import scisoftpy as dnp # Jython script for manipulating data sets. # The variables going into this actor in the workflow are available in the script. # Expected variable sets available and set when this script is run: # energy # I0 # Iref # It # Please provide maths of these variables and other available ones in the following lines. lnI0It = dnp.log(I0 / It)
def refl(runfiles, pathtofiles, outputpath, scalar, beamheight, footprint, angularfudgefactor, wl, back=()):
# scalar - scale factor to divide the data by
# beamheight FWHM in microns
# footprint in mm
# angular offset correction in degrees
# wavelength in wl
# back is an optional variable to subtract a background, set back=1 to do a background subtraction
qq = []
RR = []
dR = []
ii = -1
for filename in runfiles:
data = dnp.io.load(pathtofiles + "/" + str(filename) + ".dat")
ii += 1
theta = data.alpha
# work out the q vector
qqtemp = 4 * dnp.pi * dnp.sin((theta + angularfudgefactor) * dnp.pi /180) / wl
#qqtemp = data.qdcd
# this section is to allow users to set limits on the q range used from each file
if not 'qmin' + str(ii) in refl.__dict__:
qmin = qqtemp.min()
else:
print "USER SET",
qmin = refl.__getattribute__('qmin' + str(ii))
print 'refl.qmin' + str(ii) + " = " + str(qmin) + " ;",
if not 'qmax' + str(ii) in refl.__dict__:
qmax = qqtemp.max()
else:
print "USER SET",
qmax = refl.__getattribute__('qmax' + str(ii))
print 'refl.qmax' + str(ii) + " = " + str(qmax) + " ;",
roi1_sum = data.roi1_sum
roi1_sum = roi1_sum[dnp.where((qqtemp >= qmin) & (qqtemp <= qmax))]
roi1dr = dnp.sqrt(roi1_sum)
theta = theta[dnp.where((qqtemp >= qmin) & (qqtemp <= qmax))]
qqtemp = qqtemp[dnp.where((qqtemp >= qmin) & (qqtemp <= qmax))]
bg_sum = dnp.zeros(len(roi1_sum))
bg_dr = dnp.zeros(len(roi1dr))
# if background ROI number given as int, convert to a single-item tuple
if type(back) == int:
back = (back,)
# subtract any background ROIs from the data
if len(back) > 0 and back[0] > 0:
if ii==0:
print "Using background from " + str(len(back)) + " ROIs: " + str(back)
for bg in back:
if ('roi' + str(bg) + '_sum' in data.keys()):
bg_cur = data[data.keys().index('roi' +str(bg) + '_sum')]
dr_cur = dnp.sqrt(bg_cur)
(bg_sum, bg_dr) = ep.EPadd(bg_sum, bg_dr, bg_cur, dr_cur)
(bg_sum, bg_dr) = ep.EPmulk(bg_sum, bg_dr, 1.0/len(back))
else:
if ii==0:
print "Not subtracting a background"
(RRtemp, drtemp) = ep.EPsub(roi1_sum, roi1dr, bg_sum, bg_dr)
# do a footprint correction.
# assumes that the beam is gaussian in profile, with a FWHM of "beamheight".
# footprint of sample is measured in mm.
areamultiplier = 2*(norm.cdf(footprint * dnp.sin((theta + angularfudgefactor) / 180 * dnp.pi) / 2, 0, 1e-3 * beamheight/ (2*dnp.sqrt(2*dnp.log(2)))) - 0.5)
RRtemp /= areamultiplier
drtemp /= areamultiplier
# for the 2nd, 3rd, 4th q ranges have to splice the data on the end of the preexisting data
if(ii > 0):
# splice
(scalingfactor, sferror) = nsplice.getScalingInOverlap(qq, RR, dR, qqtemp, RRtemp, drtemp)
RRtemp *= scalingfactor
drtemp *= scalingfactor
print "Error in scaling factor: %2.3f %%" % (sferror/scalingfactor*100)
# now concatenate the data.
qq = dnp.concatenate((qq, qqtemp))
RR = dnp.concatenate((RR, RRtemp))
dR = dnp.concatenate((dR, drtemp))
# end of per-file loop
RR /= scalar
dR /= scalar
RR = RR[np.argsort(qq)]
dR = dR[np.argsort(qq)]
qq = np.sort(qq)
