def normalize_rho(orbitfile, lat, lon, alt, rho, base_alt):
"""
Uses the MSIS empirical model to return the helium and total mass density in an array
Arguments:
orbitfile: the filename of the DE-2 orbit
lat : array of latitudes [deg]
long : array of longitudes [deg]
alt : array of altitudes above body surface [km]
rho : array of unnormalized number density values for helium (1/cm^3)
base_alt: the fixed altitude to normalize density value
Returns:
rho_matrix : a 2Xn matrix of normalized number densities at the fixed "base altitude" and the expected MSIS value
densites are first row - i.e. rho_matrix[0:all]
MSIS expected values are second row - i.e. rho_matrix[1:all]
"""
species = whatplot
rho_norm = np.zeros(len(rho))
rho_MSIS_fixed, rho_MSIS_vary = np.zeros(len(rho)), np.zeros(len(rho))
ratio = np.zeros(len(rho))
date = make_date(orbitfile)
for i in range(0, len(rho)):
# MSIS Point objects - pt1 = fixed alt, pt2 = variable alt
pt1 = Point(date, lat[i], lon[i], base_alt)
pt2 = Point(date, lat[i], lon[i], alt[i])
result1, result2 = pt1.run_msis(), pt2.run_msis(
) # call MSIS for these Point objects
rho_MSIS_fixed[i] = result1.nn[species] # particles/cm^3
rho_MSIS_vary[i] = result2.nn[species]
ratio[i] = rho_MSIS_fixed[i] / rho_MSIS_vary[i]
rho_norm[i] = rho[i] * ratio[i]
plt.subplot(211)
plt.title(filenames[j])
plt.plot(alt, rho_MSIS_fixed, label='MSIS rho fixed')
plt.plot(alt, rho_MSIS_vary, label='MSIS rho vary')
plt.plot(alt, rho, label='rho')
plt.plot(alt, rho_norm, label='rho norm')
plt.legend(loc=1)
plt.ylabel(whatplot + ' Density 1/cm^3')
plt.ticklabel_format(axis='y', style='sci', scilimits=(0, 0))
plt.grid()
plt.subplot(212)
plt.plot(alt, ratio)
plt.xlabel('Altitude')
plt.ylabel(r'Ratio MSIS $\rho(z_0))/ \rho(z)$')
plt.minorticks_on()
plt.grid()
plt.show()
rho_matrix = np.array([rho_norm, rho_MSIS_fixed])
return rho_matrix # return both so you can plot
def main2():
dn = datetime(2011, 3, 23, 9, 30)
lat = 0.
lon = -80.
alt = 250.
pt = Point(dn, lat, lon, alt)
pt.run_igrf()
pt.run_hwm93()
pt.run_msis()
pt.run_iri()
print pt
print pt.nn
print pt.Tn_msis
def pyglowinput(
latlonalt=[65.1367, -147.4472, 250.00],
dn_list=[datetime(2015, 3, 21, 8, 00),
datetime(2015, 3, 21, 20, 00)],
z=None):
if z is None:
z = sp.linspace(50., 1000., 200)
dn_diff = sp.diff(dn_list)
dn_diff_sec = dn_diff[-1].seconds
timelist = sp.array([calendar.timegm(i.timetuple()) for i in dn_list])
time_arr = sp.column_stack((timelist, sp.roll(timelist, -1)))
time_arr[-1, -1] = time_arr[-1, 0] + dn_diff_sec
v = []
coords = sp.column_stack((sp.zeros((len(z), 2), dtype=z.dtype), z))
all_spec = ['O+', 'NO+', 'O2+', 'H+', 'HE+']
Param_List = sp.zeros((len(z), len(dn_list), len(all_spec), 2))
for idn, dn in enumerate(dn_list):
for iz, zcur in enumerate(z):
latlonalt[2] = zcur
pt = Point(dn, *latlonalt)
pt.run_igrf()
pt.run_msis()
pt.run_iri()
# so the zonal pt.u and meriodinal winds pt.v will coorispond to x and y even though they are
# supposed to be east west and north south. Pyglow does not seem to have
# vertical winds.
v.append([pt.u, pt.v, 0])
for is1, ispec in enumerate(all_spec):
Param_List[iz, idn, is1, 0] = pt.ni[ispec] * 1e6
Param_List[iz, idn, :, 1] = pt.Ti
Param_List[iz, idn, -1, 0] = pt.ne * 1e6
Param_List[iz, idn, -1, 1] = pt.Te
Param_sum = Param_List[:, :, :, 0].sum(0).sum(0)
spec_keep = Param_sum > 0.
