Skip to main content
torch.js has not been released yet.
torch.js logotorch.js logotorch.js
PlaygroundContact
Login
Documentation
IntroductionType SafetyTensor ExpressionsTensor IndexingEinsumEinopsAutogradTraining a ModelProfiling & MemoryPyTorch MigrationBest PracticesRuntimesPerformancePyTorch CompatibilityBenchmarksDType Coverage
IntroductionRenderer GalleryRenderersAnalysis
computeQuantilescomputePercentilescomputeCorrelationcomputeCovariancedetectOutliersdetectOutliersZScorecomputeExtendedStatsdescribeExtendedStatsQuantileResultCorrelationResultOutlierResultExtendedStatscreateDBSCANdbscanDBSCANDBSCAN.fitDBSCAN.destroyDBSCANOptionsDBSCANResultcreateHierarchicalClusteringhierarchicalClusteringHierarchicalClusteringHierarchicalClustering.fitHierarchicalClustering.destroyLinkageMethodDistanceMetricHierarchicalOptionsDendrogramNodeHierarchicalResultcomputeHistogramgetHistogramCentersnormalizeHistogramHistogramResultcreateKDEkdeKDEKDE.fitKDE.destroyKernelTypeKDEOptionsKDEResultcreateKMeanskmeansKMeansKMeans.fitKMeans.destroyKMeansOptionsKMeansResultcreatePCApcaPCAPCA.fitPCA.destroyPCAOptionsPCAResultthrottleProgressconsoleProgressProgressInfoProgressCallbackcomputeStatscomputeMinMaxdescribeStatsTensorStatscreateTSNEtsneTSNETSNE.fitTSNE.destroyTSNEOptionsTSNEResultcreateUMAPumapUMAPUMAP.fitUMAP.destroyUMAPOptionsUMAPResult
torch.js· 2026
LegalTerms of UsePrivacy Policy
/
/
  1. docs
  2. viz
  3. viz
  4. analysis
  5. HistogramResult

viz.analysis.HistogramResult

export interface HistogramResult {
  /** Bin counts */
  counts: Uint32Array;
  /** Bin edges (length = numBins + 1) */
  edges: Float32Array;
  /** Min value used for binning */
  min: number;
  /** Max value used for binning */
  max: number;
  /** Number of bins */
  numBins: number;
}
counts(Uint32Array)
– Bin counts
edges(Float32Array)
– Bin edges (length = numBins + 1)
min(number)
– Min value used for binning
max(number)
– Max value used for binning
numBins(number)
– Number of bins
Previous
HierarchicalResult
Next
kde