def makeDataSourceAndSmallData(experimentNameAndRun, h5FileName, ttDevice,
ttCode):
global ttAnalyze
smldata = "None"
if (ttDevice is not None):
print("setting up time tool.")
print("Device = " + ttDevice)
print("bykick code = " + str(ttCode))
ttOptions = TimeTool.AnalyzeOptions(get_key=ttDevice,
eventcode_nobeam=ttCode)
ttAnalyze = TimeTool.PyAnalyze(ttOptions)
print("loading experiment data using standard small data")
myDataSource = psana.MPIDataSource(experimentNameAndRun,
module=ttAnalyze)
print("defining small data")
if (h5FileName != "None"):
smldata = myDataSource.small_data(h5FileName)
else:
print("loading mpi data source")
myDataSource = psana.MPIDataSource(experimentNameAndRun)
print("defining small data. hook in place ")
if (h5FileName != "None"):
smldata = myDataSource.small_data(h5FileName)
return (myDataSource, smldata)
def main(exp, run, configFileName):
experimentNameAndRun = "exp=%s:run=%d"%(exp, run)
print("current working directory"+str(os.curdir))
os.system('mkdir config')
print("creating libraries")
os.system('touch config/__init__.py')
print("initializing")
myDataSource = psana.MPIDataSource(experimentNameAndRun)
f = open('./config/'+configFileName,'w')
print("writing libraries")
f.write('##########################\n')
f.write('#######DAQ DEVICES########\n')
f.write('##########################\n')
for thisDetectorName in psana.DetNames():
#f.write('#detectorStart, ')
f.write('#')
for i in thisDetectorName:
f.write(str(i)+', ')
#f.write(' detectorFinish')
f.write('\n')
f.write('##########################\n')
f.write('#######EPICS PVs##########\n')
f.write('##########################\n')
for thisDetectorName in psana.DetNames('epics'):
f.write('#')
for i in thisDetectorName:
f.write(str(i)+', ')
#f.write(' epicsPvFinish')
f.write('\n')
f.close()
def main(argd):
if (False == argd['shared_mem']):
experimentNameAndRun = "exp=%s:run=%d:smd" % (argd['exp'], argd['run'])
myDataSource = psana.MPIDataSource(experimentNameAndRun + ":smd")
else:
experimentNameAndRun = "shmem=psana.0:stop=no"
myDataSource = psana.DataSource(experimentNameAndRun)
myEnumeratedEvents = enumerate(myDataSource.events())
smldata = myDataSource.small_data("test.h5")
for eventNumber, thisEvent in myEnumeratedEvents:
if eventNumber < argd['start']: continue
if eventNumber > argd['final']: break
if (eventNumber % 200 == 1):
print eventNumber
my_dict = {"test": eventNumber}
#smldata.event(my_dict)
#smldata.save()
IPython.embed()
def main(fileName):
global my_dict
my_hdf5_object = h5py.File("hdf5/xpptut15run440.h5", 'r')
#convert hdf5 to dict
my_list = []
def func(name, obj):
my_list.append(name)
my_hdf5_object.visititems(func)
my_dict = {}
for i in my_list:
try:
my_dict[i] = array(my_hdf5_object[i])
except:
#IPython.embed()
pass
my_hdf5_object.close()
#%matplotlib
acqiris_alias = "Acq02"
eigen_basis_file = "hdf5/xpptut15run440_eigen_basis.h5"
experiment_name = "xpptut15"
run_number = "440"
channel_number = 3
event_number = int(200 * rand())
print("event number number for testing: " + str(event_number))
####################
#####################
my_eigen_basis = h5py.File(eigen_basis_file)
eig_bas = array(
my_eigen_basis['summary/nonMeaningfulCoreNumber0/' + acqiris_alias +
'/ch' + str(channel_number) + '/norm_eigen_wave_forms'])
import psana
my_data_source = psana.MPIDataSource("exp=" + experiment_name + ":run=" +
run_number + ":smd")
acq_det_obj = psana.Detector(acqiris_alias)
my_enum_events = enumerate(my_data_source.events())
for evt_num, this_event in my_enum_events:
if evt_num > event_number:
break
my_index = argmax((this_event.get(
psana.EventId).fiducials() == my_dict['fiducials']).astype(int))
#plot(acq_det_obj(this_event)[0][channel_number]-mean(acq_det_obj(this_event)[0][channel_number][:300]))
plot(
acq_det_obj(this_event)[0][channel_number] -
mean(acq_det_obj(this_event)[0][channel_number][:300]))
plot(
dot(
my_dict[acqiris_alias + '/ch' + str(channel_number) +
'/weightings'][my_index], eig_bas), 'r.')