species = sp.array(all_spec)[spec_keep[:-1]].tolist()
species.append('e-')
Param_List[:, :] = Param_List[:, :, spec_keep]
Iono_out = IonoContainer(coords,
Param_List,
times=time_arr,
species=species)
return Iono_out
def pyglowinput(latlonalt=[65.1367, -147.4472, 250.00], dn_list=[datetime(2015, 3, 21, 8, 00), datetime(2015, 3, 21, 20, 00)], z=None):
if z is None:
z = sp.linspace(50., 1000., 200)
dn_diff = sp.diff(dn_list)
dn_diff_sec = dn_diff[-1].seconds
timelist = sp.array([calendar.timegm(i.timetuple()) for i in dn_list])
time_arr = sp.column_stack((timelist, sp.roll(timelist, -1)))
time_arr[-1, -1] = time_arr[-1, 0]+dn_diff_sec
v=[]
coords = sp.column_stack((sp.zeros((len(z), 2), dtype=z.dtype), z))
all_spec = ['O+', 'NO+', 'O2+', 'H+', 'HE+']
Param_List = sp.zeros((len(z), len(dn_list),len(all_spec),2))
for idn, dn in enumerate(dn_list):
for iz, zcur in enumerate(z):
latlonalt[2] = zcur
pt = Point(dn, *latlonalt)
pt.run_igrf()
pt.run_msis()
pt.run_iri()
# so the zonal pt.u and meriodinal winds pt.v will coorispond to x and y even though they are
# supposed to be east west and north south. Pyglow does not seem to have
# vertical winds.
v.append([pt.u, pt.v, 0])
for is1, ispec in enumerate(all_spec):
Param_List[iz, idn, is1, 0] = pt.ni[ispec]*1e6
Param_List[iz, idn, :, 1] = pt.Ti
Param_List[iz, idn, -1, 0] = pt.ne*1e6
Param_List[iz, idn, -1, 1] = pt.Te
Param_sum = Param_List[:, :, :, 0].sum(0).sum(0)
spec_keep = Param_sum > 0.
species = sp.array(all_spec)[spec_keep[:-1]].tolist()
species.append('e-')
Param_List[:, :] = Param_List[:, :, spec_keep]
Iono_out = IonoContainer(coords, Param_List, times = time_arr, species=species)
return Iono_out
Hp_mbar = np.zeros(len(m))
Hp_he = np.zeros(len(m))
Hp_n2 = np.zeros(len(m))
Hp_o1 = np.zeros(len(m))
k = 1.3806 * 10**(-23) #Boltzmann's constant
g0 = 9.81 #m/s^2
R = 6373 #Radius of earth in km
Av = 6.022141 * 10**23 #Avogadro's Constant
n = 0
rho = np.zeros(len(m))
#Iterate through altitudes in range m
for x in m:
pt = Point(dn, lat, lon, x)
result = pt.run_msis()
#Knudsen number estimate
n_dens_tot = result.nn['HE']+result.nn['N2']+result.nn['O2'] \
+result.nn['AR']+result.nn['H']+result.nn['O']+result.nn['N']# number density per cm^3
g = g0 * R**2 / (R + x)**2
m_dens1 = (result.nn['HE']*.004003/Av+result.nn['N2']*.0280134/Av\
+result.nn['O2']*.032/Av+result.nn['AR']*.039948/Av+result.nn['N']\
*.01401/Av+result.nn['H']*.001/Av+result.nn['O']*.016/Av)#kg/cm^3
Mbar[n] = m_dens1 * Av * 1000 / (n_dens_tot) #kg/kmol
Tn[n] = result.Tn_msis
#Follows form of kT/mg for pressure scale height
Hp_mbar[n] = k * Tn[n] / (Mbar[n] * g) * Av
Hp_he[n] = k * Tn[n] / (.004003 / Av * g) / 1000
# run_parallel()
# JMAX = 121
# DEN_I = np.zeros((JMAX))
dn = datetime(2015, 10, 23, 21, 0)
msis_alt = 335.
msis_lat = 0.
msis_lon = -40.
