如何在.dat文件中写入数据Python新行多列表卫星Orbi

Question

我创建了一个函数来生成和传播卫星轨道。现在，我想把我所有的数据保存在一个.dat文件中。我不知道我需要多少个for循环，也不知道该怎么做。在

我希望时间，纬度，经度，和高度都在一条线上，为每个传播步骤。在

数据代码：

myOrbitJ2000Time = [1085.0, 2170.0, 3255.0, 4340.1, 5425.1]

lat = [48.5, 26.5, -28.8, -48.1, 0.1]

lon = [-144.1, -50.4, -1.6, 91.5, 152.8]

alt = [264779.5, 262446.1, 319661.8, 355717.3, 306129.0]

所需的.dat文件输出：

J2000时间，纬度，经度，高度

^{pr2}$

完整代码：

import orbital
from orbital import earth, KeplerianElements, plot
import matplotlib.pyplot as plt
import numpy as np
from astropy import time
from astropy.time import TimeDelta, Time
from astropy import units as u
from astropy import coordinates as coord


#def orbitPropandcoordTrans(orbitPineapple_J2000time, _ecc, _inc, _raan, _arg_pe, _meananom, meanMotion):
def orbitPropandcoordTrans(propNum, orbitPineapple_J2000time, _ecc, _inc, _raan, _arg_pe, _meananom, meanMotion):
        '''
        Create original orbit and run for 100 propagations (in total one whole orbit)
        in order to get xyz and time for each propagation step.
        The end goal is to plot the lat, lon, & alt data to see if it matches ISS groundtrace.
        '''
    import orbital
    from orbital import earth, KeplerianElements, plot
    import matplotlib.pyplot as plt
    import numpy as np
    from astropy import time
    from astropy.time import TimeDelta, Time
    from astropy import units as u
    from astropy import coordinates as coord

    'Calculate Avg. Period from Mean Motion'
    _avgPeriod = 86400 / meanMotion
    #print('_avgPeriod', _avgPeriod)

    ######
    #propNum = int(_avgPeriod)

    'Generate Orbit'
    #orbitPineapple = KeplerianElements.with_period(5560, body=earth, e=0.0004525, i=(np.deg2rad(51.6414)), raan=(np.deg2rad(247.1662)))
    orbitPineapple = KeplerianElements.with_period(_avgPeriod, body=earth, e=_ecc, i=(np.deg2rad(_inc)), raan=(np.deg2rad(_raan)), arg_pe=(np.deg2rad(_arg_pe)), M0=(np.deg2rad(_meananom))) #ref_epoch=   
    #plot(orbitPineapple)
    #plt.show()
    #print('')
    #print('')

    'Propagate Orbit and retrieve xyz'
    myOrbitX = []         #X Coordinate for propagated orbit step
    myOrbitY = []         #Y Coordinate for propagated orbit step
    myOrbitZ = []         #Z Coordinate for propagated orbit step
    myOrbitTime = []      #Time for each propagated orbit step
    myOrbitJ2000Time = [] #J2000 times
    #propNum = 100        #Number of propagations and Mean Anomaly size (one orbit 2pi/propNum)

    for i in range(propNum):
        orbitPineapple.propagate_anomaly_by(M=(2.0*np.pi/propNum)) #Propagate the orbit by the Mean Anomaly
        myOrbitX.append(orbitPineapple.r.x)                        #x vals
        myOrbitY.append(orbitPineapple.r.y)                        #y vals
        myOrbitZ.append(orbitPineapple.r.z)                        #z vals
        myOrbitTime.append(orbitPineapple_J2000time)               #J2000 time vals
        myOrbitJ2000Time.append(orbitPineapple.t)

        #plot(orbitPineapple)
    #print('X:', 'Length:', len(myOrbitX))
    #print(myOrbitX)
    #print('Y:', 'Length:',len(myOrbitY))
    #print(myOrbitY)
    #print('Z:', 'Length:', len(myOrbitZ))
    #print(myOrbitZ)
    #print('J2000 Time:', 'Length:',len(myOrbitTime))
    #print(myOrbitTime)


