def sdds_to_dict(in_complete_path):
us_string = in_complete_path.split('.')[-2]
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file.'
return
data = temp.data[0]
cycleTime = data['cycleTime'].tostring()
t_stamp_unix = time.mktime(
time.strptime(
cycleTime.replace('"', '').replace('\n', '').split('.')[0],
'%Y/%m/%d %H:%M:%S'))
beamID = np.int_(data['beamID'])
deviceName = (data['deviceName'].tostring()).split('\n')[0]
acqState = np.int_(data['acqState'])
totalIntensity = data['totalIntensity']
acqTime = data['acqTime'].tostring()
propType = np.int_(data['propType'])
totalIntensity_unitExponent = np.int_(data['totalIntensity_unitExponent'])
bunchIntensitySlow = data['bunchIntensitySlow']
bunchIntensityFast = data['bunchIntensityFast']
gateIntensity_unitExponent = np.int_(data['gateIntensity_unitExponent'])
nbOfMeas = np.int_(data['nbOfMeas'])
totalIntensityFast = data['totalIntensityFast']
superCycleNb = np.int_(data['superCycleNb'])
acqMsg = data['acqMsg'].tostring()
measStamp = data['measStamp']
acqDesc = data['acqDesc'].tostring()
observables = np.int_(data['observables'])
totalIntensity_unit = np.int_(data['totalIntensity_unit'])
dict_meas = {
'beamID': beamID,
'deviceName': deviceName,
'acqState': acqState,
'totalIntensity': totalIntensity,
'acqTime': acqTime,
'propType': propType,
'totalIntensity_unitExponent': totalIntensity_unitExponent,
'bunchIntensitySlow': bunchIntensitySlow,
'bunchIntensityFast': bunchIntensityFast,
'gateIntensity_unitExponent': gateIntensity_unitExponent,
'nbOfMeas': nbOfMeas,
'totalIntensityFast': totalIntensityFast,
'superCycleNb': superCycleNb,
'cycleTime': cycleTime,
'acqMsg': acqMsg,
'measStamp': measStamp,
'acqDesc': acqDesc,
'observables': observables,
'totalIntensity_unit': totalIntensity_unit,
'SPSuser': us_string,
't_stamp_unix': t_stamp_unix
}
return dict_meas
def sdds_to_dict(in_complete_path):
us_string = in_complete_path.split('.')[-3]
t_stamp_unix = float(in_complete_path.split('@')[-2])/1e9+1
zfile = zipfile.ZipFile(in_complete_path)
filename = zfile.namelist()[0]
zfile.extract(filename)
try:
temp = sddsdata(filename, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_blmexpert_mat)'
return
os.remove(filename)
data = temp.data[0]
dict_meas = {
'totalLoss': data['totalLoss'],
'cal2DLosses': data['cal2DLosses'],
'nbOfChannels': data['nbOfChannels'],
'measStamp': data['measStamp'],
'nbOfMeas': data['nbOfMeas'],
'superCycleNb': data['superCycleNb'],
'channelNames': data['channelNames'],
'SPSuser':us_string,
't_stamp_unix':t_stamp_unix
}
return dict_meas
def sdds_to_dict(in_complete_path):
us_string = in_complete_path.split('.')[-3]
t_stamp_unix = float(in_complete_path.split('@')[-2]) / 1e9 + 1
zfile = zipfile.ZipFile(in_complete_path)
filename = zfile.namelist()[0]
zfile.extract(filename)
try:
temp = sddsdata(filename, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_blmexpert_mat)'
return
os.remove(filename)
data = temp.data[0]
dict_meas = {
'totalLoss': data['totalLoss'],
'cal2DLosses': data['cal2DLosses'],
'nbOfChannels': data['nbOfChannels'],
'measStamp': data['measStamp'],
'nbOfMeas': data['nbOfMeas'],
'superCycleNb': data['superCycleNb'],
'channelNames': data['channelNames'],
'SPSuser': us_string,
't_stamp_unix': t_stamp_unix
}
return dict_meas
def sdds_to_dict(in_complete_path):
us_string = in_complete_path.split('.')[-2]
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_bct_mat)'
return
data = temp.data[0]
cycleTime = data['cycleTime'].tostring()
t_stamp_unix = time.mktime(time.strptime(cycleTime.replace('"', '').replace('\n','').split('.')[0], '%Y/%m/%d %H:%M:%S'))
beamID = np.int_(data['beamID'])
deviceName = ((data['deviceName'].tostring()).split('\n')[0]).split('SPS.')[-1]
sbfIntensity = np.float_(data['sbfIntensity'])
acqState = np.int_(data['acqState'])
totalIntensity = data['totalIntensity']
acqTime = data['acqTime'].tostring()
propType = np.int_(data['propType'])
totalIntensity_unitExponent = np.int_(data['totalIntensity_unitExponent'])
measStamp_unitExponent = np.float_(data['measStamp_unitExponent'])
samplingTime = np.int_(data['samplingTime'])
measStamp_unit = np.int_(data['measStamp_unit'])
