def savefile(self):
"""Saves the parameters out"""
fn = tkFileDialog.asksaveasfilename(title="Save File",filetypes=[('INI','.ini'),('PICKLE','.pickle')])
blist = self.pickbeams.output
self.pickbeams.buttonClick(fn)
radarname = self.pickbeams.var.get()
posspec = ['N2+', 'N+', 'O+', 'NO+', 'H+', 'O2+','e-' ]
specieslist = self.species.get().lower().split()
newlist =[x for x in posspec if x.lower() in specieslist]
if 'e-' not in newlist:newlist.append('e-')
simparams ={'IPP':float(self.ipp.get()),
'TimeLim':float(self.timelim.get()),
'RangeLims':[int(float(self.rangelimlow.get())),int(float(self.rangelimhigh.get()))],
'Pulselength':1e-6*float(self.pulselength.get()),
't_s': 1e-6*float(self.t_s.get()),
'Pulsetype':self.pulsetype.get(),
'Tint':float(self.tint.get()),
'Fitinter':float(self.fitinter.get()),
'NNs': int(float(self.nns.get())),
'NNp':int(float(self.nnp.get())),
'dtype':{'complex128':sp.complex128,'complex64':sp.complex64}[self.dtype.get()],
'ambupsamp':int(float(self.ambupsamp.get())),
'species':newlist,
'numpoints':int(float(self.numpoints.get())),
'startfile':self.startfile.get(),
'FitType': self.fittype.get()}
if len(self.outangles.get())>0:
outlist1 = self.outangles.get().split(',')
simparams['outangles']=[[ float(j) for j in i.lstrip().rstrip().split(' ')] for i in outlist1]
makeconfigfile(fn,blist,radarname,simparams)
def makedatasets(maindir='~/DATA/Ion_Comp_Exp/',
nomult=sp.arange(1, 5, dtype=float),
baud_len=[7, 14, 21]):
"""
This will make all of the data sets.
"""
basepath = Path(maindir).expanduser()
basepath.mkdir(exist_ok=True)
iono_orig = pyglowinput()
nion = len(iono_orig.Species) - 1
npulses = 1000
(sensdict, simparams) = getdefualtparams()
tint = simparams['IPP'] * npulses
ratio1 = tint / simparams['Tint']
simparams['RangeLims'] = [80., 750.]
simparams['Tint'] = ratio1 * simparams['Tint']
simparams['Fitinter'] = ratio1 * simparams['Fitinter']
simparams['TimeLim'] = 12 * tint
ts = simparams['t_s']
simparams['beamrate'] = 1
simparams['outangles'] = [[0]]
simparams['species'] = ['O+', 'NO+', 'O2+', 'H+', 'e-']
origtime = iono_orig.Time_Vector[0, 0]
for imult in nomult:
curiono = iono_orig.copy()
curiono.Param_List[:, :, 1, 0] *= imult
ratio = curiono.Param_List[:, :, -1, 0] / curiono.Param_List[:, :, :-1,
0].sum(-1)
ratio_ar = sp.repeat(ratio[:, :, sp.newaxis], nion, axis=-1)
curiono.Param_List[:, :, :-1, 0] *= ratio_ar
figout = plotiono(curiono)[0]
for ibaud in baud_len:
newpath = basepath.joinpath('NOMult{0:02d}baud{1:02d}'.format(
int(imult), int(ibaud)))
newpath.joinpath('Origparams').mkdir(exist_ok=True, parents=True)
figname = newpath.joinpath('InputParams.png')
figout.savefig(str(figname))
dataname = newpath.joinpath('Origparams',
'{0:d}Params.h5'.format(origtime))
curiono.saveh5(str(dataname))
simparams['Pulselength'] = ibaud * ts
sfile = str(newpath / 'startfile.h5')
iono_orig.saveh5(sfile)
simparams['startfile'] = sfile
makeconfigfile(str(newpath / 'chem_test.yml'), [23465.],
'millstone', simparams)
def configsetup(testpath):
"""This function will make a pickle file used to configure the simulation.
