def makeinputh5(Iono,basedir):
basedir = Path(basedir).expanduser()
Param_List = Iono.Param_List
dataloc = Iono.Cart_Coords
times = Iono.Time_Vector
velocity = Iono.Velocity
zlist,idx = sp.unique(dataloc[:,2],return_inverse=True)
siz = list(Param_List.shape[1:])
vsiz = list(velocity.shape[1:])
datalocsave = sp.column_stack((sp.zeros_like(zlist),sp.zeros_like(zlist),zlist))
outdata = sp.zeros([len(zlist)]+siz)
outvel = sp.zeros([len(zlist)]+vsiz)
for izn,iz in enumerate(zlist):
arr = sp.argwhere(idx==izn)
outdata[izn]=sp.mean(Param_List[arr],axis=0)
outvel[izn]=sp.mean(velocity[arr],axis=0)
Ionoout = IonoContainer(datalocsave,outdata,times,Iono.Sensor_loc,ver=0,
paramnames=Iono.Param_Names, species=Iono.Species,velocity=outvel)
ofn = basedir/'startdata.h5'
print('writing {}'.format(ofn))
Ionoout.saveh5(str(ofn))
def makeinputh5(Iono,basedir):
"""This will make a h5 file for the IonoContainer that can be used as starting
points for the fitter. The ionocontainer taken will be average over the x and y dimensions
of space to make an average value of the parameters for each altitude.
Inputs
Iono - An instance of the Ionocontainer class that will be averaged over so it can
be used for fitter starting points.
basdir - A string that holds the directory that the file will be saved to.
"""
# Get the parameters from the original data
Param_List = Iono.Param_List
dataloc = Iono.Cart_Coords
times = Iono.Time_Vector
velocity = Iono.Velocity
zlist,idx = sp.unique(dataloc[:,2],return_inverse=True)
siz = list(Param_List.shape[1:])
vsiz = list(velocity.shape[1:])
datalocsave = sp.column_stack((sp.zeros_like(zlist),sp.zeros_like(zlist),zlist))
outdata = sp.zeros([len(zlist)]+siz)
outvel = sp.zeros([len(zlist)]+vsiz)
# Do the averaging across space
for izn,iz in enumerate(zlist):
arr = sp.argwhere(idx==izn)
outdata[izn] = sp.mean(Param_List[arr],axis=0)
outvel[izn] = sp.mean(velocity[arr],axis=0)
Ionoout = IonoContainer(datalocsave,outdata,times,Iono.Sensor_loc,ver=0,
paramnames=Iono.Param_Names, species=Iono.Species,velocity=outvel)
Ionoout.saveh5(basedir/'startdata.h5')
def makedata(testpath):
""" This will make the input data for the test case. The data will have the
default set of parameters Ne=Ne=1e11 and Te=Ti=2000.
Inputs
testpath - Directory that will hold the data.
"""
finalpath = testpath.joinpath('Origparams')
if not finalpath.exists():
finalpath.mkdir()
data=SIMVALUES
z = sp.linspace(50.,1e3,50)
nz = len(z)
params = sp.tile(data[sp.newaxis,sp.newaxis,:,:],(nz,1,1,1))
coords = sp.column_stack((sp.ones(nz),sp.ones(nz),z))
species=['O+','e-']
times = sp.array([[0,1e3]])
vel = sp.zeros((nz,1,3))
Icont1 = IonoContainer(coordlist=coords,paramlist=params,times = times,sensor_loc = sp.zeros(3),ver =0,coordvecs =
['x','y','z'],paramnames=None,species=species,velocity=vel)
finalfile = finalpath.joinpath('0 stats.h5')
Icont1.saveh5(str(finalfile))
# set start temp to 1000 K.
Icont1.Param_List[:,:,:,1]=1e3
Icont1.saveh5(str(testpath.joinpath('startfile.h5')))
def makedata(testpath):
"""
This will make the input data for the test case. The data will have the
default set of parameters Ne=Ne=1e11 and Te=Ti=2000.
