Some improvements for platform compatibility

Author: AdrienCorenflos

ot/lp/emd_wrap.pyx

@@ -157,12 +157,12 @@ def emd_1d_sorted(np.ndarray[double, ndim=1, mode="c"] u_weights,
         cost associated to the optimal transportation
     """
     cdef double cost = 0.
-    cdef int n = u_weights.shape[0]
-    cdef int m = v_weights.shape[0]
+    cdef Py_ssize_t n = u_weights.shape[0]
+    cdef Py_ssize_t m = v_weights.shape[0]
 
-    cdef int i = 0
+    cdef Py_ssize_t i = 0
     cdef double w_i = u_weights[0]
-    cdef int j = 0
+    cdef Py_ssize_t j = 0
     cdef double w_j = v_weights[0]
 
     cdef double m_ij = 0.
@@ -171,7 +171,7 @@ def emd_1d_sorted(np.ndarray[double, ndim=1, mode="c"] u_weights,
                                                            dtype=np.float64)
     cdef np.ndarray[long, ndim=2, mode="c"] indices = np.zeros((n + m - 1, 2),
                                                               dtype=np.int)
-    cdef int cur_idx = 0
+    cdef Py_ssize_t cur_idx = 0
     while True:
         if metric == 'sqeuclidean':
             m_ij = (u[i] - v[j]) * (u[i] - v[j])