refactor: typing

armour/ArmourGoal.py

@@ -8,8 +8,8 @@
 import numpy as np
 from trimesh import Trimesh
 from typing import OrderedDict
-from nptyping import NDArray
 from math import pi
+from rtd.util.mixins.Typings import Matnp
 
 # define top level module logger
 import logging
@@ -79,7 +79,7 @@ def reset(self, **options):
     def create_plot_data(self, time: float = None) -> list[Actor]:
         # generate mesh
         config = self.goal_position
-        fk: OrderedDict[Trimesh, NDArray] = self.arm_agent.info.robot.visual_trimesh_fk(cfg=config)
+        fk: OrderedDict[Trimesh, Matnp] = self.arm_agent.info.robot.visual_trimesh_fk(cfg=config)
         meshes = [mesh.copy().apply_transform(transform) for mesh, transform in fk.items()]
 
         self.plot_data: list[Actor] = list()

armour/agent/ArmourAgentCollision.py

@@ -3,7 +3,7 @@
 from armour.agent import ArmourAgentInfo, ArmourAgentState
 import numpy as np
 from collections import OrderedDict
-from nptyping import NDArray
+from rtd.util.mixins.Typings import Matnp
 
 
 
@@ -25,7 +25,7 @@ def reset(self):
         pass
 
 
-    def getCollisionObject(self, q: NDArray = None, time: float = None) -> CollisionObject:
+    def getCollisionObject(self, q: Matnp = None, time: float = None) -> CollisionObject:
         '''
         Generates a CollisionObject for a given time `time` or
         configuration `q` (only one or none must be provided)
@@ -36,7 +36,7 @@ def getCollisionObject(self, q: NDArray = None, time: float = None) -> Collision
         elif time is not None and q is None:
             config = self.arm_state.get_state(np.array([time])).position   # position at given time
 
-        fk: OrderedDict[Trimesh, NDArray] = self.arm_info.robot.collision_trimesh_fk(cfg=config)
+        fk: OrderedDict[Trimesh, Matnp] = self.arm_info.robot.collision_trimesh_fk(cfg=config)
         meshes = [mesh.copy().apply_transform(transform) for mesh, transform in fk.items()]
         return CollisionObject(meshes, id(self.arm_info))
 

armour/agent/ArmourAgentVisual.py

@@ -6,8 +6,7 @@
 import numpy as np
 from trimesh import Trimesh
 from typing import OrderedDict
-from nptyping import NDArray
-
+from rtd.util.mixins.Typings import Matnp
 
 
 class ArmourAgentVisual(PyvistaVisualObject, Options):
@@ -56,7 +55,7 @@ def create_plot_data(self, time: float = None) -> list[Actor]:
 
         # generate mesh
         config = self.arm_state.get_state(np.array([time])).position
-        fk: OrderedDict[Trimesh, NDArray] = self.arm_info.robot.visual_trimesh_fk(cfg=config)
+        fk: OrderedDict[Trimesh, Matnp] = self.arm_info.robot.visual_trimesh_fk(cfg=config)
         meshes = [mesh.copy().apply_transform(transform) for mesh, transform in fk.items()]
 
         self.plot_data: list[Actor] = list()
@@ -87,7 +86,7 @@ def plot(self, time: float = None):
 
         # generate mesh
         config = self.arm_state.get_state(np.array([time])).position
-        fk: OrderedDict[Trimesh, NDArray] = self.arm_info.robot.visual_trimesh_fk(cfg=config)
+        fk: OrderedDict[Trimesh, Matnp] = self.arm_info.robot.visual_trimesh_fk(cfg=config)
         meshes = [mesh.copy().apply_transform(transform) for mesh, transform in fk.items()]
 
         for actor, mesh in zip(self.plot_data, meshes):

armour/agent/ArmourIdealController.py

@@ -5,7 +5,6 @@
 from armour.agent import ArmourAgentInfo, ArmourAgentState
 from armour.trajectory import ZeroHoldArmTrajectory
 import numpy as np
-from nptyping import NDArray
 
