def build_graphs(self) -> None: """Builds graphs for all modes currently available in the model When called, it overwrites all graphs previously created and stored in the networks' dictionary of graphs """ curr = self.conn.cursor() curr.execute('PRAGMA table_info(links);') field_names = curr.fetchall() ignore_fields = ['ogc_fid', 'geometry'] all_fields = [f[1] for f in field_names if f[1] not in ignore_fields] raw_links = curr.execute( f"select {','.join(all_fields)} from links").fetchall() links = [] for l in raw_links: lk = list(map(lambda x: np.nan if x is None else x, l)) links.append(lk) data = np.core.records.fromrecords(links, names=all_fields) valid_fields = [] removed_fields = [] for f in all_fields: if np.issubdtype(data[f].dtype, np.floating) or np.issubdtype( data[f].dtype, np.integer): valid_fields.append(f) else: removed_fields.append(f) if len(removed_fields) > 1: warn( f'Fields were removed form Graph for being non-numeric: {",".join(removed_fields)}' ) curr.execute('select node_id from nodes where is_centroid=1;') centroids = np.array([i[0] for i in curr.fetchall()], np.uint32) modes = curr.execute('select mode_id from modes;').fetchall() modes = [m[0] for m in modes] for m in modes: w = np.core.defchararray.find(data['modes'], m) net = np.array(data[valid_fields], copy=True) net['b_node'][w < 0] = net['a_node'][w < 0] g = Graph() g.mode = m g.network = net g.network_ok = True g.status = 'OK' g.prepare_graph(centroids) g.set_blocked_centroid_flows(True) self.graphs[m] = g
def assign_matrix(self, matrix: AequilibraeMatrix, result_name: str): conn = database_connection() sql = f"select link_id, direction, a_node, b_node, distance, 1 capacity from {DELAUNAY_TABLE}" df = pd.read_sql(sql, conn) centroids = np.array(np.unique(np.hstack((df.a_node.values, df.b_node.values))), int) g = Graph() g.mode = 'delaunay' g.network = df g.prepare_graph(centroids) g.set_blocked_centroid_flows(True) tc = TrafficClass('delaunay', g, matrix) ta = TrafficAssignment() ta.set_classes([tc]) ta.set_time_field('distance') ta.set_capacity_field('capacity') ta.set_vdf('BPR') ta.set_vdf_parameters({"alpha": 0, "beta": 1.0}) ta.set_algorithm('all-or-nothing') ta.execute() report = {"setup": str(ta.info())} data = [result_name, "Delaunay assignment", self.procedure_id, str(report), ta.procedure_date, ''] conn.execute("""Insert into results(table_name, procedure, procedure_id, procedure_report, timestamp, description) Values(?,?,?,?,?,?)""", data) conn.commit() conn.close() cols = [] for x in matrix.view_names: cols.extend([f'{x}_ab', f'{x}_ba', f'{x}_tot']) df = ta.results()[cols] conn = sqlite3.connect(join(environ[ENVIRON_VAR], "results_database.sqlite")) df.to_sql(result_name, conn) conn.close()
class TestGraph(TestCase): def test_create_from_geography(self): self.graph = Graph() self.graph.create_from_geography( test_network, 'link_id', 'dir', 'distance', centroids=centroids, skim_fields = [], anode="A_NODE", bnode="B_NODE") self.graph.set_graph(cost_field='distance', block_centroid_flows=True) def test_load_network_from_csv(self): pass def test_prepare_graph(self): self.test_create_from_geography() self.graph.prepare_graph(centroids) reference_graph = Graph() reference_graph.load_from_disk(test_graph) if not np.array_equal(self.graph.graph, reference_graph.graph): self.fail('Reference graph and newly-prepared graph are not equal') def test_set_graph(self): self.test_prepare_graph() self.graph.set_graph(cost_field='distance',block_centroid_flows=True) if self.graph.num_zones != centroids.shape[0]: self.fail('Number of centroids not properly set') if self.graph.num_links != 222: self.fail('Number of links not properly set') if self.graph.num_nodes != 93: self.fail('Number of nodes not properly set - ' + str(self.graph.num_nodes)) def test_save_to_disk(self): self.test_create_from_geography() self.graph.save_to_disk(join(path_test, 'aequilibrae_test_graph.aeg')) self.graph_id = self.graph.__id__ self.graph_version = self.graph.__version__ def test_load_from_disk(self): self.test_save_to_disk() reference_graph = Graph() reference_graph.load_from_disk(test_graph) new_graph = Graph() new_graph.load_from_disk(join(path_test, 'aequilibrae_test_graph.aeg')) comparisons = [('Graph', new_graph.graph, reference_graph.graph), ('b_nodes', new_graph.b_node, reference_graph.b_node), ('Forward-Star', new_graph.fs, reference_graph.fs), ('cost', new_graph.cost, reference_graph.cost), ('centroids', new_graph.centroids, reference_graph.centroids), ('skims', new_graph.skims, reference_graph.skims), ('link ids', new_graph.ids, reference_graph.ids), ('Network', new_graph.network, reference_graph.network), ('All Nodes', new_graph.all_nodes, reference_graph.all_nodes), ('Nodes to indices', new_graph.nodes_to_indices, reference_graph.nodes_to_indices)] for comparison, newg, refg in comparisons: if not np.array_equal(newg, refg): self.fail('Reference %s and %s created and saved to disk are not equal' %(comparison, comparison)) comparisons = [('nodes', new_graph.num_nodes, reference_graph.num_nodes), ('links', new_graph.num_links, reference_graph.num_links), ('zones', new_graph.num_zones, reference_graph.num_zones), ('block through centroids', new_graph.block_centroid_flows, reference_graph.block_centroid_flows), ('Graph ID', new_graph.__id__, self.graph_id), ('Graph Version', new_graph.__version__, self.graph_version)] for comparison, newg, refg in comparisons: if newg != refg: self.fail('Reference %s and %s created and saved to disk are not equal' %(comparison, comparison)) def test_reset_single_fields(self): pass def test_add_single_field(self): pass def test_available_skims(self): self.test_set_graph() if self.graph.available_skims() != ['distance']: self.fail('Skim availability with problems')
class GraphCreation(WorkerThread): def __init__(self, parentThread, net_layer, link_id, direction_field, fields_to_add, selected_only): WorkerThread.__init__(self, parentThread) self.net_layer = net_layer self.link_id = link_id self.direction_field = direction_field self.fields_to_add = fields_to_add self.selected_only = selected_only self.features = None self.error = None self.report = [] self.feat_count = 0 self.bi_directional = False if direction_field is not None: self.bi_directional = True def doWork(self): if self.selected_only: self.features = self.net_layer.selectedFeatures() self.feat_count = self.net_layer.selectedFeatureCount() else: self.features = self.net_layer.getFeatures() self.feat_count = self.net_layer.featureCount() # Checking ID uniqueness self.report.append(reporter("Checking ID uniqueness", 0)) self.emit(SIGNAL("ProgressText ( PyQt_PyObject )"),"Checking ID uniqueness. Please wait") all_ids = self.net_layer.uniqueValues(self.link_id) if NULL in all_ids: self.error = "ID field has NULL values" self.report.append(self.error) else: if len(all_ids) < self.feat_count: self.error = 'IDs are not unique.' self.report.append(self.error) if self.error is None: self.report.append(reporter('Loading data from layer', 0)) self.emit(SIGNAL("ProgressText ( PyQt_PyObject )"),"Loading data from layer") self.emit(SIGNAL("ProgressValue( PyQt_PyObject )"), 0) self.emit(SIGNAL("ProgressMaxValue( PyQt_PyObject )"), self.feat_count) self.graph = Graph() all_types = [np.int32, np.int32, np.int32, np.int8] all_titles = [reserved_fieds.link_id, reserved_fieds.a_node, reserved_fieds.b_node, reserved_fieds.direction] for name_field, values in self.fields_to_add.iteritems(): all_titles.append((name_field + '_ab').encode('ascii','ignore')) all_types.append(np.float64) all_titles.append((name_field + '_ba').encode('ascii','ignore')) all_types.append(np.float64) dt = [(t, d) for t, d in zip(all_titles, all_types)] a_node = self.net_layer.fieldNameIndex(reserved_fieds.a_node) b_node = self.net_layer.fieldNameIndex(reserved_fieds.b_node) data = [] for p, feat in enumerate(self.features): line = [] line.append(feat.attributes()[self.link_id]) line.append(feat.attributes()[a_node]) line.append(feat.attributes()[b_node]) if self.bi_directional: line.append(feat.attributes()[self.direction_field]) else: line.append(1) # We append the data fields now for k, v in self.fields_to_add.iteritems(): a, b = v line.append(feat.attributes()[a]) if self.bi_directional: line.append(feat.attributes()[b]) else: line.append(-1) for k in line: if k == NULL: t = ','.join([str(x) for x in line]) self.error = 'Field with NULL value - ID:' + str(line[0]) + " / " + t break if self.error is not None: break data.append(line) if p % 50 == 0: self.emit(SIGNAL("ProgressValue( PyQt_PyObject )"), p) if self.error is None: self.report.append(reporter('Converting data to graph', 0)) network = np.asarray(data) self.graph.network = np.zeros(network.shape[0], dtype=dt) for k, t in enumerate(dt): self.graph.network[t[0]] = network[:,k].astype(t[1]) del network self.graph.type_loaded = 'NETWORK' self.graph.status = 'OK' self.graph.network_ok = True self.graph.prepare_graph() self.graph.__source__ = None self.graph.__field_name__ = None self.graph.__layer_name__ = None self.report.append(reporter('Process finished', 0)) self.emit(SIGNAL("finished_threaded_procedure( PyQt_PyObject )"), None)
