Functions
NPY_NO_EXPORT int	PyUFunc_SimpleBinaryComparisonTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_SimpleUnaryOperationTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_NegativeTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_OnesLikeTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_SimpleBinaryOperationTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_AbsoluteTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_AdditionTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_SubtractionTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_MultiplicationTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_MixedDivisionTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	PyUFunc_DivisionTypeResolver (PyUFuncObject ufunc, NPY_CASTING casting, PyArrayObject operands, PyObject type_tup, PyArray_Descr **out_dtypes)
NPY_NO_EXPORT int	linear_search_type_resolver (PyUFuncObject self, PyArrayObject op, NPY_CASTING input_casting, NPY_CASTING output_casting, int any_object, PyArray_Descr *out_dtype)
NPY_NO_EXPORT int	type_tuple_type_resolver (PyUFuncObject self, PyObject type_tup, PyArrayObject op, NPY_CASTING casting, int any_object, PyArray_Descr out_dtype)
NPY_NO_EXPORT int	PyUFunc_DefaultLegacyInnerLoopSelector (PyUFuncObject ufunc, PyArray_Descr dtypes, PyUFuncGenericFunction out_innerloop, void *out_innerloopdata, int out_needs_api)
NPY_NO_EXPORT int	PyUFunc_DefaultMaskedInnerLoopSelector (PyUFuncObject ufunc, PyArray_Descr dtypes, PyArray_Descr mask_dtypes, npy_intp NPY_UNUSED(fixed_strides), npy_intp NPY_UNUSED(fixed_mask_stride), PyUFunc_MaskedStridedInnerLoopFunc out_innerloop, NpyAuxData out_innerloopdata, int out_needs_api)

Function Documentation

NPY_NO_EXPORT int linear_search_type_resolver	(	PyUFuncObject *	self,
		PyArrayObject **	op,
		NPY_CASTING	input_casting,
		NPY_CASTING	output_casting,
		int	any_object,
		PyArray_Descr **	out_dtype
	)

Does a linear search for the best inner loop of the ufunc.

Note that if an error is returned, the caller must free the non-zero references in out_dtype. This function does not do its own clean-up.

For making a better error message on coercion error

If the ufunc has userloops, search for them.

Error

A loop was found

Determine the UFunc loop. This could in general be much faster, and a better way to implement it might be for the ufunc to provide a function which gives back the result type and inner loop function.

A default fast mechanism could be provided for functions which follow the most typical pattern, when all functions have signatures "xx...x -> x" for some built-in data type x, as follows.

System Message: ERROR/3 (<string>, line 9) Unexpected indentation.

Use PyArray_ResultType to get the output type
Look up the inner loop in a table based on the output type_num

</blockquote>

The method for finding the loop in the previous code did not appear consistent (as noted by some asymmetry in the generated coercion tables for np.add).

Copy the types into an int array for matching

Error

Found a match

If no function was found, throw an error

TODO: We should try again if the casting rule is same_kind: or unsafe, and look for a function more liberally.

Referenced by PyUFunc_DefaultTypeResolver().

NPY_NO_EXPORT int PyUFunc_AbsoluteTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

This function applies special type resolution rules for the absolute ufunc. This ufunc converts complex -> float, so isn't covered by the simple unary type resolution.

Returns 0 on success, -1 on error.

Use the default for complex types, to find the loop producing float

NPY_NO_EXPORT int PyUFunc_AdditionTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

This function applies the type resolution rules for addition. In particular, there are a number of special cases with datetime:

System Message: ERROR/3 (<string>, line 3) Unexpected indentation.

System Message: WARNING/2 (<string>, line 10) Block quote ends without a blank line; unexpected unindent.

TODO: Non-linear time unit cases require highly special-cased loops: M8[<A>] + m8[Y|M|B] m8[Y|M|B] + M8[<A>]

Use the default when datetime and timedelta are not involved

m8[<A>] + m8[] => m8[gcd(<A>,)] + m8[gcd(<A>,)]

m8[<A>] + M8[] => m8[gcd(<A>,)] + M8[gcd(<A>,)]

Make a new NPY_TIMEDELTA, and copy the datetime's metadata

m8[<A>] + int => m8[<A>] + m8[<A>]

M8[<A>] + m8[] => M8[gcd(<A>,)] + m8[gcd(<A>,)]

Make a new NPY_TIMEDELTA, and copy the datetime's metadata

M8[<A>] + int => M8[<A>] + m8[<A>]

