fastmath.complex
Complex numbers functions.
+Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.complex
Complex numbers functions.
Complex number is represented as Vec2 type (from clojure2d.math.vector namespace).
To create complex number use complex, vec2 or ->Vec2.
Simplified implementation based on Apache Commons Math. Functions don’t check NaNs or INF values.
diff --git a/docs/fastmath.core.html b/docs/fastmath.core.html index a929cc86..ba7d4812 100755 --- a/docs/fastmath.core.html +++ b/docs/fastmath.core.html @@ -1,6 +1,6 @@ -Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
fastmath.core
Collection of fast math functions and plethora of constants known from other math libraries.
+Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.core
Collection of fast math functions and plethora of constants known from other math libraries.
Primitive math operators
Based on Primitive Math by Zach Tellman several operators are introduced and replace clojure.core functions. All operators are macros and can’t be used as functions. List includes:
Known from Clojure: * + - / > < >= <= == rem quot mod bit-or bit-and bit-xor bit-not bit-shift-left bit-shift-right unsigned-bit-shift-right inc dec zero? neg? pos? min max even? odd?
Other functions
(sample sq 1 5 5) ;;=> (1.0 4.0 9.0 16.0 25.0)
seq->double-array
(seq->double-array vs)Convert sequence to double-array.
If sequence is double-array do not convert.
Examples
Convert
(seq->double-array [1 2 3])
-;;=> [D@5d58beef
+;;=> [D@72143dfe
(seq (seq->double-array [1 2 3]))
;;=> (1.0 2.0 3.0)
(double-array->seq (seq->double-array [1 2 3]))
;;=> (1.0 2.0 3.0)seq->double-double-array
(seq->double-double-array vss)Convert sequence to double-array of double-arrays.
If sequence is double-array of double-arrays do not convert
Examples
Convert
(seq->double-double-array [[1 2] [3 4]])
-;;=> [[D@51394772
+;;=> [[D@6a57e01d
(double-double-array->seq (seq->double-double-array [[1 2] [3 4]]))
;;=> ((1.0 2.0) (3.0 4.0))sfrac
(sfrac v)Fractional part, always returns values from -1.0 to 1.0 (exclusive). See frac for unsigned version.
Examples
Examples
(sfrac 0.555)
;;=> 0.555
diff --git a/docs/fastmath.easings.html b/docs/fastmath.easings.html
index 64050c4e..6211e870 100755
--- a/docs/fastmath.easings.html
+++ b/docs/fastmath.easings.html
@@ -1,6 +1,6 @@
-fastmath.easings documentation Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
fastmath.easings
Easing functions.
+fastmath.easings documentation Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.easings
Easing functions.
List of all are in easings-list.
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
Code snippets
Save incanter graph
(defn save-graph
[f params & opts]
(let [fname (str "images/e/" (first opts) ".png")]
diff --git a/docs/fastmath.fields.html b/docs/fastmath.fields.html
index e6132a9e..2699f50f 100755
--- a/docs/fastmath.fields.html
+++ b/docs/fastmath.fields.html
@@ -1,6 +1,6 @@
-fastmath.fields documentation Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
fastmath.fields
Vector field functions.
+fastmath.fields documentation Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.fields
Vector field functions.
Vector fields are functions R^2->R^2.
Names are taken from fractal flames world where such fields are call variations. Most implementations are taken from JWildfire software.
Creation
@@ -70,7 +70,7 @@ Combinations
:angles - vector field from anglesSee random-configuration for example.
Examples
Create random combination
(let [f (combine)] (f (v/vec2 -0.5 0.5)))
-;;=> #vec2 [0.6741473813480021, 0.38662762303139153]
Create combination for given configuration
(let [conf {:type :operation,
+;;=> #vec2 [0.900191726808197, 2.356194490192345]
field
multimethod
Return vector field for given name and options: amount (scaling factor) and parametrization.
Default scaling factor is 1.0, default parametrization is random.
Resulting function operates on Vec2 type.
Examples
Get vector field by name
(field :sinusoidal)
-;;=> fastmath.fields$make_sinusoidal$fn__10985@5c15e5f7
+;;=> fastmath.fields$make_sinusoidal$fn__10985@20459a8c
((field :sinusoidal) (v/vec2 m/HALF_PI m/HALF_PI))
;;=> #vec2 [1.0, 1.0]
Get vector field by name and scale
(field :sinusoidal 0.5)
-;;=> fastmath.fields$make_sinusoidal$fn__10985@59bbc16
+;;=> fastmath.fields$make_sinusoidal$fn__10985@5adaa8a5
((field :sinusoidal 0.5) (v/vec2 m/HALF_PI m/HALF_PI))
;;=> #vec2 [0.5, 0.5]
Apply parametrization
(let [params (parametrization :cpow3)
f (field :cpow3 1.0 params)]
{:parametrization params, :value (f (v/vec2 -1.0 1.0))})
-;;=> {:parametrization {:a 0.9284980493941015,
-;;=> :discrete-spread 0.7523397310488038,
-;;=> :divisor 0.1479716654236646,
-;;=> :offset2 0.7856762036698974,
-;;=> :r 0.15972930163930155,
-;;=> :spread 1.8544955909741334,
-;;=> :spread2 0.2044971898236998},
-;;=> :value #vec2 [0.01646361352909438, -0.02537121473871867]}
fields-list
Examples
List of all vector field names.
(sort fields-list)
+;;=> {:parametrization {:a -1.4801792495439008,
+;;=> :discrete-spread -0.5523513144642497,
+;;=> :divisor 1.8108045401312511,
+;;=> :offset2 -0.24116594833311034,
+;;=> :r 1.2777466468571959,
+;;=> :spread 0.5298508465749648,
+;;=> :spread2 -0.1063172474833527},
+;;=> :value #vec2 [0.892583823438129, -0.006980184890476318]}
fields-list
Examples
List of all vector field names.
(sort fields-list)
;;=> (:arch
;;=> :asteria
;;=> :atan :auger
@@ -274,72 +274,55 @@ Combinations
Optinally you can pass part of the parametrization. In this case function will add remaining keys with randomly generated values.
If field doesn’t have parametrization, empty map will be returned.
See field.
