pysiral.l2proc.procsteps

@author: Stefan Hendricks

Classes

`Level2ProcessorStep`	Parent class for any Level-2 processor step class, which may be distributed over the
`Level2ProcessorStepOrder`	A container providing the ordered list of processing steps
`L1BL2TransferVariables`	Level-2 Processor step class to transfer variables from the
`L2ApplyRangeCorrections`	Level-2 processing step class for applying geophysical range corrections to the elevations
`CS2InstrumentModeflag`	A class creating an instrument_mode flag from radar_mode:
`ParameterRollingStatistics`	This class add rolling statistics (mean, sdev) using the pandas rolling
`TransferWaveform2L2`	This class adds the waveform and associated parameters (range, valid_flag)

Module Contents

class pysiral.l2proc.procsteps.Level2ProcessorStep(cfg)

Bases: pysiral.core.legacy_classes.DefaultLoggingClass

Parent class for any Level-2 processor step class, which may be distributed over the different pysiral modules.

This class also serves as a template for all subclasses. Mandatory methods and properties in this class which raise a NotImplementedException must be overwritten by the subclass

cfg

msgs = []

error_flag_bit_dict

execute(l1b: pysiral.l1data.Level1bData, l2: pysiral.l2data.Level2Data) → None: The main entry point for the :param l1b: :param l2: :return:

update_error_flag(l2, error_status)

Add the error_flag of the processing step to the

Param:: l2: The Level-2 data container
Param:: error_status: An array with the shape of l2.records containing the error flag (False: nominal, True: error)
Returns:

abstractmethod execute_procstep(l1b, l2)

static get_clean_error_status(shape): Return an empty (all nominal error status array) :param shape: :return:

property classname

abstract property error_bit

abstract property l2_input_vars

abstract property l2_output_vars

class pysiral.l2proc.procsteps.Level2ProcessorStepOrder(cfg)

Bases: pysiral.core.legacy_classes.DefaultLoggingClass

A container providing the ordered list of processing steps as initialized classes for each trajectory

cfg

_classes = []

get_procstep_classes(): Retrieves the required classes from the processor definition files and stores them in a list without initializing them. This way a freshly initialized version can be supplied to each l2 data object without risk of interference of class properties :return:

get_algorithm_error_flag_bit(procstep_module): Return the corresponding bit (0-15) for the procstep module :param procstep_module: str :return:

validate() → bool: Checkout the difference processing steps and validate input/output variables in the order of the steps :return:

property class_list: Return a list of not initialized classes (class instances with the options from the level-2 :return:

property class_instances: Return a list of initialized classes (class instances with the options from the level-2 processor definition file passed to the class instance) :return:

class pysiral.l2proc.procsteps.L1BL2TransferVariables(*args, **kwargs)

Bases: Level2ProcessorStep

Level-2 Processor step class to transfer variables from the l1b to the l2 data object

execute_procstep(l1b, l2): Mandatory method of Level-2 processor :param l1b: :param l2: :return: error_status

property l2_input_vars

property l2_output_vars

property error_bit

class pysiral.l2proc.procsteps.L2ApplyRangeCorrections(*args, **kwargs)

Bases: Level2ProcessorStep

Level-2 processing step class for applying geophysical range corrections to the elevations

execute_procstep(l1, l2): Mandatory method of Level-2 processor :param l1: :param l2: :return: error_status

static fill_nan_gaps(range_correction: numpy.typing.NDArray, extrapolate: bool = True) → numpy.typing.NDArray

Fills gaps in range correction. If the range correction is all-NaN, just return zeros

Parameters:

range_correction
extrapolate

Returns:

property target_variables: Return target variables from config file or default value :return:

property l2_input_vars

property l2_output_vars

property error_bit

class pysiral.l2proc.procsteps.CS2InstrumentModeflag(*args, **kwargs)

Bases: Level2ProcessorStep

A class creating an instrument_mode flag from radar_mode:

instrument_mode = radar_mode + 1

execute_procstep(l1b, l2): Mandatory method of Level-2 processor :param l1b: :param l2: :return: error_status

property l2_input_vars

property l2_output_vars

property error_bit

class pysiral.l2proc.procsteps.ParameterRollingStatistics(*args, **kwargs)

Bases: Level2ProcessorStep

This class add rolling statistics (mean, sdev) using the pandas rolling framework to the Level-2 data object.

module: l2proc.procsteps pyclass: ParameterRollingStatistics options:

window_size_m: <maximum size of the marginal ice zone> statistics: [ <list of statistics: “mean” | “sdev”] input_parameters:

<l2_parameter-01>

<l2_parameter-02>

…

For each parameter & statistics combination a new parameter will be added with the naming convention:

<source_parameter_name>_rolling_<statistics_id>

e.g.

module: l2proc.procsteps pyclass: ParameterRollingStatistics options:

window_size_m: 25000. statistics: [“sdev”] input_parameters:

pulse_peakiness

will add the parameter pulse_peakiness_rolling_sdev to the list of l2 (auxiliary) data parameters.

execute_procstep(l1: pysiral.l1data.Level1bData, l2: pysiral.l2data.Level2Data) → numpy.ndarray

API method for Level2ProcessorStep subclasses. Computes and add rolling statistics based on the processor item options in the Level-2 processor definition file.

Parameters:

l1 – Level-1 data object
l2 – Level-2 data object

Raises:

None –

Returns:

error_status

property statistics_combinations

property l2_input_vars

property l2_output_vars

property error_bit

class pysiral.l2proc.procsteps.TransferWaveform2L2(*args, **kwargs)

Bases: Level2ProcessorStep

This class adds the waveform and associated parameters (range, valid_flag) to the l2 data container

module: l2proc.procsteps pyclass: TransferWaveform2L2 options: {}

execute_procstep(l1: pysiral.l1data.Level1bData, l2: pysiral.l2data.Level2Data) → numpy.ndarray

API method for Level2ProcessorStep subclasses. Computes and add rolling statistics based on the processor item options in the Level-2 processor definition file.

Parameters:

l1 – Level-1 data object
l2 – Level-2 data object

Raises:

None –

Returns:

error_status

property statistics_combinations

property l2_input_vars

property l2_output_vars

property error_bit