stats

type AlignPoint struct {
	QueryIndex int     `json:"query_index"` // Index in query sequence
	RefIndex   int     `json:"ref_index"`   // Index in reference sequence
	Cost       float64 `json:"cost"`        // Local cost at this point
}

type AlignmentAnalyzer struct {
	// contains filtered or unexported fields
}

type AlignmentMethod int

type AlignmentResult struct {
	// Primary alignment information
	Method        AlignmentMethod `json:"method"`
	Offset        int             `json:"offset"`         // Sample offset (negative = query is delayed)
	OffsetSeconds float64         `json:"offset_seconds"` // Offset in seconds
	Confidence    float64         `json:"confidence"`     // Alignment confidence (0-1)
	Similarity    float64         `json:"similarity"`     // Overall similarity score

	// DTW-specific results
	DTWResult *DTWResult `json:"dtw_result,omitempty"`

	// Cross-correlation results
	CrossCorrResult *CorrelationResult `json:"cross_corr_result,omitempty"`

	// Quality metrics
	AlignmentQuality float64 `json:"alignment_quality"` // Quality of alignment
	NoiseLevel       float64 `json:"noise_level"`       // Estimated noise level
	Stability        float64 `json:"stability"`         // Stability of alignment

	// Analysis metadata
	QueryLength     int     `json:"query_length"`
	ReferenceLength int     `json:"reference_length"`
	ProcessingTime  float64 `json:"processing_time"` // Processing time (ms)
	SampleRate      int     `json:"sample_rate"`
}

type AlignmentStats struct {
	MeanOffset   float64 `json:"mean_offset"`
	StdDevOffset float64 `json:"stddev_offset"`
	MedianOffset float64 `json:"median_offset"`
	OffsetRange  float64 `json:"offset_range"`
	Consistency  float64 `json:"consistency"` // How consistent are multiple alignments
}

type AutoCorrelation struct {
	// contains filtered or unexported fields
}

type Cluster struct {
	ID       int         `json:"id"`
	Center   []float64   `json:"center"`   // Cluster centroid
	Points   [][]float64 `json:"points"`   // Points in this cluster
	Indices  []int       `json:"indices"`  // Original indices of points
	Size     int         `json:"size"`     // Number of points in cluster
	Variance float64     `json:"variance"` // Within-cluster variance
	Radius   float64     `json:"radius"`   // Maximum distance from center
}

type Clustering struct {
	// contains filtered or unexported fields
}

type ClusteringAlgorithm int

type ClusteringParams struct {
	NumClusters   int                 `json:"num_clusters"`
	MaxIterations int                 `json:"max_iterations"`
	Tolerance     float64             `json:"tolerance"`
	Algorithm     ClusteringAlgorithm `json:"algorithm"`
	Distance      DistanceMetric      `json:"distance"`
	Linkage       LinkageCriterion    `json:"linkage"`

	// DBSCAN specific parameters
	Epsilon   float64 `json:"epsilon"`    // Maximum distance between points
	MinPoints int     `json:"min_points"` // Minimum points to form cluster

	// Initialization parameters
	InitMethod string `json:"init_method"` // "random", "kmeans++", "manual"
	RandomSeed int64  `json:"random_seed"`

	// Convergence parameters
	RelativeTolerance bool `json:"relative_tolerance"`
}

type ClusteringResult struct {
	Clusters           []Cluster   `json:"clusters"`
	Labels             []int       `json:"labels"`            // Cluster assignment for each point
	Centers            [][]float64 `json:"centers"`           // Cluster centers
	Inertia            float64     `json:"inertia"`           // Total within-cluster sum of squares
	SilhouetteScore    float64     `json:"silhouette_score"`  // Overall silhouette coefficient
	DaviesBouldinIndex float64     `json:"davies_bouldin"`    // Davies-Bouldin index
	CalinskiHarabasz   float64     `json:"calinski_harabasz"` // Calinski-Harabasz index
	NumClusters        int         `json:"num_clusters"`
	Converged          bool        `json:"converged"`
	Iterations         int         `json:"iterations"`
}

type CorrelationMethod int

type CorrelationResult struct {
	// Primary correlation values
	Correlations []float64 `json:"correlations"`
	Lags         []int     `json:"lags"`

	// Peak correlation information
	PeakCorrelation float64 `json:"peak_correlation"`
	PeakLag         int     `json:"peak_lag"`
	PeakIndex       int     `json:"peak_index"`

	// Statistical significance
	PValue          float64 `json:"p_value"`
	IsSignificant   bool    `json:"is_significant"`
	ConfidenceLevel float64 `json:"confidence_level"`

