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Methode für STR Tree mit Bounding Box hinzugefügt.

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lertlmaier
2025-05-26 13:33:15 +02:00
parent b5c1a5f38c
commit e347794373
1 changed files with 69 additions and 45 deletions
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lib/plant.py
+69 -45
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@@ -1,5 +1,5 @@
import json
from shapely.geometry import LineString, Point
from shapely.geometry import LineString, Point, box
from shapely.ops import nearest_points
import unittest
from collections import defaultdict
@@ -9,7 +9,7 @@ import matplotlib.pyplot as plt
from itertools import pairwise, combinations, permutations
import re
from shapely.strtree import STRtree
import shapely
class PointSorter:
def __init__(self):
@@ -442,6 +442,32 @@ class Anlage():
nearest_point = nearest_line.interpolate(nearest_line.project(sensor))
return(nearest_point, rack_name)
def find_nearest_rack_from_point_STR_bbox(self, max_dist, sensor:Point) -> tuple[Point, str]:
if not hasattr(self, "_rack_tree"):
self._build_rack_strtree()
minx, miny, maxx, maxy = sensor.x - max_dist, sensor.y - max_dist, sensor.x + max_dist, sensor.y + max_dist
bbox = box(minx, miny, maxx, maxy)
candidates = self._rack_tree.query(box)
if not candidates:
return None, None
for line in candidates:
dist = sensor.distance(line)
if dist < best_dist:
best_dist = dist
best_line = line
if best_dist > max_dist:
return None, None
rack_name = self._rack_map[best_line]
nearest_point = best_line.interpolate(best_line.project(sensor))
return nearest_point, rack_name
def connect_equipment_to_racks(self, equipment: dict, onpoints: dict) -> list:
'''Verbindet Peripherie (Sensoren / Aktoren/ Unterverteiler) mit dem nächsten Rack.
Eingabe: Dict des Equipments (Sensoren o. Dists), Dict der Aufpunkte von Sensoren o. Dists
@@ -449,7 +475,7 @@ class Anlage():
'''
errors = []
for name, pos in equipment.items():
onpoint, rackname = self.find_nearest_rack_from_point_tree(self._tol_connect, pos)
onpoint, rackname = self.find_nearest_rack_from_point_STR_bbox(self._tol_connect, pos)
if onpoint == None or rackname == None:
errors.append((name, pos))
continue
@@ -496,9 +522,6 @@ class Anlage():
return errors
def find_nearest_rack_from_point(self, max_dist, coarse_step, sensor:Point, racks:dict) -> tuple[Point, str]:
# 1. grobe Kandidatensuche
@@ -840,7 +863,37 @@ class TestLinesweep(unittest.TestCase):
# self.assertEqual(plist2, [Point(0, 0), Point(0,1), Point(0, 10)])
# def test_add_equipment_w_tree(self):
def test_add_equipment_w_tree(self):
racks = {'Rack_1': [Point(0, 0), Point(0, 10)],
'Rack_2': [Point(10, -2), Point(10, 5)],
'Rack_3': [Point(0, 3), Point(10, 3)]}
sensors = {'Sens_1': Point(1, 1),
'Sens_2': Point(2, 4),
'Sens_3': Point(9, 2)}
distributors = {'Dist_1': Point(-1, 9),
'Dist_2': Point(11, 0)}
an = Anlage(tol_snap=1.5)
an.set_racks(racks)
an.join_racks()
an.add_sensors(sensors)
an.add_distributors(distributors)
an.connect_equipment_to_racks(an._sensors, an._sensor_onpoints)
an.connect_equipment_to_racks(an._distributors, an._distributors_onpoints)
plist1 = an.get_points_from_rack("Rack_1")
plist2 = an.get_points_from_rack("Rack_2")
self.assertEqual(plist1, [Point(0, 0), Point(0, 1), Point(0, 3), Point(0, 9), Point(0, 10)])
self.assertEqual(plist2, [Point(10, -2), Point(10, 0), Point(10, 2), Point(10, 3), Point(10, 5)])
# def test_add_equipment_w_tree_batch(self):
# racks = {'Rack_1': [Point(0, 0), Point(0, 10)],
# 'Rack_2': [Point(10, -2), Point(10, 5)],
@@ -859,51 +912,22 @@ class TestLinesweep(unittest.TestCase):
# an.add_sensors(sensors)
# an.add_distributors(distributors)
# an.connect_equipment_to_racks(an._sensors, an._sensor_onpoints)
# an.connect_equipment_to_racks(an._distributors, an._distributors_onpoints)
# an.connect_equipment_batch(an._sensors, an._sensor_onpoints)
# an.connect_equipment_batch(an._distributors, an._distributors_onpoints)
# plist1 = an.get_points_from_rack("Rack_1")
# plist2 = an.get_points_from_rack("Rack_2")
# G1 = nx.Graph()
# pos = an.generate_graph(G1)
# nx.draw(G1, pos, with_labels=False, node_size=10, font_size=8)
# plt.show()
# self.assertEqual(plist1, [Point(0, 0), Point(0, 1), Point(0, 3), Point(0, 9), Point(0, 10)])
# self.assertEqual(plist2, [Point(10, -2), Point(10, 0), Point(10, 2), Point(10, 3), Point(10, 5)])
def test_add_equipment_w_tree_batch(self):
racks = {'Rack_1': [Point(0, 0), Point(0, 10)],
'Rack_2': [Point(10, -2), Point(10, 5)],
'Rack_3': [Point(0, 3), Point(10, 3)]}
sensors = {'Sens_1': Point(1, 1),
'Sens_2': Point(2, 4),
'Sens_3': Point(9, 2)}
distributors = {'Dist_1': Point(-1, 9),
'Dist_2': Point(11, 0)}
an = Anlage(tol_snap=1)
an.set_racks(racks)
an.join_racks()
an.add_sensors(sensors)
an.add_distributors(distributors)
an.connect_equipment_batch(an._sensors, an._sensor_onpoints)
an.connect_equipment_batch(an._distributors, an._distributors_onpoints)
plist1 = an.get_points_from_rack("Rack_1")
plist2 = an.get_points_from_rack("Rack_2")
G1 = nx.Graph()
pos = an.generate_graph(G1)
nx.draw(G1, pos, with_labels=False, node_size=10, font_size=8)
plt.show()
self.assertEqual(plist1, [Point(0, 0), Point(0, 1), Point(0, 3), Point(0, 9), Point(0, 10)])
self.assertEqual(plist2, [Point(10, -2), Point(10, 0), Point(10, 2), Point(10, 3), Point(10, 5)])
# def test_wegsuche_w_tree(self):
# racks = {'Rack_1-0': [Point(0, 0), Point(0, 10)],