def setup(self):
"""Setup function run before each test method to setup files needed
to run the test effectively
"""
self.format = True
self.ref_file = 'ref_f_sami2py-1.00.namelist'
self.model_path = generate_path(tag='test', lon=0, year=2012, day=211,
test=True)
if not os.path.exists(self.model_path):
os.makedirs(self.model_path)
self.filelist = ['glonf.dat', 'glatf.dat', 'zaltf.dat', 'denif.dat',
'dennf.dat', 'u4f.dat', 'vsif.dat', 'tif.dat',
'tef.dat', 'time.dat']
for filename in self.filelist:
open(os.path.join(fortran_dir, filename), 'w').close()
def setup(self):
"""Setup function run before each test method to setup files needed
to run the test effectively
"""
self.format = False
self.ref_file = 'ref_u_sami2py-1.00.namelist'
self.model_path = generate_path('test', 0, 2012, 211, True)
if not os.path.exists(self.model_path):
os.makedirs(self.model_path)
self.filelist = [
'glonu.dat', 'glatu.dat', 'zaltu.dat', 'deniu.dat', 'vsiu.dat',
'tiu.dat', 'teu.dat', 'time.dat'
]
for filename in self.filelist:
open(os.path.join(fortran_dir, filename), 'w').close()
def _generate_metadata(self, namelist):
"""Reads the namelist and generates MetaData based on Parameters
Parameters
-----------
namelist : (list)
variable namelist from SAMI2 model
Returns
-------
void
Model object modified in place
"""
import re
def find_float(name, ind):
"""regular expression search for float vals"""
return float(re.findall(r"\d*\.\d+|\d+", name)[ind])
def find_int(name, ind):
"""regular expression search for int vals"""
return int(re.findall(r"\d+", name)[ind])
self.MetaData['fmtout'] = ('.true.' in namelist[1])
self.MetaData['F10.7A'] = find_float(namelist[14], 0)
self.MetaData['F10.7'] = find_float(namelist[15], 2)
self.MetaData['ap'] = find_int(namelist[16], 0)
self.MetaData['Neutral Atmosphere Model'] = 'NRLMSISe-2000'
self.MetaData['EUV Model'] = 'EUVAC'
# Ions Used
nion1 = wind_model = find_int(namelist[20], 1) - 1
nion2 = wind_model = find_int(namelist[21], 1) - 1
ions = ['H+', 'O+', 'NO+', 'O2+', 'He+', 'N2+', 'N+']
self.MetaData['Ions Used'] = ', '.join(ions[nion1:nion2])
# Multipliers
neutral_scalars = re.findall(r"\d*\.\d+|\d+", namelist[28])
self.MetaData['H Multiplier'] = float(neutral_scalars[0])
self.MetaData['O Multiplier'] = float(neutral_scalars[1])
self.MetaData['NO Multiplier'] = float(neutral_scalars[2])
self.MetaData['O2 Multiplier'] = float(neutral_scalars[3])
self.MetaData['He Multiplier'] = float(neutral_scalars[4])
self.MetaData['N2 Multiplier'] = float(neutral_scalars[5])
self.MetaData['N Multiplier'] = float(neutral_scalars[6])
self.MetaData['T_exo Multiplier'] = find_float(namelist[33], 0)
self.MetaData['T_n Multiplier'] = find_float(namelist[29], 0)
self.MetaData['EUV Multiplier'] = find_float(namelist[34], 0)
self.MetaData['ExB Drift Multiplier'] = find_float(namelist[24], 1)
self.MetaData['Wind Multiplier'] = find_float(namelist[23], 1)
if '.true.' in namelist[10]:
self.MetaData['ExB model'] = 'Fejer-Scherliess'
else:
model_path = generate_path(self.tag, self.lon0, self.year,
self.day, self.test)
self.MetaData['ExB model'] = 'Fourier Series'
self.MetaData['Fourier Coeffs'] = np.loadtxt(path.join(model_path,
'exb.inp'))
wind_model = find_int(namelist[35], 0)
self.MetaData['Wind Model'] = ('HWM-{:02d}').format(wind_model)
# Model Geometry
self.MetaData['rmin'] = find_float(namelist[11], 0)
self.MetaData['rmax'] = find_float(namelist[12], 0)
