298 lines
9.4 KiB
Python
298 lines
9.4 KiB
Python
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import sys
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import zmq
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import numpy as np
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import time
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import pickle
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import alignment
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import matplotlib.pyplot as plt
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import threading
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import datetime
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import copy
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plt.rcParams['image.cmap'] = 'viridis'
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def histVec(v,oversample=1):
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v = np.atleast_1d(v)
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v = np.unique(v)
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vd = np.diff(v)
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vd = np.hstack([vd[0],vd])
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#vv = np.hstack([v-vd/2,v[-1]+vd[-1]/2])
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vv = np.hstack([v-vd/2.,v[-1]+vd[-1]/2.])
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if oversample>1:
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vvo = []
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for i in range(len(vv)-1):
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vvo.append(np.linspace(vv[i],vv[i+1],oversample+1)[:-1])
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vvo.append(vv[-1])
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vv = np.array(np.hstack(vvo))
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return vv
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def subtractBkg(imgs,nPix=100,dKtype='corners'):
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""" Opals tend to have different backgroud for every quadrant """
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if dKtype is 'corners':
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if imgs.ndim == 2: imgs = imgs[np.newaxis,:]
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imgs = imgs.astype(np.float)
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q1 = imgs[:,:nPix,:nPix].mean(-1).mean(-1)
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imgs[:,:512,:512]-=q1[:,np.newaxis,np.newaxis]
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q2 = imgs[:,:nPix,-nPix:].mean(-1).mean(-1)
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imgs[:,:512,-512:]-=q2[:,np.newaxis,np.newaxis]
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q3 = imgs[:,-nPix:,-nPix:].mean(-1).mean(-1)
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imgs[:,-512:,-512:]-=q3[:,np.newaxis,np.newaxis]
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q4 = imgs[:,-nPix:,:nPix].mean(-1).mean(-1)
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imgs[:,-512:,:512]-=q4[:,np.newaxis,np.newaxis]
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elif dKtype is 'stripes':
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if imgs.ndim == 2: imgs = imgs[np.newaxis,:]
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imgs = imgs.astype(np.float)
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s1 = imgs[:,:nPix,:].mean(-2)
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return np.squeeze(imgs)
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def getData():
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t0 = time.time()
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context = zmq.Context()
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socket = context.socket(zmq.REQ)
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socket.connect('tcp://daq-xpp-mon06:12322')
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#socket.setsockopt(zmq.SUBSCRIBE, b'')
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while True:
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socket.send(b"Request")
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ret = socket.recv()
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ret = pickle.loads(ret, encoding='latin1')
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print('received',ret.keys(),time.time()-t0)
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t0 = time.time()
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if __name__ == "__main__":
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getData()
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class SpecHandler(object):
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def __init__(self,connectString='tcp://daq-xpp-mon06:12322',spec1name='opal0',spec2name='opal1',roi=[0,1024,0,1024]):
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self.connectString = connectString
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self.spec1name = spec1name
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self.spec2name = spec2name
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self.dataCollector = []
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#self.surveyplot = Surveyplot(spec1name=spec1name,spec2name=spec2name)
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self.roi = roi
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self.projsimple = ProjSimple(spec1name=spec1name,spec2name=spec2name,dataCollector=self.dataCollector)
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self._rawContinuousTime = None
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self.lastDat = None
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self.openSocket()
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self.runningPlot = RunningPlot(self.dataCollector)
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def openSocket(self):
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context = zmq.Context()
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self.context = context
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self.socket = context.socket(zmq.REQ)
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self.socket.connect(self.connectString)
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#self.socket.setsockopt(zmq.SUBSCRIBE, b'')
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def closeSocket(self):
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del self.context
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del self.socket
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def getData(self):
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self.socket.send(b"Request")
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ret = self.socket.recv()
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ret = pickle.loads(ret, encoding='latin1')
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for sn in [self.spec1name,self.spec2name]:
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ret[sn] = np.squeeze(alignment.subtractBkg(ret[sn], nPix=100, bkg_type='line'))
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self.lastDat = ret
