def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('-i','--input',dest='inputFileName', metavar='./input.txt', type=str,
help='Input file describing the data.',required=True)
parser.add_argument('-n','--number',dest='fileNo', metavar='N', type=int, default=200,
help='Number of files to average. Default is 200.')
args = parser.parse_args()
# Parse the input file
inputFile = args.inputFileName
fileNo = args.fileNo
calculator = pyxsvs.pyxsvs(inputFile)
defaultMask = fabio.open(calculator.Parameters['defaultMaskFile']).data
exposure = calculator.Parameters['exposureList'][-1]
expParams = calculator.Parameters['exposureParams'][exposure]
maskFile = calculator.Parameters['defaultMaskFile']
mask = fabio.open(maskFile).data
flatFieldFile = calculator.Parameters['flatFieldFile']
flatField = fabio.open(flatFieldFile).data
saveDir = calculator.Parameters['saveDir']
outPrefix = calculator.Parameters['outPrefix']
dataDir = calculator.Parameters['dataDir']
dataSuf = expParams['dataSuf']
dataPref = expParams['dataPref']
n1 = expParams['n1']
n2 = expParams['n2']
q1 = calculator.Parameters['q1']
q2 = calculator.Parameters['q2']
qs = calculator.Parameters['qs']
dq = calculator.Parameters['dq']
wavelength = calculator.Parameters['wavelength']
cenx = calculator.Parameters['cenx']
ceny = calculator.Parameters['ceny']
pixSize = calculator.Parameters['pixSize']
sdDist = calculator.Parameters['sdDist']
fileNames = pyxsvs.filename(dataDir+dataPref,dataSuf,n1,n1+fileNo)
dim1,dim2 = numpy.shape(fabio.open(fileNames[0]).data) # Get the data dimensions
qArray = numpy.ones((dim2,dim1))
wf = 4*pi/wavelength
[X,Y] = mgrid[1-ceny:dim2+1-ceny,1-cenx:dim1+1-cenx]
qArray = wf*sin(arctan(sqrt(X**2+Y**2)*pixSize/sdDist)/2)
qRings = range(calculator.qVecLen) # Initiate q partition list
qImg = numpy.ones((dim1,dim2)) # Image to show q partitions
# Populate q partition list
for j in xrange(calculator.qVecLen):
qRings[j] = where((qArray >= calculator.qVector[j] - dq)&(qArray <= calculator.qVector[j] + dq))
qImg[qRings[j]] = 0
fastStatic,histBins = calculator.createFastStatic(fileNames,qRings)
qImg = numpy.ma.masked_array(numpy.ones((dim1,dim2)),qImg)
# Save the averaged static as edf file
edfimg = fabio.edfimage.edfimage()
edfimg.data = fastStatic
saveFileName = saveDir+outPrefix+'2Dstatic.edf'
edfimg.write(saveFileName)
print 'Static file saved to %s' % saveFileName
# Plot the 2D averaged static + q partitions
#fastStatic = numpy.ma.masked_array(fastStatic,mask=defaultMask)
fastStaticMasked = numpy.ma.masked_array(fastStatic,mask=mask)
fig = pylab.figure()
ax = fig.add_subplot(111)
ax.set_title('Static + q partitions')
plt = ax.pcolormesh(numpy.log10(fastStaticMasked))
ax.pcolormesh(qImg,alpha=0.1,cmap=pylab.cm.gray)
#ax.set_xlim(numpy.min(X),numpy.max(X))
#ax.set_ylim(numpy.min(Y),numpy.max(Y))
ax.set_xlim(0,dim1)
ax.set_ylim(0,dim2)
ax.set_aspect(1)
pylab.colorbar(plt)
saveFileName = saveDir+outPrefix+'2Dstatic.png'
pylab.savefig(saveFileName,dpi=300)
# Azimuthally regoup the static image and plot together with q partitions
qv = numpy.arange(q1,q2+qs,qs)
poni1 = ceny*pixSize*1e-3
poni2 = cenx*pixSize*1e-3
integrator = pyFAI.azimuthalIntegrator.AzimuthalIntegrator(poni1=poni1,poni2=poni2,dist=sdDist*1e-3,wavelength=wavelength*1e-10,pixel1=pixSize*1e-3,pixel2=pixSize*1e-3)
staticAzim2d,q,chi = integrator.integrate2d(data=fastStatic/flatField,\
nbPt_rad=2000,nbPt_azim=360,unit='q_nm^-1',mask=mask)
q /= 10 # to 1/A
fig_azim = pylab.figure()
ax_azim = fig_azim.add_subplot(111)
ax_azim.set_title('Azimuthally regrouped static')
