Release v0.4.4 (#63)

* Prepare v0.4.4 (#62) * Bump version to 0.4.4, update code authors, and write release notes * Replace deprecated np.bool and np.float with bool and float builtins * Use np.floating instead of np.float_ to cover other floats than 64-bit * [CI] Remove unnecessary pip install wheel Co-authored-by: flomlo <[email protected]>
giotto-ai · Feb 12, 2021 · 02dcf26 · 02dcf26
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diff --git a/CODE_AUTHORS b/CODE_AUTHORS
@@ -4,3 +4,4 @@
 Guillaume Tauzin, [email protected]
 Julian Burella Pérez, [email protected]
 Umberto Lupo, [email protected]
+Florian Unger, [email protected]
diff --git a/RELEASE.rst b/RELEASE.rst
@@ -1,3 +1,31 @@
+Release 0.4.4
+=============
+
+Major Features and Improvements
+-------------------------------
+
+None.
+
+Bug Fixes
+---------
+
+A fatal error in ``save_unweighted_flag`` has been fixed (Florian Unger).
+
+Backwards-Incompatible Changes
+------------------------------
+
+None.
+
+Thanks to our Contributors
+--------------------------
+
+This release contains contributions from:
+
+Florian Unger and Umberto Lupo.
+
+We are also grateful to all who filed issues or helped resolve them, asked and answered questions, and were part of inspiring discussions.
+
+
 Release 0.4.3
 =============
 

diff --git a/azure-pipelines.yml b/azure-pipelines.yml
@@ -116,7 +116,6 @@ jobs:
     displayName: 'Uninstall pyflagser dev'
 
   - script: |
-      pip install wheel
       python setup.py bdist_wheel
     failOnStderr: false
     displayName: 'Build the wheels'
@@ -214,7 +213,6 @@ jobs:
 
   - bash: |
       sed -i $'s/\r$//' README.rst
-      pip install wheel
       python setup.py bdist_wheel
     failOnStderr: false
     displayName: 'Build the wheels'

diff --git a/pyflagser/_utils.py b/pyflagser/_utils.py
@@ -14,7 +14,7 @@ def _extract_unweighted_graph(adjacency_matrix):
 
     # Extract vertices and give them weight one
     n_vertices = max(input_shape)
-    vertices = np.ones(n_vertices, dtype=np.float)
+    vertices = np.ones(n_vertices, dtype=float)
 
     # Extract edge indices
     if isinstance(adjacency_matrix, np.ndarray):
@@ -71,7 +71,7 @@ def _extract_weighted_graph(adjacency_matrix, max_edge_weight):
         mask = row != column
 
     # Mask infinite or thresholded weights
-    if np.issubdtype(adjacency_matrix.dtype, np.float_):
+    if np.issubdtype(adjacency_matrix.dtype, np.floating):
         if (max_edge_weight is None) or np.isposinf(max_edge_weight):
             mask = np.logical_and(mask, np.isfinite(data))
         else:

diff --git a/pyflagser/_version.py b/pyflagser/_version.py
@@ -17,4 +17,4 @@
 # 'X.Y.dev0' is the canonical version of 'X.Y.dev'
 #
 
-__version__ = '0.4.3'
+__version__ = '0.4.4'
diff --git a/pyflagser/flagio.py b/pyflagser/flagio.py
@@ -7,7 +7,7 @@
 from ._utils import _extract_unweighted_graph, _extract_weighted_graph
 
 
-def load_unweighted_flag(fname, fmt='csr', dtype=np.bool):
+def load_unweighted_flag(fname, fmt='csr', dtype=bool):
     """Load a ``.flag`` file and return the adjacency matrix of the
     directed/undirected unweighted graph it describes.
 
@@ -23,7 +23,7 @@ def load_unweighted_flag(fname, fmt='csr', dtype=np.bool):
         returned. Keep in mind that some matrix formats do not track zero
         values.
 
-    dtype : data-type, optional, default: ``np.bool``
+    dtype : data-type, optional, default: ``bool``
         Data-type of the resulting array.
 
