format and return 1 on unfinished runs

python/loadleveller/clusterutils.py

@@ -16,6 +16,7 @@ batchscript_claix18 = '''#!/usr/bin/env zsh
 
 {custom_cmds}
 {mpirun} $FLAGS_MPI_BATCH {mc_cmd}
+{custom_post_cmds}
 '''
 
 batch_commands = {
@@ -31,6 +32,7 @@ def generate_batchscript_claix18(cmd, jobname, jobconfig):
     if 'project' in jobconfig:
         custom_cmds += '#SBATCH --account={}\n'.format(jobconfig['project'])
     custom_cmds += jobconfig.get('custom_cmds', '')
+    custom_cmds = jobconfig.get('custom_post_cmds', '')
 
     try:
         return template.format(
@@ -40,6 +42,7 @@ def generate_batchscript_claix18(cmd, jobname, jobconfig):
             walltime=jobconfig['mc_walltime'],
             num_cores=jobconfig['num_cores'],
             custom_cmds=custom_cmds,
+            custom_post_cmds=custom_post_cmds,
             mc_cmd=' '.join(cmd)
         )
     except KeyError as e:

src/evalable.cpp

@@ -83,7 +83,8 @@ void evalable::jackknife(const results &res, observable_result &obs_res) const {
 		if(jacked_eval_mean.size() != jacked_eval.size()) {
 			throw std::runtime_error(
 			    fmt::format("evalable '{}': evalables must not change their dimensions depending "
-			                "on the input", name_));
+			                "on the input",
+			                name_));
 		}
 
 		for(size_t i = 0; i < jacked_eval.size(); i++) {

src/iodump.cpp

@@ -48,7 +48,7 @@ const char *iodump_exception::what() const noexcept {
 }
 
 iodump::group::group(hid_t parent, const std::string &filename, const std::string &path)
-	: filename_{filename} {
+    : filename_{filename} {
 	group_ = H5Gopen(parent, path.c_str(), H5P_DEFAULT);
 	if(group_ < 0) {
 		group_ = H5Gcreate2(parent, path.c_str(), H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT);

src/jobinfo.cpp

@@ -140,7 +140,7 @@ void jobinfo::concatenate_results() {
 		std::vector<char> buf(size + 1, 0);
 		res_file.read(buf.data(), size);
 		cat_results << buf.data();
-		if(i < task_names.size()-1) {
+		if(i < task_names.size() - 1) {
 			cat_results << ",";
 		}
 		cat_results << "\n";

src/mc.cpp

@@ -86,8 +86,8 @@ void mc::_write(const std::string &dir) {
 		if(pt_mode_) {
 			therm *= pt_sweeps_per_global_update_;
 		}
-		g.write("thermalization_sweeps", std::min(sweep_,therm));
-		g.write("sweeps", sweep_-std::min(sweep_,therm));
+		g.write("thermalization_sweeps", std::min(sweep_, therm));
+		g.write("sweeps", sweep_ - std::min(sweep_, therm));
 	}
 
 	clock_gettime(CLOCK_MONOTONIC_RAW, &tend);

src/mc.h

@@ -15,6 +15,7 @@ private:
 	size_t sweep_{0};
 	size_t therm_{0};
 	int pt_sweeps_per_global_update_{-1};
+
 protected:
 	parser param;
 	std::unique_ptr<random_number_generator> rng;