Inputs
testpath - Directory that will hold the data.
"""
finalpath = testpath.joinpath('Origparams')
if not finalpath.exists():
finalpath.mkdir()
data = SIMVALUES
z = sp.linspace(50., 1e3, 50)
nz = len(z)
params = sp.tile(data[sp.newaxis, sp.newaxis, :, :], (nz, 1, 1, 1))
coords = sp.column_stack((sp.ones(nz), sp.ones(nz), z))
species = ['O+', 'e-']
times = sp.array([[0, 1e9]])
vel = sp.zeros((nz, 1, 3))
Icont1 = IonoContainer(coordlist=coords,
paramlist=params,
times=times,
sensor_loc=sp.zeros(3),
ver=0,
coordvecs=['x', 'y', 'z'],
paramnames=None,
species=species,
velocity=vel)
finalfile = finalpath.joinpath('0 stats.h5')
Icont1.saveh5(str(finalfile))
# set start temp to 1000 K.
Icont1.Param_List[:, :, :, 1] = 1e3
Icont1.saveh5(str(testpath.joinpath('startfile.h5')))
def makeinputh5(Iono,basedir):
"""This will make a h5 file for the IonoContainer that can be used as starting
points for the fitter. The ionocontainer taken will be average over the x and y dimensions
of space to make an average value of the parameters for each altitude.
Inputs
Iono - An instance of the Ionocontainer class that will be averaged over so it can
be used for fitter starting points.
basdir - A string that holds the directory that the file will be saved to.
"""
# Get the parameters from the original data
Param_List = Iono.Param_List
dataloc = Iono.Cart_Coords
times = Iono.Time_Vector
velocity = Iono.Velocity
zlist,idx = sp.unique(dataloc[:,2],return_inverse=True)
siz = list(Param_List.shape[1:])
vsiz = list(velocity.shape[1:])
datalocsave = sp.column_stack((sp.zeros_like(zlist),sp.zeros_like(zlist),zlist))
outdata = sp.zeros([len(zlist)]+siz)
outvel = sp.zeros([len(zlist)]+vsiz)
# Do the averaging across space
for izn,iz in enumerate(zlist):
arr = sp.argwhere(idx==izn)
outdata[izn]=sp.mean(Param_List[arr],axis=0)
outvel[izn]=sp.mean(velocity[arr],axis=0)
Ionoout = IonoContainer(datalocsave,outdata,times,Iono.Sensor_loc,ver=0,
paramnames=Iono.Param_Names, species=Iono.Species,velocity=outvel)
Ionoout.saveh5(str(basedir/'startdata.h5'))
def makeinputh5(Iono, basedir):
basedir = Path(basedir).expanduser()
Param_List = Iono.Param_List
dataloc = Iono.Cart_Coords
times = Iono.Time_Vector
velocity = Iono.Velocity
zlist, idx = sp.unique(dataloc[:, 2], return_inverse=True)
siz = list(Param_List.shape[1:])
vsiz = list(velocity.shape[1:])
datalocsave = sp.column_stack(
(sp.zeros_like(zlist), sp.zeros_like(zlist), zlist))
outdata = sp.zeros([len(zlist)] + siz)
outvel = sp.zeros([len(zlist)] + vsiz)
for izn, iz in enumerate(zlist):
arr = sp.argwhere(idx == izn)
outdata[izn] = sp.mean(Param_List[arr], axis=0)
outvel[izn] = sp.mean(velocity[arr], axis=0)
Ionoout = IonoContainer(datalocsave,
outdata,
times,
Iono.Sensor_loc,
ver=0,
paramnames=Iono.Param_Names,
species=Iono.Species,
velocity=outvel)
ofn = basedir / 'startdata.h5'
print('writing {}'.format(ofn))
Ionoout.saveh5(str(ofn))
def makestartfile(datapath):
outdata = sp.array([[[[1e11,3e3],[1e11,3e3]]]])
datalocs = sp.array([[225.0,15.0,89.0]])
pnames = sp.array([['Ni','Ti'],['Ne','Te']])
species=['O2+','e-']
vel = sp.array([[[0,0,0]]])
Ionoout = IonoContainer(datalocs,outdata,sp.array([0]),ver=1,
paramnames=pnames, species=species,velocity=vel)
Ionoout.saveh5(os.path.join(datapath,'startdata.h5'))
def makedata(testpath, tint):
""" This will make the input data for the test case. The data will have cases
where there will be enhancements in Ne, Ti and Te in one location. Each
case will have 3 integration periods. The first 3 integration periods will
be the default set of parameters Ne=Ne=1e11 and Te=Ti=2000.
