Commit 73f91de8 authored by myron's avatar myron
Browse files

corrected roi numbering in non regression script non_reg_testing_XRS.py

parent b8712718
This diff is collapsed.
......@@ -145,6 +145,17 @@ else:
roi = w4r.getRoiObj()
roi.writeH5(os.path.join(rois_path,'ROI_widget_roi.H5'))
###############################################################################################"
# reduce roi groups to those elements which are found in roi and with the right indexing
rois_there = list(roi.red_rois.keys())
rois_there.sort()
rois_there_num = list( map(int , [ "".join( [ c for c in rkey if c.isdigit() ] ) for rkey in rois_there ] ) )
highq = [ rois_there_num.index(rnum) for rnum in highq if rnum in rois_there_num ]
medq = [ rois_there_num.index(rnum) for rnum in medq if rnum in rois_there_num ]
lowq = [ rois_there_num.index(rnum) for rnum in lowq if rnum in rois_there_num ]
##########################################################################
# load data, use sum-algorithm
##########################################################################
......@@ -164,7 +175,7 @@ lw_ex = xrs_extraction.edge_extraction(lw,['H2O'],[1.0],{'O':['K']})
print("QUI 1 ")
# O edge low-q
lw_ex.analyzerAverage(lowq, errorweighing=False)
lw_ex.removeCorePearsonAv('O','K',[250.0,534.0],[570.0,600.0],weights=[2,1],HFcore_shift=-5.0, guess= [-1.07743447e+03, 8.42895443e+02, 4.99035465e+01, 3193e+01, -3.80090286e-07, 2.73774370e-03, 5.11920401e+03],scaling=1.2, show_plots = True)
lw_ex.removeCorePearsonAv('O','K',[250.0,534.0],[570.0,600.0],weights=[2,1],HFcore_shift=-5.0, guess= [-1.07743447e+03, 8.42895443e+02, 4.99035465e+01, 3193e+01, -3.80090286e-07, 2.73774370e-03, 5.11920401e+03],scaling=1.2, show_plots = False)
lw_ex.save_average_Sqw(os.path.join(save_path,'h2o_sum_lq.dat'), emin=00.0, emax=610.0, normrange=[520.,600.])
print("QUI OK")
......
......@@ -177,7 +177,7 @@ lw_ex = xrs_extraction.edge_extraction(lw,['H2O'],[1.0],{'O':['K']})
lw_ex.analyzerAverage(lowq, errorweighing=False)
lw_ex.removeCorePearsonAv('O','K',[250.0,534.0],[570.0,600.0],weights=[2,1],HFcore_shift=-5.0, guess= [-1.07743447e+03, 8.42895443e+02, 4.99035465e+01, 3193e+01, -3.80090286e-07, 2.73774370e-03, 5.11920401e+03],scaling=1.2)
lw_ex.removeCorePearsonAv('O','K',[250.0,534.0],[570.0,600.0],weights=[2,1],HFcore_shift=-5.0, guess= [-1.07743447e+03, 8.42895443e+02, 4.99035465e+01, 3193e+01, -3.80090286e-07, 2.73774370e-03, 5.11920401e+03],scaling=1.2, show_plots = False)
lw_ex.save_average_Sqw(os.path.join(save_path,'h2o_sum_lq_small.dat'), emin=00.0, emax=610.0, normrange=[520.,600.])
