def get_station_first_sm_layer(path, stationname):
"""
Get the metadata of the first soil moisture layer of this variable.
Parameters
----------
path: string
Folder in which the ISMN data is stored
stationname: string
Name of the station
Returns
-------
depth_from: float
depth_to: float
sensor: string
"""
iface = ISMN_Interface(path)
station = iface.get_station(stationname)
depths_from, depths_to = station.get_depths("soil moisture")
s_idx = np.argsort(depths_from)
depth_from = depths_from[s_idx[0]]
depth_to = depths_to[s_idx[0]]
sensor = station.get_sensors("soil moisture", depth_from, depth_to)
return depth_from, depth_to, sensor[0]
def get_station_data(path, stationname, variable,
depth_from, depth_to, sensor_id):
"""
Read the data from the ISMN dataset
Parameters
----------
path: string
Folder in which the ISMN data is stored
stationname: string
Name of the station
variable: string
Name of the variable to read
depth_from: string
starting depth of the variable
depth_to: string
end depth of the variable
sensor_id: string
Sensor id of the sensor to read
Returns
-------
ds: pandas.DataFrame
Data
"""
iface = ISMN_Interface(path)
station = iface.get_station(stationname)
ds = station.read_variable(variable.encode('ascii'),
float(depth_from),
float(depth_to),
sensor_id.encode('ascii'))
return ds.data[variable]
def get_station_start_end(path, stationname, variable,
depth_from, depth_to):
"""
Get the start and end date for the selected insitu time series.
Parameters
----------
path: string
Folder in which the ISMN data is stored
stationname: string
Name of the station
variable: string
Name of the variable to read
depth_from: string
starting depth of the variable
depth_to: string
end depth of the variable
Returns
-------
start: datetime
end: datetime
"""
iface = ISMN_Interface(path)
station = iface.get_station(stationname)
return station.get_min_max_obs_timestamp(variable=variable,
min_depth=depth_from,
max_depth=depth_to)
def read_ISMN(plot=False):
ismn_data_folder = os.path.join(
'.', 'data', 'Data_seperate_files_2011' + '1122_20121122_2364256_oqsd')
ISMN_reader = ISMN_Interface(ismn_data_folder)
network = 'IIT-KANPUR'
station = 'IITK-Airstrip'
station_obj = ISMN_reader.get_station(station)
print "Available Variables at Station %s" % station
#get the variables that this station measures
variables = station_obj.get_variables()
print variables
depths_from, depths_to = station_obj.get_depths(variables[0])
sensors = station_obj.get_sensors(variables[0], depths_from[0],
depths_to[0])
#read the data of the variable, depth, sensor combination
time_series = station_obj.read_variable(variables[0],
depth_from=depths_from[0],
depth_to=depths_to[0],
sensor=sensors[0])
#print information about the selected time series
print "Selected time series is:"
print time_series
#plot the data
time_series.plot()
#with pandas 0.12 time_series.plot() also works
plt.legend()
plt.show()
def read_ISMN(plot=False):
ismn_data_folder = os.path.join('.', 'data', 'Data_seperate_files_2011'+
'1122_20121122_2364256_oqsd')
ISMN_reader = ISMN_Interface(ismn_data_folder)
network = 'IIT-KANPUR'
station = 'IITK-Airstrip'
station_obj = ISMN_reader.get_station(station)
print "Available Variables at Station %s"%station
#get the variables that this station measures
variables = station_obj.get_variables()
print variables
depths_from,depths_to = station_obj.get_depths(variables[0])
sensors = station_obj.get_sensors(variables[0],depths_from[0],depths_to[0])
#read the data of the variable, depth, sensor combination
time_series = station_obj.read_variable(variables[0],depth_from=depths_from[0],depth_to=depths_to[0],sensor=sensors[0])
#print information about the selected time series
print "Selected time series is:"
print time_series
#plot the data
time_series.plot()
#with pandas 0.12 time_series.plot() also works
plt.legend()
plt.show()
def get_station_lonlat(path, stationname):
"""
Get the latitude and longitude coordinates from a station.