class GraphCreation(WorkerThread): def __init__(self, parentThread, netlayer, linkid, ablength, bidirectional, directionfield, balength, skims, selected_only, featcount): WorkerThread.__init__(self, parentThread) self.netlayer = netlayer self.linkid = linkid self.ablength = ablength self.balength = balength self.bidirectional = bidirectional self.directionfield = directionfield self.skims = skims self.selected_only = selected_only self.features = None self.featcount = featcount self.error = None def doWork(self): # Checking ID uniqueness self.emit(SIGNAL("ProgressText ( PyQt_PyObject )"), "Checking ID uniqueness") self.emit(SIGNAL("ProgressMaxValue( PyQt_PyObject )"), self.featcount) a = [] all_ids = np.zeros(self.featcount, dtype=np.int_) if self.selected_only: self.features = self.netlayer.selectedFeatures() else: self.features = self.netlayer.getFeatures() p = 0 for feat in self.features: k = feat.attributes()[self.linkid] if k == NULL: self.error = "ID field has NULL values" break else: all_ids[p] = k p += 1 if p % 50 == 0: self.emit(SIGNAL("ProgressValue( PyQt_PyObject )"), p) self.emit(SIGNAL("ProgressValue( PyQt_PyObject )"), self.featcount) if self.error is None: # Checking uniqueness y = np.bincount(all_ids) if np.max(y) > 1: self.error = 'IDs are not unique.' if self.error is None: self.emit(SIGNAL("ProgressText ( PyQt_PyObject )"), "Loading data from layer") self.emit(SIGNAL("ProgressValue( PyQt_PyObject )"), 0) self.graph = Graph() all_types = [ np.int64, np.int64, np.int64, np.float64, np.float64, np.int64 ] all_titles = [ 'link_id', 'a_node', 'b_node', 'length_ab', 'length_ba', 'direction' ] dict_field = {} for k in self.skims: a, b, t = self.skims[k] all_types.append(np.float64) all_types.append(np.float64) all_titles.append((k + '_ab').encode('ascii', 'ignore')) all_titles.append((k + '_ba').encode('ascii', 'ignore')) dict_field[k + '_ab'] = a if self.bidirectional: dict_field[k + '_ba'] = b else: dict_field[k + '_ba'] = -1 dt = [(t, d) for t, d in zip(all_titles, all_types)] anode = self.netlayer.fieldNameIndex('A_Node') bnode = self.netlayer.fieldNameIndex('B_Node') data = [] if self.selected_only: self.features = self.netlayer.selectedFeatures() else: self.features = self.netlayer.getFeatures() p = 0 for feat in self.features: line = [] line.append(feat.attributes()[self.linkid]) line.append(feat.attributes()[anode]) line.append(feat.attributes()[bnode]) line.append(feat.attributes()[self.ablength]) if self.bidirectional: line.append(feat.attributes()[self.balength]) line.append(feat.attributes()[self.directionfield]) else: line.append(-1) line.append(1) # We append the skims now for k in all_titles: if k in dict_field: if dict_field[k] >= 0: line.append(feat.attributes()[dict_field[k]]) else: line.append(-1) for k in line: if k == NULL: t = '' for j in line: t = t + ',' + str(j) self.error = 'Field with NULL value - ID:' + str( line[0]) + " / " + t break if self.error is not None: break data.append(line) p += 1 if p % 50 == 0: self.emit(SIGNAL("ProgressValue( PyQt_PyObject )"), p) if self.error is None: network = np.asarray(data) del data self.graph.network = np.zeros(network.shape[0], dtype=dt) for k, t in enumerate(dt): self.graph.network[t[0]] = network[:, k].astype(t[1]) del network self.graph.type_loaded = 'NETWORK' self.graph.status = 'OK' self.graph.network_ok = True self.graph.prepare_graph() self.graph.__source__ = None self.graph.__field_name__ = None self.graph.__layer_name__ = None self.emit(SIGNAL("FinishedThreadedProcedure( PyQt_PyObject )"), None)
class TestGraph(TestCase): def test_create_from_geography(self): self.graph = Graph() self.graph.create_from_geography( test_network, "link_id", "dir", "distance", centroids=centroids, skim_fields=[], anode="A_NODE", bnode="B_NODE", ) self.graph.set_graph(cost_field="distance") self.graph.set_blocked_centroid_flows(block_centroid_flows=True) self.graph.set_skimming("distance") def test_prepare_graph(self): self.test_create_from_geography() self.graph.prepare_graph(centroids) reference_graph = Graph() reference_graph.load_from_disk(test_graph) if not np.array_equal(self.graph.graph, reference_graph.graph): self.fail("Reference graph and newly-prepared graph are not equal") def test_set_graph(self): self.test_prepare_graph() self.graph.set_graph(cost_field="distance") self.graph.set_blocked_centroid_flows(block_centroid_flows=True) if self.graph.num_zones != centroids.shape[0]: self.fail("Number of centroids not properly set") if self.graph.num_links != 222: self.fail("Number of links not properly set") if self.graph.num_nodes != 93: self.fail("Number of nodes not properly set - " + str(self.graph.num_nodes)) def test_save_to_disk(self): self.test_create_from_geography() self.graph.save_to_disk(join(path_test, "aequilibrae_test_graph.aeg")) self.graph_id = self.graph.__id__ self.graph_version = self.graph.__version__ def test_load_from_disk(self): self.test_save_to_disk() reference_graph = Graph() reference_graph.load_from_disk(test_graph) new_graph = Graph() new_graph.load_from_disk(join(path_test, "aequilibrae_test_graph.aeg")) comparisons = [ ("Graph", new_graph.graph, reference_graph.graph), ("b_nodes", new_graph.b_node, reference_graph.b_node), ("Forward-Star", new_graph.fs, reference_graph.fs), ("cost", new_graph.cost, reference_graph.cost), ("centroids", new_graph.centroids, reference_graph.centroids), ("skims", new_graph.skims, reference_graph.skims), ("link ids", new_graph.ids, reference_graph.ids), ("Network", new_graph.network, reference_graph.network), ("All Nodes", new_graph.all_nodes, reference_graph.all_nodes), ("Nodes to indices", new_graph.nodes_to_indices, reference_graph.nodes_to_indices), ] for comparison, newg, refg in comparisons: if not np.array_equal(newg, refg): self.fail( "Reference %s and %s created and saved to disk are not equal" % (comparison, comparison)) comparisons = [ ("nodes", new_graph.num_nodes, reference_graph.num_nodes), ("links", new_graph.num_links, reference_graph.num_links), ("zones", new_graph.num_zones, reference_graph.num_zones), ("block through centroids", new_graph.block_centroid_flows, reference_graph.block_centroid_flows), ("Graph ID", new_graph.__id__, self.graph_id), ("Graph Version", new_graph.__version__, self.graph_version), ] for comparison, newg, refg in comparisons: if newg != refg: self.fail( "Reference %s and %s created and saved to disk are not equal" % (comparison, comparison)) def test_available_skims(self): self.test_set_graph() if self.graph.available_skims() != ["distance"]: self.fail("Skim availability with problems") def test_exclude_links(self): p = Project() p.load(siouxfalls_project) p.network.build_graphs() g = p.network.graphs['c'] # type: Graph # excludes a link before any setting or preparation g.exclude_links([12]) g.set_graph('distance') r1 = PathResults() r1.prepare(g) r1.compute_path(1, 14) self.assertEqual(list(r1.path), [2, 6, 10, 34]) # We exclude one link that we know was part of the last shortest path g.exclude_links([10]) r2 = PathResults() r2.prepare(g) r2.compute_path(1, 14) self.assertEqual(list(r2.path), [2, 7, 36, 34]) p.conn.close()
