def __iter__(self): for i in self.values: self.action(i) g.waitfor_move() dic = OrderedDict() dic[(self.name, self.action.unit)] = self.action() yield dic
def rotate_and_collect_data(self, angle, duration): print "Rotating to " + str(angle) + " deg..." g.set_pv(self.gonio_pv, angle) g.waitfor_move() g.change_title(g.get_title + " rot " + str(angle)) print "Beginning Run " + g.get_title + ". Collecting data for " + str(duration) + " s." g.begin() g.waitfor_time(seconds=duration) # waitfor_uamps better? g.end() print "Run complete."
def inner_pol(**kwargs): """ Get a single polarisation measurement """ slices = [ slice(222, 666), slice(222, 370), slice(370, 518), slice(518, 666) ] i = g.get_period() g.change(period=i + 1) flipper1(1) g.waitfor_move() gfrm = g.get_frames() g.resume() g.waitfor(frames=gfrm + kwargs["frames"]) g.pause() flipper1(0) g.change(period=i + 2) gfrm = g.get_frames() g.resume() g.waitfor(frames=gfrm + kwargs["frames"]) g.pause() pols = [Polarisation.zero() for _ in slices] for channel in spectra: mon1 = g.get_spectrum(1, i + 1) spec1 = g.get_spectrum(channel, i + 1) mon2 = g.get_spectrum(1, i + 2) spec2 = g.get_spectrum(channel, i + 2) for idx, slc in enumerate(slices): ups = Average( np.sum(spec1["signal"][slc]) * 100.0, np.sum(mon1["signal"]) * 100.0) down = Average( np.sum(spec2["signal"][slc]) * 100.0, np.sum(mon2["signal"]) * 100.0) pols[idx] += Polarisation(ups, down) return MonoidList(pols)
def homecoarsejaws(): print "Homing Coarse Jaws" gen.cset(cjhgap=40,cjvgap=40) gen.waitfor_move() # home north and west gen.set_pv("IN:LARMOR:MOT:JAWS1:JN:MTR.HOMR","1") gen.set_pv("IN:LARMOR:MOT:JAWS1:JW:MTR.HOMR","1") gen.waitfor_move() gen.set_pv("IN:LARMOR:MOT:JAWS1:JN:MTR.VAL","20") gen.set_pv("IN:LARMOR:MOT:JAWS1:JW:MTR.VAL","20") # home south and east gen.set_pv("IN:LARMOR:MOT:JAWS1:JS:MTR.HOMR","1") gen.set_pv("IN:LARMOR:MOT:JAWS1:JE:MTR.HOMR","1") gen.waitfor_move() gen.set_pv("IN:LARMOR:MOT:JAWS1:JS:MTR.VAL","20") gen.set_pv("IN:LARMOR:MOT:JAWS1:JE:MTR.VAL","20")
def scan_axis(axis,startval,endval,npoints,frms,rtitle,usem4=0): lm.setuplarmor_nrscanning() gen.change(title=rtitle) gen.change(nperiods=npoints) gen.begin(paused=1) # setup the scan arrays and figure xval=np.zeros(npoints) yval=np.zeros(npoints) eval=np.zeros(npoints) stepsize=(endval-startval)/float(npoints-1) for i in range(npoints): xval[i]=(startval+i*stepsize) mpl.ion() fig1=mpl.figure(1) mpl.clf() ax = mpl.subplot(111) #ax.set_xlim((0,4)) ax.set_xlabel(axis) ax.set_ylabel('Normalised Neutron counts') # reasonable x-Axis, necessary to get the full window from the first datapoint scanrange = np.absolute(endval - startval) mpl.xlim((startval-scanrange*0.05, endval+scanrange*0.05)) mpl.draw() mpl.pause(0.001) for i in range(npoints): gen.change(period=i+1) cset_str(axis,xval[i]) gen.waitfor(seconds=1) gen.waitfor_move() gfrm=gen.get_frames() gen.resume() gen.waitfor(frames=gfrm+frms) gen.pause() a1=gen.get_spectrum(1,i+1) msig=sum(a1['signal'])*100.0 mesig=(math.sqrt(msig)) print "msig="+str(msig)+" mesig="+str(mesig) # get the interesting monitor if usem4 < 1: a1=gen.get_spectrum(11,i+1) sig=sum(a1['signal'])*100.0 a1=gen.get_spectrum(12,i+1) sig+=sum(a1['signal'])*100.0 