diff --git a/cal_tools/cal_tools/agipdlib.py b/cal_tools/cal_tools/agipdlib.py
index 84bc94255fcee20b0680116306c45032a9c5fac7..5ac64e76d2636a50f9326dddaf6b9112283e99a1 100644
--- a/cal_tools/cal_tools/agipdlib.py
+++ b/cal_tools/cal_tools/agipdlib.py
@@ -72,8 +72,8 @@ class AgipdCorrections:
"""
def __init__(self, infile, outfile, max_cells, channel, max_pulses,
- bins_gain_vs_signal, bins_signal_low_range,
- bins_signal_high_range,
+ rng_pulse_idx, bins_gain_vs_signal,
+ bins_signal_low_range, bins_signal_high_range,
bins_dig_gain_vs_signal, raw_fmt_version=2, chunk_size=512,
h5_data_path="INSTRUMENT/SPB_DET_AGIPD1M-1/DET/{}CH0:xtdf/",
h5_index_path="INDEX/SPB_DET_AGIPD1M-1/DET/{}CH0:xtdf/",
@@ -91,7 +91,8 @@ class AgipdCorrections:
:param max_cell: maximum number of memory cells to handle, e.g. if
calibration constants only exist for a subset of cells
:param channel: module/channel to correct
- :param max_pulses: maximum pulse id to consider for preview histograms
+ :param max_pulses: pulse indices to consider for preview histograms
+ :param rng_pulse_idx: maximum pulse idx to consider for preview histograms
:param bins_gain_vs_signal: number of bins for gain vs signal histogram
:param bins_signal_low_range: number of bins for the low signal
range histogram
@@ -121,6 +122,7 @@ class AgipdCorrections:
self.chunksize = chunk_size
self.initialized = False
self.max_pulses = max_pulses
+ self.rng_pulse_idx = rng_pulse_idx
self.max_cells = max_cells
self.hists_signal_low = 0
self.hists_signal_high = 0
@@ -1031,16 +1033,16 @@ class AgipdCorrections:
if cidx == 0:
copim = copy.copy(im)
copim[copim < self.median_noise] = np.nan
- bins = (self.bins_signal_low_range, self.max_pulses)
- rnge = [[-50, 1000], [0, self.max_pulses + 1]]
+ bins = (self.bins_signal_low_range, self.rng_pulse_idx)
+ rnge = [[-50, 1000], [self.max_pulses[0], self.max_pulses[-1]]]
H, xe, ye = np.histogram2d(np.nanmean(copim, axis=(1, 2)),
pulseId,
bins=bins,
range=rnge)
self.hists_signal_low += H
self.low_edges = (xe, ye)
- bins = (self.bins_signal_high_range, self.max_pulses)
- rnge = [[0, 200000], [0, self.max_pulses + 1]]
+ bins = (self.bins_signal_high_range, self.rng_pulse_idx)
+ rnge = [[0, 200000], [self.max_pulses[0], self.max_pulses[-1]]]
H, xe, ye = np.histogram2d(np.nanmean(copim, axis=(1, 2)),
pulseId,
bins=bins,
@@ -1159,7 +1161,7 @@ class AgipdCorrections:
can_calibrate = (allcells < max_cells)
- can_calibrate &= (allpulses < np.max(allpulses[:self.max_pulses]))
+ can_calibrate &= (allpulses < np.max(allpulses[np.array(self.max_pulses)]))
if np.count_nonzero(can_calibrate) == 0:
return
diff --git a/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb b/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
index af85abf7dfe201047a54d2d06a46d790dea57564..59971159399109e659f8cae05001d086fd5b289e 100644
--- a/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
+++ b/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
@@ -22,9 +22,9 @@
},
"outputs": [],
"source": [
- "in_folder = \"/gpfs/exfel/exp/SPB/201901/p002545/raw\" # the folder to read data from, required\n",
- "run = 9 # runs to process, required\n",
- "out_folder = \"/gpfs/exfel/data/scratch/karnem/AGIPD_Corr12\" # the folder to output to, required\n",
+ "in_folder = \"/gpfs/exfel/exp/MID/201931/p900090/raw\" # the folder to read data from, required\n",
+ "run = 552 # runs to process, required\n",
+ "out_folder = \"/gpfs/exfel/data/scratch/ahmedk/test/AGIPD_Corr\" # the folder to output to, required\n",
"calfile = \"/gpfs/exfel/data/scratch/haufs/agipd_on_demand/agipd_store_mid.h5\" # path to calibration file. Leave empty if all data should come from DB\n",
"sequences = [-1] # sequences to correct, set to -1 for all, range allowed\n",
"mem_cells = 0 # number of memory cells used, set to 0 to automatically infer\n",
@@ -32,7 +32,7 @@
"overwrite = True # set to True if existing data should be overwritten\n",
"no_relative_gain = False # do not do relative gain correction\n",
"cluster_profile = \"noDB\"\n",
- "max_pulses = 500\n",