    '''Because the myOrbitTime is only the time between each step to be the sum of itself plus
    all the previous times. And then I need to convert that time from seconds after J2000 to UTC.'''
    myT = [] #UTC time list

    for i in range(propNum):
        myT.append((Time(2000, format='jyear') + TimeDelta(myOrbitTime[i]*u.s)).iso) #Convert time from J2000 to UTC
    #print('UTC Time List Length:', len(myT))
    #print('UTC Times:', myT)

    '''Now I have xyz and time for each propagation step and need to convert the coordinates from
    ECI to Lat, Lon, & Alt'''
    now = []     #UTC time at each propagation step
    xyz =[]      #Xyz coordinates from OrbitalPy initial orbit propagation
    cartrep = [] #Cartesian Representation
    gcrs = []    #Geocentric Celestial Reference System/Geocentric Equatorial Inertial, the default coord system of OrbitalPy
    itrs =[]     #International Terrestrial Reference System coordinates
    lat = []     #Longitude of the location, for the default ellipsoid
    lon = []     #Longitude of the location, for the default ellipsoid
    alt = []     #Height of the location, for the default ellipsoid


    for i in range(propNum):
        xyz = (myOrbitX[i], myOrbitY[i], myOrbitZ[i])                   #Xyz coord for each prop. step
        now = time.Time(myT[i])                                         #UTC time at each propagation step
        cartrep = coord.CartesianRepresentation(*xyz, unit=u.m)         #Add units of [m] to xyz
        gcrs = coord.GCRS(cartrep, obstime=time.Time(myT[i]))           #Let AstroPy know xyz is in GCRS
        itrs = gcrs.transform_to(coord.ITRS(obstime=time.Time(myT[i]))) #Convert GCRS to ITRS
        loc = coord.EarthLocation(*itrs.cartesian.xyz)                  #Get lat/lon/height from ITRS
        lat.append(loc.lat.value)                                       #Create latitude list
        lon.append(loc.lon.value)                                       #Create longitude list
        alt.append(loc.height.value)           

    #print('Current Time:', now)
    #print('')
    #print('UTC Time:')
    #print(myT)
    print('myOrbitJ2000Time', myOrbitJ2000Time)
    print('')
    print('Lat:')
    print('')
    print(lat)
    print('')
    print('Lon:')
    print(lon)
    print('')
    print('Alt:')
    print(alt)

orbitPropandcoordTrans（5，-34963095，0.0073662，51.5946，154.8079，103.6176，257.3038，15.92610159）

Answer 1

最简单的方法可能是使用zip（）：

data = zip(myOrbitJ2000Time, lat, lon, alt)

所以“数据”将具有您想要序列化的格式。别忘了序列化您想要的头。在

Answer 2

为了回答您的一般性问题，您可以先创建Numpy数组，而不是定义一堆Python列表（这些列表的附加和处理速度都很慢，尤其是在您扩展分辨率时处理大量的值时）。初始化Numpy数组时，通常需要指定数组的大小，但在这种情况下，这很简单，因为您知道需要多少次传播。例如：

>>> orbitX = np.empty(propNum, dtype=float)

创建一个由propNum浮点值组成的空Numpy数组（这里的“empty”表示数组没有用任何值初始化这是创建一个新数组的最快方法，因为我们稍后将填充其中的所有值。在

然后在循环中，而不是使用orbitX.append(x)，而是在数组中分配与当前记号相对应的值：orbitX[i] = x。其他情况也一样。在

还有几种方法可以输出数据，但是使用Astropy^{}提供了很大的灵活性。可以创建包含所需列的表，例如：

^{pr2}$

拥有Table对象的好处是有大量的输出格式选项。E、 g.在Python提示符下：

>>> table
    J2000          lat            lon            alt
   float64       float64        float64        float64
      -                       -
1085.01128806  48.5487129749 -144.175054697 264779.500823
2170.02257613  26.5068122883 -50.3805485685 262446.085716
3255.03386419 -28.7915478311  -1.6090285674 319661.817451
4340.04515225 -48.0536526356  91.5416828221 355717.274021
5425.05644032 0.084422392655  152.811717713  306129.02576

