TIC

TIC#

Getting the data#

Tess Input Catalog. See the data at NASA.

https://tess.mit.edu/science/tess-input-catalogue/

Challenges with this data set#

  • The individual files are large, and so we want to use a chunked CSV reader.

  • The rows are wide, so the chunked reader cannot read too many rows at once.

  • The CSV files don’t have a header, so we need to provide the column names and type hints to the reader.

  • The numeric fields may be null, which is not directly supported by the int64 type in pandas, so we must use the nullable Int64 type.

You can download our reference files, if you find that helpful:

Example import#

import pandas as pd

import hats_import.pipeline as runner
from hats_import.catalog.arguments import ImportArguments
from hats_import.catalog.file_readers import CsvReader

type_frame = pd.read_csv("tic_types.csv")
type_map = dict(zip(type_frame["name"], type_frame["type"]))

args = ImportArguments(
    output_artifact_name="tic_1",
    input_path="/path/to/tic/",
    file_reader=CsvReader(
        header=None,
        column_names=type_frame["name"].values.tolist(),
        type_map=type_map,
        chunksize=250_000,
    ).read,
    ra_column="ra",
    dec_column="dec",
    sort_columns="ID",
    output_path="/path/to/catalogs/",
    use_schema_file="tic_schema.parquet",
)
runner.run(args)