more id9 stuff including a difference plot with hidable curves
This commit is contained in:
Marco Cammarata
parent
57a45da3c1
commit
bde9cf8290
35
xray/azav.py
35
xray/azav.py
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@ -128,8 +128,7 @@ def doFolder(folder,files='*.edf*',nQ = 1500,force=False,mask=None,
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# which poni file to use:
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ai = _getAI(poni,folder)
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files = glob.glob("%s/%s"%(folder,files))
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files.sort()
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files = utils.getFiles(folder,files)
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if saved is not None:
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files = [f for f in files if utils.getBasename(f) not in saved["files"]]
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@ -140,8 +139,8 @@ def doFolder(folder,files='*.edf*',nQ = 1500,force=False,mask=None,
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elif mask is not None:
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mask = pyFAIread(mask).astype(bool)
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data = np.empty( (len(files),nQ),dtype=np.float32 )
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err = np.empty( (len(files),nQ),dtype=np.float32 )
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data = np.empty( (len(files),nQ) )
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err = np.empty( (len(files),nQ) )
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for ifname,fname in enumerate(files):
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img = pyFAIread(fname)
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q,i,e = pyFAI1d(ai,img,mask=mask,npt_radial=nQ)
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@ -149,7 +148,7 @@ def doFolder(folder,files='*.edf*',nQ = 1500,force=False,mask=None,
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err[ifname] = e
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if saveChi:
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chi_fname = utils.removeExt(fname) + ".chi"
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utils.saveTxt(chi_fname,q,i,e,info=pyFAI_dict(ai),overwrite=True)
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utils.saveTxt(chi_fname,q,i,e,info=pyFAI_info(ai),overwrite=True)
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files = [ utils.getBasename(f) for f in files ]
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files = np.asarray(files)
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@ -223,30 +222,6 @@ def pyFAI_find_center(img,psize=100e-6,dist=0.1,wavelength=0.8e-10,**kwargs):
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print("Final values: (in pixels) %.3f %.3f"%(xc,yc))
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return ai
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def plotdata(q,data,plot=True,showTrend=True,title=None,clim='auto'):
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if not (plot or showTrend): return
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if clim == 'auto': clim = np.nanpercentile(data,(1.5,98.5))
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one_plot = showTrend or plot
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two_plot = showTrend and plot
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if one_plot and not two_plot:
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fig,ax = plt.subplots(1,1)
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if two_plot:
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fig,ax = plt.subplots(1,2,sharey=True)
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ax = np.atleast_1d(ax)
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if showTrend:
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plt.sca(ax[0])
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plt.pcolormesh(np.arange(data.shape[0]),q,data.T)
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plt.xlabel("image number, 0 being older")
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plt.ylabel(r"q ($\AA^{-1}$)")
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plt.clim( *clim )
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if plot:
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if showTrend:
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ax[1].plot(data.mean(axis=0),q)
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else:
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ax[0].plot(q,data.mean(axis=0))
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if (plot or showTrend) and title is not None:
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plt.title(title)
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def average(fileOrFolder,delays=slice(None),scale=1,norm=None,returnAll=False,plot=False,
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showTrend=False):
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data = utils.data_storage(fileOrFolder)
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@ -268,7 +243,7 @@ def average(fileOrFolder,delays=slice(None),scale=1,norm=None,returnAll=False,pl
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if isinstance(norm,np.ndarray):
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i = i/norm[:,np.newaxis]
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title = "%s %s" % (fileOrFolder,str(delays))
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plotdata(q,i*scale,showTrend=showTrend,plot=plot,title=title)
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utils.plotdata(q,i*scale,showTrend=showTrend,plot=plot,title=title)
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if returnAll:
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return q,i.mean(axis=0)*scale,i
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else:
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@ -38,6 +38,7 @@ def subtractReferences(i,idx_ref, useRatio = False):
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# normal reference for an on chi, the weighted average
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iref[_i] = weight_before*ref_before + weight_after*ref_after
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if _i>=idx_ref_after: _ref += 1
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log.debug("For image %d : %d-%d"%(_i,idx_ref_before,idx_ref_after))
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if useRatio:
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i /= iref
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else:
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@ -59,9 +60,10 @@ def averageScanPoints(scan,data,isRef=None,lpower=None,useRatio=False,\