要先输出到文件，您必须考虑如何格式化数据。已经有很多常见的数据格式可以考虑使用，但这取决于数据的用途以及谁将使用它（“.dat file”在文件格式方面没有任何含义；或者更确切地说，它可能意味着任何）。但在您的问题中，您指出您想要的是所谓的“逗号分隔值”（CSV），其中数据的格式是按列向下排列，行中的每个值都用逗号分隔。Table类可以很容易地输出CSV（以及任何变体）：

>>> import sys
>>> table.write(sys.stdout, format='ascii.csv')  # Note: I'm just using sys.stdout for demonstration purposes; normally you would give a filename
J2000,lat,lon,alt
1085.011288063746,48.54871297493748,-144.17505469691633,264779.5008225624
2170.022576127492,26.506812288280788,-50.38054856853237,262446.0857159357
3255.0338641912376,-28.79154783108773,-1.6090285674024463,319661.81745081506
4340.045152254984,-48.05365263557444,91.54168282208444,355717.2740210131
5425.05644031873,0.08442239265500713,152.81171771323176,306129.0257600865

不过，还有很多其他的选择。例如，如果希望数据在对齐列中格式良好，也可以这样做。你可以阅读更多关于它的here。（另外，我建议，如果您想要纯文本文件格式，可以尝试ascii.ecsv，它的优点是它输出额外的元数据，从而可以轻松地将其读回Astropy表中）：

>>> table.write(sys.stdout, format='ascii.ecsv')
# %ECSV 0.9
#  -
# datatype:
# - {name: J2000, datatype: float64}
# - {name: lat, datatype: float64}
# - {name: lon, datatype: float64}
# - {name: alt, datatype: float64}
# schema: astropy-2.0
J2000 lat lon alt
1085.01128806 48.5487129749 -144.175054697 264779.500823
2170.02257613 26.5068122883 -50.3805485685 262446.085716
3255.03386419 -28.7915478311 -1.6090285674 319661.817451
4340.04515225 -48.0536526356 91.5416828221 355717.274021
5425.05644032 0.084422392655 152.811717713 306129.02576

另一件不相关的事我会注意到，除了单个值之外，Astropy中的许多对象可以对整个数组进行操作，这通常会更有效，尤其是对于许多值。特别是，您有一个Python循环：

for i in range(propNum):
    xyz = (myOrbitX[i], myOrbitY[i], myOrbitZ[i])                   #Xyz coord for each prop. step
    now = time.Time(myT[i])                                         #UTC time at each propagation step
    cartrep = coord.CartesianRepresentation(*xyz, unit=u.m)         #Add units of [m] to xyz
    gcrs = coord.GCRS(cartrep, obstime=time.Time(myT[i]))           #Let AstroPy know xyz is in GCRS
    itrs = gcrs.transform_to(coord.ITRS(obstime=time.Time(myT[i]))) #Convert GCRS to ITRS
    loc = coord.EarthLocation(*itrs.cartesian.xyz)                  #Get lat/lon/height from ITRS
    lat.append(loc.lat.value)                                       #Create latitude list
    lon.append(loc.lon.value)                                       #Create longitude list
    alt.append(loc.height.value)

这可以完全重写，无需显式循环，而是将它们视为坐标的数组。例如：

>>> times = time.Time(myT)  # All the times, not just a single one
>>> cartrep = coord.CartesianRepresentation(orbitX, orbitY, orbitZ, unit=u.m)  # Again, an array of coordinates
>>> gcrs = coord.GCRS(cartrep, obstime=times)
>>> itrs = gcrs.transform_to(coord.ITRS(obstime=ts))
>>> loc = coord.EarthLocation(*itrs.cartesian.xyz)  # I'm not sure this is the most efficient way to do this but I'm not an expert on the coordinates package

用这个我们也可以得到所有的坐标。E、 g.：

>>> loc.lat
<Latitude [ 48.54871297, 26.50681229,-28.79154783,-48.05365264,
             0.08442239] deg>

一般来说，这是处理大量坐标值的一种更有效的方法。类似地，在转换原始代码中的myT时，可以创建一个单独的TimeDelta数组并将其添加到初始时间中，而不是在所有时间偏移上循环。在

不幸的是，我不是orbital软件包的专家，但它似乎不像人们希望的那样容易获得轨道上不同点的坐标。就像应该有的。在