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pyFAI
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v0.7.8: add recalibration tool

This commit is contained in:
Jerome Kieffer 2012-10-24 18:08:44 +02:00
parent fd6ca27ff4
commit 7fc734b8f9
3 changed files with 60 additions and 45 deletions
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1
MANIFEST
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@ -52,6 +52,7 @@ scripts/diff_tomo.py
scripts/drawMask_pymca
scripts/integrate_exp.py
scripts/pyFAI-calib
scripts/pyFAI-recalib
scripts/pyFAI-saxs
scripts/pyFAI-waxs
scripts/refine_wavelength.py

2
pyFAI-src/__init__.py
View File

@ -1,4 +1,4 @@
version = "0.7.7"
version = "0.7.8"
import sys, logging
logging.basicConfig()

102
scripts/pyFAI-recalib
View File

@ -73,14 +73,13 @@ class Recalibration(object):
"""
class doing the re-calibration of frames
"""
def __init__(self, dataFiles=None, darkFiles=None, flatFiles=None, pixelSize=None, splineFile=None, gaussianWidth=None):
def __init__(self, dataFiles=None, darkFiles=None, flatFiles=None, splineFile=None, gaussianWidth=None):
"""
"""
self.dataFiles = dataFiles or []
self.darkFiles = darkFiles or []
self.flatFiles = flatFiles or []
self.pointfile = None
self.pixelSize = pixelSize
self.gaussianWidth = gaussianWidth
self.labelPattern = [[0, 1, 0], [1, 1, 1], [0, 1, 0]]
self.splineFile = splineFile
@ -100,8 +99,6 @@ class Recalibration(object):
"data= " + ", ".join(self.dataFiles),
"dark= " + ", ".join(self.darkFiles),
"flat= " + ", ".join(self.flatFiles)]
if self.pixelSize:
lst.append("pixels= " + ", ".join(self.pixelSize))
lst += ["spline= %s" % self.splineFile,
"gaussian= %s" % self.gaussianWidth]
return os.linesep.join(lst)
@ -172,8 +169,10 @@ class Recalibration(object):
if options.wavelength:
self.ai.wavelength = 1e-10 * float(options.wavelength)
if options.distance:
self.ai.distance = 1e-3 * float(options.distance)
# print "setting distance to %s" % options.distance
self.ai.dist = 1e-3 * float(options.distance)
# print 1e-3 * float(options.distance), self.ai.distance
print self.ai
def preprocess(self):
@ -188,7 +187,7 @@ class Recalibration(object):
self.outfile = self.dataFiles[0]
self.peakPicker = PeakPicker(self.outfile)
self.basename = os.path.splitext(self.outfile)[0]
self.peakPicker.gui()
self.peakPicker.gui(log=True)
self.peakPicker.fig.canvas.draw()
def extract_cpt(self):
@ -196,38 +195,52 @@ class Recalibration(object):
tth = 2.0 * numpy.arcsin(self.ai.wavelength / (2.0e-10 * d))
tth.sort()
tth = tth[numpy.where(numpy.isnan(tth) - 1)]
dtth = numpy.zeros_like(tth)
dtth[:-1] = tth[1:] - tth[:-1]
dtth[-1] = dtth[-2]
dtth = numpy.zeros((tth.size, 2))
delta = tth[1:] - tth[:-1]
dtth[:-1, 0] = delta
dtth[-1, 0] = delta[-1]
dtth[1:, 1] = delta
dtth[0, 1] = delta[0]
dtth = dtth.min(axis= -1)
ttha = self.ai.twoThetaArray(self.peakPicker.data.shape)
for i in range(tth.size):
mask = abs(ttha - tth[i]) <= dtth[i] / 4.0
self.peakPicker.massif_contour(mask)
self.peakPicker.fig.canvas.draw()
all_points = numpy.where(mask)
