arrayfire.algorithm module¶
Vector algorithms (sum, min, sort, etc).
arrayfire.algorithm.accum(a,dim=0)[source]¶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 asa containing the cumulative sum alongdim.
arrayfire.algorithm.allTrueByKey(keys,vals,dim=-1)[source]¶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 invals along dimensiondim.
- values: af.Array or scalar number
Booleans denoting if all elements are true invals along dimensiondim according to keys
arrayfire.algorithm.all_true(a,dim=None)[source]¶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 ina along the dimension are True.Ifdim isNone, output is True ifa does not have any zeros, else False.
arrayfire.algorithm.anyTrueByKey(keys,vals,dim=-1)[source]¶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 invals along dimensiondim.
- values: af.Array or scalar number
Booleans denoting if any elements are true invals along dimensiondim according to keys.
arrayfire.algorithm.any_true(a,dim=None)[source]¶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 ina along the dimension are True.Ifdim isNone, output is True ifa does not have any zeros, else False.
arrayfire.algorithm.count(a,dim=None)[source]¶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 ina alongdim.Ifdim isNone, the total number of non zero elements ina.
arrayfire.algorithm.countByKey(keys,vals,dim=-1)[source]¶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 invals along dimensiondim.
- values: af.Array or scalar number
Count of non-zero elements invals along dimensiondim according to keys.
arrayfire.algorithm.diff1(a,dim=0)[source]¶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 alongdim is 1 less than that ofa.
arrayfire.algorithm.diff2(a,dim=0)[source]¶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 alongdim is 2 less than that ofa.
arrayfire.algorithm.imax(a,dim=None)[source]¶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 ofa alongdim.idx contains the location of whereval occurs ina alongdim.Ifdim isNone,val andidx value and location of global maximum.
arrayfire.algorithm.imin(a,dim=None)[source]¶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 ofa alongdim.idx contains the location of whereval occurs ina alongdim.Ifdim isNone,val andidx value and location of global minimum.
arrayfire.algorithm.max(a,dim=None)[source]¶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 ina along dimensiondim.Ifdim isNone, maximum value of the entire Array is returned.
arrayfire.algorithm.maxByKey(keys,vals,dim=-1)[source]¶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 invals along dimensiondim.
- values: af.Array or scalar number
The max of all elements invals along dimensiondim according to keys.
arrayfire.algorithm.min(a,dim=None)[source]¶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 ina along dimensiondim.Ifdim isNone, minimum value of the entire Array is returned.
arrayfire.algorithm.minByKey(keys,vals,dim=-1)[source]¶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 invals along dimensiondim.
- values: af.Array or scalar number
The min of all elements invals along dimensiondim according to keys
arrayfire.algorithm.product(a,dim=None,nan_val=None)[source]¶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 ina along dimensiondim.Ifdim isNone, product of the entire Array is returned.
arrayfire.algorithm.productByKey(keys,vals,dim=-1,nan_val=None)[source]¶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 invals along dimensiondim.
- values: af.Array or scalar number
The product of all elements invals along dimensiondim according to keys
arrayfire.algorithm.scan(a,dim=0,op=<BINARYOP.ADD:0>,inclusive_scan=True)[source]¶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)[source]¶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)[source]¶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 ofa andb.
arrayfire.algorithm.set_union(a,b,is_unique=False)[source]¶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 ofa andb.
arrayfire.algorithm.set_unique(a,is_sorted=False)[source]¶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 froma
arrayfire.algorithm.sort(a,dim=0,is_ascending=True)[source]¶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)[source]¶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 fromik in sorted orderov contains the values fromiv after sorting them based onik
arrayfire.algorithm.sort_index(a,dim=0,is_ascending=True)[source]¶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 ofval ina.
arrayfire.algorithm.sum(a,dim=None,nan_val=None)[source]¶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 ina along dimensiondim.Ifdim isNone, sum of the entire Array is returned.
arrayfire.algorithm.sumByKey(keys,vals,dim=-1,nan_val=None)[source]¶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 invals along dimensiondim.
- values: af.Array or scalar number
The sum of all elements invals along dimensiondim according to keys
