diff --git a/notebooks/REMI/REMI_Digitize_and_Transform.ipynb b/notebooks/REMI/REMI_Digitize_and_Transform.ipynb
index 76e784362825db4e7ad53a34efe1726935ce3ddb..e17775c7101b04496092c7024e3cd40509c59a4b 100644
--- a/notebooks/REMI/REMI_Digitize_and_Transform.ipynb
+++ b/notebooks/REMI/REMI_Digitize_and_Transform.ipynb
@@ -46,6 +46,7 @@
"ppt_source = 'SQS_RR_UTC/TSYS/TIMESERVER:outputBunchPattern'\n",
"ignore_fel = False # Ignore any FEL entries in the PPT.\n",
"ignore_ppl = False # Ignore any PPL entries in the PPT.\n",
+ "trailing_trigger = True # Add a trigger after all regular pulses with the remaining trace.\n",
"ppl_offset = 0 # In units of the PPT.\n",
"laser_ppt_mask = -1 # Bit mask for used laser, negative to auto-detect from instrument. \n",
"instrument_sase = 3 # Which SASE we're running at for PPT decoding.\n",
@@ -316,6 +317,10 @@
"\n",
" # Fill any missing values with the highest.\n",
" pulse_counts[has_ppt == False] = pulse_counts.max()\n",
+ " \n",
+ " if trailing_trigger:\n",
+ " # Add a single count to every train for trailing trigger.\n",
+ " pulse_counts += 1\n",
"\n",
" # Compute offsets based on pulse counts.\n",
" pulse_offsets = np.zeros_like(pulse_counts)\n",
@@ -375,98 +380,84 @@
"\n",
"clock_factor = remi['digitizer']['clock_factor']\n",
"\n",
+ "min_trace_len = min([\n",
+ " dc[src, key].entry_shape[0] for det_name in remi['detector'].keys()\n",
+ " for src, key in remi.get_detector_sourcekeys(det_name)\n",
+ "])\n",
+ "\n",
"def trigger_by_ppt(worker_id, index, train_id, ppt):\n",
" all_pos, fel_pos, ppl_pos = get_pulse_positions(ppt, instrument_sase, laser_ppt_mask, ppl_offset)\n",
" num_pulses = len(all_pos)\n",
" \n",
- " if num_pulses == 0:\n",
- " return\n",
- " elif len(ppl_pos) == 0 and ppl_offset < 0:\n",
- " # No PPL pulses, but a negative offset is configured. This will cause\n",
- " # first_pulse_offset to start early and most likely miss pulses at the\n",
- " # end, so we correct by adding the ppl_offset to relative positions\n",
- " # when computing trace positions.\n",
- " pos_corr = abs(ppl_offset)\n",
- " else:\n",
- " pos_corr = 0\n",
- " \n",
+ " if num_pulses > 0:\n",
+ " if len(ppl_pos) == 0 and ppl_offset < 0:\n",
+ " # No PPL pulses, but a negative offset is configured. This will cause\n",
+ " # first_pulse_offset to start early and most likely miss pulses at the\n",
+ " # end, so we correct by adding the ppl_offset to relative positions\n",
+ " # when computing trace positions.\n",
+ " pos_corr = abs(ppl_offset)\n",
+ " else:\n",
+ " pos_corr = 0\n",
"\n",
- " rel_pos = all_pos - all_pos[0]\n",
+ " rel_pos = all_pos - all_pos[0]\n",
"\n",
- " if num_pulses > 1:\n",
- " pulse_len = np.unique(rel_pos[1:] - rel_pos[:-1]).min()\n",
- " elif num_pulses == 1:\n",
- " pulse_len = single_pulse_length\n",
+ " if num_pulses > 1:\n",
+ " pulse_len = np.unique(rel_pos[1:] - rel_pos[:-1]).min()\n",
+ " elif num_pulses == 1:\n",
+ " pulse_len = single_pulse_length\n",
"\n",
- " start_frac = first_pulse_offset + (rel_pos + pos_corr) * 2 * clock_factor\n",
- " start_int = start_frac.astype(int)\n",
+ " start_frac = first_pulse_offset + (rel_pos + pos_corr) * 2 * clock_factor\n",
+ " start_int = start_frac.astype(int)\n",
"\n",
- " pulse_offset = pulse_offsets[index]\n",
- " pulse_count = pulse_counts[index]\n",
+ " train_triggers = triggers[pulse_offsets[index]:int(pulse_offsets[index]+num_pulses)]\n",
+ " train_triggers['start'] = start_int + pulse_start_offset\n",
+ " train_triggers['stop'] = start_int + int(pulse_len * 2 * clock_factor) - 1 + pulse_end_offset\n",
+ " train_triggers['offset'] = start_frac - start_int\n",
+ " train_triggers['pulse'] = all_pos.astype(np.int16)\n",
+ " train_triggers['fel'] = [pos in fel_pos for pos in all_pos]\n",
+ " train_triggers['ppl'] = [pos in ppl_pos for pos in all_pos]\n",
" \n",
- " train_triggers = triggers[pulse_offset:pulse_offset+pulse_count]\n",
- " train_triggers['start'] = start_int + pulse_start_offset\n",
- " train_triggers['stop'] = start_int + int(pulse_len * 2 * clock_factor) - 1 + pulse_end_offset\n",
- " train_triggers['offset'] = start_frac - start_int\n",
- " train_triggers['pulse'] = all_pos.astype(np.int16)\n",
- " train_triggers['fel'] = [pos in fel_pos for pos in all_pos]\n",