# dn = datetime(2011, 3, 23, 9, 30)
# msis_lat = 0.
# msis_lon = -80.
# msis_alt = 250.
# Criando o Point do PyGlow
# Criando o Point do PyGlow
print('criando ponto')
ponto = Point(dn, msis_lat, msis_lon, msis_alt)
print('rodando igrf')
ponto.run_igrf()
print('rodando hwm')
ponto.run_hwm93()
print(ponto.u, ponto.v)
print('rodando msis')
ponto.run_msis()
print(ponto.Tn_msis, np.float64(ponto.nn['O']), np.float64(ponto.nn['O2']), np.float64(ponto.nn['N2']))
# from pyglow.pyglow import update_indices
# update_indices([2012, 2016]) # grabs indices for 2012 and 2013
def add_msis(inst, glat_label='glat', glong_label='glong', alt_label='alt'):
"""
Uses MSIS model to obtain thermospheric values.
Uses pyglow module to run MSIS. Configured to use actual solar parameters to run
model.
Example
-------
# function added velow modifies the inst object upon every inst.load call
inst.custom.add(add_msis, 'modify', glat_label='custom_label')
Parameters
----------
inst : pysat.Instrument
Designed with pysat_sgp4 in mind
glat_label : string
label used in inst to identify WGS84 geodetic latitude (degrees)
glong_label : string
label used in inst to identify WGS84 geodetic longitude (degrees)
alt_label : string
label used in inst to identify WGS84 geodetic altitude (km, height above surface)
Returns
-------
inst
Input pysat.Instrument object modified to include MSIS values winds.
'Nn' total neutral density particles/cm^3
'Nn_N' Nitrogen number density (particles/cm^3)
'Nn_N2' N2 number density (particles/cm^3)
'Nn_O' Oxygen number density (particles/cm^3)
'Nn_O2' O2 number density (particles/cm^3)
'Tn_msis' Temperature from MSIS (Kelvin)
"""
import pyglow
from pyglow.pyglow import Point
msis_params = []
# print 'IRI Simulations'
for time, lat, lon, alt in zip(inst.data.index, inst[glat_label],
inst[glong_label], inst[alt_label]):
pt = Point(time, lat, lon, alt)
pt.run_msis()
msis = {}
total = 0
for key in pt.nn.keys():
total += pt.nn[key]
msis['Nn'] = total
msis['Nn_N'] = pt.nn['N']
msis['Nn_N2'] = pt.nn['N2']
msis['Nn_O'] = pt.nn['O']
msis['Nn_O2'] = pt.nn['O2']
msis['Tn_msis'] = pt.Tn_msis
msis_params.append(msis)
# print 'Complete.'
msis = pds.DataFrame(msis_params)
msis.index = inst.data.index
inst[msis.keys()] = msis
# metadata
inst.meta['Nn'] = {
'units': 'cm^-3',
'desc': 'Total neutral number particle density from MSIS.'
}
inst.meta['Nn_N'] = {
'units': 'cm^-3',
'desc': 'Total nitrogen number particle density from MSIS.'
}
inst.meta['Nn_N2'] = {
'units': 'cm^-3',
'desc': 'Total N2 number particle density from MSIS.'
}
inst.meta['Nn_O'] = {
'units': 'cm^-3',
'desc': 'Total oxygen number particle density from MSIS.'
}
inst.meta['Nn_O2'] = {
'units': 'cm^-3',
'desc': 'Total O2 number particle density from MSIS.'
}
inst.meta['Tn_msis'] = {
'units': 'K',
'desc': 'Neutral temperature from MSIS.'