Inputs
testpath - Directory that will hold the data.
tint - The integration time in seconds.
"""
testpath = Path(testpath).expanduser()
finalpath = testpath.joinpath('Origparams')
if not finalpath.is_dir():
finalpath.mkdir()
data = sp.array([[1e11, 1100.], [1e11, 2100.]])
z = (50. + sp.arange(50) * 10.)
nz = len(z)
params = sp.tile(data[sp.newaxis, sp.newaxis], (nz, 1, 1, 1))
epnt = range(20, 22)
p2 = sp.tile(params, (1, 4, 1, 1))
#enhancement in Ne
p2[epnt, 1, :, 0] = 5e11
#enhancement in Ti
p2[epnt, 2, 0, 1] = 2200.
#enhancement in Te
p2[epnt, 3, 1, 1] = 4200.
coords = sp.column_stack((sp.ones(nz), sp.ones(nz), z))
species = ['O+', 'e-']
times = sp.array([[0, 1e3]])
times2 = sp.column_stack((sp.arange(0, 4), sp.arange(1, 5))) * 3 * tint
vel = sp.zeros((nz, 1, 3))
vel2 = sp.zeros((nz, 4, 3))
Icontstart = IonoContainer(coordlist=coords,
paramlist=params,
times=times,
sensor_loc=sp.zeros(3),
ver=0,
coordvecs=['x', 'y', 'z'],
paramnames=None,
species=species,
velocity=vel)
Icont1 = IonoContainer(coordlist=coords,
paramlist=p2,
times=times2,
sensor_loc=sp.zeros(3),
ver=0,
coordvecs=['x', 'y', 'z'],
paramnames=None,
species=species,
velocity=vel2)
finalfile = finalpath.joinpath('0 stats.h5')
Icont1.saveh5(str(finalfile))
Icontstart.saveh5(str(testpath.joinpath('startfile.h5')))
def makedata(testpath,tint):
""" This will make the input data for the test case. The data will have cases
where there will be enhancements in Ne, Ti and Te in one location. Each
case will have 3 integration periods. The first 3 integration periods will
be the default set of parameters Ne=Ne=1e11 and Te=Ti=2000.
Inputs
testpath - Directory that will hold the data.
tint - The integration time in seconds.
"""
testpath = Path(testpath).expanduser()
finalpath = testpath.joinpath('Origparams')
if not finalpath.is_dir():
finalpath.mkdir()
data = sp.array([[1e11,1100.], [1e11,2100.]])
z = (50.+sp.arange(50)*10.)
nz = len(z)
params = sp.tile(data[sp.newaxis, sp.newaxis],(nz, 1, 1, 1))
epnt = range(20,22)
p2 = sp.tile(params, (1, 4, 1, 1))
#enhancement in Ne
p2[epnt, 1, :, 0] = 5e11
#enhancement in Ti
p2[epnt,2,0,1] = 2200.
