Merge pull request #30 from probcomp/052924-clang-format

Update code to be clang-formatted

cxx/distributions/adapter.hh

@@ -6,55 +6,53 @@
 
 #pragma once
 #include <iostream>
-#include <string>
 #include <sstream>
+#include <string>
+
 #include "distributions/base.hh"
 
-template <typename SampleType = double> class DistributionAdapter : Distribution<std::string> {
-public:
-    // The underlying distribution that is being adapted.  We own the
-    // underlying Distribution.
-    Distribution<SampleType> *d;
-
-    DistributionAdapter(Distribution<SampleType> *dd): d(dd) {};
-
-    SampleType from_string(const std::string& x) const {
-      SampleType s;
-      std::istringstream(x) >> s;
-      return s;
-    }
-
-    std::string to_string(const SampleType& s) const {
-      std::ostringstream os;
-      os << s;
-      return os.str();
-    }
-
-    void incorporate(const std::string& x) {
-      SampleType s = from_string(x);
-      d->incorporate(s);
-    }
-
-    void unincorporate(const std::string& x) {
-      SampleType s = from_string(x);
-      d->unincorporate(s);
-    }
-
-    double logp(const std::string& x) const {
-      SampleType s = from_string(x);
-      return d->logp(s);
-    }
-
-    double logp_score() const {
-      return d->logp_score();
-    }
-
-    std::string sample() {
-      SampleType s = d->sample();
-      return to_string(s);
-    }
-
-    ~DistributionAdapter() {
-      delete d;
-    }
+template <typename SampleType = double>
+class DistributionAdapter : Distribution<std::string> {
+ public:
+  // The underlying distribution that is being adapted.  We own the
+  // underlying Distribution.
+  Distribution<SampleType>* d;
+
+  DistributionAdapter(Distribution<SampleType>* dd) : d(dd) {};
+
+  SampleType from_string(const std::string& x) const {
+    SampleType s;
+    std::istringstream(x) >> s;
+    return s;
+  }
+
+  std::string to_string(const SampleType& s) const {
+    std::ostringstream os;
+    os << s;
+    return os.str();
+  }
+
+  void incorporate(const std::string& x) {
+    SampleType s = from_string(x);
+    d->incorporate(s);
+  }
+
+  void unincorporate(const std::string& x) {
+    SampleType s = from_string(x);
+    d->unincorporate(s);
+  }
+
+  double logp(const std::string& x) const {
+    SampleType s = from_string(x);
+    return d->logp(s);
+  }
+
+  double logp_score() const { return d->logp_score(); }
+
+  std::string sample() {
+    SampleType s = d->sample();
+    return to_string(s);
+  }
+
+  ~DistributionAdapter() { delete d; }
 };

cxx/distributions/adapter_test.cc

@@ -3,13 +3,14 @@
 
 #define BOOST_TEST_MODULE test Normal
 
-#include <boost/test/included/unit_test.hpp>
 #include "distributions/adapter.hh"
+
+#include <boost/test/included/unit_test.hpp>
+
 #include "distributions/normal.hh"
 namespace tt = boost::test_tools;
 
-BOOST_AUTO_TEST_CASE(adapt_normal)
-{
+BOOST_AUTO_TEST_CASE(adapt_normal) {
   std::mt19937 prng;
   DistributionAdapter<double> ad(new Normal(&prng));
 

cxx/distributions/base.hh

@@ -1,35 +1,35 @@
 #pragma once
 
-template <typename SampleType = double> class Distribution {
-// Abstract base class for probability distributions in HIRM.
-public:
-    // N is the number of incorporated observations.
-    int N = 0;
-
-    // Accumulate x.
-    virtual void incorporate(const SampleType& x) = 0;
-
-    // Undo the accumulation of x.  Should only be called with x's that
-    // have been previously passed to incorporate().
-    virtual void unincorporate(const SampleType& x) = 0;
-
-    // The log probability of x according to the posterior predictive
-    // distribution:  log P(x | incorporated_data), where P(x | data) =
-    // \integral_{theta} P(x | theta ) P(theta | data) dtheta
-    // and theta are the parameters of the distribution.
-    virtual double logp(const SampleType& x) const = 0;
-
-    // The log probability of the data we have accumulated so far according
-    // to the prior:  log P(data | alpha) where alpha is the vector of
-    // hyperparameters of the prior and P(data)
-    // = \integral_{theta} P(data | theta) P(theta | alpha) dtheta.
-    virtual double logp_score() const = 0;
-
-    // A sample from the predictive distribution.
-    // TODO(thomaswc): Consider refactoring so that this takes a
-    // PRNG parameter.
-    virtual SampleType sample() = 0;
-
-    virtual ~Distribution() = default;
+template <typename SampleType = double>
+class Distribution {
+  // Abstract base class for probability distributions in HIRM.
+ public:
+  // N is the number of incorporated observations.
+  int N = 0;
+
+  // Accumulate x.
+  virtual void incorporate(const SampleType& x) = 0;
+
+  // Undo the accumulation of x.  Should only be called with x's that
+  // have been previously passed to incorporate().
+  virtual void unincorporate(const SampleType& x) = 0;
+
+  // The log probability of x according to the posterior predictive
+  // distribution:  log P(x | incorporated_data), where P(x | data) =
+  // \integral_{theta} P(x | theta ) P(theta | data) dtheta
+  // and theta are the parameters of the distribution.
+  virtual double logp(const SampleType& x) const = 0;
+
+  // The log probability of the data we have accumulated so far according
+  // to the prior:  log P(data | alpha) where alpha is the vector of
+  // hyperparameters of the prior and P(data)
+  // = \integral_{theta} P(data | theta) P(theta | alpha) dtheta.
+  virtual double logp_score() const = 0;
+
+  // A sample from the predictive distribution.
+  // TODO(thomaswc): Consider refactoring so that this takes a
+  // PRNG parameter.
+  virtual SampleType sample() = 0;
+
+  virtual ~Distribution() = default;
 };
-

