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9,784 | exhale | environment_ready | null | def environment_ready(app):
# Defer importing configs until sphinx is running.
from . import configs
from . import utils
from . import deploy
# First, setup the extension and verify all of the configurations.
configs.apply_sphinx_configurations(app)
####### Next, perform any cleanup
# Generate the full API!
try:
deploy.explode()
except:
utils.fancyError("Exhale: could not generate reStructuredText documents :/")
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] |
9,785 | exhale | setup | null | def setup(app):
app.setup_extension("breathe")
app.add_config_value("exhale_args", {}, "env")
app.connect("builder-inited", environment_ready)
# app.connect("env-purge-doc", cleanup_files)
return {
"version": __version__,
# Because Exhale hooks into / generates *BEFORE* any reading or writing occurs,
# it is parallel safe by default.
"parallel_read_safe": True,
"parallel_write_safe": True
}
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9,786 | oc_ocdm.reader | Reader | null | class Reader(object):
def __init__(self, repok: Reporter = None, reperr: Reporter = None, context_map: Dict[str, Any] = None) -> None:
if context_map is not None:
self.context_map: Dict[str, Any] = context_map
else:
self.context_map: Dict[str, Any] = {}
for context_url in self.context_map:
ctx_file_path: Any = self.context_map[context_url]
if type(ctx_file_path) == str and os.path.isfile(ctx_file_path):
# This expensive operation is done only when it's really needed
with open(ctx_file_path, 'rt', encoding='utf-8') as ctx_f:
self.context_map[context_url] = json.load(ctx_f)
if repok is None:
self.repok: Reporter = Reporter(prefix="[Reader: INFO] ")
else:
self.repok: Reporter = repok
if reperr is None:
self.reperr: Reporter = Reporter(prefix="[Reader: ERROR] ")
else:
self.reperr: Reporter = reperr
def load(self, rdf_file_path: str) -> Optional[ConjunctiveGraph]:
self.repok.new_article()
self.reperr.new_article()
loaded_graph: Optional[ConjunctiveGraph] = None
if os.path.isfile(rdf_file_path):
try:
loaded_graph = self._load_graph(rdf_file_path)
except Exception as e:
self.reperr.add_sentence("[1] "
"It was impossible to handle the format used for "
"storing the file (stored in the temporary path) "
f"'{rdf_file_path}'. Additional details: {e}")
else:
self.reperr.add_sentence("[2] "
f"The file specified ('{rdf_file_path}') doesn't exist.")
return loaded_graph
def _load_graph(self, file_path: str) -> ConjunctiveGraph:
formats = ["json-ld", "rdfxml", "turtle", "trig", "nt11", "nquads"]
loaded_graph = ConjunctiveGraph()
if file_path.endswith('.zip'):
try:
with ZipFile(file=file_path, mode="r") as archive:
for zf_name in archive.namelist():
with archive.open(zf_name) as f:
if self._try_parse(loaded_graph, f, formats):
return loaded_graph
except Exception as e:
raise IOError(f"Error opening or reading zip file '{file_path}': {e}")
else:
try:
with open(file_path, 'rt', encoding='utf-8') as f:
if self._try_parse(loaded_graph, f, formats):
return loaded_graph
except Exception as e:
raise IOError(f"Error opening or reading file '{file_path}': {e}")
raise IOError(f"It was impossible to load the file '{file_path}' with supported formats.")
def _try_parse(self, graph: ConjunctiveGraph, file_obj, formats: List[str]) -> bool:
for cur_format in formats:
file_obj.seek(0) # Reset file pointer to the beginning for each new attempt
try:
if cur_format == "json-ld":
json_ld_file = json.load(file_obj)
if isinstance(json_ld_file, dict):
json_ld_file = [json_ld_file]
for json_ld_resource in json_ld_file:
if "@context" in json_ld_resource and json_ld_resource["@context"] in self.context_map:
json_ld_resource["@context"] = self.context_map[json_ld_resource["@context"]]["@context"]
data = json.dumps(json_ld_file, ensure_ascii=False)
graph.parse(data=data, format=cur_format)
else:
graph.parse(file=file_obj, format=cur_format)
return True # Success, no need to try other formats
except Exception as e:
continue # Try the next format
return False # None of the formats succeeded
@staticmethod
def get_graph_from_subject(graph: Graph, subject: URIRef) -> Graph:
g: Graph = Graph(identifier=graph.identifier)
for p, o in graph.predicate_objects(subject, unique=True):
g.add((subject, p, o))
return g
@staticmethod
def _extract_subjects(graph: Graph) -> Set[URIRef]:
subjects: Set[URIRef] = set()
for s in graph.subjects(unique=True):
subjects.add(s)
return subjects
def graph_validation(self, graph: Graph, closed: bool = False) -> Graph:
valid_graph: Graph = Graph(identifier=graph.identifier)
sg = Graph()
if closed:
sg.parse(os.path.join('oc_ocdm', 'resources', 'shacle_closed.ttl'))
else:
sg.parse(os.path.join('oc_ocdm', 'resources', 'shacle.ttl'))
_, report_g, _ = validate(graph,
shacl_graph=sg,
ont_graph=None,
inference=None,
abort_on_first=False,
allow_infos=False,
allow_warnings=False,
meta_shacl=False,
advanced=False,
js=False,
debug=False)
invalid_nodes = set()
for triple in report_g.triples((None, URIRef('http://www.w3.org/ns/shacl#focusNode'), None)):
invalid_nodes.add(triple[2])
for subject in self._extract_subjects(graph):
if subject not in invalid_nodes:
for valid_subject_triple in graph.triples((subject, None, None)):
valid_graph.add(valid_subject_triple)
return valid_graph
@staticmethod
def import_entities_from_graph(g_set: GraphSet, results: List[Dict], resp_agent: str,
enable_validation: bool = False, closed: bool = False) -> List[GraphEntity]:
graph = build_graph_from_results(results)
if enable_validation:
reader = Reader()
graph = reader.graph_validation(graph, closed)
imported_entities: List[GraphEntity] = []
for subject in Reader._extract_subjects(graph):
types = []
for o in graph.objects(subject, RDF.type):
types.append(o)
# ReferenceAnnotation
if GraphEntity.iri_note in types:
imported_entities.append(g_set.add_an(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# AgentRole
elif GraphEntity.iri_role_in_time in types:
imported_entities.append(g_set.add_ar(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# BibliographicReference
elif GraphEntity.iri_bibliographic_reference in types:
imported_entities.append(g_set.add_be(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# BibliographicResource
elif GraphEntity.iri_expression in types:
imported_entities.append(g_set.add_br(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# Citation
elif GraphEntity.iri_citation in types:
imported_entities.append(g_set.add_ci(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# DiscourseElement
elif GraphEntity.iri_discourse_element in types:
imported_entities.append(g_set.add_de(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# Identifier
elif GraphEntity.iri_identifier in types:
imported_entities.append(g_set.add_id(resp_agent=resp_agent, res=subject,
| (repok: 'Reporter' = None, reperr: 'Reporter' = None, context_map: 'Dict[str, Any]' = None) -> 'None' | [
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9,787 | oc_ocdm.reader | __init__ | null | def __init__(self, repok: Reporter = None, reperr: Reporter = None, context_map: Dict[str, Any] = None) -> None:
if context_map is not None:
self.context_map: Dict[str, Any] = context_map
else:
self.context_map: Dict[str, Any] = {}
for context_url in self.context_map:
ctx_file_path: Any = self.context_map[context_url]
if type(ctx_file_path) == str and os.path.isfile(ctx_file_path):
# This expensive operation is done only when it's really needed
with open(ctx_file_path, 'rt', encoding='utf-8') as ctx_f:
self.context_map[context_url] = json.load(ctx_f)
if repok is None:
self.repok: Reporter = Reporter(prefix="[Reader: INFO] ")
else:
self.repok: Reporter = repok
if reperr is None:
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9,788 | oc_ocdm.reader | _extract_subjects | null | @staticmethod
def _extract_subjects(graph: Graph) -> Set[URIRef]:
subjects: Set[URIRef] = set()
for s in graph.subjects(unique=True):
subjects.add(s)
return subjects
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] |
9,789 | oc_ocdm.reader | _load_graph | null | def _load_graph(self, file_path: str) -> ConjunctiveGraph:
formats = ["json-ld", "rdfxml", "turtle", "trig", "nt11", "nquads"]
loaded_graph = ConjunctiveGraph()
if file_path.endswith('.zip'):
try:
with ZipFile(file=file_path, mode="r") as archive:
for zf_name in archive.namelist():
with archive.open(zf_name) as f:
if self._try_parse(loaded_graph, f, formats):
return loaded_graph
except Exception as e:
raise IOError(f"Error opening or reading zip file '{file_path}': {e}")
else:
try:
with open(file_path, 'rt', encoding='utf-8') as f:
if self._try_parse(loaded_graph, f, formats):
return loaded_graph
except Exception as e:
raise IOError(f"Error opening or reading file '{file_path}': {e}")
raise IOError(f"It was impossible to load the file '{file_path}' with supported formats.")
| (self, file_path: str) -> rdflib.graph.ConjunctiveGraph | [
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9,790 | oc_ocdm.reader | _try_parse | null | def _try_parse(self, graph: ConjunctiveGraph, file_obj, formats: List[str]) -> bool:
for cur_format in formats:
file_obj.seek(0) # Reset file pointer to the beginning for each new attempt
try:
if cur_format == "json-ld":
json_ld_file = json.load(file_obj)
if isinstance(json_ld_file, dict):
json_ld_file = [json_ld_file]
for json_ld_resource in json_ld_file:
if "@context" in json_ld_resource and json_ld_resource["@context"] in self.context_map:
json_ld_resource["@context"] = self.context_map[json_ld_resource["@context"]]["@context"]
data = json.dumps(json_ld_file, ensure_ascii=False)
graph.parse(data=data, format=cur_format)
else:
graph.parse(file=file_obj, format=cur_format)
return True # Success, no need to try other formats
except Exception as e:
continue # Try the next format
return False # None of the formats succeeded
| (self, graph: 'ConjunctiveGraph', file_obj, formats: 'List[str]') -> 'bool' | [
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9,791 | oc_ocdm.reader | get_graph_from_subject | null | @staticmethod
def get_graph_from_subject(graph: Graph, subject: URIRef) -> Graph:
g: Graph = Graph(identifier=graph.identifier)
for p, o in graph.predicate_objects(subject, unique=True):
g.add((subject, p, o))
return g
| (graph: rdflib.graph.Graph, subject: rdflib.term.URIRef) -> rdflib.graph.Graph | [
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9,792 | oc_ocdm.reader | graph_validation | null | def graph_validation(self, graph: Graph, closed: bool = False) -> Graph:
valid_graph: Graph = Graph(identifier=graph.identifier)
sg = Graph()
if closed:
sg.parse(os.path.join('oc_ocdm', 'resources', 'shacle_closed.ttl'))
else:
sg.parse(os.path.join('oc_ocdm', 'resources', 'shacle.ttl'))
_, report_g, _ = validate(graph,
shacl_graph=sg,
ont_graph=None,
inference=None,
abort_on_first=False,
allow_infos=False,
allow_warnings=False,
meta_shacl=False,
advanced=False,
js=False,
debug=False)
invalid_nodes = set()
for triple in report_g.triples((None, URIRef('http://www.w3.org/ns/shacl#focusNode'), None)):
invalid_nodes.add(triple[2])
for subject in self._extract_subjects(graph):
if subject not in invalid_nodes:
for valid_subject_triple in graph.triples((subject, None, None)):
valid_graph.add(valid_subject_triple)
return valid_graph
| (self, graph: rdflib.graph.Graph, closed: bool = False) -> rdflib.graph.Graph | [
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9,793 | oc_ocdm.reader | import_entities_from_graph | null | @staticmethod
def import_entities_from_graph(g_set: GraphSet, results: List[Dict], resp_agent: str,
enable_validation: bool = False, closed: bool = False) -> List[GraphEntity]:
graph = build_graph_from_results(results)
if enable_validation:
reader = Reader()
graph = reader.graph_validation(graph, closed)
imported_entities: List[GraphEntity] = []
for subject in Reader._extract_subjects(graph):
types = []
for o in graph.objects(subject, RDF.type):
types.append(o)
# ReferenceAnnotation
if GraphEntity.iri_note in types:
imported_entities.append(g_set.add_an(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# AgentRole
elif GraphEntity.iri_role_in_time in types:
imported_entities.append(g_set.add_ar(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# BibliographicReference
elif GraphEntity.iri_bibliographic_reference in types:
imported_entities.append(g_set.add_be(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# BibliographicResource
elif GraphEntity.iri_expression in types:
imported_entities.append(g_set.add_br(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# Citation
elif GraphEntity.iri_citation in types:
imported_entities.append(g_set.add_ci(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# DiscourseElement
elif GraphEntity.iri_discourse_element in types:
imported_entities.append(g_set.add_de(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# Identifier
elif GraphEntity.iri_identifier in types:
imported_entities.append(g_set.add_id(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# PointerList
elif GraphEntity.iri_singleloc_pointer_list in types:
imported_entities.append(g_set.add_pl(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# ResponsibleAgent
elif GraphEntity.iri_agent in types:
imported_entities.append(g_set.add_ra(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# ResourceEmbodiment
elif GraphEntity.iri_manifestation in types:
imported_entities.append(g_set.add_re(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
# ReferencePointer
elif GraphEntity.iri_intextref_pointer in types:
imported_entities.append(g_set.add_rp(resp_agent=resp_agent, res=subject,
preexisting_graph=Reader.get_graph_from_subject(graph, subject)))
return imported_entities
| (g_set: 'GraphSet', results: 'List[Dict]', resp_agent: 'str', enable_validation: 'bool' = False, closed: 'bool' = False) -> 'List[GraphEntity]' | [
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] |
9,794 | oc_ocdm.reader | import_entity_from_triplestore | null | @staticmethod
def import_entity_from_triplestore(g_set: GraphSet, ts_url: str, res: URIRef, resp_agent: str,
enable_validation: bool = False) -> GraphEntity:
sparql: SPARQLWrapper = SPARQLWrapper(ts_url)
query: str = f"SELECT ?s ?p ?o WHERE {{BIND (<{res}> AS ?s). ?s ?p ?o.}}"
sparql.setQuery(query)
sparql.setMethod('GET')
sparql.setReturnFormat(JSON)
result: ConjunctiveGraph = sparql.queryAndConvert()['results']['bindings']
if result:
imported_entities: List[GraphEntity] = Reader.import_entities_from_graph(g_set, result,
resp_agent, enable_validation)
if len(imported_entities) <= 0:
raise ValueError("The requested entity was not found or was not recognized as a proper OCDM entity.")