observables = np.int_(data['observables'])
nbOfMeas = np.int_(data['nbOfMeas'])
superCycleNb = np.int_(data['superCycleNb'])
acqMsg = data['acqMsg'].tostring()
measStamp = data['measStamp']
acqDesc = data['acqDesc'].tostring()
totalIntensity_unit = np.int_(data['totalIntensity_unit'])
dict_meas = {
'beamID':beamID,
'deviceName':deviceName,
'sbfIntensity':sbfIntensity,
'acqState':acqState,
'totalIntensity':totalIntensity,
'acqTime':acqTime,
'propType':propType,
'totalIntensity_unitExponent':totalIntensity_unitExponent,
'measStamp_unitExponent':measStamp_unitExponent,
'samplingTime':samplingTime,
'measStamp_unit':measStamp_unit,
'observables':observables,
'nbOfMeas':nbOfMeas,
'superCycleNb':superCycleNb,
'cycleTime':cycleTime,
'acqMsg':acqMsg,
'measStamp':measStamp,
'acqDesc':acqDesc,
'totalIntensity_unit':totalIntensity_unit,
'SPSuser':us_string,
't_stamp_unix':t_stamp_unix
}
return dict_meas
def sdds_to_dict(in_complete_path):
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_bct_mat)'
return
data = temp.data[0]
acq_comment = data['ACQ-COMMENT'].tostring()
cycle_length = np.float_(data['CYCLE-LENGTH'])
date = data['DATE'].tostring()
device_name = data['DEVICE-NAME'].tostring()
number_profiles = np.int_(data['NUMBER-PROFILES'])
number_strips = np.int_(data['NUMBER-STRIPS'])
profile_cycle_time = np.float_(data['PROFILE-CYCLE-TIME']) / 1e3
sc_number = np.int_(data['SC-NUMBER'])
time = data['TIME'].tostring()
timestamp_millisecond = np.int_(data['TIMESTAMP-MILLISECOND'])
timestamp_second = np.int_(data['TIMESTAMP-SECOND'])
timing_user = data['TIMING-USER'].tostring()
total_gain = data['TOTAL-GAIN']
eclm_data = np.zeros((number_profiles, number_strips))
for ii in range(number_profiles):
key_string = 'SEM-PROFILE-%d' % (ii + 1)
eclm_data[ii, :] = data[key_string]
device_name = in_complete_path.split('-')[0].split('/')[-1]
us_string = in_complete_path.split('-')[1].split('.')[-1]
dict_meas = {
'ACQ_COMMENT': acq_comment,
'DATE': date,
'DEVICE_NAME': device_name,
'NUMBER_PROFILES': number_profiles,
'NUMBER_STRIPS': number_strips,
'PROFILE_CYCLE_TIME': profile_cycle_time,
'SC_NUMBER': sc_number,
'TIME': time,
'TIMESTAMP_MILLISECOND': timestamp_millisecond,
'TIMESTAMP_SECOND': timestamp_second,
'TIMING_USER': timing_user,
'TOTAL_GAIN': total_gain,
'eclm_data': eclm_data,
'device_name': device_name,
'SPSuser': us_string
}
return dict_meas
def sdds_to_dict(in_complete_path):
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_bct_mat)'
return
data = temp.data[0]
acq_comment = data['ACQ-COMMENT'].tostring()
cycle_length = np.float_(data['CYCLE-LENGTH'])
date = data['DATE'].tostring()
device_name = data['DEVICE-NAME'].tostring()
number_profiles = np.int_(data['NUMBER-PROFILES'])
number_strips = np.int_(data['NUMBER-STRIPS'])
profile_cycle_time = np.float_(data['PROFILE-CYCLE-TIME']) / 1e3
sc_number = np.int_(data['SC-NUMBER'])
time = data['TIME'].tostring()
timestamp_millisecond = np.int_(data['TIMESTAMP-MILLISECOND'])
timestamp_second = np.int_(data['TIMESTAMP-SECOND'])
timing_user = data['TIMING-USER'].tostring()
total_gain = data['TOTAL-GAIN']
eclm_data = np.zeros((number_profiles, number_strips))
for ii in range(number_profiles):
key_string = 'SEM-PROFILE-%d'%(ii+1)
eclm_data[ii,:] = data[key_string]
device_name = in_complete_path.split('-')[0].split('/')[-1]
us_string = in_complete_path.split('-')[1].split('.')[-1]
dict_meas = {
'ACQ_COMMENT':acq_comment,
'DATE':date,
'DEVICE_NAME':device_name,
'NUMBER_PROFILES':number_profiles,
'NUMBER_STRIPS':number_strips,
'PROFILE_CYCLE_TIME':profile_cycle_time,
'SC_NUMBER':sc_number,
'TIME':time,
'TIMESTAMP_MILLISECOND':timestamp_millisecond,
'TIMESTAMP_SECOND':timestamp_second,
'TIMING_USER':timing_user,
'TOTAL_GAIN':total_gain,
'eclm_data':eclm_data,
'device_name':device_name,
'SPSuser':us_string
}
return dict_meas
def sdds_to_dict(in_complete_path):
us_string = in_complete_path.split('.')[-2]
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_multit_mat)'
return
data = temp.data[0]
nbOfMonitors = float(data['nbOfMonitors'])
BunchNos = np.float_(data['BunchNos'])
ChannelNames = data['ChannelNames']
MonStatus = np.float_(data['MonStatus'])
