brails.types.asset_inventory module

This module defines classes associated with asset inventories.

AssetInventory()	A class representing a Asset Inventory.
Asset(asset_id, coordinates[, features])	A data structure for an asset that holds it coordinates and features.

class brails.types.asset_inventory.Asset(asset_id: str | int, coordinates: list[list[float]], features: dict[str, Any] | None = None)

Bases: object

A data structure for an asset that holds it coordinates and features.

Attributes:

asset_id (str|int):: Unique identifier for the asset. coordinates (list[List[float]]): A list of coordinate pairs

[[lon1, lat1], [lon2, lat2], …, [lonN, latN]].

features (dict[str, any]): A dictionary of features (attributes) for

the asset.

Methods:

add_features(additional_features: dict[str, any],

overwrite: bool = True): Update the existing features in the asset.

print_info(): Print the coordinates and features of the asset.

add_features(additional_features: dict, overwrite: bool = True)

Update the existing features in the asset.

Args:

additional_features (dict[str, any]): New features to merge into

the asset’s features.

overwrite (bool, optional): Whether to overwrite existing features.

Defaults to True.

print_info()

Print the coordinates and features of the asset.

class brails.types.asset_inventory.AssetInventory

Bases: object

A class representing a Asset Inventory.

Attributes:

inventory (dict): The inventory stored in a dict accessed by asset_id

Methods:

print_info(): Print the asset inventory. add_asset(asset_id, Asset): Add an asset to the inventory. add_asset_coordinates(asset_id, coordinates): Add an asset to the

inventory with just a list of coordinates.

add_asset_features(asset_id, features): Append new features to the

asset.

remove_asset(asset_id): Remove an asset to the inventory. get_asset_features(asset_id): Get coordinates of a particular assset. get_asset_coordinates(asset_id): Get features of a particular assset. get_asset_ids(): Return the asset ids as a list. get_random_sample(size, seed): Get subset of the inventory. get_coordinates(): Return a list of footprints. get_geojson(): Return inventory as a geojson dict. write_to_geojson(): Wtite inventory to file in GeoJSON format. Also return inventory as a geojson dict! read_from_csv(file_path, keep_existing, str_type, id_column): Read

inventory dataset from a csv table

add_asset_features_from_csv(file_path, id_column): Add asset features

from a csv file.

add_asset(asset_id: str | int, asset: Asset) → bool

Add an Asset to the inventory.

Args:

asset_id (str|int): The unique identifier for the asset. asset (Asset): The asset to be added.

Returns:

bool: True if the asset was added successfully, False otherwise.

add_asset_coordinates(asset_id: str | int, coordinates: list[list[float]]) → bool

Add an Asset to the inventory by adding its coordinate information.

Args:

asset_id (str|int): The unique identifier for the asset. coordinates (list[list[float]]): A two-dimensional list

representing the geometry in [[lon1, lat1], [lon2, lat2], …, [lonN, latN]] format.

Returns:

bool: True if the asset was added successfully, False otherwise.

add_asset_features(asset_id: str | int, new_features: dict, overwrite=True) → bool

Add new asset features to the Asset with the specified ID.

Args:

asset_id (str|int): The unique identifier for the asset. new_features (dict): A dictionary of features to add to the asset. overwrite (bool): Whether to overwrite existing features with the

same keys. Defaults to True.

Returns:

bool: True if features were successfully added, False if the asset

does not exist or the operation fails.

add_asset_features_from_csv(file_path, id_column) → bool

Read inventory data from a CSV file and add it to the inventory.

Args:

file_path (str):

The path to the CSV file

id_column (str):

The name of column that contains id values. If None, new indicies will be assigned

Returns:

bool:

True if assets were addded, False otherwise.

get_asset_coordinates(asset_id: str | int) → tuple[bool, list]

Get the coordinates of a particular asset.

Args:

asset_id (str | int): The unique identifier for the asset.

Returns:

tuple[bool, list]]: A tuple where the first element is a boolean

indicating whether the asset was found, and the second element is a list of coordinate pairs in the format [[lon1, lat1], [lon2, lat2], …, [lonN, latN]] if the asset is present. Returns an empty list if the asset is not found.

get_asset_features(asset_id: str | int) → tuple[bool, dict]

Get features of a particular asset.

Args:

asset_id (str|int): The unique identifier for the asset.

Returns:

tuple[bool, Dict]: A tuple where the first element is a boolean

indicating whether the asset was found, and the second element is a dictionary containing the asset’s features if the asset is present. Returns an empty dictionary if the asset is not found.

get_asset_ids() → list[str | int]

Retrieve the IDs of all assets in the inventory.

Returns:

list[str | int]: A list of asset IDs, which may be strings or

integers.

get_coordinates() → tuple[list[list[list[float, float]]], list[str | int]]

Get geometry (coordinates) and keys of all assets in the inventory.

Returns:

tuple[list[list[list[float, float]]], list[str | int]]: A tuple

containing: - A list of coordinates for each asset, where each coordinate

is represented as a list of [longitude, latitude] pairs.

• A list of asset keys corresponding to each Asset.

get_dataframe(n_possible_worlds=1, features_possible_worlds=[]) → bool

Read inventory data from a CSV file and add it to the inventory.

Args:

n_possible_worlds (int):

Number of possible worlds

features_possible_worlds (list of str):

Indicate the features with multiple possible worlds

Returns:

bool:

True if assets were addded, False otherwise.

get_geojson() → dict

Generate a GeoJSON representation of the assets in the inventory.

Returns:

dict: A dictionary in GeoJSON format containing all assets, with

each asset represented as a feature. Each feature includes the geometry (Point or Polygon) and associated properties.

get_random_sample(nsamples: int, seed: int | float | str | bytes | bytearray | None = None)

Generate a smaller AssetInventory with a random selection of assets.

Args:

nsamples (int): The number of assets to include in the sampled

inventory.

seed (int | float | str | bytes | bytearray | None): The seed for

the random generator. If None, the seed is set to the sytem default (i.e., the current system time).

Returns:

AssetInventory: A new AssetInventory instance containing a random

subset of assets.

print_info()

Print the asset inventory.

read_from_csv(file_path, keep_existing, str_type='building', id_column=None) → bool

Read inventory data from a CSV file and add it to the inventory.

Args:

file_path (str):

The path to the CSV file

keep_existing (bool):

If False, the inventory will be initialized

str_type (str):

“building” or “bridge”

id_column (str):

The name of column that contains id values. If None, new indicies will be assigned

Returns:

bool:

True if assets were addded, False otherwise.

remove_asset(asset_id: str | int) → bool

Remove an Asset from the inventory.

Args:

asset_id (str|int): The unique identifier for the asset.

Returns:

bool: True if asset was removed, False otherwise.

write_to_geojson(output_file: str = '') → dict

Generate a GeoJSON representation of the assets in the inventory.

Returns:

dict: A dictionary in GeoJSON format containing all assets, with

each asset represented as a feature. Each feature includes the geometry (Point or Polygon) and associated properties.