Classification algorithms.

Categories

• Classification: ada-boost decision-tree fld gradient-tree-boost knn lda liblinear logistic-regression naive-bayes neural-net qda random-forest rbf-network rda svm
• Validation: accuracy confusion-map validate

Other vars: activation-functions-list backend bayes-models-list cv data-native error-functions-list labels liblinear-solver-list model-native multiclass-strategies-list predict predict-all split-rules-list train

Clustering algorithms.

Categories

Other vars: ->ClusteringResult clarans clustering-methods-list dbscan denclue deterministic-annealing g-means k-means map->ClusteringResult mec neural-gas predict regroup x-means

Complex numbers functions.

Categories

• Power / logarithm: exp log pow
• Trigonometry: acos asin atan cos cosh csc sec sin sinh tan tanh

Other vars: abs add arg complex conjugate div mult neg reciprocal sq sqrt sqrt1z sub

Collection of fast math functions and plethora of constants known from other math libraries.

Categories

• Bitwise: << >> >>> bit-and bit-not bit-or bit-shift-left bit-shift-right bit-xor unsigned-bit-shift-right
• Boolean: between-? between? bool-and bool-not bool-or bool-xor inf? invalid-double? nan? neg-inf? pos-inf? valid-double?
• Comparison: < <= == > >= between-? between? eq even? inf? invalid-double? nan? neg-inf? neg? not== odd? one? pos-inf? pos? valid-double? zero?
• Conversions: cnorm constrain cos-interpolation degrees lerp make-norm mlerp norm quad-interpolation radians smooth-interpolation smoothstep wrap
• Distance: dist hypot hypot-sqrt qdist
• Error: erf erfc inv-erf inv-erfc
• Mod: gcd lcm mod quot rem remainder
• Powers / logarithms: cb cbrt exp expm1 fpow high-2-exp high-exp ln log log10 log1p log1pexp log2 logb logit low-2-exp low-exp pow pow2 pow3 qexp qlog qpow qsqrt rqsqrt safe-sqrt sigmoid sq sqrt
• Primitive: * + - / dec fast* fast+ fast- fast-identity fast-max fast-min inc max min unuse-primitive-operators use-primitive-operators
• Rank: order rank
• Rounding: abs approx approx-eq ceil floor frac iabs itrunc qceil qfloor qround rint round round-even round-up-pow2 sfrac trunc
• Sampling: sample
• Primitive <-> Seq converters: double-array->seq double-double-array->seq seq->double-array seq->double-double-array
• Sign: sgn signum
• Special functions: bessel-j digamma gamma inv-gamma-1pm1 log-beta log-gamma log-gamma-1p regularized-beta regularized-gamma-p regularized-gamma-q trigamma
• Trigonometry: acos acosh acot acoth acsc acsch asec asech asin asinh atan atan2 atanh cos cosh cot coth csc csch haversine haversine-dist qcos qsin sec sech sin sinc sinh tan tanh

Other vars: co-intervals cut group-by-intervals mnorm next-double prev-double slice-range

Distance objects.

Categories

Other vars: canberra chebyshev correlation cosine discrete earth-movers euclidean euclidean-sq jensen-shannon make-mahalanobis make-minkowski manhattan

Easing functions.

Categories

• Anticipatory easings: back-in back-in-out back-out
• Bounce: bounce-in bounce-in-out bounce-out
• Circular: circle-in circle-in-out circle-out
• Creators: in-out out reflect
• Cubic: cubic-in cubic-in-out cubic-out
• Elastic: elastic-in elastic-in-out elastic-out
• Exponential: exp-in exp-in-out exp-out
• Linear: linear
• Polynomial: poly-in poly-in-out poly-out
• Quadratic: quad-in quad-in-out quad-out
• Sinusoidal: sin-in sin-in-out sin-out

Other vars: easings-list

Vector field functions.

Categories

• Create fields: field parametrization
• Derive scalar field from vector field: cross curl divergence dot heading jacobian magnitude
• Derive vector field from other vector field(s).: *skip-random-fields* angle-between combine composition derivative grad-x grad-y multiplication random-configuration randomize-configuration scalar->vector-field sum

Other vars: ->VoronCalcType ->VoronResType fields-list fields-list-not-random fields-list-random

Grid calculation functions.

Categories

Other vars: cell->anchor cell->mid cell-names coords->anchor coords->cell coords->mid corners flat-hex-corners grid grid-type pointy-hex-corners

1d, 2d interpolation functions.

Categories

• Apache Commons Math interpolators: akima-spline bicubic divided-difference interpolators-1d-list interpolators-2d-list linear loess microsphere-2d-projection microsphere-projection neville piecewise-bicubic spline step step-after step-before
• 1d interpolation: akima-spline b-spline b-spline-interp cubic-spline divided-difference interpolators-1d-list kriging-spline linear linear-smile loess microsphere-projection monotone neville polynomial rbf shepard spline step step-after step-before
• 2d interpolation (grid based): bicubic bicubic-smile bilinear cubic-2d interpolators-2d-list microsphere-2d-projection piecewise-bicubic
• Smile interpolators: bicubic-smile bilinear cubic-2d cubic-spline interpolators-1d-list interpolators-2d-list kriging-spline linear-smile rbf shepard
• SSJ interpolators: b-spline b-spline-interp polynomial

Various kernel functions.

