Fix numpy deprication warnings

doc/notebooks/demo_thermalized_lbm.ipynb

@@ -26,11 +26,11 @@
 method
 ```
 %%%% Output: execute_result
-    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7fee5d180fd0>
+    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f53ba131fa0>
 %% Cell type:markdown id: tags:
 ...and modify its collision table. The `create_lb_method_from_existing` function provides a convenient way to do this. 
 We pass a custom function that receives a row of the collision table and returns a modified version of it.
@@ -52,11 +52,11 @@
 thermalized_method
 ```
 %%%% Output: execute_result
-    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7fee54d8ee80>
+    <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f53b1d12a90>
 %% Cell type:markdown id: tags:
 ## 2) Creating the kernel equations
@@ -81,11 +81,11 @@
     
 debug_output = dh.add_array('dbg')
 linear_congruent_rng_eqs = [ps.Assignment(seedField(i), seedField(i) * 1664525 + 1013904223) 
                             for i, _ in enumerate(random_number_symbols)]
-floatEqs = [ps.Assignment(ps.TypedSymbol(s.name, np.float), seedField(i) / max_seed_type)
+floatEqs = [ps.Assignment(ps.TypedSymbol(s.name, np.float64), seedField(i) / max_seed_type)
             for i, s in enumerate(random_number_symbols)]
                       
 rng_eqs = linear_congruent_rng_eqs + floatEqs + [ps.Assignment(debug_output.center, seedField(0) / max_seed_type)]
 rng_eqs
 ```

lbmpy/geometry.py

@@ -231,17 +231,17 @@ def add_black_and_white_image(boundary_handling, image_file, target_slice=None,
     # binarize
     zoomed_image[zoomed_image <= 254] = 0
     zoomed_image[zoomed_image > 254] = 1
-    zoomed_image = np.logical_not(zoomed_image.astype(np.bool))
+    zoomed_image = np.logical_not(zoomed_image.astype(bool))
 
     # resize necessary if aspect ratio should be constant
     if zoomed_image.shape != target_size:
-        resized_image = np.zeros(target_size, dtype=np.bool)
+        resized_image = np.zeros(target_size, dtype=bool)
         mid = [(ts - s) // 2 for ts, s in zip(target_size, zoomed_image.shape)]
         resized_image[mid[0]:zoomed_image.shape[0] + mid[0], mid[1]:zoomed_image.shape[1] + mid[1]] = zoomed_image
         zoomed_image = resized_image
 
     def callback(*coordinates):
-        result = np.zeros_like(coordinates[0], dtype=np.bool)
+        result = np.zeros_like(coordinates[0], dtype=bool)
         mask_start = [int(coordinates[i][(0,) * dim] - 0.5) for i in range(dim)]
         mask_end = [int(coordinates[i][(-1,) * dim] + 1 - 0.5) for i in range(dim)]
 

lbmpy_tests/test_geometry_setup_serial.py

@@ -63,6 +63,6 @@ def test_slice_mask_combination():
         print("x", coordinates[0][:, 0])
         print("y", coordinates[1][0, :])
         print(x.shape)
-        return np.ones_like(x, dtype=np.bool)
+        return np.ones_like(x, dtype=bool)
 
     sc.boundary_handling.set_boundary(NoSlip(), make_slice[6:7, -1], callback)