"""
Easy access to administrative boundary defined by FAO GAUL 2015 from Python scripts.
This lib provides access to FAO GAUL 2015 datasets from a Python script. it is the best boundary dataset available for GEE at this point. We provide access to The current version (2015) administrative areas till level 2.
"""
import warnings
from difflib import get_close_matches
from functools import lru_cache
from itertools import product
from pathlib import Path
from typing import List, Union
import ee
import numpy as np
import pandas as pd
from deprecated.sphinx import deprecated, versionadded # type: ignore [import-untyped]
[docs]
__author__ = "Pierrick Rambaud"
[docs]
__email__ = "pierrick.rambaud49@gmail.com"
[docs]
__gaul_data__ = Path(__file__).parent / "data" / "gaul_database.parquet"
[docs]
__gaul_asset__ = "projects/sat-io/open-datasets/FAO/GAUL/GAUL_2024_L{}"
@lru_cache(maxsize=1)
[docs]
def _df() -> pd.DataFrame:
"""Get the parquet database."""
return pd.read_parquet(__gaul_data__)
@versionadded(version="0.3.1", reason="Add a Names object to handle names")
[docs]
class Names(pd.DataFrame):
def __init__(
self,
name: str = "",
admin: str = "",
content_level: int = -1,
complete: bool = False,
):
"""Object to handle names of administrative layer using the name or the administrative code.
Compute a pandas DataFrame of the names as FAO GAUL codes of and administrative region. The region can be requested either by its "name" or its "admin", the lib will identify the corresponding level on the fly. The user can also request for a specific level for its content e.g. get all admin level 1 of a country. If nothing is set we will infer the level of the item and if the level is higher than the found item, it will be ignored. If Nothing is found the method will raise an error.
Args:
name: The name of a administrative area. Cannot be set along with :code:`admin`.
admin: The id of an administrative area in the FAO GAUL nomenclature. Cannot be set along with :code:`name`.
content_level: The level to use in the final dataset. Default to -1 (use level of the selected area).
complete: If True, the method will return all the names of the higher administrative areas. Default to False.
"""
# sanitary check on parameters
if name and admin:
raise ValueError('"name" and "id" cannot be set at the same time.')
# if a name or admin number is set, we need to filter the dataset accordingly
# if not we will simply consider the world dataset
df = _df()
if name or admin:
# set the id we look for and tell the function if its a name or an admin
is_name = True if name else False
id = name if name else admin
# read the data and find if the element exist
column = "gaul{}_name" if is_name else "gaul{}_code"
is_in = (
df.filter([column.format(i) for i in range(3)])
.apply(lambda col: col.str.lower())
.isin([id.lower()])
)
if not is_in.any().any():
# find the 5 closest names/id
columns = [df[column.format(i)].dropna().str.lower().values for i in range(3)]
ids = np.unique(np.concatenate(columns))
close_ids = get_close_matches(id.lower(), ids, n=5)
if is_name is True:
close_ids = [i.capitalize() for i in close_ids]
else:
close_ids = [i.upper() for i in close_ids]
raise ValueError(
f'The requested "{id}" is not part of FAO GAUL 2024. The closest '
f'matches are: {", ".join(close_ids)}.'
)
# Get the code of the associated country of the identifed area and the associated level
line = is_in[~((~is_in).all(axis=1))].idxmax(1)
level = line.iloc[0][4]
# load the max_level available in the requested area
sub_df = df[df[column.format(level)].str.fullmatch(id, case=False)]
max_level = next(i for i in reversed(range(3)) if (sub_df[f"gaul{i}_name"] != "").any())
# get the request level from user
content_level, level = int(content_level), int(level)
if content_level == -1:
content_level = level
elif content_level < level:
warnings.warn(
f"The requested level ({content_level}) is higher than the area ({level}). "
f"Fallback to {level}."
)
content_level = level
if content_level > max_level:
warnings.warn(
f"The requested level ({content_level}) is higher than the max level "
f"in this country ({max_level}). Fallback to {max_level}."