+ "max_pulses = [0, 500, 1] # range list [st, end, step] of maximum pulse indices for the report histogram. 3 allowed maximum list input elements. \n",
"local_input = False\n",
"bias_voltage = 300\n",
"cal_db_interface = \"tcp://max-exfl016:8015#8045\" # the database interface to use\n",
@@ -348,7 +348,7 @@
"from functools import partial\n",
"def correct_module(max_cells, do_rel_gain, index_v, CHUNK_SIZE, total_sequences, sequences_qm, \n",
" bins_gain_vs_signal, bins_signal_low_range, bins_signal_high_range,\n",
- " bins_dig_gain_vs_signal, max_pulses, dbparms, fileparms, nodb, chunk_size_idim,\n",
+ " bins_dig_gain_vs_signal, max_pulses, rng_pulse_idx, dbparms, fileparms, nodb, chunk_size_idim,\n",
" special_opts, il_mode, loc, dinstance, force_hg_if_below, force_mg_if_below,\n",
" mask_noisy_adc, adjust_mg_baseline, acq_rate, dont_zero_nans, dont_zero_orange,\n",
" inp):\n",
@@ -438,7 +438,7 @@
" infile = h5py.File(filename, \"r\", driver=\"core\")\n",
" outfile = h5py.File(filename_out, \"w\")\n",
" \n",
- " agipd_corr = AgipdCorrections(infile, outfile, max_cells, channel, max_pulses,\n",
+ " agipd_corr = AgipdCorrections(infile, outfile, max_cells, channel, max_pulses, rng_pulse_idx,\n",
" bins_gain_vs_signal, bins_signal_low_range,\n",
" bins_signal_high_range, bins_dig_gain_vs_signal,\n",
" do_rel_gain=do_rel_gain, chunk_size_idim=chunk_size_idim,\n",
@@ -463,7 +463,6 @@
" return\n",
" if not nodb:\n",
" when = agipd_corr.initialize_from_db(dbparms, qm, only_dark=(fileparms != \"\"))\n",
- " print(when)\n",
" if fileparms != \"\":\n",
" agipd_corr.initialize_from_file(fileparms, qm, with_dark=nodb)\n",
" print(\"Initialized constants\")\n",
@@ -503,12 +502,39 @@
"inp = []\n",
"left = total_sequences\n",
"\n",
+ "# check if max_pulses is a list, tuple or int.\n",
+ "# if list, then it's content are the requested pulse indices.\n",
+ "# if tuple, then it is a definition for a range of pulse indices.\n",
+ "# if int, then it is the max pulse indices starting 0.\n",
+ "\n",
+ "print(type(max_pulses))\n",
+ "if isinstance(max_pulses, list):\n",
+ " if len(max_pulses) == 3:\n",
+ " max_pulses = list(range(max_pulses[0],\n",
+ " max_pulses[1],\n",
+ " max_pulses[2]))\n",
+ " elif len(max_pulses) == 2:\n",
+ " max_pulses = list(range(max_pulses[0],\n",
+ " max_pulses[1],\n",
+ " 1))\n",
+ " elif len(max_pulses) == 1:\n",
+ " rng_pulse_idx = max_pulses[0]\n",
+ " max_pulses = list(range(max_pulses[0]))\n",
+ "\n",
+ " else:\n",
+ " raise ValueError(\"Wrong input for max_pulses {} \\n\".format(max_pulses),\n",
+ " \"max_pulses tuple has more than 3 arguments\")\n",
+ " rng_pulse_idx = len(max_pulses)\n",
+ "elif isinstance(max_pulses, int):\n",
+ " rng_pulse_idx = max_pulses\n",
+ " max_pulses = list(range(max_pulses))\n",
+ " \n",
"bins_gain_vs_signal = (100, 100)\n",
"bins_signal_low_range = 100\n",
"bins_signal_high_range = 100\n",
"bins_dig_gain_vs_signal = (100, 4)\n",
- "hists_signal_low = np.zeros((bins_signal_low_range, max_pulses), np.float64)\n",
- "hists_signal_high = np.zeros((bins_signal_low_range, max_pulses), np.float64)\n",
+ "hists_signal_low = np.zeros((bins_signal_low_range, rng_pulse_idx), np.float64)\n",
+ "hists_signal_high = np.zeros((bins_signal_low_range, rng_pulse_idx), np.float64)\n",
"hists_gain_vs_signal = np.zeros((bins_gain_vs_signal), np.float64)\n",
"hists_dig_gain_vs_signal = np.zeros((bins_dig_gain_vs_signal), np.float64)\n",
"gain_stats = 0\n",
@@ -542,7 +568,7 @@
" print(\"Running {} tasks parallel\".format(len(inp)))\n",
" p = partial(correct_module, max_cells, do_rel_gain, index_v, CHUNK_SIZE, total_sequences,\n",
" sequences_qm, bins_gain_vs_signal, bins_signal_low_range, bins_signal_high_range,\n",
- " bins_dig_gain_vs_signal, max_pulses, dbparms, fileparms, nodb, chunk_size_idim,\n",
+ " bins_dig_gain_vs_signal, max_pulses, rng_pulse_idx, dbparms, fileparms, nodb, chunk_size_idim,\n",
" special_opts, il_mode, loc, dinstance, force_hg_if_below, force_mg_if_below,\n",
" mask_noisy_adc, adjust_mg_baseline, acq_rate, dont_zero_nans, dont_zero_orange)\n",
" \n",