Load vars in initial data

dinatraykova · Mar 27, 2024 · 2171d67 · 2171d67
1 parent 41457c7
commit 2171d67
Showing 1 changed file with 21 additions and 27 deletions.
diff --git a/Examples/Fluid_Kerr/InitialFluidData.hpp b/Examples/Fluid_Kerr/InitialFluidData.hpp
@@ -20,10 +20,6 @@
 // aka Kevin data
 class InitialFluidData
 {
-    // Now the non grid ADM vars
-    template <class data_t>
-    using MetricVars = ADMConformalVars::VarsWithGauge<data_t>;
-
   public:
     //! A structure for the input params for fluid properties and initial
     //! conditions
@@ -45,50 +41,48 @@ class InitialFluidData
     //! Function to compute the value of all the initial vars on the grid
     template <class data_t> void compute(Cell<data_t> current_cell) const
     {
+        // load vars
+        FluidCCZ4RHS<PerfectFluid<>>::Vars<data_t> vars;
+        VarsTools::assign(vars, 0.);
         // where am i?
         Coordinates<data_t> coords(current_cell, m_dx, m_params.center);
         data_t rr = coords.get_radius();
         data_t rr2 = rr * rr;
 
-        const auto metric_vars = current_cell.template load_vars<MetricVars>();
-
         data_t x = coords.x;
         double y = coords.y;
         double z = coords.z;
 
-        Tensor<1, data_t> vi, Sj;
-        data_t chi_regularised = simd_max(metric_vars.chi, 1e-6);
+        // Tensor<1, data_t> vi, Sj;
+        data_t chi_regularised = simd_max(vars.chi, 1e-6);
 
-        vi[0] = 0.;
-        vi[1] = 0.;
-        vi[2] = 0.;
+        // vi[0] = 0.;
+        // vi[1] = 0.;
+        // vi[2] = 0.;
 
         // calculate the field value
-        data_t rho = m_params.rho0 * (exp(-pow(rr / m_params.awidth, 2.0))) +
-                     m_params.delta;
+        vars.rho = m_params.rho0 * (exp(-pow(rr / m_params.awidth, 2.0))) +
+                   m_params.delta;
         data_t v2 = 0.;
-        FOR(i, j) v2 += metric_vars.h[i][j] * vi[i] * vi[j] / chi_regularised;
-        data_t eps = 0.;
-        data_t P = rho * (1. + eps) / 3.;
+        FOR(i, j)
+        v2 += vars.h[i][j] * vars.vi[i] * vars.vi[j] / chi_regularised;
+        vars.eps = 0.;
+        data_t P = vars.rho * (1. + vars.eps) / 3.;
         data_t WW = 1. / (1. - v2);
-        data_t hh = 1. + eps + P / rho;
+        data_t hh = 1. + vars.eps + P / vars.rho;
 
-        data_t D = rho * sqrt(WW);
-        data_t tau = rho * hh * WW - P - D;
+        vars.D = vars.rho * sqrt(WW);
+        vars.tau = vars.rho * hh * WW - P - vars.D;
         FOR(i)
         {
-            Sj[i] = 0.;
+            vars.Sj[i] = 0.;
             FOR(j)
-            Sj[i] +=
-                rho * hh * WW * metric_vars.h[i][j] * vi[j] / chi_regularised;
+            vars.Sj[i] += vars.rho * hh * WW * vars.h[i][j] * vars.vi[j] /
+                          chi_regularised;
         }
 
         // store the vars
-        current_cell.store_vars(rho, c_rho);
-        current_cell.store_vars(vi, GRInterval<c_vi1, c_vi3>());
-        current_cell.store_vars(D, c_D);
-        current_cell.store_vars(Sj, GRInterval<c_Sj1, c_Sj3>());
-        current_cell.store_vars(tau, c_tau);
+        current_cell.store_vars(vars);
     }
 
   protected: