def __run_script__(fns):
from Reduction import reduction,calibrations
from os.path import join
df.datasets.clear()
# check input
if not in_van_run.value:
print 'specify vanadium run'
return
if not in_bkg_run.value:
print 'specify background run'
return
# multiply to turn into floating point arrays
van = Dataset(str(in_van_run.value)).get_reduced()*1.0
van.location = str(in_van_run.value)
bkg = Dataset(str(in_bkg_run.value)).get_reduced()*1.0
bkg.location = str(in_bkg_run.value)
# check if input is correct
if van.ndim != 3:
raise AttributeError('van.ndim != 3')
if bkg.ndim != 3:
raise AttributeError('van.ndim != 3')
if van.axes[0].title != 'run_number':
raise AttributeError('van.axes[0].title != run_number')
if bkg.axes[0].title != 'run_number':
raise AttributeError('bkg.axes[0].title != run_number')
if van.shape != bkg.shape: # checks number of frames and detector pixel dimensions
raise AttributeError('van.shape != bkg.shape')
# check if input needs to be normalized
if norm_apply.value:
norm_ref = norm_table[str(norm_reference.value)]
else:
norm_ref = None
low_lim = tool_frame_low.value
high_lim = tool_frame_high.value
if low_lim <=0: low_lim = 0
if eff_make.value:
fl = None #holding value
#eff = calibrations.calc_eff_mark2(van, bkg, norm_ref=norm_table[norm_ref],
# esd_cutoff=eff_std_range.value)
if str(eff_technique.value)=='No V peaks':
eff, pix_ok,fudge_map,fl = calibrations.calc_eff_mark2(van,bkg,norm_ref=norm_ref,
low_frame=low_lim,
high_frame=high_lim)
elif str(eff_technique.value)=='Naive':
eff, pix_ok,fudge_map = calibrations.calc_eff_naive(van,bkg,norm_ref=norm_ref,
low_frame=low_lim,
high_frame=high_lim)
else:
raise ValueError, 'Efficiency calculation technique not recognised'
var_check = Dataset(fudge_map)
var_check.title = ('Variance against counts')
Plot1.set_dataset(var_check)
contrib_ds = Dataset(pix_ok)
contrib_ds.title = 'Pixels contributing'
Plot2.set_dataset(contrib_ds)
if fl is not None:
Plot3.set_dataset(Dataset(fl))
output_filename = join(str(out_folder.value), str(eff_name.value))
# write out new efficiency file
import time
print 'Writing efficiency file at %s' % time.asctime()
eff.save_copy(output_filename)
#calibrations.output_2d_efficiencies(eff, output_filename, comment='Created by Gumtree')
print 'Finished writing at %s' % time.asctime()
def __run_script__(fns):
from Reduction import reduction,calibrations
from os.path import join
df.datasets.clear()
# check input
if not in_van_run.value:
print 'specify vanadium run'
return
if not in_bkg_run.value:
print 'specify background run'
return
van = Dataset(str(in_van_run.value)).get_reduced()
van.location = str(in_van_run.value)
bkg = Dataset(str(in_bkg_run.value)).get_reduced()
bkg.location = str(in_bkg_run.value)
# check if input is correct
if van.ndim != 3:
raise AttributeError('van.ndim != 3')
if bkg.ndim != 3:
raise AttributeError('bkg.ndim != 3')
if van.axes[0].title != 'azimuthal_angle':
raise AttributeError('van.axes[0].title != azimuthal_angle')
if bkg.axes[0].title != 'azimuthal_angle':
raise AttributeError('bkg.axes[0].title != azimuthal_angle')
if van.shape != bkg.shape: # checks number of frames and detector pixel dimensions
raise AttributeError('van.shape != bkg.shape')
# check if input needs to be normalized
if norm_apply.value:
norm_ref = str(norm_reference.value)
# check if vertical tube correction list needs to be created
vtc_filename = join(str(out_folder.value), str(vtc_name.value))
if vtc_make.value:
if van.ndim > 2:
summed = zeros(van.shape[1:])
for step in van:
summed = summed + step
input_ds = summed
else:
input_ds = van
input_ds.location = van.location
if str(vtc_algorithm.value) == 'Vertically Centered Average':
calibrations.getVerticalCorrectionList(input_ds,
output_filename=vtc_filename)
elif str(vtc_algorithm.value) == 'Edges':
calibrations.getVerticalEdges(
input_ds,output_filename=vtc_filename)
else:
print 'Vertical offset algorithm not recognised'
if eff_make.value:
eff = calibrations.calc_eff_mark2(van, bkg,vtc_filename , norm_ref=norm_table[norm_ref])
output_filename = join(str(out_folder.value), str(eff_name.value))
# write out new efficiency file
import time
print 'Writing efficiency file at %s' % time.asctime()
calibrations.output_2d_efficiencies(eff, output_filename, comment='Created by Gumtree')
print 'Finished writing at %s' % time.asctime()
if eff_transpose.value==True:
output_filename = output_filename + '-transposed'
calibrations.output_2d_efficiencies(eff,output_filename,comment='Created by Gumtree',
transpose=True)
print 'Finished writing transposed file at %s' % time.asctime()