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Commit d7574d9a authored by myron's avatar myron
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reorganised reference extration

parent 79cb683a
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XRStools/XRS_swissknife.py
View file @ d7574d9a
......@@ -193,10 +193,10 @@ from XRStools import reponse_percussionelle
def check_allowed( mydata, allowed_keys ) :
def check_allowed_keys( mydata, allowed_keys ) :
for k in mydata.keys():
if not k in allowed_keys:
raise ValueError( (" key "+str(k) +" not in allowed keys :": + str(allowed_keys)) )
raise ValueError( (" key "+str(k) +" not in allowed keys :"+ str(allowed_keys)) )
def dump_anydict_as_map( anydict):
yaml.add_representer( anydict, _represent_dictorder)
......@@ -880,7 +880,7 @@ def loadscan_2Dimages(mydata):
#
"""
allowed_keys = ["roiaddress", 'monitorcolumn', 'recenterings', 'recenterings_confirmed', 'energycolumn', 'edfName', 'isolateSpot', "expdata","scan_interval","signaladdress","save_also_roi", 'sumto1D',]
allowed_keys = ["roiaddress", 'monitorcolumn', 'recenterings', 'recenterings_confirmed', 'energycolumn', 'edfName', 'isolateSpot', "expdata","scan_interval","scan_list","signaladdress","save_also_roi", 'sumto1D',]
check_allowed_keys(mydata, allowed_keys)
......@@ -964,12 +964,23 @@ def loadscan_2Dimages(mydata):
recenterings=recenterings)
reader.set_roiObj(roiob)
scan_interval = mydata["scan_interval"]
print( " LOAD ")
todo_list = []
ninterval = len(scan_interval)//2
for i in range(ninterval):
todo_list = todo_list + list(range( int(scan_interval[2*i]), int(scan_interval[2*i+1])) ) # *scan_interval[2*i :2*i+2])
if "scan_interval" in mydata:
scan_interval = mydata["scan_interval"]
ninterval = len(scan_interval)//2
for i in range(ninterval):
todo_list = todo_list + list(range( int(scan_interval[2*i]), int(scan_interval[2*i+1])) ) # *scan_interval[2*i :2*i+2])
else:
scan_list = mydata["scan_list"]
for i in scan_list:
todo_list = todo_list + [int(i)]
mytodo = np.array_split(todo_list, nprocs) [myrank]
print( mytodo)
......@@ -4146,7 +4157,7 @@ swissknife_operations={
"superR_getVolume_Esynt" : superR_getVolume_Esynt,
"calculate_recenterings" : calculate_recenterings,
"extract_spectra" : extract_spectra,
"sum_scans2maps" : sum_scans2maps,
# "sum_scans2maps" : sum_scans2maps,
# "XRSprediction" : XRSprediction,
# "Fourc_extraction" : Fourc_extraction,
# "Hydra_extraction" : Hydra_extraction,
......
nonregressions/volumes/interpola_1/batch_extraction_esynth1.py
View file @ d7574d9a
......@@ -22,7 +22,8 @@ def main():
roi_target_path = "results/myrois.h5:/ROIS"
# roi_target_path = "rr.h5:/extracted/ROI_AS_SELECTED"
filter_path = "mask.h5:/FILTER_MASK/filter"
filter_path = "mask.h5:/FILTER_MASK/filter"
roi_scan_num = [245,246,247]
first_scan_num = 651
......@@ -55,9 +56,8 @@ def main():
"do_step_make_roi": False,
"do_step_sample_extraction": False,
"do_step_interpolation": False,
"do_extract_reference_scan": True,
"do_extract_reference_scan": False,
"do_step_make_reference": False,
"do_step_scalar_products": False,
"do_step_finalise_for_fit": False
......@@ -129,14 +129,14 @@ def select_rois( datadir = None, roi_scan_num=None, roi_target_path = None, fil
filter_path = filter_path
)
process_input( inputstring, exploit_slurm_mpi = 0 )
def get_reference( roi_path = None,
datadir = None,
reference_scan_num=None,
reference_scan_list = None,
monitor_column = None,
extracted_reference_target_file = None,
isolate_spot_by = None,
isolate_spot_by = None
):
signal_path = extracted_reference_target_file + ":/"
......@@ -144,9 +144,9 @@ def get_reference( roi_path = None,
loadscan_2Dimages :
expdata : {expdata}
roiaddress : {roi_path}
monitor_column : {monitor_column}
scan_interval : [{reference_scan_num},{reference_scan_num_plus1} ]
signaladdress : {signal_path}
monitorcolumn : {monitor_column}
scan_list : {reference_scan_list}
signaladdress : "{extracted_reference_target_file}:/references"
isolateSpot : {isolate_spot_by}
save_also_roi : True
