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deprecated_utils

A set of utility functions slated to be deprecated once Omniverse bugs are fixed

ArticulationView

Bases: ArticulationView

ArticulationView with some additional functionality implemented.

Source code in omnigibson/utils/deprecated_utils.py 
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class ArticulationView(_ArticulationView):
    """ArticulationView with some additional functionality implemented."""

    def set_joint_limits(
        self,
        values: Union[np.ndarray, torch.Tensor],
        indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
        joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    ) -> None:
        """Sets joint limits for articulation joints in the view.

        Args:
            values (Union[np.ndarray, torch.Tensor, wp.array]): joint limits for articulations in the view. shape (M, K, 2).
            indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                                 to manipulate. Shape (M,).
                                                                                 Where M <= size of the encapsulated prims in the view.
                                                                                 Defaults to None (i.e: all prims in the view).
            joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indicies to specify which joints
                                                                                 to manipulate. Shape (K,).
                                                                                 Where K <= num of dofs.
                                                                                 Defaults to None (i.e: all dofs).
        """
        if not self._is_initialized:
            carb.log_warn("ArticulationView needs to be initialized.")
            return
        if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
            indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, "cpu")
            new_values = self._physics_view.get_dof_limits()
            values = self._backend_utils.move_data(values, device="cpu")
            new_values = self._backend_utils.assign(
                values,
                new_values,
                [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
            )
            self._physics_view.set_dof_limits(new_values, indices)
        else:
            indices = self._backend_utils.to_list(
                self._backend_utils.resolve_indices(indices, self.count, self._device)
            )
            dof_types = self._backend_utils.to_list(self.get_dof_types())
            joint_indices = self._backend_utils.to_list(
                self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
            )
            values = self._backend_utils.to_list(values)
            articulation_read_idx = 0
            for i in indices:
                dof_read_idx = 0
                for dof_index in joint_indices:
                    dof_val = values[articulation_read_idx][dof_read_idx]
                    if dof_types[dof_index] == omni.physics.tensors.DofType.Rotation:
                        dof_val /= DEG2RAD
                    prim = get_prim_at_path(self._dof_paths[i][dof_index])
                    prim.GetAttribute("physics:lowerLimit").Set(dof_val[0])
                    prim.GetAttribute("physics:upperLimit").Set(dof_val[1])
                    dof_read_idx += 1
                articulation_read_idx += 1
        return

    def get_joint_limits(
        self,
        indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
        joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
        clone: bool = True,
    ) -> Union[np.ndarray, torch.Tensor, wp.array]:
        """Gets joint limits for articulation in the view.

        Args:
            indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                                 to query. Shape (M,).
                                                                                 Where M <= size of the encapsulated prims in the view.
                                                                                 Defaults to None (i.e: all prims in the view).
            joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indicies to specify which joints
                                                                                 to query. Shape (K,).
                                                                                 Where K <= num of dofs.
                                                                                 Defaults to None (i.e: all dofs).
            clone (Optional[bool]): True to return a clone of the internal buffer. Otherwise False. Defaults to True.

        Returns:
            Union[np.ndarray, torch.Tensor, wp.indexedarray]: joint limits for articulations in the view. shape (M, K).
        """
        if not self._is_initialized:
            carb.log_warn("ArticulationView needs to be initialized.")
            return None
        if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
            indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
            values = self._backend_utils.move_data(self._physics_view.get_dof_limits(), self._device)
            if clone:
                values = self._backend_utils.clone_tensor(values, device=self._device)
            result = values[
                self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices
            ]
            return result
        else:
            indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
            dof_types = self._backend_utils.to_list(self.get_dof_types())
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
            values = np.zeros(shape=(indices.shape[0], joint_indices.shape[0], 2), dtype="float32")
            articulation_write_idx = 0
            indices = self._backend_utils.to_list(indices)
            joint_indices = self._backend_utils.to_list(joint_indices)
            for i in indices:
                dof_write_idx = 0
                for dof_index in joint_indices:
                    prim = get_prim_at_path(self._dof_paths[i][dof_index])
                    values[articulation_write_idx][dof_write_idx][0] = prim.GetAttribute("physics:lowerLimit").Get()
                    values[articulation_write_idx][dof_write_idx][1] = prim.GetAttribute("physics:upperLimit").Get()
                    if dof_types[dof_index] == omni.physics.tensors.DofType.Rotation:
                        values[articulation_write_idx][dof_write_idx] = values[articulation_write_idx][dof_write_idx] * DEG2RAD
                    dof_write_idx += 1
                articulation_write_idx += 1
            values = self._backend_utils.convert(values, dtype="float32", device=self._device, indexed=True)
            return values

    def set_max_velocities(
        self,
        values: Union[np.ndarray, torch.Tensor, wp.array],
        indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
        joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    ) -> None:
        """Sets maximum velocities for articulation in the view.

        Args:
            values (Union[np.ndarray, torch.Tensor, wp.array]): maximum velocities for articulations in the view. shape (M, K).
            indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                                 to manipulate. Shape (M,).
                                                                                 Where M <= size of the encapsulated prims in the view.
                                                                                 Defaults to None (i.e: all prims in the view).
            joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indicies to specify which joints
                                                                                 to manipulate. Shape (K,).
                                                                                 Where K <= num of dofs.
                                                                                 Defaults to None (i.e: all dofs).
        """
        if not self._is_initialized:
            carb.log_warn("ArticulationView needs to be initialized.")
            return
        if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
            indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, "cpu")
            new_values = self._physics_view.get_dof_max_velocities()
            new_values = self._backend_utils.assign(
                self._backend_utils.move_data(values, device="cpu"),
                new_values,
                [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
            )
            self._physics_view.set_dof_max_velocities(new_values, indices)
        else:
            indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
            articulation_read_idx = 0
            indices = self._backend_utils.to_list(indices)
            joint_indices = self._backend_utils.to_list(joint_indices)
            values = self._backend_utils.to_list(values)
            for i in indices:
                dof_read_idx = 0
                for dof_index in joint_indices:
                    prim = PhysxSchema.PhysxJointAPI(get_prim_at_path(self._dof_paths[i][dof_index]))
                    if not prim.GetMaxJointVelocityAttr():
                        prim.CreateMaxJointVelocityAttr().Set(values[articulation_read_idx][dof_read_idx])
                    else:
                        prim.GetMaxJointVelocityAttr().Set(values[articulation_read_idx][dof_read_idx])
                    dof_read_idx += 1
                articulation_read_idx += 1
        return

    def get_max_velocities(
        self,
        indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
        joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
        clone: bool = True,
    ) -> Union[np.ndarray, torch.Tensor, wp.indexedarray]:
        """Gets maximum velocities for articulation in the view.

        Args:
            indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                                 to query. Shape (M,).
                                                                                 Where M <= size of the encapsulated prims in the view.
                                                                                 Defaults to None (i.e: all prims in the view).
            joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indicies to specify which joints
                                                                                 to query. Shape (K,).
                                                                                 Where K <= num of dofs.
                                                                                 Defaults to None (i.e: all dofs).
            clone (Optional[bool]): True to return a clone of the internal buffer. Otherwise False. Defaults to True.

