Restore pclean's ability to output its clusters

cxx/pclean/pclean.cc

@@ -99,8 +99,8 @@ int main(int argc, char** argv) {
   if (result.count("output") > 0) {
     std::string out_fn = result["output"].as<std::string>();
     std::cout << "Savings results to " << out_fn << "\n";
-    // TODO(thomaswc): Fix this.
-    // to_txt(out_fn, gendb.hirm, encoding);
+    T_encoding encoding = make_dummy_encoding_from_gendb(gendb);
+    to_txt(out_fn, gendb.hirm, encoding);
   }
 
   std::string heldout_fn = result["heldout"].as<std::string>();

cxx/pclean/pclean_lib.cc

@@ -84,3 +84,15 @@ DataFrame make_pclean_samples(int num_samples, int start_row, GenDB *gendb,
   return df;
 }
 
+T_encoding make_dummy_encoding_from_gendb(const GenDB& gendb) {
+  T_encoding_f item_to_code;
+  T_encoding_r code_to_item;
+
+  for (const auto& [domain, crp] : gendb.domain_crps) {
+    for (int i = 0; i < crp.max_table(); ++i) {
+      code_to_item[domain][i] = domain + ":" + std::to_string(i);
+    }
+  }
+
+  return std::make_pair(item_to_code, code_to_item);
+}

cxx/pclean/pclean_lib.hh

@@ -22,3 +22,7 @@ void incorporate_observations(std::mt19937* prng,
 // All existing rows added to gendb should have ids < start_row.
 DataFrame make_pclean_samples(int num_samples, int start_row, GenDB *gendb,
                               std::mt19937* prng);
+
+// Makes an encoding from a GenDB.  The i-th entity from domain "domain"
+// is given the name "domain:i".
+T_encoding make_dummy_encoding_from_gendb(const GenDB& gendb);

cxx/pclean/pclean_lib_test.cc

@@ -166,3 +166,61 @@ observe
   BOOST_TEST(samples.data["City"].size() == 10);
   BOOST_TEST(samples.data["State"].size() == 10);
 }
+
+BOOST_AUTO_TEST_CASE(test_make_pclean_samples) {
+  std::mt19937 prng;
+
+  std::stringstream ss(R"""(
+class School
+  name ~ string
+  degree_dist ~ categorical(k=100)
+
+class Physician
+  school ~ School
+  degree ~ stringcat(strings="MD PT NP DO PHD")
+  specialty ~ stringcat(strings="Family Med:Internal Med:Physical Therapy", delim=":")
+  # observed_degree ~ maybe_swap(degree)
+
+class City
+  name ~ string
+  state ~ stringcat(strings="AL AK AZ AR CA CO CT DE DC FL GA HI ID IL IN IA KS KY LA ME MD MA MI MN MS MO MT NE NV NH NJ NM NY NC ND OH OK OR PA RI SC SD TN TX UT VT VA WA WV WI WY")
+
+class Practice
+  city ~ City
+
+class Record
+  physician ~ Physician
+  location ~ Practice
+
+observe
+  physician.specialty as Specialty
+  physician.school.name as School
+  physician.degree as Degree
+  location.city.name as City
+  location.city.state as State
+  from Record
+)""");
+
+  PCleanSchema pclean_schema;
+  BOOST_TEST(read_schema(ss, &pclean_schema));
+
+  GenDB gendb(&prng, pclean_schema);
+
+  T_encoding enc = make_dummy_encoding_from_gendb(gendb);
+
+  BOOST_TEST(enc.second.size() == 0);
+
+  std::map<std::string, ObservationVariant> obs = {
+    {"Specialty", "Internal Med"},
+    {"School", "Harvard"},
+    {"Degree", "MD"},
+    {"City", "Cambridge"},
+    {"State", "MA"}};
+
+  gendb.incorporate(prng, {0, obs}, true);
+
+  BOOST_TEST(enc.second["School"][0] == "School:0");
+  BOOST_TEST(enc.second["Physician"][0] == "Physician:0");
+  BOOST_TEST(enc.second["City"][0] == "City:0");
+  BOOST_TEST(enc.second["Practice"][0] == "Practice:0");
+}