# write out the data.
np.savetxt(outputpath+"/"+str(runfiles[0])+"_refl.dat",dnp.concatenate((qq,RR,dR)).reshape(3,qq.shape[0]).transpose())
def rerefl(runfiles):
global pathtofiles, savedbean, firstfiledata
qq = []
RR = []
dR = []
ii = -1
for filename in runfiles:
roi1sum = []
roi1dr = []
bg_sum = []
bg_dr = []
data = dnp.io.load(pathtofiles + "/" + str(filename) + ".dat")
ii += 1
if ii == 0:
firstfiledata = data
# define theta
theta = data.alpha
# define q
qqtemp = 4 * dnp.pi * dnp.sin((theta + angularfudgefactor) * dnp.pi /180) / wl
#qqtemp = data.qdcd
qmin = qqtemp.min()
qmax = qqtemp.max()
# plot first image of first file
if ii == 0:
global image
image = dnp.io.load(replace_path(data['file'][imgdisp]), warn=False)
dnp.plot.image(image[0], name='Plot 1', resetaxes=False)
# find ROIs from saved bean
try:
rois = dnp.plot.getrois(savedbean)
norois = len(rois)
# if we don't have any ROIs yet, ask the user to draw some
except(KeyError, TypeError, NameError):
if ii==0:
print "\nPlease define some regions of interest then type getrois()"
print "You must type getrois() after adding/changing any regions due to a bug in DAWN."
norois = 0
# this section to be restored when ROIs are working again
## find ROIs from plot window
#bean = dnp.plot.getbean('Plot 1')
#try:
# rois = dnp.plot.getrois(bean)
# norois = len(rois)
## if we don't have any ROIs yet, ask the user to draw some
#except(KeyError, TypeError):
# if ii==0:
# print "Please define some regions of interest"
# norois = 0
if norois > 0:
if ii == 0:
print str(norois) + " ROIs defined, " + str(norois-1) + " will be used for the background"
for imgfile in data['file']:
imgdata = dnp.io.load(replace_path(imgfile), warn=False)
dnp.plot.image(imgdata[0], name="Plot 1", resetaxes=False)
image = imgdata[0].transpose() # Pilatus images load with axes transposed for some reason
bg_pt = 0
bgdr_pt = 0
for j in range(0,norois):
roi = image[int(rois[j].spt[0]):int(rois[j].spt[0]+rois[j].len[0]), int(rois[j].spt[1]):int(rois[j].spt[1]+rois[j].len[1])]
roisum_pt = dnp.float(roi.sum())
if j == 0:
roi1sum.append(roisum_pt)
roi1dr.append(dnp.sqrt(roisum_pt))
else:
(bg_pt, bgdr_pt) = ep.EPadd(bg_pt, bgdr_pt, roisum_pt, dnp.sqrt(roisum_pt))
bg_sum.append(bg_pt)
bg_dr.append(bgdr_pt)
# convert lists to arrays
(roi1sum, roi1dr, bg_sum, bg_dr) = (dnp.array(roi1sum), dnp.array(roi1dr), dnp.array(bg_sum), dnp.array(bg_dr))
# normalise background
if norois > 1:
bgsize = 0
for k in range(1, norois):
bgsize += rois[k].len[0]*rois[k].len[1]
(bg_sum, bg_dr) = ep.EPmulk(bg_sum, bg_dr, rois[0].len[0]*rois[0].len[1]/bgsize)
# subtract background
(RRtemp, drtemp) = ep.EPsub(roi1sum, roi1dr, bg_sum, bg_dr)
# do a footprint correction.
# assumes that the beam is gaussian in profile, with a FWHM of "beamheight".
# footprint of sample is measured in mm.
areamultiplier = 2*(norm.cdf(dnp.float(footprint) * dnp.sin((theta + dnp.float(angularfudgefactor)) / 180 * dnp.pi) / 2, 0, 1e-3 * dnp.float(beamheight)/ (2*dnp.sqrt(2*dnp.log(2)))) - 0.5)
RRtemp /= areamultiplier
drtemp /= areamultiplier
# for the 2nd, 3rd, 4th q ranges have to splice the data on the end of the preexisting data
if(ii > 0):
(scalingfactor, sferror) = nsplice.getScalingInOverlap(qq, RR, dR, qqtemp, RRtemp, drtemp)
RRtemp *= scalingfactor
drtemp *= scalingfactor
# now concatenate the data.
qq = dnp.concatenate((qq, qqtemp))
RR = dnp.concatenate((RR, RRtemp))
dR = dnp.concatenate((dR, drtemp))
# end of per-file loop
if norois > 0:
RR /= dnp.float(scalar)
dR /= dnp.float(scalar)
RR = RR[np.argsort(qq)]
dR = dR[np.argsort(qq)]
qq = np.sort(qq)