ylim(-0.06, 0.0)
xlim(1100, 1400)
show()
def makeDataSourceAndSmallData(experimentNameAndRun, h5FileName, ttDevice,
ttCode, shared_memory):
global ttAnalyze
smldata = "None"
small_hdf5_dir = "hdf5"
os.system("mkdir " + small_hdf5_dir)
if (ttDevice is not None):
print("setting up time tool.")
print("Device = " + ttDevice)
print("bykick code = " + str(ttCode))
ttOptions = TimeTool.AnalyzeOptions(get_key=ttDevice,
eventcode_nobeam=ttCode)
ttAnalyze = TimeTool.PyAnalyze(ttOptions)
print("loading experiment data using standard small data")
myDataSource = psana.MPIDataSource(experimentNameAndRun,
module=ttAnalyze)
print("defining small data")
if (h5FileName != "None"):
smldata = myDataSource.small_data(small_hdf5_dir + "/" +
h5FileName,
gather_interval=10)
else:
print("loading mpi data source")
if (shared_memory):
myDataSource = psana.DataSource('shmem=psana.0:stop=no')
else:
myDataSource = psana.MPIDataSource(experimentNameAndRun)
print("defining small data. hook in place ")
if (h5FileName != "None"):
smldata = myDataSource.small_data(small_hdf5_dir + "/" +
h5FileName,
gather_interval=10)
return (myDataSource, smldata)
def main(exp, run, configFileName):
experimentNameAndRun = "exp=%s:run=%d" % (exp, run)
print("current working directory" + str(os.curdir))
os.system('mkdir config')
print("creating libraries")
os.system('touch config/__init__.py')
print("initializing")
myDataSource = psana.MPIDataSource(experimentNameAndRun)
write_config_file(configFileName, "default")
write_config_file("make_acq_eigen_basis.cfg", "make_acq_basis")
write_config_file("acqiris_eigen_analysis.cfg", "use_acq_basis")
def intensityROI():
ds = psana.MPIDataSource('exp=cxi02116:run=257:smd')
det = psana.Detector('DsaCsPad')
for nevent,evt in enumerate(ds.events()):
raw_calib = np.array(det.calib(evt))
test = np.array(det.image(evt))
print(raw_calib.shape)
print(test.shape)
roi_approx = raw_calib[750:950, 775:975]
print(roi_approx)
roi_final = sum(sum(sum(roi_approx[65:176,42:154])))
print(roi_final)
def setup(self):
self.filename = '/tmp/' + str(uuid4()) + '.h5'
self.gather_interval = 2
dstr = 'exp=sxrk4816:run=66:smd:dir=/reg/g/psdm/data_test/multifile/test_028_sxrk4816'
self.dsource = psana.MPIDataSource(dstr)
self.smldata = self.dsource.small_data(self.filename,
gather_interval=5)
self.gather_after = 3 # events (for each core)
self.end_after = 5 # events (for each core)
#self.dsource.break_after(self.end_after * size)
assert self.gather_after > 2, 'gather after should be >= 3'
assert self.gather_after < self.end_after
return
def makeCenter():
ds = psana.MPIDataSource('exp=cxi02116:run=257:smd')
det = psana.Detector('DsaCsPad')
for nevent, evt in enumerate(ds.events()):
#Figure out coordinates first
img = np.array(det.image(evt))
test = np.array(det.calib(evt))
#Y-coords, then X-coords when slciing
approximate = img[750:950, 775:975]
real = approximate[65:176, 42:154]
print(img.shape)
print(test.shape)
print(img)
print(test)
yo = np.reshape(test, (1451, 1745))
print(yo)
def __init__(self,
exp='cxip10016',
run='1',
gain_fnam=None,
mask_fnam=None):
"""
By default gain = 1 and the mask is obtained from psana.