}
return
Kn1 = np.zeros(len(m)) #Knudsen number for characteristic length
Kn2 = np.zeros(len(m))
Kn1At = np.zeros(len(m)) #Atmospheric knudsen number
Kn2At = np.zeros(len(m))
k = 1.3806 * 10**(-23) #Boltzmann's constant
g0 = 9.81 #m/s^2
R = 6373 #Radius of earth in km
Av = 6.022141 * 10**23 #Avogadro's Constant
n = 0
rho = np.zeros(len(m))
#Iterate through altitudes in range m
for x in m:
pt = Point(dn, lat, lon, x)
pt2 = Point(dn2, lat, lon, x)
result = pt.run_msis()
result2 = pt2.run_msis()
#Knudsen number estimate
n_dens_tot = result.nn['HE']+result.nn['N2']+result.nn['O2'] \
+result.nn['AR']+result.nn['H']+result.nn['O']+result.nn['N']# number density per cm^3
d_avg = (result.nn['HE']/n_dens_tot*260+result.nn['N2']/n_dens_tot*364\
+result.nn['O2']/n_dens_tot*346+result.nn['AR']/n_dens_tot*340)\
*10**(-12)+(result.nn['H']+result.nn['O']+result.nn['N'])/n_dens_tot*5.046*10**(-10)# average kinetic diameter of
# molecules in atmosphere. Note H and O are ignored due to no data on
# their kinetic diameters and the breakdown of the model with ions
# (hard sphere collisions of molecules)
lam = 1 / (math.sqrt(2) * math.pi * d_avg**2 * n_dens_tot * 10**(6))
# lam = 1/(pi*Nv*D^2*sqrt(2))
L = 1 #in meters. Chosen characteristic length
from pyglow.pyglow import Point from datetime import datetime dn = datetime(2011, 3, 23, 9, 30) lat = 0. lon = -80. alt = 250. pt = Point(dn, lat, lon, alt) print "Before running any models:" print pt pt.run_igrf() pt.run_hwm93() pt.run_msis() pt.run_iri() print "After running models:" print pt
date = datetime(2000, 1, 1, 0, 0) # (yr, month, day, hour, minute) - refer to datetime module online
latitude = 45
longitude = 90
altitude = 400
#--------------------------------------------------
# for now we will not deal with inputting our out geophys indices, so we let the Point obj do this for us.
# Now make the Point object!
new_pt = Point(date, latitude, longitude, altitude)
# from this new_pt Point object, we can run MSIS (or anything else in the Point class).
result = new_pt.run_msis() # result now contains the neutral temp, number densities (given in the run_msis fuction)
# and total number density for the specific variables given above
'''
check them out...
which neutral species do you what to look at?
Can be:
HE, O, N2, O2, AR, H, N, O_anomalous, or rho (total number density)
Or:
Tn_msis (neutral temperature [K])
'''
species = 'HE' # <---- change this to whatever species you want!
density = result.nn[species]
total_density = result.rho
elif i == 5:
long[k] = float(line.split(delimiter)[i])
elif i == 6:
LST[k] = float(line.split(delimiter)[i])
else:
continue
k += 1 # only increment k once per two lines
counter += 1
fread.close()
# Get MSIS temperature data
if add_MSIS:
date = make_date(filenames[j])
for i in range(0, len(temp)):
pt = Point(date, lat[i], long[i], alt[i])
result = pt.run_msis() # call MSIS for these Point objects
temp_MSIS[i] = result.Tn_msis
# plt the data....
print('Done reading files. Plotting...')
plt.title('DE2 Orbit 1614 - LT 19.0')
plt.scatter(lat, temp, marker='.', label='DE-2')
if add_MSIS:
plt.scatter(lat, temp_MSIS, marker='.', label='MSIS')
plt.ylabel('Neutral Temperature [K]')
plt.xlabel('Latitude [deg]')
plt.legend()
#plt.ylim([850, 1425])
#plt.xlim([40, -40])
dn = datetime(2010, 3, 23, 15, 30)
lat = 40.
lon = -80.
alt = 250.
pt = Point(dn, lat, lon, alt)
pt.run_hwm93()
pt.run_hwm07()
pt.run_hwm14()
pt.run_hwm(version=1993)
pt.run_hwm(version=2007)
pt.run_hwm(version=2014)
pt.run_hwm()
pt.run_msis()
pt.run_msis(version=2000)
pt.run_igrf()
pt.run_igrf(version=2011)
pt.run_iri()
pt.run_iri(version=2016)
pt.run_iri(version=2012)
try:
pt.run_iri(version=2020) # should fail
except ValueError as e:
print("Caught an exception: %s" % e)
