ def mean_niche_estimator(abundances, gradient): .. math:: E[g | x] = - \frac{1}{\sum\limits_{j=1}^N x_j} \sum\limits_{i=1}^N x_i g_i + \sum\limits_{i=1}^N x_i g_i \frac{x_i}{\sum\limits_{j=1}^N x_j} Where :math:`N` is the number of samples, :math:`x_i` is the proportion of species :math:`x` in sample :math:`i`, :math:`g_i` is the gradient value From c9e237381ddbf4ec31d0fe58acf276e92006af3f Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Wed, 27 Jul 2016 16:21:26 -0700 Subject: [PATCH 27/32] DOC: Correcting formula --- gneiss/sort.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/gneiss/sort.py b/gneiss/sort.py index 3751df4..70cdc58 100644 --- a/gneiss/sort.py +++ b/gneiss/sort.py @@ -22,7 +22,7 @@ def mean_niche_estimator(abundances, gradient): .. math:: E[g | x] = - \sum\limits_{i=1}^N x_i g_i \frac{x_i}{\sum\limits_{j=1}^N x_j} + \sum\limits_{i=1}^N g_i \frac{x_i}{\sum\limits_{j=1}^N x_j} Where :math:`N` is the number of samples, :math:`x_i` is the proportion of species :math:`x` in sample :math:`i`, :math:`g_i` is the gradient value From c51b2154eee11b28b90480f0dc76e0ac414d50ce Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Wed, 27 Jul 2016 19:11:19 -0700 Subject: [PATCH 28/32] Updating changelog Adding in link --- CHANGELOG.md | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 08e45ee..dc88393 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -3,6 +3,7 @@ ## Version 0.0.2 (changes since 0.0.2 go here) ### Features +* * Adding in a niche sorting algorithm `gneiss.sort.niche_sort` that can generate a band table given a gradient [#16](https://github.com/biocore/gneiss/pull/16) * Adding in utility functions for handing feature tables, metadata, and trees. [#12](https://github.com/biocore/gneiss/pull/12) * Adding GPL license. From 6a247a71fa2df4106391e17fc83c0a36566bd341 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Fri, 29 Jul 2016 11:18:31 -0700 Subject: [PATCH 29/32] Typo in ipython notebook --- ipynb/balance_trees.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ipynb/balance_trees.ipynb b/ipynb/balance_trees.ipynb index 13d41be..b9f039a 100644 --- a/ipynb/balance_trees.ipynb +++ b/ipynb/balance_trees.ipynb @@ -45,7 +45,7 @@ "$$\n", "b_i = \\sqrt{\\frac{l_i r_i}{l_i + r_i}} \n", " \\log \\big( \\frac{(\\prod_{x_n \\in L}{x_n})^{1/l_i}}\n", - " {(\\prod_{x_m \\in L}{x_m})^{1/r_i}} \\big)\n", + " {(\\prod_{x_m \\inRL}{x_m})^{1/r_i}} \\big)\n", "$$\n", "\n", "where $b_i$ is the $i$th balance, $l_i$ is the number of leaves in the left subtree, $r_i$ is the number of leaves in the right subtree $x_n$ are the abundances of the species in the left subtree, and $x_m$ are the abundances of species in the right subtree.\n" From f13954dd156fdd10d2ce8b625045953ac82dd7b1 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Fri, 29 Jul 2016 11:19:12 -0700 Subject: [PATCH 30/32] Fixing typo in ipython notebook --- ipynb/balance_trees.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ipynb/balance_trees.ipynb b/ipynb/balance_trees.ipynb index b9f039a..96f22b9 100644 --- a/ipynb/balance_trees.ipynb +++ b/ipynb/balance_trees.ipynb @@ -45,7 +45,7 @@ "$$\n", "b_i = \\sqrt{\\frac{l_i r_i}{l_i + r_i}} \n", " \\log \\big( \\frac{(\\prod_{x_n \\in L}{x_n})^{1/l_i}}\n", - " {(\\prod_{x_m \\inRL}{x_m})^{1/r_i}} \\big)\n", + " {(\\prod_{x_m \\in R}{x_m})^{1/r_i}} \\big)\n", "$$\n", "\n", "where $b_i$ is the $i$th balance, $l_i$ is the number of leaves in the left subtree, $r_i$ is the number of leaves in the right subtree $x_n$ are the abundances of the species in the left subtree, and $x_m$ are the abundances of species in the right subtree.\n" From 452d62c3c96a50c4c120d68e24f9f92283e56edf Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Thu, 4 Aug 2016 11:01:43 -0400 Subject: [PATCH 31/32] Adding another test --- gneiss/tests/data/tree.nwk | 1 + gneiss/tests/test_balances.py | 12 +++++++++++- 2 files changed, 12 insertions(+), 1 deletion(-) create mode 100644 gneiss/tests/data/tree.nwk diff --git a/gneiss/tests/data/tree.nwk b/gneiss/tests/data/tree.nwk new file mode 100644 index 0000000..a1fb1c7 --- /dev/null +++ b/gneiss/tests/data/tree.nwk @@ -0,0 +1 @@ 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diff --git a/gneiss/tests/test_balances.py b/gneiss/tests/test_balances.py index 9a8ff72..e497c1e 100644 --- a/gneiss/tests/test_balances.py +++ b/gneiss/tests/test_balances.py @@ -9,6 +9,7 @@ from gneiss.layouts import default_layout from skbio import TreeNode from skbio.util import get_data_path +from skbio.stats.composition import _check_orthogonality class TestPlot(unittest.TestCase): @@ -151,14 +152,23 @@ def test_balance_basis_large1(self): get_data_path('large_tree_basis.txt', subfolder='data')) res_basis, res_keys = balance_basis(t) + _check_orthogonality(res_basis) exp_basis = exp_basis[:, ::-1] print(exp_basis.shape) for i in range(len(res_basis)): print(i) + print(exp_basis[i]- res_basis[i]) npt.assert_allclose(exp_basis[i], res_basis[i]) - npt.assert_allclose(exp_basis[:, ::-1], res_basis) + npt.assert_allclose(exp_basis[:, ::-1], res_basis, rtol=1e-5, atol=1e-5) + + def test_balance_basis_large2(self): + fname = get_data_path('tree.nwk', + subfolder='data') + t = TreeNode.read(fname) + res_basis, res_keys = balance_basis(t) + _check_orthogonality(res_basis) if __name__ == "__main__": From 475b96fccfb33c20aa1645fd24ed753e2814dd67 Mon Sep 17 00:00:00 2001 From: Jamie Morton Date: Thu, 4 Aug 2016 14:33:47 -0400 Subject: [PATCH 32/32] Adding additional test cases --- gneiss/balances.py | 8 -------- .../tests/data/{tree.nwk => large_tree2.nwk} | 0 gneiss/tests/data/small_tree.nwk | 1 + gneiss/tests/test_balances.py | 18 ++++++++---------- 4 files changed, 9 insertions(+), 18 deletions(-) rename gneiss/tests/data/{tree.nwk => large_tree2.nwk} (100%) create mode 100644 gneiss/tests/data/small_tree.nwk diff --git a/gneiss/balances.py b/gneiss/balances.py index 8bbedc6..82cb7b1 100644 --- a/gneiss/balances.py +++ b/gneiss/balances.py @@ -1,11 +1,3 @@ -# ---------------------------------------------------------------------------- -# Copyright (c) 2016--, gneiss development team. -# -# Distributed under the terms of the GPLv3 License. -# -# The full license is in the file COPYING.txt, distributed with this software. -# ---------------------------------------------------------------------------- - from __future__ import division import numpy as np import pandas as pd diff --git a/gneiss/tests/data/tree.nwk b/gneiss/tests/data/large_tree2.nwk similarity index 100% rename from gneiss/tests/data/tree.nwk rename to gneiss/tests/data/large_tree2.nwk diff --git a/gneiss/tests/data/small_tree.nwk b/gneiss/tests/data/small_tree.nwk new file mode 100644 index 0000000..40c794f --- /dev/null +++ b/gneiss/tests/data/small_tree.nwk @@ -0,0 +1 @@ +(O0:0.316212845735,(O1:0.0544249673249,((((O8:6.17283950617e-05,O9:6.17283950617e-05):0.000396077412446,(O6:0.00015943877551,O7:0.00015943877551):0.000298367031998):0.00183128228143,(O4:0.000555555555556,O5:0.000555555555556):0.00173353253338):0.0105194882737,(O2:0.00347222222222,O3:0.00347222222222):0.00933635414042):0.0416163909622):0.26178787841); diff --git a/gneiss/tests/test_balances.py b/gneiss/tests/test_balances.py index 5cfb200..c46bb01 100644 --- a/gneiss/tests/test_balances.py +++ b/gneiss/tests/test_balances.py @@ -1,11 +1,3 @@ -# ---------------------------------------------------------------------------- -# Copyright (c) 2016--, gneiss development team. -# -# Distributed under the terms of the Modified BSD License. -# -# The full license is in the file COPYING.txt, distributed with this software. -# ---------------------------------------------------------------------------- - from __future__ import absolute_import, division, print_function import unittest import numpy as np @@ -18,7 +10,7 @@ from skbio import TreeNode from skbio.util import get_data_path from skbio.stats.composition import _check_orthogonality - +from gneiss.util import rename_internal_nodes class TestPlot(unittest.TestCase): @@ -172,12 +164,18 @@ def test_balance_basis_large1(self): npt.assert_allclose(exp_basis[:, ::-1], res_basis, rtol=1e-5, atol=1e-5) def test_balance_basis_large2(self): - fname = get_data_path('tree.nwk', + fname = get_data_path('large_tree2.nwk', subfolder='data') t = TreeNode.read(fname) res_basis, res_keys = balance_basis(t) _check_orthogonality(res_basis) + def test_balance_basis_small1(self): + fname = get_data_path('small_tree.nwk', + subfolder='data') + t = TreeNode.read(fname) + res_basis, res_keys = balance_basis(t) + _check_orthogonality(res_basis) if __name__ == "__main__": unittest.main()