---
title: "sparse_elementwise_norm_float(_:_:)"
framework: accelerate
role: symbol
role_heading: Function
path: "accelerate/sparse_elementwise_norm_float(_:_:)"
---

# sparse_elementwise_norm_float(_:_:)

Computes the specified element-wise norm of the single-precision sparse matrix A.

## Declaration

```swift
func sparse_elementwise_norm_float(_ A: sparse_matrix_float!, _ norm: sparse_norm) -> Float
```

## Parameters

- `A`: The sparse matrix, A.
- `norm`: Specify the norm to be computed. Must be one of doc://com.apple.accelerate/documentation/Accelerate/SPARSE_NORM_ONE, doc://com.apple.accelerate/documentation/Accelerate/SPARSE_NORM_TWO, doc://com.apple.accelerate/documentation/Accelerate/SPARSE_NORM_INF, or doc://com.apple.accelerate/documentation/Accelerate/SPARSE_NORM_R1. See discussion for further details.

## Return Value

Return Value The requested norm.

## Discussion

Discussion This is the norm of the matrix treated as a vector, not the operator norm. Specify one of: | SPARSE_NORM_ONE | sum over i,j ( | A[i,j] | ) | |—|—| | SPARSE_NORM_TWO | sqrt ( sum over i,j (A[i,j])² ) | | SPARSE_NORM_INF | max over i,j ( | A[i,j] | ) | | SPARSE_NORM_R1 | sum over j ( sqrt ( sum over i ( A[i,j]² ) ) ) | If norm is not one of the enumerated norm types, the default value is SPARSE_NORM_INF. important: Apple provides the BLAS and LAPACK libraries under the Accelerate framework to be in line with LAPACK 3.9.1. Starting with iOS 26, iPadOS 26, macOS 26, tvOS 26, visionOS 26, and watchOS 26, the libraries are in line with LAPACK 3.12.0. These new interfaces provide additional functionality, as well as a new ILP64 interface. To use the new interfaces, define ACCELERATE_NEW_LAPACK before including the Accelerate or vecLib headers. For ILP64 interfaces, also define ACCELERATE_LAPACK_ILP64. For Swift projects, specify ACCELERATE_NEW_LAPACK=1 and ACCELERATE_LAPACK_ILP64=1 as preprocessor macros in Xcode build settings under Apple Clang - Preprocessing > Preprocessor Macros.

## See Also

### Matrix-Vector Operations

- [sparse_matrix_vector_product_dense_double(_:_:_:_:_:_:_:)](accelerate/sparse_matrix_vector_product_dense_double(_:_:_:_:_:_:_:).md)
- [sparse_matrix_vector_product_dense_float(_:_:_:_:_:_:_:)](accelerate/sparse_matrix_vector_product_dense_float(_:_:_:_:_:_:_:).md)
- [sparse_vector_triangular_solve_dense_double(_:_:_:_:_:)](accelerate/sparse_vector_triangular_solve_dense_double(_:_:_:_:_:).md)
- [sparse_vector_triangular_solve_dense_float(_:_:_:_:_:)](accelerate/sparse_vector_triangular_solve_dense_float(_:_:_:_:_:).md)
- [sparse_outer_product_dense_double(_:_:_:_:_:_:_:_:_:)](accelerate/sparse_outer_product_dense_double(_:_:_:_:_:_:_:_:_:).md)
- [sparse_outer_product_dense_float(_:_:_:_:_:_:_:_:_:)](accelerate/sparse_outer_product_dense_float(_:_:_:_:_:_:_:_:_:).md)
- [sparse_permute_rows_double(_:_:)](accelerate/sparse_permute_rows_double(_:_:).md)
- [sparse_permute_rows_float(_:_:)](accelerate/sparse_permute_rows_float(_:_:).md)
- [sparse_permute_cols_double(_:_:)](accelerate/sparse_permute_cols_double(_:_:).md)
- [sparse_permute_cols_float(_:_:)](accelerate/sparse_permute_cols_float(_:_:).md)
- [sparse_elementwise_norm_double(_:_:)](accelerate/sparse_elementwise_norm_double(_:_:).md)
- [sparse_operator_norm_double(_:_:)](accelerate/sparse_operator_norm_double(_:_:).md)
- [sparse_operator_norm_float(_:_:)](accelerate/sparse_operator_norm_float(_:_:).md)
- [sparse_matrix_trace_double(_:_:)](accelerate/sparse_matrix_trace_double(_:_:).md)
- [sparse_matrix_trace_float(_:_:)](accelerate/sparse_matrix_trace_float(_:_:).md)