        Returns:
            Union[np.ndarray, torch.Tensor, wp.indexedarray]: maximum velocities for articulations in the view. shape (M, K).
        """
        if not self._is_initialized:
            carb.log_warn("ArticulationView needs to be initialized.")
            return None
        if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
            indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, "cpu")
            max_velocities = self._physics_view.get_dof_max_velocities()
            if clone:
                max_velocities = self._backend_utils.clone_tensor(max_velocities, device="cpu")
            result = self._backend_utils.move_data(
                max_velocities[
                    self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices
                ],
                device=self._device,
            )
            return result
        else:
            indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
            max_velocities = np.zeros(shape=(indices.shape[0], joint_indices.shape[0]), dtype="float32")
            indices = self._backend_utils.to_list(indices)
            joint_indices = self._backend_utils.to_list(joint_indices)
            articulation_write_idx = 0
            for i in indices:
                dof_write_idx = 0
                for dof_index in joint_indices:
                    prim = PhysxSchema.PhysxJointAPI(get_prim_at_path(self._dof_paths[i][dof_index]))
                    max_velocities[articulation_write_idx][dof_write_idx] = prim.GetMaxJointVelocityAttr().Get()
                    dof_write_idx += 1
                articulation_write_idx += 1
            max_velocities = self._backend_utils.convert(max_velocities, dtype="float32", device=self._device, indexed=True)
            return max_velocities

    def set_joint_positions(
        self,
        positions: Optional[Union[np.ndarray, torch.Tensor, wp.array]],
        indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
        joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    ) -> None:
        """Set the joint positions of articulations in the view

        .. warning::

            This method will immediately set (teleport) the affected joints to the indicated value.
            Use the ``set_joint_position_targets`` or the ``apply_action`` methods to control the articulation joints.

        Args:
            positions (Optional[Union[np.ndarray, torch.Tensor, wp.array]]): joint positions of articulations in the view to be set to in the next frame.
                                                                    shape is (M, K).
            indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indices to specify which prims
                                                                                 to manipulate. Shape (M,).
                                                                                 Where M <= size of the encapsulated prims in the view.
                                                                                 Defaults to None (i.e: all prims in the view).
            joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indices to specify which joints
                                                                                 to manipulate. Shape (K,).
                                                                                 Where K <= num of dofs.
                                                                                 Defaults to None (i.e: all dofs).

        .. hint::

            This method belongs to the methods used to set the articulation kinematic states:

            ``set_velocities`` (``set_linear_velocities``, ``set_angular_velocities``),
            ``set_joint_positions``, ``set_joint_velocities``, ``set_joint_efforts``

        Example:

        .. code-block:: python

            >>> # set all the articulation joints.
            >>> # Since there are 5 envs, the joint positions are repeated 5 times
            >>> positions = np.tile(np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04]), (num_envs, 1))
            >>> prims.set_joint_positions(positions)
            >>>
            >>> # set only the fingers in closed position: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 0.0
            >>> # for the first, middle and last of the 5 envs
            >>> positions = np.tile(np.array([0.0, 0.0]), (3, 1))
            >>> prims.set_joint_positions(positions, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
        """
        if not self._is_initialized:
            carb.log_warn("ArticulationView needs to be initialized.")
            return
        if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
            indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
            new_dof_pos = self._physics_view.get_dof_positions()
            new_dof_pos = self._backend_utils.assign(
                self._backend_utils.move_data(positions, device=self._device),
                new_dof_pos,
                [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
            )
            self._physics_view.set_dof_positions(new_dof_pos, indices)

            # THIS IS THE FIX: COMMENT OUT THE BELOW LINE AND SET TARGETS INSTEAD
            # self._physics_view.set_dof_position_targets(new_dof_pos, indices)
            self.set_joint_position_targets(positions, indices, joint_indices)
        else:
            carb.log_warn("Physics Simulation View is not created yet in order to use set_joint_positions")

    def set_joint_velocities(
        self,
        velocities: Optional[Union[np.ndarray, torch.Tensor, wp.array]],
        indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
        joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    ) -> None:
        """Set the joint velocities of articulations in the view

        .. warning::

            This method will immediately set the affected joints to the indicated value.
            Use the ``set_joint_velocity_targets`` or the ``apply_action`` methods to control the articulation joints.

        Args:
            velocities (Optional[Union[np.ndarray, torch.Tensor, wp.array]]): joint velocities of articulations in the view to be set to in the next frame.
                                                                    shape is (M, K).
            indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indices to specify which prims
                                                                                 to manipulate. Shape (M,).
                                                                                 Where M <= size of the encapsulated prims in the view.
                                                                                 Defaults to None (i.e: all prims in the view).
            joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indices to specify which joints
                                                                                 to manipulate. Shape (K,).
                                                                                 Where K <= num of dofs.
                                                                                 Defaults to None (i.e: all dofs).

        .. hint::

            This method belongs to the methods used to set the articulation kinematic states:

            ``set_velocities`` (``set_linear_velocities``, ``set_angular_velocities``),
            ``set_joint_positions``, ``set_joint_velocities``, ``set_joint_efforts``

        Example:

        .. code-block:: python

            >>> # set the velocities for all the articulation joints to the indicated values.
            >>> # Since there are 5 envs, the joint velocities are repeated 5 times
            >>> velocities = np.tile(np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]), (num_envs, 1))
            >>> prims.set_joint_velocities(velocities)
            >>>
            >>> # set the fingers velocities: panda_finger_joint1 (7) and panda_finger_joint2 (8) to -0.1
            >>> # for the first, middle and last of the 5 envs
            >>> velocities = np.tile(np.array([-0.1, -0.1]), (3, 1))
            >>> prims.set_joint_velocities(velocities, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
        """
        if not self._is_initialized:
            carb.log_warn("ArticulationView needs to be initialized.")
            return
        if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
            indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
            new_dof_vel = self._physics_view.get_dof_velocities()
            new_dof_vel = self._backend_utils.assign(
                self._backend_utils.move_data(velocities, device=self._device),
                new_dof_vel,
                [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
            )
            self._physics_view.set_dof_velocities(new_dof_vel, indices)

            # THIS IS THE FIX: COMMENT OUT THE BELOW LINE AND SET TARGETS INSTEAD
            # self._physics_view.set_dof_velocity_targets(new_dof_vel, indices)
            self.set_joint_velocity_targets(velocities, indices, joint_indices)
        else:
            carb.log_warn("Physics Simulation View is not created yet in order to use set_joint_velocities")
        return

    def set_joint_efforts(
        self,
        efforts: Optional[Union[np.ndarray, torch.Tensor, wp.array]],
        indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
        joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    ) -> None:
        """Set the joint efforts of articulations in the view

        .. note::

            This method can be used for effort control. For this purpose, there must be no joint drive
            or the stiffness and damping must be set to zero.

        Args:
            efforts (Optional[Union[np.ndarray, torch.Tensor, wp.array]]): efforts of articulations in the view to be set to in the next frame.
                                                                    shape is (M, K).
            indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indices to specify which prims
                                                                                 to manipulate. Shape (M,).
                                                                                 Where M <= size of the encapsulated prims in the view.
                                                                                 Defaults to None (i.e: all prims in the view).
            joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indices to specify which joints
                                                                                 to manipulate. Shape (K,).
                                                                                 Where K <= num of dofs.
                                                                                 Defaults to None (i.e: all dofs).