# write out the data.
np.savetxt(outputpath+"/"+str(runfiles[0])+"_rerefl_bkg1.dat",dnp.concatenate((qq,RR,dR)).reshape(3,qq.shape[0]).transpose(), fmt="%.10f %.10e %.10e")
print "Output saved to " + outputpath+"/"+str(runfiles[0])+"_rerefl_bkg1.dat"
# plot the resulting
dnp.plot.line(qq,dnp.log10(RR),name='Plot 2')
import scisoftpy as dnp # Jython script for manipulating data sets. # The variables going into this actor in the workflow are available in the script. # Expected variable sets available and set when this script is run: # energy # I0 # Iref # It # Please provide maths of these variables and other available ones in the following lines. lnI0It = dnp.log(I0/It)
def refl(runfiles,
pathtofiles,
outputpath,
scalar,
beamheight,
footprint,
angularfudgefactor,
wl,
back=()):
# scalar - scale factor to divide the data by
# beamheight FWHM in microns
# footprint in mm
# angular offset correction in degrees
# wavelength in wl
# back is an optional variable to subtract a background, set back=1 to do a background subtraction
qq = []
RR = []
dR = []
ii = -1
for filename in runfiles:
data = dnp.io.load(pathtofiles + "/" + str(filename) + ".dat")
ii += 1
theta = data.alpha
# work out the q vector
qqtemp = 4 * dnp.pi * dnp.sin(
(theta + angularfudgefactor) * dnp.pi / 180) / wl
#qqtemp = data.qdcd
# this section is to allow users to set limits on the q range used from each file
if not 'qmin' + str(ii) in refl.__dict__:
qmin = qqtemp.min()
else:
print "USER SET",
qmin = refl.__getattribute__('qmin' + str(ii))
print 'refl.qmin' + str(ii) + " = " + str(qmin) + " ;",
if not 'qmax' + str(ii) in refl.__dict__:
qmax = qqtemp.max()
else:
print "USER SET",
qmax = refl.__getattribute__('qmax' + str(ii))
print 'refl.qmax' + str(ii) + " = " + str(qmax) + " ;",
roi1_sum = data.roi1_sum
roi1_sum = roi1_sum[dnp.where((qqtemp >= qmin) & (qqtemp <= qmax))]
roi1dr = dnp.sqrt(roi1_sum)
theta = theta[dnp.where((qqtemp >= qmin) & (qqtemp <= qmax))]
qqtemp = qqtemp[dnp.where((qqtemp >= qmin) & (qqtemp <= qmax))]
bg_sum = dnp.zeros(len(roi1_sum))
bg_dr = dnp.zeros(len(roi1dr))
# if background ROI number given as int, convert to a single-item tuple
if type(back) == int:
back = (back, )
# subtract any background ROIs from the data
if len(back) > 0 and back[0] > 0:
if ii == 0:
print "Using background from " + str(
len(back)) + " ROIs: " + str(back)
for bg in back:
if ('roi' + str(bg) + '_sum' in data.keys()):
bg_cur = data[data.keys().index('roi' + str(bg) + '_sum')]
dr_cur = dnp.sqrt(bg_cur)
(bg_sum, bg_dr) = ep.EPadd(bg_sum, bg_dr, bg_cur, dr_cur)
(bg_sum, bg_dr) = ep.EPmulk(bg_sum, bg_dr, 1.0 / len(back))
else:
if ii == 0:
print "Not subtracting a background"
(RRtemp, drtemp) = ep.EPsub(roi1_sum, roi1dr, bg_sum, bg_dr)
# do a footprint correction.
# assumes that the beam is gaussian in profile, with a FWHM of "beamheight".
# footprint of sample is measured in mm.
areamultiplier = 2 * (norm.cdf(
footprint * dnp.sin(
(theta + angularfudgefactor) / 180 * dnp.pi) / 2, 0,
1e-3 * beamheight / (2 * dnp.sqrt(2 * dnp.log(2)))) - 0.5)
RRtemp /= areamultiplier
drtemp /= areamultiplier
# for the 2nd, 3rd, 4th q ranges have to splice the data on the end of the preexisting data
if (ii > 0):
# splice
(scalingfactor,
sferror) = nsplice.getScalingInOverlap(qq, RR, dR, qqtemp, RRtemp,
drtemp)
RRtemp *= scalingfactor
drtemp *= scalingfactor
print "Error in scaling factor: %2.3f %%" % (sferror /
scalingfactor * 100)
# now concatenate the data.
qq = dnp.concatenate((qq, qqtemp))
RR = dnp.concatenate((RR, RRtemp))
dR = dnp.concatenate((dR, drtemp))
# end of per-file loop
RR /= scalar
dR /= scalar
RR = RR[np.argsort(qq)]
dR = dR[np.argsort(qq)]
qq = np.sort(qq)
# write out the data.
np.savetxt(
outputpath + "/" + str(runfiles[0]) + "_refl.dat",
dnp.concatenate((qq, RR, dR)).reshape(3, qq.shape[0]).transpose())