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//
// Copyright (C) 2020 Gareth Jones, Glysade LLC
//
// @@ All Rights Reserved @@
// This file is part of the RDKit.
// The contents are covered by the terms of the BSD license
// which is included in the file license.txt, found at the root
// of the RDKit source tree.
//
#include <RDGeneral/RDLog.h>
#include <iostream>
#include <fstream>
#include <string>
#include <vector>
#include <memory>
#include <GraphMol/SmilesParse/SmilesParse.h>
#include <GraphMol/SmilesParse/SmilesWrite.h>
#include <GraphMol/FileParsers/MolWriters.h>
#include <GraphMol/RGroupDecomposition/RGroupDecomp.h>
#include <boost/program_options.hpp>
using namespace std;
using namespace RDKit;
using namespace boost::program_options;
namespace options = boost::program_options;
// Example systems based on Brian's MultipleCores notebook for profiling
int main(int argc, char* argv[]) {
RDLog::InitLogs();
boost::logging::disable_logs("rdApp.debug");
options_description desc("Allowed options");
desc.add_options()("help", "Help message")(
"dataset", options::value<std::string>()->default_value("rg-easy"),
"Built-in dataset rg-easy, rg-stereo")(
"maximumOperations", options::value<int>()->default_value(-1),
"Maximum number of GA operations")(
"populationSize", options::value<int>()->default_value(-1),
"GA population size")(
"numberOperationsWithoutImprovement",
options::value<int>()->default_value(-1),
"number of operations without improvement before exiting")(
"randomSeed", options::value<int>()->default_value(-1),
"Random number seed (-1 for default, -2 for random)")(
"matchingStrategy", options::value<std::string>()->default_value("GA"),
"Matching strategy- GA or GreedyChunks")(
"numberRuns", options::value<int>()->default_value(1),
"Number of GA runs")("start", options::value<int>()->default_value(0),
"start")(
"batch", options::value<int>()->default_value(10000000), "batch size");
options::variables_map vm;
options::store(options::parse_command_line(argc, argv, desc), vm);
options::notify(vm);
if (vm.count("help")) {
cerr << desc << endl;
return 0;
}
auto dataset = vm["dataset"].as<std::string>();
std::string rdBase(getenv("RDBASE"));
std::string file;
std::vector<std::string> coreSmiles;
if (dataset == "rg-easy") {
cerr << "Using dataset rg-easy" << endl;
file = rdBase + "/Docs/Notebooks/compounds.txt";
coreSmiles = {"O=C1C([*:1])C2N1C(C(O)=O)=C([*:3])CS2",
"O=C1C([*:1])C2N1C(C(O)=O)=C([*:3])CC2",
"O=C1C([*:1])C2N1C(C(O)=O)=C([*:3])CO2",
"O=C1C([*:1])C2N1C(C(O)=O)=C([*:3])C2",
"O=C1C([*:1])C2N1C(C(O)=O)C([*:3])([*:4])C2",
"O=C1C([*:1])C2N1C(C(O)=O)=C([*:3])S2",
"O=C1C([*:1])C2N1C(C(O)=O)C([*:3])([*:4])S2",
"O=C1C([*:1])C2N1C(C(O)=O)C([*:3])([*:4])O2",
"O=C1C([*:1])C([*:5])N1"};
} else if (dataset == "rg-stereo") {
cerr << "Using dataset rg-stereo" << endl;
file = rdBase + "/Docs/Notebooks/compounds.txt";
coreSmiles = {"O=C1C([*:2])([*:1])[C@@H]2N1C(C(O)=O)=C([*:3])CS2",
"O=C1C([*:2])([*:1])[C@@H]2N1C(C(O)=O)=C([*:3])CC2",
"O=C1C([*:2])([*:1])[C@@H]2N1C(C(O)=O)=C([*:3])CO2",
"O=C1C([*:2])([*:1])[C@@H]2N1C(C(O)=O)=C([*:3])C2",
"O=C1C([*:2])([*:1])[C@@H]2N1C(C(O)=O)C([*:3])([*:4])C2",
"O=C1C([*:2])([*:1])[C@@H]2N1C(C(O)=O)=C([*:3])S2",
"O=C1C([*:2])([*:1])[C@@H]2N1C(C(O)=O)C([*:3])([*:4])S2",
"O=C1C([*:2])([*:1])[C@@H]2N1C(C(O)=O)C([*:3])([*:4])O2",
"O=C1C([*:2])([*:1])C([*:6])([*:5])N1"};
} else if (dataset == "beacon") {
cerr << "Using Beacon dataset" << endl;
file = rdBase + "/Docs/Notebooks/compounds2.txt";
coreSmiles = {"N1([*:1])CCN([*:2])CC1", "C1(O[*:1])CCC(O[*:2])CC1",
"C1([*:1])CCC([*:2])CC1"};
} else {
cerr << "unknown dataset " << dataset;
return 1;
}
vector<shared_ptr<ROMol>> molecules;
{
fstream fh;
fh.open(file, ios::in);
string line;
getline(fh, line);
int count = 0;
int start = vm["start"].as<int>();
int batch = vm["batch"].as<int>();
while (getline(fh, line)) {
count++;
if (count < start) {
continue;
}
if (count > start + batch) {
break;
}
int pos = line.find_last_of("\t");
auto smiles = line.substr(pos + 1);
shared_ptr<ROMol> mol(SmilesToMol(smiles));
molecules.push_back(mol);
}
}
cerr << "Read " << molecules.size() << endl;
std::vector<ROMOL_SPTR> cores;
for (const auto& s : coreSmiles) {
cores.emplace_back(SmartsToMol(s));
}
RGroupDecompositionParameters parameters;
parameters.scoreMethod = FingerprintVariance;
parameters.gaMaximumOperations = vm["maximumOperations"].as<int>();
parameters.gaNumberOperationsWithoutImprovement =
vm["numberOperationsWithoutImprovement"].as<int>();
parameters.gaPopulationSize = vm["populationSize"].as<int>();
parameters.gaRandomSeed = vm["randomSeed"].as<int>();
parameters.gaNumberRuns = vm["numberRuns"].as<int>();
auto strategyString = vm["matchingStrategy"].as<string>();
if (strategyString == "GA") {
parameters.matchingStrategy = GA;
} else if (strategyString == "GreedyChunks") {
parameters.matchingStrategy = GreedyChunks;
} else {
cerr << "Unknown matching strategy " << strategyString << endl;
return 0;
}
RGroupDecomposition decomposition(cores, parameters);
int numberAdded(0);
for (auto& molecule : molecules) {
auto added = decomposition.add(*molecule);
if (added > -1) {
auto smiles = MolToSmiles(*molecule);
cerr << "\"" << smiles << "\", " << endl;
}
numberAdded = std::max(numberAdded, added);
}
cerr << "Added " << numberAdded << " compounds to decomposition" << endl;
auto result = decomposition.processAndScore();
cerr << "Results success " << result.success << " score " << result.score
<< endl;
}
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