def _parse_sites(points, res_file=None):
"""Parse project points from list or slice
Parameters
----------
points : str | pd.DataFrame | slice | list
Slice specifying project points, string pointing to a project
points csv, or a dataframe containing the effective csv contents.
res_file : str | NoneType
Optional resource file to find maximum length of project points if
points slice stop is None.
Returns
-------
df : pd.DataFrame
DataFrame mapping sites (gids) to SAM technology (config)
"""
df = pd.DataFrame(columns=['gid', 'config'])
if isinstance(points, (list, tuple)):
# explicit site list, set directly
df['gid'] = points
elif isinstance(points, slice):
stop = points.stop
if stop is None:
if res_file is None:
raise ValueError('Must supply a resource file if '
'points is a slice of type '
' slice(*, None, *)')
multi_h5_res, _ = check_res_file(res_file)
if multi_h5_res:
stop = MultiFileResource(res_file).shape[1]
else:
stop = Resource(res_file).shape[1]
df['gid'] = list(range(*points.indices(stop)))
else:
raise TypeError('Project Points sites needs to be set as a list, '
'tuple, or slice, but was set as: {}'.format(
type(points)))
df['config'] = None
return df
def regions(cls,
regions,
res_file,
sam_config,
tech=None,
curtailment=None):
"""
Generate ProjectPoints for gids nearest to given latitude longitudes
Parameters
----------
regions : dict
Dictionary of regions to extract points for in the form:
{'region': 'region_column'}
res_file : str
Resource file, needed to fine nearest neighbors
sam_config : dict | str | list | SAMConfig
SAM input configuration ID(s) and file path(s). Keys are the SAM
config ID(s), top level value is the SAM path. Can also be a single
config file str. If it's a list, it is mapped to the sorted list
of unique configs requested by points csv. Can also be a
pre loaded SAMConfig object.
tech : str, optional
SAM technology to analyze (pvwattsv7, windpower, tcsmoltensalt,
solarwaterheat, troughphysicalheat, lineardirectsteam)
The string should be lower-cased with spaces and _ removed,
by default None
curtailment : NoneType | dict | str | config.curtailment.Curtailment
Inputs for curtailment parameters. If not None, curtailment inputs
are expected. Can be:
- Explicit namespace of curtailment variables (dict)
- Pointer to curtailment config json file with path (str)
- Instance of curtailment config object
(config.curtailment.Curtailment)
Returns
-------
pp : ProjectPoints
Initialized ProjectPoints object for points nearest to given
lat_lons
"""
multi_h5_res, hsds = check_res_file(res_file)
if multi_h5_res:
res_cls = MultiFileResourceX
else:
res_cls = ResourceX
logger.info('Extracting ProjectPoints for desired regions')
points = []
with res_cls(res_file, hsds=hsds) as f:
meta = f.meta
for region, region_col in regions.items():
logger.debug('- {}: {}'.format(region_col, region))
# pylint: disable=no-member
gids = f.region_gids(region, region_col=region_col)
logger.debug('- Resource gids:\n{}'.format(gids))
if points:
duplicates = np.intersect1d(gids, points).tolist()
if duplicates:
msg = ('reV Cannot currently handle duplicate '
'Resource gids! The given regions containg the '
'same gids:\n{}'.format(duplicates))
logger.error(msg)
raise RuntimeError(msg)
points.extend(gids.tolist())
pp = cls(points,
sam_config,
tech=tech,
res_file=res_file,
curtailment=curtailment)
meta = meta.loc[pp.sites]
cols = list(set(regions.values()))
for c in cols:
pp._df[c] = meta[c].values
return pp
def lat_lon_coords(cls,
lat_lons,
res_file,
sam_config,
tech=None,
curtailment=None):
"""
Generate ProjectPoints for gids nearest to given latitude longitudes
Parameters
----------
lat_lons : str | tuple | list | ndarray
Pair or pairs of latitude longitude coordinates
res_file : str
Resource file, needed to fine nearest neighbors
sam_config : dict | str | list | SAMConfig
SAM input configuration ID(s) and file path(s). Keys are the SAM
config ID(s), top level value is the SAM path. Can also be a single
config file str. If it's a list, it is mapped to the sorted list
of unique configs requested by points csv. Can also be a
pre loaded SAMConfig object.
tech : str, optional
SAM technology to analyze (pvwattsv7, windpower, tcsmoltensalt,
solarwaterheat, troughphysicalheat, lineardirectsteam)
The string should be lower-cased with spaces and _ removed,
by default None
curtailment : NoneType | dict | str | config.curtailment.Curtailment
Inputs for curtailment parameters. If not None, curtailment inputs
are expected. Can be:
- Explicit namespace of curtailment variables (dict)
- Pointer to curtailment config json file with path (str)
- Instance of curtailment config object
(config.curtailment.Curtailment)
Returns
-------
pp : ProjectPoints
Initialized ProjectPoints object for points nearest to given
lat_lons
"""
lat_lons = cls._parse_lat_lons(lat_lons)
multi_h5_res, hsds = check_res_file(res_file)
if multi_h5_res:
res_cls = MultiFileResourceX
res_kwargs = {}
else:
res_cls = ResourceX
res_kwargs = {'hsds': hsds}
logger.info('Converting latitude longitude coordinates into nearest '
'ProjectPoints')
logger.debug('- (lat, lon) pairs:\n{}'.format(lat_lons))
with res_cls(res_file, **res_kwargs) as f:
gids = f.lat_lon_gid(lat_lons) # pylint: disable=no-member
if len(gids) != len(np.unique(gids)):
uniques, pos, counts = np.unique(gids,
return_counts=True,
return_inverse=True)
duplicates = {}
for idx in np.where(counts > 1)[0]:
duplicate_lat_lons = lat_lons[np.where(pos == idx)[0]]
duplicates[uniques[idx]] = duplicate_lat_lons
msg = ('reV Cannot currently handle duplicate Resource gids! The '
'given latitude and longitudes map to the same gids:\n{}'.
format(duplicates))
logger.error(msg)
raise RuntimeError(msg)
gids = gids.tolist()
logger.debug('- Resource gids:\n{}'.format(gids))
pp = cls(gids,
sam_config,
tech=tech,
res_file=res_file,
curtailment=curtailment)
if 'points_order' in pp.df:
lat_lons = lat_lons[pp.df['points_order'].values]
pp._df['latitude'] = lat_lons[:, 0]
pp._df['longitude'] = lat_lons[:, 1]
return pp
