rodluger

def get_cache_info(*args, **kwargs):
    import inspect
    from pathlib import Path

    # Wait until the DAG has been built
    snakemake.workflow.checkpoints.syw__dag.get()

    # Get all jobs from the DAG
    dag = None
    levels = inspect.stack()

rodluger

import pymc3 as pm
import pymc3_ext as pmx
import numpy as np
import starry
import theano.tensor as tt
from astropy import constants, units
import matplotlib.pyplot as plt


def get_stellar_inclination_prior(incstar):

rodluger

# Hack to allow importing `pymc3` without an internet connection
# This was fixed in https://github.com/dask/distributed/pull/3991
try:
    import distributed
except Exception as e:
    try:
        import socket

        getaddrinfo = socket.getaddrinfo
        socket.getaddrinfo = lambda *args: [

rodluger

rodluger

rodluger

"""
A very simple / slow / inefficient / unstable implementation of a Gaussian
process for stellar light curves. We sample lots of surface maps from a 
given distribution of spot sizes / locations / contrasts and compute the
empirical mean and covariance of the resulting distribution. In the limit
that our number of samples is infinite, this yields the meand and covariance
of the desired GP!
"""
import starry
import numpy as np

rodluger

import starry
import matplotlib.pyplot as plt
import numpy as np
from tqdm import tqdm

# Settings
starry.config.lazy = False
np.random.seed(12)

# Load a map of the earth

rodluger

rodluger

rodluger

Cleaning the vplanet repo

Most of what we need to know is here. First we download BFG and create the alias

alias bfg='java -jar bfg-1.13.0.jar'

Note that we need the latest version of the Java Runtime Environment installed.