arrayfire.algorithm module

Vector algorithms (sum, min, sort, etc).

arrayfire.algorithm.accum(a, dim=0)

Cumulative sum of an array along a specified dimension

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: 0

Dimension along which the cumulative sum is required.

Returns

out: af.Array

array of same size as a containing the cumulative sum along dim.

arrayfire.algorithm.allTrueByKey(keys, vals, dim=- 1)

Calculate if all elements are true along a specified dimension according to a key.

Parameters

keysaf.Array

One dimensional arrayfire array with reduction keys.

valsaf.Array

Multi dimensional arrayfire array that will be reduced.

dim: optional: int. default: -1

Dimension along which the all true check will occur.

Returns

keys: af.Array or scalar number

The reduced keys of all true check in vals along dimension dim.

values: af.Array or scalar number

Booleans denoting if all elements are true in vals along dimension dim according to keys

arrayfire.algorithm.all_true(a, dim=None)

Check if all the elements along a specified dimension are true.

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: None

Dimension along which the product is required.

Returns

out: af.Array or scalar number

Af.array containing True if all elements in a along the dimension are True. If dim is None, output is True if a does not have any zeros, else False.

arrayfire.algorithm.anyTrueByKey(keys, vals, dim=- 1)

Calculate if any elements are true along a specified dimension according to a key.

Parameters

keysaf.Array

One dimensional arrayfire array with reduction keys.

valsaf.Array

Multi dimensional arrayfire array that will be reduced.

dim: optional: int. default: -1

Dimension along which the any true check will occur.

Returns

keys: af.Array or scalar number

The reduced keys of any true check in vals along dimension dim.

values: af.Array or scalar number

Booleans denoting if any elements are true in vals along dimension dim according to keys.

arrayfire.algorithm.any_true(a, dim=None)

Check if any the elements along a specified dimension are true.

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: None

Dimension along which the product is required.

Returns

out: af.Array or scalar number

Af.array containing True if any elements in a along the dimension are True. If dim is None, output is True if a does not have any zeros, else False.

arrayfire.algorithm.count(a, dim=None)

Count the number of non zero elements in an array along a specified dimension.

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: None

Dimension along which the the non zero elements are to be counted.

Returns

out: af.Array or scalar number

The count of non zero elements in a along dim. If dim is None, the total number of non zero elements in a.

arrayfire.algorithm.countByKey(keys, vals, dim=- 1)

Counts non-zero elements along a specified dimension according to a key.

Parameters

keysaf.Array

One dimensional arrayfire array with reduction keys.

valsaf.Array

Multi dimensional arrayfire array that will be reduced.

dim: optional: int. default: -1

Dimension along which to count elements.

Returns

keys: af.Array or scalar number

The reduced keys of count in vals along dimension dim.

values: af.Array or scalar number

Count of non-zero elements in vals along dimension dim according to keys.

arrayfire.algorithm.diff1(a, dim=0)

Find the first order differences along specified dimensions

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: 0

Dimension along which the differences are required.

Returns

out: af.Array

Array whose length along dim is 1 less than that of a.

arrayfire.algorithm.diff2(a, dim=0)

Find the second order differences along specified dimensions

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: 0

Dimension along which the differences are required.

Returns

out: af.Array

Array whose length along dim is 2 less than that of a.

arrayfire.algorithm.imax(a, dim=None)

Find the value and location of the maximum value along a specified dimension

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: None

Dimension along which the maximum value is required.

Returns

(val, idx): tuple of af.Array or scalars

val contains the maximum value of a along dim. idx contains the location of where val occurs in a along dim. If dim is None, val and idx value and location of global maximum.

arrayfire.algorithm.imin(a, dim=None)

Find the value and location of the minimum value along a specified dimension

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: None

Dimension along which the minimum value is required.

Returns

(val, idx): tuple of af.Array or scalars

val contains the minimum value of a along dim. idx contains the location of where val occurs in a along dim. If dim is None, val and idx value and location of global minimum.

arrayfire.algorithm.max(a, dim=None)

Find the maximum value of all the elements along a specified dimension.

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: None

Dimension along which the maximum value is required.

Returns

out: af.Array or scalar number

The maximum value of all elements in a along dimension dim. If dim is None, maximum value of the entire Array is returned.

arrayfire.algorithm.maxByKey(keys, vals, dim=- 1)

Calculate the max of elements along a specified dimension according to a key.

Parameters

keysaf.Array

One dimensional arrayfire array with reduction keys.

valsaf.Array

Multi dimensional arrayfire array that will be reduced.

dim: optional: int. default: -1

Dimension along which the max will occur.

Returns

keys: af.Array or scalar number

The reduced keys of all elements in vals along dimension dim.

values: af.Array or scalar number

The max of all elements in vals along dimension dim according to keys.

arrayfire.algorithm.min(a, dim=None)

Find the minimum value of all the elements along a specified dimension.

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: None

Dimension along which the minimum value is required.

Returns

out: af.Array or scalar number

The minimum value of all elements in a along dimension dim. If dim is None, minimum value of the entire Array is returned.

arrayfire.algorithm.minByKey(keys, vals, dim=- 1)

Calculate the min of elements along a specified dimension according to a key.

Parameters

keysaf.Array

One dimensional arrayfire array with reduction keys.

valsaf.Array

Multi dimensional arrayfire array that will be reduced.

dim: optional: int. default: -1

Dimension along which the min will occur.

Returns

keys: af.Array or scalar number

The reduced keys of all elements in vals along dimension dim.

values: af.Array or scalar number

The min of all elements in vals along dimension dim according to keys

arrayfire.algorithm.product(a, dim=None, nan_val=None)

Calculate the product of all the elements along a specified dimension.

