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Feature Extraction/create_em_map.py

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+import numpy as np
+import h5py
+import matplotlib.pyplot as plt
+
+num_probe_x_tiles = 48
+num_probe_y_tiles = 48
+num_input_stimuli = 1000
+
+em_map = np.zeros((num_input_stimuli, 20, num_probe_x_tiles, num_probe_y_tiles))
+cema_trace_file = '../Electromagnetic Computation/fastem_sim_traces.h5'
+
+
+cema_trace_file = '../Electromagnetic Computation/fastem_sim_traces.h5'
+f = h5py.File(cema_trace_file, "r")
+print('--iterms: ', len(f.keys()), f.keys())
+x_loc = list(f.keys())
+n = len(x_loc)
+for i in range(n-1):
+    for j in range(n-1-i):
+        if float(x_loc[j]) > float(x_loc[j+1]):
+            x_loc[j], x_loc[j+1] = x_loc[j+1], x_loc[j]
+x_loc1 = x_loc
+print('--iterms: ', len(f[x_loc[0]].keys()), f[x_loc[0]].keys())
+y_loc = list(f[x_loc[0]].keys())
+m = len(y_loc)
+for i in range(m-1):
+    for j in range(m-1-i):
+        if float(y_loc[j]) > float(y_loc[j+1]):
+            y_loc[j], y_loc[j+1] = y_loc[j+1], y_loc[j]
+y_loc1 = y_loc
+print(x_loc1)
+print(y_loc1)
+
+for current_probe_x_tiles in range(num_probe_x_tiles):
+    for current_probe_y_tiles in range(num_probe_y_tiles):
+        tmp_trace = f[x_loc1[current_probe_x_tiles]][y_loc1[current_probe_y_tiles]]["traces"][:]
+        em_map[: , :, current_probe_x_tiles, current_probe_y_tiles] = tmp_trace[:num_input_stimuli, :20]  # 2:2+3
+
+#
+
+# np.save("em_map_100um.npy", em_map)
+print(np.shape(em_map))
+
+np.save("em_map_train.npy", em_map[:750, :, :, :])
+np.save("em_map_test.npy", em_map[750:, :, :, :])