cxx/distributions/beta_bernoulli.hh

@@ -3,48 +3,47 @@
 
 #pragma once
 #include <cassert>
-#include "util_math.hh"
+
 #include "distributions/base.hh"
+#include "util_math.hh"
 
 class BetaBernoulli : public Distribution<double> {
-public:
-    double alpha = 1;  // hyperparameter
-    double beta = 1;  // hyperparameter
-    int s = 0;  // sum of observed values
-    std::mt19937 *prng;
+ public:
+  double alpha = 1;  // hyperparameter
+  double beta = 1;   // hyperparameter
+  int s = 0;         // sum of observed values
+  std::mt19937* prng;
 
-    // BetaBernoulli does not take ownership of prng.
-    BetaBernoulli(std::mt19937 *prng) {
-        this->prng = prng;
-    }
-    void incorporate(const double& x){
-        assert(x == 0 || x == 1);
-        ++N;
-        s += x;
-    }
-    void unincorporate(const double& x) {
-        assert(x == 0 || x ==1);
-        --N;
-        s -= x;
-        assert(0 <= s);
-        assert(0 <= N);
-    }
-    double logp(const double& x) const {
-        assert(x == 0 || x == 1);
-        double log_denom = log(N + alpha + beta);
-        double log_numer = x ? log(s + alpha) : log(N - s + beta);
-        return log_numer - log_denom;
-    }
-    double logp_score() const {
-        double v1 = lbeta(s + alpha, N - s + beta);
-        double v2 = lbeta(alpha, beta);
-        return v1 - v2;
-    }
-    double sample() {
-        double p = exp(logp(1));
-        std::vector<int> items {0, 1};
-        std::vector<double> weights {1-p, p};
-        int idx = choice(weights, prng);
-        return items[idx];
-    }
+  // BetaBernoulli does not take ownership of prng.
+  BetaBernoulli(std::mt19937* prng) { this->prng = prng; }
+  void incorporate(const double& x) {
+    assert(x == 0 || x == 1);
+    ++N;
+    s += x;
+  }
+  void unincorporate(const double& x) {
+    assert(x == 0 || x == 1);
+    --N;
+    s -= x;
+    assert(0 <= s);
+    assert(0 <= N);
+  }
+  double logp(const double& x) const {
+    assert(x == 0 || x == 1);
+    double log_denom = log(N + alpha + beta);
+    double log_numer = x ? log(s + alpha) : log(N - s + beta);
+    return log_numer - log_denom;
+  }
+  double logp_score() const {
+    double v1 = lbeta(s + alpha, N - s + beta);
+    double v2 = lbeta(alpha, beta);
+    return v1 - v2;
+  }
+  double sample() {
+    double p = exp(logp(1));
+    std::vector<int> items{0, 1};
+    std::vector<double> weights{1 - p, p};
+    int idx = choice(weights, prng);
+    return items[idx];
+  }
 };

cxx/distributions/beta_bernoulli_test.cc

@@ -2,12 +2,12 @@
 
 #define BOOST_TEST_MODULE test BetaBernoulli
 
-#include <boost/test/included/unit_test.hpp>
 #include "distributions/beta_bernoulli.hh"
+
+#include <boost/test/included/unit_test.hpp>
 namespace tt = boost::test_tools;
 
-BOOST_AUTO_TEST_CASE(test_simple)
-{
+BOOST_AUTO_TEST_CASE(test_simple) {
   std::mt19937 prng;
   BetaBernoulli bb(&prng);