......@@ -215,7 +215,7 @@ check_results( os.path.join(save_path,'h2o_sum_lq_small.dat') , "h2o_sum_lq_smal
# O edge med-q
lw_ex.analyzerAverage(medq,errorweighing=False)
lw_ex.removeCorePearsonAv('O','K',[300.0,534.0],[570.0,600.0], weights=[2,1], HFcore_shift=-5.0, guess=[-1.39664220e+03 , 1.03655696e+03 , 7.67728511e+02, 7.30355600e+02, 7.93995221e-04, -4.76580011e-01, -1.37652621e+03], scaling=1.2)
lw_ex.removeCorePearsonAv('O','K',[300.0,534.0],[570.0,600.0], weights=[2,1], HFcore_shift=-5.0, guess=[-1.39664220e+03 , 1.03655696e+03 , 7.67728511e+02, 7.30355600e+02, 7.93995221e-04, -4.76580011e-01, -1.37652621e+03], scaling=1.2, show_plots = False)
lw_ex.save_average_Sqw(save_path+'/h2o_sum_mq_small.dat', emin=0.0, emax=610.0, normrange=[520.0,600.0])
......@@ -224,7 +224,7 @@ check_results( os.path.join(save_path,'h2o_sum_mq_small.dat') , "h2o_sum_mq_smal
# O edge high-q
lw_ex.analyzerAverage(highq,errorweighing=False)
lw_ex.removeCorePearsonAv('O','K',[52.0,534.0],[570.0,600.0],weights=[2,1], guess=[ 3.40779687e+02, 2.57030454e+02, 1.27747244e+03, 4.55875194e-01, -8.59501907e-06, 1.39969288e-02, 2.60071705e+00], HFcore_shift=-5.0,scaling=1.55)
lw_ex.removeCorePearsonAv('O','K',[52.0,534.0],[570.0,600.0],weights=[2,1], guess=[ 3.40779687e+02, 2.57030454e+02, 1.27747244e+03, 4.55875194e-01, -8.59501907e-06, 1.39969288e-02, 2.60071705e+00], HFcore_shift=-5.0,scaling=1.55, show_plots = False)
lw_ex.save_average_Sqw(save_path+'/h2o_sum_hq_small.dat', emin=0.0, emax=600.0, normrange=[520.0,600.0])
......@@ -259,7 +259,7 @@ lw_ex = xrs_extraction.edge_extraction(lw,['H2O'],[1.0],{'O':['K']})
# O edge low-q
lw_ex.analyzerAverage(lowq, errorweighing=False)
lw_ex.removeCorePearsonAv('O','K',[250.0,534.0],[570.0,600.0],weights=[2,1],HFcore_shift=-5.0, guess= [-1.07743447e+03, 8.42895443e+02, 4.99035465e+01, 3193e+01, -3.80090286e-07, 2.73774370e-03, 5.11920401e+03],scaling=1.2)
lw_ex.removeCorePearsonAv('O','K',[250.0,534.0],[570.0,600.0],weights=[2,1],HFcore_shift=-5.0, guess= [-1.07743447e+03, 8.42895443e+02, 4.99035465e+01, 3193e+01, -3.80090286e-07, 2.73774370e-03, 5.11920401e+03],scaling=1.2, show_plots = False)
lw_ex.save_average_Sqw(save_path+'/h2o_pixel_lq_small.dat', emin=00.0, emax=610.0, normrange=[520.,600.])
check_results( os.path.join(save_path,'h2o_pixel_lq_small.dat') , "h2o_pixel_lq_small.dat.ref" )
......@@ -268,7 +268,7 @@ check_results( os.path.join(save_path,'h2o_pixel_lq_small.dat') , "h2o_pixel_lq_
# O edge med-q
lw_ex.analyzerAverage(medq,errorweighing=False)
lw_ex.removeCorePearsonAv('O','K',[300.0,534.0],[570.0,600.0], weights=[2,1], HFcore_shift=-5.0, guess=[-1.39664220e+03 , 1.03655696e+03 , 7.67728511e+02, 7.30355600e+02, 7.93995221e-04, -4.76580011e-01, -1.37652621e+03], scaling=1.2)
lw_ex.removeCorePearsonAv('O','K',[300.0,534.0],[570.0,600.0], weights=[2,1], HFcore_shift=-5.0, guess=[-1.39664220e+03 , 1.03655696e+03 , 7.67728511e+02, 7.30355600e+02, 7.93995221e-04, -4.76580011e-01, -1.37652621e+03], scaling=1.2, show_plots = False)
lw_ex.save_average_Sqw(save_path+'/h2o_pixel_mq_small.dat', emin=0.0, emax=610.0, normrange=[520.0,600.0])
check_results( os.path.join(save_path,'h2o_pixel_mq_small.dat') , "h2o_pixel_mq_small.dat.ref" )
......@@ -276,7 +276,7 @@ check_results( os.path.join(save_path,'h2o_pixel_mq_small.dat') , "h2o_pixel_mq_
# O edge high-q
lw_ex.analyzerAverage(highq,errorweighing=False)
lw_ex.removeCorePearsonAv('O','K',[52.0,534.0],[570.0,600.0],weights=[2,1], guess=[ 3.40779687e+02, 2.57030454e+02, 1.27747244e+03, 4.55875194e-01, -8.59501907e-06, 1.39969288e-02, 2.60071705e+00], HFcore_shift=-5.0,scaling=1.55)
lw_ex.removeCorePearsonAv('O','K',[52.0,534.0],[570.0,600.0],weights=[2,1], guess=[ 3.40779687e+02, 2.57030454e+02, 1.27747244e+03, 4.55875194e-01, -8.59501907e-06, 1.39969288e-02, 2.60071705e+00], HFcore_shift=-5.0,scaling=1.55, show_plots = False)
lw_ex.save_average_Sqw(save_path+'/h2o_pixel_hq_small.dat', emin=0.0, emax=600.0, normrange=[520.0,600.0])
check_results( os.path.join(save_path,'h2o_pixel_hq_small.dat') , "h2o_pixel_hq_small.dat.ref" )
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