editing tests, plant provider and plant

field_friend/automations/plant.py

@@ -1,4 +1,3 @@
-import uuid
 from collections import deque
 from dataclasses import dataclass, field
 from typing import Optional

field_friend/automations/plant_provider.py

@@ -3,7 +3,7 @@
 
 import rosys
 from nicegui import ui
-from rosys.geometry import Point
+from rosys.geometry import Point3d
 
 from .plant import Plant
 
@@ -129,18 +129,18 @@ def _add_crop_prediction(self, plant: Plant) -> None:
         crop_1 = sorted_crops[0]
         crop_2 = sorted_crops[1]
 
-        yaw = crop_2.position.direction(crop_1.position)
-        prediction = crop_1.position.polar(self.crop_spacing, yaw)
+        yaw = crop_2.position.projection().direction(crop_1.position.projection())
+        prediction = crop_1.position.projection().polar(self.crop_spacing, yaw)
 
-        if plant.position.distance(prediction) > self.match_distance:
+        if plant.position.projection().distance(prediction) > self.match_distance:
             return
-        plant.positions.append(prediction)
+        plant.positions.append(Point3d.from_point(prediction, 0))
         plant.confidences.append(self.prediction_confidence)
 
-    def get_relevant_crops(self, point: Point, *, max_distance=0.5) -> list[Plant]:
+    def get_relevant_crops(self, point: Point3d, *, max_distance=0.5) -> list[Plant]:
         return [c for c in self.crops if c.position.distance(point) <= max_distance and c.confidence >= self.minimum_combined_crop_confidence]
 
-    def get_relevant_weeds(self, point: Point, *, max_distance=0.5) -> list[Plant]:
+    def get_relevant_weeds(self, point: Point3d, *, max_distance=0.5) -> list[Plant]:
         return [w for w in self.weeds if w.position.distance(point) <= max_distance and w.confidence >= self.minimum_combined_weed_confidence]
 
     def settings_ui(self) -> None:

tests/test_plant_provider.py

@@ -7,20 +7,20 @@ def test_extracting_relevant_crops():
     plants = PlantProvider()
     for i in range(20):
         plants.add_crop(create_crop(i/10.0, 0))
-    crops = plants.get_relevant_crops(rosys.geometry.Point(x=1.0, y=0), max_distance=0.45)
+    crops = plants.get_relevant_crops(rosys.geometry.Point3d(x=1.0, y=0, z=0), max_distance=0.45)
     assert len(crops) == 9
     # TODO do not clear list; better to use weighted average in confidence property
     plants.crops[10].confidences.clear()
     plants.crops[10].confidences.append(0.4)
-    crops = plants.get_relevant_crops(rosys.geometry.Point(x=1.0, y=0), max_distance=0.45)
+    crops = plants.get_relevant_crops(rosys.geometry.Point3d(x=1.0, y=0, z=0), max_distance=0.45)
     assert len(crops) == 8, 'crops with a confidence of less than PlantProvider.MINIMUM_COMBINED_CROP_CONFIDENCE should be ignored'
 
 
 def create_crop(x: float, y: float) -> Plant:
     """Creates a maize plant with three observed positions at the given coordinates."""
     plant = Plant(type='maize', detection_time=rosys.time())
     for _ in range(3):
-        plant.positions.append(rosys.geometry.Point(x=x, y=y))
+        plant.positions.append(rosys.geometry.Point3d(x=x, y=y, z=0))
         plant.confidences.append(0.9)
     return plant
 
@@ -32,7 +32,7 @@ def test_crop_prediction():
 
     def add_crop(x):
         plant = Plant(type='maize', detection_time=rosys.time())
-        plant.positions.append(rosys.geometry.Point(x=x, y=0))
+        plant.positions.append(rosys.geometry.Point3d(x=x, y=0, z=0))
         plant.confidences.append(confidence)
         plant_provider.add_crop(plant)