diff --git a/notebooks/Jungfrau/Jungfrau_Create_Fit_Spectra_Histos_NBC.ipynb b/notebooks/Jungfrau/Jungfrau_Create_Fit_Spectra_Histos_NBC.ipynb
index 6a8eef93999bc34a4980993c15b83a2a7df9838c..be566bb2cfff4a960830a2da8485eb3a8f8b2223 100644
--- a/notebooks/Jungfrau/Jungfrau_Create_Fit_Spectra_Histos_NBC.ipynb
+++ b/notebooks/Jungfrau/Jungfrau_Create_Fit_Spectra_Histos_NBC.ipynb
@@ -41,7 +41,7 @@
"det_src_template = '{}/DET/{}:daqOutput'\n",
"control_src_template = '{}/DET/CONTROL'\n",
"extra_dims = ['cell', 'row', 'col'] # labels for the DataArray dims after the first\n",
- "_fit_func = 'CHARGE_SHARING' # function used to fit the single photon peak\n",
+ "fit_func = 'CHARGE_SHARING' # function used to fit the single photon peak\n",
"off_sub = True\n",
"adc_fit = True\n",
"is_strixel = False\n",
@@ -481,7 +481,7 @@
"metadata": {},
"outputs": [],
"source": [
- "fout_temp = f\"R{runs[0]:04d}_{proposal.upper()}_Gain_Spectra_{{}}_{_fit_func}_Fit.h5\"\n",
+ "fout_temp = f\"R{runs[0]:04d}_{proposal.upper()}_Gain_Spectra_{{}}_{fit_func}_Fit.h5\"\n",
"\n",
"for da in karabo_da:\n",
" _edges = np.array(edges[da])\n",
@@ -497,7 +497,7 @@
" partial_fit = partial(\n",
" jungfrau_ff.fit_histogram,\n",
" x,\n",
- " _fit_func,\n",
+ " fit_func,\n",
" n_sigma,\n",
" rebin,\n",
" ratio,\n",
diff --git a/notebooks/Jungfrau/Jungfrau_Create_Gain_maps_NBC.ipynb b/notebooks/Jungfrau/Jungfrau_Create_Gain_maps_NBC.ipynb
index c13351f6ccabebb59f61d8ab7d7c5c75d78cad57..52e339e81a5004f53cc856eb89151fb915116199 100755
--- a/notebooks/Jungfrau/Jungfrau_Create_Gain_maps_NBC.ipynb
+++ b/notebooks/Jungfrau/Jungfrau_Create_Gain_maps_NBC.ipynb
@@ -31,7 +31,7 @@
"\n",
"karabo_id = 'MID_EXP_JF500K2' # karabo prefix of Jungfrau devices\n",
"karabo_da = ['']\n",
- "_fit_func = 'CHARGE_SHARING' # function used to fit the single photon peak\n",
+ "fit_func = 'CHARGE_SHARING' # function used to fit the single photon peak\n",
"gains = [0, 1, 2]\n",
"# Parameter conditions\n",
"bias_voltage = -1 # detector bias voltage\n",
@@ -44,7 +44,7 @@
"# Condition limits\n",
"bias_voltage_lims = [0, 200]\n",
"integration_time_lims = [0.1, 1000]\n",
- "spectra_fit_temp = 'R{:04d}_{}_Gain_Spectra_{}_{}_Fit.h5' # 'R{:04d}_{proposal.upper()}_Gain_Spectra_{da}_{_fit_func}_Fit.h5'\n",
+ "spectra_fit_temp = 'R{:04d}_{}_Gain_Spectra_{}_{}_Fit.h5' # 'R{:04d}_{proposal.upper()}_Gain_Spectra_{da}_{fit_func}_Fit.h5'\n",
"creation_time = \"\" # To overwrite the measured creation_time. Required Format: YYYY-MM-DD HR:MN:SC e.g. \"2022-06-28 13:00:00\"\n",
"g_map_old = '' # '/gpfs/exfel/data/user/mramilli/jungfrau/module_PSI_gainmaps/M302/gainMaps_M302_2022-02-23.h5' # old gain map file path to calculate gain ratios G0/G1 and G1/G2. Set to \"\" to get last gain constant from the database.\n",
"old_gain_dataset_name = 'gain_map_g0' # name of the data structure in the old gain map\n",
@@ -55,11 +55,11 @@
"g0_fit_dataset = 'gainMap_fit' # name of the data structure in the fit files\n",
"E_ph = 8.048 # photon energy of the peak fitted\n",
"badpixel_threshold_sigma = 3. # number of std in gain distribution to mark bad pixels\n",
- "_roi = [0, 1024, 0, 256] # ROI to consider to evaluate gain distribution (for bad pixels evaluation)\n",
+ "roi = [0, 1024, 0, 256] # ROI to consider to evaluate gain distribution (for bad pixels evaluation)\n",
"control_src_template = '{}/DET/CONTROL'\n",
"\n",
"# CALCAT API parameters\n",
- "cal_db_interface = \"tcp://max-exfl-cal-001:8020\" # the database interface to use\n",
+ "cal_db_interface = \"tcp://max-exfl-cal001:8020\" # the database interface to use\n",
"cal_db_timeout = 180000\n",
"\n",
"\n",
@@ -121,7 +121,7 @@
"outputs": [],
"source": [
"run = runs[0]\n",
- "out_folder = Path(out_folder) # TODO\n",
+ "out_folder = Path(out_folder)\n",
"proposal = list(filter(None, in_folder.strip('/').split('/')))[-2]\n",
"file_loc = f\"proposal:{proposal} runs:{run}\"\n",
