j-faria

1. Create a file ~/.pythonrc.py
2. Add

try:
    from IPython import get_ipython
    get_ipython().run_line_magic('load_ext', 'autoreload')
    get_ipython().run_line_magic('autoreload', '2')
except AttributeError:
 pass

j-faria

• http://jekyllthemes.org/themes/memoirs-jekyll-theme/
• http://jekyllthemes.org/themes/Minimal-Resume/

j-faria

import contextlib
import os

@contextlib.contextmanager
def working_directory(path):
    """
    A context manager which changes the working directory to the given
    path, and then changes it back to its previous value on exit.
    """
    prev_cwd = os.getcwd()

j-faria

Two small demonstration notebooks of how the Keplerian and transit curves respond to a change in the parameters.

j-faria

#!/bin/sh
#***********************************************************************
#*                    ESO Science Archive Facility
#*                        Programmatic Access
#*
#* Script:      eso_access_phase3.sh
#* Shell:       bash
#* Date:        15-Jul-2015
#* Contact:     archive@eso.org
#* Description: Script to query and download reduced data (Phase 3)

j-faria

# https://www.aanda.org/67-author-information/frequent-abbreviations

name_abbrv = {
    'Astronomy and Astrophysics': 'A&A',
    'Astronomy & Astrophysics': 'A&A',
    'Monthly Notices of the Royal Astronomical Society': 'MNRAS',
    'The Astrophysical Journal': 'ApJ',
    'The Astronomical Journal': 'AJ',
    'Publications of the Astronomical Society of the Pacific': 'PASP',
    'Annual Review of Astronomy and Astrophysics': 'ARA&A' ,

j-faria

sh downloadRequestNNNNNNscript.sh -X "-P 8 -L 1"

j-faria

from sympy import *
from astropy.constants import G
import astropy.units as u

G = G.to(u.m**3 / (u.solMass * u.s**2))

f_rhs = lambda P, K, e: (P * K**3 * (1 - e**2)**(3/2)) / (2 * pi * G.value)
f_lhs = lambda m1, m2, i: (m2**3 * sin(i)) / (m1 + m2)**2

# the earth

j-faria

from sympy import symbols, sin, nsolve

E = symbols('E')

def eccentric_anomaly(M, ecc, prec=15):
  return nsolve(E - e*sin(E) - M, M, prec=prec)


import mpmath as mp

j-faria

import numpy as np

###############################################################################
# the following is mostly a copy of the scipy implementation of
# binned_statistic and binned_statistic_dd
# but allowing for a weights parameter
from scipy._lib.six import callable, xrange
from scipy._lib._numpy_compat import suppress_warnings

## careful here!