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1
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"""
|
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2
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Search functionality for the Gemini archive of observations.
|
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3
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4
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For questions, contact ooberdorf@gemini.edu
|
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5
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"""
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6
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|
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7
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1
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import os
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8
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9
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1
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from datetime import date
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1
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from astropy import log
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1
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from astropy import units
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13
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1
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from astropy.table import Table, MaskedColumn
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14
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15
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1
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from astroquery.gemini.urlhelper import URLHelper
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1
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import numpy as np
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1
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import logging
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20
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1
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from ..query import BaseQuery, QueryWithLogin
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1
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from ..utils.class_or_instance import class_or_instance
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1
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from . import conf
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23
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1
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from ..exceptions import AuthenticationWarning
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1
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logger = logging.getLogger(__name__)
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28
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29
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1
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__all__ = ['Observations', 'ObservationsClass'] # specifies what to import
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31
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32
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1
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__valid_instruments__ = [
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33
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'GMOS',
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34
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'GMOS-N',
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'GMOS-S',
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36
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'GNIRS',
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37
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'GRACES',
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38
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'NIRI',
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39
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'NIFS',
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40
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'GSAOI',
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41
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'F2',
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42
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'GPI',
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43
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'NICI',
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44
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'MICHELLE',
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45
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'TRECS',
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46
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'BHROS',
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47
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'HRWFS',
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48
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'OSCIR',
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49
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'FLAMINGOS',
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50
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'HOKUPAA+QUIRC',
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51
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'PHOENIX',
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52
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'TEXES',
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53
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'ABU',
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54
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'CIRPASS'
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55
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]
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56
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57
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58
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1
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__valid_observation_class__ = [
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'science',
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60
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'acq',
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'progCal',
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62
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'dayCal',
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63
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'partnerCal',
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64
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'acqCal',
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65
|
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]
|
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66
|
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67
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1
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__valid_observation_types__ = [
|
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68
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'OBJECT',
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69
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'BIAS',
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70
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'DARK',
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71
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'FLAT',
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72
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'ARC',
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73
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'PINHOLE',
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74
|
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'RONCHI',
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75
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'CAL',
|
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76
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'FRINGE',
|
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77
|
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'MASK'
|
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78
|
|
]
|
|
79
|
|
|
|
80
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1
|
__valid_modes__ = [
|
|
81
|
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'imaging',
|
|
82
|
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'spectroscopy',
|
|
83
|
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'LS',
|
|
84
|
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'MOS',
|
|
85
|
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'IFS'
|
|
86
|
|
]
|
|
87
|
|
|
|
88
|
1
|
__valid_adaptive_optics__ = [
|
|
89
|
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'NOTAO',
|
|
90
|
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'AO',
|
|
91
|
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'NGS',
|
|
92
|
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'LGS'
|
|
93
|
|
]
|
|
94
|
|
|
|
95
|
1
|
__valid_raw_reduced__ = [
|
|
96
|
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'RAW',
|
|
97
|
|
'PREPARED',
|
|
98
|
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'PROCESSED_BIAS',
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|
99
|
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'PROCESSED_FLAT',
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100
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'PROCESSED_FRINGE',
|
|
101
|
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'PROCESSED_ARC'
|
|
102
|
|
]
|
|
103
|
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104
|
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|
105
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1
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class ObservationsClass(QueryWithLogin):
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106
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107
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1
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server = conf.server
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108
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1
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url_helper = URLHelper(server)
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109
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|
|
110
|
1
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def __init__(self, *args):
|
|
111
|
|
"""
|
|
112
|
|
Query class for observations in the Gemini archive.
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|
113
|
|
|
|
114
|
|
This class provides query capabilities against the gemini archive. Queries
|
|
115
|
|
can be done by cone search, by name, or by a set of criteria.
|
|
116
|
|
"""
|
|
117
|
1
|
super().__init__()
|
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118
|
|
|
|
119
|
1
|
def _login(self, username, password):
|
|
120
|
|
"""
|
|
121
|
|
Login to the Gemini Archive website.
|
|
122
|
|
|
|
123
|
|
This method will authenticate the session as a particular user. This may give you access
|
|
124
|
|
to additional information or access based on your credentials
|
|
125
|
|
|
|
126
|
|
Parameters
|
|
127
|
|
----------
|
|
128
|
|
username : str
|
|
129
|
|
The username to login as
|
|
130
|
|
password : str
|
|
131
|
|
The password for the given account
|
|
132
|
|
"""
|
|
133
|
0
|
params = dict(username=username, password=password)
|
|
134
|
0
|
r = self._session.request('POST', 'https://archive.gemini.edu/login/', params=params)
|
|
135
|
0
|
if b'<P>Welcome, you are sucessfully logged in' not in r.content:
|
|
136
|
0
|
logger.error('Unable to login, please check your credentials')
|
|
137
|
0
|
return False
|
|
138
|
0
|
return True
|
|
139
|
|
|
|
140
|
1
|
@class_or_instance
|
|
141
|
1
|
def query_region(self, coordinates, radius=0.3*units.deg):
|
|
142
|
|
"""
|
|
143
|
|
search for Gemini observations by target on the sky.
|
|
144
|
|
|
|
145
|
|
Given a sky position and radius, returns a `~astropy.table.Table` of Gemini observations.
|
|
146
|
|
|
|
147
|
|
Parameters
|
|
148
|
|
----------
|
|
149
|
|
coordinates : str or `~astropy.coordinates` object
|
|
150
|
|
The target around which to search. It may be specified as a
|
|
151
|
|
string or as the appropriate `~astropy.coordinates` object.
|
|
152
|
|
radius : str or `~astropy.units.Quantity` object, optional
|
|
153
|
|
Default 0.3 degrees.
|
|
154
|
|
The string must be parsable by `~astropy.coordinates.Angle`. The
|
|
155
|
|
appropriate `~astropy.units.Quantity` object from
|
|
156
|
|
`~astropy.units` may also be used. Defaults to 0.3 deg.
|
|
157
|
|
|
|
158
|
|
Returns
|
|
159
|
|
-------
|
|
160
|
|
response : `~astropy.table.Table`
|
|
161
|
|
"""
|
|
162
|
1
|
return self.query_criteria(coordinates=coordinates, radius=radius)
|
|
163
|
|
|
|
164
|
1
|
@class_or_instance
|
|
165
|
1
|
def query_object(self, objectname, radius=0.3*units.deg):
|
|
166
|
|
"""
|
|
167
|
|
search for Gemini observations by target on the sky.
|
|
168
|
|
|
|
169
|
|
Given an object name and optional radius, returns a `~astropy.table.Table` of Gemini observations.
|
|
170
|
|
|
|
171
|
|
Parameters
|
|
172
|
|
----------
|
|
173
|
|
objectname : str
|
|
174
|
|
The name of an object to search for. This attempts to resolve the object
|
|
175
|
|
by name and do a search on that area of the sky. This does not handle
|
|
176
|
|
moving targets.
|
|
177
|
|
radius : str or `~astropy.units.Quantity` object, optional
|
|
178
|
|
Default 0.3 degrees.
|
|
179
|
|
The string must be parsable by `~astropy.coordinates.Angle`. The
|
|
180
|
|
appropriate `~astropy.units.Quantity` object from
|
|
181
|
|
`~astropy.units` may also be used. Defaults to 0.3 deg.
|
|
182
|
|
|
|
183
|
|
Returns
|
|
184
|
|
-------
|
|
185
|
|
response : `~astropy.table.Table`
|
|
186
|
|
"""
|
|
187
|
0
|
return self.query_criteria(objectname=objectname, radius=radius)
|
|
188
|
|
|
|
189
|
1
|
@class_or_instance
|
|
190
|
1
|
def query_criteria(self, *rawqueryargs, coordinates=None, radius=0.3*units.deg, pi_name=None, program_id=None, utc_date=None,
|
|
191
|
|
instrument=None, observation_class=None, observation_type=None, mode=None,
|
|
192
|
|
adaptive_optics=None, program_text=None, objectname=None, raw_reduced=None,
|
|
193
|
|
orderby=None, **rawquerykwargs):
|
|
194
|
|
"""
|
|
195
|
|
search a variety of known parameters against the Gemini observations.
|
|
196
|
|
|
|
197
|
|
Given various criteria, search the Gemini archive for matching observations. Note that
|
|
198
|
|
``rawqueryargs`` and ``rawquerykwargs`` will pick up additional positional and key=value
|
|
199
|
|
arguments and pass then on to the raw query as is.
|
|
200
|
|
|
|
201
|
|
Parameters
|
|
202
|
|
----------
|
|
203
|
|
coordinates : str or `~astropy.coordinates` object
|
|
204
|
|
The target around which to search. It may be specified as a
|
|
205
|
|
string or as the appropriate `~astropy.coordinates` object.