#enhancement in Te
p2[epnt,3,1,1] = 4200.
coords = sp.column_stack((sp.zeros(nz), sp.zeros(nz), z))
species=['O+', 'e-']
times = sp.array([[0, 1e3]])
times2 = sp.column_stack((sp.arange(0, 4), sp.arange(1, 5)))*3*tint
vel = sp.zeros((nz, 1, 3))
vel2 = sp.zeros((nz, 4, 3))
Icontstart = IonoContainer(coordlist=coords, paramlist=params, times=times,
sensor_loc=sp.zeros(3), ver=0, coordvecs=['x', 'y', 'z'],
paramnames=None, species=species, velocity=vel)
Icont1 = IonoContainer(coordlist=coords, paramlist=p2, times=times2,
sensor_loc=sp.zeros(3), ver=0, coordvecs=['x', 'y', 'z'],
paramnames=None, species=species, velocity=vel2)
finalfile = finalpath.joinpath('0 stats.h5')
Icont1.saveh5(str(finalfile))
Icontstart.saveh5(str(testpath.joinpath('startfile.h5')))
def makedata(testpath,tint):
""" This will make the input data for the test case. The data will have cases
where there will be enhancements in Ne, Ti and Te in one location. Each
case will have 3 integration periods. The first 3 integration periods will
be the default set of parameters Ne=Ne=1e11 and Te=Ti=2000.
Inputs
testpath - Directory that will hold the data.
tint - The integration time in seconds.
"""
finalpath = os.path.join(testpath,'Origparams')
if not os.path.isdir(finalpath):
os.mkdir(finalpath)
z = sp.linspace(50.,750,150)
nz = len(z)
Z_0 = 250.
H_0=30.
N_0=6.5e11
c1 = Chapmanfunc(z,H_0,Z_0,N_0)+5e10
z0=50.
T0=600.
Te,Ti = TempProfile(z,T0,z0)
params = sp.zeros((nz,1,2,2))
params[:,0,0,0] = c1
params[:,0,1,0] = c1
params[:,0,0,1] = Ti
params[:,0,1,1] = Te
coords = sp.column_stack((sp.zeros(nz),sp.zeros(nz),z))
species=['O+','e-']
times = sp.array([[0,1e3]])
times2 = sp.column_stack((sp.arange(0,1),sp.arange(1,2)))*3*tint
vel = sp.zeros((nz,1,3))
vel2 = sp.zeros((nz,4,3))
Icontstart = IonoContainer(coordlist=coords,paramlist=params,times = times,sensor_loc = sp.zeros(3),ver =0,coordvecs =
['x','y','z'],paramnames=None,species=species,velocity=vel)
Icont1 = IonoContainer(coordlist=coords,paramlist=params,times = times,sensor_loc = sp.zeros(3),ver =0,coordvecs =
['x','y','z'],paramnames=None,species=species,velocity=vel2)
finalfile = os.path.join(finalpath,'0 stats.h5')
Icont1.saveh5(finalfile)
Icontstart.saveh5(os.path.join(testpath,'startfile.h5'))
def run_sim(args_commd):
fitoutput = fitterone.fitdata(specfuncs.ISRSfitfunction,
fitterone.simparams['startfile'], fittimes=fitlist,
printlines=printlines)
(fitteddata, fittederror, funcevals, fittedcov) = fitoutput
fittederronly = sp.sqrt(fittederror)
paramnames = []
species = fitterone.simparams['species']
# Seperate Ti and put it in as an element of the ionocontainer.
Ti = fitteddata[:, :, 1]
nTi = fittederronly[:, :, 1]
nTiTe = fittedcov[:, :, 0, 1]
nTiNe = fittedcov[:, :, 0, 2]
nTiVi = fittedcov[:, :, 0, 3]
nTeNe = fittedcov[:, :, 1, 2]
nTeVi = fittedcov[:, :, 1, 3]
nNeVi = fittedcov[:, :, 2, 3]
cov_list = [nTiTe[:, :, sp.newaxis], nTiNe[:, :, sp.newaxis],
nTiVi[:, :, sp.newaxis], nTeNe[:, :, sp.newaxis],
nTeVi[:, :, sp.newaxis], nNeVi[:, :, sp.newaxis]]
cov_list_names = ['nTiTe', 'nTiNe', 'nTiVi', 'nTeNe', 'nTeVi','nNeVi']
paramlist = sp.concatenate([fitteddata, Ti[:, :, sp.newaxis], fittederronly,
nTi[:, :, sp.newaxis], funcevals[:, :, sp.newaxis]]
+ cov_list, axis=2)
ionoout = IonoContainer(Ionoin.Cart_Coords, paramlist.real, timevec, ver=newver,
coordvecs=Ionoin.Coord_Vecs, paramnames=paranamsf,
species=species)
ionoout.saveh5(str(outfile))
def readmattsdata(filename,datadir,outdir,keepspec=[0,1,2,6],angle=20.5):
d2r=sp.pi/180.
