This library provides a collection of math and statistics classes and cmdlets for PowerShell. It is built on top of Accord.NET.
This is a work in progress but already usable for many use cases.
The library is published in PowerShell Gallery
Install-Module psmath
Each cmdlet in the library comes along with a short alias prefixed with math.
or st.
and you can use it instead of the full cmdlet name. For example, you can use math.sin
instead of Get-Math.Sin
.
PS C:\> math.sin (3 / 4 * (math.pi))
0.707106781186548
PS C:\> 1..5 | math.sqrt
1
1.4142135623731
1.73205080756888
2
2.236067977499791
PS C:\> 1..99 | math.median
50
PS C:\> 1..99 | math.var -Unbiased
825
PS C:\> 1..99 | math.summary
Name :
Count : 99
Unique : 99
Minimum : 1
LowerQuantile : 25
Median : 50
Mean : 50
UpperQuantile : 75
Maximum : 99
Cmdlets: math.abs
math.acos
math.argmax
math.argmin
math.argsort
math.asin
math.atan
math.atan2
math.binomial
math.ceiling
math.center
math.choose
math.contraharmonicmean
math.cos
math.cosh
math.cumsum
math.diff
math.distinct
math.distinctCount
math.divrem
math.e
math.entropy
math.ewmean
math.ewvar
math.exp
math.factorial
math.floor
math.geometric
math.hist
math.issorted
math.kalman
math.kurtosis
math.log
math.log10
math.loggeometric
math.lowerq
math.max
math.mean
math.median
math.min
math.mode
math.movingmean
math.movingmmax
math.movingmmin
math.movingstdev
math.movingsum
math.movingvar
math.normalize
math.pi
math.pow
math.quantile
math.randomseed
math.rank
math.rem
math.reverse
math.round
math.sample
math.scale
math.se
math.shuffle
math.sigmoid
math.sign
math.sin
math.sinh
math.skewness
math.softmax
math.sqrt
math.standardize
math.stdev
math.sum
math.summary
math.tan
math.tanh
math.ties
math.truncate
math.truncatedmean
math.truthtable
math.upperq
math.var
math.zscore
Sequence generators similar to NumPy's arange
and linspace
.
PS C:\> seq 0 5 1.5
0
1.5
3
4.5
PS C:\> $seq = seq.linspace 1 60
PS C:\> $seq -join "`t"
0 0.0166666666666667 0.0333333333333333 0.05 0.0666666666666667 0.0833333333333333
0.1 0.116666666666667 0.133333333333333 0.15 0.166666666666667 0.183333333333333
0.2 0.216666666666667 0.233333333333333 0.25 0.266666666666667 0.283333333333333
0.3 0.316666666666667 0.333333333333333 0.35 0.366666666666667 0.383333333333333
0.4 0.416666666666667 0.433333333333333 0.45 0.466666666666667 0.483333333333333
0.5 0.516666666666667 0.533333333333333 0.55 0.566666666666667 0.583333333333333
0.6 0.616666666666667 0.633333333333333 0.65 0.666666666666667 0.683333333333333
0.7 0.716666666666667 0.733333333333333 0.75 0.766666666666667 0.783333333333333
0.8 0.816666666666667 0.833333333333333 0.85 0.866666666666667 0.883333333333333
0.9 0.916666666666667 0.933333333333333 0.95 0.966666666666667 0.983333333333333
PS C:\> seq 10 20 2 -func { $x * $x }, { math.sqrt $x }
x y0 y1
- -- --
10 100 3.16227766016838
12 144 3.46410161513775
14 196 3.74165738677394
16 256 4
18 324 4.24264068711928
Cmdlets: seq
seq.linspace
seq.values
seq.zeros
The methods of System.Linq.Enumerable
and Accord.NET classes are defined in the Array class.
