NumPy Data type: find_common_type() function

numpy.find_common_type() function

The find_common_type() function determine common type following standard coercion rules.

Version: 1.15.0

Syntax:

numpy.find_common_type(array_types, scalar_types)

Parameter:

Return value:

datatype : dtype
The common data type, which is the maximum of array_types ignoring scalar_types, unless the maximum of scalar_types is of a different kind (dtype.kind). If the kind is not understood, then None is returned.

Example: numpy.find_common_type() Function

>>> import numpy as np
>>> np.find_common_type([], [np.int64, np.float32, complex])
dtype('complex128')
>>> np.find_common_type([np.int64, np.float32], [])
dtype('float64')

The standard casting rules ensure that a scalar cannot up-cast an array unless the scalar is of a fundamentally different kind of data (i.e. under a different hierarchy in the data type hierarchy) then the array:

Example: numpy.find_common_type() function

>>> import numpy as np
>>> np.find_common_type([np.float32], [np.int64, np.float64])
dtype('float32')

Complex is of a different type, so it up-casts the float in the array_types argument:

Example: numpy.find_common_type() function

>>> import numpy as np
>>> np.find_common_type([np.float32], [complex])
dtype('complex128')

Type specifier strings are convertible to dtypes and can therefore be used instead of dtypes:

Example: numpy.find_common_type() function

>>> import numpy as np
>>> np.find_common_type(['f4', 'f4', 'i4'], ['c8'])
dtype('complex128')

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