Another time when I hit the problem with compilation, and fail to solve it...

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/persistence_representation_integration@2647 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: e6a0101ab3bd96031dd9fa23e8db629f65820271

7 files changed, 128 insertions, 16 deletions

diff --git a/src/cython/cython/persistence_representations_intervals.pyx b/src/cython/cython/persistence_representations_intervals.pyx
index 42370870..c1cc347d 100644
--- a/src/cython/cython/persistence_representations_intervals.pyx
+++ b/src/cython/cython/persistence_representations_intervals.pyx
@@ -259,8 +259,7 @@ cdef class PersistenceIntervals:
             return self.thisptr.cumulative_characteristic_function_of_diagram(x_min, x_max, number_of_bins)
         else:
             if (self.thisptr != NULL) and (x_min is not None) and (x_max is not None):
-                return
-                self.thisptr.cumulative_characteristic_function_of_diagram(x_min, x_max, 10)
+                return self.thisptr.cumulative_characteristic_function_of_diagram(x_min, x_max, 10)
 
     def compute_persistent_betti_numbers(self):
         """
diff --git a/src/cython/cython/persistence_representations_landscapes.pyx b/src/cython/cython/persistence_representations_landscapes.pyx
index 9c3c2863..035c7d58 100644
--- a/src/cython/cython/persistence_representations_landscapes.pyx
+++ b/src/cython/cython/persistence_representations_landscapes.pyx
@@ -133,7 +133,8 @@ cdef class PersistenceLandscapes:
             self.thisptr = new Persistence_landscape_interface(vector_of_intervals, number_of_levels)
         else:
             print("Persistence interals can be constructed from vector of birth-death pairs,  vector_of_intervals or a Gudhi-style file.")                     
-
+            self.thisptr = new Persistence_landscape_interface()
+            
     def __dealloc__(self):
         """
         destructor
@@ -321,6 +322,7 @@ cdef class PersistenceLandscapes:
         :param vector of persistence landscapes to average
         :type vectors of references to persistence landscapes
         """            
+        #TODO -- add a check if all objects in the to_average are of the same type. 
         cdef vector[Persistence_landscape_interface*] cpp_list    
         if ( self.thisptr != NULL ) and ( to_average is not None ):	
             for elt in to_average: 
diff --git a/src/cython/example/persistence_representations_landscapes_example.py b/src/cython/example/persistence_representations_landscapes_example.py
index b7e47c0b..94b68225 100755
--- a/src/cython/example/persistence_representations_landscapes_example.py
+++ b/src/cython/example/persistence_representations_landscapes_example.py
@@ -53,11 +53,11 @@ print "L^1 Norm of l1 : ", l1.compute_norm_of_landscape(1.)
 print "L^1 Norm of l2 : ", l2.compute_norm_of_landscape(1.)
 
 #here is the average of landscapes:
-average = gudhi.PersistenceLandscapes
-average.compute_average([l1, l2])
+average = gudhi.PersistenceLandscapes()
+average.compute_average(to_average=[l1, l2])
 
 #here is the distance of landscapes:
-print "Distance : ", l1.distance(l2)
+print "Distance : ", l1.distance(average,1)
 