startTime = float(data['startTime'])
date = data['date'].tostring()
nbOfTurns = float(data['nbOfTurns'])
TurnNos = np.float_(data['TurnNos'])
scNumber = float(data['scNumber'])
SPSuser = data['user'].tostring().split('\n')[0]
acqComment = data['acqComment'].tostring()
MonPlanes = np.float_(data['MonPlanes'])
MonNames = data['MonNames']
Time = data['time'].tostring()
t_stamp_unix = float(
data['timestampSecond']) + float(data['timestampMilliSecond']) * 1e-3
dict_meas = {\
'BunchNos': BunchNos,
'ChannelNames': ChannelNames,
'MonStatus': MonStatus,
'startTime': startTime,
'date': date,
'nbOfTurns': nbOfTurns,
'TurnNos': TurnNos,
'scNumber': scNumber,
'SPSuser': SPSuser,
'acqComment': acqComment,
'MonPlanes': MonPlanes,
'nbOfMonitors': nbOfMonitors,
'MonNames': MonNames,
'Time': Time,
't_stamp_unix': t_stamp_unix\
}
for channel in ChannelNames:
dict_meas[channel] = np.float_(data[channel])
dict_meas[channel + '-SUM'] = np.float_(data[channel + '-SUM'])
return dict_meas
def sdds_to_dict(in_complete_path):
us_string = in_complete_path.split('.')[-2]
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_multit_mat)'
return
data = temp.data[0]
nbOfMonitors = float(data['nbOfMonitors'])
BunchNos = np.float_(data['BunchNos'])
ChannelNames = data['ChannelNames']
MonStatus = np.float_(data['MonStatus'])
startTime = float(data['startTime'])
date = data['date'].tostring()
nbOfTurns = float(data['nbOfTurns'])
TurnNos = np.float_(data['TurnNos'])
scNumber = float(data['scNumber'])
SPSuser = data['user'].tostring().split('\n')[0]
acqComment = data['acqComment'].tostring()
MonPlanes = np.float_(data['MonPlanes'])
MonNames = data['MonNames']
Time = data['time'].tostring()
t_stamp_unix = float(data['timestampSecond'])+float(data['timestampMilliSecond'])*1e-3
dict_meas = {\
'BunchNos': BunchNos,
'ChannelNames': ChannelNames,
'MonStatus': MonStatus,
'startTime': startTime,
'date': date,
'nbOfTurns': nbOfTurns,
'TurnNos': TurnNos,
'scNumber': scNumber,
'SPSuser': SPSuser,
'acqComment': acqComment,
'MonPlanes': MonPlanes,
'nbOfMonitors': nbOfMonitors,
'MonNames': MonNames,
'Time': Time,
't_stamp_unix': t_stamp_unix\
}
for channel in ChannelNames:
dict_meas[channel] = np.float_(data[channel])
dict_meas[channel+'-SUM'] = np.float_(data[channel+'-SUM'])
return dict_meas
def __init__(self,fn): sdds=sddsdata(fn) self.filename=fn self.bpms=r_[sdds.data[0]['bpmNames'],sdds.data[0]['bpmNames']] self.turns=sdds.data[0]['nbOfCapTurns'][0] xdata=sdds.data[0]['horPositionsConcentratedAndSorted'] ydata=sdds.data[0]['verPositionsConcentratedAndSorted'] self.data=r_[xdata,ydata].reshape(len(self.bpms),self.turns) self.xidx=zeros(len(self.bpms),dtype=bool) self.xidx[:len(self.bpms)/2]=True self.yidx=~self.xidx self.bad=self.find_bad_bpms() self.badxy=self.mk_badxy() self.t=arange(self.turns) self.goodx=(~self.badxy) & self.xidx self.goody=(~self.badxy) & self.yidx
def sdds_to_dict(in_complete_path):
us_string = in_complete_path.split('.')[-2]
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_bct_mat)'
return
data = temp.data[0]
frequency = np.float_(data['frequency'])
dict_meas = {
'frequency':frequency
}
return dict_meas
def sdds_to_dict(in_complete_path):
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_mr_mat)'
return
data = temp.data[0]
superCycleNb = float(data['SCNumber'])
cycleTag = float(data['cycleTag'])
firstSampleTime = float(data['firstSampleTime'])
offset = float(data['offset'])
sampleInterval = float(data['sampleInterval'])
sensitivity = float(data['sensitivity'])
triggerError = np.float_(data['triggerError'])
triggerStamp = data['triggerStamp']
value = np.float_(data['value'])
#value_units = data['value_units'].tostring()
first_trigger_t_stamp_unix = float(triggerStamp[0]) / 1e9
SPSuser = in_complete_path.split('SPS.USER.')[-1].split('.')[0]
time_string_filename = in_complete_path.split('@')[3]
time_string_filename = ':'.join(time_string_filename.split('_')[:-1])
date_string_path = in_complete_path.split('/')[-3]
t_stamp_unix = time.mktime(
time.strptime(date_string_path + ' ' + time_string_filename,
'%Y_%m_%d %H:%M:%S'))
dict_meas = {
'superCycleNb': superCycleNb,
