diff --git a/Plotting.py b/Plotting.py
index 87c06211251857fb7dcb3c3183c12c5965136e25..0c62c0cd231fd4c14f160c26c17f069325a679a7 100644
--- a/Plotting.py
+++ b/Plotting.py
@@ -118,7 +118,7 @@ def plot_shock_tube(num_grid_cells: int, troubled_cell_history: list,
         current_cells = troubled_cell_history[pos]
         for cell in current_cells:
             plt.plot(cell, time_history[pos], 'k.')
-    plt.xlim((0, num_grid_cells // 2))
+    plt.xlim((0, num_grid_cells))
     plt.xlabel('Cell')
     plt.ylabel('Time')
     plt.title('Shock Tubes')
diff --git a/Troubled_Cell_Detector.py b/Troubled_Cell_Detector.py
index 6f4cb596056ed437637df005b4fd5ae15c36ad46..7a637c377440bc9a90a752c878d3ca0cb409a717 100644
--- a/Troubled_Cell_Detector.py
+++ b/Troubled_Cell_Detector.py
@@ -3,7 +3,8 @@
 @author: Laura C. Kühle, Soraya Terrab (sorayaterrab)
 
 TODO: Adjust TCs for wavelet detectors (sliding window over all cells instead
-    of every second)
+    of every second) -> Done
+TODO: Replace num_coarse_grid_cells with mesh
 TODO: Introduce Adjusted Outer Fence method in Boxplot using global_mean
 TODO: Introduce overlapping cell for adjacent folds in Boxplot
 TODO: Introduce lower/upper extreme outliers in Boxplot
@@ -244,8 +245,7 @@ class WaveletDetector(TroubledCellDetector):
             List of indices for all detected troubled cells.
 
         """
-        multiwavelet_coeffs = self._calculate_wavelet_coeffs(
-            projection[:, 1: -1])
+        multiwavelet_coeffs = self._calculate_wavelet_coeffs(projection)
         return self._get_cells(multiwavelet_coeffs, projection)
 
     def _calculate_wavelet_coeffs(self, projection):
@@ -263,10 +263,10 @@ class WaveletDetector(TroubledCellDetector):
 
         """
         output_matrix = []
-        for i in range(self._num_coarse_grid_cells):
+        for i in range(self._mesh.num_grid_cells):
             new_entry = 0.5*(
-                    projection[:, 2*i] @ self._wavelet_projection_left
-                    + projection[:, 2*i+1] @ self._wavelet_projection_right)
+                    projection[:, i] @ self._wavelet_projection_left
+                    + projection[:, i+1] @ self._wavelet_projection_right)
             output_matrix.append(new_entry)
         return np.transpose(np.array(output_matrix))
 
@@ -377,12 +377,12 @@ class Boxplot(WaveletDetector):
 
         """
         indexed_coeffs = [[multiwavelet_coeffs[0, i], i]
-                          for i in range(self._num_coarse_grid_cells)]
+                          for i in range(self._mesh.num_grid_cells)]
 
-        if self._num_coarse_grid_cells < self._fold_len:
-            self._fold_len = self._num_coarse_grid_cells
+        if self._mesh.num_grid_cells < self._fold_len:
+            self._fold_len = self._mesh.num_grid_cells
 
-        num_folds = self._num_coarse_grid_cells//self._fold_len
+        num_folds = self._mesh.num_grid_cells//self._fold_len
         troubled_cells = []
 
         for fold in range(num_folds):
@@ -466,9 +466,9 @@ class Theoretical(WaveletDetector):
         troubled_cells = []
         max_avg = np.sqrt(0.5) \
             * max(1, max(abs(projection[0][cell+1])
-                         for cell in range(self._num_coarse_grid_cells)))
+                         for cell in range(self._mesh.num_grid_cells)))
 
-        for cell in range(self._num_coarse_grid_cells):
+        for cell in range(self._mesh.num_grid_cells):
             if self._is_troubled_cell(multiwavelet_coeffs, cell, max_avg):
                 troubled_cells.append(cell)