getting a lot of asteroids - maybe 100, maybe all of them - rather than a few specific ones, without being a Pandas guru

[davidmikolas]

Goal is to post a script that answers https://space.stackexchange.com/questions/57469/positions-of-asteroids-in-heliocentric-ecliptic-x-y-z-coordinates

To start of slow, this script should give me the first 100 asteroids as an excerpt. Note, I only know python, not good with command line nor Pandas

After downloading text file from https://www.minorplanetcenter.net/ I run this:

fname = 'MPCORB.DAT.txt'

with open(fname, 'r') as infile:
    lines = infile.readlines()

i_start = [i for (i, line) in enumerate(lines) if '------------------' in line][0] + 1

lines = lines[i_start:]

for line in lines[:5]:
    print(line)
print('etc.')
print('len = ', len(lines))
print('')

lines = [line for line in lines if len(line.split()) >= 24]
print('keep only lines where len(line.split()) >= 24')
print('len = ', len(lines))
print('')

print('save to MPCORB.excerpt_100.DAT')
with open ('MPCORB.excerpt_100.DAT', 'w') as outfile:
    outfile.writelines(lines[:100])

The first four lines look the same as the four lines generated by running mpc_make_excerpt.py and then

python mpc_make_excerpt.py 00001 00002 00003 00004 > MPCORB.excerpt.DAT

in the documentation , but this way I can still get a million if I want.

Then I tried to make a list of asteroid objects in the excerpt using for row in minor_planets.items(): because I don't know how to use Pandas, but that fails:

import numpy as np
import matplotlib.pyplot as plt
from skyfield.api import load, Loader
from skyfield.constants import GM_SUN_Pitjeva_2005_km3_s2 as GM_SUN
from skyfield.data import mpc

load_de = Loader('~/Documents/fishing/SkyData') # avoid multiple copies of large files

ts = load.timescale()
eph = load_de('de421.bsp')

earth, sun, moon = [eph[x] for x in ('earth', 'sun', 'moon')]

with load.open('MPCORB.excerpt_100.DAT') as f:
    minor_planets = mpc.load_mpcorb_dataframe(f)

bad_orbits = minor_planets.semimajor_axis_au.isnull()

minor_planets = minor_planets[~bad_orbits]

print(minor_planets.shape[0], 'minor planets loaded')

asteroids = []
for row in minor_planets.items():  # doesn't work
    asteroid = sun + mpc.mpcorb_orbit(row, ts, GM_SUN)
    asteroids.append(asteroid)

The error message is:

Traceback (most recent call last):
  File "asteroidz_v00.py", line 26, in <module>
    asteroid = sun + mpc.mpcorb_orbit(row, ts, GM_SUN)
  File "/Users/davido/anaconda3/lib/python3.7/site-packages/skyfield/data/mpc.py", line 81, in mpcorb_orbit
    a = row.semimajor_axis_au
AttributeError: 'tuple' object has no attribute 'semimajor_axis_au'

[brandon-rhodes]

Whenever I need to remember how to iterate over dataframe rows, I read back through the answers to this Stack Overflow question—see if they work for you too:

https://stackoverflow.com/questions/16476924/how-to-iterate-over-rows-in-a-dataframe-in-pandas

[davidmikolas]

Yes, this works! for _, row in minor_planets.iterrows():

I'm not sure it will be fast when there's a million asteroids in my "excerpt" table, there's some warning: Though iterating row-by-row is not especially efficient since Series objects have to be created. but I'll do some more testing and reading, then I'll finish up and write an answer to that Stack Exchange question and mark your reply as an answer.

Thanks!