For example:
gain_fnam = '/reg/data/ana04/cxi/cxilt1417/scratch/gain/gain_prelim.npy'
mask_fnam = '/reg/data/ana04/cxi/cxilt1417/scratch/masks/better_mask.npy'
"""
#
# Initialize variables
#
print "Debug: loading psanabb"
self.dsname_smd = 'exp=' + exp + ':run=' + run + ':smd'
self.ds_smd = psana.MPIDataSource(self.dsname_smd)
self.env_smd = self.ds_smd.env()
self.evt = self.ds_smd.events().next()
print "Debug: loading psanabb idx events"
self.dsname_idx = 'exp=' + exp + ':run=' + run + ':idx'
self.ds_idx = psana.DataSource(self.dsname_idx)
self.env_idx = self.ds_idx.env()
#
# get event times
#
self.run = self.ds_idx.runs().next()
self.times = self.run.times()
self.nevents = len(self.times)
print "Debug: loading cspad info"
# load information
self.loadCspad(gain_fnam=gain_fnam, mask_fnam=mask_fnam)
self.wavelength = self.get_wavelength(self.evt)
self.energy = self.get_photon_beam_energy(self.evt)
Interp = InterpSimple(cent[0], cent[1], interp_rmax, interp_rmin, nphi, img_sh)
pmask = Interp.nearest(mask).astype(int).astype(float)
pmask_bn = bin_ndarray(pmask, binned_pol_img_sh)
# print pmask.shape,pmask_bn.shape
# if (rbin_fct==1 and phibin_fct==1):
# print('not binning polar img')
# sys.exit()
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#~~~ data get parameters
#load the data events for the given run
ds_str = 'exp=cxilr6716:run=%d:smd' % run
ds = psana.MPIDataSource(ds_str)
events = ds.events()
# open the detector obj
cspad = psana.Detector('DsaCsPad')
# make some output dir
outdir = args.out_dir
if not os.path.exists(outdir):
os.makedirs(outdir)
# make output file
if args.fname is None:
prefix = 'BigAzzData-run%d-maxEvent%d-start%d.hdf5' % (run, args.maxcount,
args.start)
else:
import time
runNum = sys.argv[1]
eventRange = int(sys.argv[2])
#runNum = "38"
myString = "sxrlq7615:run=" + str(runNum) + "evntRange=" + str(
eventRange) + ".txt"
try:
os.remove(myString)
except OSError:
print("no previous files to delete")
#ds = psana.DataSource('exp=xpptut15:run=340') #test data from AMO runs 10, 15, and 19
#ds = psana.DataSource('exp=sxrm2316:run=103') #real data from specified experiment (sxrm2316)
ds = psana.MPIDataSource('exp=sxrlq7615:run=' + runNum)
#ds = psana.MPIDataSource('exp=sxrlq7615:run='+runNum+':smd')
#ds = psana.MPIDataSource('exp=xpptut15:run='+str(runNum))
#psana.DetNames()
aquiris2 = psana.Detector("Acq01")
det = psana.Detector('pnccd') #for LQ76 and test amo data
#det = psana.Detector('andor') #for sxrm2316
#smldata = ds.small_data('run'+str(runNum)+'.h5')
yTotal = 0
imgTotal = 0
#stackOfROIImagesForMatt = []
def make_basis(exp_name,
run,
det_name,
nWaveforms=500,
b=None,
n_c=2,
roi=None):
""" Create the SVD basis for the waveform fitting. THe output is saved in a h5 file stored
in the calib directory of the relevant experiment
Args:
exp_name (str): experiment name
run (int): run number
det_name (str): psana name for the detector (alias)
nWaveforms (int): number of waveform to use to build the basis
b (int): background index. np.mean(waveform[:b]) will be subtracted
roi (list, array): two index specifying the region of interest of the waveform
"""
hutch = exp_name[:3]
savePath = Path('/reg/d/psdm/{}/{}/calib'.format(hutch, exp_name))