|
|
206
|
|
radius : str or `~astropy.units.Quantity` object, optional
|
|
207
|
|
Default 0.3 degrees.
|
|
208
|
|
The string must be parsable by `~astropy.coordinates.Angle`. The
|
|
209
|
|
appropriate `~astropy.units.Quantity` object from
|
|
210
|
|
`~astropy.units` may also be used. Defaults to 0.3 deg.
|
|
211
|
|
pi_name : str, optional
|
|
212
|
|
Default None.
|
|
213
|
|
Can be used to search for data by the PI's name.
|
|
214
|
|
program_id : str, optional
|
|
215
|
|
Default None.
|
|
216
|
|
Can be used to match on program ID
|
|
217
|
|
utc_date : date or (date,date) tuple, optional
|
|
218
|
|
Default None.
|
|
219
|
|
Can be used to search for observations on a particular day or range of days (inclusive).
|
|
220
|
|
instrument : str, optional
|
|
221
|
|
Can be used to search for a particular instrument. Valid values are:
|
|
222
|
|
'GMOS',
|
|
223
|
|
'GMOS-N',
|
|
224
|
|
'GMOS-S',
|
|
225
|
|
'GNIRS',
|
|
226
|
|
'GRACES',
|
|
227
|
|
'NIRI',
|
|
228
|
|
'NIFS',
|
|
229
|
|
'GSAOI',
|
|
230
|
|
'F2',
|
|
231
|
|
'GPI',
|
|
232
|
|
'NICI',
|
|
233
|
|
'MICHELLE',
|
|
234
|
|
'TRECS',
|
|
235
|
|
'BHROS',
|
|
236
|
|
'HRWFS',
|
|
237
|
|
'OSCIR',
|
|
238
|
|
'FLAMINGOS',
|
|
239
|
|
'HOKUPAA+QUIRC',
|
|
240
|
|
'PHOENIX',
|
|
241
|
|
'TEXES',
|
|
242
|
|
'ABU',
|
|
243
|
|
'CIRPASS'
|
|
244
|
|
observation_class : str, optional
|
|
245
|
|
Specifies the class of observations to search for. Valid values are:
|
|
246
|
|
'science',
|
|
247
|
|
'acq',
|
|
248
|
|
'progCal',
|
|
249
|
|
'dayCal',
|
|
250
|
|
'partnerCal',
|
|
251
|
|
'acqCal'
|
|
252
|
|
observation_type : str, optional
|
|
253
|
|
Search for a particular type of observation. Valid values are:
|
|
254
|
|
'OBJECT',
|
|
255
|
|
'BIAS',
|
|
256
|
|
'DARK',
|
|
257
|
|
'FLAT',
|
|
258
|
|
'ARC',
|
|
259
|
|
'PINHOLE',
|
|
260
|
|
'RONCHI',
|
|
261
|
|
'CAL',
|
|
262
|
|
'FRINGE',
|
|
263
|
|
'MASK'
|
|
264
|
|
mode : str, optional
|
|
265
|
|
The mode of the observation. Valid values are:
|
|
266
|
|
'imaging',
|
|
267
|
|
'spectroscopy',
|
|
268
|
|
'LS',
|
|
269
|
|
'MOS',
|
|
270
|
|
'IFS'
|
|
271
|
|
adaptive_optics : str, optional
|
|
272
|
|
Specify the presence of adaptive optics. Valid values are:
|
|
273
|
|
'NOTAO',
|
|
274
|
|
'AO',
|
|
275
|
|
'NGS',
|
|
276
|
|
'LGS'
|
|
277
|
|
program_text : str, optional
|
|
278
|
|
Specify text in the information about the program. This is free form text.
|
|
279
|
|
objectname : str, optional
|
|
280
|
|
Give the name of the target.
|
|
281
|
|
raw_reduced : str, optional
|
|
282
|
|
Indicate the raw or reduced status of the observations to search for. Valid values are:
|
|
283
|
|
'RAW',
|
|
284
|
|
'PREPARED',
|
|
285
|
|
'PROCESSED_BIAS',
|
|
286
|
|
'PROCESSED_FLAT',
|
|
287
|
|
'PROCESSED_FRINGE',
|
|
288
|
|
'PROCESSED_ARC'
|
|
289
|
|
orderby : str, optional
|
|
290
|
|
Indicates how the results should be sorted. Values should be like the ones used
|
|
291
|
|
in the archive website when sorting a column. For example, ``data_label_desc`` would
|
|
292
|
|
sort by the data label in descending order.