Inputs
testpath - A string for the path that this file will be saved."""
# list of beams that will give a line of points between 70 and 80 deg el with az of 20 deg
beamlist = [16626, 16987, 17348, 17709, 18070, 18431, 18792, 19153]#, 19514] # list of beams in
radarname = 'millstone'# name of radar for parameters can either be pfisr or risr
# pulse = sp.ones(14)# pulse
rng_lims = [150,500]# limits of the range gates
IPP = 1e-2#8.7e-3 #interpulse period in seconds
NNs = 28 # number of noise samples per pulse
NNp = 100 # number of noise pulses
b_rate = 100
intrate = 2.
Tint=intrate*b_rate*IPP # integration time in seconds
time_lim = len(beamlist)/intrate*4.0*Tint # simulation length in seconds
fitter_int = Tint*len(beamlist)/intrate # time interval between fitted params
simparams = {'IPP':IPP, #interpulse period
'TimeLim':time_lim, # length of simulation
'RangeLims':rng_lims, # range swath limit
# 'Pulse':pulse, # pulse shape
'Pulselength':280e-6,
'FitType' :'acf',
't_s': 20e-6,
'Pulsetype':'long', # type of pulse can be long or barker,
'Tint':Tint, #Integration time for each fitting
'Fitinter':fitter_int, # time interval between fitted params
'NNs': NNs,# number of noise samples per pulse
'NNp':NNp, # number of noise pulses
'dtype':sp.complex128, #type of numbers used for simulation
'ambupsamp':1, # up sampling factor for ambiguity function
'species':['O+','e-'], # type of ion species used in simulation
'numpoints':128, # number of points for each spectrum
'startfile': str(testpath/'startdata.h5'),# file used for starting points
'beamrate':b_rate,# the number of pulses each beam will output until it moves
'outangles':[sp.arange(i,i+intrate) for i in sp.arange(0,len(beamlist),intrate)]}
# 'SUMRULE': sp.array([[-2,-3,-3,-4,-4,-5,-5,-6,-6,-7,-7,-8,-8,-9]
# ,[1,1,2,2,3,3,4,4,5,5,6,6,7,7]])}
fname = testpath/'DishExample'
makeconfigfile(fname.with_suffix('.ini'),beamlist,radarname,simparams)
def makeconfigfilebarker(testpath):
testpath = Path(testpath).expanduser()
beamlist = [
64094, 64091, 64088, 64085, 64082, 64238, 64286, 64070, 64061, 64058,
64055, 64052, 64049, 64046, 64043, 64067, 64040, 64037, 64034
]
radarname = 'pfisr'
Tint = 4.0 * 60.0
time_lim = 3.0 * Tint
pulse = GenBarker(7)
rng_lims = [75.0, 250.0]
IPP = .0087
NNs = 28
NNp = 100
t_s = 2e-5
Pulselength = len(pulse) * t_s
simparams = {
'IPP': IPP,
'TimeLim': time_lim,
'RangeLims': rng_lims,
'Pulse': pulse,
'Pulsetype': 'barker',
'Pulselength': Pulselength,
't_s': t_s,
'Tint': Tint,
'Fitinter': Tint,
'NNs': NNs,
'NNp': NNp,
'dtype': sp.complex128,
'ambupsamp': 30,
'species': ['O+', 'e-'],
'numpoints': 128,
'FitType': 'acf',
'startfile': str(testpath.joinpath('startdata.h5'))
}
fn = testpath / 'barkertest.yml'
makeconfigfile(fn, beamlist, radarname, simparams)
def makedatasets(maindir='~/DATA/Ion_Comp_Exp/', nomult=sp.arange(1, 5, dtype=float), baud_len=[7, 14, 21]):
"""
This will make all of the data sets.