class ImpedanceMatrixDialog(QtGui.QDialog, FORM_CLASS): def __init__(self, iface): QDialog.__init__(self) self.iface = iface self.setupUi(self) self.result = SkimResults() self.validtypes = integer_types + float_types self.tot_skims = 0 self.name_skims = 0 self.graph = None self.skimmeable_fields = [] self.skim_fields = [] self.error = None # FIRST, we connect slot signals # For loading a new graph self.load_graph_from_file.clicked.connect( self.loaded_new_graph_from_file) # For adding skims # self.bt_add_skim.clicked.connect(self.add_to_skim_list) self.but_adds_to_links.clicked.connect(self.append_to_list) self.but_removes_from_links.clicked.connect(self.removes_fields) self.do_dist_matrix.clicked.connect(self.run_skimming) # SECOND, we set visibility for sections that should not be shown when the form opens (overlapping items) # and re-dimension the items that need re-dimensioning self.hide_all_progress_bars() self.available_skims_table.setColumnWidth(0, 245) self.skim_list.setColumnWidth(0, 245) self.available_skims_table.setEditTriggers( QtGui.QAbstractItemView.NoEditTriggers) self.skim_list.setEditTriggers(QtGui.QAbstractItemView.NoEditTriggers) # loads default path from parameters self.path = standard_path() def removes_fields(self): table = self.available_skims_table final_table = self.skim_list for i in final_table.selectedRanges(): old_fields = [ final_table.item(row, 0).text() for row in xrange(i.topRow(), i.bottomRow() + 1) ] for row in xrange(i.bottomRow(), i.topRow() - 1, -1): final_table.removeRow(row) counter = table.rowCount() for field in old_fields: table.setRowCount(counter + 1) item1 = QTableWidgetItem(field) item1.setFlags(Qt.ItemIsEnabled | Qt.ItemIsSelectable) table.setItem(counter, 0, item1) counter += 1 def append_to_list(self): table = self.available_skims_table final_table = self.skim_list for i in table.selectedRanges(): new_fields = [ table.item(row, 0).text() for row in xrange(i.topRow(), i.bottomRow() + 1) ] for f in new_fields: self.skim_fields.append(f.encode('utf-8')) for row in xrange(i.bottomRow(), i.topRow() - 1, -1): table.removeRow(row) counter = final_table.rowCount() for field in new_fields: final_table.setRowCount(counter + 1) item1 = QTableWidgetItem(field) item1.setFlags(Qt.ItemIsEnabled | Qt.ItemIsSelectable) final_table.setItem(counter, 0, item1) counter += 1 def hide_all_progress_bars(self): self.progressbar.setVisible(False) self.progress_label.setVisible(False) self.progressbar.setValue(0) self.progress_label.setText('') def loaded_new_graph_from_file(self): file_types = ["AequilibraE graph(*.aeg)"] new_name, file_type = GetOutputFileName(self, 'Graph file', file_types, ".aeg", self.path) self.cb_minimizing.clear() self.available_skims_table.clearContents() self.block_paths.setChecked(False) self.graph = None if new_name is not None: self.graph_file_name.setText(new_name) self.graph = Graph() self.graph.load_from_disk(new_name) self.block_paths.setChecked(self.graph.block_centroid_flows) graph_fields = list(self.graph.graph.dtype.names) self.skimmeable_fields = self.graph.available_skims() self.available_skims_table.setRowCount(len(self.skimmeable_fields)) for q in self.skimmeable_fields: self.cb_minimizing.addItem(q) self.available_skims_table.setItem(0, 0, QTableWidgetItem(q)) def browse_outfile(self): self.imped_results = None new_name, extension = GetOutputFileName( self, 'AequilibraE impedance computation', matrix_export_types, '.aem', self.path) if new_name is not None: self.imped_results = new_name.encode('utf-8') def run_thread(self): self.do_dist_matrix.setVisible(False) self.progressbar.setRange(0, self.graph.num_zones) QObject.connect(self.worker_thread, SIGNAL("skimming"), self.signal_handler) self.worker_thread.start() self.exec_() def signal_handler(self, val): if val[0] == 'zones finalized': self.progressbar.setValue(val[1]) elif val[0] == 'text skimming': self.progress_label.setText(val[1]) elif val[0] == 'finished_threaded_procedure': self.finished_threaded_procedure() def finished_threaded_procedure(self): self.report = self.worker_thread.report self.result.skims.export(self.imped_results) self.exit_procedure() def run_skimming(self): # Saving results if self.error is None: self.browse_outfile() cost_field = self.cb_minimizing.currentText().encode('utf-8') # We prepare the graph to set all nodes as centroids if self.rdo_all_nodes.isChecked(): self.graph.prepare_graph(self.graph.all_nodes) self.graph.set_graph( cost_field=cost_field, skim_fields=self.skim_fields, block_centroid_flows=self.block_paths.isChecked()) self.result.prepare(self.graph) self.funding1.setVisible(False) self.funding2.setVisible(False) self.progressbar.setVisible(True) self.progress_label.setVisible(True) self.worker_thread = NetworkSkimming(self.graph, self.result) try: self.run_thread() except ValueError as error: qgis.utils.iface.messageBar().pushMessage("Input error", error.message, level=3) else: qgis.utils.iface.messageBar().pushMessage("Error:", self.error, level=3) def check_inputs(self): self.error = None if self.rdo_all_nodes.isChecked() and self.block_paths.isChecked(): self.error = 'It is not possible to trace paths between all nodes while blocking flows through centroids' if self.graph is None: self.error = 'No graph loaded' if len(self.skim_fields) < 1: self.error = 'No skim fields provided' def exit_procedure(self): self.close() if self.report: dlg2 = ReportDialog(self.iface, self.report) dlg2.show() dlg2.exec_()
class DesireLinesProcedure(WorkerThread): def __init__(self, parentThread, layer: str, id_field: int, matrix: AequilibraeMatrix, matrix_hash: dict, dl_type: str) -> None: WorkerThread.__init__(self, parentThread) self.layer = layer self.id_field = id_field self.matrix = matrix self.dl_type = dl_type self.error = None self.matrix_hash = matrix_hash self.report = [] self.logger = logging.getLogger('aequilibrae') self.nodes_to_indices = {matrix.index[x]: x for x in range(matrix.zones)} self.python_version = (8 * struct.calcsize("P")) if error: self.error = 'Scipy and/or Numpy not installed' self.report.append(self.error) self.procedure = "ASSIGNMENT" def doWork(self): if self.error is None: # In case we have only one class unnasigned = 0 classes = self.matrix.matrix_view.shape[2] layer = get_vector_layer_by_name(self.layer) idx = layer.dataProvider().fieldNameIndex(self.id_field) feature_count = layer.featureCount() self.desire_lines.emit(('job_size_dl', feature_count)) all_centroids = {} for P, feat in enumerate(layer.getFeatures()): geom = feat.geometry() if geom is not None: point = list(geom.centroid().asPoint()) centroid_id = feat.attributes()[idx] all_centroids[centroid_id] = point self.desire_lines.emit(('jobs_done_dl', P)) self.desire_lines.emit(('text_dl', "Loading Layer Features: " + str(P) + "/" + str(feature_count))) # Creating resulting layer EPSG_code = int(layer.crs().authid().split(":")[1]) desireline_layer = QgsVectorLayer("LineString?crs=epsg:" + str(EPSG_code), self.dl_type, "memory") dlpr = desireline_layer.dataProvider() base_dl_fields = [QgsField("link_id", QVariant.Int), QgsField("A_Node", QVariant.Int), QgsField("B_Node", QVariant.Int), QgsField("direct", QVariant.Int), QgsField("distance", QVariant.Double)] if self.dl_type == "DesireLines": items = [] for i, j in all_centroids.items(): items.append((i, j[0], j[1])) coords = np.array(items) coord_index = np.zeros((self.matrix.index[:].max().astype(np.int64) + 1, 2)) coord_index[coords[:, 0].astype(np.int64), 0] = coords[:, 1] coord_index[coords[:, 0].astype(np.int64), 1] = coords[:, 2] self.desire_lines.emit(('text_dl', "Manipulating matrix indices")) zones = self.matrix.index[:].shape[0] a = np.array(self.matrix.index[:], np.int64) ij, ji = np.meshgrid(a, a, sparse=False, indexing='ij') ij = ij.flatten() ji = ji.flatten() arrays = [ij, ji] self.desire_lines.emit(('text_dl', "Collecting