	// Correlation quality metrics
	SNR            float64 `json:"snr"`              // Signal-to-noise ratio
	Sharpness      float64 `json:"sharpness"`        // Peak sharpness
	SecondPeak     float64 `json:"second_peak"`      // Second highest peak
	PeakToSidelobe float64 `json:"peak_to_sidelobe"` // Peak-to-sidelobe ratio

	// Computational details
	Method          CorrelationMethod `json:"method"`
	Type            CorrelationType   `json:"type"`
	MaxLag          int               `json:"max_lag"`
	OverlapLength   int               `json:"overlap_length"`
	ComputationTime float64           `json:"computation_time"` // in milliseconds
}

type CorrelationType int

type CrossCorrelation struct {
	// contains filtered or unexported fields
}

type DTWAlignment struct {
	// contains filtered or unexported fields
}

type DTWResult struct {
	Distance    float64      `json:"distance"`     // Total DTW distance
	Path        []AlignPoint `json:"path"`         // Optimal alignment path
	CostMatrix  [][]float64  `json:"cost_matrix"`  // DTW cost matrix
	QueryLength int          `json:"query_length"` // Length of query sequence
	RefLength   int          `json:"ref_length"`   // Length of reference sequence
	Normalized  bool         `json:"normalized"`   // Whether distance is normalized
	StepPattern string       `json:"step_pattern"` // Step pattern used
	Constraint  int          `json:"constraint"`   // Band constraint used
}

type DistanceFunction func(a, b []float64) float64

type DistanceMetric int

type Entropy struct {
	// contains filtered or unexported fields
}

type EntropyParams struct {
	NumBins         int             `json:"num_bins"`
	HistogramMethod HistogramMethod `json:"histogram_method"`
	RenyiAlpha      float64         `json:"renyi_alpha"` // Parameter for Rényi entropy
	TsallisQ        float64         `json:"tsallis_q"`   // Parameter for Tsallis entropy

	// Normalization options
	NormalizeEntropy bool    `json:"normalize_entropy"`
	BaseLog          float64 `json:"base_log"` // Base for logarithm (2, e, 10)

	// Smoothing options
	SmoothHistogram bool    `json:"smooth_histogram"`
	SmoothingKernel string  `json:"smoothing_kernel"` // "gaussian", "uniform"
	SmoothingWidth  float64 `json:"smoothing_width"`

	// Boundary handling
	BoundaryMethod string  `json:"boundary_method"` // "reflect", "extend", "zero"
	MinProbability float64 `json:"min_probability"` // Minimum probability for log calculation
}

type EntropyResult struct {
	// Primary entropy measures
	ShannonEntropy   float64 `json:"shannon_entropy"`
	RenyiEntropy     float64 `json:"renyi_entropy"`
	TsallisEntropy   float64 `json:"tsallis_entropy"`
	HartleyEntropy   float64 `json:"hartley_entropy"`
	CollisionEntropy float64 `json:"collision_entropy"`
	MinEntropy       float64 `json:"min_entropy"`

	// Normalized entropy measures (0-1 range)
	NormalizedShannon float64 `json:"normalized_shannon"`
	NormalizedRenyi   float64 `json:"normalized_renyi"`

	// Entropy rate and conditional entropy
	EntropyRate        float64 `json:"entropy_rate"`
	ConditionalEntropy float64 `json:"conditional_entropy"`

	// Histogram information
	Histogram       []float64       `json:"histogram"`
	BinEdges        []float64       `json:"bin_edges"`
	BinCenters      []float64       `json:"bin_centers"`
	NumBins         int             `json:"num_bins"`
	HistogramMethod HistogramMethod `json:"histogram_method"`

	// Statistical measures
	Variance float64 `json:"variance"`
	Skewness float64 `json:"skewness"`
	Kurtosis float64 `json:"kurtosis"`

	// Parameters used
	RenyiAlpha float64 `json:"renyi_alpha"`
	TsallisQ   float64 `json:"tsallis_q"`

	// Data characteristics
	NumSamples     int     `json:"num_samples"`
	DataRange      float64 `json:"data_range"`
	EffectiveRange float64 `json:"effective_range"` // Range containing 95% of data
}

type EntropyType int

type ExtremeInfo struct {
	Min           float64   `json:"min"`
	Max           float64   `json:"max"`
	Range         float64   `json:"range"`
	LowerOutliers []float64 `json:"lower_outliers"` // Values < Q1 - 1.5*IQR
	UpperOutliers []float64 `json:"upper_outliers"` // Values > Q3 + 1.5*IQR
	LowerExtreme  []float64 `json:"lower_extreme"`  // Values < Q1 - 3*IQR
	UpperExtreme  []float64 `json:"upper_extreme"`  // Values > Q3 + 3*IQR
}

type HistogramMethod int

type LinkageCriterion int

type MomentParams struct {
	MaxOrder         int  `json:"max_order"`         // Maximum moment order to compute
	ComputeLMoments  bool `json:"compute_l_moments"` // Whether to compute L-moments
	ComputeCumulants bool `json:"compute_cumulants"` // Whether to compute cumulants