"""
basepath = Path(maindir).expanduser()
basepath.mkdir(exist_ok=True)
iono_orig = pyglowinput()
nion = len(iono_orig.Species)-1
npulses = 1000
(sensdict, simparams) = getdefualtparams()
tint = simparams['IPP']*npulses
ratio1 = tint/simparams['Tint']
simparams['RangeLims'] = [80., 750.]
simparams['Tint'] = ratio1 * simparams['Tint']
simparams['Fitinter'] = ratio1 * simparams['Fitinter']
simparams['TimeLim'] = 12*tint
ts = simparams['t_s']
simparams['beamrate'] = 1
simparams['outangles'] = [[0]]
simparams['species'] = ['O+', 'NO+', 'O2+', 'H+', 'e-']
origtime = iono_orig.Time_Vector[0,0]
for imult in nomult:
curiono = iono_orig.copy()
curiono.Param_List[:, :, 1, 0] *= imult
ratio = curiono.Param_List[:, :, -1, 0]/curiono.Param_List[:, :, :-1, 0].sum(-1)
ratio_ar = sp.repeat(ratio[:, :, sp.newaxis], nion, axis=-1)
curiono.Param_List[:, :, :-1, 0] *= ratio_ar
figout = plotiono(curiono)[0]
for ibaud in baud_len:
newpath = basepath.joinpath('NOMult{0:02d}baud{1:02d}'.format(int(imult), int(ibaud)))
newpath.joinpath('Origparams').mkdir(exist_ok=True, parents=True)
figname = newpath.joinpath('InputParams.png')
figout.savefig(str(figname))
dataname = newpath.joinpath('Origparams', '{0:d}Params.h5'.format(origtime))
curiono.saveh5(str(dataname))
simparams['Pulselength'] = ibaud*ts
sfile = str(newpath/'startfile.h5')
iono_orig.saveh5(sfile)
simparams['startfile'] = sfile
makeconfigfile(str(newpath/'chem_test.yml'), [23465.], 'millstone', simparams)
def configfilesetup(testpath,npulses):
""" This will create the configureation file given the number of pulses for
the test. This will make it so that there will be 12 integration periods
for a given number of pulses.
Input
testpath - The location of the data.
npulses - The number of pulses.
"""
curloc = Path(__file__).resolve().parent
defcon = curloc.joinpath('statsbase.ini')
(sensdict, simparams) = readconfigfile(defcon)
tint = simparams['IPP']*npulses
ratio1 = tint/simparams['Tint']
simparams['Tint'] = ratio1 * simparams['Tint']
simparams['Fitinter'] = ratio1 * simparams['Fitinter']
simparams['TimeLim'] = ratio1 * simparams['TimeLim']
simparams['startfile'] = 'startfile.h5'
makeconfigfile(testpath.joinpath('stats.ini'),simparams['Beamlist'],sensdict['Name'],simparams)
def configfilesetup(testpath,npulses):
""" This will create the configureation file given the number of pulses for
the test. This will make it so that there will be 12 integration periods
for a given number of pulses.
Input
testpath - The location of the data.
npulses - The number of pulses.
"""
curloc = Path(__file__).resolve().parent
defcon = curloc.joinpath('statsbase.ini')
(sensdict,simparams) = readconfigfile(defcon)
tint = simparams['IPP']*npulses
ratio1 = tint/simparams['Tint']
simparams['Tint']=ratio1 * simparams['Tint']
simparams['Fitinter'] = ratio1 * simparams['Fitinter']
simparams['TimeLim'] = ratio1 * simparams['TimeLim']
simparams['startfile']='startfile.h5'
makeconfigfile(testpath.joinpath('stats.ini'),simparams['Beamlist'],sensdict['Name'],simparams)
def configfilesetup(testpath,npulses = 1400):
""" This will create the configureation file given the number of pulses for
the test. This will make it so that there will be 12 integration periods
for a given number of pulses.
Input
testpath - The location of the data.
npulses - The number of pulses.
"""
curloc = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
defcon = os.path.join(curloc,'statsbase.ini')
(sensdict,simparams) = readconfigfile(defcon)
tint = simparams['IPP']*npulses
ratio1 = tint/simparams['Tint']
simparams['Tint']=ratio1 * simparams['Tint']
simparams['Fitinter'] = ratio1 * simparams['Fitinter']
simparams['TimeLim'] = 3*tint
simparams['startfile']='startfile.h5'
makeconfigfile(os.path.join(testpath,'stats.ini'),simparams['Beamlist'],sensdict['Name'],simparams)
def configsetup(testpath):
"""This function will make a pickle file used to configure the simulation.