all matrices")) self.desire_lines.emit(('job_size_dl', len(self.matrix.view_names))) total_mat = np.zeros((zones, zones), np.float64) for i, mat in enumerate(self.matrix.view_names): arrays.append(self.matrix.matrix[mat].flatten()) total_mat += self.matrix.matrix[mat] self.desire_lines.emit(('jobs_done_dl', i + 1)) # Eliminates the cells for which we don't have geography self.desire_lines.emit(('text_dl', "Filtering zones with no geography available")) zones_with_no_geography = [x for x in self.matrix.index[:] if x not in all_centroids] if zones_with_no_geography: self.desire_lines.emit(('job_size_dl', len(zones_with_no_geography))) for k, z in enumerate(zones_with_no_geography): i = self.matrix.matrix_hash[z] t = np.nansum(total_mat[i, :]) + np.nansum(total_mat[:, i]) unnasigned += t self.report.append( 'Zone {} does not have a corresponding centroid/zone. Total flow {}'.format(z, t)) total_mat[i, :] = 0 total_mat[:, i] = 0 self.desire_lines.emit(('jobs_done_dl', k + 1)) self.desire_lines.emit(('text_dl', "Filtering down to OD pairs with flows")) field_names = [x for x in self.matrix.view_names] nonzero = np.nonzero(total_mat.flatten()) arrays = np.vstack(arrays).transpose() arrays = arrays[nonzero, :] arrays = arrays.reshape(arrays.shape[1], arrays.shape[2]) base_types = [(x, np.float64) for x in ['from', 'to']] base_types = base_types + [(x + '_AB', np.float64) for x in field_names] dtypes_ab = [(x, np.int64) for x in ['from', 'to']] + [(x + '_AB', float) for x in field_names] dtypes_ba = [(x, np.int64) for x in ['to', 'from']] + [(x + '_BA', float) for x in field_names] ab_mat = np.array(arrays[arrays[:, 0] > arrays[:, 1], :]) ba_mat = np.array(arrays[arrays[:, 0] < arrays[:, 1], :]) flows_ab = ab_mat.view(base_types) flows_ab = flows_ab.reshape(flows_ab.shape[:-1]) flows_ab = flows_ab.astype(dtypes_ab) flows_ba = ba_mat.view(base_types) flows_ba = flows_ba.reshape(flows_ba.shape[:-1]) flows_ba = flows_ba.astype(dtypes_ba) defaults1 = {x + '_AB': 0.0 for x in field_names} defaults = {x + '_BA': 0.0 for x in field_names} defaults = {**defaults, **defaults1} self.desire_lines.emit(('text_dl', "Concatenating AB & BA flows")) flows = rfn.join_by(['from', 'to'], flows_ab, flows_ba, jointype='outer', defaults=defaults, usemask=True, asrecarray=True) flows = flows.filled() flows_ab = 0 flows_ba = 0 for f in flows.dtype.names[2:]: base_dl_fields.extend([QgsField(f, QVariant.Double)]) dlpr.addAttributes(base_dl_fields) desireline_layer.updateFields() self.desire_lines.emit(('text_dl', "Creating Desire Lines")) self.desire_lines.emit(('job_size_dl', flows.shape[0])) all_features = [] for i, rec in enumerate(flows): a_node = rec[0] b_node = rec[1] a_point = QgsPointXY(*all_centroids[a_node]) b_point = QgsPointXY(*all_centroids[b_node]) dist = QgsGeometry().fromPointXY(a_point).distance( QgsGeometry().fromPointXY(b_point)) feature = QgsFeature() feature.setGeometry(QgsGeometry.fromPolylineXY([a_point, b_point])) attrs = [i + 1, int(a_node), int(b_node), 0, dist] attrs.extend([float(x) for x in list(rec)[2:]]) feature.setAttributes(attrs) all_features.append(feature) self.desire_lines.emit(('jobs_done_dl', i)) if unnasigned > 0: self.report.append('Total non assigned flows (not counting intrazonals):' + str(unnasigned)) if flows.shape[0] > 1: a = dlpr.addFeatures(all_features) self.result_layer = desireline_layer else: self.report.append('Nothing to show') elif self.dl_type == "DelaunayLines": for f in self.matrix.view_names: base_dl_fields.extend([QgsField(f + '_ab', QVariant.Double), QgsField(f + '_ba', QVariant.Double), QgsField(f + '_tot', QVariant.Double)]) dlpr.addAttributes(base_dl_fields) desireline_layer.updateFields() self.desire_lines.emit(('text_dl', "Building Delaunay dataset")) points = [] node_id_in_delaunay_results = {} i = 0 self.desire_lines.emit(('job_size_dl', len(all_centroids))) for k, v in all_centroids.items(): self.desire_lines.emit(('jobs_done_dl', i)) points.append(v) node_id_in_delaunay_results[i] = k i += 1 self.desire_lines.emit(('text_dl', "Computing Delaunay Triangles")) tri = Delaunay(np.array(points)) # We process all the triangles to only get each edge once self.desire_lines.emit(('text_dl', "Building Delaunay Network: Collecting Edges")) edges = [] if self.python_version == 32: all_edges = tri.vertices else: all_edges = tri.simplices self.desire_lines.emit(('job_size_dl', len(all_edges))) for j, triangle in enumerate(all_edges): self.desire_lines.emit(('jobs_done_dl', j)) links = list(itertools.combinations(triangle, 2)) for i in links: edges.append([min(i[0], i[1]), max(i[0], i[1])]) self.desire_lines.emit(('text_dl', "Building Delaunay Network: Getting unique edges")) edges = OrderedDict((str(x), x) for x in edges).values() # Writing Delaunay layer self.desire_lines.emit(('text_dl', "Building Delaunay Network: Assembling Layer")) desireline_link_id = 1 data = [] dl_ids_on_links = {} self.desire_lines.emit(('job_size_dl', len(edges))) for j, edge in enumerate(edges): self.desire_lines.emit(('jobs_done_dl', j)) a_node = node_id_in_delaunay_results[edge[0]] a_point = all_centroids[a_node] a_point = QgsPointXY(a_point[0], a_point[1]) b_node = node_id_in_delaunay_results[edge[1]] b_point = all_centroids[b_node] b_point = QgsPointXY(b_point[0], b_point[1]) dist = QgsGeometry().fromPointXY(a_point).distance(QgsGeometry().fromPointXY(b_point)) line = [] line.append(desireline_link_id) line.append(a_node) line.append(b_node) line.append(dist) line.append(dist) line.append(0) data.append(line) dl_ids_on_links[desireline_link_id] = [a_node, b_node, 0, dist] desireline_link_id += 1 self.desire_lines.emit(('text_dl', "Building graph")) network = np.asarray(data) del data # types for the network self.graph = Graph() itype = self.graph.default_types('int') ftype = self.graph.default_types('float') all_types = [itype, itype, itype, ftype, ftype, np.int8] all_titles = ['link_id', 'a_node', 'b_node', 'distance_ab', 'distance_ba', 'direction'] dt = [(t, d) for t, d in zip(all_titles, all_types)] self.graph.network = np.zeros(network.shape[0], dtype=dt) for k, t in enumerate(dt): self.graph.network[t[0]] = network[:, k].astype(t[1]) del network self.graph.type_loaded = 'NETWORK' self.graph.status = 'OK' self.graph.network_ok = True self.graph.prepare_graph(self.matrix.index.astype(np.int64)) self.graph.set_graph(cost_field='distance', skim_fields=False, block_centroid_flows=False) self.results = AssignmentResults() self.results.prepare(self.graph, self.matrix) self.desire_lines.emit(('text_dl', "Assigning demand")) self.desire_lines.emit(('job_size_dl', self.matrix.index.shape[0])) assigner = allOrNothing(self.matrix, self.graph, self.results) assigner.execute() self.report = assigner.report print(self.results.link_loads) self.desire_lines.emit(('text_dl', "Collecting results")) self.desire_lines.emit(('text_dl', "Building resulting layer")) features = [] max_edges = len(edges) self.desire_lines.emit(('job_size_dl', max_edges)) link_loads = self.results.save_to_disk() for i, link_id in enumerate(link_loads.index): self.desire_lines.emit(('jobs_done_dl', i)) a_node, b_node, direct, dist = dl_ids_on_links[link_id] attr = [int(link_id), a_node, b_node, direct, dist] a_point = all_centroids[a_node] a_point = QgsPointXY(a_point[0], a_point[1]) b_point = all_centroids[b_node] b_point = QgsPointXY(b_point[0], b_point[1]) feature = QgsFeature() feature.setGeometry(QgsGeometry.fromPolylineXY([a_point, b_point])) for c in self.matrix.view_names: attr.extend([float(link_loads.data[c + '_ab'][i]), float(link_loads.data[c + '_ba'][i]), float(link_loads.data[c + '_tot'][i])]) feature.setAttributes(attr) features.append(feature) a = dlpr.addFeatures(features) self.result_layer = desireline_layer self.desire_lines.emit(('finished_desire_lines_procedure', 0))
