def __init__(self, *args, **kwargs):
"""
Takes a set of input observations and fits the orbital elements. These can then be used to
compute the position and error ellipse for the object on an arbitrary date.
Requires: observatories.dat and binEphem.423.
keyword arguments:
obsfile -- file containing observation data, either in MPC format or as
JD HH:MM:SS.SS +DD:MM:SS.SS ERROR OBSCODE or as
YYYY MM DD.DDDDD HH:MM:SS.SS +DD:MM:SS.SS ERROR OBSCODE
where the error is the astrometric error on each measurement in arcsec (default 0.2)
and OBSCODE is the observatory code in observatories.dat
The number of digits in each field is unrestricted, but ra and dec must not contain spaces.
The following options should be used only if obsfile is None. Then they must all be used. If obsfile
is supplied then these arguments are ignored.
dates -- list of observation dates, either in JD or YYYY MM DD.DDDDD format
ra -- list of RA in HH:MM:SS.SS format.
dec -- list of DEC in +DD:MM:SS.SS format
obscode -- list of observatory codes
err -- measurement error in arcsec
Methods:
get_elements() -- returns aei orbital elements and their errors
get_elements_abg() -- returns abg orbital elements and their errors
barycentric_distance() -- barycentric distance and error
perihelion() -- perihelion and error
aphelion() -- aphelion and error
cov_pq() -- covariance matrix for perihelion, aphelion
plotEllipse() -- generates an error ellipse for a given covariance matrix
predict_pos() -- predicted ra, dec, and error ellipse on a given date
ellipticalBody() -- returns an EllipticalBody object with these orbital parameters, suitable for use by pyEphem
"""
if 'file' in kwargs.keys(): # observations supplied in a file
obsfile = kwargs['file']
with open(obsfile, 'r') as fobs:
self.nobs = 0 # determine the number of observations
for line in fobs:
if line[0] != '#':
self.nobs += 1
fobs.seek(0) # rewind to the beginning
self.obsarray = orbfit.OBSERVATION_ARRAY(
self.nobs) # create empty array of observations
iobs = 0
for line in fobs:
if line[0] != '#':
thisobs = orbfit.OBSERVATION()
orbfit.scan_observation(line, thisobs)
orbfit.add_to_obsarray(self.obsarray, iobs, thisobs)
iobs += 1
if 'err' in kwargs.keys(
): # change: obserr need not be constant
obserr = kwargs['err']
elif len(args): # observations supplied in a Catalog object
self.nobs = len(args[0])
self.obsarray = orbfit.OBSERVATION_ARRAY(self.nobs)
for iobs, pt in enumerate(args[0]):
thisobs = orbfit.OBSERVATION()
if pt.err is None:
pt.err = 0.15 # This is to avoid silent crash.
if pt.obscode is None: pt.obscode = 807 # Ditto.
obsline = str(ephem.julian_date(pt.date)) + ' ' + str(
pt.ra) + ' ' + str(pt.dec) + ' ' + str(pt.err) + ' ' + str(
pt.obscode)
orbfit.scan_observation(obsline, thisobs)
orbfit.add_to_obsarray(self.obsarray, iobs, thisobs)
else: # observations specified in input lists
required_keys = ['dates', 'ra', 'dec', 'obscode']
for k in required_keys:
if k not in kwargs.keys():
raise KeyError('keyword ' + k + ' is missing')
obsdate = kwargs['dates']
ra = kwargs['ra']
dec = kwargs['dec']
obscode = kwargs['obscode']
self.nobs = len(obsdate)
if 'err' in kwargs.keys(): # change: obserr need not be constant
obserr = kwargs['err']
if not np.iterable(obserr):
obserr = [obserr for i in range(self.nobs)]
else:
obserr = [0.15 for i in range(self.nobs)
] # obervation astrometric error defaults to 0.15"
assert self.nobs == len(ra) and self.nobs == len(
dec) and self.nobs == len(obscode) and self.nobs == len(obserr)
self.obsarray = orbfit.OBSERVATION_ARRAY(
self.nobs) # create empty array of observations
for iobs in range(self.nobs): # fill the OBSERVATION_ARRAY
thisobs = orbfit.OBSERVATION()
obsline = str(ephem.julian_date(obsdate[iobs])) + ' ' + str(
ra[iobs]) + ' ' + str(dec[iobs]) + ' ' + str(
obserr[iobs]) + ' ' + str(obscode[iobs])
orbfit.scan_observation(obsline, thisobs)
orbfit.add_to_obsarray(self.obsarray, iobs, thisobs)
# At this point we have filled obsarray with the observations. Now fit the orbit.
# orbfit.set_ephem_file('/Users/gerdes/TNO/pyOrbfit/binEphem.430') # pick up the correct ephemeris and observatories file.