        .. hint::

            This method belongs to the methods used to set the articulation kinematic states:

            ``set_velocities`` (``set_linear_velocities``, ``set_angular_velocities``),
            ``set_joint_positions``, ``set_joint_velocities``, ``set_joint_efforts``

        Example:

        .. code-block:: python

            >>> # set the efforts for all the articulation joints to the indicated values.
            >>> # Since there are 5 envs, the joint efforts are repeated 5 times
            >>> efforts = np.tile(np.array([10, 20, 30, 40, 50, 60, 70, 80, 90]), (num_envs, 1))
            >>> prims.set_joint_efforts(efforts)
            >>>
            >>> # set the fingers efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 10
            >>> # for the first, middle and last of the 5 envs
            >>> efforts = np.tile(np.array([10, 10]), (3, 1))
            >>> prims.set_joint_efforts(efforts, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
        """
        if not self._is_initialized:
            carb.log_warn("ArticulationView needs to be initialized.")
            return

        if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
            indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
            joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)

            # THIS IS THE FIX: COMMENT OUT THE BELOW LINE AND USE ACTUATION FORCES INSTEAD
            # new_dof_efforts = self._backend_utils.create_zeros_tensor(
            #     shape=[self.count, self.num_dof], dtype="float32", device=self._device
            # )
            new_dof_efforts = self._physics_view.get_dof_actuation_forces()
            new_dof_efforts = self._backend_utils.assign(
                self._backend_utils.move_data(efforts, device=self._device),
                new_dof_efforts,
                [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
            )
            self._physics_view.set_dof_actuation_forces(new_dof_efforts, indices)
        else:
            carb.log_warn("Physics Simulation View is not created yet in order to use set_joint_efforts")
        return

    def _invalidate_physics_handle_callback(self, event):
        # Overwrite super method, add additional de-initialization
        if event.type == int(omni.timeline.TimelineEventType.STOP):
            self._physics_view = None
            self._invalidate_physics_handle_event = None
            self._is_initialized = False

get_joint_limits(indices=None, joint_indices=None, clone=True)

Gets joint limits for articulation in the view.

Parameters:

Name Type Description Default
indices Optional[Union[ndarray, List, Tensor, array]]

indicies to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).

 None
joint_indices Optional[Union[ndarray, List, Tensor, array]]

joint indicies to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).

 None
clone Optional[bool]

True to return a clone of the internal buffer. Otherwise False. Defaults to True.

 True

Returns:

Type Description
Union[ndarray, Tensor, array]

Union[np.ndarray, torch.Tensor, wp.indexedarray]: joint limits for articulations in the view. shape (M, K).
Source code in omnigibson/utils/deprecated_utils.py 
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def get_joint_limits(
    self,
    indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    clone: bool = True,
) -> Union[np.ndarray, torch.Tensor, wp.array]:
    """Gets joint limits for articulation in the view.

    Args:
        indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                             to query. Shape (M,).
                                                                             Where M <= size of the encapsulated prims in the view.
                                                                             Defaults to None (i.e: all prims in the view).
        joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indicies to specify which joints
                                                                             to query. Shape (K,).
                                                                             Where K <= num of dofs.
                                                                             Defaults to None (i.e: all dofs).
        clone (Optional[bool]): True to return a clone of the internal buffer. Otherwise False. Defaults to True.

    Returns:
        Union[np.ndarray, torch.Tensor, wp.indexedarray]: joint limits for articulations in the view. shape (M, K).
    """
    if not self._is_initialized:
        carb.log_warn("ArticulationView needs to be initialized.")
        return None
    if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
        indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
        values = self._backend_utils.move_data(self._physics_view.get_dof_limits(), self._device)
        if clone:
            values = self._backend_utils.clone_tensor(values, device=self._device)
        result = values[
            self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices
        ]
        return result
    else:
        indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
        dof_types = self._backend_utils.to_list(self.get_dof_types())
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
        values = np.zeros(shape=(indices.shape[0], joint_indices.shape[0], 2), dtype="float32")
        articulation_write_idx = 0
        indices = self._backend_utils.to_list(indices)
        joint_indices = self._backend_utils.to_list(joint_indices)
        for i in indices:
            dof_write_idx = 0
            for dof_index in joint_indices:
                prim = get_prim_at_path(self._dof_paths[i][dof_index])
                values[articulation_write_idx][dof_write_idx][0] = prim.GetAttribute("physics:lowerLimit").Get()
                values[articulation_write_idx][dof_write_idx][1] = prim.GetAttribute("physics:upperLimit").Get()
                if dof_types[dof_index] == omni.physics.tensors.DofType.Rotation:
                    values[articulation_write_idx][dof_write_idx] = values[articulation_write_idx][dof_write_idx] * DEG2RAD
                dof_write_idx += 1
            articulation_write_idx += 1
        values = self._backend_utils.convert(values, dtype="float32", device=self._device, indexed=True)
        return values

get_max_velocities(indices=None, joint_indices=None, clone=True)

Gets maximum velocities for articulation in the view.

Parameters:

Name Type Description Default
indices Optional[Union[ndarray, List, Tensor, array]]

indicies to specify which prims to query. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).

 None
joint_indices Optional[Union[ndarray, List, Tensor, array]]

joint indicies to specify which joints to query. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).

 None
clone Optional[bool]

True to return a clone of the internal buffer. Otherwise False. Defaults to True.

 True

Returns:

Type Description
Union[ndarray, Tensor, indexedarray]

Union[np.ndarray, torch.Tensor, wp.indexedarray]: maximum velocities for articulations in the view. shape (M, K).
Source code in omnigibson/utils/deprecated_utils.py 
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def get_max_velocities(
    self,
    indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    clone: bool = True,
) -> Union[np.ndarray, torch.Tensor, wp.indexedarray]:
    """Gets maximum velocities for articulation in the view.

    Args:
        indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                             to query. Shape (M,).
                                                                             Where M <= size of the encapsulated prims in the view.
                                                                             Defaults to None (i.e: all prims in the view).
        joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indicies to specify which joints
                                                                             to query. Shape (K,).
                                                                             Where K <= num of dofs.
                                                                             Defaults to None (i.e: all dofs).
        clone (Optional[bool]): True to return a clone of the internal buffer. Otherwise False. Defaults to True.

    Returns:
        Union[np.ndarray, torch.Tensor, wp.indexedarray]: maximum velocities for articulations in the view. shape (M, K).
    """
    if not self._is_initialized:
        carb.log_warn("ArticulationView needs to be initialized.")
        return None
    if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
        indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, "cpu")
        max_velocities = self._physics_view.get_dof_max_velocities()
        if clone:
            max_velocities = self._backend_utils.clone_tensor(max_velocities, device="cpu")
        result = self._backend_utils.move_data(
            max_velocities[
                self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices
            ],
            device=self._device,
        )
        return result
    else:
        indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
        max_velocities = np.zeros(shape=(indices.shape[0], joint_indices.shape[0]), dtype="float32")
        indices = self._backend_utils.to_list(indices)
        joint_indices = self._backend_utils.to_list(joint_indices)
        articulation_write_idx = 0
        for i in indices:
            dof_write_idx = 0
            for dof_index in joint_indices:
                prim = PhysxSchema.PhysxJointAPI(get_prim_at_path(self._dof_paths[i][dof_index]))
                max_velocities[articulation_write_idx][dof_write_idx] = prim.GetMaxJointVelocityAttr().Get()
                dof_write_idx += 1
            articulation_write_idx += 1
        max_velocities = self._backend_utils.convert(max_velocities, dtype="float32", device=self._device, indexed=True)
        return max_velocities

set_joint_efforts(efforts, indices=None, joint_indices=None)

Set the joint efforts of articulations in the view

.. note::

This method can be used for effort control. For this purpose, there must be no joint drive
or the stiffness and damping must be set to zero.