class TestGraph(TestCase): def test_create_from_geography(self): self.graph = Graph() self.graph.create_from_geography(test_network, 'link_id', 'dir', 'distance', centroids=centroids, skim_fields=[], anode="A_NODE", bnode="B_NODE") self.graph.set_graph(cost_field='distance', block_centroid_flows=True) def test_load_network_from_csv(self): pass def test_prepare_graph(self): self.test_create_from_geography() self.graph.prepare_graph(centroids) reference_graph = Graph() reference_graph.load_from_disk(test_graph) if not np.array_equal(self.graph.graph, reference_graph.graph): self.fail('Reference graph and newly-prepared graph are not equal') def test_set_graph(self): self.test_prepare_graph() self.graph.set_graph(cost_field='distance', block_centroid_flows=True) if self.graph.num_zones != centroids.shape[0]: self.fail('Number of centroids not properly set') if self.graph.num_links != 222: self.fail('Number of links not properly set') if self.graph.num_nodes != 93: self.fail('Number of nodes not properly set - ' + str(self.graph.num_nodes)) def test_save_to_disk(self): self.test_create_from_geography() self.graph.save_to_disk(join(path_test, 'aequilibrae_test_graph.aeg')) self.graph_id = self.graph.__id__ self.graph_version = self.graph.__version__ def test_load_from_disk(self): self.test_save_to_disk() reference_graph = Graph() reference_graph.load_from_disk(test_graph) new_graph = Graph() new_graph.load_from_disk(join(path_test, 'aequilibrae_test_graph.aeg')) comparisons = [ ('Graph', new_graph.graph, reference_graph.graph), ('b_nodes', new_graph.b_node, reference_graph.b_node), ('Forward-Star', new_graph.fs, reference_graph.fs), ('cost', new_graph.cost, reference_graph.cost), ('centroids', new_graph.centroids, reference_graph.centroids), ('skims', new_graph.skims, reference_graph.skims), ('link ids', new_graph.ids, reference_graph.ids), ('Network', new_graph.network, reference_graph.network), ('All Nodes', new_graph.all_nodes, reference_graph.all_nodes), ('Nodes to indices', new_graph.nodes_to_indices, reference_graph.nodes_to_indices) ] for comparison, newg, refg in comparisons: if not np.array_equal(newg, refg): self.fail( 'Reference %s and %s created and saved to disk are not equal' % (comparison, comparison)) comparisons = [ ('nodes', new_graph.num_nodes, reference_graph.num_nodes), ('links', new_graph.num_links, reference_graph.num_links), ('zones', new_graph.num_zones, reference_graph.num_zones), ('block through centroids', new_graph.block_centroid_flows, reference_graph.block_centroid_flows), ('Graph ID', new_graph.__id__, self.graph_id), ('Graph Version', new_graph.__version__, self.graph_version) ] for comparison, newg, refg in comparisons: if newg != refg: self.fail( 'Reference %s and %s created and saved to disk are not equal' % (comparison, comparison)) def test_reset_single_fields(self): pass def test_add_single_field(self): pass def test_available_skims(self): self.test_set_graph() if self.graph.available_skims() != ['distance']: self.fail('Skim availability with problems')
class TestGraph(TestCase): def test_create_from_geography(self): self.graph = Graph() self.graph.create_from_geography( test_network, "link_id", "dir", "distance", centroids=centroids, skim_fields=[], anode="A_NODE", bnode="B_NODE", ) self.graph.set_graph(cost_field="distance", block_centroid_flows=True) def test_load_network_from_csv(self): pass def test_prepare_graph(self): self.test_create_from_geography() self.graph.prepare_graph(centroids) reference_graph = Graph() reference_graph.load_from_disk(test_graph) if not np.array_equal(self.graph.graph, reference_graph.graph): self.fail("Reference graph and newly-prepared graph are not equal") def test_set_graph(self): self.test_prepare_graph() self.graph.set_graph(cost_field="distance", block_centroid_flows=True) if self.graph.num_zones != centroids.shape[0]: self.fail("Number of centroids not properly set") if self.graph.num_links != 222: self.fail("Number of links not properly set") if self.graph.num_nodes != 93: self.fail("Number of nodes not properly set - " + str(self.graph.num_nodes)) def test_save_to_disk(self): self.test_create_from_geography() self.graph.save_to_disk(join(path_test, "aequilibrae_test_graph.aeg")) self.graph_id = self.graph.__id__ self.graph_version = self.graph.__version__ def test_load_from_disk(self): self.test_save_to_disk() reference_graph = Graph() reference_graph.load_from_disk(test_graph) new_graph = Graph() new_graph.load_from_disk(join(path_test, "aequilibrae_test_graph.aeg")) comparisons = [ ("Graph", new_graph.graph, reference_graph.graph), ("b_nodes", new_graph.b_node, reference_graph.b_node), ("Forward-Star", new_graph.fs, reference_graph.fs), ("cost", new_graph.cost, reference_graph.cost), ("centroids", new_graph.centroids, reference_graph.centroids), ("skims", new_graph.skims, reference_graph.skims), ("link ids", new_graph.ids, reference_graph.ids), ("Network", new_graph.network, reference_graph.network), ("All Nodes", new_graph.all_nodes, reference_graph.all_nodes), ( "Nodes to indices", new_graph.nodes_to_indices, reference_graph.nodes_to_indices, ), ] for comparison, newg, refg in comparisons: if not np.array_equal(newg, refg): self.fail( "Reference %s and %s created and saved to disk are not equal" % (comparison, comparison) ) comparisons = [ ("nodes", new_graph.num_nodes, reference_graph.num_nodes), ("links", new_graph.num_links, reference_graph.num_links), ("zones", new_graph.num_zones, reference_graph.num_zones), ( "block through centroids", new_graph.block_centroid_flows, reference_graph.block_centroid_flows, ), ("Graph ID", new_graph.__id__, self.graph_id), ("Graph Version", new_graph.__version__, self.graph_version), ] for comparison, newg, refg in comparisons: if newg != refg: self.fail( "Reference %s and %s created and saved to disk are not equal" % (comparison, comparison) ) def test_reset_single_fields(self): pass def test_add_single_field(self): pass def test_available_skims(self): self.test_set_graph() if self.graph.available_skims() != ["distance"]: self.fail("Skim availability with problems")
def build_graphs(self, fields: list = None, modes: list = None) -> None: """Builds graphs for all modes currently available in the model When called, it overwrites all graphs previously created and stored in the networks' dictionary of graphs Args: *fields* (:obj:`list`, optional): When working with very large graphs with large number of fields in the database, it may be useful to specify which fields to use *modes* (:obj:`list`, optional): When working with very large graphs with large number of fields in the database, it may be useful to generate only those we need To use the *fields* parameter, a minimalistic option is the following :: p = Project() p.open(nm) fields = ['distance'] p.network.build_graphs(fields, modes = ['c', 'w']) """ curr = self.conn.cursor() if fields is None: curr.execute("PRAGMA table_info(links);") field_names = curr.fetchall() ignore_fields = ["ogc_fid", "geometry"] all_fields = [ f[1] for f in field_names if f[1] not in ignore_fields ] else: fields.extend( ["link_id", "a_node", "b_node", "direction", "modes"]) all_fields = list(set(fields)) if modes is None: modes = curr.execute("select mode_id from modes;").fetchall() modes = [m[0] for m in modes] elif isinstance(modes, str): modes = [modes] sql = f"select {','.join(all_fields)} from links" df = pd.read_sql(sql, self.conn).fillna(value=np.nan) valid_fields = list(df.select_dtypes(np.number).columns) + ["modes"] curr.execute( "select node_id from nodes where is_centroid=1 order by node_id;") centroids = np.array([i[0] for i in curr.fetchall()], np.uint32) data = df[valid_fields] for m in modes: net = pd.DataFrame(data, copy=True) net.loc[~net.modes.str.contains(m), "b_node"] = net.loc[~net.modes.str.contains(m), "a_node"] g = Graph() g.mode = m g.network = net g.prepare_graph(centroids) g.set_blocked_centroid_flows(True) self.graphs[m] = g
class DesireLinesProcedure(WorkerThread): def __init__(self, parentThread, layer, id_field, matrix, dl_type): WorkerThread.__init__(self, parentThread) self.layer = layer self.id_field = id_field self.matrix = matrix self.dl_type = dl_type self.error = None if error: self.error = 'Scipy and/or Numpy not installed' self.procedure = "ASSIGNMENT" def doWork(self): if self.error is None: layer = get_vector_layer_by_name(self.layer) idx = layer.fieldNameIndex(self.id_field) matrix = self.matrix featcount = layer.featureCount() self.emit(SIGNAL("ProgressMaxValue(PyQt_PyObject)"), (0, featcount)) P = 0 points = [] point_ids = [] for feat in layer.getFeatures(): P += 1 self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, int(P))) self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Loading Layer Features: " + str(P) + "/" + str(featcount))) geom = feat.geometry() if geom is not None: point = list(geom.centroid().asPoint()) points.append(point) point_ids.append(feat.attributes()[idx]) points = np.array(points) self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, featcount)) self.emit( SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Preparing consistency check Matrix Vs. Zoning layer")) vector1 = np.nonzero(np.sum(matrix, axis=0))[0] vector2 = np.nonzero(np.sum(matrix, axis=1))[0] nonzero = np.hstack((vector1, vector2)) self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, nonzero.shape[0])) for i, zone in enumerate(nonzero): if zone not in point_ids: self.error = 'Zone ' + str( zone) + ' with positive flow not in zoning file' break self.emit(SIGNAL("ProgressMaxValue(PyQt_PyObject)"), (0, i + 1)) self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, nonzero.shape[0])) if self.error is None: #Creating resulting layer EPSG_code = int(layer.crs().authid().split(":")[1]) desireline_layer = QgsVectorLayer( "LineString?crs=epsg:" + str(EPSG_code), self.dl_type, "memory") dlpr = desireline_layer.dataProvider() dlpr.addAttributes([ QgsField("link_id", QVariant.Int), QgsField("A_Node", QVariant.Int), QgsField("B_Node", QVariant.Int), QgsField("direct", QVariant.Int), QgsField("length", QVariant.Double), QgsField("AB_FLOW", QVariant.Double), QgsField("BA_FLOW", QVariant.Double), QgsField("TOT_FLOW", QVariant.Double) ]) desireline_layer.updateFields() if self.dl_type == "DesireLines": self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Creating Desire Lines")) self.emit(SIGNAL("ProgressMaxValue(PyQt_PyObject)"), (0, self.matrix.shape[0] * self.matrix.shape[1] / 2)) #We create the dictionary with point information all_points = {} point_ids = np.array(point_ids).astype(np.int) for i in range(point_ids.shape[0]): all_points[point_ids[i]] = points[i] # We are assuming that the matrix is square here. Maybe we could add more general code layer desireline_link_id = 1 q = 0 all_features = [] for i in range(self.matrix.shape[0]): for j in xrange(i + 1, self.matrix.shape[1]): q += 1 self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, q)) if self.matrix[i, j] + self.matrix[j, i] > 0: a_node = i a_point = QgsPoint(all_points[a_node][0], all_points[a_node][1]) b_node = j b_point = QgsPoint(all_points[b_node][0], all_points[b_node][1]) dist = QgsGeometry().fromPoint(a_point).distance( QgsGeometry().fromPoint(b_point)) feature = QgsFeature() feature.setGeometry( QgsGeometry.fromPolyline([a_point, b_point])) feature.setAttributes([ desireline_link_id, a_node, b_node, 0, dist, float(self.matrix[i, j]), float(self.matrix[j, i]), float(self.matrix[i, j] + self.matrix[j, i]) ]) all_features.append(feature) desireline_link_id += 1 a = dlpr.addFeatures(all_features) self.result_layer = desireline_layer elif self.dl_type == "DelaunayLines": self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Computing Delaunay Triangles")) tri = Delaunay(points) #We process all the triangles to only get each edge once self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Building Delaunay Network: Collecting Edges")) edges = [] for triangle in tri.simplices: links = list(itertools.combinations(triangle, 2)) for i in links: l = [min(i[0], i[1]), max(i[0], i[1])] if l not in edges: edges.append(l) #Writing Delaunay layer self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Building Delaunay Network: Assembling Layer")) desireline_link_id = 1 data = [] for edge in edges: a_node = edge[0] a_point = QgsPoint(points[a_node][0], points[a_node][1]) b_node = edge[1] b_point = QgsPoint(points[b_node][0], points[b_node][1]) dist = QgsGeometry().fromPoint(a_point).distance( QgsGeometry().fromPoint(b_point)) line = [] line.append(desireline_link_id) line.append(point_ids[a_node]) line.append(point_ids[b_node]) line.append(dist) line.append(dist) line.append(0) data.append(line) desireline_link_id += 1 self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Building graph")) network = np.asarray(data) del data #types for the network all_types = [ np.int64, np.int64, np.int64, np.float64, np.float64, np.int64 ] all_titles = [ 'link_id', 'a_node', 'b_node', 'length_ab', 'length_ba', 'direction' ] dt = [(t, d) for t, d in zip(all_titles, all_types)] self.graph = Graph() self.graph.network = np.zeros(network.shape[0], dtype=dt) for k, t in enumerate(dt): self.graph.network[t[0]] = network[:, k].astype(t[1]) del network # Here we transform the network to go from node 1 to N max_node = max(np.max(self.graph.network['a_node']), np.max(self.graph.network['b_node'])) max_node = max(max_node, self.matrix.shape[0], self.matrix.shape[1]) + 1 self.hash = np.zeros(max_node, np.int) # Checks if any zone from the matrix is not present in the areas/node layer t1 = np.sum(self.matrix, axis=0) t2 = np.sum(self.matrix, axis=1) if t1.shape[0] > t2.shape[0]: t2.resize(t1.shape) elif t2.shape[0] > t1.shape[0]: t1.resize(t2.shape) totals = t1 + t2 all_nodes = np.bincount(self.graph.network['a_node']) for i in range(totals.shape[0]): if totals[i]: if not all_nodes[i]: qgis.utils.iface.messageBar().pushMessage( "Matrix has demand for zones that do not exist " "in the zones/nodes provided. Demand for those" "ones were ignored. e.g. " + str(i), '', level=3) break h = 1 for i in range(self.graph.network.shape[0]): a_node = self.graph.network['a_node'][i] if self.hash[a_node] == 0: self.hash[a_node] = h h += 1 b_node = self.graph.network['b_node'][i] if self.hash[b_node] == 0: self.hash[b_node] = h h += 1 self.graph.network['a_node'][i] = self.hash[a_node] self.graph.network['b_node'][i] = self.hash[b_node] # End of network transformation #Now we transform the matrix appropriately self.matrix = reblocks_matrix(self.matrix, self.hash, h) self.graph.type_loaded = 'NETWORK' self.graph.status = 'OK' self.graph.network_ok = True self.graph.prepare_graph() self.graph.set_graph(h - 1, cost_field='length', block_centroid_flows=False) self.results = AssignmentResults() self.results.prepare(self.graph) self.results.set_cores(1) # Do the assignment all_or_nothing(self.matrix, self.graph, self.results) f = self.results.link_loads[:, 0] link_loads = np.zeros((f.shape[0] + 1, 2)) for i in range(f.shape[0] - 1): direction = self.graph.graph['direction'][i] link_id = self.graph.graph['link_id'][i] flow = f[i] if direction == 1: link_loads[link_id, 0] = flow else: link_loads[link_id, 1] = flow desireline_link_id = 1 for edge in edges: a_node = edge[0] a_point = QgsPoint(points[a_node][0], points[a_node][1]) b_node = edge[1] b_point = QgsPoint(points[b_node][0], points[b_node][1]) dist = QgsGeometry().fromPoint(a_point).distance( QgsGeometry().fromPoint(b_point)) feature = QgsFeature() feature.setGeometry( QgsGeometry.fromPolyline([a_point, b_point])) feature.setAttributes([ desireline_link_id, point_ids[a_node], point_ids[b_node], 0, dist, float(link_loads[desireline_link_id, 0]), float(link_loads[desireline_link_id, 1]), float(link_loads[desireline_link_id, 0] + link_loads[desireline_link_id, 1]) ]) a = dlpr.addFeatures([feature]) desireline_link_id += 1 self.result_layer = desireline_layer self.emit(SIGNAL("finished_threaded_procedure( PyQt_PyObject )"), True)
class DesireLinesProcedure(WorkerThread): def __init__(self, parentThread, layer, id_field, matrix, matrix_hash, dl_type): WorkerThread.__init__(self, parentThread) self.layer = layer self.id_field = id_field self.matrix = matrix self.dl_type = dl_type self.error = None self.matrix_hash = matrix_hash self.report = [] self.nodes_to_indices = {matrix.index[x]: x for x in range(matrix.zones)} self.python_version = (8 * struct.calcsize("P")) if error: self.error = 'Scipy and/or Numpy not installed' self.report.append(self.error) self.procedure = "ASSIGNMENT" def doWork(self): if self.error is None: # In case we have only one class unnasigned = 0 classes = self.matrix.matrix_view.shape[2] layer = get_vector_layer_by_name(self.layer) idx = layer.fieldNameIndex(self.id_field) feature_count = layer.featureCount() self.emit(SIGNAL("desire_lines"), ('job_size_dl', feature_count)) all_centroids = {} P = 0 for feat in layer.getFeatures(): P += 1 self.emit(SIGNAL("desire_lines"), ('jobs_done_dl', P)) self.emit(SIGNAL("desire_lines"), ('text_dl',"Loading Layer Features: " + str(P) + "/" + str(feature_count))) geom = feat.geometry() if geom is not None: point = list(geom.centroid().asPoint()) centroid_id = feat.attributes()[idx] all_centroids[centroid_id] = point #Creating resulting layer EPSG_code = int(layer.crs().authid().split(":")[1]) desireline_layer = QgsVectorLayer("LineString?crs=epsg:" + str(EPSG_code), self.dl_type, "memory") dlpr = desireline_layer.dataProvider() fields = [QgsField("link_id", QVariant.Int), QgsField("A_Node", QVariant.Int), QgsField("B_Node", QVariant.Int), QgsField("direct", QVariant.Int), QgsField("distance", QVariant.Double)] for f in self.matrix.view_names: fields.extend([QgsField(f + '_ab', QVariant.Double), QgsField(f + '_ba', QVariant.Double), QgsField(f + '_tot', QVariant.Double)]) dlpr.addAttributes(fields) desireline_layer.updateFields() if self.dl_type == "DesireLines": self.emit(SIGNAL("desire_lines"), ('text_dl',"Creating Desire Lines")) self.emit(SIGNAL("desire_lines"), ('job_size_dl', self.matrix.zones ** 2 / 2)) desireline_link_id = 1 q = 0 all_features = [] for i in range(self.matrix.zones): a_node = self.matrix.index[i] if a_node in all_centroids.keys(): if np.sum(self.matrix.matrix_view[i, :, :]) + np.sum(self.matrix.matrix_view[:, i, :]) > 0: columns_with_filled_cells = np.nonzero(np.sum(self.matrix.matrix_view[i, :, :], axis=1)) for j in columns_with_filled_cells[0]: if np.sum(self.matrix.matrix_view[i, j, :]) + np.sum(self.matrix.matrix_view[j, i, :]) > 0: b_node = self.matrix.index[j] if a_node in all_centroids.keys() and b_node in all_centroids.keys(): a_point = all_centroids[a_node] a_point = QgsPoint(a_point[0], a_point[1]) b_point = all_centroids[b_node] b_point = QgsPoint(b_point[0], b_point[1]) dist = QgsGeometry().fromPoint(a_point).distance(QgsGeometry().fromPoint(b_point)) feature = QgsFeature() feature.setGeometry(QgsGeometry.fromPolyline([a_point, b_point])) attrs = [desireline_link_id, int(a_node), int(b_node), 0, dist] for c in range(classes): attrs.extend([float(self.matrix.matrix_view[i, j, c]), float(self.matrix.matrix_view[j, i, c]), float(self.matrix.matrix_view[i, j, c]) + float(self.matrix.matrix_view[j, i, c])]) feature.setAttributes(attrs) all_features.append(feature) desireline_link_id += 1 else: tu = (a_node, b_node, np.sum(self.matrix.matrix_view[i, j, :]), np.sum(self.matrix.matrix_view[j, i, :])) self.report.append('No centroids available to depict flow between node {0} and node' '{1}. Total AB flow was equal to {2} and total BA flow was ' 'equal to {3}'.format(*tu)) unnasigned += np.sum(self.matrix.matrix_view[i, j, :]) + \ np.sum(self.matrix.matrix_view[j, i, :]) else: tu = (a_node, np.sum(self.matrix.matrix_view[i, :, :])) self.report.append('No centroids available to depict flows from node {0} to all the others.' 'Total flow from this zone is equal to {1}'.format(*tu)) unnasigned += np.sum(self.matrix.matrix_view[i, :, :]) q += self.matrix.zones self.emit(SIGNAL("desire_lines"), ('jobs_done_dl', q)) if unnasigned > 0: self.report.append('Total non assigned flows (not counting intrazonals):' + str(unnasigned)) if desireline_link_id > 1: a = dlpr.addFeatures(all_features) self.result_layer = desireline_layer else: self.report.append('Nothing to show') elif self.dl_type == "DelaunayLines": self.emit(SIGNAL("desire_lines"), ('text_dl', "Building Delaunay dataset")) points = [] node_id_in_delaunay_results = {} i = 0 self.emit(SIGNAL("desire_lines"), ('job_size_dl', len(all_centroids))) for k, v in all_centroids.iteritems(): self.emit(SIGNAL("desire_lines"), ('jobs_done_dl', i)) points.append(v) node_id_in_delaunay_results[i] = k i += 1 self.emit(SIGNAL("desire_lines"), ('text_dl', "Computing Delaunay Triangles")) tri = Delaunay(np.array(points)) # We process all the triangles to only get each edge once self.emit(SIGNAL("desire_lines"), ('text_dl', "Building Delaunay Network: Collecting Edges")) edges = [] if self.python_version == 32: all_edges = tri.vertices else: all_edges = tri.simplices self.emit(SIGNAL("desire_lines"), ('job_size_dl', len(all_edges))) for j, triangle in enumerate(all_edges): self.emit(SIGNAL("desire_lines"), ('jobs_done_dl', j)) links = list(itertools.combinations(triangle, 2)) for i in links: edges.append([min(i[0],i[1]), max(i[0],i[1])]) self.emit(SIGNAL("desire_lines"), ('text_dl', "Building Delaunay Network: Getting unique edges")) edges = OrderedDict((str(x), x) for x in edges).values() # Writing Delaunay layer self.emit(SIGNAL("desire_lines"), ('text_dl', "Building Delaunay Network: Assembling Layer")) desireline_link_id = 1 data = [] dl_ids_on_links = {} self.emit(SIGNAL("desire_lines"), ('job_size_dl', len(edges))) for j, edge in enumerate(edges): self.emit(SIGNAL("desire_lines"), ('jobs_done_dl', j)) a_node = node_id_in_delaunay_results[edge[0]] a_point = all_centroids[a_node] a_point = QgsPoint(a_point[0], a_point[1]) b_node = node_id_in_delaunay_results[edge[1]] b_point = all_centroids[b_node] b_point = QgsPoint(b_point[0], b_point[1]) dist = QgsGeometry().fromPoint(a_point).distance(QgsGeometry().fromPoint(b_point)) line = [] line.append(desireline_link_id) line.append(a_node) line.append(b_node) line.append(dist) line.append(dist) line.append(0) data.append(line) dl_ids_on_links[desireline_link_id] = [a_node, b_node, 0, dist] desireline_link_id += 1 self.emit(SIGNAL("desire_lines"), ('text_dl', "Building graph")) network = np.asarray(data) del data #types for the network self.graph = Graph() itype = self.graph.default_types('int') ftype = self.graph.default_types('float') all_types = [itype, itype, itype, ftype, ftype, np.int8] all_titles = ['link_id', 'a_node', 'b_node', 'distance_ab', 'distance_ba', 'direction'] dt = [(t, d) for t, d in zip(all_titles, all_types)] self.graph.network = np.zeros(network.shape[0], dtype=dt) for k, t in enumerate(dt): self.graph.network[t[0]] = network[:, k].astype(t[1]) del network self.graph.type_loaded = 'NETWORK' self.graph.status = 'OK' self.graph.network_ok = True try: self.graph.prepare_graph(self.matrix.index.astype(np.int64)) self.graph.set_graph(cost_field='distance', skim_fields=False, block_centroid_flows=False) self.results = AssignmentResults() self.results.prepare(self.graph, self.matrix) self.emit(SIGNAL("desire_lines"), ('text_dl', "Assigning demand")) self.emit(SIGNAL("desire_lines"), ('job_size_dl', self.matrix.index.shape[0])) assigner = allOrNothing(self.matrix, self.graph, self.results) assigner.execute() self.report = assigner.report self.emit(SIGNAL("desire_lines"), ('text_dl', "Collecting results")) link_loads = self.results.save_to_disk() self.emit(SIGNAL("desire_lines"), ('text_dl', "Building resulting layer")) features = [] max_edges = len(edges) self.emit(SIGNAL("desire_lines"), ('job_size_dl', max_edges)) for i, link_id in enumerate(link_loads.index): self.emit(SIGNAL("desire_lines"), ('jobs_done_dl', i)) a_node, b_node, direct, dist = dl_ids_on_links[link_id] attr = [int(link_id), a_node, b_node, direct, dist] a_point = all_centroids[a_node] a_point = QgsPoint(a_point[0], a_point[1]) b_point = all_centroids[b_node] b_point = QgsPoint(b_point[0], b_point[1]) feature = QgsFeature() feature.setGeometry(QgsGeometry.fromPolyline([a_point, b_point])) for c in self.matrix.view_names: attr.extend([float(link_loads.data[c + '_ab'][i]), float(link_loads.data[c + '_ba'][i]), float(link_loads.data[c + '_tot'][i])]) feature.setAttributes(attr) features.append(feature) a = dlpr.addFeatures(features) self.result_layer = desireline_layer except ValueError as error: self.report = [error.message] self.emit(SIGNAL("desire_lines"), ('finished_desire_lines_procedure', 0))
