Merge pull request #3499 from nest/fix-types-numpy

Fix Numpy types

Author: terhorstd

pynest/examples/correlospinmatrix_detector_two_neuron.py

@@ -62,13 +62,13 @@
 
 count_covariance = csd.count_covariance
 
-mean_activities = np.zeros(2, dtype=float)
+mean_activities = np.zeros(2, dtype=np.float)
 for i in range(2):
     mean_activities[i] = count_covariance[i][i][int(tau_max / h)] * (h / T)
 
 print("mean activities =", mean_activities)
 
-covariance_matrix = np.zeros((2, 2, int(2 * tau_max / h) + 1), dtype=float)
+covariance_matrix = np.zeros((2, 2, int(2 * tau_max / h) + 1), dtype=np.float)
 for i in range(2):
     for j in range(2):
         covariance_matrix[i, j] = count_covariance[i][j] * (h / T) - mean_activities[i] * mean_activities[j]

pynest/examples/pong/generate_gif.py

@@ -150,7 +150,7 @@ def grayscale_to_heatmap(in_image, min_val, max_val, base_color):
     l_paddle_positions[:, 0] -= PADDLE_WID
     r_paddle_positions = scale_coordinates(np.array(game_data["right_paddle"]))
 
-    score = np.array(game_data["score"]).astype(int)
+    score: np.ndarray = np.array(game_data["score"]).astype(int)
 
     with gzip.open(os.path.join(input_folder, "data_left.pkl.gz"), "r") as f:
         data = pickle.load(f)

pynest/examples/sudoku/sudoku_solver.py

@@ -78,7 +78,7 @@
 puzzle = get_puzzle(puzzle_index)
 network = sudoku_net.SudokuNet(pop_size=5, input=puzzle, noise_rate=noise_rate)
 
-solution_states = np.zeros((max_iterations, 9, 9), dtype=int)
+solution_states = np.zeros((max_iterations, 9, 9), dtype=np.int_)
 
 run = 0
 valid = False