def data_for_variable(self, variable, min_depth=None, max_depth=None):
"""
function to go through all the depth_from, depth_to, sensor combinations
for the given variable and yields ISMNTimeSeries if a match is found.
if min_depth and/or max_depth where given it only returns a
ISMNTimeSeries if depth_from >= min_depth and/or depth_to <= max_depth
Parameters
----------
variable: string
variable to read
one of
* 'soil moisture',
* 'soil temperature',
* 'soil suction',
* 'precipitation',
* 'air temperature',
* 'field capacity',
* 'permanent wilting point',
* 'plant available water',
* 'potential plant available water',
* 'saturation',
* 'silt fraction',
* 'snow depth',
* 'sand fraction',
* 'clay fraction',
* 'organic carbon',
* 'snow water equivalent',
* 'surface temperature',
* 'surface temperature quality flag original'
min_depth : float, optional
depth_from of variable has to be >= min_depth in order to be
included.
max_depth : float, optional
depth_to of variable has to be <= max_depth in order to be
included.
Returns
-------
time_series : iterator(ismn.readers.ISMNTimeSeries)
ISMNTimeSeries object containing data and metadata
"""
if min_depth is None:
min_depth = np.min(self.depth_from)
if max_depth is None:
max_depth = np.max(self.depth_to)
for var, d1, d2, filename in zip(self.variables, self.depth_from,
self.depth_to, self.filenames):
if var != variable:
continue
if ((d1 >= min_depth) & (d2 <= max_depth)):
yield readers.read_data(filename)
def read_ts(self, idx):
"""
read a time series directly by the id
Parameters
----------
idx : int
id into self.metadata, best one of those returned
from get_dataset_ids()
Returns
-------
timeseries : pandas.DataFrame
of the read data
"""
ts = readers.read_data(self.metadata['filename'][idx])
return ts.data
def data_import():
"""Creates a dictionary with longitude, latitude and soil moisture data
as values for each ISMN file located in ./data/ISMN_Filt .
The key of each dictionary entry is created as a combination of network
name, station name and sensor type.
Also a CSV file with each key and the corresponding coordinates (
latitude & longitude) is created in the directory ./data/
:return: Dictionary containing ISMN data.
"""
sm_files = [
f for f in glob.glob("./data/ISMN_Filt/**/*_sm_*.stm", recursive=True)
]
dict_ismn = {}
long = []
lat = []
station = []
for i in sm_files:
data = ismn.read_data(i)
header_elements, filename_elements = ismn.get_info_from_file(i)
dict_ismn[header_elements[1] + "-" + header_elements[2] + "-" +
header_elements[8]] = [
header_elements[3], header_elements[4], data.data
]
long.append(header_elements[3])
lat.append(header_elements[4])
station.append(header_elements[1] + "-" + header_elements[2] + "-" +
header_elements[8])
with open('./data/stations.csv', 'w', newline='') as csvfile:
filewriter = csv.writer(csvfile, delimiter=',')
filewriter.writerow(station)
filewriter.writerow(long)
filewriter.writerow(lat)
return dict_ismn
def read_variable(self,
variable,
depth_from=None,
depth_to=None,
sensor=None):
"""
actually reads the given variable from the file. Parameters are
required until any ambiguity is resolved. If there is only one depth for
the given variable then only variable is required. If there are multiple
depths at least depth_from is required. If there are multiple depth_to
possibilities for one variable-depth_from combination also depth_to has to
be specified. If 2 sensors are measuring the same variable in the same
depth then also the sensor has to be specified.
Parameters
----------
variable: string
variable to read
one of
* 'soil moisture',
* 'soil temperature',
* 'soil suction',
* 'precipitation',
* 'air temperature',
* 'field capacity',
* 'permanent wilting point',
* 'plant available water',
* 'potential plant available water',
* 'saturation',
* 'silt fraction',
* 'snow depth',
* 'sand fraction',
* 'clay fraction',
* 'organic carbon',
* 'snow water equivalent',
* 'surface temperature',
* 'surface temperature quality flag original'
depth_from : float, optional
shallower depth of layer the variable was measured at
depth_to : float, optional
deeper depth of layer the variable was measured at
sensor : string, optional
name of the sensor
Returns
-------
data : readers.ISMNTimeSeries
ISMNTimeSeries object containing the relevant metadata for the time series
as well as a .data pointing to a pandas.DataFrame
Raises
------
ISMNError:
if not all ambiguity was resolved by the given input parameters or
if no data was found for the given input parameters
"""
if depth_from is None:
depth_f, depth_t = self.get_depths(variable)
if depth_f.size > 1:
raise ISMNError("there are multiple depths for this variable"
"Please specify the one you want to read")
elif depth_f.size == 1:
depth_from = depth_f[0]
elif depth_f.size == 0:
raise ISMNError("there are no depths for this variable"
"Something went wrong")
if depth_to is None:
depth_f, depth_t = self.get_depths(variable)
if depth_t.size > 1:
raise ISMNError(
"there are multiple depths with the same depth_from value"
"Please specify the depth_to value you want to read")
elif depth_t.size == 1:
depth_to = depth_t[0]
elif depth_t.size == 0:
raise ISMNError("there are no depths for this variable"
"Something went wrong")
if sensor is None:
sensors = self.get_sensors(variable, depth_from, depth_to)
if sensors.size > 1:
raise ISMNError(
"there are multiple sensors for this combination of "
"variable, depth_to, depth_from. Please specify which one "
"you want to read")
elif sensors.size == 1:
sensor = sensors[0]
elif sensors.size == 0:
raise ISMNError(
"there are no sensors for this variable, depth_from, depth_to "
"combination. Please make sure you specified valid depths")
index_filename = np.where((variable == self.variables)
& (depth_from == self.depth_from)
& (depth_to == self.depth_to)
& (sensor == self.sensors))[0]
if index_filename.size != 1:
raise ISMNError(
"There is no data for this combination of variable, depth_from, "
"depth_to and sensor. Please check.")
else:
return readers.read_data(self.filenames[index_filename[0]])