Utils

ABMEv.arithsmoothMethod
function arithsmooth(x,y,smooth)

-x is the shifted x-axis vector, due to smoothing -y is the smoothed value Returning a tuple

source
ABMEv.arithsmooth2DMethod
function arithsmooth2D(xa,ya,itp,smooth)

Return xas,yas,A where A is an interpolated matrix with arithmetic smooth, whose axis are xas, yas

ARGS

xa xaxis values, ya yaxis values, itp interpolation function, smooth smoothing function

source
ABMEv.gaussianMethod
    gaussian(x::Number,mu::Number,sigma::Number) = generalised_gaussian(x,mu,sigma,2)
source
ABMEv.generalised_gaussianMethod
    generalised_gaussian(x::Number,mu::Number,sigma::Number,epsilon::Number)

Returns exp( -.5 * ((x-mu) / sigma)^epsilon)

source
ABMEv.geomsmoothMethod
function geomsmooth(x,y,smooth)

-x is the shifted x-axis vector, due to smoothing -y is the smoothed value Returning a tuple

source
ABMEv.geomsmoothMethod
function geomsmooth(x,smooth)

Geometric smoothing, cf https://en.wikipedia.org/wiki/Exponential_smoothing

source
ABMEv.geomsmooth2DMethod
function geomsmooth2D(xa,ya,itp,smooth)

Return xas,yas,A where A is an interpolated matrix with geometric smooth, whose axis are xas, yas

ARGS

xa xaxis values, ya yaxis values, itp interpolation function, smooth smoothing function

source
ABMEv.interpolate_dfMethod
function interpolate_df(df,xlab,ylab,zlab)

returns an interpolated function itp(x,y) -> z, as well as its axis xa and ya

source
ABMEv.maMethod
ma(x::Array{T},f) where T <: Number

Moving average over array x, using f as the filter, i.e. the number of points to average on. Better choosing an odd number

source
DataFrames.groupbyMethod
function groupby(f, list::Array)

returns a dictionary that group list elements by value of function f

source