Usage

`javascript
var scnrm2 = require( '@stdlib/blas-base-wasm-scnrm2' );
`

#### scnrm2.main( N, x, strideX )

Calculates the L2-norm of a complex single-precision floating-point vector.

`javascript
var Complex64Array = require( '@stdlib/array-complex64' );

var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );

var z = scnrm2.main( 3, x, 1 );
// returns ~9.54
`

The function has the following parameters:

- N: number of indexed elements.
- x: input [Complex64Array][@stdlib/array/complex64].
- strideX: index increment for x.

The N and stride parameters determine which elements in the input strided array are accessed at runtime. For example, to compute the L2-norm of every other element in x,

`javascript
var Complex64Array = require( '@stdlib/array-complex64' );

var x = new Complex64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );

var z = scnrm2.main( 2, x, 2 );
// returns ~4.24
`

Note that indexing is relative to the first index. To introduce an offset, use [typed array][mdn-typed-array] views.

`javascript
var Complex64Array = require( '@stdlib/array-complex64' );

// Initial array:
var x0 = new Complex64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, -2.0, 2.0, 3.0 ] );

// Create a typed array view:
var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var z = scnrm2.main( 2, x1, 2 );
// returns ~4.58
`

#### scnrm2.ndarray( N, x, strideX, offsetX )

Calculates the L2-norm of a complex single-precision floating-point vector using alternative indexing semantics.

`javascript
var Complex64Array = require( '@stdlib/array-complex64' );

var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );

var z = scnrm2.ndarray( 3, x, 1, 0 );
// returns ~9.54
`

The function has the following additional parameters:

- offsetX: starting index for x.

While [typed array][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the L2-norm for every other value in x starting from the second value,

`javascript
var Complex64Array = require( '@stdlib/array-complex64' );

var x = new Complex64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, -2.0, 2.0, 3.0 ] );

var z = scnrm2.ndarray( 2, x, 2, 1 );
// returns ~4.58
`

*

$3

#### scnrm2.Module( memory )

Returns a new WebAssembly [module wrapper][@stdlib/wasm/module-wrapper] instance which uses the provided WebAssembly [memory][@stdlib/wasm/memory] instance as its underlying memory.

`javascript
var Memory = require( '@stdlib/wasm-memory' );

// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
var mem = new Memory({
'initial': 10,
'maximum': 100
});

// Create a BLAS routine:
var mod = new scnrm2.Module( mem );
// returns

// Initialize the routine:
mod.initializeSync();
`

#### scnrm2.Module.prototype.main( N, xp, sx )

Computes the L2-norm of a complex single-precision floating-point vector.

`javascript
var Memory = require( '@stdlib/wasm-memory' );
var oneTo = require( '@stdlib/array-one-to' );
var Complex64Array = require( '@stdlib/array-complex64' );

// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
var mem = new Memory({
'initial': 10,
'maximum': 100
});

// Create a BLAS routine:
var mod = new scnrm2.Module( mem );
// returns

// Initialize the routine:
mod.initializeSync();

// Define a vector data type:
var dtype = 'complex64';

// Specify a vector length:
var N = 5;

// Define a pointer (i.e., byte offset) for storing the input vector:
var xptr = 0;

// Write vector values to module memory:
var xbuf = oneTo( N*2, 'float32' );
var x = new Complex64Array( xbuf.buffer );
mod.write( xptr, x );

// Perform computation:
var out = mod.main( N, xptr, 1 );
// returns ~19.62
`

The function has the following parameters:

- N: number of indexed elements.
- xp: input [Complex64Array][@stdlib/array/complex64] pointer (i.e., byte offset).
- sx: index increment for x.

#### scnrm2.Module.prototype.ndarray( N, xp, sx, ox )

Computes the L2-norm of a complex single-precision floating-point vector using alternative indexing semantics.

`javascript
var Memory = require( '@stdlib/wasm-memory' );
var oneTo = require( '@stdlib/array-one-to' );
var Complex64Array = require( '@stdlib/array-complex64' );

// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
var mem = new Memory({
'initial': 10,
'maximum': 100
});

// Create a BLAS routine:
var mod = new scnrm2.Module( mem );
// returns

// Initialize the routine:
mod.initializeSync();

// Define a vector data type:
var dtype = 'complex64';

// Specify a vector length:
var N = 5;

// Define a pointer (i.e., byte offset) for storing the input vector:
var xptr = 0;

// Write vector values to module memory:
var xbuf = oneTo( N*2, 'float32' );
var x = new Complex64Array( xbuf.buffer );
mod.write( xptr, x );

// Perform computation:
var out = mod.ndarray( N, xptr, 1, 0 );
// returns ~19.62
`

The function has the following additional parameters:

- ox: starting index for x.