Inputs
testpath - A string for the path that this file will be saved."""
testpath=Path(testpath)
beamlist = [64094,64091,64088,64085,64082,64238,64286,64070,64061,64058,64055,64052,
64049,64046,64043,64067,64040,64037,64034] # list of beams in
radarname = 'pfisr'# name of radar for parameters can either be pfisr or risr
Tint=60.0 # integration time in seconds
time_lim = 4.0*Tint # simulation length in seconds
fitter_int = 60.0 # time interval between fitted params
# pulse = sp.ones(14)# pulse
rng_lims = [150,500]# limits of the range gates
IPP = .0087 #interpulse period in seconds
NNs = 28 # number of noise samples per pulse
NNp = 100 # number of noise pulses
simparams = {'IPP':IPP, #interpulse period
'TimeLim':time_lim, # length of simulation
'RangeLims':rng_lims, # range swath limit
# 'Pulse':pulse, # pulse shape
'Pulselength':280e-6,
'FitType' :'acf',
't_s': 20e-6,
'Pulsetype':'long', # type of pulse can be long or barker,
'Tint':Tint, #Integration time for each fitting
'Fitinter':fitter_int, # time interval between fitted params
'NNs': NNs,# number of noise samples per pulse
'NNp':NNp, # number of noise pulses
'dtype':sp.complex128, #type of numbers used for simulation
'ambupsamp':1, # up sampling factor for ambiguity function
'species':['O+','e-'], # type of ion species used in simulation
'numpoints':128, # number of points for each spectrum
'startfile': str(testpath/'startdata.h5')} # file used for starting points
# 'SUMRULE': sp.array([[-2,-3,-3,-4,-4,-5,-5,-6,-6,-7,-7,-8,-8,-9]
# ,[1,1,2,2,3,3,4,4,5,5,6,6,7,7]])}
fname = testpath/'PFISRExample'
makeconfigfile(str(fname.with_suffix('.ini')),beamlist,radarname,simparams)
def makefitdirectory(sridir,srifile,fitdir,simdir):
srifiles = [glob.glob(os.path.join(sridir,'*.dt{0}.h5'.format(i))) for i in range(3)]
if [] in srifiles:
srifiles.remove([])
srifilesnew = [[None]*len(srifiles)]*len(srifiles[0])
for ieln in range(len(srifiles[0])):
srifilesnew[ieln] =[i[ieln] for i in srifiles ]
# make iono conatainers out of the SRI data
(ionolag,ionosigs,simparams,sensdict) = SRIACF2iono(srifilesnew)
paramsiono,startiono = SRIparams2iono(srifile)
# Add diretories that are needed
mkdirlist = [fitdir,simdir]
mkdirlist.append( os.path.join(fitdir,'ACF'))
mkdirlist.append(os.path.join(fitdir,'Origparams'))
mkdirlist.append(os.path.join(simdir,'Origparams'))
for idir in mkdirlist:
if not os.path.isdir(idir):
os.mkdir(idir)
# Save ACFs
ionolag.saveh5(os.path.join(mkdirlist[-3],'00lags.h5'))
ionosigs.saveh5(os.path.join(mkdirlist[-3],'00sigs.h5'))
# Save fitted data
paramsiono.saveh5(os.path.join(mkdirlist[-2],'0 srifits.h5'))
paramsiono.saveh5(os.path.join(mkdirlist[-1],'0 srifits.h5'))
# Save start data
startiono.saveh5(os.path.join(mkdirlist[0],'startdata.h5'))
startiono.saveh5(os.path.join(mkdirlist[1],'startdata.h5'))
# Save ini files
makeconfigfile(os.path.join(mkdirlist[0],'sridata.ini'),simparams['Beamlist'],sensdict['Name'],simparams)