else:
return imported_entities[0]
| (g_set: 'GraphSet', ts_url: 'str', res: 'URIRef', resp_agent: 'str', enable_validation: 'bool' = False) -> 'GraphEntity' | [
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9,795 | oc_ocdm.reader | load | null | def load(self, rdf_file_path: str) -> Optional[ConjunctiveGraph]:
self.repok.new_article()
self.reperr.new_article()
loaded_graph: Optional[ConjunctiveGraph] = None
if os.path.isfile(rdf_file_path):
try:
loaded_graph = self._load_graph(rdf_file_path)
except Exception as e:
self.reperr.add_sentence("[1] "
"It was impossible to handle the format used for "
"storing the file (stored in the temporary path) "
f"'{rdf_file_path}'. Additional details: {e}")
else:
self.reperr.add_sentence("[2] "
f"The file specified ('{rdf_file_path}') doesn't exist.")
return loaded_graph
| (self, rdf_file_path: 'str') -> 'Optional[ConjunctiveGraph]' | [
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9,796 | oc_ocdm.storer | Storer | null | class Storer(object):
def __init__(self, abstract_set: AbstractSet, repok: Reporter = None, reperr: Reporter = None,
context_map: Dict[str, Any] = None, default_dir: str = "_", dir_split: int = 0,
n_file_item: int = 1, output_format: str = "json-ld", zip_output: bool = False, modified_entities: set = None) -> None:
# We only accept format strings that:
# 1. are supported by rdflib
# 2. correspond to an output format which is effectively either NT or NQ
# The only exception to this rule is the 'json-ld' format, which is the default value of 'output_format'.
supported_formats: Set[str] = {'application/n-triples', 'ntriples', 'nt', 'nt11',
'application/n-quads', 'nquads', 'json-ld'}
if output_format not in supported_formats:
raise ValueError(f"Given output_format '{self.output_format}' is not supported."
f" Available formats: {supported_formats}.")
else:
self.output_format: str = output_format
self.zip_output = zip_output
self.dir_split: int = dir_split
self.n_file_item: int = n_file_item
self.default_dir: str = default_dir if default_dir != "" else "_"
self.a_set: AbstractSet = abstract_set
self.modified_entities = modified_entities
if context_map is not None:
self.context_map: Dict[str, Any] = context_map
else:
self.context_map: Dict[str, Any] = {}
if self.output_format == "json-ld":
for context_url in self.context_map:
ctx_file_path: Any = self.context_map[context_url]
if type(ctx_file_path) == str and os.path.isfile(ctx_file_path):
# This expensive operation is done only when it's really needed
with open(ctx_file_path, 'rt', encoding='utf-8') as ctx_f:
self.context_map[context_url] = json.load(ctx_f)
if repok is None:
self.repok: Reporter = Reporter(prefix="[Storer: INFO] ")
else:
self.repok: Reporter = repok
if reperr is None:
self.reperr: Reporter = Reporter(prefix="[Storer: ERROR] ")
else:
self.reperr: Reporter = reperr
def store_graphs_in_file(self, file_path: str, context_path: str = None) -> None:
self.repok.new_article()
self.reperr.new_article()
self.repok.add_sentence("Store the graphs into a file: starting process")
cg: ConjunctiveGraph = ConjunctiveGraph()
for g in self.a_set.graphs():
cg.addN([item + (g.identifier,) for item in list(g)])
self._store_in_file(cg, file_path, context_path)
def _store_in_file(self, cur_g: ConjunctiveGraph, cur_file_path: str, context_path: str = None) -> None:
# Note: the following lines from here and until 'cur_json_ld' are a sort of hack for including all
# the triples of the input graph into the final stored file. Somehow, some of them are not written
# in such file otherwise - in particular the provenance ones.
new_g: ConjunctiveGraph = ConjunctiveGraph()
for s, p, o in cur_g.triples((None, None, None)):
g_iri: Optional[URIRef] = None
for g_context in cur_g.contexts((s, p, o)):
g_iri = g_context.identifier
break
new_g.addN([(s, p, o, g_iri)])
zip_file_path = cur_file_path.replace(os.path.splitext(cur_file_path)[1], ".zip")
if self.zip_output:
with ZipFile(zip_file_path, mode="w", compression=ZIP_DEFLATED, allowZip64=True) as zip_file:
self._write_graph(new_g, zip_file, cur_file_path, context_path)
else:
# Handle non-zipped output directly to a file
self._write_graph(new_g, None, cur_file_path, context_path)
self.repok.add_sentence(f"File '{cur_file_path}' added.")
def _write_graph(self, graph: ConjunctiveGraph, zip_file: ZipFile, cur_file_path, context_path):
if self.output_format == "json-ld":
# Serialize the graph in JSON-LD format
cur_json_ld = json.loads(graph.serialize(format="json-ld", context=self.context_map.get(context_path)))
if context_path is not None and context_path in self.context_map:
if isinstance(cur_json_ld, dict):
cur_json_ld["@context"] = context_path
else: # When cur_json_ld is a list
for item in cur_json_ld:
item["@context"] = context_path
# Determine how to write based on zip file presence
if zip_file is not None:
dumped_json = json.dumps(cur_json_ld, ensure_ascii=False).encode('utf-8')
zip_file.writestr(zinfo_or_arcname=os.path.basename(cur_file_path), data=dumped_json)
else:
with open(cur_file_path, 'wt', encoding='utf-8') as f:
json.dump(cur_json_ld, f, ensure_ascii=False)
else:
# Handle other RDF formats
if zip_file is not None:
rdf_serialization = graph.serialize(destination=None, format=self.output_format, encoding="utf-8")
zip_file.writestr(zinfo_or_arcname=os.path.basename(cur_file_path), data=rdf_serialization)
else:
graph.serialize(destination=cur_file_path, format=self.output_format, encoding="utf-8")
def store_all(self, base_dir: str, base_iri: str, context_path: str = None, process_id: int|str = None) -> List[str]:
self.repok.new_article()
self.reperr.new_article()
self.repok.add_sentence("Starting the process")
relevant_paths: Dict[str, list] = dict()
for entity in self.a_set.res_to_entity.values():
is_relevant = True
if self.modified_entities is not None and entity.res not in self.modified_entities:
is_relevant = False
if is_relevant:
cur_dir_path, cur_file_path = self._dir_and_file_paths(entity.res, base_dir, base_iri, process_id)
if not os.path.exists(cur_dir_path):
os.makedirs(cur_dir_path)
relevant_paths.setdefault(cur_file_path, list())
relevant_paths[cur_file_path].append(entity)
for relevant_path, entities_in_path in relevant_paths.items():
stored_g = None
# Here we try to obtain a reference to the currently stored graph
output_filepath = relevant_path.replace(os.path.splitext(relevant_path)[1], ".zip") if self.zip_output else relevant_path
lock = FileLock(f"{output_filepath}.lock")
with lock:
if os.path.exists(output_filepath):
stored_g = Reader(context_map=self.context_map).load(output_filepath)
if stored_g is None:
stored_g = ConjunctiveGraph()
for entity_in_path in entities_in_path:
self.store(entity_in_path, stored_g, relevant_path, context_path, False)
self._store_in_file(stored_g, relevant_path, context_path)
return list(relevant_paths.keys())
def store(self, entity: AbstractEntity, destination_g: ConjunctiveGraph, cur_file_path: str, context_path: str = None, store_now: bool = True) -> ConjunctiveGraph:
self.repok.new_article()
self.reperr.new_article()
try:
if isinstance(entity, ProvEntity):
quads: List[Tuple] = []
graph_identifier: URIRef = entity.g.identifier
for triple in entity.g.triples((entity.res, None, None)):
quads.append((*triple, graph_identifier))
destination_g.addN(quads)
elif isinstance(entity, GraphEntity) or isinstance(entity, MetadataEntity):
if entity.to_be_deleted:
destination_g.remove((entity.res, None, None, None))
else:
if len(entity.preexisting_graph) > 0:
| (abstract_set: 'AbstractSet', repok: 'Reporter' = None, reperr: 'Reporter' = None, context_map: 'Dict[str, Any]' = None, default_dir: 'str' = '_', dir_split: 'int' = 0, n_file_item: 'int' = 1, output_format: 'str' = 'json-ld', zip_output: 'bool' = False, modified_entities: 'set' = None) -> 'None' | [
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9,797 | oc_ocdm.storer | __init__ | null | def __init__(self, abstract_set: AbstractSet, repok: Reporter = None, reperr: Reporter = None,
context_map: Dict[str, Any] = None, default_dir: str = "_", dir_split: int = 0,
n_file_item: int = 1, output_format: str = "json-ld", zip_output: bool = False, modified_entities: set = None) -> None:
# We only accept format strings that:
# 1. are supported by rdflib
# 2. correspond to an output format which is effectively either NT or NQ
# The only exception to this rule is the 'json-ld' format, which is the default value of 'output_format'.
supported_formats: Set[str] = {'application/n-triples', 'ntriples', 'nt', 'nt11',
'application/n-quads', 'nquads', 'json-ld'}
if output_format not in supported_formats:
raise ValueError(f"Given output_format '{self.output_format}' is not supported."
f" Available formats: {supported_formats}.")
else:
self.output_format: str = output_format
self.zip_output = zip_output
self.dir_split: int = dir_split
self.n_file_item: int = n_file_item
self.default_dir: str = default_dir if default_dir != "" else "_"
self.a_set: AbstractSet = abstract_set
self.modified_entities = modified_entities
if context_map is not None:
self.context_map: Dict[str, Any] = context_map
else:
self.context_map: Dict[str, Any] = {}
if self.output_format == "json-ld":
for context_url in self.context_map:
ctx_file_path: Any = self.context_map[context_url]
if type(ctx_file_path) == str and os.path.isfile(ctx_file_path):
# This expensive operation is done only when it's really needed
with open(ctx_file_path, 'rt', encoding='utf-8') as ctx_f:
self.context_map[context_url] = json.load(ctx_f)
if repok is None:
self.repok: Reporter = Reporter(prefix="[Storer: INFO] ")
else:
self.repok: Reporter = repok
if reperr is None:
self.reperr: Reporter = Reporter(prefix="[Storer: ERROR] ")
else:
self.reperr: Reporter = reperr
| (self, abstract_set: 'AbstractSet', repok: 'Reporter' = None, reperr: 'Reporter' = None, context_map: 'Dict[str, Any]' = None, default_dir: 'str' = '_', dir_split: 'int' = 0, n_file_item: 'int' = 1, output_format: 'str' = 'json-ld', zip_output: 'bool' = False, modified_entities: 'set' = None) -> 'None' | [
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] |
9,798 | oc_ocdm.storer | _class_to_entity_type | null | @staticmethod
def _class_to_entity_type(entity: AbstractEntity) -> Optional[str]:
if isinstance(entity, GraphEntity):
return "graph"
elif isinstance(entity, ProvEntity):
return "prov"
elif isinstance(entity, MetadataEntity):
return "metadata"
else:
return None
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9,799 | oc_ocdm.storer | _dir_and_file_paths | null | def _dir_and_file_paths(self, res: URIRef, base_dir: str, base_iri: str, process_id: int|str = None) -> Tuple[str, str]:
is_json: bool = (self.output_format == "json-ld")
return find_paths(res, base_dir, base_iri, self.default_dir, self.dir_split, self.n_file_item, is_json=is_json, process_id=process_id)
| (self, res: 'URIRef', base_dir: 'str', base_iri: 'str', process_id: 'int | str' = None) -> 'Tuple[str, str]' | [
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9,800 | oc_ocdm.storer | _query | null | def _query(self, query_string: str, triplestore_url: str, base_dir: str = None,
added_statements: int = 0, removed_statements: int = 0) -> bool:
if query_string != "":
try:
sparql: SPARQLWrapper = SPARQLWrapper(triplestore_url)
sparql.setQuery(query_string)
sparql.setMethod('POST')
sparql.query()
self.repok.add_sentence(
f"Triplestore updated with {added_statements} added statements and "
f"with {removed_statements} removed statements.")
return True
except Exception as e:
self.reperr.add_sentence("[3] "
"Graph was not loaded into the "
f"triplestore due to communication problems: {e}")
if base_dir is not None:
tp_err_dir: str = base_dir + os.sep + "tp_err"
if not os.path.exists(tp_err_dir):
os.makedirs(tp_err_dir)
cur_file_err: str = tp_err_dir + os.sep + \
datetime.now().strftime('%Y-%m-%d-%H-%M-%S-%f_not_uploaded.txt')
with open(cur_file_err, 'wt', encoding='utf-8') as f:
f.write(query_string)
return False
| (self, query_string: str, triplestore_url: str, base_dir: Optional[str] = None, added_statements: int = 0, removed_statements: int = 0) -> bool | [
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9,801 | oc_ocdm.storer | _store_in_file | null | def _store_in_file(self, cur_g: ConjunctiveGraph, cur_file_path: str, context_path: str = None) -> None:
# Note: the following lines from here and until 'cur_json_ld' are a sort of hack for including all
# the triples of the input graph into the final stored file. Somehow, some of them are not written
# in such file otherwise - in particular the provenance ones.
new_g: ConjunctiveGraph = ConjunctiveGraph()
for s, p, o in cur_g.triples((None, None, None)):
g_iri: Optional[URIRef] = None
for g_context in cur_g.contexts((s, p, o)):
g_iri = g_context.identifier
break
new_g.addN([(s, p, o, g_iri)])
zip_file_path = cur_file_path.replace(os.path.splitext(cur_file_path)[1], ".zip")
if self.zip_output:
with ZipFile(zip_file_path, mode="w", compression=ZIP_DEFLATED, allowZip64=True) as zip_file:
self._write_graph(new_g, zip_file, cur_file_path, context_path)
else:
# Handle non-zipped output directly to a file
self._write_graph(new_g, None, cur_file_path, context_path)
self.repok.add_sentence(f"File '{cur_file_path}' added.")