"report = get_report(metadata_folder)\n",
@@ -154,7 +154,7 @@
"g0_new = dict()\n",
"for da in karabo_da:\n",
" with h5file(\n",
- " out_folder / spectra_fit_temp.format(run, proposal.upper(), da, _fit_func),\n",
+ " out_folder / spectra_fit_temp.format(run, proposal.upper(), da, fit_func),\n",
" 'r'\n",
" ) as f:\n",
" if is_strixel:\n",
@@ -337,7 +337,7 @@
" if correct_offset:\n",
" display(Markdown(\"#### Correct with better pedestal estimation\"))\n",
" with h5file(\n",
- " out_folder / spectra_fit_temp.format(run, proposal.upper(), da, _fit_func),\n",
+ " out_folder / spectra_fit_temp.format(run, proposal.upper(), da, fit_func),\n",
" 'r'\n",
" ) as fc:\n",
" corr = np.array(fc[g0_fit_dataset])\n",
@@ -445,7 +445,7 @@
" \n",
" return mskd\n",
"\n",
- "def eval_bpidx(d_in, badpixel_threshold_sigma=badpixel_threshold_sigma, roi=_roi):\n",
+ "def eval_bpidx(d_in, badpixel_threshold_sigma=badpixel_threshold_sigma, roi=roi):\n",
" \"\"\"\n",
" evaluates the indexes of the pixels with high deviation from the median value\n",
" args:\n",
diff --git a/notebooks/Jungfrau/Jungfrau_gain_Spectra_Fit_Summary_NBC.ipynb b/notebooks/Jungfrau/Jungfrau_gain_Spectra_Fit_Summary_NBC.ipynb
index 853ec36c59753feb63ba2daef5c1d4e3b3ec79a8..2873982acaf2773caff82eff5a93aba7aa30febd 100644
--- a/notebooks/Jungfrau/Jungfrau_gain_Spectra_Fit_Summary_NBC.ipynb
+++ b/notebooks/Jungfrau/Jungfrau_gain_Spectra_Fit_Summary_NBC.ipynb
@@ -25,7 +25,7 @@
"karabo_da = [] # list of data aggregators, which corresponds to different JF modules. This is only needed for the detectors of one module.\n",
"karabo_id = \"SPB_IRDA_JF4M\" # detector identifier.\n",
"creation_time = \"\" # To overwrite the measured creation_time. Required Format: YYYY-MM-DD HR:MN:SC e.g. \"2022-06-28 13:00:00\"\n",
- "_fit_func = 'CHARGE_SHARING' # function used to fit the single photon peak\\\n",
+ "fit_func = 'CHARGE_SHARING' # function used to fit the single photon peak\\\n",
"g0_fit_dataset = 'gainMap_fit' # name of the data structure in the fit files\n",
"spectra_fit_temp = 'R{:04d}_{}_Gain_Spectra_{}_{}_Fit.h5'"
]
@@ -46,7 +46,7 @@
"import matplotlib.gridspec as gridspec\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
- "from IPython.display import Markdown, display\n",
+ "from IPython.display import display\n",
"\n",
"matplotlib.use(\"agg\")\n",
"%matplotlib inline\n",
@@ -93,7 +93,7 @@
"\n",
"for i, da in enumerate (da_to_pdu.keys()):\n",
" with h5file(\n",
- " Path(out_folder) / spectra_fit_temp.format(run, proposal.upper(), da, _fit_func),\n",
+ " Path(out_folder) / spectra_fit_temp.format(run, proposal.upper(), da, fit_func),\n",
" 'r'\n",
" ) as f:\n",
" stacked_constants[i] = np.moveaxis(\n",
@@ -128,7 +128,7 @@
"\n",
"for i, da in enumerate (da_to_pdu.keys()):\n",
" with h5file(\n",
- " Path(out_folder) / spectra_fit_temp.format(run, proposal.upper(), da, _fit_func),\n",
+ " Path(out_folder) / spectra_fit_temp.format(run, proposal.upper(), da, fit_func),\n",
" 'r'\n",
" ) as f:\n",
" stacked_constants[i] = np.moveaxis(\n",
diff --git a/notebooks/Jungfrau/Jungfrau_gain_map_Summary_NBC.ipynb b/notebooks/Jungfrau/Jungfrau_gain_map_Summary_NBC.ipynb
index 5939c1e2a0bc76be9bed9e1a4879de3c5a51d29a..3f70fcc90a122b1dde2e6cfd703108cbe0d91437 100644
--- a/notebooks/Jungfrau/Jungfrau_gain_map_Summary_NBC.ipynb
+++ b/notebooks/Jungfrau/Jungfrau_gain_map_Summary_NBC.ipynb
@@ -25,7 +25,6 @@
"karabo_da = [] # list of data aggregators, which corresponds to different JF modules. This is only needed for the detectors of one module.\n",
"karabo_id = \"SPB_IRDA_JF4M\" # detector identifier.\n",
"creation_time = \"\" # To overwrite the measured creation_time. Required Format: YYYY-MM-DD HR:MN:SC e.g. \"2022-06-28 13:00:00\"\n",
- "_fit_func = 'CHARGE_SHARING' # function used to fit the single photon peak\n",
"g0_fit_dataset = 'gainMap_fit' # name of the data structure in the fit files"
]
},