# orbfit.set_observatory_file('/Users/gerdes/TNO/pyOrbfit/observatories.dat') # Will need to handle pathnames more elegantly.
self.orbit_abg = orbfit.PBASIS()
self.orbit_xyz = orbfit.XVBASIS()
self.orbit_aei = orbfit.ORBIT()
self.cov_abg = orbfit.dmatrix(
1, 6, 1, 6
) # need to make this one globally visible since it's needed by predict_pos()
cov_xyz = orbfit.dmatrix(1, 6, 1, 6)
cov_aei = orbfit.dmatrix(1, 6, 1, 6)
derivs = orbfit.dmatrix(1, 6, 1, 6)
# fittype is 6 if normal fit, 5 if energy constraint was used.
self.fittype, self.chisq, self.ndof = orbfit.fit_observations(
self.obsarray, self.nobs, self.orbit_abg, self.cov_abg,
None) # abg orbit elements
# Transform the orbit basis and get the deriv. matrix
orbfit.pbasis_to_bary(self.orbit_abg, self.orbit_xyz, derivs)
orbfit.orbitElements(self.orbit_xyz,
self.orbit_aei) # aei orbit elements
# self.orbit_xyz.jd0 = orbfit.cvar.jd0 # time zeropoint
# covariance matrices
orbfit.covar_map(self.cov_abg, derivs, cov_xyz, 6,
6) # map the covariance matrix to xyz basis
orbfit.aei_derivs(
self.orbit_xyz,
derivs) # Get partial derivative matrix from xyz to aei
orbfit.covar_map(cov_xyz, derivs, cov_aei, 6,
6) # map covariance matrix from xyz to aei
# This is a hack to create matrices python can actually use. We have trouble wrapping double pointers.
c = orbfit.doubleArray(36)
orbfit.flatten_cov(self.cov_abg, 6, c)
self.covar_abg = np.array([c[i] for i in range(36)
]).reshape(6, 6) # a bona-fide numpy array.
c = orbfit.doubleArray(
36) # It's necessary to reallocate the space in memory
orbfit.flatten_cov(cov_xyz, 6, c)
self.covar_xyz = np.array([c[i] for i in range(36)]).reshape(6, 6)
c = orbfit.doubleArray(36)
orbfit.flatten_cov(cov_aei, 6, c)
self.covar_aei = np.array([c[i] for i in range(36)]).reshape(6, 6)
self.elements, self.elements_errs = self.get_elements()
self.jd0 = orbfit.cvar.jd0
self.lat0 = orbfit.cvar.lat0
self.lon0 = orbfit.cvar.lon0
self.xBary = orbfit.cvar.xBary
self.yBary = orbfit.cvar.yBary
self.zBary = orbfit.cvar.zBary
def __init__(self, *args, **kwargs):
"""
Takes a set of input observations and fits the orbital elements. These can then be used to
compute the position and error ellipse for the object on an arbitrary date.
Requires: observatories.dat and binEphem.423.
keyword arguments:
obsfile -- file containing observation data, either in MPC format or as
JD HH:MM:SS.SS +DD:MM:SS.SS ERROR OBSCODE or as
YYYY MM DD.DDDDD HH:MM:SS.SS +DD:MM:SS.SS ERROR OBSCODE
where the error is the astrometric error on each measurement in arcsec (default 0.2)
and OBSCODE is the observatory code in observatories.dat
The number of digits in each field is unrestricted, but ra and dec must not contain spaces.