makeconfigfile(os.path.join(mkdirlist[1],'sridata.ini'),simparams['Beamlist'],sensdict['Name'],simparams)
def makeconfigfilebarker(testpath):
testpath = Path(testpath).expanduser()
beamlist = [64094,64091,64088,64085,64082,64238,64286,64070,64061,64058,64055,64052,
64049,64046,64043,64067,64040,64037,64034]
radarname = 'pfisr'
Tint = 4.0*60.0
time_lim = 3.0*Tint
pulse = GenBarker(7)
rng_lims = [75.0,250.0]
IPP = .0087
NNs = 28
NNp = 100
t_s=2e-5
Pulselength=len(pulse)*t_s
simparams = {'IPP':IPP,
'TimeLim':time_lim,
'RangeLims':rng_lims,
'Pulse':pulse,
'Pulsetype':'barker',
'Pulselength':Pulselength,
't_s':t_s,
'Tint':Tint,
'Fitinter':Tint,
'NNs': NNs,
'NNp':NNp,
'dtype':sp.complex128,
'ambupsamp':30,
'species':['O+','e-'],
'numpoints':128,
'FitType':'acf',
'startfile':str(testpath.joinpath('startdata.h5'))}
fn = testpath/'barkertest.yml'
makeconfigfile(fn,beamlist,radarname,simparams)
def configfilesetup(testpath, npulses, radar='PFISR'):
""" This will create the configureation file given the number of pulses for
the test. This will make it so that there will be 12 integration periods
for a given number of pulses.
Input
testpath - The location of the data.
npulses - The number of pulses.
"""
testpath = Path(testpath).expanduser()
curloc = Path(__file__).resolve().parent
if radar.lower() == 'pfisr':
defcon = curloc/'statsbase.ini'
elif radar.lower() == 'millstonez':
defcon = curloc/'statsbasemhz.yml'
(sensdict, simparams) = readconfigfile(defcon)
tint = simparams['IPP']*npulses
ratio1 = tint/simparams['Tint']
simparams['Tint'] = ratio1*simparams['Tint']
simparams['Fitinter'] = ratio1 * simparams['Fitinter']
simparams['TimeLim'] = 2*tint
simparams['fitmode'] = 1
simparams['startfile'] = 'startfile.h5'
makeconfigfile(str(testpath/'stats.yml'), simparams['Beamlist'],
sensdict['Name'], simparams)
def configfilesetup(testpath, npulses, radar='PFISR'):
""" This will create the configureation file given the number of pulses for
the test. This will make it so that there will be 12 integration periods
for a given number of pulses.
Input
testpath - The location of the data.
npulses - The number of pulses.
"""
testpath = Path(testpath).expanduser()
curloc = Path(__file__).resolve().parent
if radar.lower() == 'pfisr':
defcon = curloc / 'statsbase.ini'
elif radar.lower() == 'millstonez':
defcon = curloc / 'statsbasemhz.yml'
(sensdict, simparams) = readconfigfile(defcon)
tint = simparams['IPP'] * npulses
ratio1 = tint / simparams['Tint']
simparams['Tint'] = ratio1 * simparams['Tint']
simparams['Fitinter'] = ratio1 * simparams['Fitinter']
simparams['TimeLim'] = 2 * tint
simparams['fitmode'] = 1
simparams['startfile'] = 'startfile.h5'
makeconfigfile(str(testpath / 'stats.yml'), simparams['Beamlist'],
sensdict['Name'], simparams)
def configsetup(testpath):
"""This function will make a pickle file used to configure the simulation.