Parameters:

Name Type Description Default
efforts Optional[Union[ndarray, Tensor, array]]

efforts of articulations in the view to be set to in the next frame. shape is (M, K).

 required
indices Optional[Union[ndarray, List, Tensor, array]]

indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).

 None
joint_indices Optional[Union[ndarray, List, Tensor, array]]

joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).

 None

.. hint::

This method belongs to the methods used to set the articulation kinematic states:

``set_velocities`` (``set_linear_velocities``, ``set_angular_velocities``),
``set_joint_positions``, ``set_joint_velocities``, ``set_joint_efforts``

Example:

.. code-block:: python

>>> # set the efforts for all the articulation joints to the indicated values.
>>> # Since there are 5 envs, the joint efforts are repeated 5 times
>>> efforts = np.tile(np.array([10, 20, 30, 40, 50, 60, 70, 80, 90]), (num_envs, 1))
>>> prims.set_joint_efforts(efforts)
>>>
>>> # set the fingers efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 10
>>> # for the first, middle and last of the 5 envs
>>> efforts = np.tile(np.array([10, 10]), (3, 1))
>>> prims.set_joint_efforts(efforts, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
Source code in omnigibson/utils/deprecated_utils.py 
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def set_joint_efforts(
    self,
    efforts: Optional[Union[np.ndarray, torch.Tensor, wp.array]],
    indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
) -> None:
    """Set the joint efforts of articulations in the view

    .. note::

        This method can be used for effort control. For this purpose, there must be no joint drive
        or the stiffness and damping must be set to zero.

    Args:
        efforts (Optional[Union[np.ndarray, torch.Tensor, wp.array]]): efforts of articulations in the view to be set to in the next frame.
                                                                shape is (M, K).
        indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indices to specify which prims
                                                                             to manipulate. Shape (M,).
                                                                             Where M <= size of the encapsulated prims in the view.
                                                                             Defaults to None (i.e: all prims in the view).
        joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indices to specify which joints
                                                                             to manipulate. Shape (K,).
                                                                             Where K <= num of dofs.
                                                                             Defaults to None (i.e: all dofs).

    .. hint::

        This method belongs to the methods used to set the articulation kinematic states:

        ``set_velocities`` (``set_linear_velocities``, ``set_angular_velocities``),
        ``set_joint_positions``, ``set_joint_velocities``, ``set_joint_efforts``

    Example:

    .. code-block:: python

        >>> # set the efforts for all the articulation joints to the indicated values.
        >>> # Since there are 5 envs, the joint efforts are repeated 5 times
        >>> efforts = np.tile(np.array([10, 20, 30, 40, 50, 60, 70, 80, 90]), (num_envs, 1))
        >>> prims.set_joint_efforts(efforts)
        >>>
        >>> # set the fingers efforts: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 10
        >>> # for the first, middle and last of the 5 envs
        >>> efforts = np.tile(np.array([10, 10]), (3, 1))
        >>> prims.set_joint_efforts(efforts, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
    """
    if not self._is_initialized:
        carb.log_warn("ArticulationView needs to be initialized.")
        return

    if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
        indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)

        # THIS IS THE FIX: COMMENT OUT THE BELOW LINE AND USE ACTUATION FORCES INSTEAD
        # new_dof_efforts = self._backend_utils.create_zeros_tensor(
        #     shape=[self.count, self.num_dof], dtype="float32", device=self._device
        # )
        new_dof_efforts = self._physics_view.get_dof_actuation_forces()
        new_dof_efforts = self._backend_utils.assign(
            self._backend_utils.move_data(efforts, device=self._device),
            new_dof_efforts,
            [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
        )
        self._physics_view.set_dof_actuation_forces(new_dof_efforts, indices)
    else:
        carb.log_warn("Physics Simulation View is not created yet in order to use set_joint_efforts")
    return

set_joint_limits(values, indices=None, joint_indices=None)

Sets joint limits for articulation joints in the view.

Parameters:

Name Type Description Default
values Union[ndarray, Tensor, array]

joint limits for articulations in the view. shape (M, K, 2).

 required
indices Optional[Union[ndarray, List, Tensor, array]]

indicies to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).

 None
joint_indices Optional[Union[ndarray, List, Tensor, array]]

joint indicies to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).

 None
Source code in omnigibson/utils/deprecated_utils.py 
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def set_joint_limits(
    self,
    values: Union[np.ndarray, torch.Tensor],
    indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
) -> None:
    """Sets joint limits for articulation joints in the view.

    Args:
        values (Union[np.ndarray, torch.Tensor, wp.array]): joint limits for articulations in the view. shape (M, K, 2).
        indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                             to manipulate. Shape (M,).
                                                                             Where M <= size of the encapsulated prims in the view.
                                                                             Defaults to None (i.e: all prims in the view).
        joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indicies to specify which joints
                                                                             to manipulate. Shape (K,).
                                                                             Where K <= num of dofs.
                                                                             Defaults to None (i.e: all dofs).
    """
    if not self._is_initialized:
        carb.log_warn("ArticulationView needs to be initialized.")
        return
    if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
        indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, "cpu")
        new_values = self._physics_view.get_dof_limits()
        values = self._backend_utils.move_data(values, device="cpu")
        new_values = self._backend_utils.assign(
            values,
            new_values,
            [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
        )
        self._physics_view.set_dof_limits(new_values, indices)
    else:
        indices = self._backend_utils.to_list(
            self._backend_utils.resolve_indices(indices, self.count, self._device)
        )
        dof_types = self._backend_utils.to_list(self.get_dof_types())
        joint_indices = self._backend_utils.to_list(
            self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
        )
        values = self._backend_utils.to_list(values)
        articulation_read_idx = 0
        for i in indices:
            dof_read_idx = 0
            for dof_index in joint_indices:
                dof_val = values[articulation_read_idx][dof_read_idx]
                if dof_types[dof_index] == omni.physics.tensors.DofType.Rotation:
                    dof_val /= DEG2RAD
                prim = get_prim_at_path(self._dof_paths[i][dof_index])
                prim.GetAttribute("physics:lowerLimit").Set(dof_val[0])
                prim.GetAttribute("physics:upperLimit").Set(dof_val[1])
                dof_read_idx += 1
            articulation_read_idx += 1
    return

set_joint_positions(positions, indices=None, joint_indices=None)

Set the joint positions of articulations in the view

.. warning::

This method will immediately set (teleport) the affected joints to the indicated value.
Use the ``set_joint_position_targets`` or the ``apply_action`` methods to control the articulation joints.

Parameters:

Name Type Description Default
positions Optional[Union[ndarray, Tensor, array]]

joint positions of articulations in the view to be set to in the next frame. shape is (M, K).

 required
indices Optional[Union[ndarray, List, Tensor, array]]

indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).

 None
joint_indices Optional[Union[ndarray, List, Tensor, array]]

joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).

