Commit adc1f588 authored by myron's avatar myron
Browse files

ants

parent a4e802ff
...@@ -46,7 +46,6 @@ def main(): ...@@ -46,7 +46,6 @@ def main():
## such radius from the maximum ## such radius from the maximum
isolate_spot_by = 7 isolate_spot_by = 7
#### For the fit of the response function based on reference scans #### For the fit of the response function based on reference scans
response_fit_options = dict( [ response_fit_options = dict( [
["niter_optical" , 100], ["niter_optical" , 100],
...@@ -67,7 +66,7 @@ def main(): ...@@ -67,7 +66,7 @@ def main():
steps_to_do = { steps_to_do = {
"do_step_make_roi": False, "do_step_make_roi": False,
"do_step_sample_extraction": False, "do_step_sample_extraction": True,
"do_step_interpolation": False, "do_step_interpolation": False,
"do_step_extract_reference_scan": False, "do_step_extract_reference_scan": False,
...@@ -108,10 +107,8 @@ def main(): ...@@ -108,10 +107,8 @@ def main():
elastic.get_compensation_factor( elastic_scan_for_peaks_shifts , method='sum') elastic.get_compensation_factor( elastic_scan_for_peaks_shifts , method='sum')
el_dict = elastic.cenom_dict el_dict = elastic.cenom_dict
Enominal = np.median( list( el_dict.values() ) ) Enominal = np.median( list( el_dict.values() ) )
peaks_shift = np.array([ el_dict["ROI%02d"%i] if ("ROI%02d"%i) in el_dict else nan for i in range( 72) ] ) peaks_shifts = np.array([ el_dict["ROI%02d"%i] if ("ROI%02d"%i) in el_dict else nan for i in range( 72) ] )
for p in peaks_shift:
print( p)
raise
Enominal = np.median(peaks_shifts) Enominal = np.median(peaks_shifts)
peaks_shifts-= Enominal peaks_shifts-= Enominal
......
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