diff --git a/cal_tools/cal_tools/agipdlib.py b/cal_tools/cal_tools/agipdlib.py
index 5ac64e76d2636a50f9326dddaf6b9112283e99a1..fc5412fb0bfe46b8d1650da80617d70822ec9bc2 100644
--- a/cal_tools/cal_tools/agipdlib.py
+++ b/cal_tools/cal_tools/agipdlib.py
@@ -91,8 +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: pulse indices to consider for preview histograms
- :param rng_pulse_idx: maximum pulse idx to consider for preview histograms
+ :param max_pulses: maximum pulse indices to consider for preview histograms
+ :param rng_pulse_idx: range of pulse indices 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
@@ -1029,20 +1029,25 @@ class AgipdCorrections:
if self.melt_snow is not False:
msk |= snowmask
+ agipd_base = self.agipd_base
+ allpulses = np.squeeze(self.infile[agipd_base + "image/pulseId"])
+
# for the first chunk output some statistics
if cidx == 0:
copim = copy.copy(im)
copim[copim < self.median_noise] = np.nan
- bins = (self.bins_signal_low_range, self.rng_pulse_idx)
- rnge = [[-50, 1000], [self.max_pulses[0], self.max_pulses[-1]]]
+ bins = (self.bins_signal_low_range, self.max_pulses)
+ rnge = [[-50, 1000], [allpulses[self.rng_pulse_idx[0]],
+ allpulses[self.rng_pulse_idx[-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.rng_pulse_idx)
- rnge = [[0, 200000], [self.max_pulses[0], self.max_pulses[-1]]]
+ bins = (self.bins_signal_high_range, self.max_pulses)
+ rnge = [[0, 200000], [allpulses[self.rng_pulse_idx[0]],
+ allpulses[self.rng_pulse_idx[-1]]]]
H, xe, ye = np.histogram2d(np.nanmean(copim, axis=(1, 2)),
pulseId,
bins=bins,
@@ -1161,7 +1166,7 @@ class AgipdCorrections:
can_calibrate = (allcells < max_cells)
- can_calibrate &= (allpulses < np.max(allpulses[np.array(self.max_pulses)]))
+ can_calibrate &= (allpulses < np.max(allpulses[np.array(self.rng_pulse_idx)]))
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 59971159399109e659f8cae05001d086fd5b289e..05f46a010bc4686fbf99b1fe5b96d2a2a3c3cb65 100644
--- a/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
+++ b/notebooks/AGIPD/AGIPD_Correct_and_Verify.ipynb
@@ -502,39 +502,31 @@
"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",
+ "# Checking the max_pulses input\n",
+ "# Applying default values if input not 3 elements.\n",
+ "if len(max_pulses) == 3:\n",
+ " rng_pulse_idx = list(range(max_pulses[0],\n",
+ " max_pulses[1],\n",
+ " max_pulses[2]))\n",
+ " max_pulses = len(rng_pulse_idx)\n",
+ "elif len(max_pulses) == 2:\n",
+ " rng_pulse_idx = list(range(max_pulses[0],\n",
+ " max_pulses[1],\n",
+ " 1))\n",
+ " max_pulses = len(rng_pulse_idx)\n",
+ "elif len(max_pulses) == 1:\n",
+ " rng_pulse_idx = list(range(max_pulses[0]))\n",
+ " max_pulses = max_pulses[0]\n",
+ "else:\n",
+ " raise ValueError(\"Wrong input for max_pulses {} \\n\".format(max_pulses),\n",
+ " \"max_pulses should have 3 arguments maximum\")\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, rng_pulse_idx), np.float64)\n",
- "hists_signal_high = np.zeros((bins_signal_low_range, rng_pulse_idx), np.float64)\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_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",