dstr = 'exp={}:run={}'.format(exp_name, run)
print('\n' + dstr + '\n')
ds = ps.MPIDataSource(dstr)
det = dobj.DetObject(det_name, ds.env(), int(run))
""" ---------------------------- GET BASIS ---------------------------- """
waveforms = []
ii = 0
for nevt, evt in enumerate(ds.events()):
if ii > nWaveforms:
break
try:
det.getData(evt)
wave = np.squeeze(det.evt.dat)
# print(wave.shape)
except:
continue
if b is not None:
wave = wave - np.mean(wave[:b])
if roi is not None:
wave = wave[roi[0]:roi[1]]
waveforms.append(wave)
ii += 1
waveforms = np.asarray(waveforms)
# print(waveforms.shape)
A, proj, svd = proc.get_basis_and_projector(waveforms, n_components=n_c)
""" ---------------------------- SAVE DATA ---------------------------- """
fname = 'wave_basis_' + det_name + '_' + datetime.datetime.now().strftime(
"%Y%m%d_%H%M%S") + '.h5'
print(fname)
fname = savePath / fname
# fname = Path('./') / fname
with h5.File(fname, 'w') as f:
dset = f.create_dataset("A", data=A)
dset = f.create_dataset("projector", data=proj)
dset = f.create_dataset("components", data=svd.components_)
dset = f.create_dataset("singular_values", data=svd.singular_values_)
dset = f.create_dataset("ref_waveforms", data=waveforms)
dset = f.create_dataset("roi", data=roi)
dset = f.create_dataset("background_index", data=b)
print('Basis file saved as {}.'.format(fname))
return fname
dsname='exp='+expname+':run='+run+':smd'
if args.offline:
dsname='exp='+expname+':run='+run+':smd'
if args.gather:
gatherInterval=args.gather
if args.nevt:
maxNevt=args.nevt
if args.dir:
dirname=args.dir
if dirname[-1]=='/':
dirname=dirname[:-1]
debug = True
time_ev_sum = 0.
try:
ds = psana.MPIDataSource(dsname)
except:
print 'failed to make MPIDataSource for ',dsname
import sys
sys.exit()
try:
if dirname is None:
dirname = '/reg/d/psdm/%s/%s/hdf5/smalldata'%(hutch.lower(),expname)
smldataFile = '%s/%s_Run%03d.h5'%(dirname,expname,int(run))
smldata = ds.small_data(smldataFile,gather_interval=gatherInterval)
if args.live:
smldata.connect_redis()
except:
print 'failed making the output file ',smldataFile
history
import psana
from pylab import
from pylab import *
myDataSource = psana.MPIDataSource("exp=sxr10116:run=73")
psana.DetNames()
andorDetectorObject = psana.Detector('andor')
myEnumeratedEvents = enumerate(myDataSource.events())
eventNumber,thisEvent = next(myEnumeratedEvents)
andorDetectorObject(thisEvent)
andorDetectorObject.image(thisEvent)
eventNumber,thisEvent = next(myEnumeratedEvents)
andorDetectorObject.image(thisEvent)
eventNumber,thisEvent = next(myEnumeratedEvents)
andorDetectorObject.image(thisEvent)
eventNumber,thisEvent = next(myEnumeratedEvents)
andorDetectorObject.image(thisEvent)
eventNumber,thisEvent = next(myEnumeratedEvents)
andorDetectorObject.image(thisEvent)
eventNumber,thisEvent = next(myEnumeratedEvents)
andorDetectorObject.image(thisEvent)
eventNumber,thisEvent = next(myEnumeratedEvents)
andorDetectorObject.image(thisEvent)
eventNumber,thisEvent = next(myEnumeratedEvents)
zeros([5,5])
if i in enumeratedEvents:
tempImage = andorDetectorObject.image(thisEvent)
if(tempImage is not None):
print i
for i in enumeratedEvents:
tempImage = andorDetectorObject.image(thisEvent)
delay_range_upper = args.time_high # in units of ps
