profile_operation

Provides ProfileOperationRunner — the class that ProcessedDataset.apply_profile_operation() delegates to. Use it directly for finer control over trimming, bin-cutting, and regridding.

ProfileOperationRunner

import pyadps
from pyadps.processing.profile_operation import ProfileOperationRunner

ds = pyadps.read('deployment.000')
runner = ProfileOperationRunner(ds)

Operation Methods

All methods return self for chaining.

Method	Description
`trim_ensembles(start, end)`	Mask ensembles at the start and/or end of deployment
`cut_bins_side_lobe(orientation, water_depth, extra_cells=1)`	Mask cells contaminated by acoustic side-lobe interference
`cut_bins_manual(min_cell, max_cell, min_ensemble, max_ensemble)`	Mask a rectangular region by cell and ensemble index
`regrid(method='nearest', end_cell_option='cell', trimends=None, orientation=None, boundary_limit=0.0, data_vars=None, fill_value=np.nan)`	Interpolate from cell coordinates to a regular depth grid

Control and Output Methods

Method	Description
`reset()`	Restore working dataset to original state
`finalize()`	Return processed `xarray.Dataset`
`apply_pipeline(operations, order)`	Apply multiple operations from a configuration dict

Statistics Methods

Method	Description
`get_statistics()`	Dict of `QCCheckStats` keyed by operation name
`get_modifications()`	Dict of `DataModificationStats` keyed by variable name
`print_statistics()`	Print formatted operation summary table
`get_pipeline_report()`	Return `QCPipelineReport` for `ProcessedDataset`

Usage

runner = ProfileOperationRunner(ds)
ds_processed = (runner
    .trim_ensembles(start=100, end=50)
    .cut_bins_side_lobe(extra_cells=2)
    .regrid(method='linear')
    .finalize())

runner.print_statistics()

Non-Obvious Behaviors

QC must be done before regridding. Signal quality and velocity checks operate on the cell-based coordinate system. Once regrid() converts the dataset from (beam, cell, time) to (beam, depth, time), mask-based operations can no longer be applied. Always call regrid() last.

Side-lobe cut for downward-looking ADCPs requires water_depth to determine the valid range. Upward-looking ADCPs auto-detect the range from the surface reflection.

# Upward-looking: auto-detects orientation
runner.cut_bins_side_lobe(extra_cells=2)

# Downward-looking: supply water column depth in metres
runner.cut_bins_side_lobe(orientation='down', water_depth=150.0, extra_cells=2)

Config-based use. When running from a config.ini, apply_pipeline() applies all operations in the specified order:

runner.apply_pipeline(
    operations={
        'trim_ensembles': {'start': 100, 'end': 50},
        'cut_bins_side_lobe': {'extra_cells': 2},
        'regrid': {'method': 'linear'},
    },
    order=['trim_ensembles', 'cut_bins_side_lobe', 'regrid']
)

profile_operation