 #here is the scalar product of landscapes:
 print "Scalar product : ", l1.compute_scalar_product(l2)
diff --git a/src/cython/example/persistence_representations_landscapes_on_grid_example.py b/src/cython/example/persistence_representations_landscapes_on_grid_example.py
new file mode 100755
index 00000000..60b0e873
--- /dev/null
+++ b/src/cython/example/persistence_representations_landscapes_on_grid_example.py
@@ -0,0 +1,110 @@
+#!/usr/bin/env python
+
+import gudhi
+
+
+"""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):       Pawel Dlotko
+
+   Copyright (C) 2017 Swansea University
+
+   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
+   the Free Software Foundation, either version 3 of the License, or
+   (at your option) any later version.
+
+   This program is distributed in the hope that it will be useful,
+   but WITHOUT ANY WARRANTY; without even the implied warranty of
+   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+   GNU General Public License for more details.
+
+   You should have received a copy of the GNU General Public License
+   along with this program.  If not, see <http://www.gnu.org/licenses/>.
+"""
+
+__author__ = "Pawel Dlotko"
+__copyright__ = "Copyright (C) 2017 Swansea University"
+__license__ = "GPL v3"
+
+print("#####################################################################")
+print("Persistence representations landscapes on a grid example")
+
+persistence1 = [(1, 2),(6, 8),(0, 4),(3, 8)]
+persistence2 = [(2, 9),(1, 6),(3, 5),(6, 10)]
+
+#create two persistence landscapes based on persistence1 and persistence2:
+l1 = PersistenceLandscapeOnGrid(persistence1, 0, 11, 20)
+l2 = PersistenceLandscapeOnGrid(persistence2, 0, 11, 20)
+
+#This is how to compute integral of landscapes:
+print "Integral of the first landscape : " , l1.compute_integral_of_landscape() 
+print "Integral of the second landscape : " , l2.compute_integral_of_landscape() 
+
+#here are the maxima of the functions:
+print "Maximum of l1 : " , l1.compute_maximum() 
+print "Maximum of l2 : " , l2.compute_maximum() 
+
+#here are the norms of landscapes:
+print "L^1 Norm of l1 : " , l1.compute_norm_of_landscape(1.) 
+print "L^1 Norm of l2 : " , l2.compute_norm_of_landscape(1.) 
+
+#here is the average of landscapes:
+average = PersistenceLandscapeOnGrid();
+average.compute_average(to_average=[l1, l2]);
+
+
+#here is the distance of landscapes:
+print "Distance : " , l1.distance(l2) 
+
+#here is the scalar product of landscapes:
+print "Scalar product : " , l1.compute_scalar_product(l2) 
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+persistence1 = [(1,2),(6,8),(0,4),(3,8)]
+persistence2 = [(2,9),(1,6),(3,5),(6,10)]
+
+
+#create two persistence landscapes based on persistence1 and persistence2:
+l1 = gudhi.PersistenceLandscapes(vector_of_intervals=persistence1, dimension=3)
+l2 = gudhi.PersistenceLandscapes(vector_of_intervals=persistence2)
+
+#This is how to compute integral of landscapes:
+print "Integral of the first landscape : ", l1.compute_integral_of_landscape()
+print "Integral of the second landscape : ", l2.compute_integral_of_landscape()
+
+#here are the maxima of the functions:
+print "Maximum of l1 : ", l1.compute_maximum()
+print "Maximum of l2 : ", l2.compute_maximum()
+
+#here are the norms of landscapes:
+print "L^1 Norm of l1 : ", l1.compute_norm_of_landscape(1.)
+print "L^1 Norm of l2 : ", l2.compute_norm_of_landscape(1.)
+
+#here is the average of landscapes:
+average = gudhi.PersistenceLandscapes()
+average.compute_average(to_average=[l1, l2])
+
+#here is the distance of landscapes:
+print "Distance : ", l1.distance(average,1)
+
+#here is the scalar product of landscapes:
+print "Scalar product : ", l1.compute_scalar_product(l2)
diff --git a/src/cython/gudhi.pyx.in b/src/cython/gudhi.pyx.in
index a6aa21aa..0fa226db 100644
--- a/src/cython/gudhi.pyx.in
+++ b/src/cython/gudhi.pyx.in
@@ -34,6 +34,7 @@ include "cython/witness_complex.pyx"
 include "cython/strong_witness_complex.pyx"
 include "cython/persistence_representations_intervals.pyx"
 include "cython/persistence_representations_landscapes.pyx"
+include "cython/persistence_representations_landscapes_on_grid.pyx"
 @GUDHI_CYTHON_ALPHA_COMPLEX@
 @GUDHI_CYTHON_EUCLIDEAN_WITNESS_COMPLEX@
 @GUDHI_CYTHON_SUBSAMPLING@
diff --git a/src/cython/test/test_persistence_representations_landscapes.py b/src/cython/test/test_persistence_representations_landscapes.py
index bf099f0f..f5e6f351 100755
--- a/src/cython/test/test_persistence_representations_landscapes.py
+++ b/src/cython/test/test_persistence_representations_landscapes.py
@@ -31,14 +31,14 @@ epsilon = 0.0000005;
 
