Merge branch 'develop'

cvgenerators/jurse.py

@@ -19,15 +19,22 @@ class Split:
     If used with a split first description, make sure you use compatible
     settings.
 
+    Use `sub_sample (and `random_state`) parameters to sub sample the training
+    set.
+
+    return xtrain, xtest, ytrain, ytest, test_index
+
     """
 
-    def __init__(self, ground_truth, attributes, n_test=2, order_dim=0, remove_unclassified=True):
+    def __init__(self, ground_truth, attributes, n_test=2, order_dim=0, sub_sample=1.0, random_state=0, remove_unclassified=True):
         self._att = attributes
         self._gt  = ground_truth
         self._n   = n_test
         self._d   = order_dim
         self._s   = 0
         self._r   = remove_unclassified
+        self._ssp = sub_sample
+        self._rs  = random_state
 
         self._size = ground_truth.shape[order_dim]
         self._step = int(ground_truth.shape[order_dim] / n_test)
@@ -48,10 +55,14 @@ class Split:
         unclassified = self._gt == 0
         train_index = ~test_index & ~unclassified
 
+        # Sub sample training
+        np.random.seed(self._rs)
+        train_index &= np.random.random(train_index.shape) < self._ssp
+
+        # Remove unclassified
         if self._r:
             test_index &= ~unclassified
 
-        #ipdb.set_trace()
         xtrain = self._att[train_index]
         xtest  = self._att[test_index]
         ytrain = self._gt[train_index]

descriptors/dfc_dsdaps.py

@@ -68,7 +68,20 @@ def run(rasters, treshold=1e4, areas=None, sd=None, moi=None, split=1, split_dim
     for i, cut in enumerate(dcuts):
         view[i*step:(i+1)*step+1] = np.moveaxis(cut, 0, d)
 
-    return descriptors
+    # Merge with original
+    loader = ld2dap.LoadTIFF(rasters)
+    raw_in = ld2dap.RawInput(descriptors, vout.metadata)
+    merger = ld2dap.Merger()
+    final_out = ld2dap.RawOutput()
+    
+    final_out.input = merger
+    merger.input = loader
+    merger.second.input = raw_in
+    
+    loader.run()
+    raw_in.run()
+
+    return final_out.data
 
 def version():
     return 'v0.0'