angr=d2r*angle
lsp=7
# Read in Data
inst = sio.loadmat(os.path.join(datadir,filename))
xg=inst['xg'][0,0]
x1v = xg['xp']# added to avoid gratting lobes.
x3v = xg['zp']
[x1mat,x3mat] = sp.meshgrid(x1v,x3v);
E = x1mat*sp.sin(angr)#x
N = x1mat*sp.cos(angr)#y
U = x3mat
lxs=x3mat.size
Time_Vector = sp.column_stack([inst['t'],inst['t']+15])
ns =inst['ns']
print('Loaded densities...');
ns= sp.reshape(ns,[lxs,lsp])
Ts =inst['Ts']
print('Loaded temperatures...')
Ts=sp.reshape(Ts,[lxs,lsp])
vs = inst['vsx1']
print('Loaded parallel velocities...\n');
# derive velocity from ExB
Ez,Ex=sp.gradient(-1*inst['Phi'])
dx=sp.diff(xg['x'].flatten())[0]
dEdx=Ex/dx
vx1=-1*dEdx/xg['Bmag']
# from looking at the data it seems that the velocity is off by a factor of
# 10.
vx1=vx1.flatten()/10.
vs=sp.reshape(vs,[lxs,lsp])
vs=sp.sum(ns[:,:(lsp-1)]*vs[:,:(lsp-1)],1)/ns[:,lsp-1]
v_e= vx1*sp.sin(angr)
v_n = vx1*sp.cos(angr)
v_u = vs
#change units of velocity to km/s
Velocity = sp.reshape(sp.column_stack([v_e,v_n,v_u]),[lxs,1,3])
# reduce the number of spcecies
# if islogical(keepspec)
# keepspec(end)=true;
# keepspecnum = sum(keepspec);
# elseif ~any(keepspec==numspec)
# keepspec = [keepspec(:),numspec];
# keepspecnum = length(keepspec);
# else
# keepspecnum = length(keepspec);
# end
nsout = sp.reshape(ns[:,keepspec],[lxs,1,len(keepspec)])
Tsout = sp.reshape(Ts[:,keepspec],[lxs,1,len(keepspec)])
# Put everything in to ionocontainer structure
Cart_Coords = sp.column_stack([E.flatten(),N.flatten(),U.flatten()])*1e-3
Param_List = sp.concatenate((sp.expand_dims(nsout,nsout.ndim),sp.expand_dims(Tsout,Tsout.ndim)),-1);
Species = sp.array(['O+','NO+','N2+','O2+','N+', 'H+','e-'])
Species = Species[keepspec]
fpart=os.path.splitext(filename)[0]
fout=os.path.join(outdir,fpart+'.h5')
ionoout=IonoContainer(Cart_Coords,Param_List,Time_Vector,ver=0,species=Species,velocity=Velocity)
ionoout.saveh5(fout)
def fitdata(basedir,configfile,optinputs):
""" This function will run the fitter on the estimated ACFs saved in h5 files.
Inputs:
basedir: A string for the directory that will hold all of the data for the simulation.
configfile: The configuration file for the simulation.
optinputs:A string that helps determine the what type of acfs will be fitted.