'cycleTag': cycleTag,
'firstSampleTime': firstSampleTime,
'offset': offset,
'sampleInterval': sampleInterval,
'sensitivity': sensitivity,
'triggerError': triggerError,
'triggerStamp': triggerStamp,
'value': value,
'first_trigger_t_stamp_unix': first_trigger_t_stamp_unix,
'SPSuser': SPSuser,
't_stamp_unix': t_stamp_unix
}
return dict_meas
def sdds_to_dict(in_complete_path):
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_mr_mat)'
return
data = temp.data[0]
superCycleNb = float(data['SCNumber'])
cycleTag = float(data['cycleTag'])
firstSampleTime = float(data['firstSampleTime'])
offset = float(data['offset'])
sampleInterval = float(data['sampleInterval'])
sensitivity = float(data['sensitivity'])
triggerError = np.float_(data['triggerError'])
triggerStamp = data['triggerStamp']
value = np.float_(data['value'])
#value_units = data['value_units'].tostring()
first_trigger_t_stamp_unix = float(triggerStamp[0])/1e9
SPSuser = in_complete_path.split('SPS.USER.')[-1].split('.')[0]
time_string_filename = in_complete_path.split('@')[3]
time_string_filename = ':'.join(time_string_filename.split('_')[:-1])
date_string_path = in_complete_path.split('/')[-3]
t_stamp_unix = time.mktime(time.strptime(date_string_path + ' ' + time_string_filename, '%Y_%m_%d %H:%M:%S'))
dict_meas = {
'superCycleNb': superCycleNb,
'cycleTag': cycleTag,
'firstSampleTime': firstSampleTime,
'offset': offset,
'sampleInterval': sampleInterval,
'sensitivity': sensitivity,
'triggerError': triggerError,
'triggerStamp': triggerStamp,
'value': value,
'first_trigger_t_stamp_unix': first_trigger_t_stamp_unix,
'SPSuser': SPSuser,
't_stamp_unix': t_stamp_unix }
return dict_meas
def __init__(self,fn,iqc=True):
self.fn=fn
sdds=sddsdata.sddsdata(open(fn))
self.bpms=r_[sdds.data[0]['bpmNames']]
self.nbpms=len(self.bpms)
self.turns=sdds.data[0]['nbOfCapTurns'][0]
self.bunches=sdds.data[0]['nbOfCapBunches'][0]
xdata=sdds.data[0]['horPositionsConcentratedAndSorted']
ydata=sdds.data[0]['verPositionsConcentratedAndSorted']
if iqc:
self.xbpm=xdata.reshape(self.nbpms,self.turns,self.bunches).transpose(0,2,1)
self.ybpm=ydata.reshape(self.nbpms,self.turns,self.bunches).transpose(0,2,1)
else:
self.xbpm=xdata.reshape(self.nbpms,self.bunches,self.turns)
self.ybpm=ydata.reshape(self.nbpms,self.bunches,self.turns)
self.dt=sdds.data[0]['acqStamp'][0]/1e9
self.date=dumpdate(self.dt)
self.sdds=sdds
if 'B2' in self.bpms[0]:
self.beam=2
elif 'B1' in self.bpms[0]:
self.beam=1
def sdds_to_dict(in_complete_path):
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file.'
return
data = temp.data[0]
filename = in_complete_path.split('/')[-1]
date_string = in_complete_path.split('/')[-3]
us_string = filename.split('SPS.USER.')[-1].split('.sdds')[0]
time_string = filename.split('Acquisition@')[-1].split('@')[0]
temp_timest_string = date_string + '_' + time_string
ms = float(temp_timest_string.split('_')[-1])
t_stamp_unix = time.mktime(
time.strptime(temp_timest_string[:-4],
'%Y_%m_%d_%H_%M_%S')) + ms * 1e-3
t_stamp_string = temp_timest_string
rawDataH = np.float_(data['rawDataH'])
rawDataV = np.float_(data['rawDataV'])
deviceName = str(data['deviceName']).split('\n')[0]
triggerName = str(data['triggerName']).split('\n')[0]
acqPeriod = np.int(data['acqPeriod'])
dataMode = np.int(data['dataMode'])
stopCycleTime = np.int(data['stopCycleTime'])
requestedNbOfMeas = np.int(data['requestedNbOfMeas'])
doneNbOfMeas = np.int(data['doneNbOfMeas'])
cycleNumber = np.int(data['cycleNumber'])
nbOfTurns = np.int(data['nbOfTurns'])
acqOffset = np.int(data['acqOffset'])
cycleLength = np.uint64(data['cycleLength'])
measStamp = np.int_(data['measStamp'])
propType = np.int(data['propType'])
frevSource = np.int(data['frevSource'])
doneNbOfIRQs = np.int(data['doneNbOfIRQs'])
observables = np.int(data['observables'])
exOffset = np.int(data['exOffset'])
exDelay = np.int(data['exDelay'])
exPeriod = np.int(data['exPeriod'])
exMode = np.int(data['exMode'])
windowFunction = np.int(data['windowFunction'])
minSearchWindowFreqV = np.float(data['minSearchWindowFreqV'])
minSearchWindowFreqH = np.float(data['minSearchWindowFreqH'])
maxSearchWindowFreqV = np.float(data['maxSearchWindowFreqV'])
