accessors

Domain-specific methods attached to xarray.Dataset objects via the xarray accessor pattern. Accessors are automatically registered when you import pyadps — no additional import is needed.

Three accessor namespaces are available on any Dataset returned by the read functions:

Namespace	Description
`ds.header.*`	File structure and integrity checks
`ds.fixed_leader.*`	System configuration and validation
`ds.variable_leader.*`	Sensor data analysis and diagnostics

Quick Example

import pyadps

# include_header=True is required for ds.header.* — it defaults to False
ds = pyadps.read('deployment.000', include_header=True)

# File integrity
ds.header.check_file()

# System configuration
config = ds.fixed_leader.system_configuration()
print(config['Frequency'])

# Timestamp validation
ds.variable_leader.validate_timestamps()

ds.header

Method	Description
`check_file()`	Verify file size, byte uniformity, and data type consistency
`get_available_data_types(ens=0)`	List data types present in the file
`has_data_type(name)`	Check whether a specific data type exists
`get_ensemble_info(ensemble)`	Byte size and data types for a specific ensemble
`validate()`	Full validation report
`summary()`	Print formatted header summary

ds.fixed_leader

Method	Description
`system_configuration(ens=-1)`	Frequency, beam pattern, orientation, beam angle
`coordinate_transformation(ens=0)`	Coordinate system, tilt correction, bin mapping
`sensor_info(ens=0, field='source')`	Sensor availability and source selection
`is_uniform()`	Check each field is consistent across all ensembles
`validate()`	Full validation report
`summary()`	Print formatted configuration summary

ds.variable_leader

Method	Description
`validate_timestamps()`	Check timestamp plausibility and return time range
`get_time_interval()`	Modal time interval between ensembles
`is_time_regular(tolerance_s=1.0)`	Check whether the time axis is uniform
`get_time_interval_frequency()`	Distribution of all observed intervals
`get_time_component_frequency(component)`	Frequency count for a time component (e.g. `'minute'`)
`ensemble_continuity_check()`	Detect gaps in ensemble numbering
`ensemble_rollover_count()`	Count 16-bit ensemble counter wraparounds
`bit_result_summary()`	Decode Built-In Test result bits across all ensembles
`error_status_word_summary()`	Decode all four Error Status Words
`summary()`	Print formatted variable leader summary

See Also

binary_reader — Functions that return accessor-enabled Datasets
pd0_parser — Low-level access (no accessors available)