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#!/usr/bin/env python
from __future__ import division, print_function

"""
This script generates a file to use for building authorea papers, and then runs
latex on them.

Requires python >= 2.6 (3.x should work, too)

The key assumptions are:

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from __future__ import division, print_function

"""
This script takes in the URL to the JSON version of an ADS private library, and outputs a bibtex file suitable for importing into ORCiD
"""

import json
import urllib2

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from __future__ import division

import os
import sys
import pty
import select
import subprocess


def find_dolphot(dirstocheck=None):

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from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import numpy as np
import sys
sys.path.insert(0, '/Users/bmorris/git/tmp/astropy')
import astropy
from astropy.time import Time
from astropy.coordinates import (SkyCoord, Longitude, Latitude, GCRS, ICRS,

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import schema_example  # this schema gets created *on import* here
import astropfile

astropfile.engage('parfile_example')  # runs all the tasks in the file

parset = astropfile.edit_params('parfile_example') # pops up a GUI/Web page that can edit the file
parset.engage() # actually runs the thing


parset = astropfile.edit_params(schema_example.fit_gaussian_to_echelle1)  # same as above, but creates a GUI with the defaults

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>>> import numpy as np
>>> from astropy import units as u

Create a quantity from a pre-existing sampled distribution. The MC direction is the first dimension.

>>> parr = np.random.poisson([1, 5, 30, 400],(1000, 4))
>>> distr = u.Distribution(parr, u.kpc)