def process_thar_band(utdate, refdate, band, obsids, config):
from libs.products import ProductDB, PipelineStorage
igr_path = IGRINSPath(config, utdate)
igr_storage = PipelineStorage(igr_path)
thar_filenames = igr_path.get_filenames(band, obsids)
thar_basename = os.path.splitext(os.path.basename(thar_filenames[0]))[0]
thar_master_obsid = obsids[0]
flaton_db_name = igr_path.get_section_filename_base("PRIMARY_CALIB_PATH",
"flat_on.db",
)
flaton_db = ProductDB(flaton_db_name)
flaton_basename = flaton_db.query(band, thar_master_obsid)
from libs.storage_descriptions import FLATCENTROID_SOL_JSON_DESC
desc_list = [FLATCENTROID_SOL_JSON_DESC]
products = igr_storage.load(desc_list,
mastername=flaton_basename)
aperture_solution_products = products[FLATCENTROID_SOL_JSON_DESC]
# igrins_orders = {}
# igrins_orders["H"] = range(99, 122)
# igrins_orders["K"] = range(72, 92)
if 1:
bottomup_solutions = aperture_solution_products["bottom_up_solutions"]
orders = range(len(bottomup_solutions))
ap = Apertures(orders, bottomup_solutions)
if 1:
from libs.process_thar import ThAr
thar = ThAr(thar_filenames)
thar_products = thar.process_thar(ap)
if 1: # match order
from libs.process_thar import match_order_thar
from libs.master_calib import load_thar_ref_data
#ref_date = "20140316"
thar_ref_data = load_thar_ref_data(refdate, band)
new_orders = match_order_thar(thar_products, thar_ref_data)
print thar_ref_data["orders"]
print new_orders
ap = Apertures(new_orders, bottomup_solutions)
from libs.storage_descriptions import ONED_SPEC_JSON_DESC
thar_products[ONED_SPEC_JSON_DESC]["orders"] = new_orders
if 1:
hdu = pyfits.open(thar_filenames[0])[0]
igr_storage.store(thar_products,
mastername=thar_filenames[0],
masterhdu=hdu)
if 1:
# measure shift of thar lines from reference spectra
# load spec
from libs.process_thar import reidentify_ThAr_lines
thar_reidentified_products = reidentify_ThAr_lines(thar_products,
thar_ref_data)
igr_storage.store(thar_reidentified_products,
mastername=thar_filenames[0],
masterhdu=hdu)
if 1:
from libs.process_thar import (load_echelogram,
align_echellogram_thar,
check_thar_transorm,
get_wavelength_solutions)
ref_date = thar_ref_data["ref_date"]
echel = load_echelogram(ref_date, band)
thar_aligned_echell_products = \
align_echellogram_thar(thar_reidentified_products,
echel, band, ap)
