(calibration_circe_properties)=
# Defining the `TCirce` properties

Once the `TCirce` object has been constructed, it is possible to configure several hyperparameters 
of the algorithm. 

The first one is the tolerance parameter used as a stopping criterion. Its **default value** is `1.0e-5`, 
but it can be modified with the `setTolerance` method, whose prototype is the following:

````{only} cpp
```cpp
void setTolerance(Double_t dtol);
```
````

````{only} py
```python
setTolerance(dtol)
```
````

This method accepts a single argument: a double precision value defining the new tolerance.

It is also possible to provide initial values for the algorithm:

- an initial vector of biases (**default value** is null vector), set with `setBVectorInitial`;
  
- an initial correlation matrix (**default value** is identity matrix), set with `setCMatrixInitial`.

````{only} cpp
```cpp
void setBVectorInitial(TVectorD vec);
void setCMatrixInitial(TMatrixD mat);
```
````

````{only} py
```python
setBVectorInitial(vec)
setCMatrixInitial(mat)
```
````

Each method accepts a single argument, namely the initial `TVectorD` (for the biases) or the initial `TMatrixD` (for the correlation matrix).

Finally, the user can define the number of iterations for running the algorithm with different initial correlation matrices (**default value** is 1) using the `setNCMatrix` method, whose prototype is the following:

````{only} cpp
```cpp
void setNCMatrix(Int_t n);
```
````

````{only} py
```python
setNCMatrix(n)
```
````

This method accepts a single integer argument that sets the number of iterations.

All these methods have corresponding getter functions, which allow retrieving the current values:

- `getTolerance` returns the tolerance (double),
- `getBVectorInitial` returns the initial bias vector (`TVectorD`), 
- `getCMatrixInitial` returns the initial correlation matrix (`TMatrixD`), 
- `getNCMatrix` returns the number of iterations (integer).