cleanupt cpp wrapper name

1 files changed, 0 insertions, 131 deletions

diff --git a/ot/lp/emd.pyx b/ot/lp/emd.pyx
deleted file mode 100644
index 46794ab..0000000
--- a/ot/lp/emd.pyx
+++ /dev/null
@@ -1,131 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Thu Sep 11 08:42:08 2014
-
-@author: rflamary
-"""
-import numpy as np
-cimport numpy as np
-
-cimport cython
-
-
-
-cdef extern from "EMD.h":
-    void EMD_wrap(int n1,int n2, double *X, double *Y,double *D, double *G, double *cost)
-
-
-
-@cython.boundscheck(False)
-@cython.wraparound(False)
-def emd_c( np.ndarray[double, ndim=1, mode="c"] a,np.ndarray[double, ndim=1, mode="c"]  b,np.ndarray[double, ndim=2, mode="c"]  M):
-    """
-        Solves the Earth Movers distance problem and returns the optimal transport matrix
-        
-        gamm=emd(a,b,M)
-    
-    .. math::
-        \gamma = arg\min_\gamma <\gamma,M>_F 
-        
-        s.t. \gamma 1 = a
-        
-             \gamma^T 1= b 
-             
-             \gamma\geq 0
-    where :
-    
-    - M is the metric cost matrix
-    - a and b are the sample weights
-             
-    Parameters
-    ----------
-    a : (ns,) ndarray, float64
-        source histogram 
-    b : (nt,) ndarray, float64
-        target histogram
-    M : (ns,nt) ndarray, float64
-        loss matrix        
-  
-    
-    Returns
-    -------
-    gamma: (ns x nt) ndarray
-        Optimal transportation matrix for the given parameters
- 
-    """
-    cdef int n1= M.shape[0]
-    cdef int n2= M.shape[1]
-
-    cdef float cost=0
-    cdef np.ndarray[double, ndim=2, mode="c"] G=np.zeros([n1, n2])
-    
-    if not len(a):
-        a=np.ones((n1,))/n1
-
-    if not len(b):
-        b=np.ones((n2,))/n2
-
-    # calling the function
-    EMD_wrap(n1,n2,<double*> a.data,<double*> b.data,<double*> M.data,<double*> G.data,<double*> &cost)
-
-    return G
-
-@cython.boundscheck(False)
-@cython.wraparound(False)
-def emd2_c( np.ndarray[double, ndim=1, mode="c"] a,np.ndarray[double, ndim=1, mode="c"]  b,np.ndarray[double, ndim=2, mode="c"]  M):
-    """
-        Solves the Earth Movers distance problem and returns the optimal transport loss
-        
-        gamm=emd(a,b,M)
-    
-    .. math::
-        \gamma = arg\min_\gamma <\gamma,M>_F 
-        
-        s.t. \gamma 1 = a
-        
-             \gamma^T 1= b 
-             
-             \gamma\geq 0
-    where :
-    
-    - M is the metric cost matrix
-    - a and b are the sample weights
-             
-    Parameters
-    ----------
-    a : (ns,) ndarray, float64
-        source histogram 
-    b : (nt,) ndarray, float64
-        target histogram
-    M : (ns,nt) ndarray, float64
-        loss matrix        
-  
-    
-    Returns
-    -------
-    gamma: (ns x nt) ndarray
-        Optimal transportation matrix for the given parameters
- 
-    """
-    cdef int n1= M.shape[0]
-    cdef int n2= M.shape[1]
-
-    cdef float cost=0
-    cdef np.ndarray[double, ndim=2, mode="c"] G=np.zeros([n1, n2])
-    
-    if not len(a):
-        a=np.ones((n1,))/n1
-
-    if not len(b):
-        b=np.ones((n2,))/n2
-
-    # calling the function
-    EMD_wrap(n1,n2,<double*> a.data,<double*> b.data,<double*> M.data,<double*> G.data,<double*> &cost)
-    
-    cost=0
-    for i in range(n1):
-        for j in range(n2):
-            cost+=G[i,j]*M[i,j]
-
-    return cost
-