more bugfixes in export from gpu (#66)

Author: flaport

fdtd/backend.py

@@ -338,8 +338,6 @@ def array(self, arr, dtype=None, **kwargs):
                     return arr.clone().to(device="cuda", dtype=dtype, **kwargs)
                 return torch.tensor(arr, device="cuda", dtype=dtype, **kwargs)
 
-            # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-            # The same warning applies here.
             def numpy(self, arr):
                 """convert the array to numpy array"""
                 if torch.is_tensor(arr):

fdtd/grid.py

@@ -494,12 +494,21 @@ def save_data(self):
 
         Parameters: None
         """
+        def _numpyfy(item):
+            if isinstance(item, list):
+                return [_numpyfy(el) for el in item]
+            elif bd.is_array(item):
+                return bd.numpy(item)
+            else:
+                return item
+                
         if self.folder is None:
             raise Exception(
                 "Save location not initialized. Please read about 'fdtd.Grid.saveSimulation()' or try running 'grid.saveSimulation()'."
             )
         dic = {}
         for detector in self.detectors:
-            dic[detector.name + " (E)"] = [x for x in detector.detector_values()["E"]]
-            dic[detector.name + " (H)"] = [x for x in detector.detector_values()["H"]]
+            values = detector.detector_values()
+            dic[detector.name + " (E)"] = _numpyfy(values['E'])
+            dic[detector.name + " (H)"] = _numpyfy(values['H'])
         savez(path.join(self.folder, "detector_readings"), **dic)

fdtd/visualization.py

@@ -360,14 +360,14 @@ def dB_map_2D(block_det=None, choose_axis=2, interpolation="spline16"):
             a[i].append(max(temp) - min(temp))
 
     peakVal, minVal = max(map(max, a)), min(map(min, a))
-    print(
-        "Peak at:",
-        [
-            [[i, j] for j, y in enumerate(x) if y == peakVal]
-            for i, x in enumerate(a)
-            if peakVal in x
-        ],
-    )
+    #print(
+    #    "Peak at:",
+    #    [
+    #        [[i, j] for j, y in enumerate(x) if y == peakVal]
+    #        for i, x in enumerate(a)
+    #        if peakVal in x
+    #    ],
+    #)
     a = 10 * log10([[y / minVal for y in x] for x in a])
 
     plt.title("dB map of Electrical waves in detector region")