adam.io.RadarImage#

class adam.io.RadarImage[source]#

This class contains the basic data for predicting the lake-breeze front location from radar. It includes parameters for storing the radar data for later analysis in Py-ART and for inference in the lake-breeze prediction model.

Parameters:

  • pyart_object (pyart.core.Radar() or str) – The PyART radar object that stores the radar data. This could also be a link to the radar scan file (useful for batch processing to preserve memory).

  • lat_range (2-tuple) – The minimum and maximum latitude of the inference domain.

  • lon_range (2-tuple) – The minimum and maximum longitude of the inference domain.

  • grid_lat (ndarray) – The latitude of each point in the inference domain.

  • grid_lon (ndarray) – The longitude of each point in the inference domain.

  • pytorch_image (torch.Tensor()) – The tensor containing the preprocessed radar scan for inference.

  • lakebreeze_mask (256 x 256 ndarray) – The inferred lake breeze mask, where 1 = lakebreeze and 0 = not a lake breeze.

  • times (list of np.datetime64('s')) – The epoch time of the radar scans.

__init__()#

Methods

__init__()

aggregate([start_time, end_time])

This function aggregates the lake breeze mask over a specified time period.

Attributes

aggregated_mask

grid_lat

grid_lon

lakebreeze_mask

lat_range

lon_range

pyart_object

pytorch_image

times