)
content_level = max_level
else: # no admin and no name
sub_df = df
content_level = 0 if content_level == -1 else content_level
# get the columns name corresponding to the requested level
columns = [f"gaul{content_level}_name", f"gaul{content_level}_code"]
# the list will contain duplicate as all the smaller admin level will be included
sub_df = sub_df.drop_duplicates(subset=columns, ignore_index=True)
# the list will contain NA as all the bigger admin level will be selected as well
# the database is read as pure string so dropna cannot be used
# .astype is also a vectorized operation so it goes very fast
sub_df = sub_df[sub_df[columns[0]].astype(bool)]
# filter the df if complete is set to False, the only displayed columns will be the one requested
final_df = sub_df if complete is True else sub_df[columns]
super().__init__(final_df)
@versionadded(version="0.3.1", reason="Add an Items class to handle admin items")
[docs]
class Items(ee.FeatureCollection):
def __init__(
self,
name: Union[str, List[str]] = "",
admin: Union[str, List[str]] = "",
content_level: int = -1,
):
"""Object to handle administrative boundaries using the name or the administrative code.
Return an ee.FeatureCollection representing an administrative region. The region can be requested either by its "name" or its "admin", the lib will identify the area level on the fly. The user can also request for a specific level for the GeoDataFrame features e.g. get all admin level 1 of a country. If nothing is set we will infer the level of the item and if the level is higher than the found item, it will be ignored. If Nothing is found the method will return an error.
Args:
name: The name of an administrative area. Cannot be set along with :code:`admin`. it can be a list or a single name.
admin: The id of an administrative area in the GADM nomenclature. Cannot be set along with :code:`name`. It can be a list or a single admin code.
content_level: The level to use in the final dataset. Default to -1 (use level from the area).
"""
# set up the loop
names = [name] if isinstance(name, str) else name
admins = [admin] if isinstance(admin, str) else admin
# check that they are not all empty
if names == [""] == admins:
raise ValueError('at least "name" or "admin" need to be set.')
# special parsing for continents. They are associated to the countries by FAO.
continents = _df().continent.unique()
if len(names) == 1 and (c := names[0].lower()) in continents:
admins = [a for a in _df()[_df().continent == c].gaul0_code.unique()]
names = [""]
# use itertools, normally one of them is empty so it will raise an error
# if not the case as admin and name will be set together
fc_list = [self._items(n, a, content_level) for n, a in product(names, admins)]
# concat all the data
feature_collection = fc_list[0]
if len(fc_list) > 1:
for fc in fc_list[1:]:
feature_collection = feature_collection.merge(fc)
super().__init__(feature_collection)
[docs]
def _items(
self, name: str = "", admin: str = "", content_level: int = -1
) -> ee.FeatureCollection:
"""
Return the requested administrative boundaries from a single name or administrative code.
Args:
name: The name of an administrative area. Cannot be set along with :code:`admin`.
admin: The id of an administrative area in the FAO GAUL nomenclature. Cannot be set along with :code:`name`.
content_level: The level to use in the final dataset. Default to -1 (use level from the area).
Returns:
The FeatureCollection of the requested area with all the GAUL attributes.
"""
# call to Names without level to raise an error if the requested level won't work
df = Names(name, admin)
if len(df) > 1:
raise ValueError(
f'The requested name ("{name}") is not unique ({len(df)} results). '
f"To retrieve it, please use the `admin` parameter instead. "
f"If you don't know the GAUL code, use the following code, "
f'it will return the GAUL codes as well:\n`Names(name="{name}")`'
)
df.columns[0][4]
# now load the useful one to get content_level
df = Names(name, admin, content_level)
content_level = df.columns[1][4]
# checks have already been performed in Names and there should
# be one single result
ids = [int(v) for v in df[f"gaul{content_level}_code"].to_list()]
# read the accurate dataset
feature_collection = ee.FeatureCollection(__gaul_asset__.format(content_level)).filter(
ee.Filter.inList(f"gaul{content_level}_code", ids)
)
return feature_collection
@deprecated(version="0.3.1", reason="Use the Names object instead")
[docs]
class AdmNames(Names):
pass
@deprecated(version="0.3.1", reason="Use the Items class instead")
[docs]
class AdmItems(Items):
pass
@deprecated(version="0.3.0", reason="Use the Names object instead")
[docs]
def get_names(
name: str = "", admin: str = "", content_level: int = -1, complete: bool = False
) -> pd.DataFrame:
"""Return the list of names available in a administrative layer using the name or the administrative code."""
return Names(name, admin, content_level, complete)
@deprecated(version="0.3.0", reason="Use the Items class instead")
[docs]
def get_items(
name: Union[str, List[str]] = "",
admin: Union[str, List[str]] = "",
content_level: int = -1,
) -> ee.FeatureCollection:
"""Return the requested administrative boundaries using the name or the administrative code."""
return Items(name, admin, content_level)