Make a new NPY_TIMEDELTA, and copy type1's metadata

int + m8[<A>] => m8[<A>] + m8[<A>]

Make a new NPY_TIMEDELTA, and copy type2's metadata

Check against the casting rules

NPY_NO_EXPORT int PyUFunc_DefaultLegacyInnerLoopSelector	(	PyUFuncObject *	ufunc,
		PyArray_Descr **	dtypes,
		PyUFuncGenericFunction *	out_innerloop,
		void **	out_innerloopdata,
		int *	out_needs_api
	)

If there are user-loops search them first. TODO: There needs to be a loop selection acceleration structure,

System Message: ERROR/3 (<string>, line 3) Unexpected indentation.

<blockquote> like a hash table.</blockquote>

Error

Found a loop

Copy the types into an int array for matching

References NPY_OBJECT, NPY_VOID, PyArray_CanCastArrayTo(), PyArray_CanCastTypeTo(), PyArray_DESCR, and PyArray_DescrFromType().

NPY_NO_EXPORT int PyUFunc_DefaultMaskedInnerLoopSelector	(	PyUFuncObject *	ufunc,
		PyArray_Descr **	dtypes,
		PyArray_Descr *	mask_dtype,
		npy_intp *	NPY_UNUSEDfixed_strides,
		npy_intp	NPY_UNUSEDfixed_mask_stride,
		PyUFunc_MaskedStridedInnerLoopFunc **	out_innerloop,
		NpyAuxData **	out_innerloopdata,
		int *	out_needs_api
	)

This function wraps a legacy inner loop so it becomes masked.

Returns 0 on success, -1 on error.

Create a new NpyAuxData object for the masker data

Get the unmasked ufunc inner loop

Return the loop function + aux data

NPY_NO_EXPORT int PyUFunc_DivisionTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

This function applies the type resolution rules for division. In particular, there are a number of special cases with datetime:

System Message: ERROR/3 (<string>, line 3) Unexpected indentation.

<blockquote> m8[<A>] / m8[] to m8[gcd(<A>,)] / m8[gcd(<A>,)] -> float64 m8[<A>] / int## to m8[<A>] / int64 -> m8[<A>] m8[<A>] / float## to m8[<A>] / float64 -> m8[<A>]</blockquote>

Use the default when datetime and timedelta are not involved

m8[<A>] / m8[] to m8[gcd(<A>,)] / m8[gcd(<A>,)] -> float64

m8[<A>] / int## => m8[<A>] / int64

m8[<A>] / float## => m8[<A>] / float64

Check against the casting rules

NPY_NO_EXPORT int PyUFunc_MixedDivisionTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

Function to check and report floor division warning when python2.x is invoked with -3 switch See PEP238 and #7949 for numpy This function will not be hit for py3 or when __future__ imports division. See generate_umath.py for reason

Depreciation checks needed only on python 2

If both types are integer, warn the user, same as python does

References data, _ufunc_masker_data::nargs, npy_memchr(), _ufunc_masker_data::unmasked_innerloop, and _ufunc_masker_data::unmasked_innerloopdata.

NPY_NO_EXPORT int PyUFunc_MultiplicationTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

This function applies the type resolution rules for multiplication. In particular, there are a number of special cases with datetime:

System Message: ERROR/3 (<string>, line 3) Unexpected indentation.

<blockquote> int## * m8[<A>] => int64 * m8[<A>] m8[<A>] * int## => m8[<A>] * int64 float## * m8[<A>] => float64 * m8[<A>] m8[<A>] * float## => m8[<A>] * float64</blockquote>

Use the default when datetime and timedelta are not involved

m8[<A>] * int## => m8[<A>] * int64

m8[<A>] * float## => m8[<A>] * float64

int## * m8[<A>] => int64 * m8[<A>]

float## * m8[<A>] => float64 * m8[<A>]

Check against the casting rules

References ensure_dtype_nbo(), _tagPyUFuncObject::name, NPY_DOUBLE, NPY_LONGLONG, NPY_TIMEDELTA, PyArray_DESCR, PyArray_DescrFromType(), PyArray_DescrNewFromType(), PyArray_PromoteTypes(), PyTypeNum_ISDATETIME, PyTypeNum_ISFLOAT, PyTypeNum_ISINTEGER, PyUFunc_DefaultTypeResolver(), PyUFunc_ValidateCasting(), PyUString_ConcatAndDel, PyUString_FromFormat, and PyUString_FromString.