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funcForEveraging: is usually np.nanmean or np.nanmedian. it can be any
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function that support axis=0 as keyword argument
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"""
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data = data.astype(np.float)
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if isRef is None: isRef = np.zeros( data.shape[0], dtype=bool )
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assert data.shape[0] == isRef.shape[0]
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# subtract reference only is there is at least one
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if isRef.sum()>0:
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data = subtractReferences(data,np.argwhere(isRef), useRatio=useRatio)
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@ -158,7 +160,7 @@ def errorFilter(data,threshold=4):
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idx = data.err[iscan] > threshold*median_err
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data.data[iscan][idx] = \
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np.nanmedian( data.dataInScanPoint[iscan][:,idx],axis=0 )
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# data.err[iscan][idx] = median_err
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data.err[iscan][idx] = median_err
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return data
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def saveTxt(folder,data,delayToStr=True,info="",**kw):
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@ -173,7 +175,7 @@ def saveTxt(folder,data,delayToStr=True,info="",**kw):
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# try retreiving info on chi2
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try:
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chi2_0 = data.chi2_0[iscan]
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info_delay = [ " # rep_num , chi2_0 ", ]
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info_delay = [ "# rep_num : chi2_0 ", ]
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for irep,value in enumerate(chi2_0):
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info_delay.append( "# %d : %.3f" % (irep,value))
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info_delay = "\n".join(info_delay)
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@ -4,9 +4,9 @@ log.basicConfig(level=log.INFO)
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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 .xray import azav
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from .xray import dataReduction
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from .xray import utils
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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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storage_extension = ".npz"
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@ -44,15 +44,25 @@ def doFolder_azav(folder,nQ=1500,force=False,mask=None,saveChi=True,
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return azav.doFolder(folder,files="*.edf*",nQ=nQ,force=force,mask=mask,
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saveChi=saveChi,poni=poni,storageFile=storageFile,diagnostic=diag)
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def doFolder_dataRed(folder,monitor=None,funcForEveraging=np.nanmean,errFilter=True):
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data = utils.data_storage(folder)
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scan = data.delays
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q = data.q
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i = data.data
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diffs = dataReduction.calcTimeResolvedSignal(scan,i,q=q,reference="min",
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monitor=monitor,funcForEveraging=funcForEveraging)
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def doFolder_dataRed(folder,storageFile='auto',monitor=None,
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funcForEveraging=np.nanmean,errFilter=True):
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if storageFile == 'auto' : storageFile = folder + "/" + "pyfai_1d" + storage_extension
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# read azimuthal averaged curves
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data = utils.data_storage(storageFile)
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# calculate differences
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diffs = dataReduction.calcTimeResolvedSignal(data.delays,data.data,q=data.q,\
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reference="min",monitor=monitor,funcForEveraging=funcForEveraging)
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# filter if asked so
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if funcForEveraging == np.nanmean and errFilter:
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diffs = dataReduction.errorFilter(diffs)
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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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diffs.save(folder + "/" + "diffs" + storage_extension)
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return diffs
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return data,diffs
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@ -72,6 +72,7 @@ def dictToNpz(npzFile,d): np.savez(npzFile,**d)
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def read(fname):
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extension = os.path.splitext(fname)[1]
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log.info("Reading storage file %s"%fname)
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if extension == ".npz":
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return npzToDict(fname)
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elif extension == ".h5":
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@ -81,6 +82,7 @@ def read(fname):
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def save(fname,d):
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extension = os.path.splitext(fname)[1]
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log.info("Saving storage file %s"%fname)
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if extension == ".npz":
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return dictToNpz(fname,d)
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elif extension == ".h5":
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@ -19,6 +19,14 @@ except ImportError:
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_time_regex = re.compile( "(-?\d+\.?\d*(?:ps|ns|us|ms)?)")