- " train_triggers['ppl'] = [pos in ppl_pos for pos in all_pos]\n",
- "\n",
- " \n",
- "if ignore_fel and ignore_ppl:\n",
- " # Both FEL and PPL are ignored, use virtual full train triggers.\n",
- " print('WARNING: Both FEL and PPL pulses are ignored, '\n",
- " 'virtual trigger is inserted covering the entire train')\n",
- " \n",
- " # Overwrite global pulse statistics computed before,\n",
- " num_pulses = len(dc.train_ids)\n",
- " triggers = np.empty(num_pulses, dtype=trigger_dt)\n",
- " \n",
- " pulse_counts[:] = 1\n",
- " pulse_counts = pulse_counts.astype(np.int32)\n",
- " pulse_offsets = np.arange(len(pulse_counts)).astype(np.int32)\n",
- "\n",
- " # Obtain minimal trace length.\n",
- " min_trace_len = min([\n",
- " dc[src, key].entry_shape[0]\n",
- " for det_name in remi['detector'].keys()\n",
- " for src, key in remi.get_detector_sourcekeys(det_name)\n",
- " ])\n",
- "\n",
- " triggers['start'] = first_pulse_offset\n",
- " triggers['stop'] = min_trace_len\n",
- " triggers['offset'] = 0.0\n",
- " triggers['pulse'] = -1\n",
- " triggers['fel'] = False\n",
- " triggers['ppl'] = False \n",
- " \n",
- "else:\n",
- " with timing('find_triggers'):\n",
- " psh.map(trigger_by_ppt, ppt_data)\n",
+ " last_sample = train_triggers['stop'].max()\n",
+ " \n",
+ " else:\n",
+ " last_sample = first_pulse_offset\n",
+ " \n",
+ " if trailing_trigger:\n",
+ " # Add trailing trigger if required.\n",
+ " trigger = triggers[int(pulse_offsets[index]+pulse_counts[index]-1)]\n",
+ " trigger['start'] = last_sample\n",
+ " trigger['stop'] = min_trace_len\n",
+ " trigger['offset'] = 0.0\n",
+ " trigger['pulse'] = -1\n",
+ " trigger['fel'] = False\n",
+ " trigger['ppl'] = False\n",
+ "\n",
+ "with timing('find_triggers'):\n",
+ " psh.map(trigger_by_ppt, ppt_data)\n",
" \n",
- " if (np.unique(triggers['pulse'][1:] - triggers['pulse'][:-1]) > 0).sum() > 1:\n",
- " # There is more than one delta between pulse entries across all pulses. This is not\n",
- " # necessarily a problem, as the pattern could simply have changed in between trains\n",
- " # with each train being split properly.\n",
- " # If there's more than one delta in a single train, this likely points to a mismatch\n",
- " # of FEL and PPL repetition rate. This is most likely not intended.\n",
- "\n",
- " one = np.uint64(1) # Because np.uint64 + int = np.float64\n",
- " pulse_deltas = set()\n",
- "\n",
- " for pulse_id, (offset, count) in enumerate(zip(pulse_offsets, pulse_counts)):\n",
- " deltas = triggers['pulse'][offset+one:offset+count] - triggers['pulse'][offset:offset+count-one]\n",
- "\n",
- " if len(np.unique(deltas)) > 1:\n",
- " for delta in deltas:\n",
- " pulse_deltas.add(delta)\n",
- "\n",
- " if len(pulse_deltas) > 1:\n",
- " delta_str = ', '.join([str(x) for x in sorted(pulse_deltas)])\n",
- " warning(f'Different pulse lengths (PPT: {delta_str}) encountered within single trains, '\n",
- " f'separated pulse spectra may split up signals!')\n",
- " else:\n",
- " warning('Different pulse lengths encountered across trains, separation may be unstable!')"
+ "if (np.unique(triggers['pulse'][1:] - triggers['pulse'][:-1]) > 0).sum() > 1:\n",
+ " # There is more than one delta between pulse entries across all pulses. This is not\n",
+ " # necessarily a problem, as the pattern could simply have changed in between trains\n",
+ " # with each train being split properly.\n",
+ " # If there's more than one delta in a single train, this likely points to a mismatch\n",
+ " # of FEL and PPL repetition rate. This is most likely not intended.\n",
+ "\n",
+ " one = np.uint64(1) # Because np.uint64 + int = np.float64\n",
+ " pulse_deltas = set()\n",
+ "\n",
+ " for pulse_id, (offset, count) in enumerate(zip(\n",
+ " pulse_offsets, pulse_counts - one if trailing_trigger else pulse_counts\n",
+ " )):\n",
+ " deltas = triggers['pulse'][offset+one:offset+count] - triggers['pulse'][offset:offset+count-one]\n",
+ "\n",
+ " if len(np.unique(deltas)) > 1:\n",
+ " for delta in deltas:\n",
+ " pulse_deltas.add(delta)\n",
+ "\n",
+ " if len(pulse_deltas) > 1:\n",
+ " delta_str = ', '.join([str(x) for x in sorted(pulse_deltas)])\n",
+ " warning(f'Different pulse lengths (PPT: {delta_str}) encountered within single trains, '\n",
+ " f'separated pulse spectra may split up signals!')"
]
},
{