 # define top level module logger
 import logging

armour/legacy/StraightLineHLP.py

@@ -1,22 +1,22 @@
 from armour.agent import ArmourAgentInfo
-from nptyping import NDArray
 import numpy as np
+from rtd.util.mixins.Typings import Vecnp
 
 
 
 class StraightLineHLP():
     def __init__(self):
         self.default_lookahead_distance: float = 1
-        self.goal: NDArray = None
-        self.joint_state_indices: NDArray = None
+        self.goal: Vecnp = None
+        self.joint_state_indices: Vecnp = None
 
 
     def setup(self, agent_info: ArmourAgentInfo, world_info: dict):
         self.goal = world_info["goal"]
         self.arm_joint_state_indices = agent_info.joint_state_indices
 
 
-    def get_waypoint(self, state: NDArray, lookahead_distance: float = None):
+    def get_waypoint(self, state: Vecnp, lookahead_distance: float = None) -> Vecnp:
         if lookahead_distance is None:
             lookahead_distance = self.default_lookahead_distance
         q_cur = state[self.arm_joint_state_indices]

armour/legacy/bernstein_to_poly.py

@@ -1,9 +1,10 @@
 from math import comb
 import numpy as np
+from rtd.util.mixins.Typings import Vec, Vecnp
 
 
 
-def bernstein_to_poly(beta: list[float], n: int):
+def bernstein_to_poly(beta: Vec, n: int) -> Vecnp:
     '''
     converts bernstein polynomial coefficients to
     monomial coefficients

armour/legacy/match_deg5_bernstein_coefficients.py

@@ -1,4 +1,8 @@
-def match_deg5_bernstein_coefficients(traj_constraints: list[float], T: float = 1):
+from rtd.util.mixins.Typings import Vec
+
+
+
+def match_deg5_bernstein_coefficients(traj_constraints: Vec, T: float = 1) -> Vec:
     '''
     match coefficients to initial position, velocity, acceleration (t=0)
     and final position, velocity, and acceleration (t=1)

armour/trajectory/ArmTrajectoryFactory.py

@@ -4,10 +4,7 @@
 from rtd.planner.trajopt import TrajOptProps
 from armour.reachsets import JRSInstance
 from armour.trajectory import PiecewiseArmTrajectory, ZeroHoldArmTrajectory, BernsteinArmTrajectory
-from nptyping import NDArray, Shape, Float64
-
-# type hinting
-RowVec = NDArray[Shape['N'], Float64]
+from rtd.util.mixins.Typings import Vecnp
 
 
 
@@ -21,7 +18,7 @@ def __init__(self, trajOptProps: TrajOptProps, traj_type: str = "piecewise"):
 
 
     def createTrajectory(self, robotState: EntityState, rsInstances: dict[str, ReachSetInstance] = None,
-                         trajectoryParams: RowVec = None, jrsInstance: JRSInstance = None,
+                         trajectoryParams: Vecnp = None, jrsInstance: JRSInstance = None,
                          traj_type: str = None) -> ZeroHoldArmTrajectory | PiecewiseArmTrajectory | BernsteinArmTrajectory:
         '''
         Create a new trajectory object for the given state

armour/trajectory/BernsteinArmTrajectory.py

@@ -5,10 +5,7 @@
 from armour.reachsets import JRSInstance
 from armour.legacy import bernstein_to_poly, match_deg5_bernstein_coefficients
 import numpy as np
-from nptyping import NDArray, Shape, Float64
-
-# type hinting
-RowVec = NDArray[Shape['N'], Float64]
+from rtd.util.mixins.Typings import Vecnp
 
 
 
@@ -31,7 +28,7 @@ def __init__(self, trajOptProps: TrajOptProps, startState: ArmRobotState, jrsIns
         self.jrsInstance = jrsInstance
 
 
-    def setParameters(self, trajectoryParams: RowVec, startState: ArmRobotState = None,
+    def setParameters(self, trajectoryParams: Vecnp, startState: ArmRobotState = None,
                       jrsInstance: JRSInstance = None):
         '''
         A validated method to set the parameters for the trajectory
@@ -97,7 +94,7 @@ def internalUpdate(self):
         self.q_end = q_goal
 
