view pipeline_sources.py @ 0:a35056104c2c draft default tip

planemo upload for repository https://github.com/esg-epfl-apc/tools-astro/tree/main/tools commit da42ae0d18f550dec7f6d7e29d297e7cf1909df2

import pandas as pd
import numpy as np
import re
import time
import io
import requests
from astroquery.simbad import Simbad
from astropy.coordinates import SkyCoord
from astropy import units as u

from query_tns_aux import parse_data, query_tns_main_name, query_tns_survey_name


def query_simbad(name):
    Simbad.add_votable_fields("otypes")

    table_ids = Simbad.query_objectids(name)
    table_obj = Simbad.query_object(name)

    dict_data = {}

    list_ids = None
    main_id = None
    otype_ = None
    ra = None
    dec = None
    if table_ids:
        df_ids = table_ids.to_pandas()
        df_ids.columns = df_ids.columns.str.upper()
        list_ids = list(df_ids["ID"].str.decode("utf-8").values)
    if table_obj:
        df_obj = table_obj.to_pandas()
        df_obj.columns = df_obj.columns.str.upper()
        main_id = df_obj["MAIN_ID"].values[0]
        otype_ = '|'.join(list(set(df_obj["OTYPES.OTYPE"].values)))
        str_ra_dec = str(df_obj["RA"].values[0]) + " " + str(df_obj["DEC"].values[0])
        ra_dec = SkyCoord(str_ra_dec, unit=(u.hourangle, u.deg))
        ra = ra_dec.ra.value
        dec = ra_dec.dec.value

    dict_data[name] = {"IDs": list_ids, "MAIN_ID": main_id, "OTYPES": otype_, "RA": ra, "DEC": dec, "DISCOVERY_TIME": None}

    return dict_data


def query_tns(name):
    dict_data = {}

    if ((name[0:3] == "at2") or (name[0:2] == "sn")):
        my_text = query_tns_main_name(name[2:])
    else:
        my_text = query_tns_survey_name(name)

    time.sleep(5)

    main_id, list_ids, list_otypes, ra, dec, discovery_time = parse_data(my_text)
    if ra and dec:
        str_ra_dec = ra + ":" + dec
        ra_dec = SkyCoord(str_ra_dec.replace(":", " "), unit=(u.hourangle, u.deg))
        ra = ra_dec.ra.value
        dec = ra_dec.dec.value

    if list_otypes is None:
        otype_ = None
    elif len(list_otypes) == 1:
        otype_ = list_otypes[0]
    else:
        otype_ = '|'.join(list_otypes)

    dict_data[name] = {"IDs": list_ids, "MAIN_ID": main_id, "OTYPES": otype_, "RA": ra, "DEC": dec, "DISCOVERY_TIME": discovery_time}

    return dict_data


def query_fink(name):
    dict_data = {}
    list_ids = None
    main_id = None
    otype_ = None
    ra = None
    dec = None
    discovery_time = None

    query_name = name.replace("ztf", "ZTF")
    r = requests.post('https://api.fink-portal.org/api/v1/objects', json={'objectId': query_name, 'output-format': 'json', 'columns': 'i:ra,i:dec,i:objectId'})
    # Format output in a DataFrame
    df = pd.read_json(io.BytesIO(r.content))
    if not df.empty:
        object_id = df["i:objectId"].values[0]
        main_id = object_id
        ra_tmp = df["i:ra"][df["i:objectId"] == object_id].values
        dec_tmp = df["i:dec"][df["i:objectId"] == object_id].values
        ra = np.mean(np.float32(ra_tmp))
        dec = np.mean(np.float32(dec_tmp))
        list_ids = '|'.join(list(set(df["i:objectId"].values)))

    dict_data[name] = {"IDs": list_ids, "MAIN_ID": main_id, "OTYPES": otype_, "RA": ra, "DEC": dec, "DISCOVERY_TIME": discovery_time}

