add domain adaptation

1 files changed, 50 insertions, 0 deletions

diff --git a/ot/da.py b/ot/da.py
new file mode 100644
index 0000000..8ecd952
--- /dev/null
+++ b/ot/da.py
@@ -0,0 +1,50 @@
+"""
+domain adaptation with optimal transport
+"""
+import numpy as np
+from scipy.spatial.distance import cdist
+
+from bregman import sinkhorn
+
+
+
+def indices(a, func):
+    return [i for (i, val) in enumerate(a) if func(val)]
+
+def sinkhorn_lpl1_mm(a,labels_a, b, M, reg, eta=0.1):
+    p=0.5
+    epsilon = 1e-3
+
+    # init data
+    Nini = len(a)
+    Nfin = len(b)
+     
+    indices_labels = []
+    idx_begin = np.min(labels_a)
+    for c in range(idx_begin,np.max(labels_a)+1):
+        idxc = indices(labels_a, lambda x: x==c)
+        indices_labels.append(idxc)
+
+    W=np.zeros(M.shape)
+
+    for cpt in range(10):
+        Mreg = M + eta*W
+        transp=sinkhorn(a,b,Mreg,reg,numItermax = 200)
+        # the transport has been computed. Check if classes are really separated
+        W = np.ones((Nini,Nfin))
+        for t in range(Nfin):
+            column = transp[:,t]
+            all_maj = []
+            for c in range(idx_begin,np.max(labels_a)+1):
+                col_c = column[indices_labels[c-idx_begin]]
+                if c!=-1:
+                    maj = p*((sum(col_c)+epsilon)**(p-1))
+                    W[indices_labels[c-idx_begin],t]=maj
+                    all_maj.append(maj)
+
+            # now we majorize the unlabelled by the min of the majorizations
+            # do it only for unlabbled data
+            if idx_begin==-1:
+                W[indices_labels[0],t]=np.min(all_maj)
+    
+    return transp
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