The following options should be used only if obsfile is None. Then they must all be used. If obsfile
is supplied then these arguments are ignored.
dates -- list of observation dates, either in JD or YYYY MM DD.DDDDD format
ra -- list of RA in HH:MM:SS.SS format.
dec -- list of DEC in +DD:MM:SS.SS format
obscode -- list of observatory codes
err -- measurement error in arcsec
Methods:
get_elements() -- returns aei orbital elements and their errors
get_elements_abg() -- returns abg orbital elements and their errors
barycentric_distance() -- barycentric distance and error
perihelion() -- perihelion and error
aphelion() -- aphelion and error
cov_pq() -- covariance matrix for perihelion, aphelion
plotEllipse() -- generates an error ellipse for a given covariance matrix
predict_pos() -- predicted ra, dec, and error ellipse on a given date
ellipticalBody() -- returns an EllipticalBody object with these orbital parameters, suitable for use by pyEphem
"""
if "file" in kwargs.keys(): # observations supplied in a file
obsfile = kwargs["file"]
with open(obsfile, "r") as fobs:
self.nobs = 0 # determine the number of observations
for line in fobs:
if line[0] != "#":
self.nobs += 1
fobs.seek(0) # rewind to the beginning
self.obsarray = orbfit.OBSERVATION_ARRAY(self.nobs) # create empty array of observations
iobs = 0
for line in fobs:
if line[0] != "#":
thisobs = orbfit.OBSERVATION()
orbfit.scan_observation(line, thisobs)
orbfit.add_to_obsarray(self.obsarray, iobs, thisobs)
iobs += 1
elif len(args): # observations supplied in a Catalog object
self.nobs = len(args[0])
self.obsarray = orbfit.OBSERVATION_ARRAY(self.nobs)
for iobs, pt in enumerate(args[0]):
thisobs = orbfit.OBSERVATION()
if pt.err is None:
pt.err = 0.15 # This is to avoid silent crash.
if pt.obscode is None:
pt.obscode = 807 # Ditto.
obsline = (
str(ephem.julian_date(pt.date))
+ " "
+ str(pt.ra)
+ " "
+ str(pt.dec)
+ " "
+ str(pt.err)
+ " "
+ str(pt.obscode)
)
orbfit.scan_observation(obsline, thisobs)
orbfit.add_to_obsarray(self.obsarray, iobs, thisobs)
else: # observations specified in input lists
required_keys = ["dates", "ra", "dec", "obscode"]
for k in required_keys:
if k not in kwargs.keys():
raise KeyError("keyword " + k + " is missing")
obsdate = kwargs["dates"]
ra = kwargs["ra"]
dec = kwargs["dec"]
obscode = kwargs["obscode"]
self.nobs = len(obsdate)
if "err" in kwargs.keys(): # change: obserr need not be constant
obserr = kwargs["err"]
if not np.iterable(obserr):
obserr = [obserr for i in range(self.nobs)]
else:
obserr = [0.15 for i in range(self.nobs)] # obervation astrometric error defaults to 0.15"
assert (
self.nobs == len(ra)
and self.nobs == len(dec)
and self.nobs == len(obscode)
and self.nobs == len(obserr)
)
self.obsarray = orbfit.OBSERVATION_ARRAY(self.nobs) # create empty array of observations
for iobs in range(self.nobs): # fill the OBSERVATION_ARRAY
thisobs = orbfit.OBSERVATION()
obsline = (
str(ephem.julian_date(obsdate[iobs]))
+ " "
+ str(ra[iobs])
+ " "
+ str(dec[iobs])
+ " "
+ str(obserr[iobs])
+ " "
+ str(obscode[iobs])
)
orbfit.scan_observation(obsline, thisobs)
orbfit.add_to_obsarray(self.obsarray, iobs, thisobs)
# At this point we have filled obsarray with the observations. Now fit the orbit.
# orbfit.set_ephem_file('/Users/gerdes/TNO/pyOrbfit/binEphem.430') # pick up the correct ephemeris and observatories file.
