diff --git a/notebooks/REMI/REMI_Digitize_and_Transform.ipynb b/notebooks/REMI/REMI_Digitize_and_Transform.ipynb
index 5dae80017da0519cea7136740ac5334546911389..bd867ae23db81ee0c1e16781caa773e2179509f6 100644
--- a/notebooks/REMI/REMI_Digitize_and_Transform.ipynb
+++ b/notebooks/REMI/REMI_Digitize_and_Transform.ipynb
@@ -712,9 +712,21 @@
" \n",
" with timing(f'find_edges, {det_name}'):\n",
" psh.map(find_edges, dc.select(det_sourcekeys))\n",
+ " \n",
+ " # Properly offset edges to their trigger offset and convert to time.\n",
+ " # This is not done earlier to preserve the information for plotting.\n",
+ " edges += triggers['offset'][:, None, None]\n",
+ " edges *= remi.get_time_calibration()\n",
+ " \n",
+ " det_data[det_name] = {\n",
+ " 'edges': edges,\n",
+ " 'amplitudes': amplitudes,\n",
+ " 'avg_trace': avg_traces.sum(axis=0) / len(dc.train_ids)\n",
+ " }\n",
" \n",
" if not np.isfinite(edges).any():\n",
" warning(f'No edges found for {det_name}')\n",
+ " continue\n",
" \n",
" fig, (ux, bx) = plt.subplots(num=f'digitize_result_{det_name}', ncols=1, nrows=2, figsize=(9.5, 8), clear=True,\n",
" gridspec_kw=dict(left=0.1, right=0.98, top=0.98, bottom=0.1, hspace=0.25))\n",
@@ -748,18 +760,7 @@
" bx.set_xlabel('Edge positions - ⌊edge positions⌋')\n",
" bx.set_yscale('log')\n",
" bx.set_xlim(-0.05, 1.2)\n",
- " bx.legend()\n",
- " \n",
- " # Properly offset edges to their trigger offset and convert to time.\n",
- " # This is not done earlier to preserve the information for plotting.\n",
- " edges += triggers['offset'][:, None, None]\n",
- " edges *= remi.get_time_calibration()\n",
- " \n",
- " det_data[det_name] = {\n",
- " 'edges': edges,\n",
- " 'amplitudes': amplitudes,\n",
- " 'avg_trace': avg_traces.sum(axis=0) / len(dc.train_ids)\n",
- " }"
+ " bx.legend()"
]
},
{
@@ -881,10 +882,13 @@
" fig = plt.figure(num=f'digitized_spectra_{det_name}', figsize=(9.5, 6))\n",
" \n",
" edges = det_data[det_name]['edges']\n",
- " amplitudes = det_data[det_name]['amplitudes']\n",
" \n",
" min_edge = np.nanmin(edges)\n",
" max_edge = np.nanmax(edges)\n",
+ " \n",
+ " if np.isnan(min_edge):\n",
+ " warning(f'No edges found for {det_name}')\n",
+ " continue\n",
"\n",
" grid = fig.add_gridspec(ncols=3, nrows=3, left=0.08, right=0.98, top=0.95, hspace=0.4)\n",
"\n",
@@ -965,6 +969,10 @@
" min_edge = np.nanmin(edges)\n",
" max_edge = np.nanmax(edges)\n",
" \n",
+ " if np.isnan(min_edge):\n",
+ " warning(f'No edges found for {det_name}')\n",
+ " continue\n",
+ " \n",
" max_amplitude = np.nanmax(amplitudes)\n",
"\n",
" for edge_idx, edge_name in enumerate(['u1', 'u2', 'v1', 'v2', 'w1', 'w2', 'mcp']):\n",
@@ -982,9 +990,11 @@
"\n",
" flat_edges = finite_flattened_slice(edges, np.s_[:, edge_idx, :])\n",
" flat_amplitudes = finite_flattened_slice(amplitudes, np.s_[:, edge_idx, :])\n",
- " ax.hist2d(flat_edges, flat_amplitudes,\n",
- " bins=[tof_bins, 512], norm=LogNorm(),\n",
- " range=[[min_edge, max_edge], [0, max_amplitude]])\n",
+ " \n",
+ " if flat_edges.size > 1:\n",
+ " ax.hist2d(flat_edges, flat_amplitudes,\n",
+ " bins=[tof_bins, 512], norm=LogNorm(),\n",
+ " range=[[min_edge, max_edge], [0, max_amplitude]])\n",
" \n",
" if edge_idx == 6:\n",
" ax.set_ylabel('Pulse height')\n",
@@ -1025,7 +1035,8 @@
" sum_shifts=sum_shifts)\n",
" \n",
" if not is_valid.any():\n",
- " warning(f'No valid preliminary edge combinations found for {det_name}')\n",
+ " warning(f'No preliminary edge combinations found for {det_name}')\n",
+ " continue\n",
" \n",
" signals, sums = remi.get_signals_and_sums(edges, indices=sort.channel_indices, sum_shifts=sum_shifts,\n",
" mask=is_valid)\n",
@@ -1118,6 +1129,10 @@
" num_hits = num_hits.reshape(-1, agg_window).mean(axis=1)\n",
" max_num_hits = max(max_num_hits, num_hits.max())\n",
" \n",
+ " if max_num_hits == 0:\n",
+ " warning(f'No hits found for {det_name}')\n",
+ " continue\n",
+ "\n",
" ax.plot(np.arange(0, (num_pulses // agg_window) * agg_window, agg_window), num_hits,\n",
" lw=1, label=det_name.upper())\n",
" \n",
@@ -1177,14 +1192,14 @@
"for det_name in remi['detector'].keys():\n",
" hits = det_data[det_name]['hits']\n",
" \n",
+ " if not (hits['m'] >= 0).any():\n",
+ " warning(f'No hits found for {det_name}')\n",
+ " continue \n",
+ " \n",
" fig, ax = plt.subplots(num=f'reconstruction_methods_{det_name}', figsize=(9.5, 5), ncols=1, clear=True,\n",
" gridspec_kw=dict(left=0.08, right=0.91, top=0.8))\n",
" \n",
" fig.text(0.02, 0.98, det_name.upper(), rotation=90, ha='left', va='top', size='x-large')\n",
- " \n",
- " if not (hits['m'] >= 0).any():\n",
- " warning(f'No hits found for {det_name}')\n",
- " continue\n",
"\n",
" method_bins = np.bincount(hits['m'][hits['m'] >= 0], minlength=20)\n",
" ax.bar(np.arange(20), method_bins, width=0.5)\n",
@@ -1258,6 +1273,10 @@
" flat_hits = flat_hits[np.isfinite(flat_hits[:]['x'])]\n",
" flat_hits = flat_hits[flat_hits['m'] <= 10]\n",
"\n",
+ " if flat_hits.size == 0:\n",
+ " warning(f'No hits found for {det_name}')\n",
+ " continue \n",
+ " \n",
" fig = plt.figure(num=f'detector_results_{det_name}', figsize=(9, 10.5))\n",
" \n",
" fig.text(0.02, 0.98, det_name.upper(), rotation=90, ha='left', va='top', size='x-large')\n",
@@ -1267,10 +1286,6 @@
" txp = fig.add_axes([0.1, 0.27, 0.85, 0.23])\n",
" typ = fig.add_axes([0.1, 0.02, 0.85, 0.23])\n",
" \n",
- " if flat_hits.size == 0:\n",
- " warning(f'No hits found for {det_name}')\n",
- " continue\n",
- " \n",
" mcp_radius = remi['detector'][det_name]['mcp_radius']\n",
" im_radius = mcp_radius * 1.1\n",
" \n",