Merge pull request #38 from antoinedemathelin/master

change pairwise distance

Author: antoinedemathelin

.gitignore

@@ -19,4 +19,6 @@ var/
 *.egg
 docs_build/
 docs/html/
-docs/doctrees/
+docs/doctrees/
+adapt/datasets.py
+datasets/

adapt/feature_based/_ccsa.py

@@ -17,15 +17,12 @@ def pairwise_y(X, Y):
     Y = tf.tile(tf.expand_dims(Y, -1), [1, 1, batch_size_x])
     return tf.reduce_sum(tf.abs(X-tf.transpose(Y)), 1)/2
 
+
 def pairwise_X(X, Y):
-    batch_size_x = tf.shape(X)[0]
-    batch_size_y = tf.shape(Y)[0]
-    dim = tf.reduce_prod(tf.shape(X)[1:])
-    X = tf.reshape(X, (batch_size_x, dim))
-    Y = tf.reshape(Y, (batch_size_y, dim))
-    X = tf.tile(tf.expand_dims(X, -1), [1, 1, batch_size_y])
-    Y = tf.tile(tf.expand_dims(Y, -1), [1, 1, batch_size_x])
-    return tf.reduce_sum(tf.square(X-tf.transpose(Y)), 1)
+    X2 = tf.tile(tf.reduce_sum(tf.square(X), axis=1, keepdims=True), [1, tf.shape(Y)[0]])
+    Y2 = tf.tile(tf.reduce_sum(tf.square(Y), axis=1, keepdims=True), [1, tf.shape(X)[0]])
+    XY = tf.matmul(X, tf.transpose(Y))
+    return X2 + tf.transpose(Y2) - 2*XY
 
 
 @make_insert_doc(["encoder", "task"], supervised=True)

adapt/feature_based/_fmmd.py

@@ -8,14 +8,10 @@
 
 
 def pairwise_X(X, Y):
-    batch_size_x = tf.shape(X)[0]
-    batch_size_y = tf.shape(Y)[0]
-    dim = tf.reduce_prod(tf.shape(X)[1:])
-    X = tf.reshape(X, (batch_size_x, dim))
-    Y = tf.reshape(Y, (batch_size_y, dim))
-    X = tf.tile(tf.expand_dims(X, -1), [1, 1, batch_size_y])
-    Y = tf.tile(tf.expand_dims(Y, -1), [1, 1, batch_size_x])
-    return tf.reduce_sum(tf.square(X-tf.transpose(Y)), 1)
+    X2 = tf.tile(tf.reduce_sum(tf.square(X), axis=1, keepdims=True), [1, tf.shape(Y)[0]])
+    Y2 = tf.tile(tf.reduce_sum(tf.square(Y), axis=1, keepdims=True), [1, tf.shape(X)[0]])
+    XY = tf.matmul(X, tf.transpose(Y))
+    return X2 + tf.transpose(Y2) - 2*XY
 
 
 def _get_optim_function(Xs, Xt, kernel="linear", gamma=1., degree=2, coef=1.):

adapt/parameter_based/_transfer_tree.py

@@ -10,21 +10,34 @@
 import adapt._tree_utils as ut
 
 
-@make_insert_doc(supervised=True)
+# @make_insert_doc(supervised=True)
 class TransferTreeClassifier(BaseAdaptEstimator):
     """
-    TransferTreeClassifier
-    
+    TransferTreeClassifier: Modify a source Decision tree on a target dataset.
 
     Parameters
     ----------    
     estimator : sklearn DecsionTreeClassifier (default=None)
         Source decision tree classifier.
+        
+    Xt : numpy array (default=None)
+        Target input data.
+            
+    yt : numpy array (default=None)
+        Target output data.
                 
     algo : str or callable (default="")
         Leaves relabeling if "" or "relab". 
         "ser" and "strut" for SER and STRUT algorithms
-     
+        
+    copy : boolean (default=True)
+        Whether to make a copy of ``estimator`` or not.
+        
+    verbose : int (default=1)
+        Verbosity level.
+        
+    random_state : int (default=None)
+        Seed of random generator.
         
