Fuzzy metadata

ld2dap/AttributeProfiles.py

@@ -8,7 +8,7 @@
 #
 # TODO details
 
-from core import Filter
+from core import Filter, Stack
 
 ## TODO: dep
 import sys
@@ -19,9 +19,29 @@ import triskele
 class AttributeProfiles(Filter):
     def __init__(self, area=None, sd=None, moi=None):
         super().__init__(self.__class__.__name__)
-        self.area = area
-        self.sd   = sd
-        self.moi  = moi
+        self.area = np.sort(area) if area is not None else None
+        self.sd   = np.sort(sd) if sd is not None else None
+        self.moi  = np.sort(moi) if moi is not None else None
+
+    def _process_desc(self):
+        att_desc = dict()
+        for att in ['area', 'sd', 'moi']:
+            att_desc[att] = list()
+            if self.__getattribute__(att) is not None:
+                att_desc[att].extend(
+                  ['Thickening {} {}'.format(att, x) for x in self.__getattribute__(att)[::-1]])
+                att_desc[att].append(None)
+                att_desc[att].extend(
+                  ['Thinning {} {}'.format(att, x) for x in self.__getattribute__(att)])
+
+        return att_desc
+
+    def _process_offset(self):
+        att_offset = dict()
+        for att in ['area', 'sd', 'moi']:
+            values = self.__getattribute__(att)
+            att_offset[att] = len(values) * 2 + 1 if values is not None else 0
+        return att_offset
 
     def _process(self, data, metadata):
         t       = triskele.Triskele(data, verbose=False)
@@ -32,6 +52,42 @@ class AttributeProfiles(Filter):
                               standard_deviation=self.sd,
                               moment_of_inertia=self.moi)
 
+        ## Merge filtering as APs
+
+        ## Create new metadata
+        ### Pre-process descriptions
+        att_desc = self._process_desc()
+
+        ### Compute stack offsets
+        att_offset = self._process_offset()
+        stack_offset = sum(att_offset.values())
+
+        ### Merge old and new descriptions
+        metadata_new = list()
+        for stack in metadata:
+            if stack.end - stack.begin > 1:
+                raise NotImplementedError('Nested filtering not implemented yet')
+
+            for att in ['area', 'sd', 'moi']:
+                stack_new = Stack(stack_offset * stack.begin, att_offset[att], 
+                        stack.desc[0], stack.symb[0])
+
+                for old_desc, new_desc in zip(stack_new.desc, att_desc[att]):
+                    print('DESCRIPTION: {} > {}'.format(old_desc, new_desc))
+                    old_desc.append(new_desc)
+
+                metadata_new.append(stack_new)
+
+
         att = np.dstack((att_min, att_max))
 
-        return att, metadata
+        return att, metadata_new
+
+if __name__ == '__main__':
+    area = [10, 100, 1000]
+    sd   = [.1, .9]
+
+    ap = AttributeProfiles(area, sd)
+
+    print(ap._process_desc())
+    print(ap._process_offset())

ld2dap/ShowFig.py

@@ -26,6 +26,6 @@ class ShowFig(Output):
         img = f1.imshow(data[:,:,-1])
         plt.colorbar(img)
         if metadata is not None:
-            f1.set_title(metadata[-1])
+            f1.set_title(metadata[-1].desc)
         plt.show()
         plt.close(fig)

ld2dap/Treshold.py

@@ -20,4 +20,7 @@ class Treshold(Filter):
         if self.max_value is None:
             self.max_value = data[data < self.treshold].max()
 
+        for stack in metadata:
+            stack.desc.append('treshold {}'.format(self.treshold))
+
         return data * (data < self.treshold) + self.max_value * (data >= self.treshold), metadata

ld2dap/core/Stack.py

@@ -17,7 +17,9 @@ class Stack(object):
         self.symb  = list()
 
         if desc is not None:
-            self.desc.append(desc)
+            for i in range(size):
+                self.desc.append(desc.copy() if isinstance(desc, list) else [desc])
 
         if symb is not None:
-            self.symb.append(symb)
+            for i in range(size):
+                self.symb.append(symb.copy() if isinstance(symb, list) else [symb])