|
|
293
|
|
rawqueryargs : list, optional
|
|
294
|
|
Additional arguments will be passed down to the raw query. This covers any
|
|
295
|
|
additional parameters that would end up as '/parametervalue/' in the URL to the archive
|
|
296
|
|
webservice.
|
|
297
|
|
rawquerykwargs : dict, optional
|
|
298
|
|
Additional key/value arguments will also be passed down to the raw query. This covers
|
|
299
|
|
any parameters that would end up as '/key=value/' in the URL to the archive webservice.
|
|
300
|
|
|
|
301
|
|
Returns
|
|
302
|
|
-------
|
|
303
|
|
response : `~astropy.table.Table`
|
|
304
|
|
|
|
305
|
|
Raises
|
|
306
|
|
------
|
|
307
|
|
ValueError: passed value is not recognized for the given field, see message for details
|
|
308
|
|
"""
|
|
309
|
|
|
|
310
|
|
# Build parameters into raw query
|
|
311
|
|
#
|
|
312
|
|
# This consists of a set of unnamed arguments, args, and key/value pairs, kwargs
|
|
313
|
|
|
|
314
|
|
# These will hold the passed freeform parameters plus the explicit criteria
|
|
315
|
|
# for our eventual call to the raw query method
|
|
316
|
1
|
args = list()
|
|
317
|
1
|
kwargs = dict()
|
|
318
|
|
|
|
319
|
|
# Copy the incoming set of free-form arguments
|
|
320
|
1
|
if rawqueryargs:
|
|
321
|
0
|
for arg in rawqueryargs:
|
|
322
|
0
|
args.append(arg)
|
|
323
|
1
|
if rawquerykwargs:
|
|
324
|
0
|
for (k, v) in rawquerykwargs.items():
|
|
325
|
0
|
kwargs[k] = v
|
|
326
|
|
|
|
327
|
|
# Now consider the canned criteria
|
|
328
|
1
|
if radius is not None:
|
|
329
|
1
|
kwargs["radius"] = radius
|
|
330
|
1
|
if coordinates is not None:
|
|
331
|
1
|
kwargs["coordinates"] = coordinates
|
|
332
|
1
|
if pi_name is not None:
|
|
333
|
0
|
kwargs["PIname"] = pi_name
|
|
334
|
1
|
if program_id is not None:
|
|
335
|
1
|
kwargs["progid"] = program_id.upper()
|
|
336
|
1
|
if utc_date is not None:
|
|
337
|
0
|
if isinstance(utc_date, date):
|
|
338
|
0
|
args.append(utc_date.strftime("YYYYMMdd"))
|
|
339
|
0
|
elif isinstance(utc_date, tuple):
|
|
340
|
0
|
if len(utc_date) != 2:
|
|
341
|
0
|
raise ValueError("utc_date tuple should have two values")
|
|
342
|
0
|
if not isinstance(utc_date[0], date) or not isinstance(utc_date[1], date):
|
|
343
|
0
|
raise ValueError("utc_date tuple should have date values in it")
|
|
344
|
0
|
args.append("%s-%s" % utc_date[0].strftime("YYYYMMdd"), utc_date[1].strftime("YYYYMMdd"))
|
|
345
|
1
|
if instrument is not None:
|
|
346
|
1
|
if instrument.upper() not in __valid_instruments__:
|
|
347
|
0
|
raise ValueError("Unrecognized instrument: %s" % instrument)
|
|
348
|
1
|
args.append(instrument)
|
|
349
|
1
|
if observation_class is not None:
|
|
350
|
0
|
if observation_class not in __valid_observation_class__:
|
|
351
|
0
|
raise ValueError("Unrecognized observation class: %s" % observation_class)
|
|
352
|
0
|
args.append(observation_class)
|
|
353
|
1
|
if observation_type is not None:
|
|
354
|
1
|
if observation_type not in __valid_observation_types__:
