Type Promotion Rules ¶
Array API specification for type promotion rules.
Type promotion rules can be understood at a high level from the following diagram:
Type promotion diagram. Promotion between any two types is given by their join on this lattice. Only the types of participating arrays matter, not their values). Dashed lines indicate that behaviour for Python scalars is undefined on overflow. Boolean, integer and floatingpoint dtypes are not connected, indicating mixedkind promotion is undefined.
Rules ¶
A conforming implementation of the array API standard must implement the following type promotion rules governing the common result type for two array operands during an arithmetic operation.
A conforming implementation of the array API standard may support additional type promotion rules beyond those described in this specification.
Note
Type codes are used here to keep tables readable; they are not part of the standard.
In code, use the data type objects specified in
Data Types
(e.g.,
int16
rather than
'i2'
).
The following type promotion tables specify the casting behavior for operations involving two array operands. When more than two array operands participate, application of the promotion tables is associative (i.e., the result does not depend on operand order).
Signed integer type promotion table ¶
i1  i2  i4  i8  

i1  i1  i2  i4  i8 
i2  i2  i2  i4  i8 
i4  i4  i4  i4  i8 
i8  i8  i8  i8  i8 
where

i1 : 8bit signed integer (i.e.,
int8
) 
i2 : 16bit signed integer (i.e.,
int16
) 
i4 : 32bit signed integer (i.e.,
int32
) 
i8 : 64bit signed integer (i.e.,
int64
)
Unsigned integer type promotion table ¶
u1  u2  u4  u8  

u1  u1  u2  u4  u8 
u2  u2  u2  u4  u8 
u4  u4  u4  u4  u8 
u8  u8  u8  u8  u8 
where

u1 : 8bit unsigned integer (i.e.,
uint8
) 
u2 : 16bit unsigned integer (i.e.,
uint16
) 
u4 : 32bit unsigned integer (i.e.,
uint32
) 
u8 : 64bit unsigned integer (i.e.,
uint64
)
Mixed unsigned and signed integer type promotion table ¶
u1  u2  u4  

i1  i2  i4  i8 
i2  i2  i4  i8 
i4  i4  i4  i8 
Floatingpoint type promotion table ¶
f4  f8  

f4  f4  f8 
f8  f8  f8 
where

f4 : singleprecision (32bit) floatingpoint number (i.e.,
float32
) 
f8 : doubleprecision (64bit) floatingpoint number (i.e.,
float64
)
Notes ¶

Type promotion rules must apply when determining the common result type for two array operands during an arithmetic operation, regardless of array dimension. Accordingly, zerodimensional arrays must be subject to the same type promotion rules as dimensional arrays.

Type promotion of nonnumerical data types to numerical data types is unspecified (e.g.,
bool
tointxx
orfloatxx
).
Note
Mixed integer and floatingpoint type promotion rules are not specified because behavior varies between implementations.
Mixing arrays with Python scalars ¶
Using Python scalars (i.e., instances of
bool
,
int
,
float
) together with
arrays must be supported for:

array <op> scalar

scalar <op> array
where
<op>
is a builtin operator (see
Operators
for operators
supported by the array object) and
scalar
has a compatible type and value
to the array dtype:

Python
bool
for abool
array dtype, 
a positive Python
int
for unsigned integer array dtypes, 
a Python
int
for integer array dtypes, 
a Python
int
orfloat
for floatingpoint array dtypes The expected behavior is then equivalent to:

Convert the scalar to a 0D array with the same dtype as that of the array used in the expression.

Execute the operation for
array <op> 0D array
(or0D array <op> array
ifscalar
was the lefthand argument).
Note
Behaviour is not specified when mixing a Python
float
and an array with an
integer dtype; this may give
float32
,
float64
, or raise an exception 
behavior of implementations will differ.