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# -*- 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
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