def from_M2D2(wmm_id,
primary_ano=None,
primary_vane=None,
start_date=None,
end_date=None):
'''Download mast data and metadata from the met data database M2D2 (EDF specific). Currently
this is only the 10-minute average of each installed sensor. Will add standard deviation, maximum, and
minimum in the future.
:Parameters:
wmm_id: int
Wind met mast id number in M2D2.
To get a list of masts in M2D2 run the following::
import anemoi as an
m2d2 = an.io.database.M2D2()
m2d2.get_masts()
primary_ano: string; default None
Primary anemomter sensor name
primary_vane: string; default None
Primary wind vane sensor name
start_date: string; default None
Begining of the desired data period.
If None, first available day is assumed.
Date format: 'yyyy-mm-dd' ex:'2017-01-31'
end_date: string; default None
End of the desired data period.
If None, present day is assumed from you computers clock.
Date format: 'yyyy-mm-dd' ex:'2017-01-31'
http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases
:Returns:
out: an.MetMast object
'''
M2D2 = an.io.database.M2D2()
mast_metadata = M2D2.get_wmm_id_metadata(wmm_id)
lat = mast_metadata.loc[0, 'WMM_Latitude']
lon = mast_metadata.loc[0, 'WMM_Longitude']
elev = mast_metadata.loc[0, 'WMM_Elevation']
mast_data = M2D2.get_wmm_id_data(wmm_id,
start_date=start_date,
end_date=end_date)
mast = an.MetMast(data=mast_data,
elev=elev,
lat=lat,
lon=lon,
name=wmm_id)
return mast
def return_test_mast():
index = pd.date_range(start='2000-01-01', periods=52596, freq='10min')
sensors = [
'T_78_AVG', 'T_4_AVG', 'SPD_79_NW_AVG', 'SPD_79_SW_AVG',
'SPD_76_NW_AVG', 'SPD_57_NW_AVG', 'SPD_57_SW_AVG', 'SPD_34_NW_AVG',
'SPD_34_SW_AVG', 'DIR_76_AVG', 'DIR_30_AVG'
]
mast_data = pd.DataFrame(index=index,
columns=sensors,
data=np.random.randn(len(index), len(sensors)))
mast_data.columns.name = 'sensor'
mast = an.MetMast(name=1,
data=mast_data,
lat=45,
lon=-90,
primary_ano='SPD_79_NW_AVG',
primary_vane='DIR_76_AVG')
return mast
def from_parquet_files(filename_data, filename_metadata):
data = pd.read_parquet(filename_data)
metadata = pd.read_parquet(filename_metadata).T
name = metadata.columns[0]
lat = metadata.loc['lat', name]
lon = metadata.loc['lon', name]
elev = metadata.loc['elev', name]
height = metadata.loc['height', name]
primary_ano = metadata.loc['primary_ano', name]
primary_vane = metadata.loc['primary_vane', name]
mast = an.MetMast(data=data,
name=name,
lat=lat,
lon=lon,
elev=elev,
height=height,
primary_ano=primary_ano,
primary_vane=primary_vane)
return mast
def mast_from_wmm_id(self, wmm_id):
'''Download an.MetMast from M2D2
:Parameters:
wmm_id: int
Mast ID (wmm_id) in M2D2
:Returns:
out: an.MetMast with data and metadata from M2D2
'''
print(f'Downloading Mast {wmm_id} from M2D2')
data = self.data_from_mast_wmm_id(wmm_id=wmm_id)
metadata = self.metadata_from_mast_wmm_id(wmm_id=wmm_id)
mast = an.MetMast(data=data,
name=wmm_id,
lat=metadata.WMM_Latitude[0],
lon=metadata.WMM_Longitude[0],
elev=metadata.WMM_Elevation[0])
return mast