    return dict_data


def create_pattern_list():
    pattern_list_low = []
    pattern_list_low += ["\\b(ngc) *?([0-9]{1,4})\\b", "\\b(m) *?([0-9]{1,3})\\b"]
    pattern_list_low += ["\\b(ugc) *?([0-9]{1,5})\\b"]

    pattern_list_low += ["\\b(icecube|grb|frb|pks|mrk|hawc|maxi|gw)([ -]?)([0-9\\.\\-\\+]{2,}[a-z]?)\\b"]
    pattern_list_low += ["\\b(ic)([ -]?)([0-9]{1,4})\\b"]
    pattern_list_low += ["\\b(ztf) *?([0-9]{2}[a-z]{7})\\b"]

    pattern_list_low += ["\\b(at|sn) *?([1-2]{1}[0-9]{3}[a-z]{1,4})\\b"]
    pattern_list_low += ["\\b(asas)([ -]?)(sn)([ -]?)([0-9]{2}[a-z]{2,3})\\b"]

    pattern_list_low += ["\\b(ps|gaia) *?([1-2]{1}[0-9]{1}[a-z]{1,4})\\b"]

    pattern_list_low += ["\\b(m31n) *?([0-9]{4})-([0-9]{2}[a-z]{1})\\b"]
    pattern_list_low += ["\\b(ptf|atlas) *?([0-9]{2}[a-z]{1,4})\\b"]

    pattern_list_low += ["\\b(4c) *?((\\+|-)[0-9]{2}\\.[0-9]{2}\\.[0-9]{1})\\b"]
    pattern_list_low += ["\\b(4c) *?((\\+|-)[0-9]{2}\\.[0-9]{2})\\b"]

    # new from lm-astronomy
    pattern_list_low += ["\\b(lsq12) *?([a-z]{3})\\b"]
    pattern_list_low += ["\\b(des14) *?([a-z]{1}[0-9]{1})\\b"]

    pattern_list = []

    HH = "(2[0-4]|[0-1][0-9])"
    MM = "(90|[0-8][0-9])"
    MMm = "(90|[0-8][0-9])([0-9])"
    SS = "(90|[0-8][0-9])"
    DD = "(90|[0-8][0-9])"
    pDDd = "(\\+|-)(90|[0-8][0-9])([0-9])"

    LLL = "([0-9][0-9][0-9])"
    BB = "([0-9][0-9])"
    VVV = "([0-9][0-9][0-9])"

    NAAA = "(([0-9][A-Z]{1,4})|([A-Z]{2,4}))"

    pattern_list += [f"\\b{NAAA} *?([0-9]{{6}})(?!-)\\b"]

    pattern_list += [f"\\b{NAAA} *?(J[0-9]{{6}}(\\+|-)[0-9]{{5}})(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?(J[0-9]{{6}}(\\.?)[0-9]{{1}}(\\+|-)[0-9]{{6}})(?!-)\\b"]

    pattern_list += [f"\\b{NAAA} *?(J[0-9]{{4}}(\\.?)[0-9]{{1}}(\\+|-)[0-9]{{4}})[a-z]{{0,1}}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?{HH}{MM}(\\+|-){DD}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?(J?){HH}{MM}{pDDd}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?B{HH}{MM}(\\+|-){DD}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?B{HH}{MM}{pDDd}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?J{HH}{MM}(\\+|-){DD}{MM}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?J{HH}{MM}([0-9])(\\+|-){DD}{MM}(?!-)\\b"]

    pattern_list += [f"\\b{NAAA} *?{HH}{MMm}(\\+|-){DD}{MM}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?{HH}{MM}(\\.?)([0-9])(\\+|-){DD}{MM}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?{HH}{MM}{SS}(\\+|-){DD}{MM}{SS}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?{HH}{MM}{SS}(\\.?)([0-9])(\\+|-){DD}{MM}{SS}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?B{HH}{MM}{SS}(\\.?)([0-9])(\\+|-){DD}{MM}{SS}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?J{HH}{MM}{SS}(\\.?)([0-9][0-9])(\\+|-){DD}{MM}{SS}(\\.?)([0-9])(?!-)\\b"]

    pattern_list += [f"\\b{NAAA} *?{LLL}(\\.?)([0-9])(\\+|-){BB}(\\.?)([0-9])(\\+|-){VVV}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?G{LLL}(\\.?)([0-9])(\\+|-){BB}(\\.?)([0-9])(\\+|-){VVV}(?!-)\\b"]