 
-    def getCommand(self, time: RowVec) -> EntityState:
+    def getCommand(self, time: Vecnp) -> EntityState:
         # Do a parameter check and time check, and throw if anything is
         # invalid.
         self.validate(throwOnError=True)

armour/trajectory/PieceWiseArmTrajectory.py

@@ -4,10 +4,7 @@
 from armour.reachsets import JRSInstance
 from rtd.functional.vectools import rescale
 import numpy as np
-from nptyping import NDArray, Shape, Float64
-
-# type hinting
-RowVec = NDArray[Shape['N'], Float64]
+from rtd.util.mixins.Typings import Vec, Mat, Vecnp, Matnp, Bound, Bounds, Boundsnp
 
 
 
@@ -38,7 +35,7 @@ class to update all other internal parameters once fully
         self.q_end: float = None
 
 
-    def setParameters(self, trajectoryParams: RowVec, startState: ArmRobotState = None,
+    def setParameters(self, trajectoryParams: Vecnp, startState: ArmRobotState = None,
                       jrsInstance: JRSInstance = None):
         '''
         Set the parameters of the trajectory, with a focus on the
@@ -97,7 +94,7 @@ def internalUpdate(self):
                       + 0.5*self.q_ddot_to_stop*self.trajOptProps.planTime**2)
 
 
-    def getCommand(self, time: RowVec) -> ArmRobotState:
+    def getCommand(self, time: Vecnp) -> ArmRobotState:
         '''
         Computes the actual input commands for the given time.
         throws InvalidTrajectory if the trajectory isn't set

armour/trajectory/ZeroHoldArmTrajectory.py

@@ -1,10 +1,7 @@
 from rtd.planner.trajectory import Trajectory, InvalidTrajectory
 from rtd.entity.states import ArmRobotState
 import numpy as np
-from nptyping import NDArray, Shape, Float64
-
-# type hinting
-RowVec = NDArray[Shape['N'], Float64]
+from rtd.util.mixins.Typings import Vecnp
 
 
 
@@ -23,7 +20,7 @@ class to update all other internal parameters once fully
         self.startState = startState
 
 
-    def setParameters(self, trajectoryParams: RowVec, startState: ArmRobotState = None):
+    def setParameters(self, trajectoryParams: Vecnp, startState: ArmRobotState = None):
         '''
         Set the parameters of the trajectory, with a focus on the
         parameters as the state should be set from the constructor
@@ -46,7 +43,7 @@ def validate(self, throwOnError: bool = False) -> bool:
         return valid
 
 
-    def getCommand(self, time: RowVec) -> ArmRobotState:
+    def getCommand(self, time: Vecnp) -> ArmRobotState:
         '''
         Computes the actual input commands for the given time.
         throws InvalidTrajectory if the trajectory isn't set

rtd/planner/reachsets/ReachSetInstance.py

@@ -1,10 +1,7 @@
 from abc import ABCMeta, abstractmethod
 from rtd.sim.world import WorldState
 from typing import Callable
-from nptyping import NDArray, Shape, Float64
-
-# type hinting
-BoundsVec = NDArray[Shape['N,2'], Float64]
+from rtd.util.mixins.Typings import Boundsnp
 
 
 
@@ -21,7 +18,7 @@ class ReachSetInstance(metaclass=ABCMeta):
     def __init__(self):
         # A 2-column vector denoting the input minimum and maximums for the
         # reachable set on the left and right, respectively
-        self.input_range: BoundsVec = None
+        self.input_range: Boundsnp = None
 
         # The number of main shared parameters used by this set. Generally,
         # this should match the size of the final trajectory parameters

rtd/planner/trajectory/Trajectory.py

@@ -1,10 +1,7 @@
 from abc import ABCMeta, abstractmethod
 from rtd.entity.states import EntityState
 from rtd.planner.trajopt import TrajOptProps
-from nptyping import NDArray, Shape, Float64
-
-# type hinting
-RowVec = NDArray[Shape['N'], Float64]
+from rtd.util.mixins.Typings import Vecnp
 
 
 