size = all_points[0].size
keep = int(numpy.ceil(numpy.sqrt(size)))
allpt = numpy.zeros((size, 2), dtype=numpy.int)
allpt[:, 0] = all_points[0]
allpt[:, 1] = all_points[1]
res = []
cnt = 0
logger.info("Extracting datapoint for ring %s (2theta = %.2f deg)" % (i, numpy.degrees(tth[i])))
while True:
idx = numpy.random.randint(0, size)
out = self.peakPicker.massif.nearest_peak(allpt[idx])
if mask[out[0], out[1]]:
if out not in res:
res.append(out)
cnt = 0
if len(res) >= keep or cnt > 2 * keep:
break
else:
cnt += 1
self.peakPicker.points.append(res, tth[i])
self.peakPicker.display_points()
self.peakPicker.control_points.save(self.basename + ".npt")
size = mask.sum(dtype=int)
if size > 0:
self.peakPicker.massif_contour(mask)
self.peakPicker.fig.canvas.draw()
mean = self.peakPicker.data[mask].mean(dtype=numpy.float64)
std = self.peakPicker.data[mask].std(dtype=numpy.float64)
mask2 = (self.peakPicker.data > mean + std)
size2 = mask2.sum(dtype=int)
keep = int(numpy.ceil(numpy.sqrt(size2)))
all_points = numpy.where(mask2)
allpt = numpy.zeros((size2, 2), dtype=numpy.int)
allpt[:, 0] = all_points[0]
allpt[:, 1] = all_points[1]
res = []
cnt = 0
logger.info("Extracting datapoint for ring %s (2theta = %.2f deg); searching for %i pts out of %i with I>%.1f" % (i, numpy.degrees(tth[i]), keep, size2, mean + std,))
while True:
idx = numpy.random.randint(0, size2)
out = self.peakPicker.massif.nearest_peak(allpt[idx])
p0, p1 = out
if mask[p0, p1]:
if (out not in res) and (self.peakPicker.data[p0, p1] > mean):
res.append(out)
cnt = 0
if len(res) >= keep or cnt > keep:
print len(res), cnt
break
else:
cnt += 1
self.peakPicker.points.append(res, tth[i])
self.peakPicker.display_points()
self.peakPicker.fig.canvas.draw()
self.peakPicker.points.save(self.basename + ".npt")
self.data = self.peakPicker.points.getList()
def refine(self):
if os.name == "nt" and self.peakPicker is not None:
@ -235,12 +248,13 @@ class Recalibration(object):
self.peakPicker.closeGUI()
print self.splineFile
if self.splineFile:
self.geoRef = GeometryRefinement(self.data, dist=0.1, splineFile=self.splineFile)
self.geoRef = GeometryRefinement(self.data, dist=self.ai.dist, poni1=self.ai.poni1, poni2=self.ai.poni2,
rot1=self.ai.rot1, rot2=self.ai.rot2, rot3=self.ai.rot3,
splineFile=self.splineFile)
else:
self.geoRef = GeometryRefinement(self.data, dist=0.1, pixel1=self.pixelSize[0], pixel2=self.pixelSize[1])
paramfile = self.basename + ".poni"
if os.path.isfile(paramfile):
self.geoRef.load(paramfile)
self.geoRef = GeometryRefinement(self.data, dist=self.ai.dist, poni1=self.ai.poni1, poni2=self.ai.poni2,
rot1=self.ai.rot1, rot2=self.ai.rot2, rot3=self.ai.rot3,
pixel1=self.ai.pixel1, pixel2=self.ai.pixel2)
print self.geoRef
previous = sys.maxint
finished = False
@ -333,8 +347,8 @@ if __name__ == "__main__":
c.parse()
c.preprocess()
c.extract_cpt()
print c.peakPicker.points
# print c.peakPicker.points
# c.gui_peakPicker()
# c.refine()
# c.postProcess()
# raw_input("Press enter to quit")
c.refine()
c.postProcess()
raw_input("Press enter to quit")