 None

.. hint::

This method belongs to the methods used to set the articulation kinematic states:

``set_velocities`` (``set_linear_velocities``, ``set_angular_velocities``),
``set_joint_positions``, ``set_joint_velocities``, ``set_joint_efforts``

Example:

.. code-block:: python

>>> # set all the articulation joints.
>>> # Since there are 5 envs, the joint positions are repeated 5 times
>>> positions = np.tile(np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04]), (num_envs, 1))
>>> prims.set_joint_positions(positions)
>>>
>>> # set only the fingers in closed position: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 0.0
>>> # for the first, middle and last of the 5 envs
>>> positions = np.tile(np.array([0.0, 0.0]), (3, 1))
>>> prims.set_joint_positions(positions, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
Source code in omnigibson/utils/deprecated_utils.py 
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def set_joint_positions(
    self,
    positions: Optional[Union[np.ndarray, torch.Tensor, wp.array]],
    indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
) -> None:
    """Set the joint positions of articulations in the view

    .. warning::

        This method will immediately set (teleport) the affected joints to the indicated value.
        Use the ``set_joint_position_targets`` or the ``apply_action`` methods to control the articulation joints.

    Args:
        positions (Optional[Union[np.ndarray, torch.Tensor, wp.array]]): joint positions of articulations in the view to be set to in the next frame.
                                                                shape is (M, K).
        indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indices to specify which prims
                                                                             to manipulate. Shape (M,).
                                                                             Where M <= size of the encapsulated prims in the view.
                                                                             Defaults to None (i.e: all prims in the view).
        joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indices to specify which joints
                                                                             to manipulate. Shape (K,).
                                                                             Where K <= num of dofs.
                                                                             Defaults to None (i.e: all dofs).

    .. hint::

        This method belongs to the methods used to set the articulation kinematic states:

        ``set_velocities`` (``set_linear_velocities``, ``set_angular_velocities``),
        ``set_joint_positions``, ``set_joint_velocities``, ``set_joint_efforts``

    Example:

    .. code-block:: python

        >>> # set all the articulation joints.
        >>> # Since there are 5 envs, the joint positions are repeated 5 times
        >>> positions = np.tile(np.array([0.0, -1.0, 0.0, -2.2, 0.0, 2.4, 0.8, 0.04, 0.04]), (num_envs, 1))
        >>> prims.set_joint_positions(positions)
        >>>
        >>> # set only the fingers in closed position: panda_finger_joint1 (7) and panda_finger_joint2 (8) to 0.0
        >>> # for the first, middle and last of the 5 envs
        >>> positions = np.tile(np.array([0.0, 0.0]), (3, 1))
        >>> prims.set_joint_positions(positions, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
    """
    if not self._is_initialized:
        carb.log_warn("ArticulationView needs to be initialized.")
        return
    if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
        indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
        new_dof_pos = self._physics_view.get_dof_positions()
        new_dof_pos = self._backend_utils.assign(
            self._backend_utils.move_data(positions, device=self._device),
            new_dof_pos,
            [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
        )
        self._physics_view.set_dof_positions(new_dof_pos, indices)

        # THIS IS THE FIX: COMMENT OUT THE BELOW LINE AND SET TARGETS INSTEAD
        # self._physics_view.set_dof_position_targets(new_dof_pos, indices)
        self.set_joint_position_targets(positions, indices, joint_indices)
    else:
        carb.log_warn("Physics Simulation View is not created yet in order to use set_joint_positions")

set_joint_velocities(velocities, indices=None, joint_indices=None)

Set the joint velocities of articulations in the view

.. warning::

This method will immediately set the affected joints to the indicated value.
Use the ``set_joint_velocity_targets`` or the ``apply_action`` methods to control the articulation joints.

Parameters:

Name Type Description Default
velocities Optional[Union[ndarray, Tensor, array]]

joint velocities of articulations in the view to be set to in the next frame. shape is (M, K).

 required
indices Optional[Union[ndarray, List, Tensor, array]]

indices to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).

 None
joint_indices Optional[Union[ndarray, List, Tensor, array]]

joint indices to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).

 None

.. hint::

This method belongs to the methods used to set the articulation kinematic states:

``set_velocities`` (``set_linear_velocities``, ``set_angular_velocities``),
``set_joint_positions``, ``set_joint_velocities``, ``set_joint_efforts``

Example:

.. code-block:: python

>>> # set the velocities for all the articulation joints to the indicated values.
>>> # Since there are 5 envs, the joint velocities are repeated 5 times
>>> velocities = np.tile(np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]), (num_envs, 1))
>>> prims.set_joint_velocities(velocities)
>>>
>>> # set the fingers velocities: panda_finger_joint1 (7) and panda_finger_joint2 (8) to -0.1
>>> # for the first, middle and last of the 5 envs
>>> velocities = np.tile(np.array([-0.1, -0.1]), (3, 1))
>>> prims.set_joint_velocities(velocities, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
Source code in omnigibson/utils/deprecated_utils.py 
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def set_joint_velocities(
    self,
    velocities: Optional[Union[np.ndarray, torch.Tensor, wp.array]],
    indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
) -> None:
    """Set the joint velocities of articulations in the view

    .. warning::

        This method will immediately set the affected joints to the indicated value.
        Use the ``set_joint_velocity_targets`` or the ``apply_action`` methods to control the articulation joints.

    Args:
        velocities (Optional[Union[np.ndarray, torch.Tensor, wp.array]]): joint velocities of articulations in the view to be set to in the next frame.
                                                                shape is (M, K).
        indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indices to specify which prims
                                                                             to manipulate. Shape (M,).
                                                                             Where M <= size of the encapsulated prims in the view.
                                                                             Defaults to None (i.e: all prims in the view).
        joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indices to specify which joints
                                                                             to manipulate. Shape (K,).
                                                                             Where K <= num of dofs.
                                                                             Defaults to None (i.e: all dofs).

    .. hint::

        This method belongs to the methods used to set the articulation kinematic states:

        ``set_velocities`` (``set_linear_velocities``, ``set_angular_velocities``),
        ``set_joint_positions``, ``set_joint_velocities``, ``set_joint_efforts``

    Example:

    .. code-block:: python

        >>> # set the velocities for all the articulation joints to the indicated values.
        >>> # Since there are 5 envs, the joint velocities are repeated 5 times
        >>> velocities = np.tile(np.array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]), (num_envs, 1))
        >>> prims.set_joint_velocities(velocities)
        >>>
        >>> # set the fingers velocities: panda_finger_joint1 (7) and panda_finger_joint2 (8) to -0.1
        >>> # for the first, middle and last of the 5 envs
        >>> velocities = np.tile(np.array([-0.1, -0.1]), (3, 1))
        >>> prims.set_joint_velocities(velocities, indices=np.array([0, 2, 4]), joint_indices=np.array([7, 8]))
    """
    if not self._is_initialized:
        carb.log_warn("ArticulationView needs to be initialized.")
        return
    if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
        indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
        new_dof_vel = self._physics_view.get_dof_velocities()
        new_dof_vel = self._backend_utils.assign(
            self._backend_utils.move_data(velocities, device=self._device),
            new_dof_vel,
            [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
        )
        self._physics_view.set_dof_velocities(new_dof_vel, indices)

        # THIS IS THE FIX: COMMENT OUT THE BELOW LINE AND SET TARGETS INSTEAD
        # self._physics_view.set_dof_velocity_targets(new_dof_vel, indices)
        self.set_joint_velocity_targets(velocities, indices, joint_indices)
    else:
        carb.log_warn("Physics Simulation View is not created yet in order to use set_joint_velocities")
    return

set_max_velocities(values, indices=None, joint_indices=None)

Sets maximum velocities for articulation in the view.

Parameters:

Name Type Description Default
values Union[ndarray, Tensor, array]

maximum velocities for articulations in the view. shape (M, K).

 required
indices Optional[Union[ndarray, List, Tensor, array]]

indicies to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).

