107 lines
3.7 KiB
Python
107 lines
3.7 KiB
Python
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from __future__ import print_function,division
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import os
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# prepare logging
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import logging
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logfname = os.path.splitext(__file__)[0] + ".log"
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logging.basicConfig(level=logging.DEBUG,
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format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',
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datefmt='%y-%m-%d %H:%M:%S',
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filename=logfname,
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filemode='w')
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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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from dualtree import dualtree
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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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g_default_mask = '../masks/fesalen1_run8_careful.edf'
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def prepareLog():
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""" It allows printing to terminal on top of logfile """
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# define a Handler which writes INFO messages or higher to the sys.stderr
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console = logging.StreamHandler()
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console.setLevel(logging.INFO)
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# set a format which is simpler for console use
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formatter = logging.Formatter('%(message)s')
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# tell the handler to use this format
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console.setFormatter(formatter)
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# add the handler to the root logger
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logging.getLogger('').addHandler(console)
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prepareLog()
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def findCenter():
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files = xray.utils.getEdfFiles("../fesalen/fesalen1/run8/",nFiles=100)
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img = xray.azav.read(files).mean(axis=0) - 10.
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xray.azav.find_center(img)
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def azav(folder,nQ=1500,force=False,saveChi=True,mask=g_default_mask):
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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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def removeBaseline(folder,qlims=(0.6,3),max_iter=30):
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data = azav(folder)
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idx = (data.q>qlims[0]) & (data.q<qlims[1])
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data['q'] = data.q[idx]
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data['data'] = data.data[:,idx]
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for i in range(len(data.data)):
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data['data'][i]=data.data[i]-dualtree.baseline(data.data[i],max_iter=max_iter)
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fname = os.path.splitext(data.filename)[0] + "_nobaseline" + id9.default_extension
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data.save(fname)
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return data
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def datared(folder,monitor=(0.5,4),showPlot=True,errMask=5,chi2Mask=2,
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qlims=(0.6,3),withBaseline=False,storageFile='auto',force=False,**kw):
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# ice contributes to a lot of noise, filter to q<2
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if storageFile == 'auto':
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if withBaseline:
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storageFile = folder + "/" + "pyfai_1d" + id9.default_extension
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else:
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storageFile = folder + "/" + "pyfai_1d_nobaseline" + id9.default_extension
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if not os.path.exists(storageFile) or force: removeBaseline(folder)
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data = xray.storage.DataStorage(storageFile)
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data,diffs = id9.doFolder_dataRed(folder,storageFile=data,monitor=monitor,
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errMask=errMask,chi2Mask=chi2Mask,qlims=qlims,**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.title(folder + " norm %s" % str(monitor))
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plt.figure()
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xray.utils.plotdiffs(diffs.q,diffs.dataAbsAvScanPoint,t=diffs.scan)
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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,removeBaseline=True):
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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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