esig=math.sqrt(sig) else: a1=gen.get_spectrum(4,i+1) sig=sum(a1['signal'])*100.0 esig=math.sqrt(sig) print "sig="+str(sig)+" esig="+str(esig) yval[i]=(sig/msig) eval[i]=(math.sqrt((sig/(msig*msig))+(sig*sig/(msig*msig*msig)))) print "yval="+str(yval[i])+" esig="+str(eval[i]) ax.errorbar(xval[i], yval[i], eval[i], fmt = 'ko') fig1.canvas.draw() mpl.pause(0.001) f.open('u:/users/Larmor/lastscan.csv','w') s=str(xval[i])+','+str(yval[i])+','+str(eval[i])+'\n' f.write(s) f.close() gen.abort() #f.open('u:/users/Larmor/lastscan.csv','w') #for i in range(npoints): # s=str(xval[i])+','+str(yval[i])+','+str(eval[i])+'\n' # f.write(s) #f.close() '''
def polscan_axis(axis,startval,endval,npoints,frms,rtitle): lm.setuplarmor_nrscanning() gen.change(title=rtitle) gen.change(nperiods=npoints*2) gen.begin(paused=1) # setup the scan arrays and figure xval=np.zeros(npoints) yval=np.zeros(npoints) eval=np.zeros(npoints) stepsize=(endval-startval)/float(npoints-1) for i in range(npoints): xval[i]=(startval+i*stepsize) mpl.ion() fig1=mpl.figure(1) mpl.clf() ax = mpl.subplot(111) #ax.set_xlim((0,4)) ax.set_xlabel(axis) ax.set_ylabel('Normalised Neutron counts') # reasonable x-Axis, necessary to get the full window from the first datapoint scanrange = np.absolute(endval - startval) mpl.xlim((startval-scanrange*0.05, endval+scanrange*0.05)) mpl.draw() mpl.pause(0.001) flipper1(1) for i in range(npoints): gen.change(period=(i*2)+1) cset_str(axis,xval[i]) flipper2(0) gen.waitfor_move() gfrm=gen.get_frames() resume() gen.waitfor(frames=gfrm+frms) pause() flipper2(1) gen.change(period=(i*2)+2) gfrm=gen.get_frames() resume() gen.waitfor(frames=gfrm+frms) pause() a1=gen.get_spectrum(1,(i*2)+1) msigup=sum(a1['signal'])*100.0 mesigup=(sqrt(msigup)) # get the interesting monitor a1=gen.get_spectrum(11,(i*2)+1) sigup=sum(a1['signal'])*100.0 a1=gen.get_spectrum(12,(i*2)+1) sigup+=sum(a1['signal'])*100.0 esigup=sqrt(sigup) a1=gen.get_spectrum(1,(i*2)+2) msigdo=sum(a1['signal'])*100.0 mesigdo=(sqrt(msigdo)) # get the interesting monitor a1=gen.get_spectrum(11,(i*2)+2) sigdo=sum(a1['signal'])*100.0 a1=gen.get_spectrum(12,(i*2)+2) sigdo+=sum(a1['signal'])*100.0 esigdo=sqrt(sigdo) yval[i]=(sigup-sigdo)/(sigup+sigdo) eval[i]=yval[i]*1e-3 #eval[i]=(sqrt((sig/(msig*msig))+(sig*sig/(msig*msig*msig)))) ax.errorbar(xval[i], yval[i], eval[i], fmt = 'ko') fig1.canvas.draw() mpl.pause(0.001) abort()
def scan_axis(axis, startval, endval, npoints, frms, rtitle, usem4=0): lm.setuplarmor_nrscanning() gen.change(title=rtitle) gen.change(nperiods=npoints) gen.begin(paused=1) # setup the scan arrays and figure xval = np.zeros(npoints) yval = np.zeros(npoints) eval = np.zeros(npoints) stepsize = (endval - startval) / float(npoints - 1) for i in range(npoints): xval[i] = (startval + i * stepsize) mpl.ion() fig1 = mpl.figure(1) mpl.clf() ax = mpl.subplot(111) #ax.set_xlim((0,4)) ax.set_xlabel(axis) ax.set_ylabel('Normalised Neutron counts') # reasonable x-Axis, necessary to get the full window from the first datapoint scanrange = np.absolute(endval - startval) mpl.xlim((startval - scanrange * 0.05, endval + scanrange * 0.05)) mpl.draw() mpl.pause(0.001) for i in range(npoints): gen.change(period=i + 1) cset_str(axis, xval[i]) gen.waitfor(seconds=1) gen.waitfor_move() gfrm = gen.get_frames() gen.resume() gen.waitfor(frames=gfrm + frms) gen.pause() a1 = gen.get_spectrum(1, i + 1) msig = sum(a1['signal']) * 100.0 mesig = (math.sqrt(msig)) print "msig=" + str(msig) + " mesig=" + str(mesig) # get the interesting monitor if usem4 < 1: a1 = gen.get_spectrum(11, i + 1) sig = sum(a1['signal']) * 100.0 a1 = gen.get_spectrum(12, i + 1) sig += sum(a1['signal']) * 100.0 esig = math.sqrt(sig) else: a1 = gen.get_spectrum(4, i + 1) sig = sum(a1['signal']) * 100.0 esig = math.sqrt(sig) print "sig=" + str(sig) + " esig=" + str(esig) yval[i] = (sig / msig) eval[i] = (math.sqrt((sig / (msig * msig)) + (sig * sig / (msig * msig * msig)))) print "yval=" + str(yval[i]) + " esig=" + str(eval[i]) ax.errorbar(xval[i], yval[i], eval[i], fmt='ko') fig1.canvas.draw() mpl.pause(0.001) f.open('u:/users/Larmor/lastscan.csv', 'w') s = str(xval[i]) + ',' + str(yval[i]) + ',' + str(eval[i]) + '\n' f.write(s) f.close() gen.abort() #f.open('u:/users/Larmor/lastscan.csv','w') #for i in range(npoints): # s=str(xval[i])+','+str(yval[i])+','+str(eval[i])+'\n' # f.write(s) #f.close() '''
def polscan_axis(axis, startval, endval, npoints, frms, rtitle): lm.setuplarmor_nrscanning() gen.change(title=rtitle) gen.change(nperiods=npoints * 2) gen.begin(paused=1) # setup the scan arrays and figure xval = np.zeros(npoints) yval = np.zeros(npoints) eval = np.zeros(npoints) stepsize = (endval - startval) / float(npoints - 1) for i in range(npoints): xval[i] = (startval + i * stepsize) mpl.ion() fig1 = mpl.figure(1) mpl.clf() ax = mpl.subplot(111) #ax.set_xlim((0,4)) ax.set_xlabel(axis) ax.set_ylabel('Normalised Neutron counts') # reasonable x-Axis, necessary to get the full window from the first datapoint scanrange = np.absolute(endval - startval) mpl.xlim((startval - scanrange * 0.05, endval + scanrange * 0.05)) mpl.draw() mpl.pause(0.001) flipper1(1) for i in range(npoints): gen.change(period=(i * 2) + 1) cset_str(axis, xval[i]) flipper2(0) gen.waitfor_move() gfrm = gen.get_frames() resume() gen.waitfor(frames=gfrm + frms) pause() flipper2(1) gen.change(period=(i * 2) + 2) gfrm = gen.get_frames() resume() gen.waitfor(frames=gfrm + frms) pause() a1 = gen.get_spectrum(1, (i * 2) + 1) msigup = sum(a1['signal']) * 100.0 mesigup = (sqrt(msigup)) # get the interesting monitor a1 = gen.get_spectrum(11, (i * 2) + 1) sigup = sum(a1['signal']) * 100.0 a1 = gen.get_spectrum(12, (i * 2) + 1) sigup += sum(a1['signal']) * 100.0 esigup = sqrt(sigup) a1 = gen.get_spectrum(1, (i * 2) + 2) msigdo = sum(a1['signal']) * 100.0 mesigdo = (sqrt(msigdo)) # get the interesting monitor a1 = gen.get_spectrum(11, (i * 2) + 2) sigdo = sum(a1['signal']) * 100.0 a1 = gen.get_spectrum(12, (i * 2) + 2) sigdo += sum(a1['signal']) * 100.0 esigdo = sqrt(sigdo) yval[i] = (sigup - sigdo) / (sigup + sigdo) eval[i] = yval[i] * 1e-3 #eval[i]=(sqrt((sig/(msig*msig))+(sig*sig/(msig*msig*msig)))) ax.errorbar(xval[i], yval[i], eval[i], fmt='ko') fig1.canvas.draw() mpl.pause(0.001) abort()
def _trans_mode(): """Setup the instrument for a simple transmission measurement.""" setup_dae_transmission() g.cset(m4trans=0) g.waitfor_move()