2017-01-06 18:10:54 +01:00
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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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2017-01-07 23:53:12 +01:00
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id9.default_extension = '.npz'
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#id9.default_extension_extension = '.h5'
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2017-01-06 18:10:54 +01:00
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def azav(folder,nQ=1500,force=False,saveChi=True,
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poni='auto',storageFile='auto',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.pyFAIread(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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poni=poni,storageFile=storageFile)
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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: xray.utils.plotdiffs(diffs.q,diffs.data,t=diffs.scan)
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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 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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