	// Numerical stability options
	UseWelfordMethod  bool    `json:"use_welford_method"`  // Use Welford's algorithm for numerical stability
	ClampLargeMoments bool    `json:"clamp_large_moments"` // Clamp extremely large moments
	MaxMomentValue    float64 `json:"max_moment_value"`    // Maximum allowed moment value

	// Distribution fitting options
	FitDistribution bool `json:"fit_distribution"` // Attempt to fit known distributions
	TestNormality   bool `json:"test_normality"`   // Test for normality using moments

	// Robust estimation options
	UseRobustEstimation bool    `json:"use_robust_estimation"` // Use robust moment estimation
	TrimProportion      float64 `json:"trim_proportion"`       // Proportion to trim for robust estimation
}

type MomentResult struct {
	// Basic descriptive statistics
	Mean     float64 `json:"mean"`     // First raw moment (μ₁)
	Variance float64 `json:"variance"` // Second central moment (σ²)
	StdDev   float64 `json:"std_dev"`  // Standard deviation (σ)
	Skewness float64 `json:"skewness"` // Third standardized moment
	Kurtosis float64 `json:"kurtosis"` // Fourth standardized moment (excess)

	// Raw moments about origin
	RawMoments []float64 `json:"raw_moments"` // μ'ᵣ = E[Xʳ]

	// Central moments about mean
	CentralMoments []float64 `json:"central_moments"` // μᵣ = E[(X-μ)ʳ]

	// Standardized moments
	StandardizedMoments []float64 `json:"standardized_moments"` // μᵣ/σʳ

	// Absolute moments
	AbsoluteMoments []float64 `json:"absolute_moments"` // E[|X-μ|ʳ]

	// Higher order moment statistics
	Hyperskewness float64 `json:"hyperskewness"` // Fifth standardized moment
	Hyperkurtosis float64 `json:"hyperkurtosis"` // Sixth standardized moment

	// Distribution shape measures
	CoefficientOfVariation float64 `json:"coefficient_of_variation"` // σ/μ
	StandardError          float64 `json:"standard_error"`           // σ/√n

	// Moment-based distribution measures
	PearsonMomentSkewness float64 `json:"pearson_moment_skewness"` // 3(μ-median)/σ
	BowleySkewness        float64 `json:"bowley_skewness"`         // Quartile-based skewness

	// L-moments (linear combinations of order statistics)
	LMoments      []float64 `json:"l_moments"`       // L₁, L₂, L₃, L₄, ...
	LMomentRatios []float64 `json:"l_moment_ratios"` // τ₂, τ₃, τ₄, ... (L-CV, L-skew, L-kurt)

	// Cumulants (moment-generating function derivatives)
	Cumulants []float64 `json:"cumulants"` // κ₁, κ₂, κ₃, κ₄, ...

	// Sample properties
	NumSamples  int     `json:"num_samples"`
	SampleRange float64 `json:"sample_range"`

	// Moment convergence information
	MomentOrder int    `json:"moment_order"` // Highest computed moment order
	Convergence []bool `json:"convergence"`  // Whether each moment converged
}

type MomentType int

type Moments struct {
	// contains filtered or unexported fields
}

type PercentileMethod int

type PercentileResult struct {
	Values      []float64           `json:"values"`      // Original sorted values
	Percentiles map[float64]float64 `json:"percentiles"` // Percentile -> value mapping
	Quartiles   QuartileInfo        `json:"quartiles"`   // Q1, Q2, Q3 information
	Extremes    ExtremeInfo         `json:"extremes"`    // Min, max, outliers
	Summary     SummaryStats        `json:"summary"`     // Basic statistics
	Method      PercentileMethod    `json:"method"`      // Calculation method used
}

type Percentiles struct {
	// contains filtered or unexported fields
}

type QuartileInfo struct {
	Q1  float64 `json:"q1"`  // First quartile (25th percentile)
	Q2  float64 `json:"q2"`  // Second quartile (50th percentile, median)
	Q3  float64 `json:"q3"`  // Third quartile (75th percentile)
	IQR float64 `json:"iqr"` // Interquartile range (Q3 - Q1)
}

type SummaryStats struct {
	Count    int     `json:"count"`
	Mean     float64 `json:"mean"`
	Variance float64 `json:"variance"`
	StdDev   float64 `json:"std_dev"`
	Skewness float64 `json:"skewness"`
	Kurtosis float64 `json:"kurtosis"`
}