155 lines
4.8 KiB
Python
155 lines
4.8 KiB
Python
import logging
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log = logging.getLogger(__name__)
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import os
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import collections
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import numpy as np
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from . import azav
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from . import dataReduction
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from . import utils
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from . import storage
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from . import filters
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default_extension = ".npz"
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def _conv(x):
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try:
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x = float(x)
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except:
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x = np.nan
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return x
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def _readDiagnostic(fname,retry=3):
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ntry = 0
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while ntry<retry:
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try:
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data = np.genfromtxt(fname,usecols=(2,3),\
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dtype=None,converters={3: lambda x: _conv(x)},
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names = ['fname','delay'])
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return data
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except Exception as e:
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log.warn("Could not read diagnostic file, retrying soon,error was %s"%e)
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ntry += 1
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# it should not arrive here
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raise ValueError("Could not read diagnostic file after %d attempts"%retry)
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def readDelayFromDiagnostic(fname):
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""" return an ordered dict dictionary of filename; for each key a rounded
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value of delay is associated """
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if os.path.isdir(fname): fname += "/diagnostics.log"
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# try to read diagnostic couple of times
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data = _readDiagnostic(fname,retry=4)
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files = data['fname'].astype(str)
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delays = data['delay']
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# skip lines that cannot be interpreted as float (like done, etc)
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idx_ok = np.isfinite( delays )
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files = files[idx_ok]
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delays = delays[idx_ok]
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delays = np.round(delays.astype(float),12)
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return collections.OrderedDict( zip(files,delays) )
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def doFolder_azav(folder,nQ=1500,files='*.edf*',force=False,mask=None,
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saveChi=True,poni='pyfai.poni',storageFile='auto',dark=9.9,zingerFilter=30,qlims=(0,10),
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removeBack=False,removeBack_kw=dict()):
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""" very small wrapper around azav.doFolder, essentially just reading
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the diagnostics.log """
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diag = dict( delays = readDelayFromDiagnostic(folder) )
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if storageFile == 'auto' : storageFile = folder + "/" + "pyfai_1d" + default_extension
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data = azav.doFolder(folder,files=files,nQ=nQ,force=force,mask=mask,
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saveChi=saveChi,poni=poni,storageFile=storageFile,diagnostic=diag,dark=dark,save=False)
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#try:
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# if removeBack is not None:
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# _,data.data = azav.removeBackground(data,qlims=qlims,**removeBack_kw)
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#except Exception as e:
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# log.error("Could not remove background, error was %s"%(str(e)))
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if zingerFilter > 0:
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data.data = filters.removeZingers(data.data,threshold=zingerFilter)
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#data.save(storageFile); it does not save err ?
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# idx = utils.findSlice(data.q,qlims)
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# n = np.nanmean(data.data[:,idx],axis=1)
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# data.norm_range = qlims
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# data.norm = n
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# n = utils.reshapeToBroadcast(n,data.data)
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# data.data_norm = data.data/n
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data.save(storageFile)
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return data
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def doFolder_dataRed(azavStorage,monitor=None,funcForAveraging=np.nanmean,
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qlims=None,outStorageFile='auto',reference='min'):
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""" azavStorage if a DataStorage instance or the filename to read """
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if isinstance(azavStorage,storage.DataStorage):
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data = azavStorage
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folder = azavStorage.folder
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elif os.path.isfile(azavStorage):
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folder = os.path.dirname(azavStorage)
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data = storage.DataStorage(azavStorage)
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else:
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# assume is just a folder name
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folder = azavStorage
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azavStorage = folder + "/pyfai_1d" + default_extension
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data = storage.DataStorage(azavStorage)
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#assert data.q.shape[0] == data.data.shape[1] == data.err.shape[1]
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if qlims is not None:
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idx = (data.q>qlims[0]) & (data.q<qlims[1])
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data.data = data.data[:,idx]
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data.err = data.err[:,idx]
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data.q = data.q[idx]
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# calculate differences
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diffs = dataReduction.calcTimeResolvedSignal(data.delays,data.data,err=data.err,
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q=data.q,reference=reference,monitor=monitor,
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funcForAveraging=funcForAveraging)
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# save txt and npz file
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dataReduction.saveTxt(folder,diffs,info=data.pyfai_info)
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if outStorageFile == 'auto':
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outStorageFile = folder + "/diffs" + default_extension
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diffs.save(outStorageFile)
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return data,diffs
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def doFolder(folder,azav_kw = dict(), datared_kw = dict(),online=True, retryMax=20):
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import matplotlib.pyplot as plt
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if folder == "./": folder = os.path.abspath(folder)
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fig = plt.figure()
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lastNum = None
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keepGoing = True
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lines = None
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retryNum = 0
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if online: print("Press Ctrl+C to stop")
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while keepGoing and retryNum < retryMax:
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try:
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data = doFolder_azav(folder,**azav_kw)
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# check if there are new data
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if lastNum is None or lastNum<data.data.shape[0]:
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data,diffs = doFolder_dataRed(data,**datared_kw)
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if lines is None or len(lines) != diffs.data.shape[0]:
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lines,_ = utils.plotdiffs(diffs,fig=fig,title=folder)
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else:
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utils.updateLines(lines,diffs.data)
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plt.draw()
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lastNum = data.data.shape[0]
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retryNum = 0
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else:
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retryNum += 1
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plt.pause(30)
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except KeyboardInterrupt:
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keepGoing = False
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if not online: keepGoing = False
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return data,diffs
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