Reworked Theoretical method for efficiency.

scripts/tcd/Troubled_Cell_Detector.py

@@ -432,13 +432,12 @@ class Boxplot(WaveletDetector):
 
 
 class Theoretical(WaveletDetector):
-    """Class for troubled-cell detection based on the projection averages and
-    a cutoff factor.
+    """Class for troubled-cell detection based on theoretical thresholding.
 
     Attributes
     ----------
-    cutoff_factor : float
-        Cutoff factor above which a cell is considered troubled.
+    threshold : float
+        Threshold above which a cell is considered troubled.
 
     """
     def _reset(self, config):
@@ -453,9 +452,10 @@ class Theoretical(WaveletDetector):
         super()._reset(config)
 
         # Unpack necessary configurations
-        self._cutoff_factor = config.pop('cutoff_factor',
+        cutoff_factor = config.pop('cutoff_factor',
                                    np.sqrt(2) * self._mesh.cell_len)
-        # comment to line above: or 2 or 3
+        self._threshold = cutoff_factor / (
+                self._mesh.cell_len*self._mesh.num_cells)
 
     def get_cells(self, projection):
         """Calculate troubled cells in a given projection.
@@ -473,37 +473,9 @@ class Theoretical(WaveletDetector):
         """
         coeffs = self._select_degree(self._calculate_wavelet_coeffs(
             projection))
-        troubled_cells = []
-        max_avg = np.sqrt(0.5) \
-            * max(1, max(abs(projection[0][cell+1])
-                         for cell in range(self._mesh.num_cells)))
 
-        for cell in range(self._mesh.num_cells):
-            if self._is_troubled_cell(coeffs, cell, max_avg):
-                troubled_cells.append(cell)
+        max_avg = np.sqrt(0.5) * max(1, np.max(np.abs(projection[0])))
+        troubled_cells = np.flatnonzero(
+            np.abs(coeffs)/max_avg > self._threshold).tolist()
 
         return troubled_cells
-
-    def _is_troubled_cell(self, coeffs, cell, max_avg):
-        """Checks whether a cell is troubled.
-
-        Parameters
-        ----------
-        coeffs : ndarray
-            Matrix of multiwavelet coefficients.
-        cell : int
-            Index of cell.
-        max_avg : float
-            Maximum average of projection.
-
-        Returns
-        -------
-        bool
-            Flag whether cell is troubled.
-
-        """
-        max_value = abs(coeffs[cell])/max_avg
-        eps = self._cutoff_factor\
-            / (self._mesh.cell_len*self._mesh.num_cells)
-
-        return max_value > eps