mileslucas

from collections import OrderedDict
import multiprocessing
from pathlib import Path
import shutil
from typing import Union, Optional

from astropy.io import fits
import click
import pandas
from tqdm.auto import tqdm

mileslucas

"""
Simulate the SCExAO pupil
"""
from argparse import ArgumentParser

import hcipy as hp
import numpy as np
from astropy.io import fits

__all__ = ["generate_pupil"]

mileslucas

using Glob
using SAOImageDS9

function quickselect(glob_str; logscale=true)
  # parse out the directory, if any
  directory, globstr = splitdir(glob_str)
  filelist = collect(glob(globstr, directory))
  N = length(filelist)
  @info "Selecting through $N files"
  # connect to ds9 and set up

mileslucas

from astropy.io import fits
from astropy.time import Time
from astropy.coordinates import SkyCoord, EarthLocation
import astropy.units as u


subaru_loc = EarthLocation(lat=19.825504 * u.deg, lon=-155.4760187 * u.deg)

def get_pa_from_header(filename):
    with fits.open(filename) as hdul:

mileslucas

from astropy.io import fits
import numpy as np
from vampires_dpp.constants import SUBARU_LOC, PUPIL_OFFSET
import vampires_dpp.mueller_matrices as mm

def mueller_matrix_miles(filename):
    header = fits.getheader(filename)

    bs_ord = header["U_CAMERA"] == 1

mileslucas

from reproject import reproject_interp
from astropy.io import fits
from glob import glob
import numpy as np

# get the header for the file we want to reproject to
hdr = fits.getheader("NEP5281_r_0_new.fits")
# get the filenames as a list for each filter
rfiles = glob("*r*_new.fits")
ifiles = glob("*i*_new.fits")

mileslucas

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mileslucas

import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
tfd = tfp.distributions
tfk = tfp.positive_semidefinite_kernels

from Starfish.emulator import PCAGrid

class InputTransformedKernel(tfk.PositiveSemidefiniteKernel):