repl.txt (4080B)
1 2 {{alias}}( N, x, strideX, y, strideY ) 3 Computes the dot product of two single-precision floating-point vectors with 4 extended accumulation and result. 5 6 The `N`, `strideX`, and `strideY` parameters determine which elements in `x` 7 and `y` are 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 `0.0`. 13 14 Parameters 15 ---------- 16 N: integer 17 Number of indexed elements. 18 19 x: Float32Array 20 First input array. 21 22 strideX: integer 23 Index increment for `x`. 24 25 y: Float32Array 26 Second input array. 27 28 strideY: integer 29 Index increment for `y`. 30 31 Returns 32 ------- 33 dot: number 34 The dot product of `x` and `y`. 35 36 Examples 37 -------- 38 // Standard usage: 39 > var x = new {{alias:@stdlib/array/float32}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); 40 > var y = new {{alias:@stdlib/array/float32}}( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); 41 > var dot = {{alias}}( x.length, x, 1, y, 1 ) 42 -5.0 43 44 // Strides: 45 > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); 46 > y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); 47 > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); 48 > dot = {{alias}}( N, x, 2, y, -1 ) 49 9.0 50 51 // Using view offsets: 52 > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); 53 > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); 54 > var x1 = new {{alias:@stdlib/array/float32}}( x.buffer, x.BYTES_PER_ELEMENT*1 ); 55 > var y1 = new {{alias:@stdlib/array/float32}}( y.buffer, y.BYTES_PER_ELEMENT*3 ); 56 > N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); 57 > dot = {{alias}}( N, x1, -2, y1, 1 ) 58 128.0 59 60 {{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) 61 Computes the dot product of two single-precision floating-point vectors 62 using alternative indexing semantics and with extended accumulation and 63 result. 64 65 While typed array views mandate a view offset based on the underlying 66 buffer, the `offsetX` and `offsetY` parameters support indexing based on a 67 starting index. 68 69 Parameters 70 ---------- 71 N: integer 72 Number of indexed elements. 73 74 x: Float32Array 75 First input array. 76 77 strideX: integer 78 Index increment for `x`. 79 80 offsetX: integer 81 Starting index for `x`. 82 83 y: Float32Array 84 Second input array. 85 86 strideY: integer 87 Index increment for `y`. 88 89 offsetY: integer 90 Starting index for `y`. 91 92 Returns 93 ------- 94 dot: number 95 The dot product of `x` and `y`. 96 97 Examples 98 -------- 99 // Standard usage: 100 > var x = new {{alias:@stdlib/array/float32}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ); 101 > var y = new {{alias:@stdlib/array/float32}}( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ); 102 > var dot = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) 103 -5.0 104 105 // Strides: 106 > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); 107 > y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); 108 > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); 109 > dot = {{alias}}.ndarray( N, x, 2, 0, y, 2, 0 ) 110 9.0 111 112 // Using offset indices: 113 > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); 114 > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); 115 > N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); 116 > dot = {{alias}}.ndarray( N, x, -2, x.length-1, y, 1, 3 ) 117 128.0 118 119 References 120 ---------- 121 - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald 122 Kincaid. 1979. "Algorithm 539: Basic Linear Algebra Subprograms for Fortran 123 Usage [F1]." *ACM Transactions on Mathematical Software* 5 (3). New York, 124 NY, USA: Association for Computing Machinery: 324–25. 125 doi:10.1145/355841.355848. 126 127 See Also 128 -------- 129