Restore save fluospectrum.mat in XRF.py and remove the correction with ICR/OCR...

Restore save fluospectrum.mat in XRF.py and remove the correction with ICR/OCR in the variable spectrums

CHANGELOG.md

 # Release notes
 
+## v2.12.1
+- Restore save fluospectrum.mat in XRF.py
+
+- Remove the tiny correction with ICR/OCR in XRF.py, to have exactly the same numbers in the variable spectrums, and in the saved file fluospectrum.mat
+
+
 ## v2.12
 - New rules for numbering versions: vX.Y.Z with X major, Y minor, Z patch. Each new version increments Z (not used if Z=0). If the file Example.ipynb cannot run with the new libraries, increment Y and restart at Z=0.
 

JupyLabBook.ipynb

@@ -49,7 +49,7 @@
    },
    "outputs": [],
    "source": [
-    "__version__ = '2.12'\n",
+    "__version__ = '2.12.1'\n",
     "print(\"JupyLabBook version: %s\"%__version__)\n",
     "print(\"More info on: %s\"%\"https://gitlab.com/soleil-data-treatment/soleil-beamlines/soleil-beamline-sirius/JupyLabBook\")\n",
     "\n",
@@ -112,6 +112,26 @@
     "\n",
     "FE.Action.Check_and_init(expt)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": [
+     "notPrint"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "FE.Action.Choose(expt)"
+   ]
   }
  ],
  "metadata": {

README.md

@@ -2,7 +2,7 @@
 A Jupyter Notebook used as an interactive lab book on the beamline SIRIUS (SOLEIL Synchrotron).
 
 ### Latest version
-JupyLabBook.ipynb : 2.12
+JupyLabBook.ipynb : 2.12.1
 
 # User manual
 See the file JupyLabBook_User_Manual.pdf in the repository.

lib/extraction/XRF.py

@@ -4,10 +4,12 @@ Module for extracting, plotting, and saving an XRF scan.
 """
 import os
 import sys
+import io
 import datetime
 import numpy as np
 import matplotlib.pyplot as plt
 from matplotlib import colors
+from contextlib import redirect_stdout
 
 from lib.extraction.common import PyNexus as PN
 
@@ -214,9 +216,9 @@ def Extract(nxs_filename, recording_dir,
                        datetime.datetime.fromtimestamp(epoch_time[0]),
                        datetime.datetime.fromtimestamp(epoch_time[-1]))
 
-    def extract_and_correct(ind_spectrum):
+    def extract_and_correct(ind_spectrum, is_correction):
         """
-        Extract the requested fluospectrum from the nexus file and correct it with ICR/OCR.
+        Extract the requested fluospectrum from the nexus file and correct it with ICR/OCR, if is_correction is True.
         """
         is_icr_found = False
         is_ocr_found = False
@@ -240,8 +242,12 @@ def Extract(nxs_filename, recording_dir,
                 print(_RED+"OCR not found in data. Taking OCR = spectrum_intensity/counting_time."+_RESET)
                 OCR = np.array([np.sum(fluospectrum[n])/integration_time[n] for n in range(len(fluospectrum))])
 
+            if is_correction:
                 ratio = np.array([ICR[n]/OCR[n] if (~np.isclose(OCR[n],0.) & ~np.isnan(OCR[n]) & ~np.isnan(ICR[n]))
                                   else 0. for n in range(len(ICR))])
+            else:
+                 ratio = np.array([1. if (~np.isclose(OCR[n],0.) & ~np.isnan(OCR[n]) & ~np.isnan(ICR[n]))
+                                  else 0. for n in range(len(ICR))])
             spectrums_corr = np.array([fluospectrum[n]*ratio[n] for n in range(len(ratio))])
             return spectrums_corr
 
@@ -255,7 +261,7 @@ def Extract(nxs_filename, recording_dir,
     allspectrums_corr = np.zeros((nbpts, 2048))
 
     for i in list_elems:
-        allspectrums_corr  += extract_and_correct(str(i))
+        allspectrums_corr  += extract_and_correct(ind_spectrum = str(i), is_correction = False)
 
     ind_non_zero_spectrums = np.where(np.sum(allspectrums_corr, axis = 1)>10.)[0]
     #list_ranges = np.split(ind_non_zero_spectrums, np.where(np.diff(ind_non_zero_spectrums) != 1)[0]+1)
@@ -447,7 +453,7 @@ def Plot(channels, eVs, spectrums, first_non_zero_spectrum, last_non_zero_spectr
 def Save(nxs_filename,  stamps0D, data0D, fig_spectrogram, fig_sum, fig_first_last,
          recording_dir, fast, working_dir, verbose):
     """
-    Use the PyNexus library to convert the Nexus file into a .dat file.
+    Use the PyNexus library to convert the Nexus file into a .dat and a .mat files.
 
     Parameters
     ----------
@@ -481,6 +487,22 @@ def Save(nxs_filename,  stamps0D, data0D, fig_spectrogram, fig_sum, fig_first_la
     np.savetxt(savename+'.dat', np.transpose(data0D), header = header0D,
                comments = '', fmt='%s', delimiter = '\t')
 
+    ## save non-corrected spectrums
+    # we assume extraction was already checked with Extract
+    nxs_path = recording_dir+nxs_filename
+    nexus = PN.PyNexusFile(nxs_path, fast=fast)
+    # get stamps and Data
+    stamps, data = nexus.extractData()
+    # extract without printing the sensors in the notebook
+    f = io.StringIO()
+    with redirect_stdout(f):
+        old_nexus_filename = nexus.filename
+        nexus.filename = working_dir + nxs_filename
+        nexus.saveOneDExtractedData((stamps, data))
+        nexus.filename = old_nexus_filename
+    out = f.getvalue()
+    nexus.close()
+
     # figures in pdf
     if fig_spectrogram is not None:
         plt.figure(fig_spectrogram)