[Vxl-users] Baffling change to the parameters for vnl_sparse_lst_sqr_function

[Mike P. <mi...@di...>]

Hi all – could use a hand with an issue relating to vnl_sparse_lst_sqr_function. 

 

In short, its signature changed between 1.14 and 1.17, and I need to understand how to call the 1.17 version to get the same results as I was getting with 1.14.

 

At 1.17 the call I was using grew two extra parameters “int num_params_c”, and “UseWeights w = no_weights”.

 

I tried setting num_params_c to zero and going with the default for w, but I’m getting meaningless results.

 

Can anyone tell me how to call into the 1.17 version to achieve the equivalent of the 1.14 call?

 

The signatures from the code are below incidentally.

 

Thanks

 

Mike Pelton

Digicave Ltd

 

Signature at 1.17:

 

  //: Construct vnl_sparse_lst_sqr_function.

  // Assumes A consists of \p num_a parameters each of size \p num_params_per_a

  // Assumes B consists of \p num_b parameters each of size \p num_params_per_b

  // Assumes C consists of \p num_params_c parameters

  // \p xmask is a mask for residual availability.  residual e_ij exists only if mask[i][j]==true

  // Assumes each available residual has size \p num_residuals_per_e

  // The optional argument should be no_gradient if the gradf function has not

  // been implemented.  Default is use_gradient.

  vnl_sparse_lst_sqr_function(unsigned int num_a,

                              unsigned int num_params_per_a,

                              unsigned int num_b,

                              unsigned int num_params_per_b,

                              unsigned int num_params_c,

                              const vcl_vector<vcl_vector<bool> >& xmask,

                              unsigned int num_residuals_per_e,

                              UseGradient g = use_gradient,

                              UseWeights w = no_weights);

 

==================================

 

Signature at 1.14

 

 

  //: Construct vnl_sparse_lst_sqr_function.

  // Assumes A consists of \p num_a parameters each of size \p num_params_per_a

  // Assumes B consists of \p num_b parameters each of size \p num_params_per_b

  // \p xmask is a mask for residual availability.  residual e_ij exists only if mask[i][j]==true

  // Assumes each available residual has size \p num_residuals_per_e

  // The optional argument should be no_gradient if the gradf function has not

  // been implemented.  Default is use_gradient.

  vnl_sparse_lst_sqr_function(unsigned int num_a,

                              unsigned int num_params_per_a,

                              unsigned int num_b,

                              unsigned int num_params_per_b,

                              const vcl_vector<vcl_vector<bool> >& xmask,

                              unsigned int num_residuals_per_e,

                              UseGradient g = use_gradient);

 

 

==========================

 

Mike Pelton

 <http://www.linkedin.com/profile/view?id=4601230&trk=nav_responsive_tab_profile> Senior Software Engineer

 

phone: +44 (0)1273 748 456

email:  <mailto:mi...@di...> mi...@di...

web:  <http://www.digicave.com/> www.digicave.com

Digicave Ltd

3 Orange Row


Brighton

East Sussex

BN1 1UQ

 

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