PS C:\> (0..99).Mean()
49.5
PS C:\> "A quick brown fox jumps over the lazy dog".Split().Aggregate({ $args[1] + " - " + $args[0] })
dog - lazy - the - over - jumps - fox - brown - quick - A
Methods: Aggregate
All
Any
ArgMin
ArgSort
AsEnumerable
Bottom
Cartesian
Center
Clear
Concat
Concatenate
Contains
ContraHarmonicMean
Copy
Cross
CumulativeSum
DefaultIfEmpty
Distinct
DistinctCount
DropNa
DropNaN
ElementAt
ElementAtOrDefault
Entropy
Except
Expand
ExponentialWeightedMean
ExponentialWeightedVariance
Find
First
FirstOrDefault
GeometricMean
Get
GroupBy
GroupJoin
HasInfinity
HasNaN
Intersect
IsEqual
IsSorted
Join
Kronecker
Kurtosis
Last
LastOrDefault
LogGeometricMean
LongCount
LowerQuartile
Max
Mean
Median
Min
Mode
Normalize
Null
OrderBy
OrderByDescending
Outer
Product
Quantile
Quantiles
Quartiles
Rank
Reverse
Sample
Scale
Select
SelectMany
SequenceEqual
Shuffled
Single
SingleOrDefault
Skewness
Skip
SkipWhile
Sorted
Split
Stack
StandardDeviation
StandardError
Standardize
Stdev
Sum
Swap
Take
TakeWhile
Ties
ToDictionary
ToList
ToLookup
Top
Trim
TruncatedMean
Union
UpperQuartile
Var
Variance
Where
Zip
The Matrix
class represents a matrix and offers a reasonable output format and useful methods. You can create Matrix
objects by the mat
cmdlet (New-Math.Matrix
) and variants (mat.identity
, mat.diagonal
and so on).
PS C:\> $m = mat 1,2,3,4 3 3
PS C:\> $m
[3 x 3]
1 4 3
2 1 4
3 2 1
PS C:\> $m.Inv
[3 x 3]
-0.19444 0.05556 0.36111
0.27778 -0.22222 0.05556
0.02778 0.27778 -0.19444
PS C:\> $svd = $m.Svd()
PS C:\> $svd | fl
U : [3 x 3] [ 0.67552 0.56617 -0.47235 ] [ 0.58632 -0.80092 -0.12149 ] [ 0.4471 0.19488 0.873 ]
D : [3 x 3] [ 7.13366 0 0 ] [ 0 2.31427 0 ] [ 0 0 2.1806 ]
V : [3 x 3] [ 0.4471 -0.19488 0.873 ] [ 0.58632 0.80092 -0.12149 ] [ 0.67552 -0.56617 -0.47235 ]
Source : Accord.Math.Decompositions.SingularValueDecomposition
PS C:\> $svd.U * $svd.D * $svd.V.T
[3 x 3]
1 4 3
2 1 4
3 2 1
Cmdlets: mat.diagonal
mat.fromobject
mat.identity
mat.magic
mat.mesh
mat.meshgrid
mat.onehot
mat.truthtable
mat.zeros
Methods and properties: Abs
Add
Apply
ApplyInPlace
ArgMax
ArgMin
ArgSort
AsString
Bottom
Cartesian
Ceiling
Cholesky
Clone
Combinations
Concatenate
Convolve
Correlation
Count
Covariance
Cross
CumulativeSum
Decompose
Determinant
Distinct
DistinctCount
Divide
DivideByDiagonal
Dot
Eigenvalue
Entropy
Equals
Exp
Expand
ExponentialWeightedCovariance
Find
First
FirstOrNull
Flatten
Floor
GetColumn
GetColumns
GetHashCode
GetLowerTriangle
GetNumberOfElements
GetRange
GetRow
GetRows
GetSymmetric
GetTotalLength
GetType
GetUpperTriangle
gramSchmidtOrthogonalizationWrapper
HasInfinity
HasNaN
Inverse
IsDiagonal
IsLowerTriangular
IsPositiveDefinite
IsSingular
IsSymmetric
IsUpperTriangular
Kronecker
Last
Log
LogDeterminant
LogPseudoDeterminant
Lu
Max
Mean
Median
Merge
Min
Mode
Multiply
Nmf
Normalize
Null
OneHot
Outer
Pad
Permutations
Pow
Product
PseudoDeterminant
Qr
Rank
Reversed
Round