 None
joint_indices Optional[Union[ndarray, List, Tensor, array]]

joint indicies to specify which joints to manipulate. Shape (K,). Where K <= num of dofs. Defaults to None (i.e: all dofs).

 None
Source code in omnigibson/utils/deprecated_utils.py 
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def set_max_velocities(
    self,
    values: Union[np.ndarray, torch.Tensor, wp.array],
    indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
    joint_indices: Optional[Union[np.ndarray, List, torch.Tensor, wp.array]] = None,
) -> None:
    """Sets maximum velocities for articulation in the view.

    Args:
        values (Union[np.ndarray, torch.Tensor, wp.array]): maximum velocities for articulations in the view. shape (M, K).
        indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                             to manipulate. Shape (M,).
                                                                             Where M <= size of the encapsulated prims in the view.
                                                                             Defaults to None (i.e: all prims in the view).
        joint_indices (Optional[Union[np.ndarray, List, torch.Tensor, wp.array]], optional): joint indicies to specify which joints
                                                                             to manipulate. Shape (K,).
                                                                             Where K <= num of dofs.
                                                                             Defaults to None (i.e: all dofs).
    """
    if not self._is_initialized:
        carb.log_warn("ArticulationView needs to be initialized.")
        return
    if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
        indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, "cpu")
        new_values = self._physics_view.get_dof_max_velocities()
        new_values = self._backend_utils.assign(
            self._backend_utils.move_data(values, device="cpu"),
            new_values,
            [self._backend_utils.expand_dims(indices, 1) if self._backend != "warp" else indices, joint_indices],
        )
        self._physics_view.set_dof_max_velocities(new_values, indices)
    else:
        indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
        joint_indices = self._backend_utils.resolve_indices(joint_indices, self.num_dof, self._device)
        articulation_read_idx = 0
        indices = self._backend_utils.to_list(indices)
        joint_indices = self._backend_utils.to_list(joint_indices)
        values = self._backend_utils.to_list(values)
        for i in indices:
            dof_read_idx = 0
            for dof_index in joint_indices:
                prim = PhysxSchema.PhysxJointAPI(get_prim_at_path(self._dof_paths[i][dof_index]))
                if not prim.GetMaxJointVelocityAttr():
                    prim.CreateMaxJointVelocityAttr().Set(values[articulation_read_idx][dof_read_idx])
                else:
                    prim.GetMaxJointVelocityAttr().Set(values[articulation_read_idx][dof_read_idx])
                dof_read_idx += 1
            articulation_read_idx += 1
    return

Core

Bases: Core

Subclass that overrides a specific function within Omni's Core class to fix a bug

Source code in omnigibson/utils/deprecated_utils.py 
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class Core(OmniCore):
    """
    Subclass that overrides a specific function within Omni's Core class to fix a bug
    """
    def __init__(self, popup_callback: Callable[[str], None], particle_system_name: str):
        self._popup_callback = popup_callback
        self.utils = Utils()
        self.context = ou.get_context()
        self.stage = self.context.get_stage()
        self.selection = self.context.get_selection()
        self.particle_system_name = particle_system_name
        self.sub_stage_update = self.context.get_stage_event_stream().create_subscription_to_pop(self.on_stage_update)
        self.on_stage_update()

    def get_compute_graph(self, selected_paths, create_new_graph=True, created_paths=None):
        """
        Returns the first ComputeGraph found in selected_paths.
        If no graph is found and create_new_graph is true, a new graph will be created and its
        path appended to created_paths (if provided).
        """
        graph = None
        graph_paths = [path for path in selected_paths
                       if self.stage.GetPrimAtPath(path).GetTypeName() in ["ComputeGraph", "OmniGraph"] ]

        if len(graph_paths) > 0:
            graph = ogc.get_graph_by_path(graph_paths[0])
            if len(graph_paths) > 1:
                carb.log_warn(f"Multiple ComputeGraph prims selected. Only the first will be used: {graph.get_path_to_graph()}")
        elif create_new_graph:
            # If no graph was found in the selected prims, we'll make a new graph.
            # TODO: THIS IS THE ONLY LINE THAT WE CHANGE! ONCE FIXED, REMOVE THIS
            graph_path = Sdf.Path(f"/OmniGraph/{self.particle_system_name}").MakeAbsolutePath(Sdf.Path.absoluteRootPath)
            graph_path = ou.get_stage_next_free_path(self.stage, graph_path, True)

            # prim = self.stage.GetDefaultPrim()
            # path = str(prim.GetPath()) if prim else ""
            self.stage.DefinePrim("/OmniGraph", "Scope")

            container_graphs = ogc.get_global_container_graphs()
            # FIXME: container_graphs[0] should be the simulation orchestration graph, but this may change in the future.
            container_graph = container_graphs[0]
            result, wrapper_node = ogc.cmds.CreateGraphAsNode(
                graph=container_graph,
                node_name=Sdf.Path(graph_path).name,
                graph_path=graph_path,
                evaluator_name="push",
                is_global_graph=True,
                backed_by_usd=True,
                fc_backing_type=ogc.GraphBackingType.GRAPH_BACKING_TYPE_FLATCACHE_SHARED,
                pipeline_stage=ogc.GraphPipelineStage.GRAPH_PIPELINE_STAGE_SIMULATION
            )
            graph = wrapper_node.get_wrapped_graph()

            if created_paths is not None:
                created_paths.append(graph.get_path_to_graph())

            carb.log_info(f"No ComputeGraph selected. A new graph has been created at {graph.get_path_to_graph()}")

        return graph

get_compute_graph(selected_paths, create_new_graph=True, created_paths=None)

Returns the first ComputeGraph found in selected_paths. If no graph is found and create_new_graph is true, a new graph will be created and its path appended to created_paths (if provided).

Source code in omnigibson/utils/deprecated_utils.py 
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def get_compute_graph(self, selected_paths, create_new_graph=True, created_paths=None):
    """
    Returns the first ComputeGraph found in selected_paths.
    If no graph is found and create_new_graph is true, a new graph will be created and its
    path appended to created_paths (if provided).
    """
    graph = None
    graph_paths = [path for path in selected_paths
                   if self.stage.GetPrimAtPath(path).GetTypeName() in ["ComputeGraph", "OmniGraph"] ]

    if len(graph_paths) > 0:
        graph = ogc.get_graph_by_path(graph_paths[0])
        if len(graph_paths) > 1:
            carb.log_warn(f"Multiple ComputeGraph prims selected. Only the first will be used: {graph.get_path_to_graph()}")
    elif create_new_graph:
        # If no graph was found in the selected prims, we'll make a new graph.
        # TODO: THIS IS THE ONLY LINE THAT WE CHANGE! ONCE FIXED, REMOVE THIS
        graph_path = Sdf.Path(f"/OmniGraph/{self.particle_system_name}").MakeAbsolutePath(Sdf.Path.absoluteRootPath)
        graph_path = ou.get_stage_next_free_path(self.stage, graph_path, True)

        # prim = self.stage.GetDefaultPrim()
        # path = str(prim.GetPath()) if prim else ""
        self.stage.DefinePrim("/OmniGraph", "Scope")

        container_graphs = ogc.get_global_container_graphs()
        # FIXME: container_graphs[0] should be the simulation orchestration graph, but this may change in the future.
        container_graph = container_graphs[0]
        result, wrapper_node = ogc.cmds.CreateGraphAsNode(
            graph=container_graph,
            node_name=Sdf.Path(graph_path).name,
            graph_path=graph_path,
            evaluator_name="push",
            is_global_graph=True,
            backed_by_usd=True,
            fc_backing_type=ogc.GraphBackingType.GRAPH_BACKING_TYPE_FLATCACHE_SHARED,
            pipeline_stage=ogc.GraphPipelineStage.GRAPH_PIPELINE_STAGE_SIMULATION
        )
        graph = wrapper_node.get_wrapped_graph()

        if created_paths is not None:
            created_paths.append(graph.get_path_to_graph())

        carb.log_info(f"No ComputeGraph selected. A new graph has been created at {graph.get_path_to_graph()}")

    return graph

CreateMeshPrimWithDefaultXformCommand

Bases: CreateMeshPrimWithDefaultXformCommand

Source code in omnigibson/utils/deprecated_utils.py 
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class CreateMeshPrimWithDefaultXformCommand(CMPWDXC):
    def __init__(self, prim_type: str, **kwargs):
        """
        Creates primitive.