| (self, cur_g: rdflib.graph.ConjunctiveGraph, cur_file_path: str, context_path: Optional[str] = None) -> NoneType | [
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9,802 | oc_ocdm.storer | _write_graph | null | def _write_graph(self, graph: ConjunctiveGraph, zip_file: ZipFile, cur_file_path, context_path):
if self.output_format == "json-ld":
# Serialize the graph in JSON-LD format
cur_json_ld = json.loads(graph.serialize(format="json-ld", context=self.context_map.get(context_path)))
if context_path is not None and context_path in self.context_map:
if isinstance(cur_json_ld, dict):
cur_json_ld["@context"] = context_path
else: # When cur_json_ld is a list
for item in cur_json_ld:
item["@context"] = context_path
# Determine how to write based on zip file presence
if zip_file is not None:
dumped_json = json.dumps(cur_json_ld, ensure_ascii=False).encode('utf-8')
zip_file.writestr(zinfo_or_arcname=os.path.basename(cur_file_path), data=dumped_json)
else:
with open(cur_file_path, 'wt', encoding='utf-8') as f:
json.dump(cur_json_ld, f, ensure_ascii=False)
else:
# Handle other RDF formats
if zip_file is not None:
rdf_serialization = graph.serialize(destination=None, format=self.output_format, encoding="utf-8")
zip_file.writestr(zinfo_or_arcname=os.path.basename(cur_file_path), data=rdf_serialization)
else:
graph.serialize(destination=cur_file_path, format=self.output_format, encoding="utf-8")
| (self, graph: rdflib.graph.ConjunctiveGraph, zip_file: zipfile.ZipFile, cur_file_path, context_path) | [
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9,803 | oc_ocdm.storer | execute_query | null | def execute_query(self, query_string: str, triplestore_url: str) -> bool:
self.repok.new_article()
self.reperr.new_article()
return self._query(query_string, triplestore_url)
| (self, query_string: str, triplestore_url: str) -> bool | [
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9,804 | oc_ocdm.storer | store | null | def store(self, entity: AbstractEntity, destination_g: ConjunctiveGraph, cur_file_path: str, context_path: str = None, store_now: bool = True) -> ConjunctiveGraph:
self.repok.new_article()
self.reperr.new_article()
try:
if isinstance(entity, ProvEntity):
quads: List[Tuple] = []
graph_identifier: URIRef = entity.g.identifier
for triple in entity.g.triples((entity.res, None, None)):
quads.append((*triple, graph_identifier))
destination_g.addN(quads)
elif isinstance(entity, GraphEntity) or isinstance(entity, MetadataEntity):
if entity.to_be_deleted:
destination_g.remove((entity.res, None, None, None))
else:
if len(entity.preexisting_graph) > 0:
"""
We're not in 'append mode', so we need to remove
the entity that we're going to overwrite.
"""
destination_g.remove((entity.res, None, None, None))
"""
Here we copy data from the entity into the stored graph.
If the entity was marked as to be deleted, then we're
done because we already removed all of its triples.
"""
quads: List[Tuple] = []
graph_identifier: URIRef = entity.g.identifier
for triple in entity.g.triples((entity.res, None, None)):
quads.append((*triple, graph_identifier))
destination_g.addN(quads)
if store_now:
self._store_in_file(destination_g, cur_file_path, context_path)
return destination_g
except Exception as e:
self.reperr.add_sentence(f"[1] It was impossible to store the RDF statements in {cur_file_path}. {e}")
| (self, entity: 'AbstractEntity', destination_g: 'ConjunctiveGraph', cur_file_path: 'str', context_path: 'str' = None, store_now: 'bool' = True) -> 'ConjunctiveGraph' | [
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] |
9,805 | oc_ocdm.storer | store_all | null | def store_all(self, base_dir: str, base_iri: str, context_path: str = None, process_id: int|str = None) -> List[str]:
self.repok.new_article()
self.reperr.new_article()
self.repok.add_sentence("Starting the process")
relevant_paths: Dict[str, list] = dict()
for entity in self.a_set.res_to_entity.values():
is_relevant = True
if self.modified_entities is not None and entity.res not in self.modified_entities:
is_relevant = False
if is_relevant:
cur_dir_path, cur_file_path = self._dir_and_file_paths(entity.res, base_dir, base_iri, process_id)
if not os.path.exists(cur_dir_path):
os.makedirs(cur_dir_path)
relevant_paths.setdefault(cur_file_path, list())
relevant_paths[cur_file_path].append(entity)
for relevant_path, entities_in_path in relevant_paths.items():
stored_g = None
# Here we try to obtain a reference to the currently stored graph
output_filepath = relevant_path.replace(os.path.splitext(relevant_path)[1], ".zip") if self.zip_output else relevant_path
lock = FileLock(f"{output_filepath}.lock")
with lock:
if os.path.exists(output_filepath):
stored_g = Reader(context_map=self.context_map).load(output_filepath)
if stored_g is None:
stored_g = ConjunctiveGraph()
for entity_in_path in entities_in_path:
self.store(entity_in_path, stored_g, relevant_path, context_path, False)
self._store_in_file(stored_g, relevant_path, context_path)
return list(relevant_paths.keys())
| (self, base_dir: 'str', base_iri: 'str', context_path: 'str' = None, process_id: 'int | str' = None) -> 'List[str]' | [
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9,806 | oc_ocdm.storer | store_graphs_in_file | null | def store_graphs_in_file(self, file_path: str, context_path: str = None) -> None:
self.repok.new_article()
self.reperr.new_article()
self.repok.add_sentence("Store the graphs into a file: starting process")
cg: ConjunctiveGraph = ConjunctiveGraph()
for g in self.a_set.graphs():
cg.addN([item + (g.identifier,) for item in list(g)])
self._store_in_file(cg, file_path, context_path)
| (self, file_path: str, context_path: Optional[str] = None) -> NoneType | [
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9,807 | oc_ocdm.storer | upload | null | def upload(self, entity: AbstractEntity, triplestore_url: str, base_dir: str = None) -> bool:
self.repok.new_article()
self.reperr.new_article()
update_query, n_added, n_removed = get_update_query(entity, entity_type=self._class_to_entity_type(entity))
return self._query(update_query, triplestore_url, base_dir, n_added, n_removed)
| (self, entity: 'AbstractEntity', triplestore_url: 'str', base_dir: 'str' = None) -> 'bool' | [
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9,808 | oc_ocdm.storer | upload_all | null | def upload_all(self, triplestore_url: str, base_dir: str = None, batch_size: int = 10) -> bool:
self.repok.new_article()
self.reperr.new_article()
if batch_size <= 0:
batch_size = 10
query_string: str = ""
added_statements: int = 0
removed_statements: int = 0
skipped_queries: int = 0
result: bool = True
for idx, entity in enumerate(self.a_set.res_to_entity.values()):
update_query, n_added, n_removed = get_update_query(entity, entity_type=self._class_to_entity_type(entity))
if update_query == "":
skipped_queries += 1
else:
index = idx - skipped_queries
if index == 0:
# First query
query_string = update_query
added_statements = n_added
removed_statements = n_removed
elif index % batch_size == 0:
# batch_size-multiple query
result &= self._query(query_string, triplestore_url, base_dir, added_statements, removed_statements)
query_string = update_query
added_statements = n_added
removed_statements = n_removed
else:
# Accumulated query
query_string += " ; " + update_query
added_statements += n_added
removed_statements += n_removed
if query_string != "":
result &= self._query(query_string, triplestore_url, base_dir, added_statements, removed_statements)
return result
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9,809 | oc_ocdm.storer | upload_and_store | null | def upload_and_store(self, base_dir: str, triplestore_url: str, base_iri: str, context_path: str = None,
batch_size: int = 10) -> None:
stored_graph_path: List[str] = self.store_all(base_dir, base_iri, context_path)
# If some graphs were not stored properly, then no one will be uploaded to the triplestore
# Anyway, we should highlight those ones that could have been added in principle, by
# mentioning them with a ".notuploaded" marker
if None in stored_graph_path:
for file_path in stored_graph_path:
if file_path is not None:
# Create a marker for the file not uploaded in the triplestore
open(f'{file_path}.notuploaded', 'wt', encoding='utf-8').close()
self.reperr.add_sentence("[2] "
f"The statements contained in the JSON-LD file '{file_path}' "
"were not uploaded into the triplestore.")
else: # All the files have been stored
self.upload_all(triplestore_url, base_dir, batch_size)
| (self, base_dir: str, triplestore_url: str, base_iri: str, context_path: Optional[str] = None, batch_size: int = 10) -> NoneType | [
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] |
9,820 | myx.client | Client | All client functions return the response in json format, except for get_file | class Client():
"""All client functions return the response in json format, except for get_file"""
def __init__(self, email: str, password: str, base_url="https://platform.myxrobotics.com"):
self.base_url = base_url
self.session = requests.Session()
r = self.session.post(f'{self.base_url}/users/login/',
data={'email': email, 'password': password},
allow_redirects=False
)
if r.headers['location'] != '/dashboard/':
raise Exception("Failed to authenticate. Check your email and password are correct.")
def get_file(self, twin_id: int, file_path: str):
""" Download a file if it exists. Returns a file-like object from which you can read in
binary mode. Some twin files are generated by MYX."""
return self.session.get(f'{self.base_url}/twins/{twin_id}/data/{file_path}', stream=True).raw
def upload_dir(self, directory, show_status=True):
""" Upload all files in a directory. """
for root, subdirs, files in os.walk(directory):
for fn in files:
path = os.path.join(root, fn)
if show_status: print(f"Uploading {path}")
self.upload_file(path)
def upload_file(self, filename):
""" Upload a single file from the filesystem. """
with open(filename, 'rb') as f:
return self.session.post(f'{self.base_url}/upload/file/', files={'file': f})
def finish_upload(self, twin_name='Twin from API', client_group=''):
""" Give a name for the new twin and notify MYX that there will be no more images uploaded.
This triggers the processing pipeline to start working on your data.
The first return value is whether or not you had enough balance to complete the upload.
The second value is the URL you should go to add more money to your account.
"""
r = self.session.post(f'{self.base_url}/upload/checkout/begin/', json={
'twinName': twin_name,
'clientGroup': client_group,
})
next_url = r.json()['url']
if next_url.startswith(f'{self.base_url}/upload/checkout/success/'):
self.session.get(next_url)
return True, ''
else:
return False, next_url
def get_annotations(self, twin_id: int):
""" Get a list of all annotations for a given twin. """
return self.session.get(f'{self.base_url}/twins/{twin_id}/annotations/').json()
def make_new_annotation(self, twin_id: int, x: float, y: float, z: float, label: str, iframeURL: str, notes: str):
""" Make a new annotation at the given position, with the given label,
url and additional notes. """
return self.session.post(f'{self.base_url}/twins/{twin_id}/annotations/', json={
'x': x,
'y': y,
'z': z,
'label': label,
'iframeURL': iframeURL,
'notes': notes,
}).json()
def get_twins(self) :
""" Get a list of all twins you own. """
return self.session.get(f'{self.base_url}/api/list_all/').json()
#Twin(str(json['id']), json['name'], json['latitude'], json['longitude'], json['captureDate'])
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9,821 | myx.client | __init__ | null | def __init__(self, email: str, password: str, base_url="https://platform.myxrobotics.com"):
self.base_url = base_url
self.session = requests.Session()
r = self.session.post(f'{self.base_url}/users/login/',
data={'email': email, 'password': password},
allow_redirects=False
)
if r.headers['location'] != '/dashboard/':
raise Exception("Failed to authenticate. Check your email and password are correct.")
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] |
9,822 | myx.client | finish_upload | Give a name for the new twin and notify MYX that there will be no more images uploaded.
This triggers the processing pipeline to start working on your data.
The first return value is whether or not you had enough balance to complete the upload.
The second value is the URL you should go to add more money to your account.
| def finish_upload(self, twin_name='Twin from API', client_group=''):
""" Give a name for the new twin and notify MYX that there will be no more images uploaded.
This triggers the processing pipeline to start working on your data.
The first return value is whether or not you had enough balance to complete the upload.
The second value is the URL you should go to add more money to your account.
"""
r = self.session.post(f'{self.base_url}/upload/checkout/begin/', json={
'twinName': twin_name,
'clientGroup': client_group,
})
next_url = r.json()['url']
if next_url.startswith(f'{self.base_url}/upload/checkout/success/'):
self.session.get(next_url)
return True, ''
else:
return False, next_url
| (self, twin_name='Twin from API', client_group='') | [
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9,823 | myx.client | get_annotations | Get a list of all annotations for a given twin. | def get_annotations(self, twin_id: int):
""" Get a list of all annotations for a given twin. """
return self.session.get(f'{self.base_url}/twins/{twin_id}/annotations/').json()
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9,824 | myx.client | get_file | Download a file if it exists. Returns a file-like object from which you can read in
binary mode. Some twin files are generated by MYX. | def get_file(self, twin_id: int, file_path: str):
""" Download a file if it exists. Returns a file-like object from which you can read in
binary mode. Some twin files are generated by MYX."""
return self.session.get(f'{self.base_url}/twins/{twin_id}/data/{file_path}', stream=True).raw
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9,825 | myx.client | get_twins | Get a list of all twins you own. | def get_twins(self) :
""" Get a list of all twins you own. """
return self.session.get(f'{self.base_url}/api/list_all/').json()
#Twin(str(json['id']), json['name'], json['latitude'], json['longitude'], json['captureDate'])
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9,826 | myx.client | make_new_annotation | Make a new annotation at the given position, with the given label,
url and additional notes. | def make_new_annotation(self, twin_id: int, x: float, y: float, z: float, label: str, iframeURL: str, notes: str):
""" Make a new annotation at the given position, with the given label,
url and additional notes. """
return self.session.post(f'{self.base_url}/twins/{twin_id}/annotations/', json={
'x': x,
'y': y,
'z': z,
'label': label,
'iframeURL': iframeURL,
'notes': notes,
}).json()
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9,827 | myx.client | upload_dir | Upload all files in a directory. | def upload_dir(self, directory, show_status=True):
""" Upload all files in a directory. """
for root, subdirs, files in os.walk(directory):
for fn in files:
path = os.path.join(root, fn)
if show_status: print(f"Uploading {path}")
self.upload_file(path)
| (self, directory, show_status=True) | [
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9,828 | myx.client | upload_file | Upload a single file from the filesystem. | def upload_file(self, filename):
""" Upload a single file from the filesystem. """
with open(filename, 'rb') as f:
return self.session.post(f'{self.base_url}/upload/file/', files={'file': f})
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9,830 | pygeoif.feature | Feature |
Aggregates a geometry instance with associated user-defined properties.