 def test_check_construction_of_landscape():    
     p = gudhi.Persistence_landscape("data/file_with_diagram",0)
-    q = gudhi.Persistence_landscape
+    q = gudhi.Persistence_landscape()
     q.load_landscape_from_file("data/file_with_landscape_from_file_with_diagram")
     assert p == q
 
 
 def test_check_construction_of_landscape_form_gudhi_style_file():
     p = gudhi.Persistence_landscape("data/persistence_file_with_four_entries_per_line", 1)
-    q = gudhi.Persistence_landscape
+    q = gudhi.Persistence_landscape()
     q.load_landscape_from_file("data/persistence_file_with_four_entries_per_line_landscape");  
     assert p == q;
 
@@ -85,7 +85,7 @@ def test_check_computations_of_values_on_different_points():
 def test_check_computations_of_maxima_and_norms():
     diag = read_persistence_intervals_in_one_dimension_from_file("data/file_with_diagram")
     p = gudhi.Persistence_landscape(diag)
-    second = gudhi.Persistence_landscape
+    second = gudhi.Persistence_landscape()
     second.load_landscape_from_file("data/file_with_landscape_from_file_with_diagram_1")
     sum_ = gudhi.Persistence_landscape()
     sum_ = p + second;
@@ -113,9 +113,9 @@ def test_check_computations_of_averages():
     p = gudhi.Persistence_landscape(diag)
     diag2 = read_persistence_intervals_in_one_dimension_from_file("data/file_with_diagram_1")
     q = gudhi.Persistence_landscape(diag2)
-    av = gudhi.Persistence_landscape
+    av = gudhi.Persistence_landscape()
     av.compute_average({p, q})
-    template_average = Persistence_landscape
+    template_average = Persistence_landscape()
     template_averagetemplate_average.load_landscape_from_file("data/average")
     assert template_average == av
 
diff --git a/src/cython/test/test_persistence_representations_landscapes_on_grid.py b/src/cython/test/test_persistence_representations_landscapes_on_grid.py
index c03b8312..7a1f2b49 100755
--- a/src/cython/test/test_persistence_representations_landscapes_on_grid.py
+++ b/src/cython/test/test_persistence_representations_landscapes_on_grid.py
@@ -34,15 +34,15 @@ epsilon = 0.0000005;
 def test_check_construction_of_landscape:
     l = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 100,sys.maxsize)
     l.print_to_file("landscape_from_file_with_diagram_1")
-    g = gudhi.PersistenceLandscapeOnGrid
+    g = gudhi.PersistenceLandscapeOnGrid()
     g.load_landscape_from_file("landscape_from_file_with_diagram_1")
     assert l == g
 
 
 def test_check_construction_of_landscape_using_only_ten_levels:
     number = 10
-    gudhi.PersistenceLandscapeOnGrid l("data/file_with_diagram_1", 100, number)
-    gudhi.PersistenceLandscapeOnGrid g("data/file_with_diagram_1", 100, sys.maxsize)
+    l = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 100, number)
+    g = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 100, sys.maxsize)
     for level in range(0,number):
         v1 = l.vectorize(level)
         v2 = g.vectorize(level)
@@ -98,10 +98,10 @@ def test_check_default_parameters_of_distances:
 def test_check_computations_of_averages:
     p = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram", 0., 1., 100)
     q = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 0., 1., 100)
-    av = gudhi.PersistenceLandscapeOnGrid
+    av = gudhi.PersistenceLandscapeOnGrid()
     av.compute_average({&p, &q)
 
-    template_average = gudhi.PersistenceLandscapeOnGrid
+    template_average = gudhi.PersistenceLandscapeOnGrid()
     template_average.load_landscape_from_file("data/average_on_a_grid")
     assert template_average == av