NPY_NO_EXPORT int PyUFunc_NegativeTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

The type resolver would have upcast already

2013-12-05, 1.9

References NPY_UNSAFE_CASTING, and PyUFunc_SimpleUnaryOperationTypeResolver().

NPY_NO_EXPORT int PyUFunc_OnesLikeTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

NPY_NO_EXPORT int PyUFunc_SimpleBinaryComparisonTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

This function applies special type resolution rules for the case where all the functions have the pattern XX->bool, using PyArray_ResultType instead of a linear search to get the best loop.

Returns 0 on success, -1 on error.

Use the default type resolution if there's a custom data type or object arrays.

Input types are the result type

If the type tuple isn't a single-element tuple, let the default type resolution handle this one.

Output type is always boolean

Check against the casting rules

NPY_NO_EXPORT int PyUFunc_SimpleBinaryOperationTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

This function applies special type resolution rules for the case where all the functions have the pattern XX->X, using PyArray_ResultType instead of a linear search to get the best loop.

Note that a simpler linear search through the functions loop is still done, but switching to a simple array lookup for built-in types would be better at some point.

Returns 0 on success, -1 on error.

Use the default type resolution if there's a custom data type or object arrays.

Input types are the result type

If the type tuple isn't a single-element tuple, let the default type resolution handle this one.

Check against the casting rules

Referenced by timedelta_dtype_with_copied_meta().

NPY_NO_EXPORT int PyUFunc_SimpleUnaryOperationTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

This function applies special type resolution rules for the case where all the functions have the pattern X->X, copying the input descr directly so that metadata is maintained.

Note that a simpler linear search through the functions loop is still done, but switching to a simple array lookup for built-in types would be better at some point.

Returns 0 on success, -1 on error.

Use the default type resolution if there's a custom data type or object arrays.

Input types are the result type

If the type tuple isn't a single-element tuple, let the default type resolution handle this one.

Check against the casting rules

References PyUFunc_DefaultTypeResolver().

Referenced by PyUFunc_NegativeTypeResolver().

NPY_NO_EXPORT int PyUFunc_SubtractionTypeResolver	(	PyUFuncObject *	ufunc,
		NPY_CASTING	casting,
		PyArrayObject **	operands,
		PyObject *	type_tup,
		PyArray_Descr **	out_dtypes
	)

This function applies the type resolution rules for subtraction. In particular, there are a number of special cases with datetime:

System Message: ERROR/3 (<string>, line 3) Unexpected indentation.

System Message: WARNING/2 (<string>, line 8) Block quote ends without a blank line; unexpected unindent.

TODO: Non-linear time unit cases require highly special-cased loops: M8[<A>] - m8[Y|M|B]

Use the default when datetime and timedelta are not involved

The type resolver would have upcast already

2013-12-05, 1.9

m8[<A>] - m8[] => m8[gcd(<A>,)] - m8[gcd(<A>,)]

m8[<A>] - int => m8[<A>] - m8[<A>]

M8[<A>] - m8[] => M8[gcd(<A>,)] - m8[gcd(<A>,)]

Make a new NPY_TIMEDELTA, and copy the datetime's metadata

M8[<A>] - int => M8[<A>] - m8[<A>]

Make a new NPY_TIMEDELTA, and copy type1's metadata

M8[<A>] - M8[] => M8[gcd(<A>,)] - M8[gcd(<A>,)]

Make a new NPY_TIMEDELTA, and copy type1's metadata

int - m8[<A>] => m8[<A>] - m8[<A>]

Check against the casting rules

References PyArray_DESCR, PyArray_PromoteTypes(), and timedelta_dtype_with_copied_meta().

NPY_NO_EXPORT int type_tuple_type_resolver	(	PyUFuncObject *	self,
		PyObject *	type_tup,
		PyArrayObject **	op,
		NPY_CASTING	casting,
		int	any_object,
		PyArray_Descr **	out_dtype
	)

Does a linear search for the inner loop of the ufunc specified by type_tup.

Note that if an error is returned, the caller must free the non-zero references in out_dtype. This function does not do its own clean-up.

For making a better error message on coercion error

Fill in specified_types from the tuple or string

If the ufunc has userloops, search for them.

Error

Found matching loop

Copy the types into an int array for matching

no match

Error

Cannot cast inputs

Success

If no function was found, throw an error

Referenced by PyUFunc_DefaultTypeResolver().

Functions

Function Documentation