Examples
Get random parametrization for given field
(parametrization :auger)
-;;=> {:freq -2.834029212823601,
-;;=> :scale 1.4475951323678728,
-;;=> :sym -1.0778231366575053,
-;;=> :weight 0.30027579102591284}
Add lacking fields
(parametrization :auger {:scale 1.0, :freq 1.0})
+;;=> {:freq -3.3090272736543502,
+;;=> :scale 0.6846782051128593,
+;;=> :sym 0.759167177404489,
+;;=> :weight -0.3217995869971766}
Add lacking fields
(parametrization :auger {:scale 1.0, :freq 1.0})
;;=> {:freq 1.0,
;;=> :scale 1.0,
-;;=> :sym -1.9056211915442827,
-;;=> :weight 0.5913584484730507}
Returns empty map when field doesn’t have parametrization
(parametrization :sinusoidal)
+;;=> :sym -0.1438553364483921,
+;;=> :weight -0.8027908463897253}
Returns empty map when field doesn’t have parametrization
(parametrization :sinusoidal)
;;=> {}
random-configuration
(random-configuration)(random-configuration depth)(random-configuration depth f)Examples
Generate random configuration
(random-configuration)
;;=> {:amount 1.0,
+;;=> :config {:a -1.1178466389051778,
+;;=> :b -0.9085878300203412,
+;;=> :c 0.3013813589183245,
+;;=> :d -0.012929664932459062,
+;;=> :inside true,
+;;=> :shape 7},
+;;=> :name :hole2,
+;;=> :type :variation}
One node configuration
(random-configuration 0)
+;;=> {:amount 1.0, :config {}, :name :invtree, :type :variation}
Configuration with depth 2
(random-configuration 2)
+;;=> {:amount 1.0,
;;=> :name :comp,
;;=> :type :operation,
;;=> :var1 {:amount 1.0,
-;;=> :name :add,
+;;=> :name :comp,
;;=> :type :operation,
-;;=> :var1 {:amount 0.317993143873732,
-;;=> :config {:x 1.3280065957904936, :y 1.262174786282526},
-;;=> :name :splits,
+;;=> :var1 {:amount 1.0,
+;;=> :config {:i -0.4619830659037598,
+;;=> :power 4.27443162027975,
+;;=> :r -1.4767543755603034},
+;;=> :name :cpow,
;;=> :type :variation},
-;;=> :var2 {:amount 0.7027146844737944,
-;;=> :config {:scale 0.6551997725905991,
-;;=> :size -0.3814087476735846},
-;;=> :name :blurpixelize,
-;;=> :type :variation}},
-;;=> :var2 {:amount 1.0,
-;;=> :config {:area-x -0.5710602925276899,
-;;=> :area-y -1.6745101297270022,
-;;=> :center-x -0.29515423539565866,
-;;=> :center-y 0.9228000818712152,
-;;=> :delta-x 3.454060563697908,
-;;=> :delta-y 3.200412668245601,
-;;=> :gamma 2.7134455070767194,
-;;=> :square #},
-;;=> :name :gdoffs,
-;;=> :type :variation}}
One node configuration
(random-configuration 0)
-;;=> {:amount 1.0,
-;;=> :config {:stretch 1.9498420307717055},
-;;=> :name :csin,
-;;=> :type :variation}
Configuration with depth 2
(random-configuration 2)
-;;=> {:amount 0.5249492506976801,
-;;=> :name :add,
-;;=> :type :operation,
-;;=> :var1 {:amount -1.282564871968808,
-;;=> :config {:angle -4.139983434974827},
-;;=> :name :radialblur,
-;;=> :type :variation},
-;;=> :var2 {:amount -0.6223811750461312,
-;;=> :config {:stretch -1.1534356586589611},
-;;=> :name :csin,
-;;=> :type :variation}}
randomize-configuration
(randomize-configuration f)Randomize values for given configuration. Keeps structure untouched.
Examples
Usage
(let [conf {:type :variation,
+;;=> :var2
+;;=> {:amount 1.0, :config {}, :name :heart, :type :variation}},
+;;=> :var2 {:amount 1.0, :config {}, :name :fisheye, :type :variation}}
randomize-configuration
(randomize-configuration f)Randomize values for given configuration. Keeps structure untouched.
Examples
Usage
(let [conf {:type :variation,
:name :blocky,
:amount 1.0,
:config {:x -1.4, :y 0.9, :mp 2.6}}]
[(randomize-configuration conf) (randomize-configuration conf)])
;;=> [{:amount 1.0,
-;;=> :config {:mp -3.0261871247794443,
-;;=> :x 0.8948143297301634,
-;;=> :y 1.4982241799022784},
+;;=> :config
+;;=> {:mp 4.364146710177446, :x -1.497364993663199, :y 0.87113176452678},
;;=> :name :blocky,
;;=> :type :variation}
;;=> {:amount 1.0,
-;;=> :config {:mp -4.320957736019763,
-;;=> :x 0.5113965543053611,
-;;=> :y -0.7869372078038088},
+;;=> :config {:mp -3.3912091459058704,
+;;=> :x -1.2238026763956256,
+;;=> :y -1.4674849694976613},
;;=> :name :blocky,
;;=> :type :variation}]
scalar->vector-field
(scalar->vector-field scalar f)(scalar->vector-field scalar f1 f2)Returns vector field build from scalar fields of the input vector and result of the vector field.
Examples
Usage
(let [f (scalar->vector-field v/heading (field :sinusoidal))]
(v/applyf (f (v/vec2 m/HALF_PI m/HALF_PI)) m/degrees))
diff --git a/docs/fastmath.interpolation.html b/docs/fastmath.interpolation.html
index ca8060ad..a65d8693 100755
--- a/docs/fastmath.interpolation.html
+++ b/docs/fastmath.interpolation.html
@@ -1,6 +1,6 @@
-fastmath.interpolation documentation Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
fastmath.interpolation
1d, 2d interpolation functions.
+fastmath.interpolation documentation Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.interpolation
akima-spline
(akima-spline xs ys)Create cubic spline interpolator using Akima algorithm. Minimum number of points: 5
xs[n] < xs[n+1] for all n.
-Source: Apache Commons Math.
Examples
Akima plot
(save-interpolation akima-spline ...)
bicubic
(bicubic xs ys vs)Bicubic 2d.
+Source: Apache Commons Math.
Examples
Akima plot
(save-interpolation akima-spline 0.69 6.22 ...)
bicubic-smile
(bicubic-smile xs ys vs)Array layout
(let [intrp (cubic-2d [2 5] [1 6] [[-1 -2] [3 4]])]
[(intrp 2 1) (intrp 2 6) (intrp 5 1) (intrp 5 6)])
;;=> [-1.0 -2.0 3.0 4.0]
cubic-spline
(cubic-spline xs ys)Cubic spline interpolation.
-Source: Smile.
Examples
Cubic spline plot
(save-interpolation cubic-spline ...)
divided-difference
(divided-difference xs ys)Create Divided Difference Algorithm for interpolation.
-Source: Apache Commons Math.
Examples
Divided Difference plot
(save-interpolation divided-difference ...)
interpolators-1d-list
Map of 1d interpolation functions
Examples
List of names
(keys interpolators-1d-list)
+Source: Smile.