Inputs
testpath - A string for the path that this file will be saved."""
testpath = Path(testpath)
beamlist = [
64094,
64091,
64088,
64085,
64082,
64238,
64286,
64070,
64061,
64058,
64055,
64052,
64049,
64046,
64043,
64067,
64040,
64037,
64034,
] # list of beams in
radarname = "pfisr" # name of radar for parameters can either be pfisr or risr
Tint = 60.0 # integration time in seconds
time_lim = 4.0 * Tint # simulation length in seconds
fitter_int = 60.0 # time interval between fitted params
# pulse = sp.ones(14)# pulse
rng_lims = [150, 500] # limits of the range gates
IPP = 0.0087 # interpulse period in seconds
NNs = 28 # number of noise samples per pulse
NNp = 100 # number of noise pulses
simparams = {
"IPP": IPP, # interpulse period
"TimeLim": time_lim, # length of simulation
"RangeLims": rng_lims, # range swath limit
# 'Pulse':pulse, # pulse shape
"Pulselength": 280e-6,
"FitType": "acf",
"t_s": 20e-6,
"Pulsetype": "long", # type of pulse can be long or barker,
"Tint": Tint, # Integration time for each fitting
"Fitinter": fitter_int, # time interval between fitted params
"NNs": NNs, # number of noise samples per pulse
"NNp": NNp, # number of noise pulses
"dtype": sp.complex128, # type of numbers used for simulation
"ambupsamp": 1, # up sampling factor for ambiguity function
"species": ["O+", "e-"], # type of ion species used in simulation
"numpoints": 128, # number of points for each spectrum
"startfile": str(testpath / "startdata.h5"),
} # file used for starting points
# 'SUMRULE': sp.array([[-2,-3,-3,-4,-4,-5,-5,-6,-6,-7,-7,-8,-8,-9]
# ,[1,1,2,2,3,3,4,4,5,5,6,6,7,7]])}
fname = testpath / "PFISRExample"
makeconfigfile(str(fname.with_suffix(".ini")), beamlist, radarname, simparams)
def configsetup(testpath):
"""This function will make a pickle file used to configure the simulation.
Inputs
testpath - A string for the path that this file will be saved."""
# list of beams that will give a line of points between 70 and 80 deg el with az of 20 deg
beamlist = [16626, 16987, 17348, 17709, 18070, 18431, 18792,
19153] #, 19514] # list of beams in
radarname = 'millstone' # name of radar for parameters can either be pfisr or risr
# pulse = sp.ones(14)# pulse
rng_lims = [150, 500] # limits of the range gates
IPP = 1e-2 #8.7e-3 #interpulse period in seconds
NNs = 28 # number of noise samples per pulse
NNp = 100 # number of noise pulses
b_rate = 100
intrate = 2.
Tint = intrate * b_rate * IPP # integration time in seconds
time_lim = len(
beamlist) / intrate * 4.0 * Tint # simulation length in seconds
fitter_int = Tint * len(
beamlist) / intrate # time interval between fitted params
simparams = {
'IPP':
IPP, #interpulse period
'TimeLim':
time_lim, # length of simulation
'RangeLims':
rng_lims, # range swath limit
# 'Pulse':pulse, # pulse shape
'Pulselength':
280e-6,
'FitType':
'acf',
't_s':
20e-6,
'Pulsetype':
'long', # type of pulse can be long or barker,
'Tint':
Tint, #Integration time for each fitting
'Fitinter':
fitter_int, # time interval between fitted params
'NNs':
NNs, # number of noise samples per pulse
'NNp':
NNp, # number of noise pulses
'dtype':
sp.complex128, #type of numbers used for simulation
'ambupsamp':
1, # up sampling factor for ambiguity function
'species': ['O+', 'e-'], # type of ion species used in simulation
'numpoints':
128, # number of points for each spectrum
'startfile':
str(testpath / 'startdata.h5'), # file used for starting points
'beamrate':
b_rate, # the number of pulses each beam will output until it moves
'outangles': [
sp.arange(i, i + intrate)
for i in sp.arange(0, len(beamlist), intrate)
]
}
# 'SUMRULE': sp.array([[-2,-3,-3,-4,-4,-5,-5,-6,-6,-7,-7,-8,-8,-9]
# ,[1,1,2,2,3,3,4,4,5,5,6,6,7,7]])}
fname = testpath / 'DishExample'
makeconfigfile(fname.with_suffix('.ini'), beamlist, radarname, simparams)
def SRIRAW2iono(flist,outdir,desrange=[100.,650.],inttime=5*60.,timelim=1200.):
"""
This will take a list of files and save out radar data
Inputs
flist - A list of files that will read and turned into the format
for the simulator.
outdir - The directory that that will hold the data in the format
from radardatasim. A directory will be created called RadarData
and the data will be saved there.
inttime - The number of seconds for the integration time.
