Add config for Google style clang-format, so external users share sam…

…e formatting
probcomp · May 30, 2024 · e4af495 · e4af495
1 parent e3e972b
commit e4af495
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Showing 8 changed files with 250 additions and 250 deletions.
diff --git a/cxx/distributions/normal.hh b/cxx/distributions/normal.hh
@@ -36,27 +36,27 @@ class Normal : public Distribution<double> {
   int mean = 0;  // Mean of observed values
   int var = 0;   // Variance of observed values
 
-  std::mt19937 *prng;
+  std::mt19937* prng;
 
   // Normal does not take ownership of prng.
-  Normal(std::mt19937 *prng) { this->prng = prng; }
+  Normal(std::mt19937* prng) { this->prng = prng; }
 
-  void incorporate(const double &x) {
+  void incorporate(const double& x) {
     ++N;
     double old_mean = mean;
     mean += (x - mean) / N;
     var += (x - mean) * (x - old_mean);
   }
 
-  void unincorporate(const double &x) {
+  void unincorporate(const double& x) {
     int old_N = N;
     --N;
     double old_mean = mean;
     mean = (mean * old_N - x) / N;
     var -= (x - mean) * (x - old_mean);
   }
 
-  void posterior_hypers(double *mprime, double *sprime) const {
+  void posterior_hypers(double* mprime, double* sprime) const {
     // r' = r + N
     // m' = (r m + N mean) / (r + N)
     // C = N (var + mean^2)
@@ -67,12 +67,12 @@ class Normal : public Distribution<double> {
               N * (var - 2 * mean * mdelta - mdelta * mdelta);
   }
 
-  double logp(const double &x) const {
+  double logp(const double& x) const {
     // Based on equation (13) of GaussianInverseGamma.pdf
     double unused_mprime, sprime;
-    const_cast<Normal *>(this)->incorporate(x);
+    const_cast<Normal*>(this)->incorporate(x);
     posterior_hypers(&unused_mprime, &sprime);
-    const_cast<Normal *>(this)->unincorporate(x);
+    const_cast<Normal*>(this)->unincorporate(x);
     double sprime2;
     posterior_hypers(&unused_mprime, &sprime2);
     return -0.5 * log(M_2PI) + logZ(r + N + 1, v + N + 1, sprime) -
@@ -102,6 +102,6 @@ class Normal : public Distribution<double> {
   }
 
   // Disable copying.
-  Normal &operator=(const Normal &) = delete;
-  Normal(const Normal &) = delete;
+  Normal& operator=(const Normal&) = delete;
+  Normal(const Normal&) = delete;
 };
diff --git a/cxx/hirm.cc b/cxx/hirm.cc
@@ -32,51 +32,51 @@
     fflush(stdout);                                              \
   }
 
-void inference_irm(IRM *irm, int iters, int timeout, bool verbose) {
+void inference_irm(IRM* irm, int iters, int timeout, bool verbose) {
   clock_t t_begin = clock();
   double t_total = 0;
   for (int i = 0; i < iters; ++i) {
     CHECK_TIMEOUT(timeout, t_begin);
     // TRANSITION ASSIGNMENTS.
-    for (const auto &[d, domain] : irm->domains) {
+    for (const auto& [d, domain] : irm->domains) {
       for (const auto item : domain->items) {
         clock_t t = clock();
         irm->transition_cluster_assignment_item(d, item);
         REPORT_SCORE(verbose, t, t_total, irm);
       }
     }
     // TRANSITION ALPHA.
-    for (const auto &[d, domain] : irm->domains) {
+    for (const auto& [d, domain] : irm->domains) {
       clock_t t = clock();
       domain->crp.transition_alpha();
       REPORT_SCORE(verbose, t, t_total, irm);
     }
   }
 }
 
-void inference_hirm(HIRM *hirm, int iters, int timeout, bool verbose) {
+void inference_hirm(HIRM* hirm, int iters, int timeout, bool verbose) {
   clock_t t_begin = clock();
   double t_total = 0;
   for (int i = 0; i < iters; ++i) {
     CHECK_TIMEOUT(timeout, t_begin);
     // TRANSITION RELATIONS.
-    for (const auto &[r, rc] : hirm->relation_to_code) {
+    for (const auto& [r, rc] : hirm->relation_to_code) {
       clock_t t = clock();
       hirm->transition_cluster_assignment_relation(r);
       REPORT_SCORE(verbose, t, t_total, hirm);
     }
     // TRANSITION IRMs.
-    for (const auto &[t, irm] : hirm->irms) {
+    for (const auto& [t, irm] : hirm->irms) {
       // TRANSITION ASSIGNMENTS.
-      for (const auto &[d, domain] : irm->domains) {
+      for (const auto& [d, domain] : irm->domains) {
         for (auto item : domain->items) {
           clock_t t = clock();
           irm->transition_cluster_assignment_item(d, item);
           REPORT_SCORE(verbose, t, t_total, irm);
         }
       }
       // TRANSITION ALPHA.
-      for (const auto &[d, domain] : irm->domains) {
+      for (const auto& [d, domain] : irm->domains) {
         clock_t t = clock();
         domain->crp.transition_alpha();
         REPORT_SCORE(verbose, t, t_total, irm);
@@ -85,7 +85,7 @@ void inference_hirm(HIRM *hirm, int iters, int timeout, bool verbose) {
   }
 }
 
-int main(int argc, char **argv) {
+int main(int argc, char** argv) {
   cxxopts::Options options("hirm",
                            "Run a hierarchical infinite relational model.");
   options.add_options()("help", "show help message")(
@@ -146,7 +146,7 @@ int main(int argc, char **argv) {
 
   if (mode == "irm") {
     std::cout << "selected model is IRM" << std::endl;
-    IRM *irm;
+    IRM* irm;
     // Load
     if (path_clusters.empty()) {
       irm = new IRM(schema, &prng);
@@ -172,7 +172,7 @@ int main(int argc, char **argv) {
 
   if (mode == "hirm") {
     std::cout << "selected model is HIRM" << std::endl;
-    HIRM *hirm;
+    HIRM* hirm;
     // Load
     if (path_clusters.empty()) {
       hirm = new HIRM(schema, &prng);