     Attributes
     ----------
@@ -1011,19 +1024,33 @@ def _strut(self,X_target_node,Y_target_node,node=0,no_prune_on_cl=False,cl_no_pr
 
 class TransferForestClassifier(BaseAdaptEstimator):
     """
-    TransferForestClassifier
+    TransferForestClassifier: Modify a source Random Forest on a target dataset.
     
     Parameters
     ----------    
     estimator : sklearn RandomForestClassifier (default=None)
         Source random forest classifier.
         
+    Xt : numpy array (default=None)
+        Target input data.
+            
+    yt : numpy array (default=None)
+        Target output data.
+                
     algo : str or callable (default="")
         Leaves relabeling if "" or "relab". 
         "ser" and "strut" for SER and STRUT algorithms
         
     bootstrap : boolean (default=True).
-
+        
+    copy : boolean (default=True)
+        Whether to make a copy of ``estimator`` or not.
+        
+    verbose : int (default=1)
+        Verbosity level.
+        
+    random_state : int (default=None)
+        Seed of random generator.
         
     Attributes
     ----------

src_docs/_templates/layout.html

@@ -53,6 +53,7 @@
 <li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.parameter_based.RegularTransferNN") }}">RegularTransferNN</a></li>
 <li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.parameter_based.FineTuning") }}">FineTuning</a></li>
 <li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.parameter_based.TransferTreeClassifier") }}">TransferTreeClassifier</a></li>
+<li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.parameter_based.TransferForestClassifier") }}">TransferForestClassifier</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="{{ pathto("contents") }}{{ contents }}{{ "adapt-metrics" }}">Metrics</a><ul>

src_docs/contents.rst

@@ -139,6 +139,7 @@ the **source** data are adapted to build a suited model for the **task** on the
    parameter_based.RegularTransferNN
    parameter_based.FineTuning
    parameter_based.TransferTreeClassifier
+   parameter_based.TransferForestClassifier
 
 
 .. _adapt.metrics:

src_docs/gallery/TransferForest.rst

@@ -0,0 +1,47 @@
+:ref:`adapt.parameter_based <adapt.parameter_based>`.TransferForestClassifier
+==================================================================================
+
+.. currentmodule:: adapt.parameter_based
+
+.. autoclass:: TransferForestClassifier
+	:no-members:
+	:no-inherited-members:
+	:no-special-members:
+	
+	
+	
+	
+	.. rubric:: Methods
+	
+	.. autosummary::
+	    
+		~TransferForestClassifier.__init__
+		~TransferForestClassifier.fit
+		~TransferForestClassifier.fit_estimator
+		~TransferForestClassifier.get_params
+		~TransferForestClassifier.predict
+		~TransferForestClassifier.predict_estimator
+		~TransferForestClassifier.score
+		~TransferForestClassifier.set_params
+		~TransferForestClassifier.unsupervised_score
+	
+	
+	.. automethod:: __init__
+	.. automethod:: fit
+	.. automethod:: fit_estimator
+	.. automethod:: get_params
+	.. automethod:: predict
+	.. automethod:: predict_estimator
+	.. automethod:: score
+	.. automethod:: set_params
+	.. automethod:: unsupervised_score
+	
+    
+	
+	
+.. raw:: html
+
+   <h2> Examples </h2>
+	
+.. include:: ../gallery/TransferForestClassifier.rst
+	

src_docs/generated/adapt.parameter_based.TransferForestClassifier.rst

@@ -25,6 +25,7 @@
 		~TransferTreeClassifier.prune
 		~TransferTreeClassifier.score
 		~TransferTreeClassifier.set_params
+		~TransferTreeClassifier.swap_subtrees
 		~TransferTreeClassifier.unsupervised_score
 		~TransferTreeClassifier.updateSplit
 		~TransferTreeClassifier.updateValue
@@ -40,6 +41,7 @@
 	.. automethod:: prune
 	.. automethod:: score
 	.. automethod:: set_params
+	.. automethod:: swap_subtrees
 	.. automethod:: unsupervised_score
 	.. automethod:: updateSplit
 	.. automethod:: updateValue