sklearn.utils.check_scalar

sklearn.utils.check_scalar(x, name, target_type, *, min_val=None, max_val=None, include_boundaries='both')[source]

Validate scalar parameters type and value.

Parameters
xobject

The scalar parameter to validate.

namestr

The name of the parameter to be printed in error messages.

target_typetype or tuple

Acceptable data types for the parameter.

min_valfloat or int, default=None

The minimum valid value the parameter can take. If None (default) it is implied that the parameter does not have a lower bound.

max_valfloat or int, default=False

The maximum valid value the parameter can take. If None (default) it is implied that the parameter does not have an upper bound.

include_boundaries{“left”, “right”, “both”, “neither”}, default=”both”

Whether the interval defined by min_val and max_val should include the boundaries. Possible choices are:

  • "left": only min_val is included in the valid interval;

  • "right": only max_val is included in the valid interval;

  • "both": min_val and max_val are included in the valid interval;

  • "neither": neither min_val nor max_val are included in the valid interval.

Returns
xnumbers.Number

The validated number.

Raises
TypeError

If the parameter’s type does not match the desired type.

ValueError

If the parameter’s value violates the given bounds.