Move cython directory stuff to python directory. Make example work. Fix CMake for sktda. Make sktda a submodule of gudhi package.

7 files changed, 19 insertions, 15 deletions

diff --git a/src/python/CMakeLists.txt b/src/python/CMakeLists.txt
index 9e128d30..26cd6ec1 100644
--- a/src/python/CMakeLists.txt
+++ b/src/python/CMakeLists.txt
@@ -49,6 +49,7 @@ if(PYTHONINTERP_FOUND)
     set(GUDHI_PYTHON_MODULES "${GUDHI_PYTHON_MODULES}'alpha_complex', ")
     set(GUDHI_PYTHON_MODULES "${GUDHI_PYTHON_MODULES}'euclidean_witness_complex', ")
     set(GUDHI_PYTHON_MODULES "${GUDHI_PYTHON_MODULES}'euclidean_strong_witness_complex', ")
+    set(GUDHI_PYTHON_MODULES "${GUDHI_PYTHON_MODULES}'sktda', ")
 
     add_gudhi_debug_info("Python version ${PYTHON_VERSION_STRING}")
     add_gudhi_debug_info("Cython version ${CYTHON_VERSION}")
@@ -199,6 +200,7 @@ if(PYTHONINTERP_FOUND)
 
     # Other .py files
     file(COPY "gudhi/persistence_graphical_tools.py" DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/gudhi")
+    file(COPY "gudhi/sktda" DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/gudhi/")
 
     add_custom_command(
         OUTPUT gudhi.so
diff --git a/src/cython/example/ex_diagrams.py b/src/python/example/ex_diagrams.py
index aee20245..3dc6fe84 100644
--- a/src/cython/example/ex_diagrams.py
+++ b/src/python/example/ex_diagrams.py
@@ -2,12 +2,11 @@ import matplotlib.pyplot as plt
 import numpy as np
 from sklearn.kernel_approximation import RBFSampler
 
-import sys
-sys.path.append("../sktda/")
-from preprocessing import *
-from metrics import *
-from vector_methods import *
-from kernel_methods import *
+from gudhi.sktda import Landscape, Silhouette, BettiCurve, ComplexPolynomial,\
+  TopologicalVector, DiagramScaler, BirthPersistenceTransform,\
+  PersistenceImage, PersistenceWeightedGaussianKernel,\
+  PersistenceScaleSpaceKernel, SlicedWassersteinDistance,\
+  SlicedWassersteinKernel, BottleneckDistance, PersistenceFisherKernel
 
 D = np.array([[0.,4.],[1.,2.],[3.,8.],[6.,8.]])
 plt.scatter(D[:,0],D[:,1])
@@ -44,11 +43,11 @@ TV = TopologicalVector(threshold=-1)
 tv = TV.fit_transform(diags)
 print("Topological vector is " + str(tv[0,:]))
 
-diagsT = DiagramPreprocessor(use=True, scalers=[([0,1], BirthPersistenceTransform())]).fit_transform(diags)
-PI = PersistenceImage(bandwidth=1., weight=lambda x: x[1], im_range=[0,10,0,10], resolution=[100,100])
-pi = PI.fit_transform(diagsT)
-plt.imshow(np.flip(np.reshape(pi[0], [100,100]), 0))
-plt.show()
+#diagsT = DiagramPreprocessor(use=True, scalers=[([0,1], BirthPersistenceTransform())]).fit_transform(diags)
+#PI = PersistenceImage(bandwidth=1., weight=lambda x: x[1], im_range=[0,10,0,10], resolution=[100,100])
+#pi = PI.fit_transform(diagsT)
+#plt.imshow(np.flip(np.reshape(pi[0], [100,100]), 0))
+#plt.show()
 
 plt.scatter(D[:,0],D[:,1])
 D = np.array([[1.,5.],[3.,6.],[2.,7.]])
diff --git a/src/python/gudhi/sktda/__init__.py b/src/python/gudhi/sktda/__init__.py
new file mode 100644
index 00000000..f020248d
--- /dev/null
+++ b/src/python/gudhi/sktda/__init__.py
@@ -0,0 +1,6 @@
+from .kernel_methods import *
+from .metrics import *
+from .preprocessing import *
+from .vector_methods import *
+
+__all__ = ["kernel_methods", "metrics", "preprocessing", "vector_methods"]
diff --git a/src/cython/sktda/kernel_methods.py b/src/python/gudhi/sktda/kernel_methods.py
index d90bf164..d90bf164 100644
--- a/src/cython/sktda/kernel_methods.py
+++ b/src/python/gudhi/sktda/kernel_methods.py
diff --git a/src/cython/sktda/metrics.py b/src/python/gudhi/sktda/metrics.py
index 18db432a..8092f7af 100644
--- a/src/cython/sktda/metrics.py
+++ b/src/python/gudhi/sktda/metrics.py
@@ -3,12 +3,11 @@
 All rights reserved
 """
 
-import sys
 import numpy as np
 from sklearn.base import BaseEstimator, TransformerMixin
 from sklearn.metrics import pairwise_distances
 try:
-    from gudhi import bottleneck_distance
+    from .. import bottleneck_distance
     USE_GUDHI = True
 except ImportError:
     USE_GUDHI = False
@@ -120,7 +119,6 @@ class BottleneckDistance(BaseEstimator, TransformerMixin):
 
             if USE_GUDHI:
                 for i in range(num_diag1):
-                    #sys.stdout.write( str(i*1.0 / num_diag1) + "\r")
                     for j in range(i+1, num_diag1):
                         matrix[i,j] = bottleneck_distance(X[i], X[j], self.epsilon)
                         matrix[j,i] = matrix[i,j]
@@ -133,7 +131,6 @@ class BottleneckDistance(BaseEstimator, TransformerMixin):
 
             if USE_GUDHI:
                 for i in range(num_diag1):
-                    #sys.stdout.write( str(i*1.0 / num_diag1) + "\r")
                     for j in range(num_diag2):
                         matrix[i,j] = bottleneck_distance(X[i], self.diagrams_[j], self.epsilon)
             else:
diff --git a/src/cython/sktda/preprocessing.py b/src/python/gudhi/sktda/preprocessing.py
index 512b02f3..512b02f3 100644
--- a/src/cython/sktda/preprocessing.py
+++ b/src/python/gudhi/sktda/preprocessing.py
diff --git a/src/cython/sktda/vector_methods.py b/src/python/gudhi/sktda/vector_methods.py
index 3862f815..3862f815 100644
--- a/src/cython/sktda/vector_methods.py
+++ b/src/python/gudhi/sktda/vector_methods.py