|
|
355
|
0
|
raise ValueError("Unrecognized observation type: %s" % observation_type)
|
|
356
|
1
|
args.append(observation_type)
|
|
357
|
1
|
if mode is not None:
|
|
358
|
0
|
if mode not in __valid_modes__:
|
|
359
|
0
|
raise ValueError("Unrecognized mode: %s" % mode)
|
|
360
|
0
|
args.append(mode)
|
|
361
|
1
|
if adaptive_optics is not None:
|
|
362
|
0
|
if adaptive_optics not in __valid_adaptive_optics__:
|
|
363
|
0
|
raise ValueError("Unrecognized adaptive optics: %s" % adaptive_optics)
|
|
364
|
0
|
args.append(adaptive_optics)
|
|
365
|
1
|
if program_text is not None:
|
|
366
|
0
|
kwargs["ProgramText"] = program_text
|
|
367
|
1
|
if objectname is not None:
|
|
368
|
0
|
kwargs["object"] = objectname
|
|
369
|
1
|
if raw_reduced is not None:
|
|
370
|
0
|
if raw_reduced not in __valid_raw_reduced__:
|
|
371
|
0
|
raise ValueError("Unrecognized raw/reduced setting: %s" % raw_reduced)
|
|
372
|
0
|
args.append(raw_reduced)
|
|
373
|
1
|
if orderby is not None:
|
|
374
|
0
|
kwargs["orderby"] = orderby
|
|
375
|
|
|
|
376
|
1
|
return self.query_raw(*args, **kwargs)
|
|
377
|
|
|
|
378
|
1
|
@class_or_instance
|
|
379
|
|
def query_raw(self, *args, **kwargs):
|
|
380
|
|
"""
|
|
381
|
|
perform flexible query against Gemini observations
|
|
382
|
|
|
|
383
|
|
This is a more flexible query method. This method will do special handling for
|
|
384
|
|
coordinates and radius if present in kwargs. However, for the remaining arguments
|
|
385
|
|
it assumes all of args are useable as query path elements. For kwargs, it assumes
|
|
386
|
|
all of the elements can be passed as name=value within the query path to Gemini.
|
|
387
|
|
|
|
388
|
|
This method does not do any validation checking or attempt to interperet the
|
|
389
|
|
values being passed, aside from coordinates and radius.
|
|
390
|
|
|
|
391
|
|
This method is most useful when the query_criteria and query_region do not
|
|
392
|
|
meet your needs and you can build the appropriate search in the website. When
|
|
393
|
|
you see the URL that is generated by the archive, you can translate that into
|
|
394
|
|
an equivalent python call with this method. For example, if the URL in the
|
|
395
|
|
website is:
|
|
396
|
|
|
|
397
|
|
https://archive.gemini.edu/searchform/RAW/cols=CTOWEQ/notengineering/GMOS-N/PIname=Hirst/NotFail
|
|
398
|
|
|
|
399
|
|
You can disregard NotFail, cols=x and notengineering. You would run this query as
|
|
400
|
|
|
|
401
|
|
query_raw('GMOS-N', PIname='Hirst')
|
|
402
|
|
|
|
403
|
|
Parameters
|
|
404
|
|
----------
|
|
405
|
|
args :
|
|
406
|
|
The list of parameters to be passed via the query path to the webserver
|
|
407
|
|
kwargs :
|
|
408
|
|
The dictionary of parameters to be passed by name=value within the query
|
|
409
|
|
path to the webserver. The ``orderby`` key value pair has a special
|
|
410
|
|
intepretation and is appended as a query parameter like the one used
|
|
411
|
|
in the archive website for sorting results.
