numpy is now a hard dependency. persistence_intervals_in_dimension and read_persistence_intervals_in_dimension now returns a numpy array of dimension 2 (list of [birth, death]).

7 files changed, 64 insertions, 54 deletions

diff --git a/src/cython/cython/cubical_complex.pyx b/src/cython/cython/cubical_complex.pyx
index e94cd539..53d79b92 100644
--- a/src/cython/cython/cubical_complex.pyx
+++ b/src/cython/cython/cubical_complex.pyx
@@ -5,13 +5,15 @@ from libcpp.string cimport string
 from libcpp cimport bool
 import os
 
+from numpy import array as np_array
+
 """This file is part of the Gudhi Library. The Gudhi library
    (Geometric Understanding in Higher Dimensions) is a generic C++
    library for computational topology.
 
    Author(s):       Vincent Rouvreau
 
-   Copyright (C) 2016 Inria
+   Copyright (C) 2019 Inria
 
    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
@@ -182,9 +184,9 @@ cdef class CubicalComplex:
         specific dimension.
 
         :param dimension: The specific dimension.
-        :type from_value: int.
+        :type dimension: int.
         :returns: The persistence intervals.
-        :rtype:  list of pair of float
+        :rtype:  numpy array of dimension 2
 
         :note: intervals_in_dim function requires persistence function to be
             launched first.
@@ -195,4 +197,4 @@ cdef class CubicalComplex:
         else:
             print("intervals_in_dim function requires persistence function"
                   " to be launched first.")
-        return intervals_result
+        return np_array(intervals_result)
diff --git a/src/cython/cython/periodic_cubical_complex.pyx b/src/cython/cython/periodic_cubical_complex.pyx
index e626950b..3866f53b 100644
--- a/src/cython/cython/periodic_cubical_complex.pyx
+++ b/src/cython/cython/periodic_cubical_complex.pyx
@@ -5,13 +5,15 @@ from libcpp.string cimport string
 from libcpp cimport bool
 import os
 
+from numpy import array as np_array
+
 """This file is part of the Gudhi Library. The Gudhi library
    (Geometric Understanding in Higher Dimensions) is a generic C++
    library for computational topology.
 
    Author(s):       Vincent Rouvreau
 
-   Copyright (C) 2016 Inria
+   Copyright (C) 2019 Inria
 
    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
@@ -184,9 +186,9 @@ cdef class PeriodicCubicalComplex:
         specific dimension.
 
         :param dimension: The specific dimension.
-        :type from_value: int.
+        :type dimension: int.
         :returns: The persistence intervals.
-        :rtype:  list of pair of float
+        :rtype:  numpy array of dimension 2
 
         :note: intervals_in_dim function requires persistence function to be
             launched first.
@@ -197,4 +199,4 @@ cdef class PeriodicCubicalComplex:
         else:
             print("intervals_in_dim function requires persistence function"
                   " to be launched first.")
-        return intervals_result
+        return np_array(intervals_result)
diff --git a/src/cython/cython/persistence_graphical_tools.py b/src/cython/cython/persistence_graphical_tools.py
index d7be936f..98cd355c 100644
--- a/src/cython/cython/persistence_graphical_tools.py
+++ b/src/cython/cython/persistence_graphical_tools.py
@@ -1,10 +1,14 @@
+from os import path
+from math import isfinite
+import numpy as np
+
 """This file is part of the Gudhi Library. The Gudhi library
    (Geometric Understanding in Higher Dimensions) is a generic C++
    library for computational topology.
 
    Author(s):       Vincent Rouvreau, Bertrand Michel
 
-   Copyright (C) 2016 Inria
+   Copyright (C) 2019 Inria
 
    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
@@ -85,11 +89,9 @@ def plot_persistence_barcode(persistence=[], persistence_file='', alpha=0.6,
     try:
         import matplotlib.pyplot as plt
         import matplotlib.patches as mpatches
-        import numpy as np
-        import os
 
         if persistence_file is not '':
-            if os.path.isfile(persistence_file):
+            if path.isfile(persistence_file):
                 # Reset persistence
                 persistence = []
                 diag = read_persistence_intervals_grouped_by_dimension(persistence_file=persistence_file)
@@ -144,7 +146,7 @@ def plot_persistence_barcode(persistence=[], persistence_file='', alpha=0.6,
         return plt
 
     except ImportError:
-        print("This function is not available, you may be missing numpy and/or matplotlib.")
+        print("This function is not available, you may be missing matplotlib.")
 
