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from dalek import assemble_tardis_model
from dalek.base.model import SimpleTARDISUncertaintyModel, NormRedSpectrum, LogLikelihood
from dalek.base.base import BaseLikelihoodModel
from dalek.base.transform import uniform_transform
from astropy import units as u, constants as const
import os

base_dir = '/home/hpc/pr94se/di73qom/projects/tardis/dalek/test_artis_run/artis_fit'

artis_filename = os.path.join(base_dir, 'aaflux_057.dat')

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from astropy import coordinates as coord
from astropy import units as u, constants as const
import pandas as pd
cats = ['ut150625_g.h5', 'ut150625_r.h5', 'ut150625_u.h5']

gdata = pd.read_hdf(cats[0], 'data')
gdata = gdata[gdata.type == 1]
gcat = coord.SkyCoord(gdata.RA.values, gdata.Dec.values, unit=u.degree)

rdata = pd.read_hdf(cats[1], 'data')

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import argparse
from astropy.io import fits
from astropy import wcs
import os
from glob import glob
import pandas as pd


parser = argparse.ArgumentParser(description='Convert DECAM photometry to Tables')

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from astropy.table import Table
from astropy.io import fits
import pandas as pd
import numpy as np



class XShooterEchelle(object):
    coef_types = ['cen', 'edgup', 'edglo']

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from astropy.io import fits
from scipy import optimize
import numpy as np
from extract_spectral.trace import GaussianPolynomialTrace, ModelFrame2D, LogLikelihood, LinearLstSqExtraction

from DIRECT import solve
from astropy.modeling import models
#download from 
data = fits.getdata('IRCQ00467448.fits')
#data = fits.getdata('test_data/fors_many_stars.fits').T

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class IRCSEchelle(Model):
  inputs = ()
  outputs = ('polygon_array', )
  
  slit_width = Parameter(default=5.)
  slit_length = Parameter(default=10.)
  
  def evaluate(self, slit_width, slit_length, ...):
    parray = run_idl_code(slit_width, slit_length)
    return parray

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import requests
from bs4 import BeautifulSoup

base_url = 'http://henke.lbl.gov/cgi-bin/pert_cgi.pl'


def get_photo_absorption_cross_section(element_code, energy):
    data = requests.get(base_url, data=dict(
        Element=element_code, Energy=energy))
    bs = BeautifulSoup(data.text)

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class MultiSpecWCS(Model):


  def __init__(self, single_wcs=[list of 1d WCSs]):
    self.single_wcs = single_wcs
  
  def __call__(self, x, y):
    assert type(x) == int # we need to make sure that the user does not expect to interpolate between two adjacent spectra

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#!/usr/bin/env python
# -*- coding: utf-8 -*- 

import sys
import os
import shutil

pdflatex_bin = 'pdflatex'
bibtex_bin = 'bibtex'

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ERROR: AttributeError: 'Spectrum1DLookupWCS' object has no attribute '_param_dim' [astropy.modeling.core]
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-3-01a2fdaa6cd5> in <module>()
----> 1 specwcs.Spectrum1DLookupWCS(np.arange(3000, 6000) * u.Angstrom)

/Users/wkerzend/scripts/python/specutils/specutils/wcs/specwcs.py in __init__(self, lookup_table, unit, lookup_table_interpolation_kind)
     60             self.lookup_table_parameter = lookup_table * unit
     61         elif unit is None: # lookup_table is already unit'd
---> 62             self.lookup_table_parameter = lookup_table