updated simulation grid

scripts/simulate_grid.py

@@ -20,32 +20,61 @@
 """Simulate a grid of configurations.
 """
 
+import numpy as np
+
 
 from hexsample import HEXSAMPLE_DATA, logger
 from hexsample.pipeline import hxsim, hxrecon
+from hexsample.readout import HexagonalReadoutMode
 
 
 # Number of events to be generated for each configuration.
 NUM_EVENTS = 100000
 # Detector thickness grid in cm.
-THICKNESS = (0.005, 0.01, 0.015, 0.02, 0.025, 0.03, 0.035, 0.04, 0.045, 0.05)
+THICKNESS = (0.02, 0.025, 0.03, 0.035)
 # Equivalent noise charge grid in e.
-NOISE = (0, 10, 20, 25, 30, 35, 40)
+NOISE = (20, 30, 40)
+# Chip pitch in cm
+PITCH = (0.0050, 0.0055, 0.0060)
+# Number of neirest neighbors in track clusters
+N_NEIGHBORS = np.arange(1,8)
+# Zero suppression threshold 
+THRESHOLD = np.linspace(0,1000,50)
 # Zero-suppression threshold, expressed in units of enc.
 SIGMA_THRESHOLD = 2.
 # Number of neighbors for the clustering.
 NUM_NEIGHBORS = 2
+# Readout mode
+#READOUT_MODE = HexagonalReadoutMode.CIRCULAR
 
-
+'''
 for thickness in THICKNESS:
     for noise in NOISE:
-        # Simulate...
-        file_name = f'sim_{1.e4 * thickness:.0f}um_{noise:.0f}enc.h5'
-        file_path = HEXSAMPLE_DATA / file_name
-        kwargs = dict(outfile=file_path, thickness=thickness, noise=noise)
-        file_path = hxsim(numevents=NUM_EVENTS, **kwargs)
+        for pitch in PITCH:
+            # Simulate...
+            file_name = f'sim_{1.e4 * thickness:.0f}um_{noise:.0f}enc_{1e4 * pitch:.0f}pitch.h5'
+            file_path = HEXSAMPLE_DATA / file_name
+            kwargs = dict(outfile=file_path, thickness=thickness, noise=noise, pitch=pitch)
+            file_path = hxsim(numevents=NUM_EVENTS, **kwargs)
+            # ... and reconstruct.
+            threshold = noise * SIGMA_THRESHOLD
+            suffix = f'recon_nn{NUM_NEIGHBORS}_thr{threshold:.0f}'
+            kwargs = dict(zsupthreshold=threshold, nneighbors=NUM_NEIGHBORS, suffix=suffix)
+            hxrecon(infile=file_path, **kwargs)
+'''
+
+# Simulate...
+file_name = f'sim_250um_20enc_60pitch.h5'
+file_path = HEXSAMPLE_DATA / file_name
+kwargs = dict(outfile=file_path, thickness=0.025, noise=20, pitch=0.006)
+file_path = hxsim(numevents=NUM_EVENTS, **kwargs)
+
+for thr in THRESHOLD:
+    for nn in N_NEIGHBORS:
         # ... and reconstruct.
-        threshold = noise * SIGMA_THRESHOLD
-        suffix = f'recon_nn{NUM_NEIGHBORS}_thr{threshold:.0f}'
-        kwargs = dict(zsupthreshold=threshold, nneighbors=NUM_NEIGHBORS, suffix=suffix)
+        #threshold = 20 * SIGMA_THRESHOLD
+        suffix = f'recon_nn{nn}_thr{thr:.0f}'
+        kwargs = dict(zsupthreshold=thr, nneighbors=nn, suffix=suffix)
         hxrecon(infile=file_path, **kwargs)
+
+