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return ret
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def getRaw(self,repoenConnection=False,doAlign=False,show=False,doFit=False,updateImg=True,updateProj=True,updateFom=True, ispaceCorr=False,flipit=False,xshift=None):
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if doFit is True: doFit='iminuit'
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if repoenConnection:
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self.closeSocket()
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self.openSocket()
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dat = self.getData()
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im1 = dat[self.spec1name]; im2 = dat[self.spec2name]
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if doAlign:
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#t = np.load("gui_align_transform_xppl3716.npy").item()
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if hasattr(self,'transformer'):
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algn = self.transformer
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else:
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algn = alignment.loadAlignment('last_trafo.npy')
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t = algn['transform']
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roi1 = algn['roi1']
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roi2 = algn['roi2']
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im1 = im1[roi1];
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if flipit:
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im1 = im1[::-1]
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im2 = im2[roi2]
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alignment.clearCache()
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r = alignment.doShot( im1,im2, t, show=show, doFit=doFit, xshift=xshift)
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self.transformer = dict(transform=r.final_transform,roi1=roi1,roi2=roi2)
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alignment.saveAlignment('last_trafo.npy',r.final_transform,roi1,roi2)
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im1 = r.im1; im2 = r.im2
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showDiff = True
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showRatio = True
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else:
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showDiff = False
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showRatio = False
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if doAlign:
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thres = 0.05
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#im1[im1<thres*np.max(im1.ravel())] = np.nan
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#im2[im2<thres*np.max(im2.ravel())] = np.nan
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self.dataCollector.append(\
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dict( time=datetime.datetime.now(),
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fom=r.fom,
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ratProj = np.nansum(im2/im1,axis=0),
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im1Proj = np.nansum(im1,axis=0),
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im2Proj = np.nansum(im2,axis=0)))
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if updateFom:
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self.runningPlot.updatePlot()
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#if updateImg:
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#self.surveyplot.plotImages(im1,im2,showDiff=showDiff,showRatio=showRatio)
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#if updateProj:
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self.projsimple.plotProfiles(im1,im2)
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def alignFeatures(self,flipit=False):
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im1 = copy.copy(self.lastDat[self.spec1name])
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im2 = copy.copy(self.lastDat[self.spec2name])
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if flipit:
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im1 = im1[::-1]
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roi1 = alignment.findRoi(im1)
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roi2 = alignment.findRoi(im2)
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tra = alignment.GuiAlignment(im1[roi1,:],im2[roi2,:],autostart=False)
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self.transformer = dict(transform=tra.start(),roi1=roi1,roi2=roi2)
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def getRawContinuuous(self,sleepTime,**kwargs):
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self._rawContinuousTime = sleepTime
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if not hasattr(self,'_rawContinuousThread'):
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def upd():
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while not self._rawContinuousTime is None:
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self.getRaw(**kwargs)
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plt.draw()
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time.sleep(self._rawContinuousTime)
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self._rawContinuousThread = threading.Thread(target=upd)
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self._rawContinuousThread.start()
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class Surveyplot(object):
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def __init__(self,spec1name='spec1',spec2name='spec2'):
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self.fig,self.axs = plt.subplots(4,1,sharex=True,sharey=True)
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self.axs[0].set_title(spec1name)
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self.axs[1].set_title(spec2name)
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self.axs[2].set_title("Difference")
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self.axs[3].set_title("Ratio")
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def plotImages(self,img1,img2,showDiff=False,showRatio=False):
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if hasattr(self,'i1'):
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self.i1.set_data(img1)
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else:
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self.i1 = self.axs[0].imshow(img1,origin='lower',interpolation='none')
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if hasattr(self,'i2'):
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self.i2.set_data(img2)
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else:
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self.i2 = self.axs[1].imshow(img2,origin='lower',interpolation='none')
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if showDiff:
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tdiff = img2-img1
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if hasattr(self,'idiff'):