Shuffle
Sign
SignedPow
SignSqrt
Skewness
Solve
Sort
Split
Sqrt
Stack
StanardDeviation
StanardError
Subsets
Subtract
Sum
Svd
ToFlatArray
ToJagged
Top
ToPSObject
ToString
Trace
Transpose
Variance
WeightedCovariance
Whitening
ZScores
Item
Columns
Inv
Rows
T
Values
PS C:\> $n = st.normal -Mean 10 -StdDev 3
PS C:\> $n
Mean : 10
Median : 10
Variance : 9
StandardDeviation : 3
Mode : 10
Skewness : 0
Kurtosis : 0
Support : [-∞, ∞]
Entropy : 2.51755082187278
Quartiles : [7.97653074941176, 12.0234692505882]
PS C:\> $n.Generate(3)
6.70926907721133
7.16162377748582
15.2954486068024
PS C:\> seq 7 13 .01 -func { $n.pdf($x) }
x y0
- --
7 0.0806569081730478
7.01 0.0809257635370322
7.02 0.0811946129148634
7.03 0.0814634503023332
7.04 0.0817322696757198
:
Cmdlets: st.bernoulli
st.beta
st.binomial
st.cauchy
st.chisquire
st.empirical
st.exponential
st.f
st.gamma
st.geometric
st.hypergeo
st.logistic
st.lognormal
st.negbinomial
st.normal
st.poison
st.t
st.uniform
st.uniformd
st.weibull
PS C:\> $samples = (st.normal 10 9).generate(20)
PS C:\> $samples | Invoke-TTest -HypothesizedMean 0 -Alternate Different
Analysis : 0.999782277992546
StandardError : 1.98120573653148
EstimatedValue : 11.4688217870095
HypothesizedValue : 0
Confidence : [7.3221105237174, 15.6155330503016]
Hypothesis : ValueIsDifferentFromHypothesis
StatisticDistribution : T(x; df = 19)
PValue : 1.40972806286221E-05
Statistic : 5.78880909515642
Tail : TwoTail
Size : 0.05
Significant : True
CriticalValue : 2.09302405440831
Cmdlets: Invoke-BinomialTest
Invoke-ChiSquareTest
Invoke-FisherExactTest
Invoke-FTest
Invoke-KolmogorovSmirnovTest
Invoke-LeveneTest
Invoke-MannWhitneyWilcoxonTest
Invoke-PairedTTest
Invoke-ShapiroWilkTest
Invoke-SignTest
Invoke-TTest
Invoke-TwoSampleKolmogorovSmirnovTest
Invoke-TwoSampleSignTest
Invoke-TwoSampleTTest
Invoke-TwoSampleWilcoxonSignedRankTest
Invoke-WilcoxonSignedRankTest
(particularly WIP)
PS C:\> $samples = seq 0 10 1 -func { 2 * $x + (st.normal).generate() + 10 }
PS C:\> $samples
x y0
- --
0 12.4668147765386
1 12.3778237651562
2 13.5261567687156
3 16.6537265658641
4 19.4478735361853
5 21.6786215694439
6 20.8376203580729
7 24.4205486696051
8 25.2553007079806
9 26.5474208799279
PS C:\> $r = $samples | Invoke-LinearRegression -OutputName y0
PS C:\> $r.Regression.ToString()
y(x0) = 3.55268307161757*x0
PS C:\> $r.RSquareAdjusted
-0.719608861231189
Cmdlets: Invoke-GeneralizedLinearRegression
Invoke-LinearRegression
Invoke-LogisticRegression
Invoke-StepwiseLogisticRegression
Flexible type conversion cmdlets.
PS C:\> math.todouble '$3.99', '1,000,000', '3e-4'
3.99
1000000
0.0003
PS C:\> math.todatetime 1998/3/7, Aug-7, "Sunday, May 7, 2017"
3/7/1998 12:00:00 AM
8/7/2018 12:00:00 AM
5/7/2017 12:00:00 AM
Cmdlets: math.fromunixtime
math.todatetime
math.todatetimeoffset
math.todouble
math.tounixtime
This library is licensed under the GNU Lesser General Public License version 2.1 or later.