src/merger.cpp

@@ -67,10 +67,10 @@ results merge(const std::vector<std::string> &filenames, const std::vector<evala
 				    "merge: sample count is not an integer multiple of the vector length. Corrupt "
 				    "file?"};
 			}
-			
+
 			sample_size /= vector_length;
-	
-			obs.total_sample_count += sample_size-std::min(sample_size, sample_skip);
+
+			obs.total_sample_count += sample_size - std::min(sample_size, sample_skip);
 			obs.mean.resize(vector_length);
 			obs.error.resize(vector_length);
 			obs.autocorrelation_time.resize(vector_length);
@@ -98,9 +98,9 @@ results merge(const std::vector<std::string> &filenames, const std::vector<evala
 				    min_bin_count + cbrt(obs.total_sample_count - min_bin_count);
 			}
 		} else {
-			obs.rebinning_bin_count = obs.total_sample_count/rebinning_bin_length;
+			obs.rebinning_bin_count = obs.total_sample_count / rebinning_bin_length;
 		}
-		
+
 		if(obs.rebinning_bin_count == 0) {
 			continue;
 		}
@@ -124,14 +124,14 @@ results merge(const std::vector<std::string> &filenames, const std::vector<evala
 			// total_sample_count. In that case, we throw away the leftover samples.
 			//
 			size_t vector_length = obs.mean.size();
-			for(size_t i = sample_skip*vector_length; metadata[obs_name].sample_counter <
-			                      obs.rebinning_bin_count * obs.rebinning_bin_length &&
-			                  i < samples.size();
+			for(size_t i = sample_skip * vector_length;
+			    metadata[obs_name].sample_counter <
+			        obs.rebinning_bin_count * obs.rebinning_bin_length &&
+			    i < samples.size();
 			    i++) {
 				size_t vector_idx = i % vector_length;
-				
-				obs.mean[vector_idx] += samples[i];
 
+				obs.mean[vector_idx] += samples[i];
 
 				if(vector_idx == vector_length - 1) {
 					metadata[obs_name].sample_counter++;
@@ -140,15 +140,15 @@ results merge(const std::vector<std::string> &filenames, const std::vector<evala
 		}
 	}
 
-
 	for(auto &[obs_name, obs] : res.observables) {
-		assert(metadata[obs_name].sample_counter == obs.rebinning_bin_count * obs.rebinning_bin_length);
+		assert(metadata[obs_name].sample_counter ==
+		       obs.rebinning_bin_count * obs.rebinning_bin_length);
 		if(obs.rebinning_bin_count == 0) {
 			continue;
 		}
 
 		for(auto &mean : obs.mean) {
-			mean /= obs.rebinning_bin_count*obs.rebinning_bin_length;
+			mean /= obs.rebinning_bin_count * obs.rebinning_bin_length;
 		}
 		metadata[obs_name].sample_counter = 0;
 	}
@@ -165,7 +165,7 @@ results merge(const std::vector<std::string> &filenames, const std::vector<evala
 
 			g.read(fmt::format("{}/samples", obs_name), samples);
 
-			for(size_t i = sample_skip*vector_length;
+			for(size_t i = sample_skip * vector_length;
 			    obs_meta.current_rebin < obs.rebinning_bin_count && i < samples.size(); i++) {
 				size_t vector_idx = i % vector_length;
 
@@ -192,7 +192,7 @@ results merge(const std::vector<std::string> &filenames, const std::vector<evala
 						obs_meta.current_rebin_filling = 0;
 					}
 				}
-				
+
 				if(vector_idx == vector_length - 1) {
 					metadata[obs_name].sample_counter++;
 				}

src/results.cpp

@@ -10,7 +10,7 @@ void results::write_json(const std::string &filename, const std::string &taskdir
 	using json = nlohmann::json;
 
 	json obs_list;
-	
+
 	for(auto &[obs_name, obs] : observables) {
 		double max_auto_time = 0;
 		if(obs.autocorrelation_time.size() > 0) {
@@ -19,21 +19,16 @@ void results::write_json(const std::string &filename, const std::string &taskdir
 		}
 
 		obs_list[obs_name] = {
-			{"rebin_len", obs.rebinning_bin_length},
-			{"rebin_count", obs.rebinning_bin_count},
-			{"internal_bin_len", obs.internal_bin_length},
-			{"autocorr_time", max_auto_time},
-			{"mean", obs.mean},
-			{"error", obs.error},
+		    {"rebin_len", obs.rebinning_bin_length},
+		    {"rebin_count", obs.rebinning_bin_count},
+		    {"internal_bin_len", obs.internal_bin_length},
+		    {"autocorr_time", max_auto_time},
+		    {"mean", obs.mean},
+		    {"error", obs.error},
 		};
-		
 	}
-	
-	nlohmann::json out = {
-		{"task", taskdir},
-		{"parameters", params},
-		{"results", obs_list}
-	};
+
+	nlohmann::json out = {{"task", taskdir}, {"parameters", params}, {"results", obs_list}};
 
 	std::ofstream file(filename);
 	file << out.dump(1);

src/results.h

 #pragma once
 #include <map>
-#include <vector>
 #include <nlohmann/json.hpp>
+#include <vector>
 
 namespace loadl {
 

src/runner.cpp

@@ -31,10 +31,11 @@ int runner_mpi_start(jobinfo job, const mc_factory &mccreator, int argc, char **
 
 	int rank;
 	MPI_Comm_rank(MPI_COMM_WORLD, &rank);
+	int rc = 0;
 
 	if(rank == 0) {
 		runner_master r{std::move(job)};
-		r.start();
+		rc = r.start();
 	} else {
 		runner_slave r{std::move(job), mccreator};
 		r.start();
@@ -42,12 +43,12 @@ int runner_mpi_start(jobinfo job, const mc_factory &mccreator, int argc, char **
 
 	MPI_Finalize();
 
-	return 0;
+	return rc;
 }
 
 runner_master::runner_master(jobinfo job) : job_{std::move(job)} {}
 
-void runner_master::start() {
+int runner_master::start() {
 	MPI_Comm_size(MPI_COMM_WORLD, &num_active_ranks_);
 
 	job_.log(fmt::format("Starting job '{}'", job_.jobname));
@@ -56,6 +57,9 @@ void runner_master::start() {
 	while(num_active_ranks_ > 1) {
 		react();
 	}
+
+	bool all_done = current_task_id_ < 0;
+	return !all_done;
 }
 
 int runner_master::get_new_task_id(int old_id) {
@@ -84,15 +88,20 @@ void runner_master::react() {
 			send_action(A_NEW_JOB, node);
 			tasks_[current_task_id_].scheduled_runs++;
 
-			size_t sweeps_until_comm = 1 + tasks_[current_task_id_].target_sweeps - std::min(tasks_[current_task_id_].target_sweeps, tasks_[current_task_id_].sweeps);
+			size_t sweeps_until_comm =
+			    1 + tasks_[current_task_id_].target_sweeps -
+			    std::min(tasks_[current_task_id_].target_sweeps, tasks_[current_task_id_].sweeps);
 			assert(current_task_id_ >= 0);
-			uint64_t msg[3] = {static_cast<uint64_t>(current_task_id_), static_cast<uint64_t>(tasks_[current_task_id_].scheduled_runs),
-			              sweeps_until_comm};
-			MPI_Send(&msg, sizeof(msg) / sizeof(msg[0]), MPI_UINT64_T, node, T_NEW_JOB, MPI_COMM_WORLD);
+			uint64_t msg[3] = {static_cast<uint64_t>(current_task_id_),
+			                   static_cast<uint64_t>(tasks_[current_task_id_].scheduled_runs),
+			                   sweeps_until_comm};
+			MPI_Send(&msg, sizeof(msg) / sizeof(msg[0]), MPI_UINT64_T, node, T_NEW_JOB,
+			         MPI_COMM_WORLD);
 		}
 	} else if(node_status == S_BUSY) {
 		uint64_t msg[2];
-		MPI_Recv(msg, sizeof(msg) / sizeof(msg[0]), MPI_UINT64_T, node, T_STATUS, MPI_COMM_WORLD, &stat);
+		MPI_Recv(msg, sizeof(msg) / sizeof(msg[0]), MPI_UINT64_T, node, T_STATUS, MPI_COMM_WORLD,
+		         &stat);
 		int task_id = msg[0];
 		size_t completed_sweeps = msg[1];
 