# count how many events are skipped
skipctr = 0
count = 0
#ds = psana.DataSource('exp=' + expname + ':run=%s:smd'%run_num)
# ds = psana.MPIDataSource('exp=' + expname + ':run=%s:smd'%run_num)
# psana.DataSource('dir=/reg/d/ffb/xpp/xpph6615/xtc/:exp=xpph6615:run=%s:idx'%run)
if args.custom_calibration_directory != '':
print('Using a custom calibration directory: ' +
args.custom_calibration_directory)
psana.setOption('psana.calib-dir', args.custom_calibration_directory)
if pull_from_ffb == 0:
ds = psana.MPIDataSource('exp=' + expname + ':run=%s:smd' % run_num)
else:
ds = psana.MPIDataSource('exp=' + expname +
':run=%s:smd:dir=/cds/data/drpsrcf/xpp/' %
run_num + expname + '/xtc')
epics = ds.env().epicsStore()
configStore = ds.env().configStore()
evr2skip = laseroffevr
total_events = 0
ipm2_src = psana.Source('BldInfo(XPP-SB2-BMMON)')
ipm3_src = psana.Source('BldInfo(XPP-SB3-BMMON)')
evr_src = psana.Source("NoDetector.0:Evr.0")
cspadDet = psana.Detector('jungfrau1M', ds.env())
#!/usr/bin/env python
print 'Use command: mpirun -n 8 python hexanode/examples/ex-09-MPIDataSource.py'
from time import time
import psana
from pyimgalgos.GlobalUtils import print_ndarr
#ds = psana.DataSource('exp=xpptut15:run=390') # :smd ?
#det = psana.Detector('AmoETOF.0:Acqiris.0')
dsource = psana.MPIDataSource('exp=xpptut15:run=54:smd')
cspaddet = psana.Detector('cspad')
smldata = dsource.small_data('run54.h5', gather_interval=100)
partial_run_sum = None
for nevt, evt in enumerate(dsource.events()):
calib = cspaddet.calib(evt)
if calib is None: continue
cspad_sum = calib.sum() # number
cspad_roi = calib[0][0][3:5] # array
if partial_run_sum is None:
partial_run_sum = cspad_roi
else:
partial_run_sum += cspad_roi
# save per-event data
smldata.event(cspad_sum=cspad_sum, cspad_roi=cspad_roi)
if nevt > 3: break
import matplotlib.pyplot as plt
import h5py as h5
from scipy.signal import savgol_filter as savgol
from scipy.interpolate import interp1d
import IPython
#from importlib import reload
import psana as ps
import ana_fun as ana
reload(ana)
""" ---------------------------- """
exp_name = 'sxri0414'
run = 60
dstr = 'exp={}:run={}:smd'.format(exp_name, run)
dsource = ps.MPIDataSource(dstr)
#h5_dir = '/reg/d/psdm/SXR/sxri0414/hdf5'
h5_dir = './'
fh5 = h5_dir + 'test.h5'
smldata = dsource.small_data(fh5, gather_interval=100) #save file
for nevt,evt in enumerate(dsource.events()):
if nevt==50: break
if not (nevt % 100): print('Running event number {}\n'.format(nevt))
#try:
dl = ps.Detector('SXR:LAS:MCN1:08.RBV')()
def smooth(x, beta=10.0, window_size=11):
"""a nice recipe"""
if window_size % 2 == 0:
window_size += 1
s = np.r_[x[window_size - 1:0:-1], x, x[-1:-window_size:-1]]
w = np.kaiser(window_size, beta)
y = np.convolve(w / w.sum(), s, mode='valid')
b = (window_size - 1) / 2
smoothed = y[b:len(y) - b]
return smoothed
ds = psana.MPIDataSource("exp=%s:run=%d:smd" % (exp, run))
smldata = ds.small_data(outname) # , gather_interval=100)
# for finding the max position(s) in power spectrum
# we use Kmeans
k_for_max = KMeans(n_clusters=2)
events = ds.events()
####
# first iterate and figure out how long the traces are
has_mpi = True
Npts = None
for i_ev, ev in enumerate(events):
xx.processEvent(ev)
