mt_metadata.processing.time_series_decimation

Classes

MethodEnum	str(object='') -> str
TimeSeriesDecimation	Base class for all metadata objects with Pydantic validation.

Module Contents

class mt_metadata.processing.time_series_decimation.MethodEnum

Bases: mt_metadata.common.enumerations.StrEnumerationBase

str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to ‘utf-8’. errors defaults to ‘strict’.

default = 'default'

other = 'other'

class mt_metadata.processing.time_series_decimation.TimeSeriesDecimation(**data)

Bases: mt_metadata.base.MetadataBase

Base class for all metadata objects with Pydantic validation.

MetadataBase extends DotNotationBaseModel (which inherits from Pydantic’s BaseModel) to provide automatic validation according to metadata standards. It adds functionality beyond dictionaries, supporting JSON, XML, pandas Series, and other formats for metadata interchange.

_skip_equals

Private attribute listing fields to skip in equality comparisons

Type:

list[str]

_fields

Private attribute caching field information

Type:

dict[str, Any]

Notes

• All field assignments are validated automatically via Pydantic

• None values are converted to appropriate defaults (empty string or 0.0)

• Supports nested attribute access via dot notation

• Thread-safe for read operations after initialization

level: Annotated[int | None, Field(default=None, description='Decimation level, must be a non-negative integer starting at 0', alias=None, json_schema_extra={'units': None, 'required': True, 'examples': ['0']})]

factor: Annotated[float, Field(default=1.0, description='Decimation factor between parent sample rate and decimated time series sample rate.', alias=None, json_schema_extra={'units': None, 'required': True, 'examples': ['4.0']})]

method: Annotated[MethodEnum, Field(default=MethodEnum.default, description='Type of decimation', alias=None, json_schema_extra={'units': '', 'required': True, 'examples': ['default']})]

sample_rate: Annotated[float, Field(default=1.0, description='Sample rate of the decimation level data (after decimation).', alias=None, json_schema_extra={'units': 'samples per second', 'required': True, 'examples': ['256']})]

anti_alias_filter: Annotated[str | None, Field(default='default', description='Type of anti alias filter for decimation.', alias=None, json_schema_extra={'units': None, 'required': True, 'examples': ['default']})]

classmethod check_level(values)

Check that level is a non-negative integer and set anti_alias_filter for level 0.