# orbfit.set_observatory_file('/Users/gerdes/TNO/pyOrbfit/observatories.dat') # Will need to handle pathnames more elegantly.
self.orbit_abg = orbfit.PBASIS()
self.orbit_xyz = orbfit.XVBASIS()
self.orbit_aei = orbfit.ORBIT()
self.cov_abg = orbfit.dmatrix(
1, 6, 1, 6
) # need to make this one globally visible since it's needed by predict_pos()
cov_xyz = orbfit.dmatrix(1, 6, 1, 6)
cov_aei = orbfit.dmatrix(1, 6, 1, 6)
derivs = orbfit.dmatrix(1, 6, 1, 6)
# fittype is 6 if normal fit, 5 if energy constraint was used.
self.fittype, self.chisq, self.ndof = orbfit.fit_observations(
self.obsarray, self.nobs, self.orbit_abg, self.cov_abg, None
) # abg orbit elements
# Transform the orbit basis and get the deriv. matrix
orbfit.pbasis_to_bary(self.orbit_abg, self.orbit_xyz, derivs)
orbfit.orbitElements(self.orbit_xyz, self.orbit_aei) # aei orbit elements
# self.orbit_xyz.jd0 = orbfit.cvar.jd0 # time zeropoint
# covariance matrices
orbfit.covar_map(self.cov_abg, derivs, cov_xyz, 6, 6) # map the covariance matrix to xyz basis
orbfit.aei_derivs(self.orbit_xyz, derivs) # Get partial derivative matrix from xyz to aei
orbfit.covar_map(cov_xyz, derivs, cov_aei, 6, 6) # map covariance matrix from xyz to aei
# This is a hack to create matrices python can actually use. We have trouble wrapping double pointers.
c = orbfit.doubleArray(36)
orbfit.flatten_cov(self.cov_abg, 6, c)
self.covar_abg = np.array([c[i] for i in range(36)]).reshape(6, 6) # a bona-fide numpy array.
c = orbfit.doubleArray(36) # It's necessary to reallocate the space in memory
orbfit.flatten_cov(cov_xyz, 6, c)
self.covar_xyz = np.array([c[i] for i in range(36)]).reshape(6, 6)
c = orbfit.doubleArray(36)
orbfit.flatten_cov(cov_aei, 6, c)
self.covar_aei = np.array([c[i] for i in range(36)]).reshape(6, 6)
self.elements, self.elements_errs = self.get_elements()
self.jd0 = orbfit.cvar.jd0
self.lat0 = orbfit.cvar.lat0
self.lon0 = orbfit.cvar.lon0
self.xBary = orbfit.cvar.xBary
self.yBary = orbfit.cvar.yBary
self.zBary = orbfit.cvar.zBary
def orbfit_abg(abgfile):
with open(abgfile) as f:
lines = [line for line in f if line[0] != '#']
elem_abg = [float(e) for e in lines[0].split()]
cov_arr = np.array([[float(de) for de in lines[i].split()]
for i in range(1, 7)],
dtype=np.float64)
last = lines[7].split()
lat0 = float(last[0])
lon0 = float(last[1])
xBary = float(last[2])
yBary = float(last[3])
zBary = float(last[4])
jd0 = float(last[5])
abginfo = {
'elem': elem_abg,
'cov': cov_arr,
'lat0': lat0,
'lon0': lon0,
'xBary': xBary,
'yBary': yBary,
'zBary': zBary,
'jd0': jd0
}
jd0 = abginfo['jd0'] # zeropoint of time scale
# Create space for various useful matrices
cov_abg = orbfit.dmatrix(1, 6, 1, 6)
p_in = orbfit.PBASIS()
orbit_xyz = orbfit.XVBASIS()
orbit_aei = orbfit.ORBIT()
p_in.a = abginfo['elem'][0]
p_in.adot = abginfo['elem'][1]
p_in.b = abginfo['elem'][2]
p_in.bdot = abginfo['elem'][3]
p_in.g = abginfo['elem'][4]
p_in.gdot = abginfo['elem'][5]
