esynth for the ant

XRStools/tools_sequencer_esynth.py

@@ -388,9 +388,6 @@ def tools_sequencer(  peaks_shifts = None,
                       selected_rois = None, 
                       scalar_products_target_file     = None,
 
-                      volume_retrieval_beta  = None,
-                      volume_retrieval_niter = None ,
-
                       energy_custom_grid =  None,
                       custom_components_file = None  ,
                       interpolation_infos_file =  None,

nonregressions/volumes/esrf_scans/esynth/batch_extraction_esynth1.py

@@ -20,7 +20,7 @@ def main():
     monitor_column = "izero/0.000001"
     
     first_scan_num = 651 
-    Ydim        = 25
+    Ydim        = None # not used. it is the scan lenght , it is given by the data, contained in the scan
     Zdim        = 10
     Edim        = 7
 
@@ -42,10 +42,10 @@ def main():
         ["beta_optical"  , 0.1],
         ["niter_global"  , 3  ]
     ])
-                                 
+
+    resynth_z_square = 0
+    
     selected_rois = list(range(0,72))
-    volume_retrieval_beta  = 6.0e-20
-    volume_retrieval_niter = 100 
     
     steps_to_do = {
         "do_step_make_roi":                      False,
@@ -83,22 +83,24 @@ def main():
     ###### peaks_shifts = h5py.File("../peaks_positions_for_analysers.h5","r")["peaks_positions"][()]
     ###### assert( len(peaks_shifts) == 72)
     
-    roiob = xrs_rois.roi_object()
-    roiob.loadH5( roi_target_path  )
-    elastic = xrs_read.Hydra( datadir )
-    elastic.set_roiObj( roiob )
-    elastic.get_compensation_factor( elastic_scan_for_peaks_shifts , method='sum')
-    el_dict = elastic.cenom_dict
-    Enominal = np.median(  list( el_dict.values() ) )
-    peaks_shifts = np.array([    el_dict["ROI%02d"%i] if ("ROI%02d"%i) in  el_dict else nan    for i in range( 72)  ] ) 
-    peaks_shifts-= Enominal
+    if steps_to_do["do_step_interpolation_coefficients"]:
+        roiob = xrs_rois.roi_object()
+        roiob.loadH5( roi_target_path  )
+        elastic = xrs_read.Hydra( datadir )
+        elastic.set_roiObj( roiob )
+        elastic.get_compensation_factor( elastic_scan_for_peaks_shifts , method='sum')
+        el_dict = elastic.cenom_dict
+        Enominal = np.median(  list( el_dict.values() ) )
+        peaks_shifts = np.array([    el_dict["ROI%02d"%i] if ("ROI%02d"%i) in  el_dict else nan    for i in range( 72)  ] ) 
+        peaks_shifts -= Enominal
+    else:
+        peaks_shifts = None
     
     ##############################################################
     ##########################################################################
 
-
-    
-    tools_sequencer_esynth.tools_sequencer(  peaks_shifts          = peaks_shifts          ,
+    tools_sequencer_esynth.tools_sequencer(
+        peaks_shifts          = peaks_shifts          ,
                       datadir               = datadir               ,
                       filter_path           = filter_path           ,
                       roi_scan_num          = roi_scan_num          ,
@@ -122,14 +124,12 @@ def main():
                       response_fit_options = response_fit_options,
                       
                       resynthetised_reference_and_roi_target_file = resynthetised_reference_and_roi_target_file,
+                      resynth_z_square = resynth_z_square,
 
                       selected_rois = selected_rois,
                       
                       scalar_products_target_file      = scalar_products_target_file ,
                       
-                      volume_retrieval_beta  = volume_retrieval_beta ,
-                      volume_retrieval_niter = volume_retrieval_niter ,
-
                       energy_custom_grid =  energy_custom_grid,
                       custom_components_file = custom_components_file,
                       interpolation_infos_file =  interpolation_infos_file

