{{alias}}( N, x, stride ) Computes the arithmetic mean of a single-precision floating-point strided array. The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. If `N <= 0`, the function returns `NaN`. Parameters ---------- N: integer Number of indexed elements. x: Float32Array Input array. stride: integer Index increment. Returns ------- out: float The arithmetic mean. Examples -------- // Standard Usage: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] ); > {{alias}}( x.length, x, 1 ) ~0.3333 // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); > var stride = 2; > {{alias}}( N, x, stride ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); > stride = 2; > {{alias}}( N, x1, stride ) ~-0.3333 {{alias}}.ndarray( N, x, stride, offset ) Computes the arithmetic mean of a single-precision floating-point strided array using alternative indexing semantics. While typed array views mandate a view offset based on the underlying buffer, the `offset` parameter supports indexing semantics based on a starting index. Parameters ---------- N: integer Number of indexed elements. x: Float32Array Input array. stride: integer Index increment. offset: integer Starting index. Returns ------- out: float The arithmetic mean. Examples -------- // Standard Usage: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] ); > {{alias}}.ndarray( x.length, x, 1, 0 ) ~0.3333 // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); > {{alias}}.ndarray( N, x, 2, 1 ) ~-0.3333 See Also --------