self.MetaData['gams'] = find_int(namelist[26], 0)
self.MetaData['gamp'] = find_int(namelist[27], 0)
self.MetaData['altmin'] = find_float(namelist[13], 0)
# Model runtime
self.MetaData['dthr'] = find_float(namelist[5], 0)
self.MetaData['hrinit'] = find_float(namelist[22], 0)
self.MetaData['hrpr'] = find_float(namelist[6], 0)
self.MetaData['hrmax'] = find_float(namelist[3], 0)
self.MetaData['dt0'] = find_float(namelist[4], 0)
self.MetaData['maxstep'] = find_int(namelist[2], 0)
self.MetaData['denmin'] = find_float(namelist[30], 0)
def _load_model(self):
"""Loads model results
Returns
-------
void
Model object modified in place
"""
nf = 98
nz = 101
ni = 7
def return_fourier(x, coeffs):
"""
Returns a Fourier series up to NumF coefficients
"""
def cos_a(x, n):
"""simple cosine"""
return np.cos(n * np.pi * x / 12.0)
def sin_a(x, n):
"""simple sine"""
return np.sin(n * np.pi * x / 12.0)
NumF = int((len(coeffs) - 1)/2)
y = coeffs[0]
for i in range(1, NumF+1):
y = y + coeffs[2*i-1]*cos_a(x, i) + coeffs[2*i]*sin_a(x, i)
return y
model_path = generate_path(self.tag, self.lon0, self.year, self.day,
self.test)
# Get NameList
namelist_file = open(path.join(model_path, 'sami2py-1.00.namelist'))
self.namelist = namelist_file.readlines()
namelist_file.close()
self.MetaData = dict()
self._generate_metadata(self.namelist)
# Get times
time = np.loadtxt(path.join(model_path, 'time.dat'))
self.ut = time[:, 1] + time[:, 2] / 60 + time[:, 3] / 3600
self._calculate_slt()
nt = len(self.ut)
if self.MetaData['fmtout']:
# Get Location
glat = np.loadtxt(path.join(model_path, 'glatf.dat'))
glon = np.loadtxt(path.join(model_path, 'glonf.dat'))
zalt = np.loadtxt(path.join(model_path, 'zaltf.dat'))
# Get plasma values
deni = np.loadtxt(path.join(model_path, 'denif.dat'))
vsi = np.loadtxt(path.join(model_path, 'vsif.dat'))
ti = np.loadtxt(path.join(model_path, 'tif.dat'))
te = np.loadtxt(path.join(model_path, 'tef.dat'))
# get neutral values
if self.outn:
denn = np.loadtxt(path.join(model_path, 'dennf.dat'))
u4 = np.loadtxt(path.join(model_path, 'u4f.dat'))
else:
# Get Location
glat = get_unformatted_data(model_path, 'glat')
glon = get_unformatted_data(model_path, 'glon')
zalt = get_unformatted_data(model_path, 'zalt')
# Get plasma values
dim0 = nz * nf * ni + 2
dim1 = nt
deni = get_unformatted_data(model_path, 'deni',
dim=(dim0, dim1), reshape=True)
vsi = get_unformatted_data(model_path, 'vsi',
dim=(dim0, dim1), reshape=True)
ti = get_unformatted_data(model_path, 'ti',
dim=(dim0, dim1), reshape=True)
# Electron Temperatures have only one species
dim0 = nz * nf + 2
te = get_unformatted_data(model_path, 'te',
dim=(dim0, dim1), reshape=True)
if self.outn:
# Multiple neutral species
dim0 = nz * nf * ni + 2
denn = get_unformatted_data(model_path, 'denn',
dim=(dim0, dim1), reshape=True)
# Only one wind
dim0 = nz * nf + 2
u4 = get_unformatted_data(model_path, 'u4',
dim=(dim0, dim1), reshape=True)
glat = np.reshape(glat, (nz, nf), order="F")
glon = np.reshape(glon, (nz, nf), order="F")
zalt = np.reshape(zalt, (nz, nf), order="F")
deni = np.reshape(deni, (nz, nf, ni, nt), order="F")
vsi = np.reshape(vsi, (nz, nf, ni, nt), order="F")
ti = np.reshape(ti, (nz, nf, ni, nt), order="F")
te = np.reshape(te, (nz, nf, nt), order="F")
self.data = xr.Dataset({'deni': (['z', 'f', 'ion', 'ut'], deni),
'vsi': (['z', 'f', 'ion', 'ut'], vsi),
'ti': (['z', 'f', 'ion', 'ut'], ti),
