enrich

enrich(
    patch: Patch ,
    inventory: Inventory ,
    attrs: bool | tuple[bool, tuple[str, …]] = True,
    coords: bool | tuple[bool, tuple[str, …]] = True,
    acquisition_key: str | None[str, None] = None,
    time = None,
    on_missing: Literal[‘raise’, ‘warn’, ‘ignore’, ‘null’] = raise,
    conflict: Literal[‘drop’, ‘raise’, ‘keep_first’] = keep_first,
)-> ‘PatchType’

Copy inventory metadata onto a patch.

The patch resolves its inventory context from its acquisition_key and its time, then the acquisition’s channel map places each channel on the optical path so the path’s tracks can be projected onto it. The patch keeps no reference to the inventory afterwards.

Parameters

Parameter	Description
patch	The patch to enrich.
inventory	The inventory to resolve against.
attrs	True (the default) to copy the observing-system facts the inventory is authoritative for, a tuple of names to copy exactly those, or False to copy none. The blanket form excludes `data_type`, `data_category`, and `data_units`, which describe the data as it now stands, and `sample_rate` and `spatial_interval`, which the patch’s own coordinates already state; naming one restores the as-acquired value.
coords	True (the default) to add the geometry axes and annotation groups of the resolved optical path, a tuple of names to add exactly those, or False to add none. Names may be `distance` for optical distance, a coordinate label the inventory’s CRS defines, an annotation group, or a qualified track field such as `coupling.medium`.
acquisition_key	The inventory identity to resolve, for a patch which does not carry one. Given both, the patch and this argument must agree.
time	The instant to resolve at, for a patch whose time axis is not physical. A patch with a real time coordinate resolves at its own time and passing this raises.
on_missing	What to do when an explicitly requested name is one the inventory does not define: “raise” (the default), “warn” to say so and leave it off, “ignore” to leave it off silently, or “null” to fill the dtype-appropriate missing marker so the name is present either way. Blanket requests copy what is applicable and never trigger it, and per-channel coverage gaps are always missing values rather than errors.
conflict	Indicates how to handle conflicts in attributes other than those indicated by dim (eg tag, history, acquisition_key, etc). If “drop” simply drop conflicting attributes, or attributes not shared by all models. If “raise” raise an [AttributeMergeError](`dascore.exceptions.AttributeMergeError`] when issues are encountered. If “keep_first”, just keep the first value for each attribute. Enrichment combines the inventory’s values with the patch’s own, so the default `keep_first` lets the inventory win and re-enriching is a refresh. `raise` is the misresolution guard: a header disagreeing with the resolved acquisition usually means the `acquisition_key` resolved to the wrong place.

Examples

import dascore as dc
from dascore.examples import inventory_patch_pair

patch, inventory = inventory_patch_pair()
# Copy everything applicable.
enriched = patch.enrich(inventory)
# Or name what is wanted.
enriched = patch.enrich(
    inventory, attrs=("gauge_length",), coords=("x", "y", "z"),
)