......@@ -154,15 +154,15 @@ def get_reference( roi_path = None,
energycolumn : 'stx'
"""
s=inputstring.format(
exp_data = os.path.join( datadir, "hydra"),
reference_scan_num = reference_scan_num,
reference_scan_num_plus1 = reference_scan_num+1,
expdata = os.path.join( datadir, "hydra"),
reference_scan_list = reference_scan_list,
monitor_column = monitor_column,
roi_path = roi_path,
isolate_spot_by = isolate_spot_by,
signal_path = signal_path
signal_path = signal_path,
extracted_reference_target_file = extracted_reference_target_file
)
process_input( s , exploit_slurm_mpi = 1)
process_input( s , exploit_slurm_mpi = 0)
def extract_sample_givenrois(
......@@ -229,7 +229,7 @@ def interpolate( peaks_shifts, interp_file_str, interp_file_target_str):
print ( roi_num, "===== " , t_ene+de , ene_list .min() , t_ene+de , ene_list .max() )
if t_ene+de < ene_list .min() or t_ene+de > ene_list .max():
continue
print ( " CONTINUO ", t_ene+de, ene_list .min() ,ene_list .max() )
i0 = np.searchsorted( ene_list , t_ene+de )-1
......@@ -362,50 +362,48 @@ def tools_sequencer( peaks_shifts = None,
if(steps_to_do["do_extract_reference_scan"]): # of course we need the REFERENCE SCAN
for reference_scan_num in reference_scan_list:
get_reference( datadir = datadir,
monitor_column = monitor_column,
extracted_reference_target_file = extracted_reference_target_file,
isolate_spot_by = isolate_spot_by,
reference_scan_num = reference_scan_num
)
get_reference( datadir = datadir,
roi_path = roi_path,
monitor_column = monitor_column,
extracted_reference_target_file = extracted_reference_target_file,
isolate_spot_by = isolate_spot_by,
reference_scan_list = reference_scan_list
)
# for other in other_rois_for_ref:
# os.system("cp roi_%d.h5 roi_%d.h5"%(roi_scann, other) )
# if reference_clip is not None:
if reference_clip is not None:
# clip1, clip2= reference_clip
clip1, clip2= reference_clip
# ftarget = h5py.File( "roi_%d.h5" % roi_scann ,"r+")
# target_group = ftarget["extracted/ROI_AS_SELECTED/calibration_scan/scans/Scan%03d"% roi_scann ]
# for k in target_group.keys():
# if k != "motorDict":
# print(" SHRINKING scan for ROI %s in file roi_%d.h5 " %( k, roi_scann ))
# for dsn in ["matrix", "monitor", "xscale"]:
# mat = target_group[k][dsn][()]
# del target_group[k][dsn]
# target_group[k][dsn] = mat[clip1:clip2]
# ftarget.close()
# for other in other_rois_for_ref:
# get_reference(roi_scan_num=other)
# ftarget = h5py.File( "roi_%d.h5" % roi_scann ,"r+")
# fsource = h5py.File( "roi_%d.h5" % other , "r")
# source_group = fsource["extracted/ROI_AS_SELECTED/calibration_scan/scans/Scan%03d"% other ]
# target_group = ftarget["extracted/ROI_AS_SELECTED/calibration_scan/scans/Scan%03d"% roi_scann ]
# for k in target_group.keys():
# if k != "motorDict":
# print(" ADDING data for ROI %s from file roi_%d.h5 " %( k, other ))
# mat = source_group[k]["matrix"][()]
# if clip1 is not None:
# mat = mat[clip1:clip2]
# target_group[k]["matrix"][:] += mat
# print( " SUCCESS ")
ftarget = h5py.File( extracted_reference_target_file ,"r+")
for roi_scann in reference_scan_list:
target_group = ftarget["references/scans/Scan%03d"% roi_scann ]
for k in target_group.keys():
if k != "motorDict":
print(" SHRINKING scan for ROI %s in file roi_%d.h5 " %( k, roi_scann ))
for dsn in ["matrix", "monitor", "xscale"]:
mat = target_group[k][dsn][()]
del target_group[k][dsn]
target_group[k][dsn] = mat[clip1:clip2]
ftarget.close()
ftarget = h5py.File( extracted_reference_target_file ,"r+")
ftarget["references/scans/ScansSum"] = ftarget["references/scans/Scan%03d"% reference_scan_list[0] ]
for other in reference_scan_list[1:]:
source_group = ftarget["references/scans/Scan%03d"% other ]
target_group = ftarget["references/scans/ScansSum" ]
for k in target_group.keys():
if k != "motorDict":
print(" ADDING data for ROI %s from file roi_%d.h5 " %( k, other ))
mat = source_group[k]["matrix"][()]
target_group[k]["matrix"][:] += mat
ftarget.close()
main()
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