-- SPDX-License-Identifier: Apache-2.0
--
-- Copyright (c) 2022 onox <denkpadje@gmail.com>
--
-- Licensed under the Apache License, Version 2.0 (the "License");
-- you may not use this file except in compliance with the License.
-- You may obtain a copy of the License at
--
-- http://www.apache.org/licenses/LICENSE-2.0
--
-- Unless required by applicable law or agreed to in writing, software
-- distributed under the License is distributed on an "AS IS" BASIS,
-- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-- See the License for the specific language governing permissions and
-- limitations under the License.
private with Ada.Containers.Indefinite_Holders;
with Orka.Numerics.Tensors;
generic
with package Tensors is new Orka.Numerics.Tensors (<>);
type Tensor (<>) is new Tensors.Tensor with private;
package Orka.Numerics.Kalman is
pragma Preelaborate;
use type Tensors.Tensor_Shape;
subtype Vector is Tensor;
subtype Matrix is Tensor;
type Update_Phase is (Time_Update, Measurement_Update);
type Filter_Kind is (Filter_UKF, Filter_CDKF);
type State_Covariance is private;
type Weights_Type (N : Positive; Kind : Filter_Kind) is private;
type Filter (Kind : Filter_Kind; Dimension_X, Dimension_Z : Positive) is tagged private;
function State (Object : Filter) return Vector
with Post => State'Result.Shape = (1 => Object.Dimension_X);
procedure Set_State (Object : in out Filter; State : Vector)
with Pre => State.Shape = (1 => Object.Dimension_X);
private
subtype Element_Type is Tensors.Element_Type;
package Tensor_Holders is new Ada.Containers.Indefinite_Holders (Tensor);
-- These predicates cannot be applied to the formal types above
subtype Vector_Holder is Tensor_Holders.Holder;
subtype Matrix_Holder is Tensor_Holders.Holder;
type Weights_Type (N : Positive; Kind : Filter_Kind) is record
Mean : Vector_Holder;
Scaling_Factor : Element_Type;
case Kind is
when Filter_UKF =>
Covariance : Vector_Holder;
when Filter_CDKF =>
Covariance_1 : Element_Type;
Covariance_2 : Element_Type;
end case;
end record;
type State_Covariance is record
State : Vector_Holder;
Covariance : Matrix_Holder;
end record;
type Filter (Kind : Filter_Kind; Dimension_X, Dimension_Z : Positive) is tagged record
Process_Noise : Matrix_Holder;
Measurement_Noise : Matrix_Holder;
Weights : Weights_Type (Dimension_X, Kind);
Estimate : State_Covariance;
end record;
function State (Object : Filter) return Vector is (Object.Estimate.State.Element);
end Orka.Numerics.Kalman;