opensrdk_symbolic_computation/expression/matrix_expression/operations/
inv.rs

1use std::collections::HashMap;
2
3use opensrdk_linear_algebra::Matrix;
4
5use crate::{BracketsLevel, ConstantValue, Expression, MatrixExpression};
6
7impl Expression {
8    pub fn inv(self) -> Expression {
9        if let Expression::Constant(v) = self {
10            let inv = |v: Matrix| v.getrf().unwrap().getri().unwrap().into();
11            return match v {
12                ConstantValue::Scalar(v) => v.abs().into(),
13                ConstantValue::Tensor(v) => inv(v.reduce_1dimension_rank().to_mat()),
14                ConstantValue::Matrix(v) => return inv(v),
15            };
16        }
17
18        MatrixExpression::Inv(self.into()).into()
19    }
20}
21
22impl MatrixExpression {
23    pub(crate) fn diff_inv(v: &Expression, symbols: &[&str]) -> Vec<Expression> {
24        v.differential(symbols)
25            .into_iter()
26            .map(|d_v_d_symbol| {
27                let v_inv = v.clone().inv();
28                let d_v_inv_d_v = -v_inv.clone().dot(v_inv, &[[1, 0]]);
29
30                d_v_inv_d_v.dot(d_v_d_symbol, &[[0, 0], [1, 1]])
31            })
32            .collect()
33    }
34
35    pub(crate) fn tex_code_inv(v: &Expression, symbols: &HashMap<&str, &str>) -> String {
36        format!(
37            r"{{{}^{{-1}}}}",
38            v._tex_code(symbols, BracketsLevel::ForOperation)
39        )
40    }
41}

opensrdk_symbolic_computation/expression/matrix_expression/operations/inv.rs

opensrdk_symbolic_computation/expression/matrix_expression/operations/
inv.rs