 def plot_persistence_diagram(persistence=[], persistence_file='', alpha=0.6,
         band=0., max_intervals=1000, max_plots=1000, inf_delta=0.1, legend=False):
@@ -177,11 +179,9 @@ def plot_persistence_diagram(persistence=[], persistence_file='', alpha=0.6,
     try:
         import matplotlib.pyplot as plt
         import matplotlib.patches as mpatches
-        import numpy as np
-        import os
 
         if persistence_file is not '':
-            if os.path.isfile(persistence_file):
+            if path.isfile(persistence_file):
                 # Reset persistence
                 persistence = []
                 diag = read_persistence_intervals_grouped_by_dimension(persistence_file=persistence_file)
@@ -240,7 +240,7 @@ def plot_persistence_diagram(persistence=[], persistence_file='', alpha=0.6,
         return plt
 
     except ImportError:
-        print("This function is not available, you may be missing numpy and/or matplotlib.")
+        print("This function is not available, you may be missing matplotlib.")
 
 def plot_persistence_density(persistence=[], persistence_file='',
                              nbins=300, bw_method=None,
@@ -288,13 +288,10 @@ def plot_persistence_density(persistence=[], persistence_file='',
     """
     try:
         import matplotlib.pyplot as plt
-        import numpy as np
         from scipy.stats import kde
-        import os
-        import math
 
         if persistence_file is not '':
-            if os.path.isfile(persistence_file):
+            if path.isfile(persistence_file):
                 # Reset persistence
                 persistence = []
                 diag = read_persistence_intervals_grouped_by_dimension(persistence_file=persistence_file)
@@ -318,8 +315,8 @@ def plot_persistence_density(persistence=[], persistence_file='',
                                  reverse=True)[:max_intervals]
 
         # Set as numpy array birth and death (remove undefined values - inf and NaN)
-        birth = np.asarray([(interval[1][0]) for interval in persistence_dim if (math.isfinite(interval[1][1]) and math.isfinite(interval[1][0]))])
-        death = np.asarray([(interval[1][1]) for interval in persistence_dim if (math.isfinite(interval[1][1]) and math.isfinite(interval[1][0]))])
+        birth = np.asarray([(interval[1][0]) for interval in persistence_dim if (isfinite(interval[1][1]) and isfinite(interval[1][0]))])
+        death = np.asarray([(interval[1][1]) for interval in persistence_dim if (isfinite(interval[1][1]) and isfinite(interval[1][0]))])
 
         # line display of equation : birth = death
         x = np.linspace(death.min(), birth.max(), 1000)
@@ -345,4 +342,4 @@ def plot_persistence_density(persistence=[], persistence_file='',
         return plt
 
     except ImportError:
-        print("This function is not available, you may be missing numpy, matplotlib and/or scipy.")
+        print("This function is not available, you may be missing matplotlib and/or scipy.")
diff --git a/src/cython/cython/reader_utils.pyx b/src/cython/cython/reader_utils.pyx
index e4572db0..6dde5286 100644
--- a/src/cython/cython/reader_utils.pyx
+++ b/src/cython/cython/reader_utils.pyx
@@ -3,7 +3,9 @@ from libcpp.vector cimport vector
 from libcpp.string cimport string
 from libcpp.map cimport map
 from libcpp.pair cimport pair
-import os
+
+from os import path
+from numpy import array as np_array
 
 """This file is part of the Gudhi Library. The Gudhi library
    (Geometric Understanding in Higher Dimensions) is a generic C++
@@ -11,7 +13,7 @@ import os
 
    Author(s):       Vincent Rouvreau
 
-   Copyright (C) 2017 Inria
+   Copyright (C) 2019 Inria
 
    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
@@ -48,7 +50,7 @@ def read_lower_triangular_matrix_from_csv_file(csv_file='', separator=';'):
     :rtype: vector[vector[double]]
     """
     if csv_file is not '':
-        if os.path.isfile(csv_file):
+        if path.isfile(csv_file):
             return read_matrix_from_csv_file(str.encode(csv_file), ord(separator[0]))
     print("file " + csv_file + " not set or not found.")
     return []
@@ -67,29 +69,31 @@ def read_persistence_intervals_grouped_by_dimension(persistence_file=''):
     :rtype: map[int, vector[pair[double, double]]]
     """
     if persistence_file is not '':
-        if os.path.isfile(persistence_file):
+        if path.isfile(persistence_file):
             return read_pers_intervals_grouped_by_dimension(str.encode(persistence_file))
     print("file " + persistence_file + " not set or not found.")
     return []
 
 def read_persistence_intervals_in_dimension(persistence_file='', only_this_dim=-1):
     """Reads a file containing persistence intervals.
-    Each line might contain 2, 3 or 4 values: [[field] dimension] birth death
-    If `only_this_dim` = -1, dimension is ignored and all lines are returned.
-    If `only_this_dim` is >= 0, only the lines where dimension = `only_this_dim`
-    (or where dimension is not specified) are returned.
-    The return value is an `vector[pair[birth, death]]`
-    where `birth` a `double`, and `death` a `double`.
+    Each line of persistence_file might contain 2, 3 or 4 values:
+    [[field] dimension] birth death
     Note: the function does not check that birth <= death.
 
