Tibeuleu/FOC_Reduction
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

handle multi target query

Browse Source
This commit is contained in:
Thibault Barnouin
2026-02-11 15:16:15 +01:00
parent 561f226473
commit 4341897ba4
1 changed files with 61 additions and 25 deletions
Download Patch File Download Diff File Expand all files Collapse all files

86
package/lib/query.py
View File

@@ -11,7 +11,7 @@ from warnings import filterwarnings
import astropy.units as u import astropy.units as u
import numpy as np import numpy as np
from astropy.table import Column, unique from astropy.table import Column, unique, vstack
from astropy.time import Time, TimeDelta from astropy.time import Time, TimeDelta
from astroquery.exceptions import NoResultsWarning from astroquery.exceptions import NoResultsWarning
from astroquery.mast import MastMissions, Observations from astroquery.mast import MastMissions, Observations
@@ -82,14 +82,20 @@ def get_product_list(target=None, proposal_id=None, instrument="foc"):
"References", "References",
] ]
if target is None: if target is None and proposal_id is None:
target = input("Target name:\n>") target = input("Target name:\n>")
# Use query_object method to resolve the object name into coordinates # Use query_object method to resolve the object name into coordinates
if instrument == "foc": if instrument == "foc":
results = mission.query_object( if target is None and proposal_id is not None:
target, radius=radius, select_cols=select_cols, sci_spec_1234="POL*", sci_obs_type="image", sci_aec="S", sci_instrume="foc" results = mission.query_criteria(
) sci_pep_id=proposal_id, radius=radius, select_cols=select_cols, sci_spec_1234="POL*", sci_obs_type="image", sci_aec="S", sci_instrume="foc"
)
target = list(results["sci_targname"])
else:
results = mission.query_object(
target, radius=radius, select_cols=select_cols, sci_spec_1234="POL*", sci_obs_type="image", sci_aec="S", sci_instrume="foc"
)
dataproduct_type = "image" dataproduct_type = "image"
description = "DADS C0F file - Calibrated exposure WFPC/WFPC2/FOC/FOS/GHRS/HSP" description = "DADS C0F file - Calibrated exposure WFPC/WFPC2/FOC/FOS/GHRS/HSP"
elif instrument == "fos": elif instrument == "fos":
@@ -110,8 +116,16 @@ def get_product_list(target=None, proposal_id=None, instrument="foc"):
results["Start"] = Column(Time(results["Start"])) results["Start"] = Column(Time(results["Start"]))
results["Stop"] = Column(Time(results["Stop"])) results["Stop"] = Column(Time(results["Stop"]))
results = divide_proposal(results) if isinstance(target, list):
obs = results.copy() for i, targ in enumerate(target):
results_div = divide_proposal(results[results["Target name"] == targ])
if i == 0:
obs = results_div.copy()
else:
obs = vstack([obs, results_div])
else:
results_div = divide_proposal(results)
obs = results_div.copy()
# Remove single observations for which a FIND filter is used # Remove single observations for which a FIND filter is used
to_remove = [] to_remove = []
@@ -142,6 +156,7 @@ def get_product_list(target=None, proposal_id=None, instrument="foc"):
if len(c3prod) < 1: if len(c3prod) < 1:
obs.remove_rows(np.arange(len(obs))[obs["Proposal ID"] == pid]) obs.remove_rows(np.arange(len(obs))[obs["Proposal ID"] == pid])
# tab = unique(obs, ["Target name", "Proposal ID"])
tab = unique(obs, ["Target name", "Proposal ID"]) tab = unique(obs, ["Target name", "Proposal ID"])
obs["Obs"] = [np.argmax(np.logical_and(tab["Proposal ID"] == data["Proposal ID"], tab["Target name"] == data["Target name"])) + 1 for data in obs] obs["Obs"] = [np.argmax(np.logical_and(tab["Proposal ID"] == data["Proposal ID"], tab["Target name"] == data["Target name"])) + 1 for data in obs]
try: try:
@@ -150,7 +165,7 @@ def get_product_list(target=None, proposal_id=None, instrument="foc"):