pulse_t, pulse_power = xx.xRayPower()
if pulse_power is not None:
Npts = pulse_power[0].shape[0]
break
#%matplotlib
acqiris_alias = "Acq02"
eigen_basis_file = "eigen_traces.h5"
experiment_name = "sxrx21715"
run_number = "193"
channel_number = 3
event_number = 80
####################
#####################
my_eigen_basis = h5py.File(eigen_basis_file)
eig_bas = array(
my_eigen_basis['summary/nonMeaningfulCoreNumber0/' + acqiris_alias +
'/ch' + str(channel_number) + '/norm_eigen_wave_forms'])
import psana
my_data_source = psana.MPIDataSource("exp=" + experiment_name + ":run=" +
run_number + ":smd")
acq_det_obj = psana.Detector(acqiris_alias)
my_enum_events = enumerate(my_data_source.events())
for evt_num, this_event in my_enum_events:
if evt_num > event_number:
break
my_index = argmax((this_event.get(
psana.EventId).fiducials() == my_dict['fiducials']).astype(int))
#plot(acq_det_obj(this_event)[0][channel_number]-mean(acq_det_obj(this_event)[0][channel_number][:300]))
plot(
acq_det_obj(this_event)[0][channel_number] -
mean(acq_det_obj(this_event)[0][channel_number][:300]))
plot(
dot(
my_dict[acqiris_alias + '/ch' + str(channel_number) +
import psana
import sys
import numpy as np
import matplotlib.pyplot as plt
run = int(sys.argv[-1]) # make me better yash
def tt_correction(edge):
a = -1.527864480143
b = 0.003652900467
c = -0.000001106143
return (a + b * edge + c * edge**2) / 1000.
ds = psana.MPIDataSource('exp=cxilr3816:run=%d' % run)
smd = ds.small_data('run%d_data.h5' % run)
evr = psana.Detector('NoDetector.0:Evr.1')
acq = psana.Detector('Acqiris')
las_dly = psana.Detector('LAS:FS5:VIT:FS_TGT_TIME_DIAL')
tt_edge = psana.Detector('CXI:TTSPEC:FLTPOS')
tt_fwhm = psana.Detector('CXI:TTSPEC:FLTPOSFWHM')
tt_famp = psana.Detector('CXI:TTSPEC:AMPL')
tt_stage_pos = psana.Detector('CXI:LAS:MMN:04') # convert me from mm to ns
for n, evt in enumerate(ds.events()):
try:
from pylab import *
import psana
#############################################
############standard intro###################
#Live data during beamtime
#dsource = psana.MPIDataSource('exp=sxr22915:run=104:smd:dir=/reg/d/ffb/sxr/sxro5916/xtc:live')
#After beamtime
dsource = psana.MPIDataSource("exp=sxrx22915:run=104")
#smldata = dsource.small_data('run104.h5')
smldata = dsource.small_data('run104c.h5')
f = open("manualWriteRun104.dat", "w")
psana.DetNames()
#############################################
############defining detector objects########
kbFluorescenceMontior = psana.Detector("Acq02")
imagingDetectorObject = psana.Detector("pnccd")
#xSampleAxis = psana.Detector("SXR:RCI:MZM:SMP:x.RBV")
#############################################
############enumerating events###############
enumeratedEvents = enumerate(dsource.events())
eventNumber, myEvent = next(enumeratedEvents)
MCP = kbFluorescenceMontior(myEvent)[0][3]
import psana
from pylab import *
my_list = arange(71,118)
for i in my_list:
myDataSource = psana.MPIDataSource("exp=sxrlr0716:run="+str(i))
my_events = myDataSource.events()
evt = next(my_events)
env = myDataSource.env()
configs = env.configStore()
configs.keys()
andor_config = configs.get(psana.Andor.ConfigV2)
print("run = "+str(i)+ " readout speed = "+str(andor_config.readoutSpeedIndex()))