"""
# determine the input folders which can be ACFs from the full simulation
dirdict = {'fitting':('ACF', 'Fitted'), 'fittingmat':('ACFMat', 'FittedMat'),
'fittinginv':('ACFInv', 'FittedInv'), 'fittingmatinv':('ACFMatInv', 'FittedMatInv')}
dirio = dirdict[optinputs[0]]
inputdir = basedir/dirio[0]
outputdir = basedir/dirio[1]
fitlist = optinputs[1]
if len(optinputs) > 2:
exstr = optinputs[2]
printlines = optinputs[3]
else:
exstr = ''
dirlist = [str(i) for i in inputdir.glob('*lags{0}.h5'.format(exstr))]
dirlistsig = [str(i) for i in inputdir.glob('*sigs{0}.h5'.format(exstr))]
Ionoin = IonoContainer.readh5(dirlist[0])
if len(dirlistsig) == 0:
Ionoinsig = None
else:
Ionoinsig = IonoContainer.readh5(dirlistsig[0])
fitterone = Fitterionoconainer(Ionoin, Ionoinsig, configfile)
fitoutput = fitterone.fitdata(specfuncs.ISRSfitfunction,
fitterone.simparams['startfile'], fittimes=fitlist,
printlines=printlines)
#ipdb.set_trace()
(fitteddata, fittederror, funcevals, fittedcov) = fitoutput
if fitterone.simparams['Pulsetype'].lower() == 'barker':
paramlist = fitteddata
species = fitterone.simparams['species']
paramnames = ['Ne']
if not fittederror is None:
fittederronly = sp.sqrt(fittederror)
paramlist = sp.concatenate([fitteddata, fittederronly], axis=2)
paramnamese = ['n'+ip for ip in paramnames]
paranamsf = sp.array(paramnames+paramnamese)
else:
paranamsf = sp.array(paramnames)
else:
fittederronly = sp.sqrt(fittederror)
paramnames = []
species = fitterone.simparams['species']
# Seperate Ti and put it in as an element of the ionocontainer.
Ti = fitteddata[:, :, 1]
nTi = fittederronly[:, :, 1]
nTiTe = fittedcov[:, :, 0, 1]
nTiNe = fittedcov[:, :, 0, 2]
nTiVi = fittedcov[:, :, 0, 3]
nTeNe = fittedcov[:, :, 1, 2]
nTeVi = fittedcov[:, :, 1, 3]
nNeVi = fittedcov[:, :, 2, 3]
cov_list = [nTiTe[:, :, sp.newaxis], nTiNe[:, :, sp.newaxis],
nTiVi[:, :, sp.newaxis], nTeNe[:, :, sp.newaxis],
nTeVi[:, :, sp.newaxis], nNeVi[:, :, sp.newaxis]]
cov_list_names = ['nTiTe', 'nTiNe', 'nTiVi', 'nTeNe', 'nTeVi','nNeVi']
paramlist = sp.concatenate([fitteddata, Ti[:, :, sp.newaxis], fittederronly,
nTi[:, :, sp.newaxis], funcevals[:, :, sp.newaxis]]
+ cov_list, axis=2)
for isp in species[:-1]:
paramnames.append('Ni_'+isp)
paramnames.append('Ti_'+isp)
paramnames = paramnames+['Ne', 'Te', 'Vi', 'Nepow', 'Ti']
paramnamese = ['n'+ip for ip in paramnames]
paranamsf = sp.array(paramnames+paramnamese+['FuncEvals']+cov_list_names)
if fitlist is None:
timevec = Ionoin.Time_Vector
else:
if len(fitlist) == 0:
timevec = Ionoin.Time_Vector
else:
timevec = Ionoin.Time_Vector[fitlist]
# This requires
if set(Ionoin.Coord_Vecs) == {'x', 'y', 'z'}:
newver = 0
ionoout = IonoContainer(Ionoin.Cart_Coords, paramlist.real, timevec, ver=newver,
coordvecs=Ionoin.Coord_Vecs, paramnames=paranamsf,
species=species)
elif set(Ionoin.Coord_Vecs) == {'r', 'theta', 'phi'}:
newver = 1
ionoout = IonoContainer(Ionoin.Sphere_Coords, paramlist.real, timevec, ver=newver,
coordvecs=Ionoin.Coord_Vecs, paramnames=paranamsf,
species=species)
outfile = outputdir.joinpath('fitteddata{0}.h5'.format(exstr))
ionoout.saveh5(str(outfile))
