Tibeuleu/FOC_Reduction
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filter data products on target name

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This commit is contained in:
Thibault Barnouin
2023-05-14 13:13:52 +02:00
parent 89393637e5
commit 8e19cc74f1
2 changed files with 24 additions and 16 deletions
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38
src/lib/query.py
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@@ -94,11 +94,11 @@ def get_product_list(target=None, proposal_id=None):
if np.all(used_pol < 1):
obs.remove_rows(np.arange(len(obs))[obs['Proposal ID'] == pid])
obs["Obs"] = [np.argmax(unique(obs, 'Proposal ID')[
'Proposal ID'] == data['Proposal ID'])+1 for data in obs]
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]
try:
obs = unique(obs[["Obs", "Filters", "Start", "Central wavelength", "Instrument",
"Size", "Target name", "Proposal ID", "PI last name"]], 'Proposal ID')
n_obs = unique(obs[["Obs", "Filters", "Start", "Central wavelength", "Instrument",
"Size", "Target name", "Proposal ID", "PI last name"]], 'Obs')
except IndexError:
raise ValueError(
"There is no observation with POL0, POL60 and POL120 for {0:s} in HST/FOC Legacy Archive".format(target))
@@ -107,7 +107,7 @@ def get_product_list(target=None, proposal_id=None):
if not proposal_id is None and str(proposal_id) in obs['Proposal ID']:
b[results['Proposal ID'] == str(proposal_id)] = True
else:
print(obs)
n_obs.pprint(len(n_obs)+2)
a = [np.array(i.split(":"), dtype=str) for i in input("select observations to be downloaded ('1,3,4,5' or '1,3:5' or 'all','*' default to 1)\n>").split(',')]
if a[0][0]=='':
a = [[1]]
@@ -118,9 +118,9 @@ def get_product_list(target=None, proposal_id=None):
for i in a:
if len(i) > 1:
for j in range(i[0], i[1]+1):
b[results['Proposal ID'] == obs['Proposal ID'][obs["Obs"] == j]] = True
b[np.array([dataset in obs['Dataset'][obs["Obs"] == j] for dataset in results['Dataset']])] = True
else:
b[results['Proposal ID'] == obs['Proposal ID'][obs['Obs'] == i[0]]] = True
b[np.array([dataset in obs['Dataset'][obs['Obs'] == i[0]] for dataset in results['Dataset']])] = True
observations = Observations.query_criteria(obs_id=list(results['Dataset'][b]))
products = Observations.filter_products(Observations.get_product_list(observations),
@@ -129,12 +129,18 @@ def get_product_list(target=None, proposal_id=None):
calib_level=[2],
description="DADS C0F file - Calibrated exposure WFPC/WFPC2/FOC/FOS/GHRS/HSP")
products['proposal_id'] = Column(products['proposal_id'],dtype='U35')
products['target_name'] = Column(observations['target_name'])
for pid in np.unique(results['Proposal ID']):
rpid = results['Proposal ID']==pid
ppid = np.argmax([results['Dataset'][rpid] == prod[:len(results['Dataset'][0])].upper() for prod in products['productFilename']],axis=0)
products['proposal_id'][ppid] = pid
for prod in products:
products['proposal_id'] = results['Proposal ID'][results['Dataset']==prod['productFilename'][:len(results['Dataset'][0])].upper()]
#for prod in products:
# prod['target_name'] = observations['target_name'][observation['obsid']==prod['obsID']]
tab = unique(products, ['target_name', 'proposal_id'])
if np.all(tab['target_name']==tab['target_name'][0]):
target = tab['target_name'][0]
products["Obs"] = [np.argmax(np.logical_and(tab['proposal_id']==data['proposal_id'],tab['target_name']==data['target_name']))+1 for data in products]
return target, products
@@ -146,12 +152,14 @@ def retrieve_products(target=None, proposal_id=None, output_dir='./data'):
prodpaths = []
data_dir = path_join(output_dir, target)
out = ""
for obs_id in unique(products, 'proposal_id')['proposal_id']:
for obs in unique(products,'Obs'):
filepaths = []
obs_dir = path_join(data_dir, obs_id)
#obs_dir = path_join(data_dir, obs['prodposal_id'])
#if obs['target_name']!=target:
obs_dir = path_join(path_join(output_dir, obs['target_name']), 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['proposal_id'] == obs_id]:
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(