def __init__(self, dataset, url, data, lccs):
"""Initialize instance with dictionary data.
:param data: Dict with class system metadata.
"""
super(Dataset, self).__init__(data or {})
#: Dataset: The associated Dataset.
self._dataset = dataset
self.metadata_json = self.prepare_metadata()
self.__url = url
self.__lccs_server = LCCS(lccs)
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("http://brazildatacube.dpi.inpe.br/dev/lccs/")
# Get a specific classification system
# Make sure the classification system is available in service
classification_system = service.classification_system('PRODES-1.0')
# Return the metadata of a specific class
class_metadata = classification_system.get_class('Desflorestamento')
print(class_metadata)
# You can access specific attributes
print(class_metadata.id)
print(class_metadata.name)
print(class_metadata.description)
print(class_metadata.code)
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("http://brazildatacube.dpi.inpe.br/dev/lccs/")
# Get a specific classification system
# Make sure the classification system is available in service
classification_system = service.classification_system(
system_id='TerraClass_AMZ')
# Return the metadata of a specific class
class_metadata = classification_system.classes(class_id='Desflorestamento')
print(class_metadata)
# You can access specific attributes
print(class_metadata.id)
print(class_metadata.name)
print(class_metadata.description)
print(class_metadata.code)
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("http://brazildatacube.dpi.inpe.br/dev/lccs/")
# Save Style File
service.get_styles(system_id='MapBiomas5', format_id='QGIS')
# Save Style File passing the path directory
service.get_styles(system_id='MapBiomas5', format_id='QGIS', path='/home/user/Downloads/')
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("https://brazildatacube.dpi.inpe.br/lccs/")
# Return the list of available clasification system for mapping
available_mappings = service.available_mappings('PRODES-1.0')
print(available_mappings)
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("https://brazildatacube.dpi.inpe.br/dev/lccs/")
# Save Style File
service.get_style(system_name='PRODES-1.0', format_name='QGIS')
# Save Style File passing the path directory
service.get_style(system_name='PRODES-1.0',
format_name='QGIS',
path='/home/user/Downloads/')
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("https://brazildatacube.dpi.inpe.br/lccs/")
# Get all styles available for a specific classification system
styles = service.style_formats('PRODES-1.0')
print(styles)
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("http://brazildatacube.dpi.inpe.br/dev/lccs/")
# Get all styles available for a specific classification system
styles = service.styles(system_id='MapBiomas5')
print(styles)
class Dataset(dict):
"""DataSet Class."""
def __init__(self, dataset, url, data, lccs):
"""Initialize instance with dictionary data.
:param data: Dict with class system metadata.
"""
super(Dataset, self).__init__(data or {})
#: Dataset: The associated Dataset.
self._dataset = dataset
self.metadata_json = self.prepare_metadata()
self.__url = url
self.__lccs_server = LCCS(lccs)
def prepare_metadata(self) -> Union[None, DSMetada]:
"""Prepare dataset metadata."""
if isinstance(self['metadata_json'], dict):
metadata_json = DSMetada(self['metadata_json'])
return metadata_json
else:
return None
@property
def id(self) -> str:
"""Return the dataset id."""
return self['id']
@property
def classification_system_name(self) -> str:
"""Return the dataset classification system id."""
return self['classification_system_name']
@property
def classification_system_id(self) -> str:
"""Return the dataset classification system name."""
return self['classification_system_id']
@property
def classification_system_version(self) -> str:
"""Return the dataset classification system version."""
return self['classification_system_version']
def _get_classification_system(self) -> ClassificationSystem:
"""Return the classification system object."""
system_id = f"{self['classification_system_name']}-{self['classification_system_version']}"
return self.__lccs_server.classification_system(system_id)
@property
def classification_system(self) -> ClassificationSystem:
"""Return the classification system object."""
return self._get_classification_system()
@property
def collect_method(self) -> str:
"""Return the dataset collect method name."""
return self['collect_method_name']
@property
def collect_method_id(self) -> str:
"""Return the dataset collect method id."""
return self['collect_method_id']
@property
def description(self) -> str:
"""Return the dataset description."""
return self['description']
@property
def end_date(self) -> str:
"""Return the dataset end date."""
return self['end_date']
@property
def start_date(self) -> str:
"""Return the dataset start date."""
return self['start_date']
@property
def name(self) -> str:
"""Return the dataset name."""
return self['name']
@property
def title(self) -> str:
"""Return the dataset identifier."""
return self['title']
@property
def is_public(self) -> str:
"""Return the dataset is_public."""
return self['is_public']
@property
def version(self) -> str:
"""Return the dataset version."""
return self['version']
@property
def version_successor(self) -> Union[int, None]:
"""Return the dataset version_successor."""
return self['version_successor']
@property
def version_predecessor(self) -> Union[int, None]:
"""Return the dataset version_predecessor."""
return self['version_predecessor']
@property
def metadata(self) -> Union[DSMetada, None]:
"""Return the dataset metadata."""
return self.metadata_json
@property
def dataset_table_id(self) -> int:
"""Return the dataset table name."""
return self['dataset_table_id']
@property
def user_id(self):
"""Return the dataset user id (user id who performed the insertion of the dataset)."""
return self['user_id']
@property
def created_at(self):
"""Return the dataset created_at date."""
return self['created_at']
@property
def updated_at(self):
"""Return the dataset updated_at date."""
return self['updated_at']
@property
def number_of_features(self):
"""Return the dataset updated_at date."""
return self['number_of_features']
def data(self,
data_id: int = None,
filter: dict = dict()) -> gpd.GeoDataFrame:
"""Return the dataset observation dataframe."""
url = f'{self._dataset._url}/datasets/data'
filter["access_token"] = self._dataset._access_token
filter["dataset_id"] = self.id
if data_id:
filter["data_id"] = data_id
else:
if 'limit' not in filter or filter["limit"] is None:
filter["limit"] = self.number_of_features
features = Utils._get(url=url, **filter)
return gpd.GeoDataFrame.from_features(features["features"])
def _repr_html_(self):
"""HTML repr."""
return Utils.render_html('dataset.html', dataset=self)
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("https://brazildatacube.dpi.inpe.br/lccs/")
# Returns the list of classification system available on the service
print(service.classification_systems)
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("http://brazildatacube.dpi.inpe.br/dev/lccs/")
# Returns the mapping between two classification systems.
# Make sure the classification system is available in service
mappings = service.mappings(system_id_source='TerraClass_AMZ',
system_id_target='PRODES')
for mp in mappings.mapping:
print("Source Class: {} ID: {} | Target Class: {} ID: {}".format(
mp.source_class, mp.source_class_id, mp.target_class,
mp.target_class_id))
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("https://brazildatacube.dpi.inpe.br/lccs/")
# Returns the mapping between two classification systems.
# Make sure the classification system is available in service
mapping = service.mappings(system_name_source='PRODES-1.0', system_name_target='TerraClass_AMZ-1.0')
print(mapping)
#
# This file is part of Python Client Library for the LCCS-WS.
# Copyright (C) 2020 INPE.
#
# Python Client Library for the LCCS-WS is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
#
"""LCCS Python Client examples."""
from lccs import LCCS
# Change to the LCCS-WS URL you want to use.
service = LCCS("http://brazildatacube.dpi.inpe.br/dev/lccs/")
# Return the list of available clasification system for mapping
available_mappings = service.available_mappings(
system_id_source='TerraClass_AMZ')
print(available_mappings)