maxSearchWindowFreqH = np.float(data['maxSearchWindowFreqH'])
ring = np.int(data['ring'])
chirpMode = np.int(data['chirpMode'])
chirpStartFreqH = np.float(data['chirpStartFreqH'])
chirpStartFreqV = np.float(data['chirpStartFreqV'])
chirpStopFreqH = np.float(data['chirpStopFreqH'])
chirpStopFreqV = np.float(data['chirpStopFreqV'])
enableExcitationH = np.int(data['enableExcitationH'])
enableExcitationV = np.int(data['enableExcitationV'])
excitationAmplitudeV = np.float(data['excitationAmplitudeV'])
excitationAmplitudeH = np.float(data['excitationAmplitudeH'])
dict_meas = {
't_stamp_unix': t_stamp_unix,
't_stamp_string': t_stamp_string,
'SPSuser': us_string,
'deviceName': deviceName,
'rawDataH': rawDataH,
'rawDataV': rawDataV,
'triggerName': triggerName,
'acqPeriod': acqPeriod,
'dataMode': dataMode,
'stopCycleTime': stopCycleTime,
'requestedNbOfMeas': requestedNbOfMeas,
'doneNbOfMeas': doneNbOfMeas,
'cycleNumber': cycleNumber,
'nbOfTurns': nbOfTurns,
'acqOffset': acqOffset,
'cycleLength': cycleLength,
'measStamp': measStamp,
'propType': propType,
'frevSource': frevSource,
'doneNbOfIRQs': doneNbOfIRQs,
'observables': observables,
'exOffset': exOffset,
'exDelay': exDelay,
'exPeriod': exPeriod,
'exMode': exMode,
'windowFunction': windowFunction,
'minSearchWindowFreqV': minSearchWindowFreqV,
'minSearchWindowFreqH': minSearchWindowFreqH,
'maxSearchWindowFreqV': maxSearchWindowFreqV,
'maxSearchWindowFreqH': maxSearchWindowFreqH,
'ring': ring,
'chirpMode': chirpMode,
'chirpStartFreqH': chirpStartFreqH,
'chirpStartFreqV': chirpStartFreqV,
'chirpStopFreqH': chirpStopFreqH,
'chirpStopFreqV': chirpStopFreqV,
'enableExcitationH': enableExcitationH,
'enableExcitationV': enableExcitationV,
'excitationAmplitudeV': excitationAmplitudeV,
'excitationAmplitudeH': excitationAmplitudeH
}
return dict_meas
def sdds_to_dict(in_complete_path):
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file.'
return
data = temp.data[0]
filename = in_complete_path.split('/')[-1]
date_string = in_complete_path.split('/')[-3]
us_string = filename.split('SPS.USER.')[-1].split('.sdds')[0]
time_string = filename.split('Acquisition@')[-1].split('@')[0]
temp_timest_string = date_string+'_'+time_string
ms = float(temp_timest_string.split('_')[-1])
t_stamp_unix = time.mktime(time.strptime(temp_timest_string[:-4], '%Y_%m_%d_%H_%M_%S'))+ms*1e-3
t_stamp_string = temp_timest_string
rawDataH = np.float_(data['rawDataH'])
rawDataV = np.float_(data['rawDataV'])
deviceName = str(data['deviceName']).split('\n')[0]
triggerName = str(data['triggerName']).split('\n')[0]
acqPeriod = np.int(data['acqPeriod'])
dataMode = np.int(data['dataMode'])
stopCycleTime = np.int(data['stopCycleTime'])
requestedNbOfMeas = np.int(data['requestedNbOfMeas'])
doneNbOfMeas = np.int(data['doneNbOfMeas'])
cycleNumber = np.int(data['cycleNumber'])
nbOfTurns = np.int(data['nbOfTurns'])
acqOffset = np.int(data['acqOffset'])
cycleLength = np.uint64(data['cycleLength'])
measStamp = np.int_(data['measStamp'])
propType = np.int(data['propType'])
frevSource = np.int(data['frevSource'])
doneNbOfIRQs = np.int(data['doneNbOfIRQs'])
observables = np.int(data['observables'])
exOffset = np.int(data['exOffset'])
exDelay = np.int(data['exDelay'])
exPeriod = np.int(data['exPeriod'])
exMode = np.int(data['exMode'])
windowFunction = np.int(data['windowFunction'])
minSearchWindowFreqV = np.float(data['minSearchWindowFreqV'])
minSearchWindowFreqH = np.float(data['minSearchWindowFreqH'])
maxSearchWindowFreqV = np.float(data['maxSearchWindowFreqV'])
maxSearchWindowFreqH = np.float(data['maxSearchWindowFreqH'])
ring = np.int(data['ring'])
chirpMode = np.int(data['chirpMode'])
chirpStartFreqH = np.float(data['chirpStartFreqH'])
chirpStartFreqV = np.float(data['chirpStartFreqV'])
chirpStopFreqH = np.float(data['chirpStopFreqH'])
chirpStopFreqV = np.float(data['chirpStopFreqV'])
enableExcitationH = np.int(data['enableExcitationH'])
enableExcitationV = np.int(data['enableExcitationV'])
excitationAmplitudeV = np.float(data['excitationAmplitudeV'])
excitationAmplitudeH = np.float(data['excitationAmplitudeH'])
dict_meas = {
't_stamp_unix':t_stamp_unix,
't_stamp_string':t_stamp_string,