Examples
Cubic spline plot
(save-interpolation cubic-spline 0 7 ...)
divided-difference
(divided-difference xs ys)Create Divided Difference Algorithm for interpolation.
+Source: Apache Commons Math.
Examples
Divided Difference plot
(save-interpolation divided-difference 0.65 6.5 ...)
interpolators-1d-list
Map of 1d interpolation functions
linear
(linear xs ys)Create Divided Difference Algorithm for inqterpolation.
-Source: Apache Commons Math.
Examples
Linear (Apache Commons version) plot
(save-interpolation linear ...)
linear-smile
(linear-smile xs ys)Linear interpolation from Smile library.
-Source: Smile.
Examples
Linear (SMILE version) plot
(save-interpolation linear-smile ...)
loess
(loess xs ys)(loess bandwidth robustness-iters xs ys)(loess bandwidth robustness-iters accuracy xs ys)Local Regression Algorithm
+;; Test: ok.Kriging spline plot
(save-interpolation kriging-spline 0 7 ...)
linear
(linear xs ys)Create Divided Difference Algorithm for inqterpolation.
+Source: Apache Commons Math.
Examples
Linear (Apache Commons version) plot
(save-interpolation linear 0.69 6.22 ...)
linear-smile
(linear-smile xs ys)Linear interpolation from Smile library.
+Source: Smile.
Examples
Linear (SMILE version) plot
(save-interpolation linear-smile 0 7 ...)
loess
(loess xs ys)(loess bandwidth robustness-iters xs ys)(loess bandwidth robustness-iters accuracy xs ys)Local Regression Algorithm
- bandwidth: 0.2-1.0 (optimal: 0.25-0.5, default: 0.4)
- robustness-iters: 0-4 (optimal: 0, default: 2)
- accuracy: double (default: 1e-12)
-Source: Apache Commons Math.
Examples
Loess plot
(save-interpolation loess ...)
Loess plot, bandwidth=0.7, robustness-iters=4
(save-interpolation (fn [xs ys] (loess 0.7 4 xs ys)) ...)
Loess plot, bandwidth=0.2, robustness-iters=1
(save-interpolation (fn [xs ys] (loess 0.2 1 xs ys)) ...)
microsphere-2d-projection
(microsphere-2d-projection elements max-dark-friction dark-threshold background exponent shared-sphere? no-interpolation-tolerance xs ys vs)Microsphere projection interpolator - 2d version
+Source: Apache Commons Math.
Examples
Loess plot
(save-interpolation loess 0.69 6.22 ...)
Loess plot, bandwidth=0.7, robustness-iters=4
(save-interpolation (fn [xs ys] (loess 0.7 4 xs ys)) 0.69 6.22 ...)
Loess plot, bandwidth=0.2, robustness-iters=1
(save-interpolation (fn [xs ys] (loess 0.2 1 xs ys)) 0.69 6.22 ...)
microsphere-2d-projection
(microsphere-2d-projection elements max-dark-friction dark-threshold background exponent shared-sphere? no-interpolation-tolerance xs ys vs)Microsphere projection interpolator - 2d version
Grid based.
Source: Apache Commons Math.
microsphere-projection
(microsphere-projection elements max-dark-friction dark-threshold background exponent shared-sphere? no-interpolation-tolerance xs ys)Microsphere projection interpolator - 1d version
Source: Apache Commons Math.
Examples
Microsphere projection plot
(save-interpolation
(fn [xs ys]
(microsphere-projection 4 0.5 1.0E-7 0.1 2.5 false 0.1 xs ys))
- ...)
neville
(neville xs ys)Neville algorithm
-Source: Apache Commons Math.
Examples
Neville plot
(save-interpolation neville ...)
neville
(neville xs ys)Neville algorithm
+Source: Apache Commons Math.
Examples
Neville plot
(save-interpolation neville 0.65 6.5 ...)
piecewise-bicubic
(piecewise-bicubic xs ys vs)Piecewise bicubic 2d.
Grid based.
Source: Apache Commons Math.
rbf
(rbf rbf-fn normalize? xs ys)(rbf rbf-fn xs ys)RBF (Radial Basis Function) interpolation.
-Source: Smile
Examples
RBF - Linear
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :linear) xs ys)) ...)
RBF - Gaussian
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :gaussian) xs ys)) ...)
RBF - Multiquadratic
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :multiquadratic) xs ys))
- ...)
RBF - Inverse ultiquadratic
(save-interpolation (fn [xs ys]
+Source: Smile
Examples
RBF - Linear
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :linear) xs ys)) 0 7 ...)
RBF - Gaussian
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :gaussian) xs ys))
+ 0
+ 7
+ ...)
RBF - Multiquadratic
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :multiquadratic) xs ys))
+ 0
+ 7
+ ...)
RBF - Inverse ultiquadratic
(save-interpolation (fn [xs ys]
(rbf (rbf/rbf :inverse-multiquadratic) xs ys))
- ...)
RBF - Inverse quadratic
(save-interpolation (fn [xs ys]
+ 0
+ 7
+ ...)
RBF - Inverse quadratic
(save-interpolation (fn [xs ys]
(rbf (rbf/rbf :inverse-quadratic) xs ys))
- ...)
RBF - Thinplate
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :thinplate) xs ys)) ...)
RBF - Polyharmonic 3
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :polyharmonic 3) xs ys))
- ...)
RBF - Polyharmonic 4
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :polyharmonic 4) xs ys))
- ...)
RBF - Wendland
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :wendland) xs ys)) ...)
RBF - Wu
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :wu) xs ys)) ...)
shepard
(shepard xs ys)(shepard p xs ys)Shepard interpolation.
-Source: Smile.
Examples
Shepard plot
(save-interpolation shepard ...)
Shepard plot, p=5
(save-interpolation (fn [xs ys] (shepard 5 xs ys)) ...)
Shepard plot, p=0.9
(save-interpolation (fn [xs ys] (shepard 0.9 xs ys)) ...)
spline
(spline xs ys)Cubic spline interpolation
-Source: Apache Commons Math.
Examples
Spline plot
(save-interpolation spline ...)
step-after
(step-after xs ys)Step function.
Examples
Step function plot
(save-interpolation step-after ...)
step-before
(step-before xs ys)Step function.
Examples
Step function plot
(save-interpolation step-before ...)
\ No newline at end of file
+ 0
+ 7
+ ...)
RBF - Thinplate
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :thinplate) xs ys))
+ 0
+ 7
+ ...)
RBF - Polyharmonic 3
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :polyharmonic 3) xs ys))
+ 0
+ 7
+ ...)
