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):

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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

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 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

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

"""
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

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