'SPSuser':us_string,
'deviceName':deviceName,
'rawDataH':rawDataH,
'rawDataV':rawDataV,
'triggerName':triggerName,
'acqPeriod':acqPeriod,
'dataMode':dataMode,
'stopCycleTime':stopCycleTime,
'requestedNbOfMeas':requestedNbOfMeas,
'doneNbOfMeas':doneNbOfMeas,
'cycleNumber':cycleNumber,
'nbOfTurns':nbOfTurns,
'acqOffset':acqOffset,
'cycleLength':cycleLength,
'measStamp':measStamp,
'propType':propType,
'frevSource':frevSource,
'doneNbOfIRQs':doneNbOfIRQs,
'observables':observables,
'exOffset':exOffset,
'exDelay':exDelay,
'exPeriod':exPeriod,
'exMode':exMode,
'windowFunction':windowFunction,
'minSearchWindowFreqV':minSearchWindowFreqV,
'minSearchWindowFreqH':minSearchWindowFreqH,
'maxSearchWindowFreqV':maxSearchWindowFreqV,
'maxSearchWindowFreqH':maxSearchWindowFreqH,
'ring':ring,
'chirpMode':chirpMode,
'chirpStartFreqH':chirpStartFreqH,
'chirpStartFreqV':chirpStartFreqV,
'chirpStopFreqH':chirpStopFreqH,
'chirpStopFreqV':chirpStopFreqV,
'enableExcitationH':enableExcitationH,
'enableExcitationV':enableExcitationV,
'excitationAmplitudeV':excitationAmplitudeV,
'excitationAmplitudeH':excitationAmplitudeH
}
return dict_meas
import sddsdata as sdds filename = "LHCBPM2-Mon_Jun_29_16-26-00_CEST_2009.sdds" a = sdds.sddsdata(filename, 'big') print a.data[0].keys()
def pull_to_hdf5(device='fbct', day=pd.datetime.today().strftime("%Y_%m_%d")):
global path_to_fbct, output_path
if device is 'fbct':
device_no = '31450'
path_to_fbct += "{:s}/SPS.BCTFR.{:s}@Acquisition/".format(
day, device_no)
output_path += device.upper(
) + "/{:s}/SPS.BCTFR.{:s}@Acquisition/".format(day, device_no)
files = glob.glob(path_to_fbct + "*.sdds")
filenames = map(lambda s: s.split('/')[-1], files)
else:
raise ValueError("Unknown device {:s}".format(device))
# Create output directories if not already present
if not os.path.isdir(output_path):
os.makedirs(output_path)
# Store in file all sdds which have already been converted
if not os.path.exists(output_path + 'converted_fbct.txt'):
with open(output_path + 'converted_fbct.txt', 'w') as fh:
fh.write("*** Converted fbct files created at {:s}".format(
str(pd.datetime.now())))
else:
with open(output_path + 'converted_fbct.txt', 'r') as fh:
converted_list = fh.read().splitlines()
del converted_list[0]
# List of files still to be converted
unconverted_files = [
fn for i, fn in enumerate(files) if filenames[i] not in converted_list
]
for fl in unconverted_files[:]:
try:
data = sddsdata(fl, endian='little', full=True)
except IOError as err:
print("Failed to open file {:s}!".format(fl.split('/')[-1]))
print(err.message)
raise err
ddict = data.data[0]
fname = data.filename.split("/")[-1].replace("sdds", "h5")
with h5py.File(output_path + fname, "w") as h5file:
for t, v in ddict.items():
try:
h5file.create_dataset(t,
data=v,
compression='gzip',
compression_opts=9)
except TypeError as err:
# print(err.message)
h5file.create_dataset(t, data=v)
# Register converted files in converted file list
with open(output_path + 'converted_fbct.txt', 'a') as fh:
fh.write(fname.replace("h5", "sdds") + "\n")
print("\n--> Converted file {:s} to hdf5 in folder {:s}".format(
fname, output_path))
def sdds_to_dict(in_complete_path):
us_string = in_complete_path.split('.')[-2]
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_multiq_mat)'
return
data = temp.data[0]
BBQ_Version = data['BBQ-Version'].tostring()
acqOffset = float(data['acqOffset'])
acqPeriod = float(data['acqPeriod'])
acqStartTimes = np.float_(data['acqStartTimes'])
acqTimes = np.float_(data['acqTimes'])
chirpStartFreqH = float(data['chirpStartFreqH'])
chirpStartFreqV = float(data['chirpStartFreqV'])
chirpStopFreqH = float(data['chirpStopFreqH'])
chirpStopFreqV = float(data['chirpStopFreqV'])
date = data['date'].tostring()
enableExcitationH = bool(data['enableExcitationH'])
enableExcitationV = bool(data['enableExcitationV'])
exDelay = float(data['exDelay'])
exOffset = float(data['exOffset'])
exPeriod = float(data['exPeriod'])
excitationAmplitudeH = float(data['excitationAmplitudeH'])
excitationAmplitudeV = float(data['excitationAmplitudeV'])
fullNumberOfTurns = float(data['fullNumberOfTurns'])
nbOfMeas = float(data['nbOfMeas'])