RBF - Polyharmonic 4
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :polyharmonic 4) xs ys))
+ 0
+ 7
+ ...)
RBF - Wendland
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :wendland) xs ys))
+ 0
+ 7
+ ...)
RBF - Wu
(save-interpolation (fn [xs ys] (rbf (rbf/rbf :wu) xs ys)) 0 7 ...)
shepard
(shepard xs ys)(shepard p xs ys)Shepard interpolation.
+Source: Smile.
Examples
Shepard plot
(save-interpolation shepard 0 7 ...)
Shepard plot, p=5
(save-interpolation (fn [xs ys] (shepard 5 xs ys)) 0 7 ...)
Shepard plot, p=0.9
(save-interpolation (fn [xs ys] (shepard 0.9 xs ys)) 0 7 ...)
spline
(spline xs ys)Cubic spline interpolation
+Source: Apache Commons Math.
Examples
Spline plot
(save-interpolation spline 0.69 6.22 ...)
step-after
(step-after xs ys)Step function.
Examples
Step function plot
(save-interpolation step-after 0 7 ...)
step-before
(step-before xs ys)Step function.
Examples
Step function plot
(save-interpolation step-before 0 7 ...)
\ No newline at end of file
diff --git a/docs/fastmath.random.html b/docs/fastmath.random.html
index 2cdbd350..339cbf0e 100755
--- a/docs/fastmath.random.html
+++ b/docs/fastmath.random.html
@@ -1,6 +1,6 @@
-fastmath.random documentation Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
fastmath.random
Various random and noise functions.
+fastmath.random documentation Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.random
Various random and noise functions.
Namespace defines various random number generators (RNGs), different types of random functions, sequence generators and noise functions.
RNGs
You can use a selection of various RNGs defined in Apache Commons Math library.
@@ -75,19 +75,19 @@ Distribution
To create distribution call distribution multimethod with name as a keyword and map as parameters.
Categories
- Distributions: cdf distribution distributions-list icdf likelihood log-likelihood lower-bound lpdf mean pdf probability sample upper-bound variance
- Random sequence generation: sequence-generator sequence-generators-list
- Noise functions: billow-noise discrete-noise fbm-noise interpolations noise noise-types random-noise-cfg random-noise-fn ridgedmulti-noise simplex single-noise vnoise
- Random number generation: ->seq brand brandom default-rng drand drandom frand frandom grand grandom irand irandom lrand lrandom randval rng rngs-list set-seed!
billow-noise
Examples
Usage
(let [n (billow-noise {:seed 12345, :interpolation :none})]
(n 0.5 1.1 -1.3))
;;=> 0.16031746031746036
2d noise
brand
Random boolean with Mersenne Twister RNG.
Examples
Usage
(brand)
-;;=> false
+;;=> true
(brand 0.1)
-;;=> false
Count number of true values with probability 0.15
(count (filter true? (repeatedly 100000 (fn* [] (brand 0.15)))))
-;;=> 15032
default-rng
Default RNG - Mersenne Twister
Examples
Usage
(set-seed! default-rng 111)
-;;=> org.apache.commons.math3.random.MersenneTwister@e98004e
+;;=> true
Count number of true values with probability 0.15
(count (filter true? (repeatedly 100000 (fn* [] (brand 0.15)))))
+;;=> 15009
default-rng
Default RNG - Mersenne Twister
Examples
Usage
(set-seed! default-rng 111)
+;;=> org.apache.commons.math3.random.MersenneTwister@33293b34
(irandom default-rng)
;;=> 1470976170
(set-seed! default-rng 999)
-;;=> org.apache.commons.math3.random.MersenneTwister@e98004e
+;;=> org.apache.commons.math3.random.MersenneTwister@33293b34
(irandom default-rng)
;;=> -1716016164
(set-seed! default-rng 111)
-;;=> org.apache.commons.math3.random.MersenneTwister@e98004e
+;;=> org.apache.commons.math3.random.MersenneTwister@33293b34
(irandom default-rng)
;;=> 1470976170
discrete-noise
macro
(discrete-noise X Y)(discrete-noise X)Examples
Usage
(distribution :beta)
-;;=> org.apache.commons.math3.distribution.BetaDistribution@5ba6659d
+;;=> org.apache.commons.math3.distribution.BetaDistribution@2841dcb6
(distribution :beta {:alpha 1.0, :beta 1.0})
-;;=> org.apache.commons.math3.distribution.BetaDistribution@40f7ae65
PDFs of beta
PDFs of binomial
PDFs of cauchy
PDFs of chi-squared
PDFs of empirical
PDFs of enumerated-int
PDFs of enumerated-real
PDFs of exponential
PDFs of f
PDFs of gamma
PDFs of geometric
PDFs of gumbel
PDFs of hypergeometric
PDFs of laplace
PDFs of levy
PDFs of log-normal
PDFs of logistic
PDFs of nakagami
PDFs of normal
PDFs of pareto
PDFs of pascal
PDFs of poisson
PDFs of t
PDFs of triangular
PDFs of uniform-int
PDFs of uniform-real
PDFs of weibull
PDFs of zipf
DistributionProto
protocol
Get information from distributions.
members
cdf
(cdf d v)(cdf d v1 v2)Cumulative probability.
Examples
Usage
(cdf (distribution :gamma) 1)
+;;=> org.apache.commons.math3.distribution.BetaDistribution@7145c88
PDFs of beta
PDFs of binomial
PDFs of cauchy
PDFs of chi-squared
PDFs of empirical
PDFs of enumerated-int
PDFs of enumerated-real
PDFs of exponential
PDFs of f
PDFs of gamma
PDFs of geometric
PDFs of gumbel
PDFs of hypergeometric
PDFs of laplace
PDFs of levy
PDFs of log-normal
PDFs of logistic
PDFs of nakagami
PDFs of normal
PDFs of pareto
PDFs of pascal
PDFs of poisson
PDFs of t
PDFs of triangular
PDFs of uniform-int
PDFs of uniform-real
PDFs of weibull
PDFs of zipf
DistributionProto
protocol
Get information from distributions.
members
cdf
(cdf d v)(cdf d v1 v2)Cumulative probability.
Examples
Usage
(cdf (distribution :gamma) 1)
;;=> 0.09020401043104985
(cdf (distribution :gamma) 1 4)
;;=> 0.5037901398591113
icdf
(icdf d p)Inversed cumulative probability
Examples
noise
(noise x)(noise x y)(noise x y z)Create improved Perlin Noise.
6 octaves, quintic interpolation.
Examples
Usage
(noise 3.3)
-;;=> 0.4517074285714284
+;;=> 0.45384482539682564
(noise 3.3 1.1)
-;;=> 0.3854944434793651
+;;=> 0.5155615818768254
(noise 3.3 0.0 -0.1)
-;;=> 0.44945232359619036
2d noise
noise-types
List of possible noise types as a map of names and values.
