spt/loot-dump-processor
spt/loot-dump-processor
0
0
Fork 0
mirror of https://github.com/sp-tarkov/loot-dump-processor.git synced 2025-02-13 03:30:45 -05:00
Code

Replaced NumSharp with custom math functions for mean and standard deviation calculations

Browse Source
This commit is contained in:
bluextx 2025-01-11 08:31:59 +03:00
parent 36917aa556
commit f31fdaa27d
2 changed files with 51 additions and 37 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

15
source/LootDumpProcessor/LootDumpProcessor.csproj
View File

@ -11,14 +11,13 @@
</PropertyGroup>
<ItemGroup>
<PackageReference Include="7z.Libs" Version="21.7.0" />
<PackageReference Include="Microsoft.Extensions.Logging" Version="9.0.0" />
<PackageReference Include="Microsoft.Extensions.Logging.Console" Version="9.0.0" />
<PackageReference Include="Newtonsoft.Json" Version="13.0.2" />
<PackageReference Include="NumSharp" Version="0.30.0" />
<PackageReference Include="SevenZipSharp.Interop" Version="19.1.0" />
<PackageReference Include="System.Configuration.ConfigurationManager" Version="7.0.0" />
<PackageReference Include="YamlDotNet" Version="13.0.0" />
<PackageReference Include="7z.Libs" Version="21.7.0"/>
<PackageReference Include="Microsoft.Extensions.Logging" Version="9.0.0"/>
<PackageReference Include="Microsoft.Extensions.Logging.Console" Version="9.0.0"/>
<PackageReference Include="Newtonsoft.Json" Version="13.0.2"/>
<PackageReference Include="SevenZipSharp.Interop" Version="19.1.0"/>
<PackageReference Include="System.Configuration.ConfigurationManager" Version="7.0.0"/>
<PackageReference Include="YamlDotNet" Version="13.0.0"/>
</ItemGroup>
<ItemGroup>

29
source/LootDumpProcessor/Process/Processor/v2/LooseLootProcessor/LooseLootProcessor.cs
View File

@ -6,7 +6,6 @@ using LootDumpProcessor.Storage;
using LootDumpProcessor.Storage.Collections;
using LootDumpProcessor.Utils;
using Microsoft.Extensions.Logging;
using NumSharp;
namespace LootDumpProcessor.Process.Processor.v2.LooseLootProcessor
{
@ -61,7 +60,7 @@ namespace LootDumpProcessor.Process.Processor.v2.LooseLootProcessor
)
{
var config = LootDumpProcessorContext.GetConfig();
var spawnPointTolerance = config.ProcessorConfig.SpawnPointToleranceForForced / 100;
var spawnPointTolerance = config.ProcessorConfig.SpawnPointToleranceForForced / 100.0;
var looseLootDistribution = new LooseLootRoot();
var probabilities = new Dictionary<string, double>();
@ -73,9 +72,9 @@ namespace LootDumpProcessor.Process.Processor.v2.LooseLootProcessor
probabilities[itemId] = (double)count / mapCount;
}
var spawnPointCount = looseLootCountsItem.MapSpawnpointCount.Select(Convert.ToDouble);
var initialMean = np.mean(np.array(spawnPointCount)).ToArray<double>().First();
var tolerancePercentage = config.ProcessorConfig.LooseLootCountTolerancePercentage / 100;
var spawnPointCount = looseLootCountsItem.MapSpawnpointCount.Select(Convert.ToDouble).ToList();
var initialMean = CalculateMean(spawnPointCount);
var tolerancePercentage = config.ProcessorConfig.LooseLootCountTolerancePercentage / 100.0;
var highThreshold = initialMean * (1 + tolerancePercentage);
looseLootCountsItem.MapSpawnpointCount = looseLootCountsItem.MapSpawnpointCount
@ -84,8 +83,8 @@ namespace LootDumpProcessor.Process.Processor.v2.LooseLootProcessor
looseLootDistribution.SpawnPointCount = new SpawnPointCount
{
Mean = np.mean(np.array(looseLootCountsItem.MapSpawnpointCount)),
Std = np.std(np.array(looseLootCountsItem.MapSpawnpointCount))
Mean = CalculateMean(looseLootCountsItem.MapSpawnpointCount.Select(Convert.ToDouble).ToList()),
Std = CalculateStandardDeviation(looseLootCountsItem.MapSpawnpointCount.Select(Convert.ToDouble).ToList())
};
looseLootDistribution.SpawnPointsForced = new List<SpawnPointsForced>();
looseLootDistribution.SpawnPoints = new List<SpawnPoint>();
@ -227,5 +226,21 @@ namespace LootDumpProcessor.Process.Processor.v2.LooseLootProcessor
return looseLootDistribution;
}
private double CalculateMean(IReadOnlyList<double> numbers)
{
if (!numbers.Any()) return 0;
return numbers.Average();
}
private double CalculateStandardDeviation(IReadOnlyList<double> numbers)
{
if (numbers.Count == 0) return 0;
var mean = CalculateMean(numbers);
var variance = numbers.Sum(num => Math.Pow(num - mean, 2)) / numbers.Count;
return Math.Sqrt(variance);
}
}
}