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QPALM
1.2.1
Proximal Augmented Lagrangian method for Quadratic Programs
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Problem data scaling during setup.
This file includes the routine that is called during setup to scale the problem data, and initial guesses if the problem is warm-started. Scaling the problem is useful to prevent large changes in the active set and to guard against ill-conditioning in the objective function.
Definition in file scaling.c.
Include dependency graph for scaling.c:Go to the source code of this file.
Functions | |
| void | limit_scaling (c_float *D, size_t n) |
| void | scale_data (QPALMWorkspace *work) |
| Scale problem matrices. | |
| void | unscale_data (QPALMWorkspace *work) |
| Unscale the problem data. | |
| void limit_scaling | ( | c_float * | D, |
| size_t | n | ||
| ) |
| void scale_data | ( | QPALMWorkspace * | work | ) |
Scale problem matrices.
Ruiz scaling [4] is applied to the constraint matrix A. This means that the rows and columns of A are scaled elementwise by the square root of their infinity norm, and this for a number of work->settings->scaling iterations. The resulting scaling can be written as
| work | Workspace |
Definition at line 31 of file scaling.c.
Here is the call graph for this function:| void unscale_data | ( | QPALMWorkspace * | work | ) |