Merge pull request #36 from KrishnaswamyLab/dev

graphtools v1.1

Author: scottgigante

graphtools/__init__.py

@@ -1,2 +1,2 @@
-from .api import Graph, from_igraph
+from .api import Graph, from_igraph, read_pickle
 from .version import __version__

graphtools/api.py

@@ -2,6 +2,8 @@
 import warnings
 import tasklogger
 from scipy import sparse
+import pickle
+import pygsp
 
 from . import base
 from . import graphs
@@ -283,3 +285,22 @@ def from_igraph(G, attribute="weight", **kwargs):
         K = G.get_adjacency(attribute=None).data
     return Graph(sparse.coo_matrix(K),
                  precomputed='adjacency', **kwargs)
+
+
+def read_pickle(path):
+    """Load pickled Graphtools object (or any object) from file.
+
+    Parameters
+    ----------
+    path : str
+        File path where the pickled object will be loaded.
+    """
+    with open(path, 'rb') as f:
+        G = pickle.load(f)
+
+    if not isinstance(G, base.BaseGraph):
+        warnings.warn(
+            'Returning object that is not a graphtools.base.BaseGraph')
+    elif isinstance(G, base.PyGSPGraph) and isinstance(G.logger, str):
+        G.logger = pygsp.utils.build_logger(G.logger)
+    return G

graphtools/base.py

@@ -3,14 +3,15 @@
 import numpy as np
 import abc
 import pygsp
-from sklearn.utils.fixes import signature
+from inspect import signature
 from sklearn.decomposition import PCA, TruncatedSVD
 from sklearn.preprocessing import normalize
-from sklearn.utils.graph import graph_shortest_path
 from scipy import sparse
 import warnings
 import numbers
 import tasklogger
+import pickle
+import sys
 
 try:
     import pandas as pd
@@ -106,10 +107,10 @@ class Data(Base):
     def __init__(self, data, n_pca=None, random_state=None, **kwargs):
 
         self._check_data(data)
-        if n_pca is not None and data.shape[1] <= n_pca:
+        if n_pca is not None and np.min(data.shape) <= n_pca:
             warnings.warn("Cannot perform PCA to {} dimensions on "
-                          "data with {} dimensions".format(n_pca,
-                                                           data.shape[1]),
+                          "data with min(n_samples, n_features) = {}".format(
+                              n_pca, np.min(data.shape)),
                           RuntimeWarning)
             n_pca = None
         try:
@@ -316,7 +317,7 @@ class BaseGraph(with_metaclass(abc.ABCMeta, Base)):
         'theta' : min-max
         'none' : no symmetrization
 
-    theta: float (default: 0.5)
+    theta: float (default: 1)
         Min-max symmetrization constant.
         K = `theta * min(K, K.T) + (1 - theta) * max(K, K.T)`
 
@@ -385,7 +386,7 @@ def _check_symmetrization(self, kernel_symm, theta):
             if theta is None:
                 warnings.warn("kernel_symm='theta' but theta not given. "
                               "Defaulting to theta=0.5.")
-                self.theta = theta = 0.5
+                self.theta = theta = 1
             elif not isinstance(theta, numbers.Number) or \
                     theta < 0 or theta > 1:
                 raise ValueError("theta {} not recognized. Expected "
@@ -636,6 +637,23 @@ def to_igraph(self, attribute="weight", **kwargs):
         return ig.Graph.Weighted_Adjacency(utils.to_dense(W).tolist(),
                                            attr=attribute, **kwargs)
 
+    def to_pickle(self, path):
+        """Save the current Graph to a pickle.
+
+        Parameters
+        ----------
+        path : str
+            File path where the pickled object will be stored.
+        """
+        if int(sys.version.split(".")[1]) < 7 and isinstance(self, pygsp.graphs.Graph):
+            # python 3.5, 3.6
+            logger = self.logger
+            self.logger = logger.name
+        with open(path, 'wb') as f:
+            pickle.dump(self, f)
+        if int(sys.version.split(".")[1]) < 7 and isinstance(self, pygsp.graphs.Graph):
+            self.logger = logger
+
 
 class PyGSPGraph(with_metaclass(abc.ABCMeta, pygsp.graphs.Graph, Base)):
     """Interface between BaseGraph and PyGSP.