@@ -207,7 +216,8 @@ int runner_slave::what_is_next(int status) {
 		}
 		MPI_Status stat;
 		uint64_t msg[3];
-		MPI_Recv(&msg, sizeof(msg) / sizeof(msg[0]), MPI_UINT64_T, 0, T_NEW_JOB, MPI_COMM_WORLD, &stat);
+		MPI_Recv(&msg, sizeof(msg) / sizeof(msg[0]), MPI_UINT64_T, 0, T_NEW_JOB, MPI_COMM_WORLD,
+		         &stat);
 		task_id_ = msg[0];
 		run_id_ = msg[1];
 		sweeps_before_communication_ = msg[2];

src/runner.h

@@ -32,7 +32,7 @@ private:
 
 public:
 	runner_master(jobinfo job);
-	void start();
+	int start();
 };
 
 class runner_slave {

src/runner_pt.cpp

 #include "runner_pt.h"
-#include <fstream>
 #include "util.h"
+#include <fstream>
 
 namespace loadl {
 
@@ -85,12 +85,11 @@ void pt_chain::clear_histograms() {
 	std::fill(rejection_rates.begin(), rejection_rates.end(), 0);
 }
 
-
 // https://arxiv.org/pdf/1905.02939.pdf
 std::tuple<double, double> pt_chain::optimize_params() {
 	std::vector<double> rejection_est(rejection_rates);
 	bool odd = false;
-	for(auto& r : rejection_est) {
+	for(auto &r : rejection_est) {
 		r /= rejection_rate_entries[odd];
 		odd = !odd;
 		if(r == 0) { // ensure the comm_barrier is invertible
@@ -100,30 +99,29 @@ std::tuple<double, double> pt_chain::optimize_params() {
 
 	std::vector<double> comm_barrier(params.size());
 
-
 	double sum{};
 	double efficiency{};
-	for(size_t i = 0; i < comm_barrier.size()-1; i++) {
+	for(size_t i = 0; i < comm_barrier.size() - 1; i++) {
 		comm_barrier[i] = sum;
-		sum += rejection_est[i]; 
-		efficiency += rejection_est[i]/(1-rejection_est[i]);
+		sum += rejection_est[i];
+		efficiency += rejection_est[i] / (1 - rejection_est[i]);
 	}
-	comm_barrier[comm_barrier.size()-1] = sum;
+	comm_barrier[comm_barrier.size() - 1] = sum;
 
 	monotonic_interpolator lambda{comm_barrier, params};
 	double convergence{};
 
-	for(size_t i = 1; i < params.size()-1; i++) {
-		double new_param = lambda(sum*i/(params.size()-1));
+	for(size_t i = 1; i < params.size() - 1; i++) {
+		double new_param = lambda(sum * i / (params.size() - 1));
 		double d = (new_param - params[i]);
-		
-		convergence += d*d;
+
+		convergence += d * d;
 		params[i] = new_param;
 	}
 
-	convergence = sqrt(convergence)/params.size();
+	convergence = sqrt(convergence) / params.size();
 
-	double round_trip_rate = (1+sum)/(1+efficiency);
+	double round_trip_rate = (1 + sum) / (1 + efficiency);
 
 	return std::tie(round_trip_rate, convergence);
 }
@@ -137,10 +135,11 @@ int runner_pt_start(jobinfo job, const mc_factory &mccreator, int argc, char **a
 
 	int rank;
 	MPI_Comm_rank(MPI_COMM_WORLD, &rank);
+	int rc = 0;
 
 	if(rank == 0) {
 		runner_pt_master r{std::move(job)};
-		r.start();
+		rc = r.start();
 	} else {
 		runner_pt_slave r{std::move(job), mccreator};
 		r.start();
@@ -148,7 +147,7 @@ int runner_pt_start(jobinfo job, const mc_factory &mccreator, int argc, char **a
 
