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Assign element values from a broadcasted input
ndarrayto corresponding elements in an outputndarrayview.
npm install @stdlib/ndarray-slice-assignAlternatively,
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varsliceAssign=require('@stdlib/ndarray-slice-assign');Assigns element values from a broadcasted input ndarray to corresponding elements in an output ndarray view.
varSlice=require('@stdlib/slice-ctor');varMultiSlice=require('@stdlib/slice-multi');varndarray=require('@stdlib/ndarray-ctor');varndzeros=require('@stdlib/ndarray-zeros');varndarray2array=require('@stdlib/ndarray-to-array');// Define an input array:varbuffer=[1.0,2.0,3.0,4.0,5.0,6.0];varshape=[3,2];varstrides=[2,1];varoffset=0;varx=ndarray('generic',buffer,shape,strides,offset,'row-major');// returns <ndarray>varsh=x.shape;// returns [ 3, 2 ]vararr=ndarray2array(x);// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ]// Define an output array:vary=ndzeros([2,3,2],{'dtype': x.dtype});// Create a slice:vars0=null;vars1=newSlice(null,null,-1);vars2=newSlice(null,null,-1);vars=newMultiSlice(s0,s1,s2);// returns <MultiSlice>// Perform assignment:varout=sliceAssign(x,y,s);// returns <ndarray>varbool=(out===y);// returns truearr=ndarray2array(y);// returns [ [ [ 6.0, 5.0 ], [ 4.0, 3.0 ], [ 2.0, 1.0 ] ], [ [ 6.0, 5.0 ], [ 4.0, 3.0 ], [ 2.0, 1.0 ] ] ]The function accepts the following arguments:
- x: input
ndarray. - y: output
ndarray. - s: a
MultiSliceinstance, an array of slice arguments, or slice arguments as separate arguments. - options: function options.
The function supports three (mutually exclusive) means for providing slice arguments:
- providing a single
MultiSliceinstance. - providing a single array of slice arguments.
- providing slice arguments as separate arguments.
The following example demonstrates each invocation style achieving equivalent results.
varSlice=require('@stdlib/slice-ctor');varMultiSlice=require('@stdlib/slice-multi');varscalar2ndarray=require('@stdlib/ndarray-from-scalar');varndzeros=require('@stdlib/ndarray-zeros');varndarray2array=require('@stdlib/ndarray-to-array');// 1. Using a MultiSlice:varx=scalar2ndarray(10.0);vary=ndzeros([2,3]);vars0=0;vars1=newSlice(1,null,1);vars=newMultiSlice(s0,s1);// returns <MultiSlice>varout=sliceAssign(x,y,s);// returns <ndarray>vararr=ndarray2array(out);// returns [ [ 0.0, 10.0, 10.0 ], [ 0.0, 0.0, 0.0 ] ]// 2. Using an array of slice arguments:x=scalar2ndarray(10.0);y=ndzeros([2,3]);out=sliceAssign(x,y,[s0,s1]);// returns <ndarray>arr=ndarray2array(out);// returns [ [ 0.0, 10.0, 10.0 ], [ 0.0, 0.0, 0.0 ] ]// 3. Providing separate arguments:x=scalar2ndarray(10.0);y=ndzeros([2,3]);out=sliceAssign(x,y,s0,s1);// returns <ndarray>arr=ndarray2array(out);// returns [ [ 0.0, 10.0, 10.0 ], [ 0.0, 0.0, 0.0 ] ]The function supports the following options:
- strict: boolean indicating whether to enforce strict bounds checking.