Attributes:
----------
geometry : object
A geometry instance
properties : dict
A dictionary linking field keys with values
associated with geometry instance
Example:
-------
>>> p = Point(1.0, -1.0)
>>> props = {'Name': 'Sample Point', 'Other': 'Other Data'}
>>> a = Feature(p, props)
>>> a.properties
{'Name': 'Sample Point', 'Other': 'Other Data'}
>>> a.properties['Name']
'Sample Point'
| class Feature:
"""
Aggregates a geometry instance with associated user-defined properties.
Attributes:
----------
geometry : object
A geometry instance
properties : dict
A dictionary linking field keys with values
associated with geometry instance
Example:
-------
>>> p = Point(1.0, -1.0)
>>> props = {'Name': 'Sample Point', 'Other': 'Other Data'}
>>> a = Feature(p, props)
>>> a.properties
{'Name': 'Sample Point', 'Other': 'Other Data'}
>>> a.properties['Name']
'Sample Point'
"""
def __init__(
self,
geometry: Geometry,
properties: Optional[Dict[str, Any]] = None,
feature_id: Optional[Union[str, int]] = None,
) -> None:
"""Initialize the feature."""
self._geometry = geometry
self._properties = properties or {}
self._feature_id = feature_id
def __eq__(self, other: object) -> bool:
"""Check if the geointerfaces are equal."""
try:
if not other.__geo_interface__.get( # type: ignore [attr-defined]
"geometry",
):
return False
except AttributeError:
return False
return feature_geo_interface_equals(
my_interface=self.__geo_interface__,
other_interface=other.__geo_interface__, # type: ignore [attr-defined]
)
def __repr__(self) -> str:
"""Return the representation."""
return (
f"{self.__class__.__name__}({self._geometry!r},"
f" {self._properties}, {self._feature_id!r})"
)
@property
def id(self) -> Optional[Union[str, int]]:
"""Return the id of the feature."""
return self._feature_id
@property
def geometry(self) -> Geometry:
"""Return the geometry of the feature."""
return self._geometry
@property
def properties(self) -> Dict[str, Any]:
"""Return a dictionary of properties."""
return self._properties
@property
def __geo_interface__(self) -> GeoFeatureInterface:
"""Return the GeoInterface of the geometry with properties."""
geo_interface: GeoFeatureInterface = {
"type": "Feature",
"bbox": cast(Bounds, self._geometry.bounds),
"geometry": self._geometry.__geo_interface__,
"properties": self._properties,
}
if self._feature_id is not None:
geo_interface["id"] = self._feature_id
return geo_interface
| (geometry: Union[pygeoif.geometry.Point, pygeoif.geometry.LineString, pygeoif.geometry.LinearRing, pygeoif.geometry.Polygon, pygeoif.geometry.MultiPoint, pygeoif.geometry.MultiLineString, pygeoif.geometry.MultiPolygon], properties: Optional[Dict[str, Any]] = None, feature_id: Union[str, int, NoneType] = None) -> None | [
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9,831 | pygeoif.feature | __eq__ | Check if the geointerfaces are equal. | def __eq__(self, other: object) -> bool:
"""Check if the geointerfaces are equal."""
try:
if not other.__geo_interface__.get( # type: ignore [attr-defined]
"geometry",
):
return False
except AttributeError:
return False
return feature_geo_interface_equals(
my_interface=self.__geo_interface__,
other_interface=other.__geo_interface__, # type: ignore [attr-defined]
)
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9,832 | pygeoif.feature | __init__ | Initialize the feature. | def __init__(
self,
geometry: Geometry,
properties: Optional[Dict[str, Any]] = None,
feature_id: Optional[Union[str, int]] = None,
) -> None:
"""Initialize the feature."""
self._geometry = geometry
self._properties = properties or {}
self._feature_id = feature_id
| (self, geometry: Union[pygeoif.geometry.Point, pygeoif.geometry.LineString, pygeoif.geometry.LinearRing, pygeoif.geometry.Polygon, pygeoif.geometry.MultiPoint, pygeoif.geometry.MultiLineString, pygeoif.geometry.MultiPolygon], properties: Optional[Dict[str, Any]] = None, feature_id: Union[str, int, NoneType] = None) -> NoneType | [
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9,833 | pygeoif.feature | __repr__ | Return the representation. | def __repr__(self) -> str:
"""Return the representation."""
return (
f"{self.__class__.__name__}({self._geometry!r},"
f" {self._properties}, {self._feature_id!r})"
)
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] |
9,834 | pygeoif.feature | FeatureCollection |
A heterogenous collection of Features.
Attributes:
----------
features : sequence
A sequence of feature instances
Example:
-------
>>> from pygeoif import geometry
>>> p = geometry.Point(1.0, -1.0)
>>> props = {'Name': 'Sample Point', 'Other': 'Other Data'}
>>> a = geometry.Feature(p, props)
>>> p2 = geometry.Point(1.0, -1.0)
>>> props2 = {'Name': 'Sample Point2', 'Other': 'Other Data2'}
>>> b = geometry.Feature(p2, props2)
>>> features = [a, b]
>>> c = geometry.FeatureCollection(features)
>>> c.__geo_interface__
{'type': 'FeatureCollection',
'features': [{'geometry': {'type': 'Point', 'coordinates': (1.0, -1.0)},
'type': 'Feature',
'properties': {'Other': 'Other Data', 'Name': 'Sample Point'}},
{'geometry': {'type': 'Point', 'coordinates': (1.0, -1.0)},
'type': 'Feature',
'properties': {'Other': 'Other Data2', 'Name': 'Sample Point2'}}]}
| class FeatureCollection:
"""
A heterogenous collection of Features.
Attributes:
----------
features : sequence
A sequence of feature instances
Example:
-------
>>> from pygeoif import geometry
>>> p = geometry.Point(1.0, -1.0)
>>> props = {'Name': 'Sample Point', 'Other': 'Other Data'}
>>> a = geometry.Feature(p, props)
>>> p2 = geometry.Point(1.0, -1.0)
>>> props2 = {'Name': 'Sample Point2', 'Other': 'Other Data2'}
>>> b = geometry.Feature(p2, props2)
>>> features = [a, b]
>>> c = geometry.FeatureCollection(features)
>>> c.__geo_interface__
{'type': 'FeatureCollection',
'features': [{'geometry': {'type': 'Point', 'coordinates': (1.0, -1.0)},
'type': 'Feature',
'properties': {'Other': 'Other Data', 'Name': 'Sample Point'}},
{'geometry': {'type': 'Point', 'coordinates': (1.0, -1.0)},
'type': 'Feature',
'properties': {'Other': 'Other Data2', 'Name': 'Sample Point2'}}]}
"""
def __init__(self, features: Sequence[Feature]) -> None:
"""Initialize the feature."""
self._features = tuple(features)
def __eq__(self, other: object) -> bool:
"""Check if the geointerfaces are equal."""
return self._check_interface(other) and all(
(
feature_geo_interface_equals(my_interface=mine, other_interface=other)
for mine, other in zip(
self.__geo_interface__["features"],
other.__geo_interface__["features"], # type: ignore [attr-defined]
)
),
)
def __len__(self) -> int:
"""Return the umber of features in this collection."""
return len(self._features)
def __iter__(self) -> Iterator[Feature]:
"""Iterate over the features of the collection."""
return iter(self._features)
def __repr__(self) -> str:
"""Return the representation."""
return f"{self.__class__.__name__}({self._features!r})"
@property
def features(self) -> Generator[Feature, None, None]:
"""Iterate over the features of the collection."""
yield from self._features
@property
def bounds(self) -> Bounds:
"""Return the X-Y bounding box."""
geom_bounds = list(
zip(*(feature.geometry.bounds for feature in self._features)),
)
return (
min(geom_bounds[0]),
min(geom_bounds[1]),
max(geom_bounds[2]),
max(geom_bounds[3]),
)
@property
def __geo_interface__(self) -> GeoFeatureCollectionInterface:
"""Return the GeoInterface of the feature."""
return {
"type": "FeatureCollection",
"bbox": self.bounds,
"features": tuple(feature.__geo_interface__ for feature in self._features),
}
def _check_interface(self, other: object) -> bool:
try:
return self.__geo_interface__[
"type"
] == other.__geo_interface__.get( # type: ignore [attr-defined]
"type",
) and len(
self.__geo_interface__["features"],
) == len(
other.__geo_interface__.get( # type: ignore [attr-defined]
"features",
[],
),
)
except AttributeError:
return False
| (features: Sequence[pygeoif.feature.Feature]) -> None | [
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] |
9,835 | pygeoif.feature | __eq__ | Check if the geointerfaces are equal. | def __eq__(self, other: object) -> bool:
"""Check if the geointerfaces are equal."""
return self._check_interface(other) and all(
(
feature_geo_interface_equals(my_interface=mine, other_interface=other)
for mine, other in zip(
self.__geo_interface__["features"],
other.__geo_interface__["features"], # type: ignore [attr-defined]
)
),
)
| (self, other: object) -> bool | [
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] |
9,836 | pygeoif.feature | __init__ | Initialize the feature. | def __init__(self, features: Sequence[Feature]) -> None:
"""Initialize the feature."""
self._features = tuple(features)
| (self, features: Sequence[pygeoif.feature.Feature]) -> NoneType | [
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9,837 | pygeoif.feature | __iter__ | Iterate over the features of the collection. | def __iter__(self) -> Iterator[Feature]:
"""Iterate over the features of the collection."""
return iter(self._features)
| (self) -> Iterator[pygeoif.feature.Feature] | [
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9,838 | pygeoif.feature | __len__ | Return the umber of features in this collection. | def __len__(self) -> int:
"""Return the umber of features in this collection."""
return len(self._features)
| (self) -> int | [
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9,839 | pygeoif.feature | __repr__ | Return the representation. | def __repr__(self) -> str:
"""Return the representation."""
return f"{self.__class__.__name__}({self._features!r})"
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] |
9,840 | pygeoif.feature | _check_interface | null | def _check_interface(self, other: object) -> bool:
try:
return self.__geo_interface__[
"type"
] == other.__geo_interface__.get( # type: ignore [attr-defined]
"type",
) and len(
self.__geo_interface__["features"],
) == len(
other.__geo_interface__.get( # type: ignore [attr-defined]
"features",
[],
),
)
except AttributeError:
return False
| (self, other: object) -> bool | [
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9,841 | pygeoif.geometry | GeometryCollection |
A heterogenous collection of geometries.
Attributes:
----------
geoms : sequence
A sequence of geometry instances
Please note:
GEOMETRYCOLLECTION isn't supported by the Shapefile format. And this sub-
class isn't generally supported by ordinary GIS sw (viewers and so on). So
it's very rarely used in the real GIS professional world.
Example:
-------
Initialize Geometries and construct a GeometryCollection
>>> from pygeoif import geometry
>>> p = geometry.Point(1.0, -1.0)
>>> p2 = geometry.Point(1.0, -1.0)
>>> geoms = [p, p2]
>>> c = geometry.GeometryCollection(geoms)
>>> c.__geo_interface__
{'type': 'GeometryCollection',
'geometries': [{'type': 'Point', 'coordinates': (1.0, -1.0)},
{'type': 'Point', 'coordinates': (1.0, -1.0)}]}
| class GeometryCollection(_MultiGeometry):
"""
A heterogenous collection of geometries.
Attributes:
----------
geoms : sequence
A sequence of geometry instances
Please note:
GEOMETRYCOLLECTION isn't supported by the Shapefile format. And this sub-
class isn't generally supported by ordinary GIS sw (viewers and so on). So
it's very rarely used in the real GIS professional world.
Example:
-------
Initialize Geometries and construct a GeometryCollection
>>> from pygeoif import geometry
>>> p = geometry.Point(1.0, -1.0)
>>> p2 = geometry.Point(1.0, -1.0)
>>> geoms = [p, p2]
>>> c = geometry.GeometryCollection(geoms)
>>> c.__geo_interface__
{'type': 'GeometryCollection',
'geometries': [{'type': 'Point', 'coordinates': (1.0, -1.0)},
{'type': 'Point', 'coordinates': (1.0, -1.0)}]}
"""
_geoms: Tuple[Union[Geometry, "GeometryCollection"], ...]
def __init__(
self,
geometries: Iterable[Union[Geometry, "GeometryCollection"]],
) -> None:
"""
Initialize the MultiGeometry with Geometries.
Args:
----
geometries (Iterable[Geometry]
"""
object.__setattr__(self, "_geoms", tuple(geom for geom in geometries if geom))
def __eq__(self, other: object) -> bool:
"""
Return equality between collections.
Types and coordinates from all contained geometries must be equal.
"""
try:
if self.is_empty:
return False
if (
other.__geo_interface__.get("type") # type: ignore [attr-defined]
!= self.geom_type
):
return False
if len(
other.__geo_interface__.get( # type: ignore [attr-defined]
"geometries",
[],
),
) != len(
self,
):
return False
except AttributeError:
return False
return compare_geo_interface(
first=self.__geo_interface__,
second=other.__geo_interface__, # type: ignore [attr-defined]
)
def __len__(self) -> int:
"""
Length of the collection.
Returns
-------
int: Number of geometries in the collection.