class DesireLinesProcedure(WorkerThread): def __init__(self, parentThread, layer, id_field, matrix, matrix_hash, dl_type): WorkerThread.__init__(self, parentThread) self.layer = layer self.id_field = id_field self.matrix = matrix self.dl_type = dl_type self.error = None self.matrix_hash = matrix_hash self.report = [] self.python_version = (8 * struct.calcsize("P")) if error: self.error = 'Scipy and/or Numpy not installed' self.procedure = "ASSIGNMENT" def doWork(self): if self.error is None: layer = get_vector_layer_by_name(self.layer) idx = layer.fieldNameIndex(self.id_field) matrix = self.matrix matrix_nodes = max(self.matrix_hash.values()) + 1 featcount = layer.featureCount() self.emit(SIGNAL("ProgressMaxValue(PyQt_PyObject)"), (0, featcount)) all_centroids = {} P = 0 for feat in layer.getFeatures(): P += 1 self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, int(P))) self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Loading Layer Features: " + str(P) + "/" + str(featcount))) geom = feat.geometry() if geom is not None: point = list(geom.centroid().asPoint()) centroid_id = feat.attributes()[idx] all_centroids[centroid_id] = point if centroid_id not in self.matrix_hash.keys(): self.matrix_hash[centroid_id] = matrix_nodes matrix_nodes += 1 reverse_hash = {v: k for k, v in self.matrix_hash.iteritems()} #Creating resulting layer EPSG_code = int(layer.crs().authid().split(":")[1]) desireline_layer = QgsVectorLayer( "LineString?crs=epsg:" + str(EPSG_code), self.dl_type, "memory") dlpr = desireline_layer.dataProvider() dlpr.addAttributes([ QgsField("link_id", QVariant.Int), QgsField("A_Node", QVariant.Int), QgsField("B_Node", QVariant.Int), QgsField("direct", QVariant.Int), QgsField("length", QVariant.Double), QgsField("ab_flow", QVariant.Double), QgsField("ba_flow", QVariant.Double), QgsField("tot_flow", QVariant.Double) ]) desireline_layer.updateFields() if self.dl_type == "DesireLines": self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Creating Desire Lines")) self.emit(SIGNAL("ProgressMaxValue(PyQt_PyObject)"), (0, self.matrix.shape[0] * self.matrix.shape[1] / 2)) desireline_link_id = 1 q = 0 all_features = [] for i in range(self.matrix.shape[0]): if np.sum(self.matrix[i, :]) > 0: a_node = reverse_hash[i] for j in xrange(i + 1, self.matrix.shape[1]): q += 1 b_node = reverse_hash[j] self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, q)) if self.matrix[i, j] + self.matrix[j, i] > 0: if a_node in all_centroids.keys( ) and b_node in all_centroids.keys(): a_point = all_centroids[a_node] a_point = QgsPoint(a_point[0], a_point[1]) b_point = all_centroids[b_node] b_point = QgsPoint(b_point[0], b_point[1]) dist = QgsGeometry().fromPoint( a_point).distance( QgsGeometry().fromPoint(b_point)) feature = QgsFeature() feature.setGeometry( QgsGeometry.fromPolyline( [a_point, b_point])) feature.setAttributes([ desireline_link_id, int(a_node), int(b_node), 0, dist, float(self.matrix[i, j]), float(self.matrix[j, i]), float(self.matrix[i, j] + self.matrix[j, i]) ]) all_features.append(feature) desireline_link_id += 1 else: tu = (a_node, b_node, self.matrix[i, j], self.matrix[j, i]) self.report.append( 'No centroids available to depict flow between node {0} and node {1}. AB flow was equal to {2} and BA flow was equal to {3}' .format(*tu)) else: q += self.matrix.shape[1] self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, q)) if desireline_link_id > 1: a = dlpr.addFeatures(all_features) self.result_layer = desireline_layer else: self.error = 'Nothing to show' elif self.dl_type == "DelaunayLines": self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Computing Delaunay Triangles")) points = [] seccond_relation = {} i = 0 for k, v in all_centroids.iteritems(): points.append(v) seccond_relation[i] = k i += 1 tri = Delaunay(np.array(points)) #We process all the triangles to only get each edge once self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Building Delaunay Network: Collecting Edges")) edges = [] if self.python_version == 32: all_edges = tri.vertices else: all_edges = tri.simplices for triangle in all_edges: links = list(itertools.combinations(triangle, 2)) for i in links: l = [min(i[0], i[1]), max(i[0], i[1])] if l not in edges: edges.append(l) #Writing Delaunay layer self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Building Delaunay Network: Assembling Layer")) desireline_link_id = 1 data = [] dl_link_ids = {} for edge in edges: a_node = seccond_relation[edge[0]] a_point = all_centroids[a_node] a_point = QgsPoint(a_point[0], a_point[1]) b_node = seccond_relation[edge[1]] b_point = all_centroids[b_node] b_point = QgsPoint(b_point[0], b_point[1]) dist = QgsGeometry().fromPoint(a_point).distance( QgsGeometry().fromPoint(b_point)) line = [] line.append(desireline_link_id) line.append(self.matrix_hash[a_node]) line.append(self.matrix_hash[b_node]) line.append(dist) line.append(dist) line.append(0) data.append(line) if a_node not in dl_link_ids.keys(): dl_link_ids[a_node] = {} dl_link_ids[a_node][b_node] = desireline_link_id desireline_link_id += 1 self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Building graph")) network = np.asarray(data) del data #types for the network all_types = [ np.int64, np.int64, np.int64, np.float64, np.float64, np.int64 ] all_titles = [ 'link_id', 'a_node', 'b_node', 'length_ab', 'length_ba', 'direction' ] dt = [(t, d) for t, d in zip(all_titles, all_types)] self.graph = Graph() self.graph.network = np.zeros(network.shape[0], dtype=dt) for k, t in enumerate(dt): self.graph.network[t[0]] = network[:, k].astype(t[1]) del network self.graph.type_loaded = 'NETWORK' self.graph.status = 'OK' self.graph.network_ok = True self.graph.prepare_graph() self.graph.set_graph(matrix_nodes, cost_field='length', block_centroid_flows=False) self.results = AssignmentResults() self.results.prepare(self.graph) # self.results.set_cores(1) self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Assigning demand")) # Do the assignment #self.all_or_nothing(self.matrix, self.graph, self.results) self.report = all_or_nothing(self.matrix, self.graph, self.results) self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Collecting results")) f = self.results.link_loads link_loads = np.zeros((f.shape[0] + 1, 2)) self.emit(SIGNAL("ProgressMaxValue(PyQt_PyObject)"), (0, f.shape[0] - 1)) for i in range(f.shape[0] - 1): self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, i)) direction = self.graph.graph['direction'][i] link_id = self.graph.graph['link_id'][i] flow = f[i] if direction == 1: link_loads[link_id, 0] = flow else: link_loads[link_id, 1] = flow self.emit(SIGNAL("ProgressText (PyQt_PyObject)"), (0, "Building resulting layer")) features = [] max_edges = len(edges) self.emit(SIGNAL("ProgressMaxValue(PyQt_PyObject)"), (0, max_edges)) for i, edge in enumerate(edges): self.emit(SIGNAL("ProgressValue(PyQt_PyObject)"), (0, i)) a_node = seccond_relation[edge[0]] a_point = all_centroids[a_node] a_point = QgsPoint(a_point[0], a_point[1]) b_node = seccond_relation[edge[1]] b_point = all_centroids[b_node] b_point = QgsPoint(b_point[0], b_point[1]) dist = QgsGeometry().fromPoint(a_point).distance( QgsGeometry().fromPoint(b_point)) feature = QgsFeature() feature.setGeometry( QgsGeometry.fromPolyline([a_point, b_point])) desireline_link_id = dl_link_ids[a_node][b_node] feature.setAttributes([ desireline_link_id, a_node, b_node, 0, dist, float(link_loads[desireline_link_id, 0]), float(link_loads[desireline_link_id, 1]), float(link_loads[desireline_link_id, 0] + link_loads[desireline_link_id, 1]) ]) features.append(feature) a = dlpr.addFeatures(features) self.result_layer = desireline_layer self.emit(SIGNAL("finished_threaded_procedure( PyQt_PyObject )"), True)