"""
# make directory structure
if not os.path.isdir(outdir):
os.mkdir(outdir)
radardatadir = os.path.join(outdir,'Radardata')
if not os.path.isdir(radardatadir):
os.mkdir(radardatadir)
pulsetimes=[]
outfilelist = []
pulsenumbers = []
beam_list_all = []
noisetimes=[]
for ifile,filename in enumerate(flist):
outdict={}
fullfile = h5file(filename)
fullfiledict = fullfile.readWholeh5file()
if fullfiledict['/Site']['Name'] =='Resolute North':
radarname='risr'
Pcal=fullfiledict['/Rx']['Bandwidth']*fullfiledict['/Rx']['CalTemp']*v_Boltz
else:
radarname='pfisr'
Pcal=fullfiledict['/Rx']['Bandwidth']*fullfiledict['/Rx']['CalTemp']*v_Boltz
bco = fullfiledict['/S/Data']['Beamcodes']
beamlist = bco[0]
if ifile==0:
bstart = sp.zeros(len(beamlist),dtype=sp.int32)
time= fullfiledict['/Time']['UnixTime']
#
fullfile = h5file(filename)
fullfiledict = fullfile.readWholeh5file()
print('Main file being operated on: '+os.path.split(filename)[-1])
acflags = fullfiledict['/S/Data/Acf']['Lags'].flatten()
nlags = len(acflags)
lagdown = sp.arange(-sp.floor(float(nlags-1)/2.),0).astype(int)
lagup = sp.arange(1,sp.ceil(float(nlags+1)/2.)).astype(int)
# Get the raw samples
all_data = fullfiledict['/Raw11/Raw/Samples']['Data']
rawrange = fullfiledict['/Raw11/Raw/Samples']['Range'][0]*1e-3
rngkeep= sp.where(sp.logical_and(rawrange>=desrange[0],rawrange<desrange[1]))[0]
rngkeep = sp.hstack((lagdown+rngkeep[0],rngkeep,lagup+rngkeep[-1]))
rawrange=rawrange[rngkeep]
pulse_times = fullfiledict['/Raw11/Raw/RadacHeader']['RadacTime']
rawsamps = all_data[:,:,:,0]+1j*all_data[:,:,:,1]
rawsamps = rawsamps[:,:,rngkeep]
(nrecs, np_rec,nrng)=rawsamps.shape
all_beams_mat = fullfiledict['/Raw11/Raw/RadacHeader']['BeamCode']
#
pwidth = float(fullfiledict['/S/Data']['Pulsewidth'])
#
# # Pull in call and noise material because these will needed for fitting
beamcodes_cal = fullfiledict['/S/Cal']['Beamcodes']
cal_pint = fullfiledict['/S/Cal']['PulsesIntegrated']
caldata = fullfiledict['/S/Cal/Power']['Data']
noise_pint = fullfiledict['/S/Noise']['PulsesIntegrated']
noise_pwer = fullfiledict['/S/Noise/Power']['Data']
noise_data =fullfiledict['/S/Noise/Acf']['Data']
noise_acf = noise_data[:,:,:,:,0]+1j*noise_data[:,:,:,:,1]
noise_acf2 = sp.transpose(noise_acf,(0,1,3,2))
(nbeams,nnrng,nlags)=noise_acf2.shape[1:]