# We do not save this product yet.
# igr_storage.store(thar_aligned_echell_products,
# mastername=thar_filenames[0],
# masterhdu=hdu)
fig_list = check_thar_transorm(thar_products,
thar_aligned_echell_products)
from libs.qa_helper import figlist_to_pngs
thar_figs = igr_path.get_section_filename_base("QA_PATH",
"thar",
"thar_"+thar_basename)
figlist_to_pngs(thar_figs, fig_list)
thar_wvl_sol = get_wavelength_solutions(thar_aligned_echell_products,
echel)
igr_storage.store(thar_wvl_sol,
mastername=thar_filenames[0],
masterhdu=hdu)
if 1: # make amp and order falt
from libs.storage_descriptions import ONED_SPEC_JSON_DESC
orders = thar_products[ONED_SPEC_JSON_DESC]["orders"]
order_map = ap.make_order_map()
#slitpos_map = ap.make_slitpos_map()
# load flat on products
#flat_on_params_name = flaton_path.get_secondary_path("flat_on_params")
#flaton_products = PipelineProducts.load(flat_on_params_name)
from libs.storage_descriptions import (FLAT_NORMED_DESC,
FLAT_MASK_DESC)
flaton_products = igr_storage.load([FLAT_NORMED_DESC, FLAT_MASK_DESC],
flaton_basename)
from libs.process_flat import make_order_flat, check_order_flat
order_flat_products = make_order_flat(flaton_products,
orders, order_map)
#fn = thar_path.get_secondary_path("orderflat")
#order_flat_products.save(fn, masterhdu=hdu)
igr_storage.store(order_flat_products,
mastername=flaton_basename,
masterhdu=hdu)
if 1:
fig_list = check_order_flat(order_flat_products)
from libs.qa_helper import figlist_to_pngs
orderflat_figs = igr_path.get_section_filename_base("QA_PATH",
"orderflat",
"orderflat_"+thar_basename)
figlist_to_pngs(orderflat_figs, fig_list)
if 1:
from libs.products import ProductDB
thar_db_name = igr_path.get_section_filename_base("PRIMARY_CALIB_PATH",
"thar.db",
)
thar_db = ProductDB(thar_db_name)
# os.path.join(igr_path.secondary_calib_path,
# "thar.db"))
thar_db.update(band, thar_basename)
def save_figures(helper, band, obsids):
### THIS NEEDS TO BE REFACTORED!
caldb = helper.get_caldb()
master_obsid = obsids[0]
orders = caldb.load_resource_for((band, master_obsid), "orders")["orders"]
thar_filenames = helper.get_filenames(band, obsids)
thar_basename = os.path.splitext(os.path.basename(thar_filenames[0]))[0]
thar_master_obsid = obsids[0]
if 1: # make amp and order falt
ap = get_simple_aperture(helper, band, obsids,
orders=orders)
# from libs.storage_descriptions import ONED_SPEC_JSON_DESC
#orders = thar_products[ONED_SPEC_JSON_DESC]["orders"]
order_map = ap.make_order_map()
#slitpos_map = ap.make_slitpos_map()
# load flat on products
#flat_on_params_name = flaton_path.get_secondary_path("flat_on_params")
#flaton_products = PipelineProducts.load(flat_on_params_name)
from libs.storage_descriptions import (FLAT_NORMED_DESC,
FLAT_MASK_DESC)
flaton_db_name = helper.igr_path.get_section_filename_base("PRIMARY_CALIB_PATH",
"flat_on.db",
)
flaton_db = ProductDB(flaton_db_name)
flaton_basename = flaton_db.query(band, thar_master_obsid)
flaton_products = helper.igr_storage.load([FLAT_NORMED_DESC,
FLAT_MASK_DESC],
flaton_basename)
from libs.process_flat import make_order_flat, check_order_flat
order_flat_products = make_order_flat(flaton_products,
orders, order_map)
#fn = thar_path.get_secondary_path("orderflat")
#order_flat_products.save(fn, masterhdu=hdu)
hdu = pyfits.open(thar_filenames[0])[0]
helper.igr_storage.store(order_flat_products,
mastername=flaton_basename,
masterhdu=hdu)
flat_mask = helper.igr_storage.load1(FLAT_MASK_DESC,
flaton_basename)
order_map2 = ap.make_order_map(mask_top_bottom=True)
bias_mask = flat_mask.data & (order_map2 > 0)
pp = PipelineProducts("")
from libs.storage_descriptions import BIAS_MASK_DESC
pp.add(BIAS_MASK_DESC,
PipelineImageBase([], bias_mask))
helper.igr_storage.store(pp,
mastername=flaton_basename,
masterhdu=hdu)
if 1:
fig_list = check_order_flat(order_flat_products)
from libs.qa_helper import figlist_to_pngs
orderflat_figs = helper.igr_path.get_section_filename_base("QA_PATH",
"orderflat",
"orderflat_"+thar_basename)
figlist_to_pngs(orderflat_figs, fig_list)