Commit 38a17b0b authored by Markus Holzer's avatar Markus Holzer
Browse files

Fix numpy deprication warnings

parent dd98681c
...@@ -26,11 +26,11 @@ ...@@ -26,11 +26,11 @@
method method
``` ```
   
%%%% Output: execute_result %%%% Output: execute_result
   
<lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7fee5d180fd0> <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f53ba131fa0>
   
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
   
...and modify its collision table. The `create_lb_method_from_existing` function provides a convenient way to do this. ...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. We pass a custom function that receives a row of the collision table and returns a modified version of it.
...@@ -52,11 +52,11 @@ ...@@ -52,11 +52,11 @@
thermalized_method thermalized_method
``` ```
   
%%%% Output: execute_result %%%% Output: execute_result
   
<lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7fee54d8ee80> <lbmpy.methods.momentbased.momentbasedmethod.MomentBasedLbMethod at 0x7f53b1d12a90>
   
%% Cell type:markdown id: tags: %% Cell type:markdown id: tags:
   
## 2) Creating the kernel equations ## 2) Creating the kernel equations
   
...@@ -81,11 +81,11 @@ ...@@ -81,11 +81,11 @@
debug_output = dh.add_array('dbg') debug_output = dh.add_array('dbg')
   
linear_congruent_rng_eqs = [ps.Assignment(seedField(i), seedField(i) * 1664525 + 1013904223) linear_congruent_rng_eqs = [ps.Assignment(seedField(i), seedField(i) * 1664525 + 1013904223)
for i, _ in enumerate(random_number_symbols)] 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)] 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 = linear_congruent_rng_eqs + floatEqs + [ps.Assignment(debug_output.center, seedField(0) / max_seed_type)]
rng_eqs rng_eqs
``` ```
......
...@@ -231,17 +231,17 @@ def add_black_and_white_image(boundary_handling, image_file, target_slice=None, ...@@ -231,17 +231,17 @@ def add_black_and_white_image(boundary_handling, image_file, target_slice=None,
# binarize # binarize
zoomed_image[zoomed_image <= 254] = 0 zoomed_image[zoomed_image <= 254] = 0
zoomed_image[zoomed_image > 254] = 1 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 # resize necessary if aspect ratio should be constant
if zoomed_image.shape != target_size: 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)] 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 resized_image[mid[0]:zoomed_image.shape[0] + mid[0], mid[1]:zoomed_image.shape[1] + mid[1]] = zoomed_image
zoomed_image = resized_image zoomed_image = resized_image
def callback(*coordinates): 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_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)] mask_end = [int(coordinates[i][(-1,) * dim] + 1 - 0.5) for i in range(dim)]
......
...@@ -63,6 +63,6 @@ def test_slice_mask_combination(): ...@@ -63,6 +63,6 @@ def test_slice_mask_combination():
print("x", coordinates[0][:, 0]) print("x", coordinates[0][:, 0])
print("y", coordinates[1][0, :]) print("y", coordinates[1][0, :])
print(x.shape) 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) sc.boundary_handling.set_boundary(NoSlip(), make_slice[6:7, -1], callback)
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