Examples
List of names (keys)
(keys noise-types)
+;;=> 0.5615359622095238
2d noise
noise-types
List of possible noise types as a map of names and values.
Examples
List of names (keys)
(keys noise-types)
;;=> (:value :gradient :simplex)
random-noise-cfg
(random-noise-cfg)Create random noise configuration.
Examples
Random configuration
(random-noise-cfg)
;;=> {:gain 0.7775713724640989,
;;=> :interpolation :linear,
;;=> :lacunarity 1.7314283620797077,
-;;=> :noise-type :value,
+;;=> :noise-type :gradient,
;;=> :normalize? true,
;;=> :octaves 6,
;;=> :seed -1208843915}
Create function
(random-noise-fn)
-;;=> fastmath.random$billow_noise$fn__8943@35f045d
+;;=> fastmath.random$fbm_noise$fn__8939@1e5ba462
(random-noise-fn (random-noise-cfg))
-;;=> fastmath.random$fbm_noise$fn__8939@5b4b2bfa
One
Two
Three
random-noise-fn
(random-noise-fn cfg)(random-noise-fn)Create random noise function from all possible options.
+;;=> fastmath.random$billow_noise$fn__8943@1d694d9aOne
Two
Three
random-noise-fn
(random-noise-fn cfg)(random-noise-fn)Create random noise function from all possible options.
Optionally provide own configuration cfg. In this case one of 4 different blending methods will be selected.
randval
macro
(randval v1 v2)(randval prob v1 v2)Retrun value with given probability (default 0.5)
rng
multimethod
Examples
Creating
(rng :mersenne)
-;;=> org.apache.commons.math3.random.MersenneTwister@90d007a
+;;=> org.apache.commons.math3.random.MersenneTwister@43f79aa0
(rng :isaac 1234)
-;;=> org.apache.commons.math3.random.ISAACRandom@315d19f1
Using
(irandom (rng :mersenne 999) 15 25)
+;;=> org.apache.commons.math3.random.ISAACRandom@3fa57a5a
Using
(irandom (rng :mersenne 999) 15 25)
;;=> 17
RNGProto
protocol
Defines set of random functions for different RNGs or distributions returning primitive values.
members
->seq
(->seq t)(->seq t n)Returns sequence of random samples limited to optional n values.
brandom
(brandom t)(brandom t thr)Boolean random. Returns true or false with equal probability. You can set probability for true setting thr (from [0-1] range).
See brand.
Examples
boolean
(rngproto-snippet brandom ...)
-;;=> false
drandom
(drandom t)(drandom t mx)(drandom t mn mx)Random double.
+;;=> truedrandom
(drandom t)(drandom t mx)(drandom t mn mx)Random double.
For RNGs: As default returns random double from [0,1) range. When mx is passed, range is set to [0, mx). When mn is passed, range is set to [mn, mx).
See drand.
For distributions, just returns random double (call without parameters).
Examples
double
(rngproto-snippet drandom ...)
-;;=> 0.038337527867269294
Double random value from distribution
(drandom (distribution :gamma))
+;;=> 0.5685805469972727
Double random value from distribution
(drandom (distribution :gamma))
;;=> 2.5462703911794446
frandom
(frandom t)(frandom t mx)(frandom t mn mx)Random float.
For RNGs: As default returns random float from [0,1) range. When mx is passed, range is set to [0, mx). When mn is passed, range is set to [mn, mx).
See frand.
For distributions, just returns random float (call without parameters).
Examples
float
(rngproto-snippet frandom ...)
-;;=> 0.9157808
Float random value from distribution (sample cast to float)
(frandom (distribution :gamma))
+;;=> 0.4603822
Float random value from distribution (sample cast to float)
(frandom (distribution :gamma))
;;=> 2.3635364
grandom
(grandom t)(grandom t std)(grandom t mean std)Random double from gaussian distribution. As default returns random double from N(0,1). When std is passed, N(0,std) is used. When mean is passed, distribution is set to N(mean, std).
See grand.
Examples
gaussian double
(rngproto-snippet grandom ...)
-;;=> -0.750989538652659
irandom
(irandom t)(irandom t mx)(irandom t mn mx)Random integer.
+;;=> 1.2539258998485059irandom
(irandom t)(irandom t mx)(irandom t mn mx)Random integer.
For RNGs: As default returns random integer from full integer range. When mx is passed, range is set to [0, mx). When mn is passed, range is set to [mn, mx).
See irand.
For distributions, just returns random integer (call without parameters).
Examples
integer
(rngproto-snippet irandom ...)
-;;=> -1424653085
Integer random value from distribution (sample cast to int)
(irandom (distribution :gamma))
+;;=> -424877262
Integer random value from distribution (sample cast to int)
(irandom (distribution :gamma))
;;=> 1
lrandom
(lrandom t)(lrandom t mx)(lrandom t mn mx)Random long.
For RNGs: As default returns random long from full long range. When mx is passed, range is set to [0, mx). When mn is passed, range is set to [mn, mx).
See lrand.
For distributions, just returns random long (call without parameters).
Examples
long
(rngproto-snippet lrandom ...)
-;;=> -642072816814758594
Long random value from distribution (sample cast to long)
(lrandom (distribution :gamma))
+;;=> -1312719526820938797
Long random value from distribution (sample cast to long)
(lrandom (distribution :gamma))
;;=> 2
set-seed!
(set-seed! t v)Sets seed. Returns RNG or distribution itself.
Examples
Set seed for the RNG object
(let [rng (rng :isaac)]
(set-seed! rng 1234)
(irandom rng 10 15))
@@ -272,15 +272,15 @@ Integer di
;;=> #vec2 [0.125, 0.8888888888888888])
Usage (1d)
(let [gen (sequence-generator :sobol 1)] (take 5 (gen)))
;;=> (0.0 0.5 0.75 0.25 0.375)
Halton plot (1000 samples)
Sobol plot (1000 samples)
Sphere plot (1000 samples)
Gaussian plot (1000 samples)
Default plot (1000 samples)
sequence-generators-list
List of random sequence generator. See sequence-generator.
Examples
Generator names.
(sort sequence-generators-list)
;;=> (:default :gaussian :halton :sobol :sphere)
simplex
(simplex x)(simplex x y)(simplex x y z)Create Simplex noise. 6 octaves.