     :param persistence_file: A persistence file style name.
     :type persistence_file: string
-
-    :returns:  The persistence pairs grouped by dimension.
-    :rtype: map[int, vector[pair[double, double]]]
+    :param only_this_dim: The specific dimension. Default value is -1.
+        If `only_this_dim` = -1, dimension is ignored and all lines are returned.
+        If `only_this_dim` is >= 0, only the lines where dimension =
+        `only_this_dim` (or where dimension is not specified) are returned.
+    :type only_this_dim: int.
+
+    :returns:  The persistence intervals.
+    :rtype: numpy array of dimension 2
     """
     if persistence_file is not '':
-        if os.path.isfile(persistence_file):
-            return read_pers_intervals_in_dimension(str.encode(persistence_file), only_this_dim)
+        if path.isfile(persistence_file):
+            return np_array(read_pers_intervals_in_dimension(str.encode(
+                persistence_file), only_this_dim))
     print("file " + persistence_file + " not set or not found.")
     return []
diff --git a/src/cython/cython/simplex_tree.pyx b/src/cython/cython/simplex_tree.pyx
index 0ab97f80..ee04589e 100644
--- a/src/cython/cython/simplex_tree.pyx
+++ b/src/cython/cython/simplex_tree.pyx
@@ -4,13 +4,15 @@ from libcpp.utility cimport pair
 from libcpp cimport bool
 from libcpp.string cimport string
 
+from numpy import array as np_array
+
 """This file is part of the Gudhi Library. The Gudhi library
    (Geometric Understanding in Higher Dimensions) is a generic C++
    library for computational topology.
 
    Author(s):       Vincent Rouvreau
 
-   Copyright (C) 2016 Inria
+   Copyright (C) 2019 Inria
 
    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
@@ -498,7 +500,7 @@ cdef class SimplexTree:
         :param dimension: The specific dimension.
         :type dimension: int.
         :returns: The persistence intervals.
-        :rtype:  list of pair of float
+        :rtype:  numpy array of dimension 2
 
         :note: intervals_in_dim function requires
             :func:`persistence()<gudhi.SimplexTree.persistence>`
@@ -510,7 +512,7 @@ cdef class SimplexTree:
         else:
             print("intervals_in_dim function requires persistence function"
                   " to be launched first.")
-        return intervals_result
+        return np_array(intervals_result)
 
     def persistence_pairs(self):
         """This function returns the persistence pairs of the simplicial
diff --git a/src/cython/setup.py.in b/src/cython/setup.py.in
index 4037aab6..c66905ac 100644
--- a/src/cython/setup.py.in
+++ b/src/cython/setup.py.in
@@ -1,5 +1,6 @@
 from distutils.core import setup, Extension
 from Cython.Build import cythonize
+from numpy import get_include as numpy_get_include
 
 """This file is part of the Gudhi Library. The Gudhi library
    (Geometric Understanding in Higher Dimensions) is a generic C++
@@ -7,7 +8,7 @@ from Cython.Build import cythonize
 
    Author(s):       Vincent Rouvreau
 
-   Copyright (C) 2016  Inria
+   Copyright (C) 2019  Inria
 
    This program is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
@@ -35,7 +36,7 @@ gudhi = Extension(
     extra_link_args=[@GUDHI_CYTHON_EXTRA_LINK_ARGS@],
     libraries=[@GUDHI_CYTHON_LIBRARIES@],
     library_dirs=[@GUDHI_CYTHON_LIBRARY_DIRS@],
-    include_dirs = [@GUDHI_CYTHON_INCLUDE_DIRS@],
+    include_dirs = [numpy_get_include(), @GUDHI_CYTHON_INCLUDE_DIRS@],
     runtime_library_dirs=[@GUDHI_CYTHON_RUNTIME_LIBRARY_DIRS@],
 )
 
