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

dtype, result_type

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

>>> import numpy as np
>>> 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
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