Examples
Usage
(simplex 3.3)
-;;=> 0.6518222195619048
+;;=> 0.6709703704761902
(simplex 3.3 1.1)
-;;=> 0.6116429442141537
+;;=> 0.6447862629219117
(simplex 3.3 0.0 -0.1)
-;;=> 0.2745496230975243
2d noise
single-noise
Examples
Usage
(let [n (single-noise {:interpolation :linear})] (n 0.5 1.1 -1.3))
+;;=> 0.6277449408844472
2d noise
single-noise
Examples
Usage
(let [n (single-noise {:interpolation :linear})] (n 0.5 1.1 -1.3))
;;=> 0.4065
2d noise
vnoise
(vnoise x)(vnoise x y)(vnoise x y z)Value Noise.
6 octaves, Hermite interpolation (cubic, h01).
Examples
Usage
(vnoise 3.3)
-;;=> 0.665599770847052
+;;=> 0.5842235196433692
(vnoise 3.3 1.1)
-;;=> 0.4403501571382373
+;;=> 0.7372213484363309
(vnoise 3.3 0.0 -0.1)
-;;=> 0.4886291945718484
2d noise
\ No newline at end of file
+;;=> 0.36691298907493612d noise
\ No newline at end of file
diff --git a/docs/fastmath.rbf.html b/docs/fastmath.rbf.html
index 96b2424b..d61f88d3 100755
--- a/docs/fastmath.rbf.html
+++ b/docs/fastmath.rbf.html
@@ -1,6 +1,6 @@
-fastmath.rbf documentation Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
fastmath.rbf
Radial Basis Function
+fastmath.rbf documentation Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.rbf
Radial Basis Function
Create with multifunction rbf.
All of them accept scaling factor scale. Only polyharmonic is defined with integer exponent k. See rbfs-list for all names.
rbf-obj returns SMILE library object for defined function.
Code snippets
Save graph
(defn save-graph
@@ -13,7 +13,7 @@
:height 250)
fname))
rbf
multimethod
Create Radial Basis Function
Optional parameter scale.
-:polyharmonic has also exponent k parameter.
Examples
Linear
(save-graph (rbf :linear) ...)
Gaussian
(save-graph (rbf :gaussian) ...)
Multiquadratic
(save-graph (rbf :multiquadratic) ...)
Inverse multiquadratic
(save-graph (rbf :inverse-multiquadratic) ...)
Inverse quadratic
(save-graph (rbf :inverse-quadratic) ...)
Thinplate
(save-graph (rbf :thinplate) ...)
Polyharmonic 3
(save-graph (rbf :polyharmonic 3) ...)
Polyharmonic 4
(save-graph (rbf :polyharmonic 4) ...)
Wendland
(save-graph (rbf :wendland) ...)
Wu
(save-graph (rbf :wu) ...)
rbf-obj
(rbf-obj rbf-fn)Create RBF Smile object.
+:polyharmonic has also exponent k parameter.
Examples
Linear
(save-graph (rbf :linear) -2.0 2.0 ...)
Gaussian
(save-graph (rbf :gaussian) -2.0 2.0 ...)
Multiquadratic
(save-graph (rbf :multiquadratic) -3.0 3.0 ...)
Inverse multiquadratic
(save-graph (rbf :inverse-multiquadratic) -3.0 3.0 ...)
Inverse quadratic
(save-graph (rbf :inverse-quadratic) -3.0 3.0 ...)
Thinplate
(save-graph (rbf :thinplate) -1.0 3.0 ...)
Polyharmonic 3
(save-graph (rbf :polyharmonic 3) -3.0 3.0 ...)
Polyharmonic 4
(save-graph (rbf :polyharmonic 4) -3.0 3.0 ...)
Wendland
(save-graph (rbf :wendland) -3.0 3.0 ...)
Wu
(save-graph (rbf :wu) -3.0 3.0 ...)
rbf-obj
(rbf-obj rbf-fn)Create RBF Smile object.
Used to pass to Smile constructors/functions.
rbfs-list
Radial Basis function names
Examples
List of names
(sort rbfs-list)
;;=> (:gaussian :inverse-multiquadratic :inverse-quadratic
;;=> :linear :multiquadratic
diff --git a/docs/fastmath.stats.html b/docs/fastmath.stats.html
index 04d78737..457a3fc8 100755
--- a/docs/fastmath.stats.html
+++ b/docs/fastmath.stats.html
@@ -1,6 +1,6 @@
-fastmath.stats documentation Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
fastmath.stats
Statistics functions.
+fastmath.stats documentation Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.stats
Examples
3 bins from uniform distribution.
(histogram (repeatedly 1000 rand) 3)
-;;=> {:bins ([0.0022484030992574455 337]
-;;=> [0.334680819937947 317]
-;;=> [0.6671132367766366 346]),
+;;=> {:bins ([0.0017608710974496011 358]
+;;=> [0.33441364055651407 302]
+;;=> [0.6670664100155785 340]),
;;=> :size 3,
-;;=> :step 0.33243241683868957}
3 bins from uniform distribution for given range.
(histogram (repeatedly 10000 rand) 3 [0.1 0.5])
+;;=> :step 0.33265276945906447}
3 bins from uniform distribution for given range.
(histogram (repeatedly 10000 rand) 3 [0.1 0.5])
;;=> {:bins
-;;=> ([0.1 1346] [0.23333333333333334 1323] [0.3666666666666667 1340]),
+;;=> ([0.1 1339] [0.23333333333333334 1320] [0.3666666666666667 1310]),
;;=> :size 3,
;;=> :step 0.13333333333333333}
5 bins from normal distribution.
(histogram (repeatedly 10000 r/grand) 5)
;;=> {:bins ([-3.9488932738004707 81]
diff --git a/docs/fastmath.transform.html b/docs/fastmath.transform.html
index bcd80ba2..ed272d0f 100755
--- a/docs/fastmath.transform.html
+++ b/docs/fastmath.transform.html
@@ -1,6 +1,6 @@
-fastmath.transform documentation Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
fastmath.transform
Transforms.
+fastmath.transform documentation Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.transform
Transforms.
See transformer and TransformProto for details.
Wavelet
Based on JWave library.
@@ -47,7 +47,7 @@ Fourier
:standard :dft - 1d Discrete Fourier Transform - returns double-array where even elements are real part, odd elements are imaginary part.
Examples
Usage
(transformer :packet :discrete-mayer)
-;;=> jwave.transforms.WaveletPacketTransform@358720a0
TransformProto
protocol
Transformer functions.
members
forward-1d
(forward-1d t xs)Forward transform of sequence or array. Returns double array.
Examples
Usage
(seq (forward-1d (transformer :packet :haar-orthogonal) [-1 8 7 6]))
+;;=> jwave.transforms.WaveletPacketTransform@70f15b
TransformProto
protocol
Transformer functions.
members
forward-1d
(forward-1d t xs)Forward transform of sequence or array. Returns double array.