 	MPI_Finalize();
 
-	return 0;
+	return rc;
 }
 
 runner_pt_master::runner_pt_master(jobinfo job) : job_{std::move(job)} {
@@ -187,13 +186,14 @@ void runner_pt_master::construct_pt_chains() {
 		chain.task_ids.at(chain_pos) = i;
 
 		const char *pt_sweep_error =
-		    "chain {}: task {}: in parallel tempering mode, sweeps are measured in global updates and need to be the "
+		    "chain {}: task {}: in parallel tempering mode, sweeps are measured in global updates "
+		    "and need to be the "
 		    "same within each chain: {} = {} != {}";
 
 		int64_t target_sweeps = task.get<int>("sweeps");
 		if(chain.target_sweeps >= 0 && target_sweeps != chain.target_sweeps) {
-			throw std::runtime_error{
-			    fmt::format(pt_sweep_error, chain.id, i, "target_sweeps", chain.target_sweeps, target_sweeps)};
+			throw std::runtime_error{fmt::format(pt_sweep_error, chain.id, i, "target_sweeps",
+			                                     chain.target_sweeps, target_sweeps)};
 		}
 		chain.target_sweeps = target_sweeps;
 
@@ -209,7 +209,8 @@ void runner_pt_master::construct_pt_chains() {
 		int64_t sweeps_per_global_update = task.get<int>("pt_sweeps_per_global_update");
 		int64_t sweeps = job_.read_dump_progress(i) / sweeps_per_global_update;
 		if(chain.sweeps >= 0 && sweeps != chain.sweeps) {
-			throw std::runtime_error{fmt::format(pt_sweep_error, chain.id, i, "sweeps", chain.sweeps, sweeps)};
+			throw std::runtime_error{
+			    fmt::format(pt_sweep_error, chain.id, i, "sweeps", chain.sweeps, sweeps)};
 		}
 		chain.sweeps = sweeps;
 	}
@@ -226,7 +227,7 @@ void runner_pt_master::construct_pt_chains() {
 
 		chain_len_ = c.task_ids.size();
 
-		c.rejection_rates.resize(chain_len_-1);
+		c.rejection_rates.resize(chain_len_ - 1);
 
 		if(po_config_.enabled) {
 			c.entries_before_optimization = po_config_.nsamples_initial;
@@ -288,7 +289,7 @@ void runner_pt_master::write_statistics(const pt_chain_run &chain_run) {
 	auto g = stat.get_root();
 
 	g.write("chain_length", chain_len_);
-	
+
 	auto cg = g.open_group(fmt::format("chain{:04d}_run{:04d}", chain_run.id, chain_run.run_id));
 	cg.insert_back("rank_to_pos", chain_run.rank_to_pos);
 }
@@ -299,7 +300,7 @@ void runner_pt_master::write_param_optimization_statistics() {
 	auto g = stat.get_root();
 
 	g.write("chain_length", chain_len_);
-	
+
 	for(auto &chain : pt_chains_) {
 		auto cg = g.open_group(fmt::format("chain{:04d}", chain.id));
 		cg.insert_back("params", chain.params);
@@ -340,12 +341,10 @@ void runner_pt_master::checkpoint_write() {
 	}
 }
 
-void runner_pt_master::start() {
+int runner_pt_master::start() {
 	MPI_Comm_size(MPI_COMM_WORLD, &num_active_ranks_);
 
-
-	po_config_.enabled =
-	    job_.jobfile["jobconfig"].defined("pt_parameter_optimization");
+	po_config_.enabled = job_.jobfile["jobconfig"].defined("pt_parameter_optimization");
 	if(po_config_.enabled) {
 		job_.log("using feedback parameter optimization");
 		const auto &po = job_.jobfile["jobconfig"]["pt_parameter_optimization"];
@@ -380,6 +379,15 @@ void runner_pt_master::start() {
 		}
 	}
 	checkpoint_write();
+
+	bool all_done = true;
+	for(auto &c : pt_chains_) {
+		if(!c.is_done()) {
+			all_done = false;
+			break;
+		}
+	}
+	return !all_done;
 }
 
 int runner_pt_master::schedule_chain_run() {
@@ -430,7 +438,8 @@ int runner_pt_master::assign_new_chain(int rank_section) {
 }
 
 void runner_pt_master::pt_param_optimization(pt_chain &chain) {
-	if(std::min(chain.rejection_rate_entries[0], chain.rejection_rate_entries[1]) >= chain.entries_before_optimization) {
+	if(std::min(chain.rejection_rate_entries[0], chain.rejection_rate_entries[1]) >=
+	   chain.entries_before_optimization) {
 		chain.entries_before_optimization *= po_config_.nsamples_growth;
 
 		auto [efficiency, convergence] = chain.optimize_params();
@@ -451,7 +460,8 @@ void runner_pt_master::react() {
 	int rank = stat.MPI_SOURCE - 1;
 	if(rank_status == S_BUSY) {
 		int64_t msg[1];
-		MPI_Recv(msg, sizeof(msg) / sizeof(msg[0]), MPI_INT64_T, rank + 1, 0, MPI_COMM_WORLD, &stat);
+		MPI_Recv(msg, sizeof(msg) / sizeof(msg[0]), MPI_INT64_T, rank + 1, 0, MPI_COMM_WORLD,
+		         &stat);
 		int64_t completed_sweeps = msg[0];
 
 		int chain_run_id = rank_to_chain_run_[rank / chain_len_];
@@ -549,7 +559,7 @@ void runner_pt_master::pt_global_update(pt_chain &chain, pt_chain_run &chain_run
 		double w1 = chain_run.weight_ratios[i];
 		double w2 = chain_run.weight_ratios[i + 1];
 
-		double p = std::min(exp(w1+w2),1.);
+		double p = std::min(exp(w1 + w2), 1.);
 		double r = rng_->random_double();
 
 		chain.rejection_rates[i] += 1 - p;
@@ -592,8 +602,7 @@ void runner_pt_slave::start() {
 
 	MPI_Comm_rank(chain_comm_, &chain_rank_);
 
-	bool use_param_optimization =
-	    job_.jobfile["jobconfig"].defined("pt_parameter_optimization");
+	bool use_param_optimization = job_.jobfile["jobconfig"].defined("pt_parameter_optimization");
 
 	if(!accept_new_chain()) {
 		job_.log(fmt::format("rank {} exits: out of work", rank_));
@@ -704,7 +713,8 @@ void runner_pt_slave::pt_global_update() {
 
 bool runner_pt_slave::accept_new_chain() {
 	int64_t msg[3];
-	MPI_Recv(&msg, sizeof(msg) / sizeof(msg[0]), MPI_INT64_T, 0, 0, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
+	MPI_Recv(&msg, sizeof(msg) / sizeof(msg[0]), MPI_INT64_T, 0, 0, MPI_COMM_WORLD,
+	         MPI_STATUS_IGNORE);
 	task_id_ = msg[0];
 	run_id_ = msg[1];
 	sweeps_before_communication_ = msg[2];
@@ -713,8 +723,8 @@ bool runner_pt_slave::accept_new_chain() {
 		return false;
 	}
 