@@ -46,5 +47,6 @@ setup(
     version='@GUDHI_VERSION@',
     url='http://gudhi.gforge.inria.fr/',
     ext_modules = cythonize(gudhi),
-    install_requires = ["cython",],
+    install_requires = ['cython','numpy >= 1.9',],
+    setup_requires = ['numpy >= 1.9',],
 )
diff --git a/src/cython/test/test_reader_utils.py b/src/cython/test/test_reader_utils.py
index b240c84f..36e927b0 100755
--- a/src/cython/test/test_reader_utils.py
+++ b/src/cython/test/test_reader_utils.py
@@ -1,4 +1,5 @@
 import gudhi
+import numpy as np
 
 """This file is part of the Gudhi Library. The Gudhi library
    (Geometric Understanding in Higher Dimensions) is a generic C++
@@ -53,7 +54,7 @@ def test_non_existing_persistence_file():
     persistence = gudhi.read_persistence_intervals_grouped_by_dimension(persistence_file='pouetpouettralala.toubiloubabdou')
     assert persistence == []
     persistence = gudhi.read_persistence_intervals_in_dimension(persistence_file='pouetpouettralala.toubiloubabdou', only_this_dim=1)
-    assert persistence == []
+    np.testing.assert_array_equal(persistence, [])
 
 def test_read_persistence_intervals_without_dimension():
     # Create test file
@@ -61,11 +62,11 @@ def test_read_persistence_intervals_without_dimension():
     test_file.write('# Simple persistence diagram without dimension\n2.7 3.7\n9.6 14.\n34.2 34.974\n3. inf')
     test_file.close()
     persistence = gudhi.read_persistence_intervals_in_dimension(persistence_file='persistence_intervals_without_dimension.pers')
-    assert persistence == [(2.7, 3.7), (9.6, 14.), (34.2, 34.974), (3., float('Inf'))]
+    np.testing.assert_array_equal(persistence, [(2.7, 3.7), (9.6, 14.), (34.2, 34.974), (3., float('Inf'))])
     persistence = gudhi.read_persistence_intervals_in_dimension(persistence_file='persistence_intervals_without_dimension.pers', only_this_dim=0)
-    assert persistence == []
+    np.testing.assert_array_equal(persistence, [])
     persistence = gudhi.read_persistence_intervals_in_dimension(persistence_file='persistence_intervals_without_dimension.pers', only_this_dim=1)
-    assert persistence == []
+    np.testing.assert_array_equal(persistence, [])
     persistence = gudhi.read_persistence_intervals_grouped_by_dimension(persistence_file='persistence_intervals_without_dimension.pers')
     assert persistence == {-1: [(2.7, 3.7), (9.6, 14.0), (34.2, 34.974), (3.0, float('Inf'))]}
 
@@ -75,14 +76,14 @@ def test_read_persistence_intervals_with_dimension():
     test_file.write('# Simple persistence diagram with dimension\n0 2.7 3.7\n1 9.6 14.\n3 34.2 34.974\n1 3. inf')
     test_file.close()
     persistence = gudhi.read_persistence_intervals_in_dimension(persistence_file='persistence_intervals_with_dimension.pers')
-    assert persistence == [(2.7, 3.7), (9.6, 14.), (34.2, 34.974), (3., float('Inf'))]
+    np.testing.assert_array_equal(persistence, [(2.7, 3.7), (9.6, 14.), (34.2, 34.974), (3., float('Inf'))])
     persistence = gudhi.read_persistence_intervals_in_dimension(persistence_file='persistence_intervals_with_dimension.pers', only_this_dim=0)
-    assert persistence == [(2.7, 3.7)]
+    np.testing.assert_array_equal(persistence, [(2.7, 3.7)])
     persistence = gudhi.read_persistence_intervals_in_dimension(persistence_file='persistence_intervals_with_dimension.pers', only_this_dim=1)
-    assert persistence == [(9.6, 14.), (3., float('Inf'))]
+    np.testing.assert_array_equal(persistence, [(9.6, 14.), (3., float('Inf'))])
     persistence = gudhi.read_persistence_intervals_in_dimension(persistence_file='persistence_intervals_with_dimension.pers', only_this_dim=2)
-    assert persistence == []
+    np.testing.assert_array_equal(persistence, [])
     persistence = gudhi.read_persistence_intervals_in_dimension(persistence_file='persistence_intervals_with_dimension.pers', only_this_dim=3)
-    assert persistence == [(34.2, 34.974)]
+    np.testing.assert_array_equal(persistence, [(34.2, 34.974)])
     persistence = gudhi.read_persistence_intervals_grouped_by_dimension(persistence_file='persistence_intervals_with_dimension.pers')
     assert persistence == {0: [(2.7, 3.7)], 1: [(9.6, 14.0), (3.0, float('Inf'))], 3: [(34.2, 34.974)]}