import psana
import numpy as np
from matplotlib import pyplot as plt
ds = psana.MPIDataSource('exp=cxilr3816:run=8:smd')
smd = ds.small_data('run8_acq_data.h5')
las_dly = psana.Detector('LAS:FS5:VIT:FS_TGT_TIME_DIAL', ds.env())
tt_edge = psana.Detector('CXI:TTSPEC:FLTPOS', ds.env())
delayArray = []
edgeArray = []
for evt in ds.events():
delayArray.append(las_dly(evt))
edgeArray.append(tt_edge(evt))
edgeArray = np.array(edgeArray[0:19800])
delayArray = np.array(delayArray[0:19800])
for n, evt in enumerate(ds.events()):
try:
diode = np.sum(acq(evt)[0][0, 760:860])
except:
diode = None
delay = las_delay(evt)
smd.event(acqiris=diode, las_delay=delay)
if smd.master:
def main(fileName):
#global myDict
global my_dict
#f = h5py.File("sxr10116run73.h5",'r')
#f = h5py.File(fileName,'r')
my_hdf5_object = h5py.File("sxrx30116run6.h5", 'r')
#f = h5py.File("sxrx24615run21.h5",'r')
#for i in f:
# print(str(i))
# print(str(array(f[i])[:10]))
#f.close()
#myDict= hdf5_to_dict(f)
#convert hdf5 to dict
my_list = []
def func(name, obj):
my_list.append(name)
my_hdf5_object.visititems(func)
my_dict = {}
for i in my_list:
try:
my_dict[i] = array(my_hdf5_object[i])
except:
#IPython.embed()
pass
my_hdf5_object.close()
#%matplotlib
acqiris_alias = "Acq01"
eigen_basis_file = "eigen_traces.h5"
experiment_name = "sxrx30116"
run_number = "6"
channel_number = 3
event_number = 80
####################
#####################
my_eigen_basis = h5py.File(eigen_basis_file)
eig_bas = array(
my_eigen_basis['summary/nonMeaningfulCoreNumber0/' + acqiris_alias +
'/ch' + str(channel_number) + '/norm_eigen_wave_forms'])
import psana
my_data_source = psana.MPIDataSource("exp=" + experiment_name + ":run=" +
run_number + ":smd")
acq_det_obj = psana.Detector(acqiris_alias)
my_enum_events = enumerate(my_data_source.events())
for evt_num, this_event in my_enum_events:
if evt_num > event_number:
break
my_index = argmax((this_event.get(
psana.EventId).fiducials() == my_dict['fiducials']).astype(int))
#plot(acq_det_obj(this_event)[0][channel_number]-mean(acq_det_obj(this_event)[0][channel_number][:300]))
plot(
acq_det_obj(this_event)[0][channel_number] -
mean(acq_det_obj(this_event)[0][channel_number][:300]))
plot(
dot(
my_dict[acqiris_alias + '/ch' + str(channel_number) +
'/weightings'][evt_num], eig_bas), 'r.')
show()
#runNum = sys.argv[1]
runNum = "38"
#ds = psana.DataSource('exp=xpptut15:run=340') #test data from AMO runs 10, 15, and 19
#ds = psana.DataSource('exp=sxrm2316:run=103') #real data from specified experiment (sxrm2316)
#ds = psana.DataSource('exp=sxrlq7615:run='+runNum)
#ds = psana.MPIDataSource('exp=sxrlq7615:run='+runNum+':smd')
#ds = psana.MPIDataSource('exp=sxrlq7615:run='+runNum+':smd')
#ds = psana.MPIDataSource('exp=xpptut15:run='+str(runNum))
#myDataSource = psana.MPIDataSource('exp=sxrk3016:run=118:smd')
#myDataSource = psana.MPIDataSource('exp=sxr10116:run=73:smd')
#myDataSource = psana.MPIDataSource('exp=sxri0414:run=60:smd',module=ttAnalyze)
#myDataSource = psana.MPIDataSource('exp=amolp0515:run=105:smd',module=ttAnalyze)
#myDataSource = psana.MPIDataSource('exp=sxrlp2615:run=6:smd')
myDataSource = psana.MPIDataSource('exp=xpptut15:run=360')
#psana.DetNames()
#acqirisDetectorObject = psana.Detector("Acq02")
