The following script is for reading the text format catalog. Now UiO also provides a CSV catalog.
from pathlib import Path import pandas as pd # SPICE data tree path, to be changed to your SPICE data mirror data_path = "/archive/SOLAR-ORBITER/SPICE" # example for IAS computing servers def date_parser(string): try: return pd.Timestamp(string) except ValueError: return pd.NaT def read_uio_cat(): """ Read UiO text table SPICE FITS files catalog http://astro-sdc-db.uio.no/vol/spice/fits/spice_catalog.txt Return ------ pandas.DataFrame Table Example queries that can be done on the result: * `df[(df.LEVEL == "L2") & (df["DATE-BEG"] >= "2020-11-17") & (df["DATE-BEG"] < "2020-11-18") & (df.XPOSURE > 60.)]` * `df[(df.LEVEL == "L2") & (df.STUDYDES == "Standard dark for cruise phase")]` """ cat_file = Path(data_path) / "fits" / "spice_catalog.txt" if not cat_file.exists(): print(f'Error: Catalog file not available at {cat_file.as_posix()}') sys.exit(1) columns = list(pd.read_csv(cat_file, nrows=0).keys()) date_columns = ['DATE-BEG','DATE', 'TIMAQUTC'] df = pd.read_table(cat_file, skiprows=1, names=columns, parse_dates=date_columns, date_parser=date_parser, low_memory=False) return df
Then we can read the catalog and filter it:
cat = read_uio_cat() filtered_cat = cat[(cat['DATE-BEG'] > '2021-11-05') & (cat.LEVEL == 'L2')]
cat
then contains the full catalogue (as a pandas
dataframe) and filtered_cat
contains a catalogue in which rows have been filtered (in this particular case) by observation date and file level.
The catalogue or filtered catalogue can be exported, e.g. to a CSV table by cat.to_csv()
.