@@ -23,7 +20,7 @@ def __init__(self):
         self.trajOptProps: TrajOptProps = None
 
         # The parameters used for this trajectory
-        self.trajectoryParams: RowVec = None
+        self.trajectoryParams: Vecnp = None
 
         # The time at which this trajectory is valid
         self.startTime: float = None
@@ -52,7 +49,7 @@ def validate(self, throwOnError: bool = False) -> bool:
 
 
     @abstractmethod
-    def setParameters(self, trajectoryParams: RowVec, **options):
+    def setParameters(self, trajectoryParams: Vecnp, **options):
         '''
         Set the parameters for the trajectory
         
@@ -67,7 +64,7 @@ def setParameters(self, trajectoryParams: RowVec, **options):
 
 
     @abstractmethod
-    def getCommand(self, time: float | RowVec) -> EntityState:
+    def getCommand(self, time: float | Vecnp) -> EntityState:
         '''
         Computes the actual state to track for the given time
         

rtd/planner/trajectory/TrajectoryContainer.py

@@ -2,7 +2,6 @@
 from rtd.entity.states import EntityState
 from rtd.functional.sequences import toSequence
 import numpy as np
-from nptyping import NDArray
 
 
 class BadTrajectoryException(Exception):

rtd/planner/trajectory/TrajectoryFactory.py

@@ -3,10 +3,7 @@
 from rtd.planner.trajopt import TrajOptProps
 from rtd.planner.trajectory import Trajectory
 from rtd.planner.reachsets import ReachSetInstance
-from nptyping import NDArray, Shape, Float64
-
-# type hinting
-RowVec = NDArray[Shape['N'], Float64]
+from rtd.util.mixins.Typings import Vecnp
 
 
 
@@ -25,7 +22,7 @@ def __init__(self):
 
     @abstractmethod
     def createTrajectory(self, robotState: EntityState, rsInstances: dict[str, ReachSetInstance] = None,
-                         trajectoryParams: RowVec = None, **options) -> Trajectory:
+                         trajectoryParams: Vecnp = None, **options) -> Trajectory:
         '''
         Factory method to create the trajectory
         

rtd/planner/trajopt/GenericArmObjective.py

@@ -4,10 +4,7 @@
 from rtd.planner.trajopt import Objective, TrajOptProps
 from rtd.planner.trajectory import TrajectoryFactory, Trajectory
 import numpy as np
-from nptyping import NDArray, Shape, Float64
-
-# type hinting
-RowVec = NDArray[Shape['N'], Float64]
+from rtd.util.mixins.Typings import Vecnp
 
 
 
@@ -43,7 +40,7 @@ def genObjective(self, robotState: EntityState, waypoint, reachableSets: dict[st
 
 
     @staticmethod
-    def evalTrajectory(trajectoryParams: RowVec, trajectoryObj: Trajectory, q_des, t_cost: float | RowVec) -> float:
+    def evalTrajectory(trajectoryParams: Vecnp, trajectoryObj: Trajectory, q_des, t_cost: float | Vecnp) -> float:
         '''
         Helper function purely accessible to this class without any class state
         which a handle can be made to to evaluate the trajectory for the cost.

rtd/planner/trajopt/OptimizationEngine.py

@@ -1,9 +1,6 @@
 from abc import ABCMeta, abstractmethod
 from typing import Callable
-from nptyping import NDArray, Shape, Float64
-
-# type hinting
-RowVec = NDArray[Shape['N'], Float64]
+from rtd.util.mixins.Typings import Vecnp
 
 
 
@@ -12,8 +9,8 @@ class OptimizationEngine(metaclass=ABCMeta):
     Base class for any sort of nonlinear optimizer used
     '''
     @abstractmethod
-    def performOptimization(self, initialGuess: RowVec, objectiveCallback: Callable,
-            constraintCallback: Callable, bounds: dict) -> tuple[bool, RowVec, float]:
+    def performOptimization(self, initialGuess: Vecnp, objectiveCallback: Callable,
+            constraintCallback: Callable, bounds: dict) -> tuple[bool, Vecnp, float]:
         '''
         Use the given optimizer to perform the optimization
         RowVector