Parameters
----------
path: string
Folder in which the ISMN data is stored
stationname: string
Name of the station
Returns
-------
lon: float
lat: float
"""
iface = ISMN_Interface(path)
station = iface.get_station(stationname)
return station.longitude, station.latitude
def prepare_station_interface(path, stationname, variable,
depth_from, depth_to, sensor_id):
"""
Prepare an interface to the requested station data that
provides the data via a read_ts(id) function. This is at the moment
necessary since the ISMN interface does not follow the standards of
other interfaces.
Parameters
----------
path: string
Folder in which the ISMN data is stored
stationname: string
Name of the station
variable: string
Name of the variable to read
depth_from: string
starting depth of the variable
depth_to: string
end depth of the variable
sensor_id: string
Sensor id of the sensor to read
Returns
-------
iface: object
interface object which has a read_ts method
"""
iface = ISMN_Interface(path)
station = iface.get_station(stationname)
def read_ts(idx):
ds = station.read_variable(variable.encode('ascii'),
float(depth_from),
float(depth_to),
sensor_id.encode('ascii'))
return ds.data
station.read_ts = read_ts
return station
def variable_list(path, stationname):
"""
Goes through a downloaded ISMN dataset and reads the necessary metadata
needed for the viewer.
Parameters
----------
path: string
Folder in which the ISMN data is stored
stationname: string
Name of the station
Returns
-------
metadata: dict
Metadata dictionary.
"""
variables = []
iface = ISMN_Interface(path)
station = iface.get_station(stationname)
for i, var in enumerate(station.variables):
name = "{}_{:.2f}_{}".format(var,
station.depth_from[i],
station.sensors[i])
var_dict = {"quantityName": var,
"unit": "",
"depthFrom": station.depth_from[i],
"depthTo": station.depth_to[i],
"sensorId": station.sensors[i],
"variableName": name
}
variables.append(var_dict)
dmin, dmax = station.get_min_max_obs_timestamp()
vl = {"maxtime": dmax.date().isoformat(),
"mintime": dmin.date().isoformat(),
"originalTimeframeValid": False,
"variables": variables}
return vl
def ismn_metadata(path):
"""
Goes through a downloaded ISMN dataset and reads the necessary metadata
needed for the viewer.
Parameters
----------
path: string
Folder in which the ISMN data is stored
Returns
-------
metadata: dict
Metadata dictionary.
"""
metadata = {"Networks": []}
iface = ISMN_Interface(path)
for networkname in iface.list_networks():
network_dict = {
"networkID": networkname,
"network_abstract": "",
"network_status": "",
"network_country": "",
"network_continent": "",
"network_op_start": "",
"network_op_end": "",
"network_type": "project",
"network_constraints": "",
"network_reference": "",
"network_url_data": "",
"network_url": "",
"network_acknowledge": "",
"network_variables": "",
"network_depths": "",
"network_sensors": "",
"Stations": []}
metadata['Networks'].append(network_dict)
station_list = network_dict['Stations']
stations = iface.list_stations(network=networkname)
for stationname in stations:
station = iface.get_station(stationname, network=networkname)
dmin, dmax = station.get_min_max_obs_timestamp()
if dmin is None or dmax is None:
# No soil moisture measured at this station
continue
station_dict = {
"station_abbr": stationname,
"lat": station.latitude,
"lng": station.longitude,
"comment": None,
"stationID": stationname,
"extMetadata": None,
"station_name": stationname,
"variableText": '<br>'.join(np.unique(station.variables)),
"depthText": get_depth_text(station.depth_from,
station.depth_to,
station.variables),
"sensorText": '<br>'.join(np.unique(station.sensors)),
"maximum": dmax.isoformat(),
"minimum": dmin.isoformat()
}
station_list.append(station_dict)
return metadata