pltA = ax_azim.pcolormesh(q,chi,numpy.log10(staticAzim2d+1))
pylab.colorbar(pltA)
ax_azim.set_xlim(numpy.min(q),numpy.max(q))
ax_azim.set_ylim(numpy.min(chi),numpy.max(chi))
saveFileName = saveDir+outPrefix+'azim.png'
pylab.savefig(saveFileName,dpi=300)
# 1D integration
q,staticAzim1d = integrator.integrate1d(data=fastStatic/flatField,\
nbPt=2000,unit='q_nm^-1',mask=mask)
q /= 10 # to 1/A
fig1d = pylab.figure()
roi = where(staticAzim1d>0)
ax1d = fig1d.add_subplot(111)
ax1d.set_title('Averaged SAXS + q partitions')
ax1d.semilogy(q[roi],staticAzim1d[roi])
ax1d.set_xlim(numpy.min(q[roi]),numpy.max(q[roi]))
for i in xrange(len(qv)):
ymin, ymax = pylab.ylim()
pylab.fill([qv[i]-dq,qv[i]-dq,qv[i]+dq,qv[i]+dq],[ymin,ymax,ymax,ymin],'b',alpha=.2,edgecolor='r')
pylab.text(qv[i],0.5*ymax,str(i+1),fontsize=7,horizontalalignment='center')
saveFileName = saveDir+outPrefix+'1Dstatic.png'
pylab.savefig(saveFileName,dpi=300)
pylab.show()
def main():
global report_title
parser = argparse.ArgumentParser(description="Python XSVS data analysis.")
parser.add_argument(
"-i",
dest="inputFileName",
metavar="./input_file.txt",
type=str,
help="Input file describing the data",
required=True,
)
args = parser.parse_args()
calculator = pyxsvs.pyxsvs(args.inputFileName, useFlatField=True)
expList = sorted(calculator.Parameters["exposureParams"].keys())
saveDir = calculator.Parameters["saveDir"]
report_title = "XSVS data analysis: %s" % (calculator.Parameters["figTitle"])
imgFiles = glob(saveDir + "*.png")
# Create the document
fileName = saveDir + calculator.Parameters["outPrefix"] + "report.pdf"
doc = SimpleDocTemplate(fileName)
Story = [Spacer(1, 1 * inch)]
results_file = glob(saveDir + "*.p")
style = styles["Normal"]
main_info = (
"Analysis done: %s <br />\
Partitions of q defined by: <br />\
q1 = %.4f <br /> q2 = %.4f <br />\
qs = %.4f <br /> dq = %.4f"
% (
time.ctime(os.path.getctime(results_file[0])),
calculator.Parameters["q1"],
calculator.Parameters["q2"],
calculator.Parameters["qs"],
calculator.Parameters["dq"],
)
)
Story.append(Paragraph(main_info, style))
Story.append(Spacer(1, 0.4 * inch))
# Add the plots
for i in xrange(len(expList)):
exposure = expList[i]
# Find images for the current exposure:
currImg = [img for img in sorted(imgFiles) if exposure in img]
section_caption = "Exposure %d" % int(exposure.split("_")[-1])
ptext = "<font size=14><b>%s</b></font>" % section_caption
Story.append(Paragraph(ptext, style))
Story.append(Spacer(1, 0.4 * inch))
currParams = calculator.Parameters["exposureParams"][exposure]
exp_info_txt = "Number of data frames: %d" % (currParams["n2"] - currParams["n1"] + 1,)
Story.append(Paragraph(exp_info_txt, style))
Story.append(Spacer(1, 0.2 * inch))
data_file_list = pyxsvs.filename(
calculator.Parameters["dataDir"] + currParams["dataPref"],
currParams["dataSuf"],
currParams["n1"],
currParams["n2"],
)
first_header = pyxsvs.fabio.open(data_file_list[0]).header
time_txt = "Acquisition started on %s" % (first_header["time"])
Story.append(Paragraph(time_txt, style))
Story.append(Spacer(1, 0.2 * inch))
for j in xrange(len(currImg)):
bogustext = ("This is Paragraph number %s. " % i) * 20
Story.append(get_image(currImg[j], width=5 * inch))
Story.append(Spacer(1, 0.1 * inch))
ctxt = get_caption(currImg[j])
caption = Paragraph(r"<b>Fig. %d.%d:</b> %s" % (i + 1, j + 1, ctxt), style)
Story.append(caption)
Story.append(Spacer(1, 0.4 * inch))
Story.append(Spacer(1, 0.4 * inch))
doc.build(Story, onFirstPage=ReportFirstPage, onLaterPages=ReportLaterPages)