"""
return len(self._geoms)
def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}({tuple(self.geoms)})"
@property
def _wkt_coords(self) -> str:
return ", ".join(geom.wkt for geom in self.geoms)
@property
def __geo_interface__(self) -> GeoCollectionInterface: # type: ignore [override]
"""Return the geo interface of the collection."""
return {
"type": "GeometryCollection",
"geometries": tuple(geom.__geo_interface__ for geom in self.geoms),
}
def _prepare_hull(self) -> Iterable[Point2D]:
return chain.from_iterable(
geom._prepare_hull() for geom in self.geoms # noqa: SLF001
)
| (geometries: Iterable[Union[pygeoif.geometry.Point, pygeoif.geometry.LineString, pygeoif.geometry.LinearRing, pygeoif.geometry.Polygon, pygeoif.geometry.MultiPoint, pygeoif.geometry.MultiLineString, pygeoif.geometry.MultiPolygon, ForwardRef('GeometryCollection')]]) -> None | [
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9,842 | pygeoif.geometry | __bool__ | null | def __bool__(self) -> bool:
return self.is_empty is False
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9,843 | pygeoif.geometry | __delattr__ | null | def __delattr__(self, *args: Any) -> NoReturn: # noqa: ANN401
msg = f"Attributes of {self.__class__.__name__} cannot be deleted"
raise AttributeError(
msg,
)
| (self, *args: Any) -> NoReturn | [
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] |
9,844 | pygeoif.geometry | __eq__ |
Return equality between collections.
Types and coordinates from all contained geometries must be equal.
| def __eq__(self, other: object) -> bool:
"""
Return equality between collections.
Types and coordinates from all contained geometries must be equal.
"""
try:
if self.is_empty:
return False
if (
other.__geo_interface__.get("type") # type: ignore [attr-defined]
!= self.geom_type
):
return False
if len(
other.__geo_interface__.get( # type: ignore [attr-defined]
"geometries",
[],
),
) != len(
self,
):
return False
except AttributeError:
return False
return compare_geo_interface(
first=self.__geo_interface__,
second=other.__geo_interface__, # type: ignore [attr-defined]
)
| (self, other: object) -> bool | [
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9,845 | pygeoif.geometry | __init__ |
Initialize the MultiGeometry with Geometries.
Args:
----
geometries (Iterable[Geometry]
| def __init__(
self,
geometries: Iterable[Union[Geometry, "GeometryCollection"]],
) -> None:
"""
Initialize the MultiGeometry with Geometries.
Args:
----
geometries (Iterable[Geometry]
"""
object.__setattr__(self, "_geoms", tuple(geom for geom in geometries if geom))
| (self, geometries: Iterable[Union[pygeoif.geometry.Point, pygeoif.geometry.LineString, pygeoif.geometry.LinearRing, pygeoif.geometry.Polygon, pygeoif.geometry.MultiPoint, pygeoif.geometry.MultiLineString, pygeoif.geometry.MultiPolygon, pygeoif.geometry.GeometryCollection]]) -> NoneType | [
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9,846 | pygeoif.geometry | __len__ |
Length of the collection.
Returns
-------
int: Number of geometries in the collection.
| def __len__(self) -> int:
"""
Length of the collection.
Returns
-------
int: Number of geometries in the collection.
"""
return len(self._geoms)
| (self) -> int | [
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9,847 | pygeoif.geometry | __repr__ | Return the representation. | def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}({tuple(self.geoms)})"
| (self) -> str | [
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] |
9,848 | pygeoif.geometry | __setattr__ | null | def __setattr__(self, *args: Any) -> NoReturn: # noqa: ANN401
msg = f"Attributes of {self.__class__.__name__} cannot be changed"
raise AttributeError(
msg,
)
| (self, *args: Any) -> NoReturn | [
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9,849 | pygeoif.geometry | __str__ | null | def __str__(self) -> str:
return self.wkt
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] |
9,850 | pygeoif.geometry | _get_bounds | Return the X-Y bounding box. | def _get_bounds(self) -> Bounds:
"""Return the X-Y bounding box."""
geom_bounds = list(
zip(*(geom.bounds for geom in self.geoms)),
)
return (
min(geom_bounds[0]),
min(geom_bounds[1]),
max(geom_bounds[2]),
max(geom_bounds[3]),
)
| (self) -> Tuple[float, float, float, float] | [
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9,851 | pygeoif.geometry | _prepare_hull | null | def _prepare_hull(self) -> Iterable[Point2D]:
return chain.from_iterable(
geom._prepare_hull() for geom in self.geoms # noqa: SLF001
)
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9,852 | pygeoif.geometry | LineString |
A one-dimensional figure comprising one or more line segments.
A LineString has non-zero length and zero area. It may approximate a curve
and need not be straight. Unlike a LinearRing, a LineString is not closed.
Attributes
----------
geoms : sequence
A sequence of Points
| class LineString(_Geometry):
"""
A one-dimensional figure comprising one or more line segments.
A LineString has non-zero length and zero area. It may approximate a curve
and need not be straight. Unlike a LinearRing, a LineString is not closed.
Attributes
----------
geoms : sequence
A sequence of Points
"""
_geoms: Tuple[Point, ...]
def __init__(self, coordinates: LineType) -> None:
"""
Initialize a Linestring.
Parameters
----------
coordinates : sequence
A sequence of (x, y [,z]) numeric coordinate pairs or triples
Example
-------
Create a line with two segments
>>> a = LineString([(0, 0), (1, 0), (1, 1)])
"""
object.__setattr__(self, "_geoms", self._set_geoms(coordinates))
def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}({self.coords})"
@property
def geoms(self) -> Tuple[Point, ...]:
"""Return the underlying geometries."""
return self._geoms
@property
def coords(self) -> LineType:
"""Return the geometry coordinates."""
return cast(
LineType,
tuple(point.coords[0] for point in self.geoms if point.coords),
)
@property
def is_empty(self) -> bool:
"""
Return if this geometry is empty.
A Linestring is considered empty when it has no points.
"""
return len(self._geoms) == 0
@property
def has_z(self) -> Optional[bool]:
"""Return True if the geometry's coordinate sequence(s) have z values."""
return self._geoms[0].has_z if self.geoms else None
@property
def _wkt_coords(self) -> str:
return ", ".join(point._wkt_coords for point in self.geoms) # noqa: SLF001
@property
def __geo_interface__(self) -> GeoInterface:
"""Return the geo interface."""
geo_interface = super().__geo_interface__
geo_interface["coordinates"] = self.coords
return geo_interface
@classmethod
def from_coordinates(cls, coordinates: LineType) -> "LineString":
"""Construct a linestring from coordinates."""
return cls(coordinates)
@classmethod
def from_points(cls, *args: Point) -> "LineString":
"""Create a linestring from points."""
return cls(
cast(LineType, tuple(point.coords[0] for point in args if point.coords)),
)
@classmethod
def _from_dict(cls, geo_interface: GeoInterface) -> "LineString":
cls._check_dict(geo_interface)
return cls(cast(LineType, geo_interface["coordinates"]))
@staticmethod
def _set_geoms(coordinates: LineType) -> Tuple[Point, ...]:
geoms = []
last_len = None
for coord in dedupe(coordinates):
if len(coord) != last_len and last_len is not None:
msg = ( # type: ignore [unreachable]
"All coordinates must have the same dimension"
)
raise DimensionError(
msg,
)
last_len = len(coord)
point = Point(*coord)
if point:
geoms.append(point)
return tuple(geoms)
def _get_bounds(self) -> Bounds:
"""Return the X-Y bounding box."""
xy = list(zip(*((p.x, p.y) for p in self._geoms)))
return (
min(xy[0]),
min(xy[1]),
max(xy[0]),
max(xy[1]),
)
def _prepare_hull(self) -> Iterable[Point2D]:
return ((pt.x, pt.y) for pt in self._geoms)
| (coordinates: Union[Sequence[Tuple[float, float]], Sequence[Tuple[float, float, float]]]) -> None | [
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] |
9,855 | pygeoif.geometry | __eq__ |
Check if the geometry objects have the same coordinates and type.
Empty geometries are always considered as not equal.
| def __eq__(self, other: object) -> bool:
"""
Check if the geometry objects have the same coordinates and type.
Empty geometries are always considered as not equal.
"""
try:
return all(
(
not self.is_empty,
self.__geo_interface__["type"]
== other.__geo_interface__.get( # type: ignore [attr-defined]
"type",
),
compare_coordinates(
coords=self.__geo_interface__["coordinates"],
other=other.__geo_interface__.get( # type: ignore [attr-defined]
"coordinates",
),
),
),
)
except AttributeError:
return False
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9,856 | pygeoif.geometry | __init__ |
Initialize a Linestring.
Parameters
----------
coordinates : sequence
A sequence of (x, y [,z]) numeric coordinate pairs or triples
Example
-------
Create a line with two segments
>>> a = LineString([(0, 0), (1, 0), (1, 1)])
| def __init__(self, coordinates: LineType) -> None:
"""
Initialize a Linestring.
Parameters
----------
coordinates : sequence
A sequence of (x, y [,z]) numeric coordinate pairs or triples
Example
-------
Create a line with two segments
>>> a = LineString([(0, 0), (1, 0), (1, 1)])
"""
object.__setattr__(self, "_geoms", self._set_geoms(coordinates))
| (self, coordinates: Union[Sequence[Tuple[float, float]], Sequence[Tuple[float, float, float]]]) -> NoneType | [
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9,857 | pygeoif.geometry | __repr__ | Return the representation. | def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}({self.coords})"
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] |
9,860 | pygeoif.geometry | _get_bounds | Return the X-Y bounding box. | def _get_bounds(self) -> Bounds:
"""Return the X-Y bounding box."""
xy = list(zip(*((p.x, p.y) for p in self._geoms)))
return (
min(xy[0]),
min(xy[1]),
max(xy[0]),
max(xy[1]),
)
| (self) -> Tuple[float, float, float, float] | [
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9,861 | pygeoif.geometry | _prepare_hull | null | def _prepare_hull(self) -> Iterable[Point2D]:
return ((pt.x, pt.y) for pt in self._geoms)
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] |
9,862 | pygeoif.geometry | _set_geoms | null | @staticmethod
def _set_geoms(coordinates: LineType) -> Tuple[Point, ...]:
geoms = []
last_len = None
for coord in dedupe(coordinates):
if len(coord) != last_len and last_len is not None:
msg = ( # type: ignore [unreachable]
"All coordinates must have the same dimension"
)
raise DimensionError(
msg,
)
last_len = len(coord)
point = Point(*coord)
if point:
geoms.append(point)
return tuple(geoms)
| (coordinates: Union[Sequence[Tuple[float, float]], Sequence[Tuple[float, float, float]]]) -> Tuple[pygeoif.geometry.Point, ...] | [
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9,863 | pygeoif.geometry | LinearRing |
A closed one-dimensional geometry comprising one or more line segments.
A LinearRing that crosses itself or touches itself at a single point is
invalid and operations on it may fail.
A Linear Ring is self closing
| class LinearRing(LineString):
"""
A closed one-dimensional geometry comprising one or more line segments.
A LinearRing that crosses itself or touches itself at a single point is
invalid and operations on it may fail.
A Linear Ring is self closing
"""
def __init__(self, coordinates: LineType) -> None:
"""
Initialize a LinearRing.
Args:
----
coordinates (Sequence):
A sequence of (x, y [,z]) numeric coordinate pairs or triples
"""
super().__init__(coordinates)
if not self.is_empty and self._geoms[0].coords != self._geoms[-1].coords:
object.__setattr__(self, "_geoms", (*self._geoms, self._geoms[0]))
@property
def centroid(self) -> Optional[Point]:
"""Return the centroid of the ring."""
if self.has_z:
msg = "Centeroid is only implemented for 2D coordinates"
raise DimensionError(msg)
cent, area = centroid(self.coords)
if any(math.isnan(coord) for coord in cent):
return None
return (
Point(x=cent[0], y=cent[1])
if math.isclose(a=area, b=signed_area(self.coords))
else None
)
@property
def is_ccw(self) -> bool:
"""Return True if the ring is oriented counter clock-wise."""
return signed_area(self.coords) >= 0
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9,867 | pygeoif.geometry | __init__ |
Initialize a LinearRing.
Args:
----
coordinates (Sequence):
A sequence of (x, y [,z]) numeric coordinate pairs or triples
| def __init__(self, coordinates: LineType) -> None:
"""
Initialize a LinearRing.
Args:
----
coordinates (Sequence):
A sequence of (x, y [,z]) numeric coordinate pairs or triples
"""
super().__init__(coordinates)
if not self.is_empty and self._geoms[0].coords != self._geoms[-1].coords:
object.__setattr__(self, "_geoms", (*self._geoms, self._geoms[0]))
| (self, coordinates: Union[Sequence[Tuple[float, float]], Sequence[Tuple[float, float, float]]]) -> NoneType | [
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9,874 | pygeoif.geometry | MultiLineString |
A collection of one or more line strings.
A MultiLineString has non-zero length and zero area.
Attributes
----------
geoms : sequence
A sequence of LineStrings
| class MultiLineString(_MultiGeometry):
"""
A collection of one or more line strings.
A MultiLineString has non-zero length and zero area.
Attributes
----------
geoms : sequence
A sequence of LineStrings
"""
_geoms: Tuple[LineString, ...]
def __init__(self, lines: Sequence[LineType], unique: bool = False) -> None:
"""
Initialize the MultiLineString.
Parameters
----------
lines : sequence
A sequence of line-like coordinate sequences.
unique: boolean,
when unique is true duplicates will be removed,
the ordering will not be preserved.
Example
-------
Construct a collection containing one line string.
>>> lines = MultiLineString( [[[0.0, 0.0], [1.0, 2.0]]] )
"""
if unique:
lines = {tuple(line) for line in lines} # type: ignore [assignment]
object.__setattr__(self, "_geoms", tuple(LineString(line) for line in lines))
def __len__(self) -> int:
"""Return the number of lines in the collection."""
return len(self._geoms)
def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}({tuple(geom.coords for geom in self._geoms)})"
@property
def geoms(self) -> Iterator[LineString]:
"""Iterate over the points."""
yield from (cast(LineString, line) for line in super().geoms)
@property
def _wkt_coords(self) -> str:
return ",".join(
f"({linestring._wkt_coords})" for linestring in self.geoms # noqa: SLF001
)
@property
def __geo_interface__(self) -> GeoInterface:
"""Return the geo interface."""
geo_interface = super().__geo_interface__
geo_interface["coordinates"] = tuple(geom.coords for geom in self.geoms)
return geo_interface
@classmethod
def from_linestrings(
cls,
*args: LineString,
unique: bool = False,
) -> "MultiLineString":
"""Create a MultiLineString from LineStrings."""
return cls([line.coords for line in args], unique=unique)
@classmethod
def _from_dict(cls, geo_interface: GeoInterface) -> "MultiLineString":
cls._check_dict(geo_interface)
return cls(cast(Sequence[LineType], geo_interface["coordinates"]))
def _prepare_hull(self) -> Iterable[Point2D]:
return (
(pt.x, pt.y)
for pt in chain.from_iterable(line.geoms for line in self.geoms)
)
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9,878 | pygeoif.geometry | __init__ |
Initialize the MultiLineString.
