Linting

Author: tkoskela

cpp/example/padmm_mpi_random_coverage.cc

@@ -92,7 +92,8 @@ std::shared_ptr<sopt::algorithm::ImagingProximalADMM<t_complex>> padmm_factory(
                            sara.size()) *
       1e-3;
   PURIFY_LOW_LOG("Epsilon {}, Rank = {}", epsilon, comm.rank());
-  PURIFY_LOW_LOG("Regulariser_Strength {}, SARA Size = {}, Rank = {}", regulariser_strength, sara.size(), comm.rank());
+  PURIFY_LOW_LOG("Regulariser_Strength {}, SARA Size = {}, Rank = {}", regulariser_strength,
+                 sara.size(), comm.rank());
 
   // shared pointer because the convergence function need access to some data that we would rather
   // not reproduce. E.g. padmm definition is self-referential.

cpp/example/padmm_mpi_real_data.cc

@@ -130,10 +130,13 @@ std::shared_ptr<sopt::algorithm::ImagingProximalADMM<t_complex>> padmm_factory(
     if (comm.is_root()) PURIFY_MEDIUM_LOG("Step size γ {}", padmm->regulariser_strength());
     *iter = *iter + 1;
     Vector<t_complex> const alpha = padmm->Psi().adjoint() * x;
-    const t_real new_regulariser_strength = comm.all_reduce(alpha.real().cwiseAbs().maxCoeff(), MPI_MAX) * 1e-3;
+    const t_real new_regulariser_strength =
+        comm.all_reduce(alpha.real().cwiseAbs().maxCoeff(), MPI_MAX) * 1e-3;
     if (comm.is_root()) PURIFY_MEDIUM_LOG("Step size γ update {}", new_regulariser_strength);
-    padmm->regulariser_strength(((std::abs(padmm->regulariser_strength() - new_regulariser_strength) > 0.2) and *iter < 200) ? new_regulariser_strength
-                                                                                : padmm->regulariser_strength());
+    padmm->regulariser_strength(
+        ((std::abs(padmm->regulariser_strength() - new_regulariser_strength) > 0.2) and *iter < 200)
+            ? new_regulariser_strength
+            : padmm->regulariser_strength());
     // updating parameter
 
     Vector<t_complex> const residual = padmm->Phi().adjoint() * (uv_data.vis - padmm->Phi() * x);

cpp/example/padmm_random_coverage.cc

@@ -90,10 +90,11 @@ void padmm(const std::string &name, const Image<t_complex> &M31, const std::stri
   auto const padmm =
       sopt::algorithm::ImagingProximalADMM<t_complex>(uv_data.vis)
           .itermax(500)
-          .regulariser_strength((Psi.adjoint() * (measurements_transform->adjoint() * uv_data.vis).eval())
-                     .cwiseAbs()
-                     .maxCoeff() *
-                 1e-3)
+          .regulariser_strength(
+              (Psi.adjoint() * (measurements_transform->adjoint() * uv_data.vis).eval())
+                  .cwiseAbs()
+                  .maxCoeff() *
+              1e-3)
           .relative_variation(1e-3)
           .l2ball_proximal_epsilon(epsilon)
           .tight_frame(false)

cpp/example/padmm_real_data.cc

@@ -54,7 +54,8 @@ void padmm(const std::string &name, const t_uint &imsizex, const t_uint &imsizey
   pfitsio::write2d(Image<t_real>::Map(dimage.data(), imsizey, imsizex), dirty_image_fits);
   pfitsio::write2d(Image<t_real>::Map(psf.data(), imsizey, imsizex), psf_image_fits);
   auto const epsilon = 3 * std::sqrt(2 * uv_data.size()) * sigma;
-  auto const regulariser_strength = (measurements_transform->adjoint() * uv_data.vis).real().maxCoeff() * 1e-3;
+  auto const regulariser_strength =
+      (measurements_transform->adjoint() * uv_data.vis).real().maxCoeff() * 1e-3;
   PURIFY_HIGH_LOG("Using epsilon of {}", epsilon);
 #ifdef PURIFY_CImg
   auto const canvas = std::make_shared<CDisplay>(
@@ -107,8 +108,10 @@ void padmm(const std::string &name, const t_uint &imsizex, const t_uint &imsizey
     // updating parameter
     const t_real new_regulariser_strength = alpha.real().cwiseAbs().maxCoeff() * 1e-3;
     PURIFY_MEDIUM_LOG("Step size γ update {}", new_regulariser_strength);
-    padmm->regulariser_strength(((std::abs(padmm->regulariser_strength() - new_regulariser_strength) > 0.2) and *iter < 200) ? new_regulariser_strength
-                                                                                : padmm->regulariser_strength());
+    padmm->regulariser_strength(
+        ((std::abs(padmm->regulariser_strength() - new_regulariser_strength) > 0.2) and *iter < 200)
+            ? new_regulariser_strength
+            : padmm->regulariser_strength());
 
     Vector<t_complex> const residual = padmm->Phi().adjoint() * (uv_data.vis - padmm->Phi() * x);
 

cpp/example/sara_padmm_random_coverage.cc

@@ -80,8 +80,8 @@ int main(int, char **) {
           .maxCoeff() *
       beta;
 
-  // auto purify_regulariser_strength = 3 * utilities::median((Psi.adjoint() * (measurements_transform.adjoint() *
-  // (uv_data.vis - y0))).real().cwiseAbs())/0.6745;
+  // auto purify_regulariser_strength = 3 * utilities::median((Psi.adjoint() *
+  // (measurements_transform.adjoint() * (uv_data.vis - y0))).real().cwiseAbs())/0.6745;
 
   SOPT_INFO("Using epsilon of {} \n", epsilon);
   auto const padmm = sopt::algorithm::ImagingProximalADMM<t_complex>(uv_data.vis)