nonregressions/volumes/esrf_scans/fourmis/esynth/batch_extraction_esynth.py

+import numpy as np
+import h5py
+import glob
+import json
+import os
+import h5py
+import math
+
+from XRStools import tools_sequencer_esynth
+from XRStools import xrs_read,  xrs_rois
+
+import os
+def main():
+    
+    filter_path = None
+    # filter_path = "mask.h5:/FILTER_MASK/filter"
+
+    roi_scan_num   = list(range(592,600))
+    reference_scan_list = list(range(592,600))
+    
+    monitor_column = "izero/0.000001"
+    
+    first_scan_num = 464
+    Ydim        = None   # not used, it is the scan lenght , it is given by the data, contained in the scang
+    Zdim        = 2
+    Edim        = 62
+
+    elastic_scan_for_peaks_shifts = 38
+
+    energy_custom_grid = 9.96595 + np.arange(72)*0.0005
+    ### custom_components_file = "abc.h5"
+    custom_components_file = None
+    
+    datadir =   "/data/id20/inhouse/data/run5_17/run7_ihr/"
+
+    # If reference_clip is not None, then a smaller part of the reference scan is considered
+    # This may be usefule to obtain smaller volumes containing the interesting part
+    # The used reference scan  will the correspond to the positions from reference_clip[0] to reference_clip[1]-1 included
+    ###########
+    reference_clip = None
+    # reference_clip = [ 90, 180 ]
+
+    ## in the reference scan for each position there is a spot with a maximum. We set zero the background which is further than
+    ## such radius from the maximum
+    isolate_spot_by = 7
+
+    #### For the fit of the response function based on reference scans
+    response_fit_options = dict( [
+        ["niter_optical" , 40],
+        ["beta_optical"  , 0.1],
+        ["niter_global"  , 1  ]
+    ])
+
+    resynth_z_square = 0
+
+    selected_rois = list(range(0,24)) + list( range(36,60) ) 
+    
+    steps_to_do = {
+        "do_step_make_roi":                      False,
+        "do_step_sample_extraction":             False,
+        "do_step_extract_reference_scan":        False,
+        "do_step_fit_reference_response":               False,
+        "do_step_resynthetise_reference":        False,
+        
+        "do_step_scalars"               :    False,
+
+        "do_step_interpolation_coefficients":    True,
+        
+        "do_step_finalise_for_fit":              False
+    }
+
+    
+    os.system("mkdir results")
+
+
+    scalar_products_target_file  = "results/scalar_products_target_file.h5"
+
+    roi_target_path    = "results/myrois.h5:/ROIS"
+        
+    signals_target_file = "results/signals.h5"
+    
+    extracted_reference_target_file = "results/reference.h5"
+    
+    response_target_file = "results/response.h5"
+
+    resynthetised_reference_and_roi_target_file = "results/resynthetised_roi_and_scan.h5"
+
+    interpolation_infos_file =  "interpolation_infos.json"
+
+    ###########################################################################################
+    ######  LOADING PEAKS SHIFTS
+    ###### peaks_shifts = h5py.File("../peaks_positions_for_analysers.h5","r")["peaks_positions"][()]
+    ###### assert( len(peaks_shifts) == 72)
+
+    if steps_to_do["do_step_interpolation_coefficients"]:
+        ## in this case peaks shifts are needed. They are passed
+        # to tools_sequencer which calculates the coefficients
+        roiob = xrs_rois.roi_object()
+        roiob.loadH5( roi_target_path  )
+        elastic = xrs_read.Hydra( datadir )
+        elastic.set_roiObj( roiob )
+        elastic.get_compensation_factor( elastic_scan_for_peaks_shifts , method='sum')
+        el_dict = elastic.cenom_dict
+        Enominal = np.median(  list( el_dict.values() ) )
+        peaks_shifts = np.array([    el_dict["ROI%02d"%i] if ("ROI%02d"%i) in  el_dict else nan    for i in range( 72)  ] )
+        peaks_shifts -= Enominal
+    else:
+        peaks_shifts = None
+    
+    ##############################################################
+    ##########################################################################
+    
+    tools_sequencer_esynth.tools_sequencer(peaks_shifts          = peaks_shifts          ,
+                      datadir               = datadir               ,
+                      filter_path           = filter_path           ,
+                      roi_scan_num          = roi_scan_num          ,
+                      roi_target_path       = roi_target_path       ,
+                      
+                      steps_to_do = steps_to_do,
+                      
+                      first_scan_num =  first_scan_num,
+                      Ydim        =  Ydim       ,                    # not used 
+                      Zdim        =  Zdim       ,
+                      Edim        =  Edim       ,
+
+                      monitor_column = monitor_column,
+                      signals_target_file = signals_target_file,
+
+                      reference_scan_list = reference_scan_list,
+                      reference_clip = reference_clip,
+                      extracted_reference_target_file = extracted_reference_target_file ,
+                      isolate_spot_by =  isolate_spot_by,
+                      response_target_file = response_target_file,
+                      response_fit_options = response_fit_options,
+                      
+                      resynthetised_reference_and_roi_target_file = resynthetised_reference_and_roi_target_file,
+                      resynth_z_square = resynth_z_square,
+                                             
+                      selected_rois = selected_rois,
+
+                      scalar_products_target_file      = scalar_products_target_file ,
+                                           
+                      energy_custom_grid =  energy_custom_grid,
+                      custom_components_file = custom_components_file,
+                      interpolation_infos_file =  interpolation_infos_file
+    )
+    
+            
+            
+main()
+
+

nonregressions/volumes/esrf_scans/fourmis/interp/batch_extraction_interp.py

@@ -30,7 +30,6 @@ def main():
     Zdim        = 2
     Edim        = 62
 
-    rois_are_ready = True
     elastic_scan_for_peaks_shifts = 38
 
     datadir =   "/data/id20/inhouse/data/run5_17/run7_ihr/"
@@ -110,10 +109,7 @@ def main():
         el_dict = elastic.cenom_dict
         Enominal = np.median(  list( el_dict.values() ) )
         peaks_shifts = np.array([    el_dict["ROI%02d"%i] if ("ROI%02d"%i) in  el_dict else nan    for i in range( 72)  ] )
-
-        Enominal = np.median(peaks_shifts)
         peaks_shifts-= Enominal
-        
     else:
         peaks_shifts = None
     

nonregressions/volumes/esrf_scans/interpolation/batch_extraction_interp.py

@@ -37,6 +37,8 @@ def main():
         ["niter_global"  , 3  ]
     ])                                 
 
+    resynth_z_square = 0
+
     selected_rois = list(range(0,24)) + list( range(36,60) ) 
 
     scal_prod_use_optional_solution = True 
@@ -119,6 +121,7 @@ def main():
                       response_fit_options = response_fit_options,
                       
                       resynthetised_reference_and_roi_target_file = resynthetised_reference_and_roi_target_file,
+                      resynth_z_square = 0
 
                       selected_rois = selected_rois,