How to use shape_graph method in localstack

Best Python code snippet using localstack_python

validator.py

Source:validator.py

1#!/usr/bin/env python2# -*- coding: utf-8 -*-3# author: houzhiwei4# time: 2020/1/5 17:565# https://github.com/RDFLib/pySHACL6from rdflib import Graph7from rdflib.util import guess_format8from pyshacl import validate, Validator9from datagraph import DataGraph10from utils import Utils11class GeoValidator(object):12	@staticmethod13	def read_graphs(*ont_graphs):14		"""15		read and merge a set of ont graphs16		:param ont_graphs:17		:return: A merge of a set of RDF graphs18		"""19		g = Graph()20		for ont in ont_graphs:21			f = guess_format(ont)22			g.parse(ont, format=f)23		return g24	@staticmethod25	def data_2_graph(parameter_id:str, data, data_theme=None, data_type=None):26		"""27		read input data and generate RDF graph28		:param parameter_id: parameter identifier, indicates which parameter this data is prepared for29		:param data: input data path or value30		:param data_theme: data theme. e.g., DEM, soil, landuse, city, etc.31		:param data_type: automatically detect if is None. 0 for raster data; 1 for vector data; 2 for general (non-geospatial) data32		:return: data graph33		"""34		_dg = DataGraph()35		if data_type is None:36			data_type = Utils.detect_data_type(data)37		# raster data38		if data_type == 0:39			graph = _dg.raster_graph(parameter_id, data, data_theme)40		# vector data41		elif data_type == 1:42			graph = _dg.vector_graph(parameter_id, data, data_theme)43		# non-geospatial data44		else:45			graph = _dg.general_graph(parameter_id, data, data_theme)46		return graph47	@staticmethod48	def validate_data(data_graph, shape_graph, ont=None):49		"""50		validate_data input data against a predefined shape graph51		:param data_graph:52		:param shape_graph:53		:param ont:54		:return:55		"""56		results = validate(data_graph, shacl_graph=shape_graph,57		                   ont_graph=ont, inference='rdfs', debug=False)58		# conforms, results_graph, results_text = results59		return results60	@staticmethod61	def advanced_validate(data_graph, shape_graph, ont=None):62		# enable SHACL advanced features: rules, custom targets63		results = validate(data_graph, shacl_graph=shape_graph, ont_graph=ont,64		                   advanced=True, inference='rdfs', debug=False)65		# conforms, results_graph, results_text = results66		# the results_graph just contains the validation report, not inferred triples67		return results68	@staticmethod69	def infer_with_extended_graph(data_graph, shacl_rule, ont=None):70		"""71		use validate directly cannot get the inferred triples72		:param data_graph:73		:param shacl_rule:74		:param ont:75		:return:76		"""77		v = Validator(data_graph=data_graph, shacl_graph=shacl_rule,78		              options={"inference": "rdfs", "advanced": True}, ont_graph=ont)79		conforms, report_graph, report_text = v.run()80		# mixed in the extra-ontology graph81		expanded_graph = v.target_graph...

path.py

Source:path.py

1from .bspline import Curve2Closed_BSpline2from .smoothen import smooth_spline3# Returns the slope of the line connecting two points4def slope(p0, p1):5    dx = p1[0] - p0[0]6    dy = p1[1] - p0[1]7    if dx == 0:8        return (9            dy * 9999999999999910        )  # Since dx is zero, we avoid division by zero. Instead, we multiply dy by a large number11    return 1.0 * dy / dx12class Path(object):13    # The path class encodes all the splines that are fit to a shape14    def __init__(self, shape_graph):15        self.path = self.make_path(shape_graph)16        self.shapes = set()17    def key(self):18        # This is the key used in the dict stored in the pixel graph19        return tuple(self.path)20    def make_path(self, shape_graph):21        # Creates the path and returns it22        nodes = set(shape_graph.nodes())23        path = [min(nodes)]24        neighbors = sorted(25            shape_graph.neighbors(path[0]), key=lambda p: slope(path[0], p)26        )27        path.append(neighbors[0])28        nodes.difference_update(29            path30        )  # This is equivalent to set difference between nodes and path31        # Go through the rest of the nodes and add nodes appropriately to the path32        p = path[-1]33        i = 034        while nodes:35            for neighbor in shape_graph.neighbors(path[-1]):36                if neighbor in nodes:37                    nodes.remove(neighbor)38                    path.append(neighbor)39                    break40            if p != path[-1]:41                p = path[-1]42                i = 043            else:44                i += 145                if i == 3:46                    break47        return path48    def make_spline(self):49        # Fit a spline to the path50        self.spline = Curve2Closed_BSpline(self.path)51    def smooth_spline(self):52        # Optimise the spline that is already fit to the path...

shapeImport.py

Source:shapeImport.py

1import math2import networkx as nx3from ac_metro.importing.abstractImport import AbstractImport4class ShapeImport(AbstractImport):5    '''6    Load a shape graph from an Graphml file.7    '''8    @staticmethod9    def load(options: dict):10        print(f"Loading Shape with cost {options['shape_cost']}")11        if options['filepath'] is None:12            raise FileNotFoundError13        g_in = nx.read_graphml(options['filepath'])14        if 'x_attr' in options:15            x_attr = options['x_attr']16        else:17            x_attr = 'x'18        if 'y_attr' in options:19            y_attr = options['y_attr']20        else:21            y_attr = 'y'22        if 'id_start' in options:23            id_counter = options['id_start']24        else:25            id_counter = 026        shape_graph = nx.Graph()27        id_map = {}28        for v, data in g_in.nodes(data=True):29            x = float(data[x_attr])30            y = float(data[y_attr])31            id_map[v] = id_counter32            shape_graph.add_node(id_counter, x=x, y=y)33            id_counter += 134        for u, v, data in g_in.edges(data=True):35            shape_graph.add_edge(id_map[u], id_map[v], crossing=[],36                                 weight=options["shape_cost"] if "shape_cost" in options else 1)...

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