andorDetectorObject = psana.Detector('andor')
#pnccdDetectorObject = psana.Detector('pnccdFront')
#tssOpalDetectorObject = psana.Detector('TSS_OPAL')
myEnumeratedEvents = enumerate(myDataSource.events())
myImage = 0
myHist = 0
for eventNumber, thisEvent in myEnumeratedEvents:
import psana
import sys
import numpy as np
from matplotlib import pyplot as plt
from decimal import Decimal
from random import randint
run = int(sys.argv[-1])
ds = psana.MPIDataSource('exp=cxix29016:run=%d' % run)
det = psana.Detector('DsaCsPad')
gas_det = psana.Detector('FEEGasDetEnergy')
phot_energy = psana.Detector('EBeam')
low_filter_PE = 0.95
high_filter_PE = 1.05
low_filter_I = 0.9
high_filter_I = 1.1
def accessData(run):
photon_energies = []
intensities = []
pulse_energies = []
total_events = []
low_limit = 0.90
high_limit = 1.10
if args.gather:
gatherInterval=args.gather
if args.nevt:
maxNevt=args.nevt
if args.dir:
dirname=args.dir
if dirname[-1]=='/':
dirname=dirname[:-1]
if args.norecorder:
dsname=dsname+':stream=0-79'
debug = True
time_ev_sum = 0.
try:
ds = psana.MPIDataSource(str(dsname))
except:
print('failed to make MPIDataSource for ',dsname)
import sys
sys.exit()
try:
if dirname is None:
dirname = '/reg/d/psdm/%s/%s/hdf5/smalldata'%(hutch.lower(),expname)
smldataFile = '%s/%s_Run%03d.h5'%(dirname,expname,int(run))
smldata = ds.small_data(smldataFile,gather_interval=gatherInterval)
except:
print('failed making the output file ',smldataFile)
import sys
if nevent > 10:
cspad_data=cspadDet.image(ev)
if cspad_data is None:
print("*** missing cspad data. Skipping event...")
continue
break
cspad_data_shape = cspad_data.shape
else:
cspad_data_shape = None
# print(cspad_data_shape)
comm.Barrier()
cspad_data_shape = comm.bcast(cspad_data_shape, root=0)
####
ds = psana.MPIDataSource('exp=' + expname + ':run=%s:smd'%run_num)
# psana.DataSource('dir=/reg/d/ffb/xpp/xpph6615/xtc/:exp=xpph6615:run=%s:idx'%run)
epics = ds.env().epicsStore()
configStore = ds.env().configStore()
total_events = 0
cspadDet = psana.Detector('jungfrau1M',ds.env())
ipm2_src = psana.Source('BldInfo(XPP-SB2-BMMON)')
ipm3_src = psana.Source('BldInfo(XPP-SB3-BMMON)')
evr_src = psana.Source("DetInfo(NoDetector.0:Evr.0)")
def mpi_message(msg):
if rank == 0:
print(msg)
level=myloglevel)
EXPSTR = 'exp=mfxx32516:run=%d:smd' % (args.run[0])
# EXPSTR = 'exp=mfxx32516:run=%d:smd:dir=/reg/d/ffb/mfx/mfxx32516/xtc:live' % (args.run[0])
# 'MfxEndstation.0:Epix10ka.0' # spaghetti
# 'MfxEndstation.0:Epix10ka.1' # meatballs
# 'MfxEndstation.0:Epix10ka.2' # cheese
# filename = "".join([c for c in EXPSTR if c.isalnum()]).rstrip() + '.h5'
filename = "run_%d.h5" % (args.run[0])
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()
dsrc = pa.MPIDataSource(EXPSTR)
detNames = pa.DetNames() # detector names
mdets = [] # list of detectors
mdets_sname = [] # list of short detector names
mdets_idx = [] # list of detector indicies
# only archive detectors of interest
for idx, detname in enumerate(detNames):
sdet = detname[0].lower()
if "epix10ka" in sdet or "beammon" in sdet or "acqiris" in sdet or "wave8" in sdet:
mdets.append(detname[0])
mdets_sname.append(detname[1])
mdets_idx.append(idx)
# lists to keep track of detectors
mdets_d = []