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_timeInStr_regex = re.compile("_(-?\d+\.?\d*(?:ps|ns|us|ms)?)")
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def getFiles(folder,basename="*.edf*"):
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files = glob.glob(folder + "/" + basename)
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files.sort()
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return files
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def getEdfFiles(folder):
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return getFiles(folder,basename="*.edf*")
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def getDelayFromString(string) :
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match = _timeInStr_regex_regex.search(string)
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return match and match.group(1) or None
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@ -51,6 +59,8 @@ def timeToStr(delay,fmt="%+.0f"):
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ret = fmt % (delay*1e12) + "fs"
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elif 1e-18 <= a_delay < 1e-15:
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ret = fmt % (delay*1e12) + "as"
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else:
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ret = str(delay) +"s"
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return ret
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def removeExt(fname):
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@ -61,6 +71,80 @@ def removeExt(fname):
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def getBasename(fname):
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return removeExt(os.path.basename(fname));
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def plotdata(q,data,t=None,plot=True,showTrend=True,title=None,clim='auto'):
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if not (plot or showTrend): return
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if t is None: t = np.arange(data.shape[0])
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if clim == 'auto': clim = np.nanpercentile(data,(1.5,98.5))
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one_plot = showTrend or plot
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two_plot = showTrend and plot
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if one_plot and not two_plot:
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fig,ax = plt.subplots(1,1)
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if two_plot:
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fig,ax = plt.subplots(1,2,sharey=True)
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ax = np.atleast_1d(ax)
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if showTrend:
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plt.sca(ax[0])
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plt.pcolormesh(t,q,data.T)
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plt.xlabel("image number, 0 being older")
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plt.ylabel(r"q ($\AA^{-1}$)")
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plt.clim( *clim )
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if plot:
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if showTrend:
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ax[1].plot(data.mean(axis=0),q)
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else:
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ax[0].plot(q,data.mean(axis=0))
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if (plot or showTrend) and title is not None:
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plt.title(title)
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def plotdiffs(q,diffs,t,select=None,err=None,showErr=False,cmap=plt.cm.jet):
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# this selection trick done in this way allows to keep the same colors when
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# subselecting (because I do not change the size of diffs)
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if select is not None:
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indices = range(*select.indices(t.shape[0]))
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else:
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indices = range(len(t))
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lines = []
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for idiff in indices:
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color = cmap(idiff/(len(diffs)-1))
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label = timeToStr(t[idiff])
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kw = dict( color = color, label = label )
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if err is not None and showErr:
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line = plt.errorbar(q,diffs[idiff],err[idiff],**kw)[0]
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else:
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line = plt.plot(q,diffs[idiff],**kw)[0]
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lines.append(line)
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fig = plt.gcf()
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legend = plt.legend()
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plt.grid()
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plt.xlabel(r"q ($\AA^{-1}$)")
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# we will set up a dict mapping legend line to orig line, and enable
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# picking on the legend line
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lined = dict()
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for legline, origline in zip(legend.get_lines(), lines):
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legline.set_picker(5) # 5 pts tolerance
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lined[legline] = origline
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def onpick(event):
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# on the pick event, find the orig line corresponding to the
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# legend proxy line, and toggle the visibility
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legline = event.artist
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origline = lined[legline]
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vis = not origline.get_visible()
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origline.set_visible(vis)
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# Change the alpha on the line in the legend so we can see what lines
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# have been toggled
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if vis:
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legline.set_alpha(1.0)
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else:
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legline.set_alpha(0.2)
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fig = plt.gcf()
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fig.canvas.draw()
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fig.canvas.mpl_connect('pick_event', onpick)
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def saveTxt(fname,q,i,e=None,headerv=None,info=None,overwrite=True):
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""" Write data to file 'fname' in text format.
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Inputs:
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