nbOfTurns = float(data['nbOfTurns'])
superCycleNb = float(data['scNumber'])
Time = data['time'].tostring()
triggerName = data['triggerName'].tostring()
tuneDataH = data['tuneDataH']
tuneDataV = data['tuneDataV']
SPSuser = data['user'].tostring().split('\n')[0]
window = data['window'].tostring()
windowFunction = float(data['windowFunction'])
t_stamp_unix = float(
data['timestampSecond']) + float(data['timestampMilliSecond']) * 1e-3
rawData_H = []
rawData_V = []
for ii in xrange(int(nbOfMeas)):
rawData_H.append(data['rawData-H-%d' % (ii + 1)])
rawData_V.append(data['rawData-V-%d' % (ii + 1)])
rawData_H = np.float_(np.array(rawData_H))
rawData_V = np.float_(np.array(rawData_V))
dict_meas = {\
'BBQ_Version': BBQ_Version,
'acqOffset': acqOffset,
'acqPeriod': acqPeriod,
'acqStartTimes':acqStartTimes,
'acqTimes': acqTimes,
'chirpStartFreqH': chirpStartFreqH,
'chirpStartFreqV': chirpStartFreqV,
'chirpStopFreqH ':chirpStopFreqH,
'chirpStopFreqV':chirpStopFreqV,
'date':date,
'enableExcitationH':enableExcitationH,
'enableExcitationV':enableExcitationV,
'exDelay':exDelay,
'exOffset':exOffset,
'exPeriod': exPeriod,
'excitationAmplitudeH':excitationAmplitudeH,
'excitationAmplitudeV': excitationAmplitudeV,
'fullNumberOfTurns': fullNumberOfTurns,
'nbOfMeas':nbOfMeas,
'nbOfTurns':nbOfTurns,
'superCycleNb': superCycleNb,
'Time': Time,
'triggerName': triggerName,
'tuneDataH': tuneDataH,
'tuneDataV': tuneDataV,
'SPSuser': SPSuser,
'window ':window,
'windowFunction': windowFunction,
'rawData_H':rawData_H,
'rawData_V':rawData_V,
't_stamp_unix':t_stamp_unix\
}
return dict_meas
#!/afs/cern.ch/eng/sl/lintrack/Python-2.5_32bit/Python-2.5_32bit/bin/python
import sddsdata as sdds
t=sdds.sddsdata('/afs/cern.ch/user/r/rtomas/lintrack/LHCBPM1-Wed_Sep_10_21-01-36_CEST_2008.sdds.sdds','big')
print t.data[t.data.keys()[0]]
bpm1=t.data.keys()[1]
print bpm1, t.data[bpm1]
header= t.header
bpmnames = t.data['bpmNames']
print bpmnames
othernames= [i for i in t.data.keys() if 'BPM' not in i]
thevalues = [t.data[i] for i in othernames]
print othernames
print thevalues
#print t.data['bpmNames']
filenamedir=filenamedir+'/'
onlyfilename=filename.split('/')[-1]
convert=sys.argv[0] #We assume that twiss.dat is in the same dir as the convert.py
convertdir=join(convert.split('/')[0:-1], '/')
if convertdir=='':
convertdir='.'
tf=convertdir+'/twiss.dat'
print "TWISS FILE: ", tf
tw=twiss(tf)
#t=sdds.sddsdata('/afs/cern.ch/user/r/rtomas/lintrack/LHCBPM1-Wed_Sep_10_21-01-36_CEST_2008.sdds.sdds','big')
a=sdds.sddsdata(filename, 'big')
nbOfCapBunches=int(a.data['nbOfCapBunches'])
nbOfCapTurns=int(a.data['nbOfCapTurns'])
print "Turns, Bunches:", nbOfCapTurns,nbOfCapBunches
bpmnames = a.data['bpmNames']
channelnames = a.data['ChannelNames']
#otherBPMnames= [i for i in a.data.keys() if 'BPM' in i]
othernames= [i for i in a.data.keys() if 'BPM' not in i]
#print bpmnames[0],otherBPMnames[0]
#print othernames
#print a.data['BPMSW.1L1.B1/H-bunch111']
bunchfile={}
def sdds_to_dict(in_complete_path):
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_bct_mat)'
return
data = temp.data[0]
try:
dict_meas = {
'acqDesc':
data['acqDesc'].tostring(),
'acqMsg':
data['acqMsg'].tostring(),
'acqState':
np.int_(data['acqState']),
'acqTime':
data['acqTime'].tostring(),
'measStamp':
data['measStamp'],
'measStamp_unit':
np.int_(data['measStamp_unit']),
'measStamp_unitExponent':
np.float_(data['measStamp_unitExponent']),
'nbOfMeas':
np.int_(data['nbOfMeas']),
'observables':
np.int_(data['observables']),
'propType':
np.int_(data['propType']),
'samplingTime':
np.int_(data['samplingTime']),
'sbfIntensity':
np.float_(data['sbfIntensity']),
'superCycleNb':
np.int_(data['superCycleNb']),
'totalIntensity':
data['totalIntensity'],
'totalIntensity_unit':
np.int_(data['totalIntensity_unit']),
'totalIntensity_unitExponent':
np.int_(data['totalIntensity_unitExponent']),
'deviceName':
((data['deviceName'].tostring()).split('\n')[0]).split('SPS.')[-1],
'beamID':
np.int_(data['beamID']),
'cycleTime':
data['cycleTime'].tostring(),
}
except KeyError as err:
print(err.message)
print("This looks like a post October 2017 SDDS... will try to adapt.")