Examples
Usage
(seq (forward-1d (transformer :packet :haar-orthogonal) [-1 8 7 6]))
;;=> (20.0 -6.0 -8.0 -10.0)
(seq (forward-1d (transformer :fast :haar-orthogonal) [-1 8 7 6]))
;;=> (20.0 -6.0 -9.0 1.0)
diff --git a/docs/fastmath.vector.html b/docs/fastmath.vector.html
index dde79748..29a3a9fb 100755
--- a/docs/fastmath.vector.html
+++ b/docs/fastmath.vector.html
@@ -1,6 +1,6 @@
-fastmath.vector documentation Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
fastmath.vector
Mathematical vector operations.
+fastmath.vector documentation Generated by Codox with RDash UI theme
Fastmath 1.0.0
fastmath.vector
array->vec2
(array->vec2 a)Doubles array to Vec2
Examples
Usage
(array->vec2 (double-array [11 22 33 44 55]))
+;;=> 46.25272535004715
array->vec2
(array->vec2 a)Doubles array to Vec2
Examples
Usage
(array->vec2 (double-array [11 22 33 44 55]))
;;=> #vec2 [11.0, 22.0]
array->vec3
(array->vec3 a)Doubles array to Vec3
Examples
Usage
(array->vec3 (double-array [11 22 33 44 55]))
;;=> #vec3 [11.0, 22.0, 33.0]
array->vec4
(array->vec4 a)Doubles array to Vec4
Examples
Usage
(array->vec4 (double-array [11 22 33 44 55]))
;;=> #vec4 [11.0, 22.0, 33.0, 44.0]
array-vec
(array-vec xs)Make ArrayVec type based on provided sequence xs.
generate-vec2
(generate-vec2 f1 f2)(generate-vec2 f)Generate Vec2 with fn(s)
Examples
Usage
(generate-vec2 (constantly 2))
;;=> #vec2 [2.0, 2.0]
(generate-vec2 rand (constantly 1))
-;;=> #vec2 [0.5302930846414526, 1.0]
generate-vec3
(generate-vec3 f1 f2 f3)(generate-vec3 f)Generate Vec3 with fn(s)
Examples
Usage
(generate-vec3 rand)
-;;=> #vec3 [0.25638509955713584, 0.5166151187131103, 0.24388241645863107]
+;;=> #vec2 [0.5483162026864916, 1.0]
generate-vec3
(generate-vec3 f1 f2 f3)(generate-vec3 f)Generate Vec3 with fn(s)
Examples
Usage
(generate-vec3 rand)
+;;=> #vec3 [0.41101574911093164, 0.185473471211277, 0.6301936665927065]
(generate-vec3 rand (constantly 1) (constantly 2))
-;;=> #vec3 [0.1760653355321553, 1.0, 2.0]
generate-vec4
(generate-vec4 f1 f2 f3 f4)(generate-vec4 f)Generate Vec4 with fn(s)
Examples
Usage
(generate-vec4 rand)
-;;=> #vec4 [0.7792681543720726, 0.25196273021617865, 0.18401138504016257, 0.5552858980127775]
+;;=> #vec3 [0.28379256112998774, 1.0, 2.0]
generate-vec4
(generate-vec4 f1 f2 f3 f4)(generate-vec4 f)Generate Vec4 with fn(s)
Examples
Usage
(generate-vec4 rand)
+;;=> #vec4 [0.3592070085427427, 0.6160604340888605, 0.1475581211588579, 0.4175589607879455]
(generate-vec4 rand rand (constantly 1) (constantly 2))
-;;=> #vec4 [0.06995759698620418, 0.5662049056229967, 1.0, 2.0]
limit
(limit v len)Limit length of the vector by given value
Examples
Usage
(limit (vec3 1.0 1.0 1.0) 1.0)
+;;=> #vec4 [0.7924475133768876, 0.8306449490126698, 1.0, 2.0]
limit
(limit v len)Limit length of the vector by given value
Examples
Usage
(limit (vec3 1.0 1.0 1.0) 1.0)
;;=> #vec3 [0.5773502691896258, 0.5773502691896258, 0.5773502691896258]
(limit (vec3 1.0 1.0 1.0) 2.0)
;;=> #vec3 [1.0, 1.0, 1.0]
normalize
(normalize v)Normalize vector (set length = 1.0)
Examples
set-mag
(set-mag v len)Set length of the vector
Examples
Usage
(set-mag (vec2 0.22 0.22) (m/sqrt 2.0))
+;;=> 1.415520536588972
set-mag
(set-mag v len)Set length of the vector
Examples
Usage
(set-mag (vec2 0.22 0.22) (m/sqrt 2.0))
;;=> #vec2 [1.0000000000000002, 1.0000000000000002]
(set-mag (vec2 1.0 1.0) 0.0)
;;=> #vec2 [0.0, 0.0]
TOLERANCE
const
;;=> 1.0E-6Tolerance used in is-near-zero?. Values less than this value are treated as zero.
maxdim
(maxdim v)Index of maximum value.
Examples
Usage
(let [v (vec (repeatedly 100 (fn [] (- (int (rand-int 200)) 100))))
mdim (maxdim v)]
[mdim (v mdim)])
-;;=> [7 99]
+;;=> [20 99]
(maxdim (vec3 1 2 3))
;;=> 2
mindim
(mindim v)Index of minimum value.
Examples
Usage
(let [v (vec (repeatedly 100 (fn [] (- (int (rand-int 200)) 100))))
mdim (mindim v)]
[mdim (v mdim)])
-;;=> [51 -98]
+;;=> [48 -100]
(mindim (vec3 1 2 3))
;;=> 0
mn
(mn v1)Minimum value of vector elements
Examples
Usage
(mn (vec4 -1 -2 3 4))
;;=> -2.0
mult
(mult v1 v)Multiply vector by number v.
Examples
Usage
(mult (vec4 5 4 3 5) 4.0)
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-Fastmath 0.1.2-SNAPSHOT Generated by Codox with RDash UI theme
Fastmath 0.1.2-SNAPSHOT
Fastmath 0.1.2-SNAPSHOT
Released under the Unlicence
Fast and primitive math library.
