111 lines
5.7 KiB
Python
111 lines
5.7 KiB
Python
from astropy.time import Time
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from ..msise.nrlmsise00 import nrlmsise00
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class Coordinate(object):
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'''
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space-time coordinate class
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The coordinate of this class can be initialized using the following
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constructor method:
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x = coordinate(t,lat,lon,alt)
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Once initialized, each class instance defines the following class
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attributes:
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t : time, default in UTC
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lat : latitude, default in degrees
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lon : longitude, default in degrees
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alt : altitude, default in km
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Each class instance provides the following methods:
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nrlmsise00() : Estimate the atmosphere parameters at a specific coordinate using the nrlmsise00 model
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'''
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def __init__(self,t,lat,lon,alt):
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self.t = t
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self.lat = lat
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self.lon = lon
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self.alt = alt
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def __repr__(self):
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return 't = {:s} UTC\nlat = {:f} deg\nlon = {:f} deg\nalt = {:f} km'.format(self.t,self.lat,self.lon,self.alt)
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def nrlmsise00(self,sw_obs_pre,omode='Oxygen',aphmode='NoAph'):
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'''
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Estimate the atmosphere parameters at a specific coordinate(time and location) using the nrlmsise00 model.
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Usage:
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para_input,para_output = st.nrlmsis00_data(sw_obs_pre,[omode,aphmode])
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Inputs:
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st -> [Coordinate class instance] It can be initialized by defining a specific set of time and location
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sw_obs_pre -> [2d str array] space weather data
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omode -> [str, optional, default = 'Oxygen'] If 'Oxygen', Anomalous Oxygen density will be included. If 'NoOxygen', Anomalous Oxygen density will be excluded.
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aphmode -> [str, optional, default = 'NoAph'] If NoAph', 3-hour geomagnetic index will not be used. If Aph', 3h geomagnetic index will be used.
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Outputs:
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para_input -> [dictionary] parameters for time, location, solar radiation index, and geomagnetic index
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para_output -> [dictionary] parameters for atmospheric density and temperature
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Examples:
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>>> from pyatmos.msise import download_sw,read_sw
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>>> from pyatmos.atmosclasses import Coordinate
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>>> # Download or update the space weather file from www.celestrak.com
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>>> swfile = download_sw()
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>>> # Read the space weather data
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>>> sw_obs_pre = read_sw(swfile)
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>>>
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>>> # Test 1
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>>> # Set a specific time and location
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>>> t = '2015-10-05 03:00:00' # time(UTC)
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>>> lat,lon = 25,102 # latitude and longitude [degree]
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>>> alt = 70 # altitude [km]
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>>> # Initialize a coordinate instance by a space-time point
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>>> st = Coordinate(t,lat,lon,alt)
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>>>
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>>> para_input,para_output = st.nrlmsise00(sw_obs_pre)
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>>> print(para_input)
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{'doy': 278, 'year': 2015, 'sec': 10800.0, 'alt': 70, 'g_lat': 25, 'g_long': 102, 'lst': 9.8, 'f107A': 150, 'f107': 150, 'ap': 4, 'ap_a': array([4, 4, 4, 4, 4, 4, 4])}
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>>> print(para_output)
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>>> {'d': {'He': 9100292488300570.0, 'O': 0, 'N2': 1.3439413974205876e+21, 'O2': 3.52551376755781e+20, 'AR': 1.6044163757370681e+19, 'RHO': 8.225931818480755e-05, 'H': 0, 'N': 0, 'ANM O': 0}, 't': {'TINF': 1027.3184649, 'TG': 219.9649472491653}}
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>>>
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>>> # Test 2
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>>> t = '2004-07-08 10:30:50'
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>>> lat,lon,alt = -65,-120,100
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>>> st = Coordinate(t,lat,lon,alt)
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>>> para_input,para_output = st.nrlmsise00(sw_obs_pre)
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>>> print(para_input)
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{'doy': 190, 'year': 2004, 'sec': 37850.0, 'alt': 100, 'g_lat': -65, 'g_long': -120, 'lst': 2.5138888888888893, 'f107A': 109.0, 'f107': 79.3, 'ap': 2, 'ap_a': array([2. , 2. , 2. , 2. , 2. , 3.125, 4.625])}
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>>> print(para_output)
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{'d': {'He': 119477307274636.89, 'O': 4.1658304136233e+17, 'N2': 7.521248904485598e+18, 'O2': 1.7444969074975662e+18, 'AR': 7.739495767665198e+16, 'RHO': 4.584596293339505e-07, 'H': 22215754381448.5, 'N': 152814261016.3964, 'ANM O': 1.8278224834873257e-37}, 't': {'TINF': 1027.3184649, 'TG': 192.5868649143824}}
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>>>
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>>> # Test 3
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>>> t = '2010-02-15 12:18:37'
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>>> lat,lon,alt = 85,210,500
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>>> st = Coordinate(t,lat,lon,alt)
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>>> para_input,para_output = st.nrlmsise00(sw_obs_pre,'NoOxygen','Aph')
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>>> print(para_input)
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{'doy': 46, 'year': 2010, 'sec': 44317.0, 'alt': 500, 'g_lat': 85, 'g_long': 210, 'lst': 2.310277777777779, 'f107A': 83.4, 'f107': 89.4, 'ap': 14, 'ap_a': array([14. , 5. , 7. , 6. , 15. , 5.375, 4. ])}
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>>> print(para_output)
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{'d': {'He': 3314507585382.5425, 'O': 3855595951659.0874, 'N2': 19285497858.028534, 'O2': 395599656.3119481, 'AR': 146073.85956102316, 'RHO': 1.2650700238089615e-13, 'H': 171775437382.8238, 'N': 38359828672.39737, 'ANM O': 5345258193.554493}, 't': {'TINF': 776.3155804924045, 'TG': 776.3139192714452}}
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>>>
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>>> # Test 4
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>>> t = '2019-08-20 23:10:59'
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>>> lat,lon,alt = 3,5,900
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>>> st = Coordinate(t,lat,lon,alt)
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>>> para_input,para_output = st.nrlmsise00(sw_obs_pre,aphmode = 'Aph')
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>>> print(para_input)
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{'doy': 232, 'year': 2019, 'sec': 83459.0, 'alt': 900, 'g_lat': 3, 'g_long': 5, 'lst': 23.51638888888889, 'f107A': 67.4, 'f107': 67.7, 'ap': 4, 'ap_a': array([4. , 4. , 3. , 3. , 5. , 3.625, 3.5 ])}
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>> print(para_output)
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{'d': {'He': 74934329990.0412, 'O': 71368139.39199762, 'N2': 104.72048033793158, 'O2': 0.09392848471935447, 'AR': 1.3231114543012155e-07, 'RHO': 8.914971667362366e-16, 'H': 207405192640.34592, 'N': 3785341.821909535, 'ANM O': 1794317839.638502}, 't': {'TINF': 646.8157488121493, 'TG': 646.8157488108872}}
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'''
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para_input,para_output = nrlmsise00(Time(self.t),self.lat,self.lon,self.alt,sw_obs_pre,omode,aphmode)
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return para_input,para_output
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