repl.txt (3624B)
1 2 {{alias}}( N, sum, x, strideX, y, strideY ) 3 Computes the cumulative sum of single-precision floating-point strided array 4 elements using a second-order iterative Kahan–Babuška algorithm. 5 6 The `N` and `stride` parameters determine which elements in `x` and `y` are 7 accessed at runtime. 8 9 Indexing is relative to the first index. To introduce an offset, use a typed 10 array view. 11 12 If `N <= 0`, the function returns `y` unchanged. 13 14 Parameters 15 ---------- 16 N: integer 17 Number of indexed elements. 18 19 sum: number 20 Initial sum. 21 22 x: Float32Array 23 Input array. 24 25 strideX: integer 26 Index increment for `x`. 27 28 y: Float32Array 29 Output array. 30 31 strideY: integer 32 Index increment for `y`. 33 34 Returns 35 ------- 36 out: Float32Array 37 Output array. 38 39 Examples 40 -------- 41 // Standard Usage: 42 > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] ); 43 > var y = new {{alias:@stdlib/array/float32}}( x.length ); 44 > {{alias}}( x.length, 0.0, x, 1, y, 1 ) 45 <Float32Array>[ 1.0, -1.0, 1.0 ] 46 47 // Using `N` and `stride` parameters: 48 > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); 49 > y = new {{alias:@stdlib/array/float32}}( x.length ); 50 > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); 51 > {{alias}}( N, 0.0, x, 2, y, 2 ) 52 <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] 53 54 // Using view offsets: 55 > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); 56 > var y0 = new {{alias:@stdlib/array/float32}}( x0.length ); 57 > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); 58 > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); 59 > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); 60 > {{alias}}( N, 0.0, x1, 2, y1, 1 ) 61 <Float32Array>[ -2.0, 0.0, -1.0 ] 62 > y0 63 <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] 64 65 {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) 66 Computes the cumulative sum of single-precision floating-point strided array 67 elements using a second-order iterative Kahan–Babuška algorithm and 68 alternative indexing semantics. 69 70 While typed array views mandate a view offset based on the underlying 71 buffer, the `offset` parameter supports indexing semantics based on a 72 starting index. 73 74 Parameters 75 ---------- 76 N: integer 77 Number of indexed elements. 78 79 sum: number 80 Initial sum. 81 82 x: Float32Array 83 Input array. 84 85 strideX: integer 86 Index increment for `x`. 87 88 offsetX: integer 89 Starting index for `x`. 90 91 y: Float32Array 92 Output array. 93 94 strideY: integer 95 Index increment for `y`. 96 97 offsetY: integer 98 Starting index for `y`. 99 100 Returns 101 ------- 102 out: Float32Array 103 Output array. 104 105 Examples 106 -------- 107 // Standard Usage: 108 > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] ); 109 > var y = new {{alias:@stdlib/array/float32}}( x.length ); 110 > {{alias}}.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 ) 111 <Float32Array>[ 1.0, -1.0, 1.0 ] 112 113 // Advanced indexing: 114 > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); 115 > y = new {{alias:@stdlib/array/float32}}( x.length ); 116 > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); 117 > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) 118 <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] 119 120 See Also 121 -------- 122