lidarwind.data_operator.GetRestructuredData

class lidarwind.data_operator.GetRestructuredData(data, snr=False, status=True, n_prof=500, center=True, min_periods=30, n_std=2, check90=True)[source]

Data re-structurer

It prepares the data structure for using the wind retrieval modules.

Examples

>>> wind_prop = lidarwind.GetRestructuredData(merged_data)
Parameters:

  • data (xr.Dataset) – a xr.Dataset of pre-processed data

  • snr (bool, int, optional) – if an interger is given it is used to as threshold to filter the data based on the signal to noise ratio

  • status (bool, optional) – if true it filters the data using the status variable generated by the WindCube’s software

  • sProf (int, optional) – number of profiles used to calculate the anomaly for partially filter the second trip echoes (IT GOES TO FILTER MODULE)

  • center (bool, optional) – (IT GOES TO FILTER MODULE)

  • min_periods (int, optional) – (IT GOES TO FILTER MODULE)

  • n_std (int, optional) – size of the standard deviation window used to partially remove the second trip echoes (IT GOES TO FILTER MODULE)

  • check90 (bool, optional) – If True, it checks if the vertical observations are available. If False, the verification is ignored.

Returns:

object – an instance of the prepared for the retrieval

Return type:

object

__init__(data, snr=False, status=True, n_prof=500, center=True, min_periods=30, n_std=2, check90=True)[source]

Methods

__init__(data[, snr, status, n_prof, ...])

data_transform()

It creates an xr.DataArray from all slanted observations

data_transform_90()

It creates an xr.DataArray from all vertically pointing observations

get_coord_non_90()

It identifies and selects the slanted data

vertical_component_check(check90)