variable

Classes

Variable

Bases: BaseModel

Attributes

attrs class-attribute instance-attribute

attrs: VariableAttributes = Field(
    description="The attrs section is where variable-specific metadata are stored. This metadata is incredibly important for data users, and we recommend including several properties for each variable in order to have the greatest impact. In particular, we recommend adding the 'units', 'long_name', and 'standard_name' attributes, if possible."
)

data class-attribute instance-attribute

data: Optional[Any] = Field(
    description="If the variable is not meant to be retrieved from an input dataset and the value is known in advance, then the 'data' property should specify its value exactly as it should appear in the output dataset. This is commonly used for latitude/longitude/altitude data for datasets measured from a specific geographical location."
)

dims class-attribute instance-attribute

dims: List[StrictStr] = Field(
    unique_items=True,
    description="A list of coordinate variable names that dimension this data variable. Most commonly this will be set to ['time'], but for datasets where there are multiple dimensions (e.g., ADCP data measuring current velocities across time and several depths, it may look like ['time', 'depth']).",
)

dtype class-attribute instance-attribute

dtype: StrictStr = Field(
    description="The numpy dtype of the underlying data. This is passed to numpy as the 'dtype' keyword argument used to initialize an array (e.g., `numpy.array([1.0, 2.0], dtype='float')`). Commonly-used values include 'float', 'int', 'long'."
)

name class-attribute instance-attribute

name: str = Field(
    "", regex="^[a-zA-Z0-9_\\(\\)\\/\\[\\]\\{\\}\\.]+$"
)

Should be left empty. This property will be set automatically by the data_vars or coords pydantic model upon instantiation.

Functions

set_default_fill_value

set_default_fill_value(
    attrs: VariableAttributes, values: Dict[str, Any]
) -> VariableAttributes

Source code in tsdat/config/variables/variable.py

@validator("attrs")
def set_default_fill_value(
    cls, attrs: VariableAttributes, values: Dict[str, Any]
) -> VariableAttributes:
    dtype: str = values["dtype"]
    if (
        "fill_value" in attrs.__fields_set__  # Preserve _FillValues set explicitly
        or (dtype == "str")
        or ("datetime" in dtype)
    ):
        return attrs
    attrs.fill_value = np.array([-9999.0], dtype=dtype)[0]  # type: ignore
    return attrs