        Args:
            prim_type (str): It supports Plane/Sphere/Cone/Cylinder/Disk/Torus/Cube.

        kwargs:
            object_origin (Gf.Vec3f): Position of mesh center in stage units.

            u_patches (int): The number of patches to tessellate U direction.

            v_patches (int): The number of patches to tessellate V direction.

            w_patches (int): The number of patches to tessellate W direction.
                             It only works for Cone/Cylinder/Cube.

            half_scale (float): Half size of mesh in centimeters. Default is None, which means it's controlled by settings.

            u_verts_scale (int): Tessellation Level of U. It's a multiplier of u_patches.

            v_verts_scale (int): Tessellation Level of V. It's a multiplier of v_patches.

            w_verts_scale (int): Tessellation Level of W. It's a multiplier of w_patches.
                                 It only works for Cone/Cylinder/Cube.
                                 For Cone/Cylinder, it's to tessellate the caps.
                                 For Cube, it's to tessellate along z-axis.

            above_ground (bool): It will offset the center of mesh above the ground plane if it's True,
                False otherwise. It's False by default. This param only works when param object_origin is not given.
                Otherwise, it will be ignored.

            stage (Usd.Stage): If specified, stage to create prim on
        """

        self._prim_type = prim_type[0:1].upper() + prim_type[1:].lower()
        self._usd_context = omni.usd.get_context()
        self._selection = self._usd_context.get_selection()
        self._stage = kwargs.get("stage", self._usd_context.get_stage())
        self._settings = carb.settings.get_settings()
        self._default_path = kwargs.get("prim_path", None)
        self._select_new_prim = kwargs.get("select_new_prim", True)
        self._prepend_default_prim = kwargs.get("prepend_default_prim", True)
        self._above_round = kwargs.get("above_ground", False)

        self._attributes = {**kwargs}
        # Supported mesh types should have an associated evaluator class
        self._evaluator_class = _get_all_evaluators()[prim_type]
        assert isinstance(self._evaluator_class, type)

__init__(prim_type, **kwargs)

Creates primitive.

Parameters:

Name Type Description Default
prim_type str

It supports Plane/Sphere/Cone/Cylinder/Disk/Torus/Cube.

 required
kwargs

object_origin (Gf.Vec3f): Position of mesh center in stage units.

u_patches (int): The number of patches to tessellate U direction.

v_patches (int): The number of patches to tessellate V direction.

w_patches (int): The number of patches to tessellate W direction. It only works for Cone/Cylinder/Cube.

half_scale (float): Half size of mesh in centimeters. Default is None, which means it's controlled by settings.

u_verts_scale (int): Tessellation Level of U. It's a multiplier of u_patches.

v_verts_scale (int): Tessellation Level of V. It's a multiplier of v_patches.

w_verts_scale (int): Tessellation Level of W. It's a multiplier of w_patches. It only works for Cone/Cylinder/Cube. For Cone/Cylinder, it's to tessellate the caps. For Cube, it's to tessellate along z-axis.

above_ground (bool): It will offset the center of mesh above the ground plane if it's True, False otherwise. It's False by default. This param only works when param object_origin is not given. Otherwise, it will be ignored.

stage (Usd.Stage): If specified, stage to create prim on

Source code in omnigibson/utils/deprecated_utils.py 
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def __init__(self, prim_type: str, **kwargs):
    """
    Creates primitive.

    Args:
        prim_type (str): It supports Plane/Sphere/Cone/Cylinder/Disk/Torus/Cube.

    kwargs:
        object_origin (Gf.Vec3f): Position of mesh center in stage units.

        u_patches (int): The number of patches to tessellate U direction.

        v_patches (int): The number of patches to tessellate V direction.

        w_patches (int): The number of patches to tessellate W direction.
                         It only works for Cone/Cylinder/Cube.

        half_scale (float): Half size of mesh in centimeters. Default is None, which means it's controlled by settings.

        u_verts_scale (int): Tessellation Level of U. It's a multiplier of u_patches.

        v_verts_scale (int): Tessellation Level of V. It's a multiplier of v_patches.

        w_verts_scale (int): Tessellation Level of W. It's a multiplier of w_patches.
                             It only works for Cone/Cylinder/Cube.
                             For Cone/Cylinder, it's to tessellate the caps.
                             For Cube, it's to tessellate along z-axis.

        above_ground (bool): It will offset the center of mesh above the ground plane if it's True,
            False otherwise. It's False by default. This param only works when param object_origin is not given.
            Otherwise, it will be ignored.

        stage (Usd.Stage): If specified, stage to create prim on
    """

    self._prim_type = prim_type[0:1].upper() + prim_type[1:].lower()
    self._usd_context = omni.usd.get_context()
    self._selection = self._usd_context.get_selection()
    self._stage = kwargs.get("stage", self._usd_context.get_stage())
    self._settings = carb.settings.get_settings()
    self._default_path = kwargs.get("prim_path", None)
    self._select_new_prim = kwargs.get("select_new_prim", True)
    self._prepend_default_prim = kwargs.get("prepend_default_prim", True)
    self._above_round = kwargs.get("above_ground", False)

    self._attributes = {**kwargs}
    # Supported mesh types should have an associated evaluator class
    self._evaluator_class = _get_all_evaluators()[prim_type]
    assert isinstance(self._evaluator_class, type)

RigidPrimView

Bases: RigidPrimView

Source code in omnigibson/utils/deprecated_utils.py 
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class RigidPrimView(_RigidPrimView):
    def enable_gravities(self, indices: Optional[Union[np.ndarray, list, torch.Tensor, wp.array]] = None) -> None:
        """Enable gravity on rigid bodies (enabled by default).

        Args:
            indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                                 to manipulate. Shape (M,).
                                                                                 Where M <= size of the encapsulated prims in the view.
                                                                                 Defaults to None (i.e: all prims in the view).
        """
        if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
            indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
            data = self._physics_view.get_disable_gravities().reshape(self._count)
            data = self._backend_utils.assign(
                self._backend_utils.create_tensor_from_list([False] * len(indices), dtype="uint8"), data, indices
            )
            self._physics_view.set_disable_gravities(data, indices)
        else:
            indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
            indices = self._backend_utils.to_list(indices)
            for i in indices:
                if self._physx_rigid_body_apis[i] is None:
                    if self._prims[i].HasAPI(PhysxSchema.PhysxRigidBodyAPI):
                        rigid_api = PhysxSchema.PhysxRigidBodyAPI(self._prims[i])
                    else:
                        rigid_api = PhysxSchema.PhysxRigidBodyAPI.Apply(self._prims[i])
                    self._physx_rigid_body_apis[i] = rigid_api
                self._physx_rigid_body_apis[i].GetDisableGravityAttr().Set(False)

    def disable_gravities(self, indices: Optional[Union[np.ndarray, list, torch.Tensor, wp.array]] = None) -> None:
        """Disable gravity on rigid bodies (enabled by default).

