pysiral.l3proc.alg.statistics

Attributes

__author__

Classes

`Level3ValidSeaIceFreeboardCount`	A Level-3 processor item to count valid sea ice freeboard values.
`Level3SurfaceTypeStatistics`	A Level-3 processor item to compute surface type stastics
`Level3TemporalCoverageStatistics`	A Level-3 processor item to compute temporal coverage statistics of sea-ice thickness in the grid period
`Level3GriddedClassifiers`	A Level-3 processor item to provide gridded classifiers (for different surface types)

Module Contents

pysiral.l3proc.alg.statistics.__author__ = 'Stefan Hendricks <stefan.hendricks@awi.de>'

class pysiral.l3proc.alg.statistics.Level3ValidSeaIceFreeboardCount(*args, **kwargs)

Bases: pysiral.l3proc.Level3ProcessorItem

A Level-3 processor item to count valid sea ice freeboard values. This class should be used for very limited l2i outputs files that do not have the surface_type variable necessary for Level3SurfaceTypeStatistics

required_options = []

l2_variable_dependencies = []

l3_variable_dependencies = ['sea_ice_freeboard']

l3_output_variables

apply(): Computes the number of valid sea_ice_freeboard values

class pysiral.l3proc.alg.statistics.Level3SurfaceTypeStatistics(*args, **kwargs)

Bases: pysiral.l3proc.Level3ProcessorItem

A Level-3 processor item to compute surface type stastics

required_options = []

l2_variable_dependencies = ['surface_type']

l3_variable_dependencies = []

l3_output_variables

_surface_type_dict

apply()

Computes the mandatory surface type statistics on the surface type stack flag

The current list

is_land (land flag exists in l2i stack)
n_total_waveforms (size of l2i stack)
n_valid_waveforms (tagged as either lead, sea ice or ocean )
valid_fraction (n_valid/n_total)
lead_fraction (n_leads/n_valid)
ice_fraction (n_ice/n_valid)
ocean_fraction (n_ocean/n_valid)
negative thickness fraction (n_sit<0 / n_sit)

class pysiral.l3proc.alg.statistics.Level3TemporalCoverageStatistics(*args, **kwargs)

Bases: pysiral.l3proc.Level3ProcessorItem

A Level-3 processor item to compute temporal coverage statistics of sea-ice thickness in the grid period

required_options = []

l2_variable_dependencies = ['time', 'sea_ice_thickness']

l3_variable_dependencies = []

l3_output_variables

apply(): Computes statistics of the temporal coverage of sea ice thickness :return:

class pysiral.l3proc.alg.statistics.Level3GriddedClassifiers(*args, **kwargs)

Bases: pysiral.l3proc.Level3ProcessorItem

A Level-3 processor item to provide gridded classifiers (for different surface types)

required_options = ['parameters', 'surface_types', 'statistics']

l2_variable_dependencies = ['surface_type']

l3_variable_dependencies = []

l3_output_variables

_surface_type_dict

_stat_functions

apply(): Mask certain parameters based on condition of one other parameter :return:

_compute_grid_variable(parameter_name, classifier_stack, surface_type, target_surface_type, statistic): Computes gridded surface type statistics for all grid cells :param parameter_name: The name of the classifier (for output name generation) :param classifier_stack: The Level-2 stack for the given classifier :param surface_type: The Level-2 stack of surface type :param target_surface_type: The name of the target surface type :param statistic: The name of the statistic to be computed :return: