private static void Evaluate
(
int remainingCombinations,
bool enableMultithreading,
IEnumerable <AminoAcidProfile> currentProfiles,
IEnumerable <AminoAcidProfile> profiles,
OptimalSource optimalSource,
OptimalSource optimalSource2
)
{
if (remainingCombinations <= 0)
{
decimal muscleGain = GetMuscleGain(currentProfiles);
UpdateOptimalSource(muscleGain, currentProfiles, optimalSource);
var sourceNames = new HashSet <string>();
foreach (var profile in currentProfiles)
{
sourceNames.Add(profile.Source);
}
if (sourceNames.Count <= 2)
{
UpdateOptimalSource(muscleGain, currentProfiles, optimalSource2);
}
return;
}
int newRemainingCombinations = remainingCombinations - 1;
var tasks = new List <Task>();
foreach (var profile in profiles)
{
var newProfileList = new AminoAcidProfile[] { profile };
var newCurrentProfiles = currentProfiles.Concat(newProfileList);
Action evaluate = () => Evaluate(newRemainingCombinations, false, newCurrentProfiles, profiles, optimalSource, optimalSource2);
if (enableMultithreading)
{
var task = new Task(evaluate);
task.Start();
tasks.Add(task);
}
else
{
evaluate();
}
}
if (enableMultithreading)
{
foreach (var task in tasks)
{
task.Wait();
}
}
}
static void Main(string[] arguments)
{
var currentProfiles = new AminoAcidProfile[] { };
var optimalSource = new OptimalSource();
var optimalSource2 = new OptimalSource();
int granularity = 10;
Evaluate(granularity, true, currentProfiles, Profiles.Sources, optimalSource, optimalSource2);
PrintOptimalSource("Optimal combination of plant-based protein sources for muscle gain", optimalSource, granularity);
PrintOptimalSource("When limiting blend to just two ingredients", optimalSource2, granularity);
foreach (var profile in Profiles.Sources)
{
var simpleProfile = new AminoAcidProfile[] { profile };
decimal muscleGain = GetMuscleGain(simpleProfile);
Console.WriteLine($"In comparison to 100% \"{profile.Source}\" protein: {muscleGain * 100:0.0} g");
}
}