        Args:
            indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                                 to manipulate. Shape (M,).
                                                                                 Where M <= size of the encapsulated prims in the view.
                                                                                 Defaults to None (i.e: all prims in the view).
        """
        indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
        if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
            data = self._physics_view.get_disable_gravities().reshape(self._count)
            data = self._backend_utils.assign(
                self._backend_utils.create_tensor_from_list([True] * len(indices), dtype="uint8"), data, indices
            )
            self._physics_view.set_disable_gravities(data, indices)
        else:
            indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
            indices = self._backend_utils.to_list(indices)
            for i in indices:
                if self._physx_rigid_body_apis[i] is None:
                    if self._prims[i].HasAPI(PhysxSchema.PhysxRigidBodyAPI):
                        rigid_api = PhysxSchema.PhysxRigidBodyAPI(self._prims[i])
                    else:
                        rigid_api = PhysxSchema.PhysxRigidBodyAPI.Apply(self._prims[i])
                    self._physx_rigid_body_apis[i] = rigid_api
                self._physx_rigid_body_apis[i].GetDisableGravityAttr().Set(True)
            return

disable_gravities(indices=None)

Disable gravity on rigid bodies (enabled by default).

Parameters:

Name Type Description Default
indices Optional[Union[ndarray, list, Tensor, array]]

indicies to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).

 None
Source code in omnigibson/utils/deprecated_utils.py 
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def disable_gravities(self, indices: Optional[Union[np.ndarray, list, torch.Tensor, wp.array]] = None) -> None:
    """Disable gravity on rigid bodies (enabled by default).

    Args:
        indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                             to manipulate. Shape (M,).
                                                                             Where M <= size of the encapsulated prims in the view.
                                                                             Defaults to None (i.e: all prims in the view).
    """
    indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
    if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
        data = self._physics_view.get_disable_gravities().reshape(self._count)
        data = self._backend_utils.assign(
            self._backend_utils.create_tensor_from_list([True] * len(indices), dtype="uint8"), data, indices
        )
        self._physics_view.set_disable_gravities(data, indices)
    else:
        indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
        indices = self._backend_utils.to_list(indices)
        for i in indices:
            if self._physx_rigid_body_apis[i] is None:
                if self._prims[i].HasAPI(PhysxSchema.PhysxRigidBodyAPI):
                    rigid_api = PhysxSchema.PhysxRigidBodyAPI(self._prims[i])
                else:
                    rigid_api = PhysxSchema.PhysxRigidBodyAPI.Apply(self._prims[i])
                self._physx_rigid_body_apis[i] = rigid_api
            self._physx_rigid_body_apis[i].GetDisableGravityAttr().Set(True)
        return

enable_gravities(indices=None)

Enable gravity on rigid bodies (enabled by default).

Parameters:

Name Type Description Default
indices Optional[Union[ndarray, list, Tensor, array]]

indicies to specify which prims to manipulate. Shape (M,). Where M <= size of the encapsulated prims in the view. Defaults to None (i.e: all prims in the view).

 None
Source code in omnigibson/utils/deprecated_utils.py 
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def enable_gravities(self, indices: Optional[Union[np.ndarray, list, torch.Tensor, wp.array]] = None) -> None:
    """Enable gravity on rigid bodies (enabled by default).

    Args:
        indices (Optional[Union[np.ndarray, list, torch.Tensor, wp.array]], optional): indicies to specify which prims
                                                                             to manipulate. Shape (M,).
                                                                             Where M <= size of the encapsulated prims in the view.
                                                                             Defaults to None (i.e: all prims in the view).
    """
    if not omni.timeline.get_timeline_interface().is_stopped() and self._physics_view is not None:
        indices = self._backend_utils.resolve_indices(indices, self.count, "cpu")
        data = self._physics_view.get_disable_gravities().reshape(self._count)
        data = self._backend_utils.assign(
            self._backend_utils.create_tensor_from_list([False] * len(indices), dtype="uint8"), data, indices
        )
        self._physics_view.set_disable_gravities(data, indices)
    else:
        indices = self._backend_utils.resolve_indices(indices, self.count, self._device)
        indices = self._backend_utils.to_list(indices)
        for i in indices:
            if self._physx_rigid_body_apis[i] is None:
                if self._prims[i].HasAPI(PhysxSchema.PhysxRigidBodyAPI):
                    rigid_api = PhysxSchema.PhysxRigidBodyAPI(self._prims[i])
                else:
                    rigid_api = PhysxSchema.PhysxRigidBodyAPI.Apply(self._prims[i])
                self._physx_rigid_body_apis[i] = rigid_api
            self._physx_rigid_body_apis[i].GetDisableGravityAttr().Set(False)

colorize_bboxes(bboxes_2d_data, bboxes_2d_rgb, num_channels=3)

Colorizes 2D bounding box data for visualization.

We are overriding the replicator native version of this function to fix a bug. In their version of this function, the ordering of the rectangle corners is incorrect and we fix it here.

Parameters:

Name Type Description Default
bboxes_2d_data ndarray

2D bounding box data from the sensor.

 required
bboxes_2d_rgb ndarray

RGB data from the sensor to embed bounding box.

 required
num_channels int

Specify number of channels i.e. 3 or 4.

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Source code in omnigibson/utils/deprecated_utils.py 
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def colorize_bboxes(bboxes_2d_data, bboxes_2d_rgb, num_channels=3):
    """Colorizes 2D bounding box data for visualization.

    We are overriding the replicator native version of this function to fix a bug.
    In their version of this function, the ordering of the rectangle corners is incorrect and we fix it here.

    Args:
        bboxes_2d_data (numpy.ndarray): 2D bounding box data from the sensor.
        bboxes_2d_rgb (numpy.ndarray): RGB data from the sensor to embed bounding box.
        num_channels (int): Specify number of channels i.e. 3 or 4.
    """
    semantic_id_list = []
    bbox_2d_list = []
    rgb_img = Image.fromarray(bboxes_2d_rgb)
    rgb_img_draw = ImageDraw.Draw(rgb_img)
    for bbox_2d in bboxes_2d_data:
        semantic_id_list.append(bbox_2d['semanticId'])
        bbox_2d_list.append(bbox_2d)
    semantic_id_list_np = np.unique(np.array(semantic_id_list))
    color_list = random_colours(len(semantic_id_list_np.tolist()), True, num_channels)
    for bbox_2d in bbox_2d_list:
        index = np.where(semantic_id_list_np == bbox_2d['semanticId'])[0][0]
        bbox_color = color_list[index]
        outline = (bbox_color[0], bbox_color[1], bbox_color[2])
        if num_channels == 4:
            outline = (
                bbox_color[0],
                bbox_color[1],
                bbox_color[2],
                bbox_color[3],
            )
        rgb_img_draw.rectangle([(bbox_2d['x_min'], bbox_2d['y_min']), (bbox_2d['x_max'], bbox_2d['y_max'])], outline=outline, width=2)
    bboxes_2d_rgb = np.array(rgb_img)
    return bboxes_2d_rgb