    FFF = "([0-9][0-9][0-9])"
    FFFF = "([0-9][0-9][0-9][0-9])"
    NNNN = FFFF
    NNNNN = "([0-9][0-9][0-9][0-9][0-9])"

    pattern_list += [f"\\b{NAAA} *?{FFF}-{NNNN}(?!-)\\b"]
    pattern_list += [f"\\b{NAAA} *?{FFFF}-{NNNNN}(?!-)\\b"]

    YY = "[0-9][0-9]"
    MM = "[0-1][0-9]"
    DD = "[0-3][0-9]"
    pattern_list += [f"\\b{NAAA} *?{YY}{MM}{DD}A{{0,1}}(?!-)\\b"]

    return pattern_list, pattern_list_low


def rule_based_source_detector(text_id, text_id_text):
    pattern_list, pattern_list_low = create_pattern_list()

    regex_sources = []

    for pattern in pattern_list_low:
        for m in re.finditer(pattern, text_id_text.lower()):
            source_ = m.group(0).replace(" ", "")

            if "asas" in source_:
                source_ = source_.replace("-", "")
                source_ = source_.replace("sn", "sn-")

            regex_sources.append(source_)

    for pattern in pattern_list:
        for m in re.finditer(pattern, text_id_text):
            source_ = m.group(0)
            if source_.replace(" ", "").lower() not in regex_sources:
                regex_sources.append(source_)

    return list(set(regex_sources))


def query_info_sources(text_id, sources):
    if len(sources) != 0:
        source_list = []
        otype_list = []
        mainid_list = []
        ra_list = []
        dec_list = []
        pattern_string = re.compile("[a-z]")
        dict_unknown = {}
        dict_unknown = {"Raw Source Name": []}

        for source_name_0 in sources:
            # TODO:  remove all non a-z0-9 characters from the beginning and ending of the source name
            # Now: remove "," from the beginning and ending of the source name
            if source_name_0[0] == ",":
                source_name = source_name_0[1:]
            elif source_name_0[-1] == ",":
                source_name = source_name_0[:-1]
            else:
                source_name = source_name_0

            if pattern_string.findall(source_name.lower()):
                dict_otype = query_simbad(source_name)
                if dict_otype[source_name]["MAIN_ID"] is None:
                    dict_otype = query_tns(source_name)
                if dict_otype[source_name]["MAIN_ID"] is None:
                    dict_otype = query_fink(source_name)

                if dict_otype[source_name]["MAIN_ID"] is None:
                    dict_unknown["Raw Source Name"].append(source_name)
                else:
                    mainid_list.append(dict_otype[source_name]["MAIN_ID"])
                    otype_list.append(dict_otype[source_name]["OTYPES"])
                    ra_list.append(dict_otype[source_name]["RA"])
                    dec_list.append(dict_otype[source_name]["DEC"])
                    source_list.append(source_name)
            else:
                dict_unknown["Raw Source Name"].append(source_name_0)

        dict_data = {"TEXT_ID": [text_id] * len(source_list), "Raw Source Name": source_list, "Main ID Name": mainid_list, "OTYPE": otype_list, "RA": ra_list, "Dec": dec_list}
        df_save = pd.DataFrame(dict_data)
        df_save.replace({None: "NotKnown"}, inplace=True)
        return df_save.drop_duplicates(subset=['Main ID Name']), pd.DataFrame(dict_unknown)

    return pd.DataFrame(), pd.DataFrame()