# Here follows kludginess to put the covariance matrix into C double pointers
c = orbfit.doubleArray(36)
cc = abginfo['cov'].reshape(36, order='F')
for i in range(len(cc)):
c[i] = cc[i]
orbfit.unflatten_cov(c, 6, cov_abg)
abginfo['pbasis'] = p_in
abginfo['cov_abg'] = cov_abg
cov_xyz = orbfit.dmatrix(1, 6, 1, 6)
cov_aei = orbfit.dmatrix(1, 6, 1, 6)
derivs = orbfit.dmatrix(1, 6, 1, 6)
# Transform the orbit basis and get the deriv. matrix
orbfit.cvar.jd0 = abginfo['jd0']
orbfit.cvar.xBary = abginfo['xBary']
orbfit.cvar.yBary = abginfo['yBary']
orbfit.cvar.zBary = abginfo['zBary']
orbfit.cvar.lon0 = abginfo['lon0'] * np.pi / 180
orbfit.cvar.lat0 = abginfo['lat0'] * np.pi / 180
#CHANGE HERE
orbfit.pbasis_to_bary(p_in, orbit_xyz, derivs)
orbfit.orbitElements(orbit_xyz, orbit_aei) # aei orbit elements
abginfo['orbit_aei'] = orbit_aei
abginfo['cov_aei'] = cov_aei
abginfo['elems_aei'] = {
'a': orbit_aei.a,
'e': orbit_aei.e,
'i': orbit_aei.i,
'lan': orbit_aei.lan,
'aop': orbit_aei.aop,
'top': orbit_aei.T
}
return abginfo
def orbfit_abg(abgfile):
with open(abgfile) as f:
lines = [line for line in f if line[0] != "#"]
elem_abg = [float(e) for e in lines[0].split()]
cov_arr = np.array([[float(de) for de in lines[i].split()] for i in range(1, 7)], dtype=np.float64)
last = lines[7].split()
lat0 = float(last[0])
lon0 = float(last[1])
xBary = float(last[2])
yBary = float(last[3])
zBary = float(last[4])
jd0 = float(last[5])
abginfo = {
"elem": elem_abg,
"cov": cov_arr,
"lat0": lat0,
"lon0": lon0,
"xBary": xBary,
"yBary": yBary,
"zBary": zBary,
"jd0": jd0,
}
jd0 = abginfo["jd0"] # zeropoint of time scale
# Create space for various useful matrices
cov_abg = orbfit.dmatrix(1, 6, 1, 6)
p_in = orbfit.PBASIS()
orbit_xyz = orbfit.XVBASIS()
orbit_aei = orbfit.ORBIT()
p_in.a = abginfo["elem"][0]
p_in.adot = abginfo["elem"][1]
p_in.b = abginfo["elem"][2]
p_in.bdot = abginfo["elem"][3]
p_in.g = abginfo["elem"][4]
p_in.gdot = abginfo["elem"][5]
# Here follows kludginess to put the covariance matrix into C double pointers
c = orbfit.doubleArray(36)
cc = abginfo["cov"].reshape(36, order="F")
for i in range(len(cc)):
c[i] = cc[i]
orbfit.unflatten_cov(c, 6, cov_abg)
abginfo["pbasis"] = p_in
abginfo["cov_abg"] = cov_abg
cov_xyz = orbfit.dmatrix(1, 6, 1, 6)
cov_aei = orbfit.dmatrix(1, 6, 1, 6)
derivs = orbfit.dmatrix(1, 6, 1, 6)
# Transform the orbit basis and get the deriv. matrix
orbfit.cvar.jd0 = abginfo["jd0"]
orbfit.cvar.xBary = abginfo["xBary"]
orbfit.cvar.yBary = abginfo["yBary"]
orbfit.cvar.zBary = abginfo["zBary"]
orbfit.cvar.lon0 = abginfo["lon0"] * np.pi / 180
orbfit.cvar.lat0 = abginfo["lat0"] * np.pi / 180
orbfit.pbasis_to_bary(p_in, orbit_xyz, derivs)
orbfit.orbitElements(orbit_xyz, orbit_aei) # aei orbit elements
abginfo["orbit_aei"] = orbit_aei
abginfo["cov_aei"] = cov_aei
abginfo["elems_aei"] = {
"a": orbit_aei.a,
"e": orbit_aei.e,
"i": orbit_aei.i,
"lan": orbit_aei.lan,
"aop": orbit_aei.aop,
"top": orbit_aei.T,
}
return abginfo