By default, the function throws an error when provided a slice which exceeds array bounds. To ignore slice indices exceeding array bounds, set the strict option to false.
varSlice=require('@stdlib/slice-ctor');varMultiSlice=require('@stdlib/slice-multi');varscalar2ndarray=require('@stdlib/ndarray-from-scalar');varndzeros=require('@stdlib/ndarray-zeros');varndarray2array=require('@stdlib/ndarray-to-array');// Define an input array:varx=scalar2ndarray(10.0);// Define an output array:vary=ndzeros([3,2],{'dtype': x.dtype});// Create a slice:vars0=newSlice(1,null,1);vars1=newSlice(10,20,1);vars=newMultiSlice(s0,s1);// returns <MultiSlice>// Perform assignment:varout=sliceAssign(x,y,s,{'strict': false});// returns <ndarray>vararr=ndarray2array(y);// returns [ [ 0.0, 0.0 ], [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]- An output
ndarraymust be writable. If provided a read-onlyndarray, the function throws an error. - A slice argument must be either a
Slice, an integer,null, orundefined. - The number of slice dimensions must match the number of output array dimensions. Hence, if
yis a zero-dimensionalndarray, then, ifsis aMultiSlice,sshould be empty, and, ifsis an array,sshould not contain any slice arguments. Similarly, ifyis a one-dimensionalndarray, then, ifsis aMultiSlice,sshould have one slice dimension, and, ifsis an array,sshould contain a single slice argument. And so on and so forth. - The input
ndarraymust be broadcast compatible with the outputndarrayview. - The input
ndarraymust have a data type which can be safely cast to the outputndarraydata type. Floating-point data types (both real and complex) are allowed to downcast to a lower precision data type of the same kind (e.g., element values from a'float64'inputndarraycan be assigned to corresponding elements in a'float32'outputndarray).
varE=require('@stdlib/slice-multi');varscalar2ndarray=require('@stdlib/ndarray-from-scalar');varndarray2array=require('@stdlib/ndarray-to-array');varndzeros=require('@stdlib/ndarray-zeros');varslice=require('@stdlib/ndarray-slice');varsliceAssign=require('@stdlib/ndarray-slice-assign');// Alias `null` to allow for more compact indexing expressions:var_=null;// Create an output ndarray:vary=ndzeros([3,3,3]);// Update each matrix...vars1=E(0,_,_);sliceAssign(scalar2ndarray(100),y,s1);vara1=ndarray2array(slice(y,s1));// returns [ [ 100, 100, 100 ], [ 100, 100, 100 ], [ 100, 100, 100 ] ]vars2=E(1,_,_);sliceAssign(scalar2ndarray(200),y,s2);vara2=ndarray2array(slice(y,s2));// returns [ [ 200, 200, 200 ], [ 200, 200, 200 ], [ 200, 200, 200 ] ]vars3=E(2,_,_);sliceAssign(scalar2ndarray(300),y,s3);vara3=ndarray2array(slice(y,s3));// returns [ [ 300, 300, 300 ], [ 300, 300, 300 ], [ 300, 300, 300 ] ]// Update the second rows in each matrix:vars4=E(_,1,_);sliceAssign(scalar2ndarray(400),y,s4);vara4=ndarray2array(slice(y,s4));// returns [ [ 400, 400, 400 ], [ 400, 400, 400 ], [ 400, 400, 400 ] ]// Update the second columns in each matrix:vars5=E(_,_,1);sliceAssign(scalar2ndarray(500),y,s5);vara5=ndarray2array(slice(y,s5));// returns [ [ 500, 500, 500 ], [ 500, 500, 500 ], [ 500, 500, 500 ] ]// Return the contents of the entire ndarray:vara6=ndarray2array(y);/* returns [ [ [ 100, 500, 100 ], [ 400, 500, 400 ], [ 100, 500, 100 ] ], [ [ 200, 500, 200 ], [ 400, 500, 400 ], [ 200, 500, 200 ] ], [ [ 300, 500, 300 ], [ 400, 500, 400 ], [ 300, 500, 300 ] ] ]*/@stdlib/ndarray-array: multidimensional arrays.@stdlib/ndarray-ctor: multidimensional array constructor.@stdlib/ndarray-slice: return a read-only view of an input ndarray.
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