# import pdb; pdb.set_trace()
dict_meas = {
'calMarkerData':
data['calMarkerData'],
'inCheckStatusData':
data['inCheckStatusData'],
'range1Data':
data['range1Data'],
'range2Data':
data['range2Data'],
'range3Data':
data['range3Data'],
'totalIntensity':
data['totalIntensity'],
'totalIntensity4Ranges':
data['totalIntensity4Ranges'],
'acqMsg':
data['acqMsg'],
'acqState':
data['acqState'],
'acqTime':
data['acqTime'],
'cycleTime':
data['cycleTime'],
'dumpCycleTime':
data['dumpCycleTime'],
'dumpInt':
data['dumpInt'],
'measStamp_unit':
np.int_(data['measStamp_unit']),
'measStamp_unitExponent':
data['measStamp_unitExponent'],
'nbOfAdcData':
np.int_(data['nbOfAdcData']),
'nbOfMeas':
data['nbOfMeas'],
'samplingTime':
data['samplingTime'],
'sbfCycleTime':
data['sbfCycleTime'],
'sbfIntensity':
data['sbfIntensity'],
'selectedRange':
data['selectedRange'],
'slowCycleTime':
data['slowCycleTime'],
'slowExtInt':
data['slowExtInt'],
'superCycleNb':
data['superCycleNb'],
'totalIntensity_unit':
data['totalIntensity_unit'],
'totalIntensity_unitExponent':
data['totalIntensity_unitExponent'],
'vmodStatus':
data['vmodStatus'],
'acqDesc':
data['acqDesc'],
'beamID':
0,
'deviceName':
data['acqMsg'].tostring().replace(
'\n', '').strip('"').split(':')[-1].split('SPS.')[-1],
'lowIbStatusData':
data['lowIbStatusData'],
'measStamp':
data['measStamp'],
'range4Data':
data['range4Data'],
}
us_string = in_complete_path.split('.')[-2]
cycleTime = data['cycleTime'].tostring()
t_stamp_unix = time.mktime(
time.strptime(
cycleTime.replace('"', '').replace('\n', '').split('.')[0],
'%Y/%m/%d %H:%M:%S'))
dict_meas['SPSuser'] = us_string
dict_meas['t_stamp_unix'] = t_stamp_unix
return dict_meas
def sdds_to_dict(in_complete_path):
us_string = in_complete_path.split('.')[-2]
try:
temp = sddsdata(in_complete_path, endian='little', full=True)
except IndexError:
print 'Failed to open data file. (save_multiq_mat)'
return
data = temp.data[0]
BBQ_Version = data['BBQ-Version'].tostring()
acqOffset = float(data['acqOffset'])
acqPeriod = float(data['acqPeriod'])
acqStartTimes = np.float_(data['acqStartTimes'])
acqTimes = np.float_(data['acqTimes'])
chirpStartFreqH = float(data['chirpStartFreqH'])
chirpStartFreqV = float(data['chirpStartFreqV'])
chirpStopFreqH = float(data['chirpStopFreqH'])
chirpStopFreqV = float(data['chirpStopFreqV'])
date = data['date'].tostring()
enableExcitationH = bool(data['enableExcitationH'])
enableExcitationV = bool(data['enableExcitationV'])
exDelay = float(data['exDelay'])
exOffset = float(data['exOffset'])
exPeriod = float(data['exPeriod'])
excitationAmplitudeH = float(data['excitationAmplitudeH'])
excitationAmplitudeV = float(data['excitationAmplitudeV'])
fullNumberOfTurns = float(data['fullNumberOfTurns'])
nbOfMeas = float(data['nbOfMeas'])
nbOfTurns = float(data['nbOfTurns'])
superCycleNb = float(data['scNumber'])
Time = data['time'].tostring()
triggerName = data['triggerName'].tostring()
tuneDataH = data['tuneDataH']
tuneDataV = data['tuneDataV']
SPSuser = data['user'].tostring().split('\n')[0]
window = data['window'].tostring()
windowFunction = float(data['windowFunction'])
t_stamp_unix = float(data['timestampSecond'])+float(data['timestampMilliSecond'])*1e-3
rawData_H=[]
rawData_V=[]
for ii in xrange(int(nbOfMeas)):
rawData_H.append(data['rawData-H-%d'%(ii+1)])
rawData_V.append(data['rawData-V-%d'%(ii+1)])
rawData_H = np.float_(np.array(rawData_H))
rawData_V = np.float_(np.array(rawData_V))
dict_meas = {\
'BBQ_Version': BBQ_Version,
'acqOffset': acqOffset,
'acqPeriod': acqPeriod,
'acqStartTimes':acqStartTimes,
'acqTimes': acqTimes,
'chirpStartFreqH': chirpStartFreqH,
'chirpStartFreqV': chirpStartFreqV,
'chirpStopFreqH ':chirpStopFreqH,
'chirpStopFreqV':chirpStopFreqV,
'date':date,
'enableExcitationH':enableExcitationH,
'enableExcitationV':enableExcitationV,
'exDelay':exDelay,
'exOffset':exOffset,
'exPeriod': exPeriod,
'excitationAmplitudeH':excitationAmplitudeH,
'excitationAmplitudeV': excitationAmplitudeV,
'fullNumberOfTurns': fullNumberOfTurns,
'nbOfMeas':nbOfMeas,
'nbOfTurns':nbOfTurns,
'superCycleNb': superCycleNb,
'Time': Time,
'triggerName': triggerName,
'tuneDataH': tuneDataH,
'tuneDataV': tuneDataV,
'SPSuser': SPSuser,
'window ':window,
'windowFunction': windowFunction,
'rawData_H':rawData_H,
'rawData_V':rawData_V,
't_stamp_unix':t_stamp_unix\
}
return dict_meas
