(calibration_classes_functions_observations_calibration_classes_draw_parameter)=
# Drawing the parameters

This method is used to visualize parameter values and posterior samples. The prototype is:

````{only} cpp
```cpp
void drawParameters(TString sTitre, const char *variable = "*", Option_t * option = "");
```
````

````{only} py
```python
drawParameters(sTitre, variable = "*", option = "")
```
````

It takes up to three arguments, two of which are optional:

1. **sTitre**: the title of the plot (an empty string is allowed);

2. **variable** (optional): a list of parameter names to be drawn, separated by colons ":". The default **"*"** draws all parameters;

3. **option** (optional): a list of options, separated by commas "," to adjust the plotting behavior:

    - **"nonewcanvas"**: draw on the current canvas (instead of creating a new one);

    - **"vertical"**: if multiple parameters are plotted, display them stacked vertically (one per row). By default, 
    plots are arranged horizontally, side by side.

```{warning}
If the `TMCMC` calibration object is used, the `drawParameters` method accounts for the potential *burn-in* and *lag* values 
by discarding the initial samples of the Markov chain and thinning it according to the specified values, in order to properly 
represent the behavior of the posterior distribution (see [](#calibration_markov_chain)).
```