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LarCurrent

dexter.LarCurrent()

Analytical Large Aspect Ratio Current with \(g=1\) and \(I=0\).

Example
LarCurrent creation
>>> current = dex.LarCurrent()

Methods:

Attributes:

dexter.LarCurrent.psi_state: FluxState property

The state of the toroidal flux coordinate.

dexter.LarCurrent.psip_state: FluxState property

The state of the poloidal flux coordinate.

dexter.LarCurrent.equilibrium_type: EquilibriumType property

The object's equilibrium's type.

dexter.LarCurrent.g_of_psi(psi: ArrayLike) -> NDArray

The \(g(\psi)\) value in Normalized Units.

Parameters:

  • psi (ArrayLike) –

    The toroidal flux \(\psi\) in Normalized Units.

dexter.LarCurrent.g_of_psip(psip: ArrayLike) -> NDArray

The \(g(\psi_p)\) value in Normalized Units.

Parameters:

  • psip (ArrayLike) –

    The poloidal flux \(\psi_p\) in Normalized Units.

dexter.LarCurrent.i_of_psi(psi: ArrayLike) -> NDArray

The \(I(\psi)\) value in Normalized Units.

Parameters:

  • psi (ArrayLike) –

    The toroidal flux \(\psi\) in Normalized Units.

dexter.LarCurrent.i_of_psip(psip: ArrayLike) -> NDArray

The \(I(\psi_p)\) value in Normalized Units.

Parameters:

  • psip (ArrayLike) –

    The poloidal flux \(\psi_p\) in Normalized Units.

dexter.LarCurrent.dg_dpsi(psi: ArrayLike) -> NDArray

The \(dg(\psi)/d\psi\) value in Normalized Units.

Parameters:

  • psi (ArrayLike) –

    The toroidal flux \(\psi\) in Normalized Units.

dexter.LarCurrent.dg_dpsip(psip: ArrayLike) -> NDArray

The \(dg(\psi_p)/d\psi_p\) value in Normalized Units.

Parameters:

  • psip (ArrayLike) –

    The poloidal flux \(\psi\) in Normalized Units.

dexter.LarCurrent.di_dpsi(psi: ArrayLike) -> NDArray

The \(dg(\psi)/d\psi\) value in Normalized Units.

Parameters:

  • psi (ArrayLike) –

    The toroidal flux \(\psi\) in Normalized Units.

dexter.LarCurrent.di_dpsip(psip: ArrayLike) -> NDArray

The \(dg(\psi_p)/d\psi_p\) value in Normalized Units.

Parameters:

  • psip (ArrayLike) –

    The poloidal flux \(\psi\) in Normalized Units.

dexter.LarCurrent.plot_g_of_psi(points: int = 1000, data: bool = False, show: bool = True) -> Canvas

Plots \(g(\psi)\).

Parameters:

  • points (int, default: 1000 ) –

    The number of points in which to evaluate \(g(\psi)\). Defaults to 1000.

  • data (bool, default: False ) –

    Whether or not to plot the data array points (numerical equilibria only). Defaults to False.

  • show (bool, default: True ) –

    Whether or not to call plt.show(). Defaults to True.

Returns:

  • Canvas –

    The produced Figure and Ax.

dexter.LarCurrent.plot_g_of_psip(points: int = 1000, data: bool = False, show: bool = True) -> Canvas

Plots \(g(\psi_p)\).

Parameters:

  • points (int, default: 1000 ) –

    The number of points in which to evaluate \(g(\psi_p)\). Defaults to 1000.

  • data (bool, default: False ) –

    Whether or not to plot the data array points (numerical equilibria only). Defaults to False.

  • show (bool, default: True ) –

    Whether or not to call plt.show(). Defaults to True.

Returns:

  • Canvas –

    The produced Figure and Ax.

dexter.LarCurrent.plot_i_of_psi(points: int = 1000, data: bool = False, show: bool = True) -> Canvas

Plots \(I(\psi)\).

Parameters:

  • points (int, default: 1000 ) –

    The number of points in which to evaluate \(I(\psi)\). Defaults to 1000.

  • data (bool, default: False ) –

    Whether or not to plot the data array points (numerical equilibria only). Defaults to False.

  • show (bool, default: True ) –

    Whether or not to call plt.show(). Defaults to True.

Returns:

  • Canvas –

    The produced Figure and Ax.

dexter.LarCurrent.plot_i_of_psip(points: int = 1000, data: bool = False, show: bool = True) -> Canvas

Plots \(I(\psi_p)\).

Parameters:

  • points (int, default: 1000 ) –

    The number of points in which to evaluate \(I(\psi_p)\). Defaults to 1000.

  • data (bool, default: False ) –

    Whether or not to plot the data array points (numerical equilibria only). Defaults to False.

  • show (bool, default: True ) –

    Whether or not to call plt.show(). Defaults to True.

Returns:

  • Canvas –

    The produced Figure and Ax.

dexter.LarCurrent.plot_dg_dpsi(points: int = 1000, show: bool = True) -> Canvas

Plots \(dg(\psi)/d\psi\).

Parameters:

  • points (int, default: 1000 ) –

    The number of points in which to evaluate \(dg(\psi)/d\psi\). Defaults to 1000.

  • show (bool, default: True ) –

    Whether or not to call plt.show(). Defaults to True.

Returns:

  • Canvas –

    The produced Figure and Ax.

dexter.LarCurrent.plot_dg_dpsip(points: int = 1000, show: bool = True) -> Canvas

Plots \(dg(\psi_p)/d\psi_p\).

Parameters:

  • points (int, default: 1000 ) –

    The number of points in which to evaluate \(dg(\psi_p)/d\psi_p\). Defaults to 1000.

  • show (bool, default: True ) –

    Whether or not to call plt.show(). Defaults to True.

Returns:

  • Canvas –

    The produced Figure and Ax.

dexter.LarCurrent.plot_di_dpsi(points: int = 1000, show: bool = True) -> Canvas

Plots \(dI(\psi)/d\psi\).

Parameters:

  • points (int, default: 1000 ) –

    The number of points in which to evaluate \(dI(\psi)/d\psi\). Defaults to 1000.

  • show (bool, default: True ) –

    Whether or not to call plt.show(). Defaults to True.

Returns:

  • Canvas –

    The produced Figure and Ax.

dexter.LarCurrent.plot_di_dpsip(points: int = 1000, show: bool = True) -> Canvas

Plots \(dI(\psi_p)/d\psi_p\).

Parameters:

  • points (int, default: 1000 ) –

    The number of points in which to evaluate \(dI(\psi_p)/d\psi_p\). Defaults to 1000.

  • show (bool, default: True ) –

    Whether or not to call plt.show(). Defaults to True.

Returns:

  • Canvas –

    The produced Figure and Ax.