R6 Class for floundeR based analyses

This is an overarching class which other flounder classes are expected to inherit from. The floundeR object contains methods and variables that are maintained for other objects - there is probably not a sensible usecase for actually creating a floundeR instance on its own.

Methods

Public methods

• FloundeR$new()

• FloundeR$print()

• FloundeR$bin_data()

• FloundeR$num_scale()

• FloundeR$nums_scale()

• FloundeR$clone()

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Method new()

Creates a new FloundeR object.

Usage

FloundeR$new()

Returns

A new FloundeR object.

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Method print()

this print method overrides the standard print function as included with R6 objects - this is to better define what is contained within an object and to provide better floundeR abstraction

Usage

FloundeR$print(...)

Arguments

...

additional stuff passed on

Returns

nothing (at present) - output to stdout

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Method bin_data()

general method for binning continuous data into sensible bins - used by various methods within the broader floundeR framework.

Usage

FloundeR$bin_data(data, bins = 20, outliers = 0.025, qmax = NA)

Arguments

data

• the dataset (series) to be binned

bins

• the number of bins to prepare

outliers

• the fraction of longest outlying features that should be excluded to simplify the plot.

qmax

• a manual upper limit to use

Returns

bin assignments for data elements

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Method num_scale()

scale numerics in bases into kilo/mega/giga etc measurements for e.g. plots and other graphic visualisations

Usage

FloundeR$num_scale(val)

Arguments

val

a numeric (raw)

Returns

character representation scaled accordingly

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Method nums_scale()

Apply the num_scale method across a multi-member vector of numerics

Usage

FloundeR$nums_scale(vals)

Arguments

vals

the vector of numerics

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Method clone()

The objects of this class are cloneable with this method.

Usage

FloundeR$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.