Parameters
----------
lines : sequence
A sequence of line-like coordinate sequences.
unique: boolean,
when unique is true duplicates will be removed,
the ordering will not be preserved.
Example
-------
Construct a collection containing one line string.
>>> lines = MultiLineString( [[[0.0, 0.0], [1.0, 2.0]]] )
| def __init__(self, lines: Sequence[LineType], unique: bool = False) -> None:
"""
Initialize the MultiLineString.
Parameters
----------
lines : sequence
A sequence of line-like coordinate sequences.
unique: boolean,
when unique is true duplicates will be removed,
the ordering will not be preserved.
Example
-------
Construct a collection containing one line string.
>>> lines = MultiLineString( [[[0.0, 0.0], [1.0, 2.0]]] )
"""
if unique:
lines = {tuple(line) for line in lines} # type: ignore [assignment]
object.__setattr__(self, "_geoms", tuple(LineString(line) for line in lines))
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9,879 | pygeoif.geometry | __len__ | Return the number of lines in the collection. | def __len__(self) -> int:
"""Return the number of lines in the collection."""
return len(self._geoms)
| (self) -> int | [
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9,880 | pygeoif.geometry | __repr__ | Return the representation. | def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}({tuple(geom.coords for geom in self._geoms)})"
| (self) -> str | [
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9,884 | pygeoif.geometry | _prepare_hull | null | def _prepare_hull(self) -> Iterable[Point2D]:
return (
(pt.x, pt.y)
for pt in chain.from_iterable(line.geoms for line in self.geoms)
)
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9,885 | pygeoif.geometry | MultiPoint |
A collection of one or more points.
Attributes
----------
geoms : sequence
A sequence of Points
| class MultiPoint(_MultiGeometry):
"""
A collection of one or more points.
Attributes
----------
geoms : sequence
A sequence of Points
"""
_geoms: Tuple[Point, ...]
def __init__(self, points: Sequence[PointType], unique: bool = False) -> None:
"""
Create a collection of one or more points.
Parameters
----------
points : sequence
A sequence of (x, y [,z]) numeric coordinate pairs or triples.
unique: boolean,
when unique is true duplicates will be removed,
the ordering will not be preserved.
Example
-------
Construct a 2 point collection
>>> ob = MultiPoint([[0.0, 0.0], [1.0, 2.0]])
>>> len(ob.geoms)
2
>>> type(ob.geoms[0]) == Point
True
"""
if unique:
points = set(points) # type: ignore [assignment]
object.__setattr__(self, "_geoms", tuple(Point(*point) for point in points))
def __len__(self) -> int:
"""Return the number of points in this MultiPoint."""
return len(self._geoms)
def __repr__(self) -> str:
"""Return the representation."""
return (
f"{self.geom_type}"
f"({tuple(geom.coords[0] for geom in self._geoms if geom.coords)})"
)
@property
def geoms(self) -> Iterator[Point]:
"""Iterate over the points."""
yield from (cast(Point, p) for p in super().geoms)
@property
def _wkt_coords(self) -> str:
return ", ".join(point._wkt_coords for point in self.geoms) # noqa: SLF001
@property
def __geo_interface__(self) -> GeoInterface:
"""Return the geo interface."""
geo_interface = super().__geo_interface__
geo_interface["coordinates"] = tuple(
geom.coords[0] for geom in self.geoms if geom.coords
)
return geo_interface
@classmethod
def from_points(cls, *args: Point, unique: bool = False) -> "MultiPoint":
"""Create a MultiPoint from Points."""
return cls([point.coords[0] for point in args if point.coords], unique=unique)
@classmethod
def _from_dict(cls, geo_interface: GeoInterface) -> "MultiPoint":
cls._check_dict(geo_interface)
return cls(cast(Sequence[PointType], geo_interface["coordinates"]))
def _prepare_hull(self) -> Iterable[Point2D]:
return ((pt.x, pt.y) for pt in self.geoms)
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9,889 | pygeoif.geometry | __init__ |
Create a collection of one or more points.
Parameters
----------
points : sequence
A sequence of (x, y [,z]) numeric coordinate pairs or triples.
unique: boolean,
when unique is true duplicates will be removed,
the ordering will not be preserved.
Example
-------
Construct a 2 point collection
>>> ob = MultiPoint([[0.0, 0.0], [1.0, 2.0]])
>>> len(ob.geoms)
2
>>> type(ob.geoms[0]) == Point
True
| def __init__(self, points: Sequence[PointType], unique: bool = False) -> None:
"""
Create a collection of one or more points.
Parameters
----------
points : sequence
A sequence of (x, y [,z]) numeric coordinate pairs or triples.
unique: boolean,
when unique is true duplicates will be removed,
the ordering will not be preserved.
Example
-------
Construct a 2 point collection
>>> ob = MultiPoint([[0.0, 0.0], [1.0, 2.0]])
>>> len(ob.geoms)
2
>>> type(ob.geoms[0]) == Point
True
"""
if unique:
points = set(points) # type: ignore [assignment]
object.__setattr__(self, "_geoms", tuple(Point(*point) for point in points))
| (self, points: Sequence[Union[Tuple[float, float], Tuple[float, float, float]]], unique: bool = False) -> NoneType | [
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9,890 | pygeoif.geometry | __len__ | Return the number of points in this MultiPoint. | def __len__(self) -> int:
"""Return the number of points in this MultiPoint."""
return len(self._geoms)
| (self) -> int | [
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9,891 | pygeoif.geometry | __repr__ | Return the representation. | def __repr__(self) -> str:
"""Return the representation."""
return (
f"{self.geom_type}"
f"({tuple(geom.coords[0] for geom in self._geoms if geom.coords)})"
)
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9,895 | pygeoif.geometry | _prepare_hull | null | def _prepare_hull(self) -> Iterable[Point2D]:
return ((pt.x, pt.y) for pt in self.geoms)
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9,896 | pygeoif.geometry | MultiPolygon |
A collection of one or more polygons.
If component polygons overlap the collection is `invalid` and some
operations on it may fail.
Attributes
----------
geoms : sequence
A sequence of `Polygon` instances
| class MultiPolygon(_MultiGeometry):
"""
A collection of one or more polygons.
If component polygons overlap the collection is `invalid` and some
operations on it may fail.
Attributes
----------
geoms : sequence
A sequence of `Polygon` instances
"""
_geoms: Tuple[Polygon, ...]
def __init__(self, polygons: Sequence[PolygonType], unique: bool = False) -> None:
"""
Initialize a Multipolygon.
Parameters
----------
polygons : sequence
A sequence of (shell, holes) tuples where shell is the sequence
representation of a linear ring and holes is
a sequence of such linear rings
unique: boolean,
when unique is true duplicates will be removed,
the ordering will not be preserved.
Example
-------
Construct a collection from a sequence of coordinate tuples
>>> ob = MultiPolygon([
... (
... ((0.0, 0.0), (0.0, 1.0), (1.0, 1.0), (1.0, 0.0)),
... [((0.1, 0.1), (0.1, 0.2), (0.2, 0.2), (0.2, 0.1))]
...)
...])
>>> len(ob.geoms)
1
>>> type(ob.geoms[0]) == Polygon
True
"""
if unique:
polygons = set(polygons) # type: ignore [assignment]
object.__setattr__(
self,
"_geoms",
tuple(
Polygon(
shell=polygon[0],
holes=polygon[1] if len(polygon) == 2 else None, # noqa: PLR2004
)
for polygon in polygons
),
)
def __len__(self) -> int:
"""Return the number of polygons in the collection."""
return len(self._geoms)
def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}({tuple(geom.coords for geom in self.geoms)})"
@property
def geoms(self) -> Iterator[Polygon]:
"""Iterate over the points."""
yield from (cast(Polygon, p) for p in super().geoms)
@property
def _wkt_coords(self) -> str:
return ",".join(f"({poly._wkt_coords})" for poly in self.geoms) # noqa: SLF001
@property
def __geo_interface__(self) -> GeoInterface:
"""Return the geo interface."""
geo_interface = super().__geo_interface__
coords = tuple(
(geom.exterior.coords, *tuple(hole.coords for hole in geom.interiors))
for geom in self.geoms
)
geo_interface["coordinates"] = coords
return geo_interface
@classmethod
def from_polygons(cls, *args: Polygon, unique: bool = False) -> "MultiPolygon":
"""Create a MultiPolygon from Polygons."""
return cls([poly.coords for poly in args], unique=unique)
@classmethod
def _from_dict(cls, geo_interface: GeoInterface) -> "MultiPolygon":
cls._check_dict(geo_interface)
coords = tuple(
(poly[0], poly[1:]) # type: ignore [index]
for poly in geo_interface["coordinates"]
)
return cls(cast(Sequence[PolygonType], coords))
def _prepare_hull(self) -> Iterable[Point2D]:
return (
(pt.x, pt.y)
for pt in chain.from_iterable(poly.exterior.geoms for poly in self.geoms)
)
| (polygons: Sequence[Union[Tuple[Sequence[Tuple[float, float]], Sequence[Sequence[Tuple[float, float]]]], Tuple[Sequence[Tuple[float, float]]], Tuple[Sequence[Tuple[float, float, float]], Sequence[Sequence[Tuple[float, float, float]]]], Tuple[Sequence[Tuple[float, float, float]]]]], unique: bool = False) -> None | [
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9,900 | pygeoif.geometry | __init__ |
Initialize a Multipolygon.
Parameters
----------
polygons : sequence
A sequence of (shell, holes) tuples where shell is the sequence
representation of a linear ring and holes is
a sequence of such linear rings
unique: boolean,
when unique is true duplicates will be removed,
the ordering will not be preserved.
Example
-------
Construct a collection from a sequence of coordinate tuples
>>> ob = MultiPolygon([
... (
... ((0.0, 0.0), (0.0, 1.0), (1.0, 1.0), (1.0, 0.0)),
... [((0.1, 0.1), (0.1, 0.2), (0.2, 0.2), (0.2, 0.1))]
...)
...])
>>> len(ob.geoms)
1
>>> type(ob.geoms[0]) == Polygon
True
| def __init__(self, polygons: Sequence[PolygonType], unique: bool = False) -> None:
"""
Initialize a Multipolygon.
Parameters
----------
polygons : sequence
A sequence of (shell, holes) tuples where shell is the sequence
representation of a linear ring and holes is
a sequence of such linear rings
unique: boolean,
when unique is true duplicates will be removed,
the ordering will not be preserved.
Example
-------
Construct a collection from a sequence of coordinate tuples
>>> ob = MultiPolygon([
... (
... ((0.0, 0.0), (0.0, 1.0), (1.0, 1.0), (1.0, 0.0)),
... [((0.1, 0.1), (0.1, 0.2), (0.2, 0.2), (0.2, 0.1))]
...)
...])
>>> len(ob.geoms)
1
>>> type(ob.geoms[0]) == Polygon
True
"""
if unique:
polygons = set(polygons) # type: ignore [assignment]
object.__setattr__(
self,
"_geoms",
tuple(
Polygon(
shell=polygon[0],
holes=polygon[1] if len(polygon) == 2 else None, # noqa: PLR2004
)
for polygon in polygons
),
)
| (self, polygons: Sequence[Union[Tuple[Sequence[Tuple[float, float]], Sequence[Sequence[Tuple[float, float]]]], Tuple[Sequence[Tuple[float, float]]], Tuple[Sequence[Tuple[float, float, float]], Sequence[Sequence[Tuple[float, float, float]]]], Tuple[Sequence[Tuple[float, float, float]]]]], unique: bool = False) -> NoneType | [
0.012482324615120888,
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9,901 | pygeoif.geometry | __len__ | Return the number of polygons in the collection. | def __len__(self) -> int:
"""Return the number of polygons in the collection."""
return len(self._geoms)
| (self) -> int | [
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9,902 | pygeoif.geometry | __repr__ | Return the representation. | def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}({tuple(geom.coords for geom in self.geoms)})"
| (self) -> str | [
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9,906 | pygeoif.geometry | _prepare_hull | null | def _prepare_hull(self) -> Iterable[Point2D]:
return (
(pt.x, pt.y)
for pt in chain.from_iterable(poly.exterior.geoms for poly in self.geoms)
)
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9,907 | pygeoif.geometry | Point |
A zero dimensional geometry.
A point has zero length and zero area.
Attributes:
----------
x, y, z : float
Coordinate values
Example:
-------
>>> p = Point(1.0, -1.0)
>>> print p
POINT (1.0 -1.0)
>>> p.y
-1.0
>>> p.x
1.0
| class Point(_Geometry):
"""
A zero dimensional geometry.
A point has zero length and zero area.
Attributes:
----------
x, y, z : float
Coordinate values
Example:
-------
>>> p = Point(1.0, -1.0)
>>> print p
POINT (1.0 -1.0)
>>> p.y
-1.0
>>> p.x
1.0
"""
_geoms: PointType
def __init__(self, x: float, y: float, z: Optional[float] = None) -> None:
"""
Initialize a Point.
Parameters
----------
2 or 3 coordinate parameters: x, y, [z] : float
Easting, northing, and elevation.
"""
geoms = (x, y, z) if z is not None else (x, y)
object.__setattr__(
self,
"_geoms",
geoms,
)
def __repr__(self) -> str:
"""Return the representation."""
if self.is_empty:
return f"{self.geom_type}()"
return f"{self.geom_type}{self._geoms}"
@property
def is_empty(self) -> bool:
"""
Return if this geometry is empty.
A Point is considered empty when it has no valid coordinates.