-	sweeps_per_global_update_ =
-	    job_.jobfile["tasks"][job_.task_names[task_id_]].get<int64_t>("pt_sweeps_per_global_update");
+	sweeps_per_global_update_ = job_.jobfile["tasks"][job_.task_names[task_id_]].get<int64_t>(
+	    "pt_sweeps_per_global_update");
 
 	sys_ = std::unique_ptr<mc>{mccreator_(job_.jobfile["tasks"][job_.task_names[task_id_]])};
 	sys_->pt_mode_ = true;

src/runner_pt.h

@@ -19,7 +19,7 @@ struct pt_chain {
 	int entries_before_optimization{0};
 
 	std::vector<double> rejection_rates;
-	std::vector<int> rejection_rate_entries{0,0};
+	std::vector<int> rejection_rate_entries{0, 0};
 
 	bool is_done();
 	void checkpoint_read(const iodump::group &g);
@@ -90,7 +90,7 @@ private:
 
 public:
 	runner_pt_master(jobinfo job);
-	void start();
+	int start();
 };
 
 class runner_pt_slave {

src/runner_single.cpp

@@ -11,8 +11,7 @@ namespace loadl {
 
 int runner_single_start(jobinfo job, const mc_factory &mccreator, int, char **) {
 	runner_single r{std::move(job), mccreator};
-	r.start();
-	return 0;
+	return r.start();
 }
 
 runner_single::runner_single(jobinfo job, mc_factory mccreator)
@@ -50,7 +49,8 @@ int runner_single::start() {
 		task_id_ = get_new_task_id(task_id_);
 	}
 
-	return 0;
+	bool all_done = task_id_ < 0;
+	return !all_done;
 }
 
 bool runner_single::is_checkpoint_time() const {

src/runner_task.cpp

@@ -3,10 +3,8 @@
 
 namespace loadl {
 
-runner_task::runner_task(size_t target_sweeps, size_t sweeps,
-                         int scheduled_runs)
-    : target_sweeps{target_sweeps}, sweeps{sweeps},
-      scheduled_runs{scheduled_runs} {}
+runner_task::runner_task(size_t target_sweeps, size_t sweeps, int scheduled_runs)
+    : target_sweeps{target_sweeps}, sweeps{sweeps}, scheduled_runs{scheduled_runs} {}
 
 bool runner_task::is_done() const {
 	return sweeps >= target_sweeps;

src/util.cpp

@@ -4,66 +4,69 @@
 
 namespace loadl {
 
-//https://en.wikipedia.org/wiki/Monotone_cubic_interpolation
-monotonic_interpolator::monotonic_interpolator(const std::vector<double>& x, const std::vector<double>& y) : x_(x), y_(y), m_(x.size()) {
+// https://en.wikipedia.org/wiki/Monotone_cubic_interpolation
+monotonic_interpolator::monotonic_interpolator(const std::vector<double> &x,
+                                               const std::vector<double> &y)
+    : x_(x), y_(y), m_(x.size()) {
 	assert(x.size() == y.size());
 	assert(x.size() > 1);
 
 	std::vector<double> d(x.size());
-	for(size_t i = 0; i < x.size()-1; i++) {
-		d[i] = (y[i+1]-y[i])/(x[i+1]-x[i]);
+	for(size_t i = 0; i < x.size() - 1; i++) {
+		d[i] = (y[i + 1] - y[i]) / (x[i + 1] - x[i]);
 	}
 	m_[0] = d[0];
-	m_[x.size()-1] = d[x.size()-2];
-	for(std::size_t i = 1; i < x.size()-1; i++) {
-		m_[i] = (d[i-1]+d[i])/2;
+	m_[x.size() - 1] = d[x.size() - 2];
+	for(std::size_t i = 1; i < x.size() - 1; i++) {
+		m_[i] = (d[i - 1] + d[i]) / 2;
 
-		if(d[i-1]*d[i] <= 0) {
+		if(d[i - 1] * d[i] <= 0) {
 			m_[i] = 0;
 		}
 	}
-	for(std::size_t i = 0; i < x.size()-1; i++) {
-		double a = m_[i]/d[i];
-		double b = m_[i+1]/d[i];
+	for(std::size_t i = 0; i < x.size() - 1; i++) {
+		double a = m_[i] / d[i];
+		double b = m_[i + 1] / d[i];
 
-		double r = a*a + b*b;
+		double r = a * a + b * b;
 		if(r > 9) {