graphtools/graphs.py

@@ -14,8 +14,6 @@
 import tasklogger
 
 from .utils import (set_diagonal,
-                    elementwise_minimum,
-                    elementwise_maximum,
                     set_submatrix)
 from .base import DataGraph, PyGSPGraph
 
@@ -245,7 +243,7 @@ def _check_duplicates(self, distances, indices):
                     "Detected zero distance between {} pairs of samples. "
                     "Consider removing duplicates to avoid errors in "
                     "downstream processing.".format(
-                        np.sum(np.sum(distances[:, 1:]))),
+                        np.sum(np.sum(distances[:, 1:] == 0))),
                     RuntimeWarning)
 
     def build_kernel_to_data(self, Y, knn=None, bandwidth=None,

graphtools/version.py

@@ -1 +1 @@
-__version__ = "1.0.0"
+__version__ = "1.1.0"

test/test_api.py

@@ -9,6 +9,8 @@
 import igraph
 import numpy as np
 import graphtools
+import tempfile
+import os
 
 
 def test_from_igraph():
@@ -81,6 +83,56 @@ def test_to_igraph():
         attribute="weight").data) == G.W)
 
 
+def test_pickle_io_knngraph():
+    G = build_graph(data, knn=5, decay=None)
+    with tempfile.TemporaryDirectory() as tempdir:
+        path = os.path.join(tempdir, 'tmp.pkl')
+        G.to_pickle(path)
+        G_prime = graphtools.read_pickle(path)
+    assert isinstance(G_prime, type(G))
+
+
+def test_pickle_io_traditionalgraph():
+    G = build_graph(data, knn=5, decay=10, thresh=0)
+    with tempfile.TemporaryDirectory() as tempdir:
+        path = os.path.join(tempdir, 'tmp.pkl')
+        G.to_pickle(path)
+        G_prime = graphtools.read_pickle(path)
+    assert isinstance(G_prime, type(G))
+
+
+def test_pickle_io_landmarkgraph():
+    G = build_graph(data, knn=5, decay=None,
+                    n_landmark=data.shape[0] // 2)
+    L = G.landmark_op
+    with tempfile.TemporaryDirectory() as tempdir:
+        path = os.path.join(tempdir, 'tmp.pkl')
+        G.to_pickle(path)
+        G_prime = graphtools.read_pickle(path)
+    assert isinstance(G_prime, type(G))
+    np.testing.assert_array_equal(L, G_prime._landmark_op)
+
+
+def test_pickle_io_pygspgraph():
+    G = build_graph(data, knn=5, decay=None, use_pygsp=True)
+    with tempfile.TemporaryDirectory() as tempdir:
+        path = os.path.join(tempdir, 'tmp.pkl')
+        G.to_pickle(path)
+        G_prime = graphtools.read_pickle(path)
+    assert isinstance(G_prime, type(G))
+    assert G_prime.logger.name == G.logger.name
+
+
+@warns(UserWarning)
+def test_pickle_bad_pickle():
+    import pickle
+    with tempfile.TemporaryDirectory() as tempdir:
+        path = os.path.join(tempdir, 'tmp.pkl')
+        with open(path, 'wb') as f:
+            pickle.dump('hello world', f)
+        G = graphtools.read_pickle(path)
+
+
 @warns(UserWarning)
 def test_to_pygsp_invalid_precomputed():
     G = build_graph(data)

test/test_data.py

@@ -44,6 +44,12 @@ def test_too_many_n_pca():
     build_graph(data, n_pca=data.shape[1])
 
 
+@warns(RuntimeWarning)
+def test_too_many_n_pca():
+    build_graph(data[:data.shape[1] - 1],
+                n_pca=data.shape[1] - 1)
+
+
 @warns(RuntimeWarning)
 def test_precomputed_with_pca():
     build_graph(squareform(pdist(data)),