|
|
412
|
|
|
|
413
|
|
Returns
|
|
414
|
|
-------
|
|
415
|
|
response : `~astropy.table.Table`
|
|
416
|
|
"""
|
|
417
|
1
|
url = self.url_helper.build_url(*args, **kwargs)
|
|
418
|
|
|
|
419
|
1
|
response = self._request(method="GET", url=url, data={}, timeout=180, cache=False)
|
|
420
|
|
|
|
421
|
1
|
js = response.json()
|
|
422
|
1
|
return _gemini_json_to_table(js)
|
|
423
|
|
|
|
424
|
1
|
def get_file(self, filename, *, download_dir='.', timeout=None):
|
|
425
|
|
"""
|
|
426
|
|
Download the requested file to the current directory
|
|
427
|
|
|
|
428
|
|
filename : str
|
|
429
|
|
Name of the file to download
|
|
430
|
|
download_dir : str, optional
|
|
431
|
|
Name of the directory to download to
|
|
432
|
|
timeout : int, optional
|
|
433
|
|
Timeout of the request in milliseconds
|
|
434
|
|
"""
|
|
435
|
0
|
url = "https://archive.gemini.edu/file/%s" % filename
|
|
436
|
0
|
local_filepath = os.path.join(download_dir, filename)
|
|
437
|
0
|
self._download_file(url=url, local_filepath=local_filepath, timeout=timeout)
|
|
438
|
|
|
|
439
|
|
|
|
440
|
1
|
def _gemini_json_to_table(json):
|
|
441
|
|
"""
|
|
442
|
|
takes a JSON object as returned from the Gemini archive webserver and turns it into an `~astropy.table.Table`
|
|
443
|
|
|
|
444
|
|
Parameters
|
|
445
|
|
----------
|
|
446
|
|
json : dict
|
|
447
|
|
A JSON object from the Gemini archive webserver
|
|
448
|
|
|
|
449
|
|
Returns
|
|
450
|
|
-------
|
|
451
|
|
response : `~astropy.table.Table`
|
|
452
|
|
"""
|
|
453
|
|
|
|
454
|
1
|
data_table = Table(masked=True)
|
|
455
|
|
|
|
456
|
1
|
for key in __keys__:
|
|
457
|
1
|
col_data = np.array([obj.get(key, None) for obj in json])
|
|
458
|
|
|
|
459
|
1
|
atype = str
|
|
460
|
|
|
|
461
|
1
|
col_mask = np.equal(col_data, None)
|
|
462
|
1
|
data_table.add_column(MaskedColumn(col_data.astype(atype), name=key, mask=col_mask))
|
|
463
|
|
|
|
464
|
1
|
return data_table
|
|
465
|
|
|
|
466
|
|
|
|
467
|
1
|
__keys__ = ["exposure_time",
|
|
468
|
|
"detector_roi_setting",
|
|
469
|
|
"detector_welldepth_setting",
|
|
470
|
|
"telescope",
|
|
471
|
|
"mdready",
|
|
472
|
|
"requested_bg",
|
|
473
|
|
"engineering",
|
|
474
|
|
"cass_rotator_pa",
|
|
475
|
|
"ut_datetime",
|
|
476
|
|
"file_size",
|
|
477
|
|
"types",
|
|
478
|
|
"requested_wv",
|
|
479
|
|
"detector_readspeed_setting",
|
|
480
|
|
"size",
|
|
481
|
|
"laser_guide_star",
|
|
482
|
|
"observation_id",
|
|
483
|
|
"science_verification",
|
|
484
|
|
"raw_cc",
|
|
485
|
|
"filename",
|
|
486
|
|
"instrument",
|
|
487
|
|
"reduction",
|
|
488
|
|
"camera",
|
|
489
|
|
"ra",
|
|
490
|
|
"detector_binning",
|
|
491
|
|
"lastmod",
|
|
492
|
|
"wavelength_band",
|
|
493
|
|
"data_size",
|
|
494
|
|
"mode",
|
|
495
|
|
"raw_iq",
|
|
496
|
|
"airmass",
|
|
497
|
|
"elevation",
|
|
498
|
|
"data_label",
|
|
499
|
|
"requested_iq",
|
|
500
|
|
"object",
|
|
501
|
|
"requested_cc",
|
|
502
|
|
"program_id",
|
|
503
|
|
"file_md5",
|
|
504
|
|
"central_wavelength",
|
|
505
|
|
"raw_wv",
|
|
506
|
|
"compressed",
|
|
507
|
|
"filter_name",
|
|
508
|
|
"detector_gain_setting",
|
|
509
|
|
"path",
|
|
510
|
|
"observation_class",
|
|
511
|
|
"qa_state",
|
|
512
|
|
"observation_type",
|
|
513
|
|
"calibration_program",
|
|
514
|
|
"md5",
|
|
515
|
|
"adaptive_optics",
|
|
516
|
|
"name",
|
|
517
|
|
"focal_plane_mask",
|
|
518
|
|
"data_md5",
|
|
519
|
|
"raw_bg",
|
|
520
|
|
"disperser",
|
|
521
|
|
"wavefront_sensor",
|
|
522
|
|
"gcal_lamp",
|
|
523
|
|
"detector_readmode_setting",
|
|
524
|
|
"phot_standard",
|
|
525
|
|
"local_time",
|
|
526
|
|
"spectroscopy",
|
|
527
|
|
"azimuth",
|
|
528
|
|
"release",
|
|
529
|
|
"dec"]
|
|
530
|
|
|
|
531
|
1
|
Observations = ObservationsClass()
|
lvalerom