You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
@@ -32,7 +32,7 @@ var dger = require( '@stdlib/blas/base/dger' );
32
32
33
33
#### dger( ord, M, N, α, x, sx, y, sy, A, lda )
34
34
35
-
Performs the rank 1 operation `A = α*x*y^T + A`, where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector and `A` is an `M` by `N` matrix.
35
+
Performs the rank 1 operation `A = α*x*y^T + A`, where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M` by `N` matrix.
-**A**: input matrix stored in linear memory as a [`Float64Array`][mdn-float64array].
59
59
-**lda**: stride of the first dimension of `A` (leading dimension of `A`).
60
60
61
-
The stride parameters determine how operations are performed. For example, to iterate over every other element in `x` and `y`,
61
+
The stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to iterate over every other element in `x` and `y`,
#### dger.ndarray( M, N, α, x, sx, ox, y, sy, oy, A, sa1, sa2, oa )
95
95
96
-
Performs the rank 1 operation `A = α*x*y^T + A`, using alternative indexing semantics and where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector and `A` is an `M` by `N` matrix.
96
+
Performs the rank 1 operation `A = α*x*y^T + A`, using alternative indexing semantics and where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M` by `N` matrix.
#### c_dger( layout, M, N, alpha, \*X, strideX, \*Y, strideY, \*A, LDA )
204
204
205
-
TODO.
205
+
Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M`-by-`N` matrix.
206
206
207
207
```c
208
-
TODO
208
+
#include"stdlib/blas/base/shared.h"
209
+
210
+
double A[ 3*4 ] = {
211
+
0.0, 0.0, 0.0, 0.0,
212
+
0.0, 0.0, 0.0, 0.0,
213
+
0.0, 0.0, 0.0, 0.0
214
+
};
215
+
216
+
constdouble x[ 3 ] = { 1.0, 4.0, 0.0 };
217
+
const double y[ 4 ] = { 0.0, 1.0, 2.0, 3.0 };
218
+
219
+
c_dger( CblasRowMajor, 3, 4, 1.0, x, 1, y, 1, A, 4 );
209
220
```
210
221
211
-
TODO
222
+
The function accepts the following arguments:
223
+
224
+
- **layout**: `[in] CBLAS_LAYOUT` storage layout.
225
+
- **M**: `[in] CBLAS_INT` number of rows in the matrix `A`.
226
+
- **N**: `[in] CBLAS_INT` number of columns in the matrix `A`.
227
+
- **alpha**: `[in] double` scalar constant.
228
+
- **X**: `[in] double*` an `M` element vector.
229
+
- **strideX**: `[in] CBLAS_INT` stride length for `X`.
230
+
- **Y**: `[in] double*` an `N` element vector.
231
+
- **strideY**: `[in] CBLAS_INT` stride length for `Y`.
232
+
- **A**: `[inout] double*` input matrix.
233
+
- **LDA**: `[in] CBLAS_INT` stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`).
#### c_dger_ndarray( M, N, alpha, \*X, sx, ox, \*Y, sy, oy, \*A, sa1, sa2, oa )
240
+
241
+
Performs the rank 1 operation `A = alpha*x*y^T + A`, using alternative indexing semantics and where `alpha` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M`-by-`N` matrix.
242
+
243
+
```c
244
+
#include"stdlib/blas/base/shared.h"
245
+
246
+
double A[ 3*4 ] = {
247
+
0.0, 0.0, 0.0, 0.0,
248
+
0.0, 0.0, 0.0, 0.0,
249
+
0.0, 0.0, 0.0, 0.0
250
+
};
251
+
252
+
constdouble x[ 3 ] = { 1.0, 4.0, 0.0 };
253
+
const double y[ 4 ] = { 0.0, 1.0, 2.0, 3.0 };
254
+
255
+
c_dger_ndarray( 3, 4, 1.0, x, 1, 0, y, 1, 0, A, 4, 1, 0 );
256
+
```
257
+
258
+
The function accepts the following arguments:
259
+
260
+
- **layout**: `[in] CBLAS_LAYOUT` storage layout.
261
+
- **M**: `[in] CBLAS_INT` number of rows in the matrix `A`.
262
+
- **N**: `[in] CBLAS_INT` number of columns in the matrix `A`.
263
+
- **alpha**: `[in] double` scalar constant.
264
+
- **X**: `[in] double*` an `M` element vector.
265
+
- **sx**: `[in] CBLAS_INT` stride length for `X`.
266
+
- **ox**: `[in] CBLAS_INT` starting index for `X`.
267
+
- **Y**: `[in] double*` an `N` element vector.
268
+
- **sy**: `[in] CBLAS_INT` stride length for `Y`.
269
+
- **oy**: `[in] CBLAS_INT` starting index for `Y`.
270
+
- **A**: `[inout] double*` input matrix.
271
+
- **sa1**: `[in] CBLAS_INT` stride of the first dimension of `A`.
272
+
- **sa2**: `[in] CBLAS_INT` stride of the second dimension of `A`.
273
+
- **oa**: `[in] CBLAS_INT` starting index for `A`.
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/blas/base/dger/docs/types/index.d.ts
+3-3Lines changed: 3 additions & 3 deletions
Original file line number
Diff line number
Diff line change
@@ -27,7 +27,7 @@ import { Layout } from '@stdlib/types/blas';
27
27
*/
28
28
interfaceRoutine{
29
29
/**
30
-
* Performs the rank 1 operation `A = α*x*y^T + A`, where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector and `A` is an `M` by `N` matrix.
30
+
* Performs the rank 1 operation `A = α*x*y^T + A`, where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M` by `N` matrix.
* Performs the rank 1 operation `A = α*x*y^T + A`, using alternative indexing semantics and where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector and `A` is an `M` by `N` matrix.
57
+
* Performs the rank 1 operation `A = α*x*y^T + A`, using alternative indexing semantics and where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M` by `N` matrix.
58
58
*
59
59
* @param M - number of rows in the matrix `A`
60
60
* @param N - number of columns in the matrix `A`
@@ -85,7 +85,7 @@ interface Routine {
85
85
}
86
86
87
87
/**
88
-
* Performs the rank 1 operation `A = α*x*y^T + A`, where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector and `A` is an `M` by `N` matrix.
88
+
* Performs the rank 1 operation `A = α*x*y^T + A`, where `α` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M` by `N` matrix.
* Performs the rank 1 operation `A = alpha*x*y^T + A`, using alternative indexing semantics and where `alpha` is a scalar, `x` is an `M` element vector, `y` is an `N` element vector, and `A` is an `M`-by-`N` matrix.
0 commit comments