"""
return any(coord is None or math.isnan(coord) for coord in self._geoms)
@property
def x(self) -> float:
"""Return x coordinate."""
return self._geoms[0]
@property
def y(self) -> float:
"""Return y coordinate."""
return self._geoms[1]
@property
def z(self) -> Optional[float]:
"""Return z coordinate."""
if self.has_z:
return self._geoms[2] # type: ignore [misc]
msg = f"The {self!r} geometry does not have z values"
raise DimensionError(msg)
@property
def coords(self) -> Union[Tuple[PointType], Tuple[()]]:
"""Return the geometry coordinates."""
return () if self.is_empty else (self._geoms,)
@property
def has_z(self) -> bool:
"""Return True if the geometry's coordinate sequence(s) have z values."""
return len(self._geoms) == 3 # noqa: PLR2004
@property
def _wkt_coords(self) -> str:
return " ".join(str(coordinate) for coordinate in self._geoms)
@property
def __geo_interface__(self) -> GeoInterface:
"""Return the geo interface."""
geo_interface = super().__geo_interface__
geo_interface["coordinates"] = cast(PointType, tuple(self._geoms))
return geo_interface
@classmethod
def from_coordinates(cls, coordinates: Sequence[PointType]) -> "Point":
"""Construct a point from coordinates."""
return cls(*coordinates[0])
@classmethod
def _from_dict(cls, geo_interface: GeoInterface) -> "Point":
cls._check_dict(geo_interface)
return cls(*geo_interface["coordinates"])
def _get_bounds(self) -> Bounds:
return self.x, self.y, self.x, self.y
def _prepare_hull(self) -> Iterable[Point2D]:
return ((self.x, self.y),)
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] |
9,911 | pygeoif.geometry | __init__ |
Initialize a Point.
Parameters
----------
2 or 3 coordinate parameters: x, y, [z] : float
Easting, northing, and elevation.
| def __init__(self, x: float, y: float, z: Optional[float] = None) -> None:
"""
Initialize a Point.
Parameters
----------
2 or 3 coordinate parameters: x, y, [z] : float
Easting, northing, and elevation.
"""
geoms = (x, y, z) if z is not None else (x, y)
object.__setattr__(
self,
"_geoms",
geoms,
)
| (self, x: float, y: float, z: Optional[float] = None) -> NoneType | [
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9,912 | pygeoif.geometry | __repr__ | Return the representation. | def __repr__(self) -> str:
"""Return the representation."""
if self.is_empty:
return f"{self.geom_type}()"
return f"{self.geom_type}{self._geoms}"
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9,915 | pygeoif.geometry | _get_bounds | null | def _get_bounds(self) -> Bounds:
return self.x, self.y, self.x, self.y
| (self) -> Tuple[float, float, float, float] | [
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9,916 | pygeoif.geometry | _prepare_hull | null | def _prepare_hull(self) -> Iterable[Point2D]:
return ((self.x, self.y),)
| (self) -> Iterable[Tuple[float, float]] | [
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9,917 | pygeoif.geometry | Polygon |
A two-dimensional figure bounded by a linear ring.
A polygon has a non-zero area. It may have one or more negative-space
"holes" which are also bounded by linear rings. If any rings cross each
other, the geometry is invalid and operations on it may fail.
Attributes
----------
exterior : LinearRing
The ring which bounds the positive space of the polygon.
interiors : sequence
A sequence of rings which bound all existing holes.
| class Polygon(_Geometry):
"""
A two-dimensional figure bounded by a linear ring.
A polygon has a non-zero area. It may have one or more negative-space
"holes" which are also bounded by linear rings. If any rings cross each
other, the geometry is invalid and operations on it may fail.
Attributes
----------
exterior : LinearRing
The ring which bounds the positive space of the polygon.
interiors : sequence
A sequence of rings which bound all existing holes.
"""
_geoms: Tuple[LinearRing, ...]
def __init__(
self,
shell: LineType,
holes: Optional[Sequence[LineType]] = None,
) -> None:
"""
Initialize the polygon.
Parameters
----------
shell : sequence
A sequence of (x, y [,z]) numeric coordinate pairs or triples
holes : sequence
A sequence of objects which satisfy the same requirements as the
shell parameters above
Example
-------
Create a square polygon with no holes
>>> coords = ((0., 0.), (0., 1.), (1., 1.), (1., 0.), (0., 0.))
>>> polygon = Polygon(coords)
"""
interiors = tuple(LinearRing(hole) for hole in holes) if holes else ()
exterior = LinearRing(shell)
object.__setattr__(self, "_geoms", (exterior, interiors))
def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}{self.coords}"
@property
def exterior(self) -> LinearRing:
"""Return the exterior Linear Ring of the polygon."""
return self._geoms[0]
@property
def interiors(self) -> Iterator[LinearRing]:
"""Interiors (Holes) of the polygon."""
yield from (
interior
for interior in self._geoms[1] # type: ignore [attr-defined]
if interior
)
@property
def is_empty(self) -> bool:
"""
Return if this geometry is empty.
A polygon is empty when it does not have an exterior.
"""
return self._geoms[0].is_empty
@property
def coords(self) -> PolygonType:
"""
Return Coordinates of the Polygon.
Note that this is not implemented in Shapely.
"""
if self._geoms[1]:
return cast(
PolygonType,
(
self.exterior.coords,
tuple(interior.coords for interior in self.interiors if interior),
),
)
return cast(PolygonType, (self.exterior.coords,))
@property
def has_z(self) -> Optional[bool]:
"""Return True if the geometry's coordinate sequence(s) have z values."""
return self._geoms[0].has_z
@property
def _wkt_coords(self) -> str:
ec = self.exterior._wkt_coords # noqa: SLF001
ic = "".join(
f",({interior._wkt_coords})" for interior in self.interiors # noqa: SLF001
)
return f"({ec}){ic}"
@property
def __geo_interface__(self) -> GeoInterface:
"""Return the geo interface."""
geo_interface = super().__geo_interface__
coords = (self.exterior.coords, *tuple(hole.coords for hole in self.interiors))
geo_interface["coordinates"] = coords
return geo_interface
@classmethod
def from_coordinates(cls, coordinates: PolygonType) -> "Polygon":
"""Construct a linestring from coordinates."""
return cls(*coordinates)
@classmethod
def from_linear_rings(cls, shell: LinearRing, *args: LinearRing) -> "Polygon":
"""Construct a Polygon from linear rings."""
return cls(
shell=shell.coords,
holes=tuple(lr.coords for lr in args),
)
@classmethod
def _from_dict(cls, geo_interface: GeoInterface) -> "Polygon":
cls._check_dict(geo_interface)
if not geo_interface["coordinates"]:
return cls(shell=(), holes=())
return cls(
shell=cast(LineType, geo_interface["coordinates"][0]),
holes=cast(Tuple[LineType], geo_interface["coordinates"][1:]),
)
def _get_bounds(self) -> Bounds:
return self.exterior._get_bounds() # noqa: SLF001
def _prepare_hull(self) -> Iterable[Point2D]:
return self.exterior._prepare_hull() # noqa: SLF001
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9,921 | pygeoif.geometry | __init__ |
Initialize the polygon.
Parameters
----------
shell : sequence
A sequence of (x, y [,z]) numeric coordinate pairs or triples
holes : sequence
A sequence of objects which satisfy the same requirements as the
shell parameters above
Example
-------
Create a square polygon with no holes
>>> coords = ((0., 0.), (0., 1.), (1., 1.), (1., 0.), (0., 0.))
>>> polygon = Polygon(coords)
| def __init__(
self,
shell: LineType,
holes: Optional[Sequence[LineType]] = None,
) -> None:
"""
Initialize the polygon.
Parameters
----------
shell : sequence
A sequence of (x, y [,z]) numeric coordinate pairs or triples
holes : sequence
A sequence of objects which satisfy the same requirements as the
shell parameters above
Example
-------
Create a square polygon with no holes
>>> coords = ((0., 0.), (0., 1.), (1., 1.), (1., 0.), (0., 0.))
>>> polygon = Polygon(coords)
"""
interiors = tuple(LinearRing(hole) for hole in holes) if holes else ()
exterior = LinearRing(shell)
object.__setattr__(self, "_geoms", (exterior, interiors))
| (self, shell: Union[Sequence[Tuple[float, float]], Sequence[Tuple[float, float, float]]], holes: Optional[Sequence[Union[Sequence[Tuple[float, float]], Sequence[Tuple[float, float, float]]]]] = None) -> NoneType | [
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9,922 | pygeoif.geometry | __repr__ | Return the representation. | def __repr__(self) -> str:
"""Return the representation."""
return f"{self.geom_type}{self.coords}"
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9,925 | pygeoif.geometry | _get_bounds | null | def _get_bounds(self) -> Bounds:
return self.exterior._get_bounds() # noqa: SLF001
| (self) -> Tuple[float, float, float, float] | [
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9,926 | pygeoif.geometry | _prepare_hull | null | def _prepare_hull(self) -> Iterable[Point2D]:
return self.exterior._prepare_hull() # noqa: SLF001
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9,931 | pygeoif.factories | from_wkt | Create a geometry from its WKT representation. | def from_wkt(geo_str: str) -> Optional[Union[Geometry, GeometryCollection]]:
"""Create a geometry from its WKT representation."""
type_map = {
"POINT": _point_from_wkt_coordinates,
"LINESTRING": _line_from_wkt_coordinates,
"LINEARRING": _ring_from_wkt_coordinates,
"POLYGON": _polygon_from_wkt_coordinates,
"MULTIPOINT": _multipoint_from_wkt_coordinates,
"MULTILINESTRING": _multiline_from_wkt_coordinates,
"MULTIPOLYGON": _multipolygon_from_wkt_coordinates,
"GEOMETRYCOLLECTION": _multigeometry_from_wkt_coordinates,
}
wkt = geo_str.upper().strip()
wkt = " ".join(line.strip() for line in wkt.splitlines())
try:
wkt = wkt_regex.match(wkt).group("wkt") # type: ignore [union-attr]
geometry_type = wkt_regex.match(wkt).group("type") # type: ignore [union-attr]
outerstr = outer.search(wkt)
coordinates = outerstr.group(1) # type: ignore [union-attr]
except AttributeError as exc:
msg = f"Cannot parse {wkt}"
raise WKTParserError(msg) from exc
constructor = type_map[geometry_type]
try:
return constructor(coordinates) # type: ignore [return-value]
except TypeError as exc:
msg = f"Cannot parse {wkt}"
raise WKTParserError(msg) from exc
| (geo_str: str) -> Union[pygeoif.geometry.Point, pygeoif.geometry.LineString, pygeoif.geometry.LinearRing, pygeoif.geometry.Polygon, pygeoif.geometry.MultiPoint, pygeoif.geometry.MultiLineString, pygeoif.geometry.MultiPolygon, pygeoif.geometry.GeometryCollection, NoneType] | [
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9,934 | pygeoif.factories | mapping |
Return a GeoJSON-like mapping.
Parameters
----------
ob :
An object which implements __geo_interface__.
Returns
-------
dict
Example
-------
>>> pt = Point(0, 0)
>>> mapping(pt)
{'type': 'Point', 'bbox': (0, 0, 0, 0), 'coordinates': (0, 0)}
| def mapping(
ob: Union[GeoType, GeoCollectionType],
) -> Union[GeoCollectionInterface, GeoInterface]:
"""
Return a GeoJSON-like mapping.
Parameters
----------
ob :
An object which implements __geo_interface__.
Returns
-------
dict
Example
-------
>>> pt = Point(0, 0)
>>> mapping(pt)
{'type': 'Point', 'bbox': (0, 0, 0, 0), 'coordinates': (0, 0)}
"""
return ob.__geo_interface__
| (ob: Union[pygeoif.types.GeoType, pygeoif.types.GeoCollectionType]) -> Union[pygeoif.types.GeoCollectionInterface, pygeoif.types.GeoInterface] | [
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] |
9,935 | pygeoif.factories | orient |
Return a polygon with exteriors and interiors in the right orientation.
if ccw is True than the exterior will be in counterclockwise orientation
and the interiors will be in clockwise orientation, or
the other way round when ccw is False.
| def orient(polygon: Polygon, ccw: bool = True) -> Polygon: # noqa: FBT001, FBT002
"""
Return a polygon with exteriors and interiors in the right orientation.
if ccw is True than the exterior will be in counterclockwise orientation
and the interiors will be in clockwise orientation, or
the other way round when ccw is False.
"""
shell = get_oriented_ring(polygon.exterior.coords, ccw)
ccw = not ccw # flip orientation for holes
holes = [get_oriented_ring(ring.coords, ccw) for ring in polygon.interiors]
return Polygon(shell=shell, holes=holes)
| (polygon: pygeoif.geometry.Polygon, ccw: bool = True) -> pygeoif.geometry.Polygon | [
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] |
9,936 | pygeoif.factories | shape |
Return a new geometry with coordinates *copied* from the context.
Changes to the original context will not be reflected in the
geometry object.
Parameters
----------
context :
a GeoJSON-like dict, which provides a "type" member describing the type
of the geometry and "coordinates" member providing a list of coordinates,
or an object which implements __geo_interface__.
Returns
-------
Geometry object
Example
-------
Create a Point from GeoJSON, and then create a copy using __geo_interface__.
>>> context = {'type': 'Point', 'coordinates': [0, 1]}
>>> geom = shape(context)
>>> geom.geom_type == 'Point'
True
>>> geom.wkt
'POINT (0 1)'
>>> geom2 = shape(geom)
>>> geom == geom2
True
| def shape(
context: Union[
GeoType,
GeoCollectionType,
GeoInterface,
GeoCollectionInterface,
],
) -> Union[Geometry, GeometryCollection]:
"""
Return a new geometry with coordinates *copied* from the context.
Changes to the original context will not be reflected in the
geometry object.
Parameters
----------
context :
a GeoJSON-like dict, which provides a "type" member describing the type
of the geometry and "coordinates" member providing a list of coordinates,
or an object which implements __geo_interface__.
Returns
-------
Geometry object
Example
-------
Create a Point from GeoJSON, and then create a copy using __geo_interface__.
