def __init__(self, index=None, product=None, geopolygon=None, like=None, **search_terms):
""""Parses search terms in preparation for querying the Data Cube Index.
Create a :class:`Query` object by passing it a set of search terms as keyword arguments.
>>> query = Query(product='ls5_nbar_albers', time=('2001-01-01', '2002-01-01'))
Use by accessing :attr:`search_terms`::
>>> query.search_terms['time'] # doctest: +NORMALIZE_WHITESPACE
Range(begin=datetime.datetime(2001, 1, 1, 0, 0, tzinfo=<UTC>), \
end=datetime.datetime(2002, 1, 1, 0, 0, tzinfo=<UTC>))
By passing in an ``index``, the search parameters will be validated as existing on the ``product``.
Used by :meth:`datacube.Datacube.find_datasets` and :meth:`datacube.Datacube.load`.
:param datacube.index.Index index: An optional `index` object, if checking of field names is desired.
:param str product: name of product
:param geopolygon: spatial bounds of the search
:type geopolygon: geometry.Geometry or None
:param xarray.Dataset like: spatio-temporal bounds of `like` are used for the search
:param search_terms:
* `measurements` - list of measurements to retrieve
* `latitude`, `lat`, `y`, `longitude`, `lon`, `long`, `x` - tuples (min, max) bounding spatial dimensions
* `crs` - spatial coordinate reference system to interpret the spatial bounds
* `group_by` - observation grouping method. One of `time`, `solar_day`. Default is `time`
"""
self.product = product
self.geopolygon = query_geopolygon(geopolygon=geopolygon, **search_terms)
if 'source_filter' in search_terms and search_terms['source_filter'] is not None:
self.source_filter = Query(**search_terms['source_filter'])
else:
self.source_filter = None
remaining_keys = set(search_terms.keys()) - set(SPATIAL_KEYS + CRS_KEYS + OTHER_KEYS)
if index:
unknown_keys = remaining_keys - set(index.datasets.get_field_names())
# TODO: What about keys source filters, and what if the keys don't match up with this product...
if unknown_keys:
raise LookupError('Unknown arguments: ', unknown_keys)
self.search = {}
for key in remaining_keys:
self.search.update(_values_to_search(**{key: search_terms[key]}))
if like:
assert self.geopolygon is None, "'like' with other spatial bounding parameters is not supported"
self.geopolygon = getattr(like, 'extent', self.geopolygon)
if 'time' not in self.search:
time_coord = like.coords.get('time')
if time_coord is not None:
self.search['time'] = _time_to_search_dims(
(pandas_to_datetime(time_coord.values[0]).to_pydatetime(),
pandas_to_datetime(time_coord.values[-1]).to_pydatetime()
+ datetime.timedelta(milliseconds=1)) # TODO: inclusive time searches
)
def __init__(self,
index=None,
product=None,
geopolygon=None,
like=None,
**kwargs):
"""Parses a kwarg dict for query parameters
:param datacube.index._api.Index index: An optional `index` object, if checking of field names is desired.
:param str product: name of product
:param Union[datacube.utils.Geometry|None] geopolygon: spatial bounds of the search
:param xarray.Dataset like: spatio-temporal bounds of `like` are used for the search
:param kwargs:
* `measurements` - list of measurements to retrieve
* `latitude`, `lat`, `y`, `longitude`, `lon`, `long`, `x` - tuples (min, max) bounding spatial dimensions
* `crs` - spatial coordinate reference system to interpret the spatial bounds
* `group_by` - observation grouping method. One of 'time', 'solar_day'. Default is 'time'
"""
self.product = product
self.geopolygon = query_geopolygon(geopolygon=geopolygon, **kwargs)
if 'source_filter' in kwargs and kwargs['source_filter'] is not None:
self.source_filter = Query(**kwargs['source_filter'])
else:
self.source_filter = None
remaining_keys = set(
kwargs.keys()) - set(SPATIAL_KEYS + CRS_KEYS + OTHER_KEYS)
if index:
unknown_keys = remaining_keys - set(
index.datasets.get_field_names())
# TODO: What about keys source filters, and what if the keys don't match up with this product...
if unknown_keys:
raise LookupError('Unknown arguments: ', unknown_keys)
self.search = {}
for key in remaining_keys:
self.search.update(_values_to_search(**{key: kwargs[key]}))
if like:
assert self.geopolygon is None, "'like' with other spatial bounding parameters is not supported"
self.geopolygon = getattr(like, 'extent', self.geopolygon)
if 'time' not in self.search:
time_coord = like.coords.get('time')
if time_coord is not None:
self.search['time'] = _time_to_search_dims(
(pandas_to_datetime(
time_coord.values[0]).to_pydatetime(),
pandas_to_datetime(
time_coord.values[-1]).to_pydatetime() +
datetime.timedelta(milliseconds=1)
) # TODO: inclusive time searches
)
def _to_datetime(t):
if isinstance(t, (float, int)):
t = datetime.datetime.fromtimestamp(t, tz=tz.tzutc())
if isinstance(t, tuple):
t = datetime.datetime(*t, tzinfo=tz.tzutc())
elif isinstance(t, str):
try:
t = datetime.datetime.strptime(t, "%Y-%m-%dT%H:%M:%S.%fZ")
except ValueError:
pass
elif isinstance(t, datetime.datetime):
if t.tzinfo is None:
t = t.replace(tzinfo=tz.tzutc())
return t
return pandas_to_datetime(t, utc=True, infer_datetime_format=True).to_pydatetime()
def to_datetime(t):
if isinstance(t, compat.integer_types + (float,)):
t = datetime.datetime.fromtimestamp(t, tz=tz.tzutc())
if isinstance(t, tuple):
t = datetime.datetime(*t, tzinfo=tz.tzutc())
elif isinstance(t, compat.string_types):
try:
t = datetime.datetime.strptime(t, "%Y-%m-%dT%H:%M:%S.%fZ")
except ValueError:
pass
try:
from pandas import to_datetime as pandas_to_datetime
return pandas_to_datetime(t, utc=True, infer_datetime_format=True).to_pydatetime()
except ImportError:
pass
if isinstance(t, datetime.datetime):
if t.tzinfo is None:
t = t.replace(tzinfo=tz.tzutc())
return t
raise ValueError('Could not parse the time for {}'.format(t))
def to_datetime(t):
if isinstance(t, compat.integer_types + (float, )):
t = datetime.datetime.fromtimestamp(t, tz=tz.tzutc())
if isinstance(t, tuple):
t = datetime.datetime(*t, tzinfo=tz.tzutc())
elif isinstance(t, compat.string_types):
try:
t = datetime.datetime.strptime(t, "%Y-%m-%dT%H:%M:%S.%fZ")
except ValueError:
pass
try:
from pandas import to_datetime as pandas_to_datetime
return pandas_to_datetime(
t, utc=True, infer_datetime_format=True).to_pydatetime()
except ImportError:
pass
if isinstance(t, datetime.datetime):
if t.tzinfo is None:
t = t.replace(tzinfo=tz.tzutc())
return t
raise ValueError('Could not parse the time for {}'.format(t))
