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class fynance.features.scale.Scale(X, kind='std', a=0.0, b=1.0, axis=0, **kwargs)

Object to scale data.

X : np.ndarray[dtype, ndim=1 or 2]

Data to fit the parameters of scale transformation.

kind : str, optional
  • “std” : Standardized scale transformation (default), see standardize.
  • “norm” : Normalized scale transformation, see normalize.
  • “raw” : No scale is apply.
  • “roll_std” : Standardized scale transformation, computed with rolling mean and standard deviation (see roll_standardize).
  • “roll_norm” : Normalized scale transformation, computed with roling minimum and maximum (see roll_normalize).
a, b : float or array_like, optional

Some scale factors to apply after the transformation. By default is respectively 0 and 1.

axis : int, optional

Axis along which compute the scale parameters. Default is 0.

**kwargs : keyword arguments for particular functions

E.g: for rolling function set w the lagged window (see roll_normalize) or for rolling standardization set kind_moment={"s", "w", "e"} (see roll_standardize).

func : callable

The scale function.

revert_func : callable

The revert scale function.

params : dict

Parameters of the scale transformation.

axis : int

The axis along which is computed the scale parameters.

kind : str

The kind of scale transformation.


fit(X[, kind, a, b, axis]) Compute the parameters of the scale transformation.
scale(X[, axis]) Scale the data with the fitted parameters.
revert(X[, axis]) Revert the transformation of the scale with the fitted parameters.