     Returns
@@ -65,7 +65,7 @@ def load_unweighted_flag(fname, fmt='csr', dtype=np.bool):
     return adjacency_matrix.asformat(fmt)
 
 
-def load_weighted_flag(fname, fmt='csr', dtype=np.float, infinity_value=None):
+def load_weighted_flag(fname, fmt='csr', dtype=float, infinity_value=None):
     """Load a ``.flag`` file and return the adjacency matrix of the
     directed/undirected weighted graph it describes.
 
@@ -81,7 +81,7 @@ def load_weighted_flag(fname, fmt='csr', dtype=np.float, infinity_value=None):
         returned. Keep in mind that some matrix formats do not track zero
         values.
 
-    dtype : data-type, optional, default: ``np.float``
+    dtype : data-type, optional, default: ``float``
         Data-type of the resulting array.
 
     infinity_value : int or float or None, optional, default: ``None``
@@ -122,7 +122,7 @@ def load_weighted_flag(fname, fmt='csr', dtype=np.float, infinity_value=None):
             # Get the maximum value depending on adjacency_matrix.dtype
             if np.issubdtype(dtype, np.integer):
                 _infinity_value = np.iinfo(dtype).max
-            elif np.issubdtype(dtype, np.float_):
+            elif np.issubdtype(dtype, np.floating):
                 _infinity_value = np.inf
             else:
                 _infinity_value = 0
@@ -191,9 +191,9 @@ def save_unweighted_flag(fname, adjacency_matrix):
     vertices, edges = _extract_unweighted_graph(adjacency_matrix)
 
     with open(fname, 'w') as f:
-        np.savetxt(f, vertices, delimiter=' ', comments='', header='dim 0',
-                   fmt='%.18e')
-        np.savetxt(f, edges, comments='', header='dim 1', fmt='%i %i')
+        np.savetxt(f, vertices.reshape((1, -1)), delimiter=' ', header='dim 0',
+                   fmt='%i')
+        np.savetxt(f, edges, comments='', header='dim 1', fmt='%i %i %i')
 
 
 def save_weighted_flag(fname, adjacency_matrix, max_edge_weight=None):

diff --git a/pyflagser/tests/test_flagio.py b/pyflagser/tests/test_flagio.py
@@ -7,7 +7,7 @@
 from numpy.testing import assert_almost_equal
 
 from pyflagser import load_unweighted_flag, load_weighted_flag, \
-    save_weighted_flag
+    save_weighted_flag, save_unweighted_flag
 from pyflagser._utils import _extract_unweighted_graph, \
     _extract_weighted_graph
 
@@ -34,3 +34,15 @@ def test_weighted(flag_file_small, max_edge_length):
     os.remove(fname_temp)
     assert_almost_equal(vertices_a, vertices_a)
     assert_almost_equal(edges_b, edges_b)
+
+
+def test_unweighted(flag_file_small):
+    adjacency_matrix = load_unweighted_flag(flag_file_small)
+    vertices_a, edges_a = _extract_unweighted_graph(adjacency_matrix)
+    fname_temp = os.path.split(flag_file_small)[1]
+    save_unweighted_flag(fname_temp, adjacency_matrix)
+    adjacency_matrix = load_unweighted_flag(fname_temp)
+    vertices_b, edges_b = _extract_unweighted_graph(adjacency_matrix)
+    os.remove(fname_temp)
+    assert_almost_equal(vertices_a, vertices_a)
+    assert_almost_equal(edges_b, edges_b)
diff --git a/setup.py b/setup.py
@@ -28,7 +28,7 @@
 MAINTAINER_EMAIL = '[email protected]'
 URL = 'https://github.com/giotto-ai/pyflagser'
 LICENSE = 'GNU AGPLv3'
-DOWNLOAD_URL = 'https://github.com/giotto-ai/pyflagser/tarball/v0.4.3'
+DOWNLOAD_URL = 'https://github.com/giotto-ai/pyflagser/tarball/v0.4.4'
 VERSION = __version__ # noqa
 CLASSIFIERS = ['Intended Audience :: Science/Research',
                'Intended Audience :: Developers',