Installation
To install, add the following dependency to your project or build file:
[generateme/fastmath "0.1.2-SNAPSHOT"]
Namespaces
fastmath.complex
Complex numbers functions.
fastmath.core
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: bool-and bool-not bool-or bool-xor
- Comparison: < <= == > >= eq even? neg? not== odd? pos? 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: mod quot rem remainder
- Powers / logarithms: cbrt exp fpow high-2-exp high-exp ln log log10 log1p log2 logb low-2-exp low-exp pow pow2 pow3 qexp qlog qpow qsqrt rqsqrt safe-sqrt sigmoid sq sqrt
- primitive: * + - / dec inc
- Rounding: abs approx approx-eq ceil floor frac iabs itrunc qceil qfloor qround rint round round-up-pow2 sfrac trunc
- 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
- stat: max min
- Trigonometry: acos acosh acot acoth acsc acsch asec asech asin asinh atan atan2 atanh cos cosh cot coth csc csch qcos qsin sec sech sin sinc sinh tan tanh
Other vars: double-array->seq double-double-array->seq gcd next-double prev-double sample seq->double-array seq->double-double-array unuse-primitive-operators use-primitive-operators
fastmath.easings
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
fastmath.fields
Vector field functions.
Categories
- Create fields: field parametrization
- Derive scalar field from vector field: cross 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
fastmath.interpolation
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-after step-before
- 1d interpolation: akima-spline cubic-spline divided-difference interpolators-1d-list kriging-spline linear linear-smile loess microsphere-projection neville rbf shepard spline 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
fastmath.random
Various random and noise functions.
Categories
- Distributions: cdf distribution distributions-list icdf likelihood log-likelihood lower-bound lpdf mean pdf probability sample upper-bound variance
- Random sequence generation: sequence-generator sequence-generators-list
- Noise functions: billow-noise discrete-noise fbm-noise interpolations noise noise-types random-noise-cfg random-noise-fn ridgedmulti-noise simplex single-noise vnoise
- Random number generation: ->seq brand brandom default-rng drand drandom frand frandom grand grandom irand irandom lrand lrandom randval rng rngs-list set-seed!
fastmath.stats
Statistics functions.
Categories
- Correlation: correlation covariance jensen-shannon-divergence kendall-correlation kullback-leibler-divergence pearson-correlation spearman-correlation
- Descriptive statistics: adjacent-values estimation-strategies-list extent histogram kurtosis maximum mean median median-3 median-absolute-deviation minimum mode modes outliers percentile population-stddev population-variance quantile second-moment skewness stats-map stddev sum variance
Other vars: k-means standardize
fastmath.transform
Transforms.
Categories
- Process: compress denoise
- Transform: forward-1d forward-2d reverse-1d reverse-2d transformer wavelet wavelets-list
fastmath.vector
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 generate-vec2 generate-vec3 generate-vec4 to-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
- Operations: abs add applyf approx average-vectors div econstrain ediv einterpolate emn emult emx interpolate is-near-zero? is-zero? maxdim mindim mn mult mx permute reciprocal sub sum
Other vars: ->ArrayVec ->Vec2 ->Vec3 ->Vec4
\ No newline at end of file
+Fastmath 1.0.0 Generated by Codox with RDash UI theme
Fastmath 1.0.0
Fastmath 1.0.0
Released under the Unlicence
Fast and primitive math library.
Installation
To install, add the following dependency to your project or build file:
[generateme/fastmath "1.0.0"]
Namespaces
fastmath.complex
Complex numbers functions.
fastmath.core
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: bool-and bool-not bool-or bool-xor
- Comparison: < <= == > >= eq even? neg? not== odd? pos? 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: mod quot rem remainder
- Powers / logarithms: cbrt exp fpow high-2-exp high-exp ln log log10 log1p log2 logb low-2-exp low-exp pow pow2 pow3 qexp qlog qpow qsqrt rqsqrt safe-sqrt sigmoid sq sqrt
- primitive: * + - / dec inc
- Rounding: abs approx approx-eq ceil floor frac iabs itrunc qceil qfloor qround rint round round-up-pow2 sfrac trunc
- 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
- stat: max min
- Trigonometry: acos acosh acot acoth acsc acsch asec asech asin asinh atan atan2 atanh cos cosh cot coth csc csch qcos qsin sec sech sin sinc sinh tan tanh
Other vars: double-array->seq double-double-array->seq gcd next-double prev-double sample seq->double-array seq->double-double-array unuse-primitive-operators use-primitive-operators
fastmath.easings
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
fastmath.fields
Vector field functions.
Categories
- Create fields: field parametrization
- Derive scalar field from vector field: cross 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
fastmath.interpolation
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-after step-before
- 1d interpolation: akima-spline cubic-spline divided-difference interpolators-1d-list kriging-spline linear linear-smile loess microsphere-projection neville rbf shepard spline 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
fastmath.random
Various random and noise functions.
Categories
- Distributions: cdf distribution distributions-list icdf likelihood log-likelihood lower-bound lpdf mean pdf probability sample upper-bound variance
- Random sequence generation: sequence-generator sequence-generators-list
- Noise functions: billow-noise discrete-noise fbm-noise interpolations noise noise-types random-noise-cfg random-noise-fn ridgedmulti-noise simplex single-noise vnoise
- Random number generation: ->seq brand brandom default-rng drand drandom frand frandom grand grandom irand irandom lrand lrandom randval rng rngs-list set-seed!
fastmath.stats
Statistics functions.
Categories
- Correlation: correlation covariance jensen-shannon-divergence kendall-correlation kullback-leibler-divergence pearson-correlation spearman-correlation
- Descriptive statistics: adjacent-values estimation-strategies-list extent histogram kurtosis maximum mean median median-3 median-absolute-deviation minimum mode modes outliers percentile population-stddev population-variance quantile second-moment skewness stats-map stddev sum variance
Other vars: k-means standardize
fastmath.transform
Transforms.
Categories
- Process: compress denoise
- Transform: forward-1d forward-2d reverse-1d reverse-2d transformer wavelet wavelets-list
fastmath.vector
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 generate-vec2 generate-vec3 generate-vec4 to-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
- Operations: abs add applyf approx average-vectors div econstrain ediv einterpolate emn emult emx interpolate is-near-zero? is-zero? maxdim mindim mn mult mx permute reciprocal sub sum
Other vars: ->ArrayVec ->Vec2 ->Vec3 ->Vec4
\ No newline at end of file
diff --git a/project.clj b/project.clj
index 0e767563..a33611c8 100755
--- a/project.clj
+++ b/project.clj
@@ -1,4 +1,4 @@
-(defproject generateme/fastmath "0.1.2-SNAPSHOT"
+(defproject generateme/fastmath "1.0.0"
:description "Fast and primitive math library"
:url "https://github.com/generateme/fastmath"
:license {:name "The Unlicence"
@@ -26,7 +26,7 @@
[criterium "0.4.4"]
[incanter/incanter-charts "1.9.2"]
[incanter/incanter-core "1.9.2"]
- [metadoc "0.2.2"]]
+ [metadoc "0.2.3"]]
:codox {:themes [:rdash]
:metadata {:doc/format :markdown}
:output-path "docs/"
