numpy.find_common_type — NumPy v1.11 Manual (original) (raw)
numpy.find_common_type(array_types, scalar_types)[source]¶
Determine common type following standard coercion rules.
| Parameters: | array_types : sequence A list of dtypes or dtype convertible objects representing arrays. scalar_types : sequence A list of dtypes or dtype convertible objects representing scalars. |
|---|---|
| Returns: | 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. |
Examples
np.find_common_type([], [np.int64, np.float32, np.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:
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:
np.find_common_type([np.float32], [np.complex]) dtype('complex128')
Type specifier strings are convertible to dtypes and can therefore be used instead of dtypes:
np.find_common_type(['f4', 'f4', 'i4'], ['c8']) dtype('complex128')