Tibeuleu/FOC_Reduction
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Fix MAST target query

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This commit is contained in:
Thibault Barnouin
2024-05-02 12:36:53 +02:00
parent 845c6c30da
commit a931e20f5f
1 changed files with 8 additions and 10 deletions
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18
src/lib/query.py
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@@ -16,14 +16,6 @@ def divide_proposal(products):
"""
Divide observation in proposals by time or filter
"""
for pid in np.unique(products['Proposal ID']):
obs = products[products['Proposal ID'] == pid].copy()
close_date = np.unique(np.array([TimeDelta(np.abs(obs['Start'][0].unix-date.unix), format='sec')
< 7.*u.d for date in obs['Start']], dtype=bool), axis=0)
if len(close_date) > 1:
for date in close_date:
products['Proposal ID'][np.any([products['Dataset'] == dataset for dataset in obs['Dataset'][date]], axis=0)
] = "_".join([obs['Proposal ID'][date][0], str(obs['Start'][date][0])[:10]])
for pid in np.unique(products['Proposal ID']):
obs = products[products['Proposal ID'] == pid].copy()
same_filt = np.unique(np.array(np.sum([obs['Filters'][:, 1:] == filt[1:] for filt in obs['Filters']], axis=2) < 3, dtype=bool), axis=0)
@@ -31,6 +23,14 @@ def divide_proposal(products):
for filt in same_filt:
products['Proposal ID'][np.any([products['Dataset'] == dataset for dataset in obs['Dataset'][filt]], axis=0)] = "_".join(
[obs['Proposal ID'][filt][0], "_".join([fi for fi in obs['Filters'][filt][0][1:] if fi[:-1] != "CLEAR"])])
for pid in np.unique(products['Proposal ID']):
obs = products[products['Proposal ID'] == pid].copy()
close_date = np.unique([[np.abs(TimeDelta(obs['Start'][i].unix-date.unix, format='sec'))
< 7.*u.d for i in range(len(obs))] for date in obs['Start']], axis=0)
if len(close_date) > 1:
for date in close_date:
products['Proposal ID'][np.any([products['Dataset'] == dataset for dataset in obs['Dataset'][date]], axis=0)
] = "_".join([obs['Proposal ID'][date][0], str(obs['Start'][date][0])[:10]])
return products
@@ -147,8 +147,6 @@ def get_product_list(target=None, proposal_id=None):
for prod in products:
prod['target_name'] = observations['target_name'][observations['obsid'] == prod['obsID']][0]
tab = unique(products, ['target_name', 'proposal_id'])
if len(tab) > 1 and 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