'te': (['z', 'f', 'ut'], te),
'slt': (['ut'], self.slt)},
coords={'glat': (['z', 'f'], glat),
'glon': (['z', 'f'], glon),
'zalt': (['z', 'f'], zalt),
'ut': self.ut})
if self.outn:
denn = np.reshape(denn, (nz, nf, ni, nt), order="F")
self.data['denn'] = (('z', 'f', 'ion', 'ut'), denn)
u4 = np.reshape(u4, (nz, nf, nt), order="F")
self.data['u4'] = (('z', 'f', 'ut'), u4)
# Add drifts
if self.MetaData['ExB model'] == 'Fourier Series':
self.data['ExB'] = return_fourier(self.data['slt'],
self.MetaData['Fourier Coeffs'])
def _load_model(self):
"""Loads model results
Returns
-------
void
Model object modified in place
"""
nf = 98
nz = 101
ni = 7
model_path = generate_path(self.tag, self.lon0, self.year, self.day,
self.test)
# Get NameList
namelist_file = open(path.join(model_path, 'sami2py-1.00.namelist'))
self.namelist = namelist_file.readlines()
namelist_file.close()
self.MetaData = dict()
self._generate_metadata(self.namelist)
# Get times
time = np.loadtxt(path.join(model_path, 'time.dat'))
self.ut = time[:, 1] + time[:, 2] / 60 + time[:, 3] / 3600
self._calculate_slt()
nt = len(self.ut)
if self.MetaData['fmtout']:
# Get Location
glat = np.loadtxt(path.join(model_path, 'glatf.dat'))
glon = np.loadtxt(path.join(model_path, 'glonf.dat'))
zalt = np.loadtxt(path.join(model_path, 'zaltf.dat'))
# Get plasma values
deni = np.loadtxt(path.join(model_path, 'denif.dat'))
vsi = np.loadtxt(path.join(model_path, 'vsif.dat'))
ti = np.loadtxt(path.join(model_path, 'tif.dat'))
te = np.loadtxt(path.join(model_path, 'tef.dat'))
# get neutral values
if self.outn:
denn = np.loadtxt(path.join(model_path, 'dennf.dat'))
u4 = np.loadtxt(path.join(model_path, 'u4f.dat'))
else:
# Get Location
glat = get_unformatted_data(model_path, 'glat')
glon = get_unformatted_data(model_path, 'glon')
zalt = get_unformatted_data(model_path, 'zalt')
# Get plasma values
dim0 = nz * nf * ni + 2
dim1 = nt
deni = get_unformatted_data(model_path,
'deni',
dim=(dim0, dim1),
reshape=True)
vsi = get_unformatted_data(model_path,
'vsi',
dim=(dim0, dim1),
reshape=True)
ti = get_unformatted_data(model_path,
'ti',
dim=(dim0, dim1),
reshape=True)
# Electron Temperatures have only one species
dim0 = nz * nf + 2
te = get_unformatted_data(model_path,
'te',
dim=(dim0, dim1),
reshape=True)
if self.outn:
# Multiple neutral species
dim0 = nz * nf * ni + 2
denn = get_unformatted_data(model_path,
'denn',
dim=(dim0, dim1),
reshape=True)
# Only one wind
dim0 = nz * nf + 2
u4 = get_unformatted_data(model_path,
'u4',
dim=(dim0, dim1),
reshape=True)
glat = np.reshape(glat, (nz, nf), order="F")
glon = np.reshape(glon, (nz, nf), order="F")
zalt = np.reshape(zalt, (nz, nf), order="F")
deni = np.reshape(deni, (nz, nf, ni, nt), order="F")
vsi = np.reshape(vsi, (nz, nf, ni, nt), order="F")
ti = np.reshape(ti, (nz, nf, ni, nt), order="F")
te = np.reshape(te, (nz, nf, nt), order="F")
self.data = xr.Dataset(
{
'deni': (['z', 'f', 'ion', 'ut'], deni),
'vsi': (['z', 'f', 'ion', 'ut'], vsi),
'ti': (['z', 'f', 'ion', 'ut'], ti),
'te': (['z', 'f', 'ut'], te),
'slt': (['ut'], self.slt)
},
coords={
'glat': (['z', 'f'], glat),
'glon': (['z', 'f'], glon),
'zalt': (['z', 'f'], zalt),
'ut': self.ut
})
if self.outn:
denn = np.reshape(denn, (nz, nf, ni, nt), order="F")
self.data['denn'] = (('z', 'f', 'ion', 'ut'), denn)
u4 = np.reshape(u4, (nz, nf, nt), order="F")
self.data['u4'] = (('z', 'f', 'ut'), u4)