update test [ci skip]

kthohr · May 28, 2018 · dca3987 · dca3987
1 parent 03e0f40
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Showing 2 changed files with 17 additions and 55 deletions.
diff --git a/README.md b/README.md
@@ -165,6 +165,7 @@ For a data-based example, consider maximum likelihood estimation of a logit mode
 
 // sigmoid function
 
+inline
 arma::mat sigm(const arma::mat& X)
 {
     return 1.0 / (1.0 + arma::exp(-X));
@@ -178,33 +179,6 @@ struct ll_data_t
     arma::mat X;
 };
 
-// log-likelihood function for Adam
-
-double ll_fn(const arma::vec& vals_inp, arma::vec* grad_out, void* opt_data)
-{
-    ll_data_t* objfn_data = reinterpret_cast<ll_data_t*>(opt_data);
-
-    arma::vec Y = objfn_data->Y;
-    arma::mat X = objfn_data->X;
-
-    arma::vec mu = sigm(X*vals_inp);
-
-    const double norm_term = static_cast<double>(Y.n_elem);
-
-    const double obj_val = - arma::accu( Y%arma::log(mu) + (1.0-Y)%arma::log(1.0-mu) ) / norm_term;
-
-    //
-
-    if (grad_out)
-    {
-        *grad_out = X.t() * (mu - Y) / norm_term;
-    }
-
-    //
-
-    return obj_val;
-}
-
 // log-likelihood function with hessian
 
 double ll_fn_whess(const arma::vec& vals_inp, arma::vec* grad_out, arma::mat* hess_out, void* opt_data)
@@ -240,6 +214,13 @@ double ll_fn_whess(const arma::vec& vals_inp, arma::vec* grad_out, arma::mat* he
     return obj_val;
 }
 
+// log-likelihood function for Adam
+
+double ll_fn(const arma::vec& vals_inp, arma::vec* grad_out, void* opt_data)
+{
+    return ll_fn_whess(vals_inp,grad_out,nullptr,opt_data);
+}
+
 //
 
 int main()
@@ -272,7 +253,7 @@ int main()
     optim::algo_settings_t settings;
 
     settings.gd_method = 6;
-    settings.gd_settings.step_size = 0.1; // the 'learning rate'
+    settings.gd_settings.step_size = 0.1;
 
     std::chrono::time_point<std::chrono::system_clock> start = std::chrono::system_clock::now();
 

diff --git a/examples/logit_reg.cpp b/examples/logit_reg.cpp
@@ -8,6 +8,7 @@
 
 // sigmoid function
 
+inline
 arma::mat sigm(const arma::mat& X)
 {
     return 1.0 / (1.0 + arma::exp(-X));
@@ -21,33 +22,6 @@ struct ll_data_t
     arma::mat X;
 };
 
-// log-likelihood function for Adam
-
-double ll_fn(const arma::vec& vals_inp, arma::vec* grad_out, void* opt_data)
-{
-    ll_data_t* objfn_data = reinterpret_cast<ll_data_t*>(opt_data);
-
-    arma::vec Y = objfn_data->Y;
-    arma::mat X = objfn_data->X;
-
-    arma::vec mu = sigm(X*vals_inp);
-
-    const double norm_term = static_cast<double>(Y.n_elem);
-
-    const double obj_val = - arma::accu( Y%arma::log(mu) + (1.0-Y)%arma::log(1.0-mu) ) / norm_term;
-
-    //
-
-    if (grad_out)
-    {
-        *grad_out = X.t() * (mu - Y) / norm_term;
-    }
-
-    //
-
-    return obj_val;
-}
-
 // log-likelihood function with hessian
 
 double ll_fn_whess(const arma::vec& vals_inp, arma::vec* grad_out, arma::mat* hess_out, void* opt_data)
@@ -83,6 +57,13 @@ double ll_fn_whess(const arma::vec& vals_inp, arma::vec* grad_out, arma::mat* he
     return obj_val;
 }
 
+// log-likelihood function for Adam
+
+double ll_fn(const arma::vec& vals_inp, arma::vec* grad_out, void* opt_data)
+{
+    return ll_fn_whess(vals_inp,grad_out,nullptr,opt_data);
+}
+
 //
 
 int main()