from nuwavdet import nuwavdet as nw


OBS_PATH = r'.//path_to_obs//nu<obsid><DET>01_cl.evt'
THRESH = (3, 2)

SAVE_BADPIX_PATH = r'.//out//badpix.fits'
SAVE_REGION_PATH = r'.//out//region.fits'
SAVE_WAVSUM_PATH = r'.//out//wavsum.fits'

METADATA_PATH = r'.//out//metadata.csv'
METADATA_FITS_PATH = r'.//out//metadata.fits'


if __name__ == '__main__':
    # PROCESS THE OBSERVATION WITH GIVEN THRESHOLD
    result, region, region_raw, wav_sum = nw.process(OBS_PATH, thresh=THRESH)

    # SAVE THE REGION BAD PIXEL FILES TO THE FITS FILE WITH NUPIPELINE
    # COMPATIBLE FORMAT AND HEADERS.
    region_raw.writeto(SAVE_BADPIX_PATH)

    # SAVE REGION MASK AS A FITS IMAGE
    nw.save_region(region, SAVE_REGION_PATH, overwrite=False)
    # Note that the Python script uses numpy masked array with
    # True (1) as as masked and False (0) as unmasked pixel.
    # nw.save_region transfers the numpy masked array to
    # conventional format with 1 for unmasked and 0 for masked pixel.
    # However, if mask is used in the Python you need to transfer it back with
    # numpy.logical_not(mask).

    # SAVE WAVSUM ARRAY AS A FITS IMAGE
    nw.fits.writeto(SAVE_WAVSUM_PATH, wav_sum, overwrite=False)

    # SAVE METADATA
    # WE SUGGEST SAVING ALL THE METADATA FOR SEVERAL OBSERVATIONS
    # IN ONE FILE.

    # CREATE CSV FILE TO SAVE DATA
    # IF FILE ALREADY EXISTS YOU SHOULD REMOVE THIS BLOCK FROM YOUR CODE
    table = {
        'obs_id': [], 'detector': [], 'ra': [], 'dec': [],
        'lon': [], 'lat': [], 't_start': [], 'exposure': [],
        'count_rate': [], 'remaining_area': [], 'cash_stat': [],
        'cash_stat_full': []
    }
    out_table = nw.DataFrame(table)
    out_table.to_csv(METADATA_PATH)

    # SAVE DATA TO CREATED CSV
    nw.DataFrame(result, index=[0]).to_csv(METADATA_PATH, mode='a', header=False)

    # TRANSFORM THE CSV TO FITS-TABLE
    nw.csv_to_table(METADATA_PATH, METADATA_FITS_PATH)