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self.idiff.set_data(tdiff)
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else:
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self.idiff = self.axs[2].imshow(tdiff,interpolation='none',origin='lower')
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lms = np.percentile(tdiff,[30,70])
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self.idiff.set_clim(lms)
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if showRatio:
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tratio = img2/img1
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if hasattr(self,'iratio'):
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self.iratio.set_data(tratio)
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else:
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self.iratio = self.axs[3].imshow(tratio,interpolation='none',origin='lower')
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lms = np.percentile(tratio,[30,70])
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self.iratio.set_clim(lms)
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class ProjSimple(object):
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def __init__(self,spec1name='spec1',spec2name='spec2',roi1=[0,1024,0,1024],roi2=[0,1024,0,1024],dataCollector=[]):
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self.fig,self.axs = plt.subplots(2,1,sharex=True)
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self.roi1 = roi1
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self.roi2 = roi2
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self.spec1name=spec1name
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self.spec2name=spec2name
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self.dataCollector = dataCollector
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#def getROI(self,specNo):
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def _roiit(self,img,roi):
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return img[roi[0]:roi[1],roi[2]:roi[3]]
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def plotProfiles(self,img1,img2):
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prof1 = np.nansum(self._roiit(img1,self.roi1),0)
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prof2 = np.nansum(self._roiit(img2,self.roi2),0)
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if hasattr(self,'l1'):
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self.l1.set_ydata(prof1)
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else:
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self.l1 = self.axs[0].plot(prof1,label=self.spec1name)[0]
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if hasattr(self,'l2'):
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self.l2.set_ydata(prof2)
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else:
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self.l2 = self.axs[0].plot(prof2,label=self.spec2name)[0]
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plt.legend()
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if hasattr(self,'lrat'):
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self.lrat.set_ydata(prof2/prof1)
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else:
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self.lrat = self.axs[1].plot(prof2/prof1,'k',label='ratio')[0]
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self.axs[1].set_ylim(0,2)
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if len(self.dataCollector) > 0 :
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im1Proj = np.asarray([i['im1Proj'] for i in self.dataCollector])
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im2Proj = np.asarray([i['im2Proj'] for i in self.dataCollector])
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#print(im1Proj.shape,im2Proj.shape)
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ratAv = np.median(im2Proj[-10:],0)/np.median(im1Proj[-10:],0)
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if hasattr(self,'lratAv'):
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self.lratAv.set_ydata(ratAv)
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else:
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self.lratAv = self.axs[1].plot(ratAv,'r',label='ratio Avg')[0]
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self.axs[1].set_ylim(0,2)
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class RunningPlot(object):
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def __init__(self,dataCollector):
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self.dataCollector = dataCollector
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self.fig,self.axs = plt.subplots(1,1)
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def updatePlot(self):
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if len(self.dataCollector)>0:
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times = np.asarray(([i['time'] for i in self.dataCollector]))
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foms = np.asarray(([i['fom'] for i in self.dataCollector]))
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im1Proj = np.asarray(([i['im1Proj'] for i in self.dataCollector]))
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im2Proj = np.asarray(([i['im2Proj'] for i in self.dataCollector]))
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if hasattr(self,'fomline'):
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self.fomline.set_ydata(foms)
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self.fomline.set_xdata(times)
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self.axs.set_xlim(np.min(times)-datetime.timedelta(0,10),np.max(times)+datetime.timedelta(0,10))
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#self.axs[0].autoscale(enable=True,axis='x')
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else:
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self.fomline = self.axs.plot(times,foms,'o-')[0]
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self.axs.autoscale(enable=True,axis='x')
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#if hasattr(self,'ratioimg'):
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#self.ratioimg.set_data()
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#self.ratioimg.set_ydata(foms)
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#else:
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#self.axs[0].plot(times,foms,'o-')
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#def plotOrUpdate(img1,img2):
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#if hasattr(self,i1):
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#self.i1.set_data(img1)
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#else:
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#self.i1 = self.axs.imshow(img1,interpolate='none',origin='bottom')
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#if hasattr(self,i1):
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#self.i1.set_data(img1)
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#else:
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#self.i1 = self.axs.imshow(img1,interpolate='none',origin='bottom')
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