Sieve Test Data Object

Description

Functions to create, test and subset a std object.

Usage

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std(a, r, desc = desc.std(), lmargs = list())
is.std(x)
## S3 method for class 'std'
x[i, ...]

Arguments

a

A vector of sieve net aperture sizes in micrometers, zero size means the receiver.

i

An integer or vector of integers

r

Mass percent of remaining material on the sieve, vector with the same length as vector a, sum should be equal 100, if not the function will give warning and recalculate the values. If the value is 0, then will be excluded with warning.

desc

A description meta data prepared by desc.std

lmargs

A list of additional arguments to lm

x

An object of std class

...

Not used

Details

Basically the std object is list of lists, in the first level (trunk) are stored particular sieve test samples, in the second level (branches) are stored details of each single sample. If there is only one sample in the std object, then the length will be 1. The object can be created by hand using std function or by reading the basic information from CSV file using read.std function. Once the std object exists, it can be sub-selected using x[i] or concatenated by c(...).

Value

Both std(a,r) and x[i] functions return std object, x[[i]] returns list holding following informations:

Description

Terse description of a sample

Title

Title of particular measurement

Sample

Name of the sample

Unit

To which unit the sample belongs

Date

Day when the sample was taken

stdata

Data frame with given and calculated values

lmfit

Result of linear model fit, lm object

RRcoefficients

List of coefficients for Rosin - Rammler distribution

size

List of characteristic sizes of Rosin - Rammler distribution

The is.std(x) function returns logical value.

See Also

read.std, c.std, summary.std, tweak.std

Examples

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## create std
sieve_aperture_size <- c(500, 200, 90, 0)
mass_ppc_retained <- c(1.01, 24, 42.8, 32.190)
# some meta data:
md <- desc.std("Coal powder, learning std")
# sieve test data (std) object
my_sample <- std(a=sieve_aperture_size, r=mass_ppc_retained, desc=md)
is.std(my_sample)