#
# use median to avoid large jumps. The difference between the mean and median estimator
# goes to zero after enough pulses have been originally integrated. From what Im seeing you're
# close to 64 pulses integrated you this will be off by only a 1/2 % of the true value.
n_pow_e = sp.nanmedian(noise_pwer,axis=-1)/noise_pint
c_pow_e = sp.nanmedian(caldata,axis=-1)/cal_pint
# Need to adjust for cal and noise
powmult = Pcal/(c_pow_e-n_pow_e)
noise_mult = sp.tile(powmult[:,:,sp.newaxis,sp.newaxis],noise_acf2.shape[2:])
npint_mat = sp.tile(noise_pint[:,:,sp.newaxis,sp.newaxis],noise_acf2.shape[2:])
noise_acf_out = noise_acf2*noise_mult/npint_mat
datamult = sp.zeros_like(rawsamps)
for irec,ibeamlist in enumerate(beamcodes_cal):
for ibpos,ibeam in enumerate(ibeamlist):
b_idx = sp.where(ibeam==all_beams_mat[irec])[0]
datamult[irec,b_idx]=sp.sqrt(powmult[irec,ibpos])
outraw= rawsamps*datamult
timep = pulse_times.reshape(nrecs*np_rec)
beamn = all_beams_mat.reshape(nrecs*np_rec)
beamnrs = sp.zeros_like(beamn)
pulsen = sp.ones(beamn.shape,dtype=sp.int32)
for ibn, ibeam in enumerate(beamlist):
curlocs = sp.where(beamn==ibeam)[0]
beamnrs[curlocs] = ibn
curtime = timep[curlocs]
cursort = sp.argsort(curtime)
curlocs_sort = curlocs[cursort]
pulsen[curlocs_sort]= sp.arange(len(curlocs)) +bstart[ibn]
bstart[ibn]=bstart[ibn]+len(curlocs)
outdict['RawData']=outraw.reshape(nrecs*np_rec,nrng)
outdict['RawDatanonoise'] = outdict['RawData']
outdict['AddedNoise'] = (1./sp.sqrt(2.))*(sp.randn(*outdict['RawData'].shape)+1j*sp.randn(*outdict['RawData'].shape))
outdict['NoiseDataACF'] = noise_acf_out
outdict['BeamsNoise'] = bco[0]
outdict['Beams']= beamnrs
outdict['Time'] =timep
outdict['NoiseTime'] = time
outdict['Pulses']= pulsen
#
fname = '{0:d} RawData.h5'.format(ifile)
newfn = os.path.join(radardatadir,fname)
outfilelist.append(newfn)
pulsetimes.append(timep)
pulsenumbers.append(pulsen)
noisetimes.append(time)
beam_list_all.append(beamnrs)
dict2h5(newfn,outdict)
# # save the information file
infodict = {'Files':outfilelist,'Time':pulsetimes,'Beams':beam_list_all,'Pulses':pulsenumbers,'NoiseTime':noisetimes,'Range':rawrange}
dict2h5(os.path.join(radardatadir,'INFO.h5'),infodict)
#
ts = fullfiledict['/Rx']['SampleTime']
sumrule = makesumrule('long',fullfiledict['/S/Data']['Pulsewidth'],ts)
# minrg = -sumrule[0].min()
# maxrg = len(rng_vec)-sumrule[1].max()
maxrg = len(rawrange)+sumrule[0].min()
minrg = sumrule[1].max()
rng_lims = [rawrange[minrg],rawrange[maxrg]]# limits of the range gates
IPP = .0087 #interpulse period in seconds
#
simparams = {'IPP':IPP, #interpulse period
'TimeLim':timelim, # length of simulation
'RangeLims':rng_lims, # range swath limit
# 'Pulse':pulse, # pulse shape
'Pulselength':pwidth,
'FitType' :'acf',
't_s': ts,
'Pulsetype':'long', # type of pulse can be long or barker,
'Tint':inttime, #Integration time for each fitting
'Fitinter':inttime, # time interval between fitted params
'NNs': nnrng+nlags-1,# number of noise samples per pulse
'NNp':100, # number of noise pulses
'dtype':sp.complex128, #type of numbers used for simulation
'ambupsamp':1, # up sampling factor for ambiguity function
'species':['O+','e-'], # type of ion species used in simulation
'numpoints':128,
'startfile':'startfile.h5'
} # number of points for each spectrum
makeconfigfile(os.path.join(outdir,'sriconfig1.ini'),beamlist,radarname,simparams)