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: None

Dimension along which the product is required.

nan_val: optional: scalar. default: None

The value that replaces NaN in the array

Returns

out: af.Array or scalar number

The product of all elements in a along dimension dim. If dim is None, product of the entire Array is returned.

arrayfire.algorithm.productByKey(keys, vals, dim=- 1, nan_val=None)

Calculate the product of elements along a specified dimension according to a key.

Parameters

keysaf.Array

One dimensional arrayfire array with reduction keys.

valsaf.Array

Multi dimensional arrayfire array that will be reduced.

dim: optional: int. default: -1

Dimension along which the product will occur.

nan_val: optional: scalar. default: None

The value that replaces NaN in the array

Returns

keys: af.Array or scalar number

The reduced keys of all elements in vals along dimension dim.

values: af.Array or scalar number

The product of all elements in vals along dimension dim according to keys

arrayfire.algorithm.scan(a, dim=0, op=<BINARYOP.ADD: 0>, inclusive_scan=True)

Generalized scan of an array.

Parameters

aaf.Array

Multi dimensional arrayfire array.

dimoptional: int. default: 0

Dimension along which the scan is performed.

opoptional: af.BINARYOP. default: af.BINARYOP.ADD.

Binary option the scan algorithm uses. Can be one of: - af.BINARYOP.ADD - af.BINARYOP.MUL - af.BINARYOP.MIN - af.BINARYOP.MAX

inclusive_scan: optional: bool. default: True

Specifies if the scan is inclusive

Returns

outaf.Array

• will contain scan of input.

arrayfire.algorithm.scan_by_key(key, a, dim=0, op=<BINARYOP.ADD: 0>, inclusive_scan=True)

Generalized scan by key of an array.

Parameters

keyaf.Array

key array.

aaf.Array

Multi dimensional arrayfire array.

dimoptional: int. default: 0

Dimension along which the scan is performed.

opoptional: af.BINARYOP. default: af.BINARYOP.ADD.

Binary option the scan algorithm uses. Can be one of: - af.BINARYOP.ADD - af.BINARYOP.MUL - af.BINARYOP.MIN - af.BINARYOP.MAX

inclusive_scan: optional: bool. default: True

Specifies if the scan is inclusive

Returns

outaf.Array

• will contain scan of input.

arrayfire.algorithm.set_intersect(a, b, is_unique=False)

Find the intersect of two arrays.

Parameters

aaf.Array

A 1D arrayfire array.

baf.Array

A 1D arrayfire array.

is_unique: optional: bool. default: False

Specifies if the both inputs contain unique elements.

Returns

out: af.Array

an array values after performing the intersect of a and b.

arrayfire.algorithm.set_union(a, b, is_unique=False)

Find the union of two arrays.

Parameters

aaf.Array

A 1D arrayfire array.

baf.Array

A 1D arrayfire array.

is_unique: optional: bool. default: False

Specifies if the both inputs contain unique elements.

Returns

out: af.Array

an array values after performing the union of a and b.

arrayfire.algorithm.set_unique(a, is_sorted=False)

Find the unique elements of an array.

Parameters

aaf.Array

A 1D arrayfire array.

is_sorted: optional: bool. default: False

Specifies if the input is pre-sorted.

Returns

out: af.Array

an array containing the unique values from a

arrayfire.algorithm.sort(a, dim=0, is_ascending=True)

Sort the array along a specified dimension

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: 0

Dimension along which sort is to be performed.

is_ascending: optional: bool. default: True

Specifies the direction of the sort

Returns

out: af.Array

array containing the sorted values

arrayfire.algorithm.sort_by_key(ik, iv, dim=0, is_ascending=True)

Sort an array based on specified keys

Parameters

ikaf.Array

An Array containing the keys

ivaf.Array

An Array containing the values

dim: optional: int. default: 0

Dimension along which sort is to be performed.

is_ascending: optional: bool. default: True

Specifies the direction of the sort

Returns

(ok, ov): tuple of af.Array

ok contains the values from ik in sorted order ov contains the values from iv after sorting them based on ik

arrayfire.algorithm.sort_index(a, dim=0, is_ascending=True)

Sort the array along a specified dimension and get the indices.

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: 0

Dimension along which sort is to be performed.

is_ascending: optional: bool. default: True

Specifies the direction of the sort

Returns

(val, idx): tuple of af.Array

val is an af.Array containing the sorted values. idx is an af.Array containing the original indices of val in a.

arrayfire.algorithm.sum(a, dim=None, nan_val=None)

Calculate the sum of all the elements along a specified dimension.

Parameters

aaf.Array

Multi dimensional arrayfire array.

dim: optional: int. default: None

Dimension along which the sum is required.

nan_val: optional: scalar. default: None

The value that replaces NaN in the array

Returns

out: af.Array or scalar number

The sum of all elements in a along dimension dim. If dim is None, sum of the entire Array is returned.

arrayfire.algorithm.sumByKey(keys, vals, dim=- 1, nan_val=None)

Calculate the sum of elements along a specified dimension according to a key.

Parameters

keysaf.Array

One dimensional arrayfire array with reduction keys.

valsaf.Array

Multi dimensional arrayfire array that will be reduced.

dim: optional: int. default: -1

Dimension along which the sum will occur.

nan_val: optional: scalar. default: None

The value that replaces NaN in the array

Returns

keys: af.Array or scalar number

The reduced keys of all elements in vals along dimension dim.

values: af.Array or scalar number

The sum of all elements in vals along dimension dim according to keys

arrayfire.algorithm.where(a)

Find the indices of non zero elements

Parameters

aaf.Array

Multi dimensional arrayfire array.

Returns

idx: af.Array

Linear indices for non zero elements.