numpy.can_cast#
- numpy.can_cast(from_, to, casting='safe')#
Returns True if cast between data types can occur according to the casting rule.
- Parameters:
- from_dtype, dtype specifier, NumPy scalar, or array
Data type, NumPy scalar, or array to cast from.
- todtype or dtype specifier
Data type to cast to.
- casting{‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional
Controls what kind of data casting may occur.
‘no’ means the data types should not be cast at all.
‘equiv’ means only byte-order changes are allowed.
‘safe’ means only casts which can preserve values are allowed.
‘same_kind’ means only safe casts or casts within a kind, like float64 to float32, are allowed.
‘unsafe’ means any data conversions may be done.
- Returns:
- outbool
True if cast can occur according to the casting rule.
See also
Notes
Changed in version 1.17.0: Casting between a simple data type and a structured one is possible only for “unsafe” casting. Casting to multiple fields is allowed, but casting from multiple fields is not.
Changed in version 1.9.0: Casting from numeric to string types in ‘safe’ casting mode requires that the string dtype length is long enough to store the maximum integer/float value converted.
Changed in version 2.0: This function does not support Python scalars anymore and does not apply any value-based logic for 0-D arrays and NumPy scalars.
Examples
Basic examples
>>> np.can_cast(np.int32, np.int64) True >>> np.can_cast(np.float64, complex) True >>> np.can_cast(complex, float) False
>>> np.can_cast('i8', 'f8') True >>> np.can_cast('i8', 'f4') False >>> np.can_cast('i4', 'S4') False