raise ValueError("There is no observation with polarimetry for {0:s} in HST/{1:s} Legacy Archive".format(target, instrument.upper())) raise ValueError("There is no observation with polarimetry for {0:s} in HST/{1:s} Legacy Archive".format(target, instrument.upper()))
b = np.zeros(len(results), dtype=bool) b = np.zeros(len(results), dtype=bool)
if proposal_id is not None and str(proposal_id) in obs["Proposal ID"]: if proposal_id is not None and np.all(str(proposal_id) == np.unique(obs["Proposal ID"])):
b[results["Proposal ID"] == str(proposal_id)] = True b[results["Proposal ID"] == str(proposal_id)] = True
else: else:
n_obs.pprint(len(n_obs) + 2) n_obs.pprint(len(n_obs) + 2)
@@ -184,6 +199,7 @@ def get_product_list(target=None, proposal_id=None, instrument="foc"):
tab = unique(products, "proposal_id") tab = unique(products, "proposal_id")
products["Obs"] = [np.argmax(tab["proposal_id"] == data["proposal_id"]) + 1 for data in products] products["Obs"] = [np.argmax(tab["proposal_id"] == data["proposal_id"]) + 1 for data in products]
products["targname"] = [obs["Target name"][np.argmax(obs["Dataset"] == data[:-9].upper())] for data in products["productFilename"]]
return target, products return target, products
@@ -195,23 +211,43 @@ def retrieve_products(target=None, proposal_id=None, instrument="foc", output_di
prodpaths = [] prodpaths = []
# data_dir = path_join(output_dir, target) # data_dir = path_join(output_dir, target)
out = "" out = ""
for obs in unique(products, "Obs"): if isinstance(target, list):
filepaths = [] for targ in target:
# obs_dir = path_join(data_dir, obs['prodposal_id']) for obs in unique(products[products["targname"] == targ], "Obs"):
# if obs['target_name']!=target: filepaths = []
obs_dir = path_join(path_join(output_dir, target), obs["proposal_id"]) # obs_dir = path_join(data_dir, obs['prodposal_id'])
if not path_exists(obs_dir): # if obs['target_name']!=target:
system("mkdir -p {0:s} {1:s}".format(obs_dir, obs_dir.replace("data", "plots"))) obs_dir = path_join(path_join(output_dir, targ), obs["proposal_id"])
for file in products["productFilename"][products["Obs"] == obs["Obs"]]: if not path_exists(obs_dir):
fpath = path_join(obs_dir, file) system("mkdir -p {0:s} {1:s}".format(obs_dir, obs_dir.replace("data", "plots")))
if not path_exists(fpath): for file in products["productFilename"][products["Obs"] == obs["Obs"]]:
out += "{0:s} : {1:s}\n".format( fpath = path_join(obs_dir, file)
file, Observations.download_file(products["dataURI"][products["productFilename"] == file][0], local_path=fpath)[0] if not path_exists(fpath):
) out += "{0:s} : {1:s}\n".format(
else: file, Observations.download_file(products["dataURI"][products["productFilename"] == file][0], local_path=fpath)[0]
out += "{0:s} : Exists\n".format(file) )
filepaths.append([obs_dir, file]) else:
prodpaths.append(np.array(filepaths, dtype=str)) out += "{0:s} : Exists\n".format(file)
filepaths.append([obs_dir, file])
prodpaths.append(np.array(filepaths, dtype=str))
else:
for obs in unique(products[products["Target name"] == targ], "Obs"):
filepaths = []
# obs_dir = path_join(data_dir, obs['prodposal_id'])
# if obs['target_name']!=target:
obs_dir = path_join(path_join(output_dir, target), obs["proposal_id"])
if not path_exists(obs_dir):
system("mkdir -p {0:s} {1:s}".format(obs_dir, obs_dir.replace("data", "plots")))
for file in products["productFilename"][products["Obs"] == obs["Obs"]]:
fpath = path_join(obs_dir, file)
if not path_exists(fpath):
out += "{0:s} : {1:s}\n".format(
file, Observations.download_file(products["dataURI"][products["productFilename"] == file][0], local_path=fpath)[0]
)
else:
out += "{0:s} : Exists\n".format(file)
filepaths.append([obs_dir, file])
prodpaths.append(np.array(filepaths, dtype=str))
return target, prodpaths return target, prodpaths