67 lines
2.2 KiB
Python
67 lines
2.2 KiB
Python
from __future__ import print_function,division
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import numpy as np
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import pylab as plt
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import mcutils as mc
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import mcutils.xray as xray
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from mcutils.xray import id9
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id9 = xray.id9
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# use npz files (they can handle more stuff (list of arrays,unicode) than h5py)
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id9.default_extension = '.npz'
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#id9.default_extension = '.h5'
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def readCalc():
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fold = "../tiox/calculated_patterns/"
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names = "alpha beta lam".split()
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fnames = "alpha500K beta290K lambda".split()
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calc = dict()
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for name,fname in zip(names,fnames):
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q,i=np.loadtxt(fold + "%s.xye.q"%fname,unpack=True)
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calc[name] = xray.storage.DataStorage( dict( q=q, i=i ) )
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return xray.storage.DataStorage(calc)
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calc = readCalc()
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def azav(folder,nQ=1500,force=False,saveChi=True,mask=470):
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if isinstance(mask,int):
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files = xray.utils.getFiles(folder,"*.edf*")
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img = xray.azav.read(files[0])
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temp = np.ones_like(img,dtype=bool)
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temp[:mask] = False
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mask = temp
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return id9.doFolder_azav(folder,nQ=nQ,force=force,mask=mask,saveChi=saveChi)
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def datared(folder,monitor=(1,5),showPlot=True,**kw):
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data,diffs = id9.doFolder_dataRed(folder,monitor=monitor,**kw)
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if showPlot:
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xray.utils.plotdiffs(diffs.q,diffs.data,t=diffs.scan,
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absSignal=diffs.dataAbsAvAll,absSignalScale=30)
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plt.plot(calc.lam.q,calc.lam.i/1000+0.1,label='calc')
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plt.title(folder + " norm %s" % str(monitor))
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return data,diffs
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def doall(folder,force=False):
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azav(folder,force=force)
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return datared(folder)
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def anaAmplitue(run=6):
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fname = "../tiox/tiox1/run%d/diffs.npz" % run
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data = xray.storage.DataStorage(fname)
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ranges = ( (1.75,1.85), (2.2,2.4), (3.25,3.4) )
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nPlot = len(ranges)
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fig,ax = plt.subplots(nPlot,1,sharex=True)
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for r,a in zip(ranges,ax):
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idx = (data.q>r[0]) & (data.q<r[1])
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amplitude = np.abs(data.data[:,idx]).mean(axis=1)
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a.plot(data.scan,amplitude,'-o')
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a.set_title("Range %s"%(str(r)))
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def plotCalc(scale=1):
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fold = "../tiox/calculated_patterns/"
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q,i=readtxt(fold + "alpha500K.xye.q")
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plt.plot(q,i*scale,label="alpha")
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q,i=readtxt(fold + "beta290K.xye.q")
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plt.plot(q,i*scale,label="beta")
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q,i=readtxt(fold + "lambda.xye.q")
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plt.plot(q,i*scale,label="lambda")
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