>>> context = {'type': 'Point', 'coordinates': [0, 1]}
>>> geom = shape(context)
>>> geom.geom_type == 'Point'
True
>>> geom.wkt
'POINT (0 1)'
>>> geom2 = shape(geom)
>>> geom == geom2
True
"""
type_map = {
"Point": Point,
"LineString": LineString,
"LinearRing": LinearRing,
"Polygon": Polygon,
"MultiPoint": MultiPoint,
"MultiLineString": MultiLineString,
"MultiPolygon": MultiPolygon,
}
geometry = context if isinstance(context, dict) else mapping(context)
if not geometry:
msg = ( # type: ignore [unreachable]
"Object does not implement __geo_interface__"
)
raise TypeError(msg)
if constructor := type_map.get(geometry["type"]):
return constructor._from_dict( # type: ignore [attr-defined, no-any-return]
geometry,
)
if geometry["type"] == "GeometryCollection":
geometries = [shape(fi) for fi in geometry["geometries"]]
return GeometryCollection(geometries)
msg = f"[{geometry['type']} is not implemented"
raise NotImplementedError(msg)
| (context: Union[pygeoif.types.GeoType, pygeoif.types.GeoCollectionType, pygeoif.types.GeoInterface, pygeoif.types.GeoCollectionInterface]) -> Union[pygeoif.geometry.Point, pygeoif.geometry.LineString, pygeoif.geometry.LinearRing, pygeoif.geometry.Polygon, pygeoif.geometry.MultiPoint, pygeoif.geometry.MultiLineString, pygeoif.geometry.MultiPolygon, pygeoif.geometry.GeometryCollection] | [
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] |
9,939 | rouver.util | absolute_url |
Construct an absolute URL, using the request URL as base.
Non-printable and non-ASCII characters in the path are encoded,
but other characters, most notably slashes and percent signs are
not encoded. Make sure to call urllib.parse.quote() on paths that
can potentially contain such characters before passing them to
absolute_url().
| def absolute_url(request: Request, path: str) -> str:
"""
Construct an absolute URL, using the request URL as base.
Non-printable and non-ASCII characters in the path are encoded,
but other characters, most notably slashes and percent signs are
not encoded. Make sure to call urllib.parse.quote() on paths that
can potentially contain such characters before passing them to
absolute_url().
"""
base_url: str = request.base_url
return urljoin(base_url, quote(path, safe="/:?&$@,;+=%~"))
| (request: werkzeug.wrappers.request.Request, path: str) -> str | [
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] |
9,941 | sentence_transformers.cross_encoder.CrossEncoder | CrossEncoder |
A CrossEncoder takes exactly two sentences / texts as input and either predicts
a score or label for this sentence pair. It can for example predict the similarity of the sentence pair
on a scale of 0 ... 1.
It does not yield a sentence embedding and does not work for individual sentences.
:param model_name: A model name from Hugging Face Hub that can be loaded with AutoModel, or a path to a local
model. We provide several pre-trained CrossEncoder models that can be used for common tasks.
:param num_labels: Number of labels of the classifier. If 1, the CrossEncoder is a regression model that
outputs a continuous score 0...1. If > 1, it output several scores that can be soft-maxed to get
probability scores for the different classes.
:param max_length: Max length for input sequences. Longer sequences will be truncated. If None, max
length of the model will be used
:param device: Device that should be used for the model. If None, it will use CUDA if available.
:param tokenizer_args: Arguments passed to AutoTokenizer
:param automodel_args: Arguments passed to AutoModelForSequenceClassification
:param trust_remote_code: Whether or not to allow for custom models defined on the Hub in their own modeling files.
This option should only be set to True for repositories you trust and in which you have read the code, as it
will execute code present on the Hub on your local machine.
:param revision: The specific model version to use. It can be a branch name, a tag name, or a commit id,
for a stored model on Hugging Face.
:param default_activation_function: Callable (like nn.Sigmoid) about the default activation function that
should be used on-top of model.predict(). If None. nn.Sigmoid() will be used if num_labels=1,
else nn.Identity()
:param classifier_dropout: The dropout ratio for the classification head.
| class CrossEncoder(PushToHubMixin):
"""
A CrossEncoder takes exactly two sentences / texts as input and either predicts
a score or label for this sentence pair. It can for example predict the similarity of the sentence pair
on a scale of 0 ... 1.
It does not yield a sentence embedding and does not work for individual sentences.
:param model_name: A model name from Hugging Face Hub that can be loaded with AutoModel, or a path to a local
model. We provide several pre-trained CrossEncoder models that can be used for common tasks.
:param num_labels: Number of labels of the classifier. If 1, the CrossEncoder is a regression model that
outputs a continuous score 0...1. If > 1, it output several scores that can be soft-maxed to get
probability scores for the different classes.
:param max_length: Max length for input sequences. Longer sequences will be truncated. If None, max
length of the model will be used
:param device: Device that should be used for the model. If None, it will use CUDA if available.
:param tokenizer_args: Arguments passed to AutoTokenizer
:param automodel_args: Arguments passed to AutoModelForSequenceClassification
:param trust_remote_code: Whether or not to allow for custom models defined on the Hub in their own modeling files.
This option should only be set to True for repositories you trust and in which you have read the code, as it
will execute code present on the Hub on your local machine.
:param revision: The specific model version to use. It can be a branch name, a tag name, or a commit id,
for a stored model on Hugging Face.
:param default_activation_function: Callable (like nn.Sigmoid) about the default activation function that
should be used on-top of model.predict(). If None. nn.Sigmoid() will be used if num_labels=1,
else nn.Identity()
:param classifier_dropout: The dropout ratio for the classification head.
"""
def __init__(
self,
model_name: str,
num_labels: int = None,
max_length: int = None,
device: str = None,
tokenizer_args: Dict = {},
automodel_args: Dict = {},
trust_remote_code: bool = False,
revision: Optional[str] = None,
default_activation_function=None,
classifier_dropout: float = None,
):
self.config = AutoConfig.from_pretrained(model_name, trust_remote_code=trust_remote_code, revision=revision)
classifier_trained = True
if self.config.architectures is not None:
classifier_trained = any(
[arch.endswith("ForSequenceClassification") for arch in self.config.architectures]
)
if classifier_dropout is not None:
self.config.classifier_dropout = classifier_dropout
if num_labels is None and not classifier_trained:
num_labels = 1
if num_labels is not None:
self.config.num_labels = num_labels
self.model = AutoModelForSequenceClassification.from_pretrained(
model_name, config=self.config, revision=revision, trust_remote_code=trust_remote_code, **automodel_args
)
self.tokenizer = AutoTokenizer.from_pretrained(model_name, revision=revision, **tokenizer_args)
self.max_length = max_length
if device is None:
device = get_device_name()
logger.info("Use pytorch device: {}".format(device))
self._target_device = torch.device(device)
if default_activation_function is not None:
self.default_activation_function = default_activation_function
try:
self.config.sbert_ce_default_activation_function = util.fullname(self.default_activation_function)
except Exception as e:
logger.warning(
"Was not able to update config about the default_activation_function: {}".format(str(e))
)
elif (
hasattr(self.config, "sbert_ce_default_activation_function")
and self.config.sbert_ce_default_activation_function is not None
):
self.default_activation_function = util.import_from_string(
self.config.sbert_ce_default_activation_function
)()
else:
self.default_activation_function = nn.Sigmoid() if self.config.num_labels == 1 else nn.Identity()
def smart_batching_collate(self, batch):
texts = [[] for _ in range(len(batch[0].texts))]
labels = []
for example in batch:
for idx, text in enumerate(example.texts):
texts[idx].append(text.strip())
labels.append(example.label)
tokenized = self.tokenizer(
*texts, padding=True, truncation="longest_first", return_tensors="pt", max_length=self.max_length
)
labels = torch.tensor(labels, dtype=torch.float if self.config.num_labels == 1 else torch.long).to(
self._target_device
)
for name in tokenized:
tokenized[name] = tokenized[name].to(self._target_device)
return tokenized, labels
def smart_batching_collate_text_only(self, batch):
texts = [[] for _ in range(len(batch[0]))]
for example in batch:
for idx, text in enumerate(example):
texts[idx].append(text.strip())
tokenized = self.tokenizer(
*texts, padding=True, truncation="longest_first", return_tensors="pt", max_length=self.max_length
)
for name in tokenized:
tokenized[name] = tokenized[name].to(self._target_device)
return tokenized
def fit(
self,
train_dataloader: DataLoader,
evaluator: SentenceEvaluator = None,
epochs: int = 1,
loss_fct=None,
activation_fct=nn.Identity(),
scheduler: str = "WarmupLinear",
warmup_steps: int = 10000,
optimizer_class: Type[Optimizer] = torch.optim.AdamW,
optimizer_params: Dict[str, object] = {"lr": 2e-5},
weight_decay: float = 0.01,
evaluation_steps: int = 0,
output_path: str = None,
save_best_model: bool = True,
max_grad_norm: float = 1,
use_amp: bool = False,
callback: Callable[[float, int, int], None] = None,
show_progress_bar: bool = True,
):
"""
Train the model with the given training objective
Each training objective is sampled in turn for one batch.
We sample only as many batches from each objective as there are in the smallest one
to make sure of equal training with each dataset.
:param train_dataloader: DataLoader with training InputExamples
:param evaluator: An evaluator (sentence_transformers.evaluation) evaluates the model performance during training on held-out dev data. It is used to determine the best model that is saved to disc.
:param epochs: Number of epochs for training
:param loss_fct: Which loss function to use for training. If None, will use nn.BCEWithLogitsLoss() if self.config.num_labels == 1 else nn.CrossEntropyLoss()
:param activation_fct: Activation function applied on top of logits output of model.
:param scheduler: Learning rate scheduler. Available schedulers: constantlr, warmupconstant, warmuplinear, warmupcosine, warmupcosinewithhardrestarts
:param warmup_steps: Behavior depends on the scheduler. For WarmupLinear (default), the learning rate is increased from o up to the maximal learning rate. After these many training steps, the learning rate is decreased linearly back to zero.
:param optimizer_class: Optimizer
:param optimizer_params: Optimizer parameters
:param weight_decay: Weight decay for model parameters
:param evaluation_steps: If > 0, evaluate the model using evaluator after each number of training steps
:param output_path: Storage path for the model and evaluation files
:param save_best_model: If true, the best model (according to evaluator) is stored at output_path
:param max_grad | (model_name: str, num_labels: int = None, max_length: int = None, device: str = None, tokenizer_args: Dict = {}, automodel_args: Dict = {}, trust_remote_code: bool = False, revision: Optional[str] = None, default_activation_function=None, classifier_dropout: float = None) | [
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9,942 | sentence_transformers.cross_encoder.CrossEncoder | __init__ | null | def __init__(
self,
model_name: str,
num_labels: int = None,
max_length: int = None,
device: str = None,
tokenizer_args: Dict = {},
automodel_args: Dict = {},
trust_remote_code: bool = False,
revision: Optional[str] = None,
default_activation_function=None,
classifier_dropout: float = None,
):
self.config = AutoConfig.from_pretrained(model_name, trust_remote_code=trust_remote_code, revision=revision)
classifier_trained = True
if self.config.architectures is not None:
classifier_trained = any(
[arch.endswith("ForSequenceClassification") for arch in self.config.architectures]
)
if classifier_dropout is not None:
self.config.classifier_dropout = classifier_dropout
if num_labels is None and not classifier_trained:
num_labels = 1
if num_labels is not None:
self.config.num_labels = num_labels
self.model = AutoModelForSequenceClassification.from_pretrained(
model_name, config=self.config, revision=revision, trust_remote_code=trust_remote_code, **automodel_args
)
self.tokenizer = AutoTokenizer.from_pretrained(model_name, revision=revision, **tokenizer_args)
self.max_length = max_length
if device is None:
device = get_device_name()
logger.info("Use pytorch device: {}".format(device))
self._target_device = torch.device(device)
if default_activation_function is not None:
self.default_activation_function = default_activation_function
try:
self.config.sbert_ce_default_activation_function = util.fullname(self.default_activation_function)
except Exception as e:
logger.warning(
"Was not able to update config about the default_activation_function: {}".format(str(e))
)
elif (
hasattr(self.config, "sbert_ce_default_activation_function")
and self.config.sbert_ce_default_activation_function is not None
):
self.default_activation_function = util.import_from_string(
self.config.sbert_ce_default_activation_function
)()
else:
self.default_activation_function = nn.Sigmoid() if self.config.num_labels == 1 else nn.Identity()
| (self, model_name: str, num_labels: Optional[int] = None, max_length: Optional[int] = None, device: Optional[str] = None, tokenizer_args: Dict = {}, automodel_args: Dict = {}, trust_remote_code: bool = False, revision: Optional[str] = None, default_activation_function=None, classifier_dropout: Optional[float] = None) | [
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] |
9,943 | transformers.utils.hub | _create_repo |
Create the repo if needed, cleans up repo_id with deprecated kwargs `repo_url` and `organization`, retrieves
the token.
| def _create_repo(
self,
repo_id: str,
private: Optional[bool] = None,
token: Optional[Union[bool, str]] = None,
repo_url: Optional[str] = None,
organization: Optional[str] = None,
) -> str:
"""
Create the repo if needed, cleans up repo_id with deprecated kwargs `repo_url` and `organization`, retrieves
the token.
"""
if repo_url is not None:
warnings.warn(
"The `repo_url` argument is deprecated and will be removed in v5 of Transformers. Use `repo_id` "
"instead."
)
if repo_id is not None:
raise ValueError(
"`repo_id` and `repo_url` are both specified. Please set only the argument `repo_id`."
)
repo_id = repo_url.replace(f"{HUGGINGFACE_CO_RESOLVE_ENDPOINT}/", "")
if organization is not None:
warnings.warn(
"The `organization` argument is deprecated and will be removed in v5 of Transformers. Set your "
"organization directly in the `repo_id` passed instead (`repo_id={organization}/{model_id}`)."
)
if not repo_id.startswith(organization):
if "/" in repo_id:
repo_id = repo_id.split("/")[-1]
repo_id = f"{organization}/{repo_id}"
url = create_repo(repo_id=repo_id, token=token, private=private, exist_ok=True)
return url.repo_id
| (self, repo_id: str, private: Optional[bool] = None, token: Union[bool, str, NoneType] = None, repo_url: Optional[str] = None, organization: Optional[str] = None) -> str | [
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9,944 | sentence_transformers.cross_encoder.CrossEncoder | _eval_during_training | Runs evaluation during the training | def _eval_during_training(self, evaluator, output_path, save_best_model, epoch, steps, callback):
"""Runs evaluation during the training"""
if evaluator is not None:
score = evaluator(self, output_path=output_path, epoch=epoch, steps=steps)
if callback is not None:
callback(score, epoch, steps)
if score > self.best_score:
self.best_score = score
if save_best_model:
self.save(output_path)
| (self, evaluator, output_path, save_best_model, epoch, steps, callback) | [
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