Categories

• Density kernels: kernel-density kernel-density-ci
• Vector kernels: approx cpd->pd exp fields kernel kernel->rbf mult rbf->kernel scale smile-mercer wadd
• RBF kernels: kernel->rbf rbf rbf->kernel smile-rbf

Other vars: kernel-density-list kernels-list rbf-list

Optimization.

Categories

Other vars: bayesian-optimization maximize maximizer minimize minimizer scan-and-maximize scan-and-minimize

Set of protocols for fastmath.

Categories

Other vars: ->seq abs add approx as-vec axis-rotate backend base-from brandom cdf cell->anchor continuous? coords->cell coords->mid corners covariance cross cv data-native dimensions distribution-id distribution-parameters dot drandom econstrain einterpolate emn emult emx fmap forward-1d forward-2d frandom from-polar grandom grid-type heading icdf interpolate irandom is-near-zero? is-zero? lower-bound lpdf lrandom mag magsq maxdim mean means mindim mn model-native mult mx pdf permute perpendicular posterior-samples predict predict-all prior-samples probability reciprocal reverse-1d reverse-2d rotate sample set-seed! source-object sub sum to-polar to-vec train transform upper-bound variance

Various random and noise functions.

Categories

• Distributions: cdf continuous? covariance default-normal dimensions distribution distribution-id distribution-parameters distributions-list icdf likelihood log-likelihood lower-bound lpdf mean means observe observe1 pdf probability sample source-object upper-bound variance
• Random sequence generation: sequence-generator sequence-generators-list
• Noise functions: billow-noise discrete-noise fbm-noise noise noise-generators noise-interpolations noise-types random-noise-cfg random-noise-fn ridgedmulti-noise simplex single-noise vnoise warp-noise-fn
• Random number generation: ->seq brand brandom default-rng drand drandom flip flipb frand frandom grand grandom irand irandom lrand lrandom randval rng rngs-list set-seed! synced-rng

Other vars: jittered-sequence-generator

Categories

• reg: elastic-net gaussian-process gradient-tree-boost lasso neural-net ols random-forest rbf-network regression-tree ridge rls svr

Other vars: backend cv data-native gaussian-process+ loss-list model-native posterior-samples predict predict-all prior-samples regression train validate

Signal processing (effect) and generation (oscillators).

Categories

• Effects: apply-effects apply-effects-raw compose-effects effect effects-list
• oscillator: oscillator oscillator->signal oscillator-gain oscillators oscillators-sum signal->oscillator
• Signal: load-signal save-signal

Other vars: ->BiquadConf ->EffectsList ->SampleAndState ->StateBassTreble ->StateBiquad ->StateDecimator ->StateDivider ->StateEcho ->StateFm ->StateMdaThruZero ->StateVcf303 db->linear linear->db

Statistics functions.

Categories

• Correlation: correlation covariance covariance-matrix jensen-shannon-divergence kendall-correlation kullback-leibler-divergence pearson-correlation spearman-correlation
• Effect size: ameasure cliffs-delta cohens-d cohens-d-orig glass-delta hedges-g hedges-g*
• Extents: adjacent-values bootstrap-ci ci extent mad-extent percentile-extent sem-extent stddev-extent
• Normalize: demean standardize
• Descriptive statistics: binary-measures binary-measures-all estimate-bins estimation-strategies-list histogram iqr kurtosis maximum mean median median-3 median-absolute-deviation minimum mode modes outliers percentile percentiles population-stddev population-variance quantile quantiles sem skewness stats-map stddev sum variance
• Hypothesis test: ttest-one-sample ttest-two-samples
• Time series: acf acf-ci pacf pacf-ci

Other vars: bootstrap moment second-moment

Transforms.

Categories

• Process: compress denoise
• Transform: forward-1d forward-2d reverse-1d reverse-2d transformer wavelets-list

Mathematical vector operations.

Categories

• Distance / length: dist dist-abs dist-canberra dist-cheb dist-cos dist-discrete dist-emd dist-sq distances limit mag magsq normalize set-mag
• Creators: array->vec2 array->vec3 array->vec4 array-vec as-vec generate-vec2 generate-vec3 generate-vec4 make-vector seq->vec2 seq->vec3 seq->vec4 to-vec vec->Vec vec2 vec3 vec4
• Geometric: aligned? angle-between axis-rotate base-from cross dot faceforward from-polar heading mag magsq perpendicular relative-angle-between rotate to-polar transform
• Math operations: acos acosh acot acoth acsc asec asech asin asinh atan atanh cbrt ceil cos cosh cot coth csc csch degrees exp expm1 floor frac ln log log10 log1p log2 radians rint round safe-sqrt sec sech sfrac sgn sigmoid signum sin sinc sinh sq sqrt tan tanh trunc
• Operations: abs add applyf approx average-vectors clamp div econstrain ediv einterpolate emn emult emx fmap interpolate is-near-zero? is-zero? maxdim mindim mn mult mx nonzero-count permute reciprocal sub sum zero-count

Other vars: ->ArrayVec ->Vec2 ->Vec3 ->Vec4