Package 'mpspline2'

Title: Mass-Preserving Spline Functions for Soil Data
Description: A low-dependency implementation of GSIF::mpspline() <https://r-forge.r-project.org/scm/viewvc.php/pkg/R/mpspline.R?view=markup&revision=240&root=gsif>, which applies a mass-preserving spline to soil attributes. Splining soil data is a safe way to make continuous down-profile estimates of attributes measured over discrete, often discontinuous depth intervals.
Authors: Lauren O'Brien [aut, cre] , Brendan Malone [ctb] , Tomislav Hengl [ctb] , Tom Bishop [ctb], David Rossiter [ctb], Dylan Beaudette [ctb], Andrew Brown [ctb]
Maintainer: Lauren O'Brien <[email protected]>
License: GPL
Version: 0.1.8
Built: 2025-03-02 05:04:16 UTC
Source: https://github.com/obrl-soil/mpspline2

Help Index

Spline discrete soils data - multiple sites

Description

This function implements the mass-preserving spline method of Bishop et al (1999) (doi:10.1016/S0016-7061(99)00003-8) for interpolating between measured soil attributes down a soil profile, across multiple sites' worth of data.

Usage

mpspline(
  obj = NULL,
  var_name = NULL,
  lam = 0.1,
  d = c(0, 5, 15, 30, 60, 100, 200),
  vlow = 0,
  vhigh = 1000
)

Arguments

obj

data.frame or matrix. Column 1 must contain site identifiers. Columns 2 and 3 must contain upper and lower sample depths, respectively. Subsequent columns will contain measured values for those depths.
var_name

length-1 character or length-1 integer denoting the column in obj in which target data is stored. If not supplied, the fourth column of the input object is assumed to contain the target data.
lam

number; smoothing parameter for spline. Defaults to 0.1.
d

sequential integer vector; denotes the output depth ranges in cm. Defaults to c(0, 5, 15, 30, 60, 100, 200) after the GlobalSoilMap specification, giving output predictions over intervals 0-5cm, 5-15cm, etc.
vlow

numeric; constrains the minimum predicted value to a realistic number. Defaults to 0.
vhigh

numeric; constrains the maximum predicted value to a realistic number. Defaults to 1000.

Value

A nested list of data for each input site. List elements are: Site ID, vector of predicted values over input intervals, vector of predicted values for each cm down the profile to max(d), vector of predicted values over d (output) intervals, and root mean squared error.

Examples

dat <- data.frame("SID" = c( 1,  1,  1,  1,   2,   2,   2,   2),
                   "UD" = c( 0, 20, 40, 60,   0,  15,  45,  80),
                   "LD" = c(10, 30, 50, 70,   5,  30,  60, 100),
                  "VAL" = c( 6,  4,  3, 10, 0.1, 0.9, 2.5,   6),
                   stringsAsFactors = FALSE)
m1 <- mpspline(obj = dat, var_name = 'VAL')

Spline discrete soils data - multiple sites, compact output

Description

This function implements the mass-preserving spline method of Bishop et al (1999) (doi:10.1016/S0016-7061(99)00003-8) for interpolating between measured soil attributes down a soil profile, across multiple sites' worth of data. It returns a more compact output object than mpspline().

Usage

mpspline_compact(
  obj = NULL,
  var_name = NULL,
  lam = 0.1,
  d = c(0, 5, 15, 30, 60, 100, 200),
  vlow = 0,
  vhigh = 1000
)

Arguments

obj

data.frame or matrix. Column 1 must contain site identifiers. Columns 2 and 3 must contain upper and lower sample depths, respectively. Subsequent columns will contain measured values for those depths.
var_name

length-1 character or length-1 integer denoting the column in obj in which target data is stored. If not supplied, the fourth column of the input object is assumed to contain the target data.
lam

number; smoothing parameter for spline. Defaults to 0.1.
d

sequential integer vector; denotes the output depth ranges in cm. Defaults to c(0, 5, 15, 30, 60, 100, 200) after the GlobalSoilMap specification, giving output predictions over intervals 0-5cm, 5-15cm, etc.
vlow

numeric; constrains the minimum predicted value to a realistic number. Defaults to 0.
vhigh

numeric; constrains the maximum predicted value to a realistic number. Defaults to 1000.

Value

A four-item list containing a matrix of predicted values over the input depth ranges, a matrix of predicted values over the output depth ranges, a matrix of 1cm predictions, and a matrix of RMSE and IQR-scaled RMSE values. Site identifiers are in rownames attributes.

Examples

dat <- data.frame("SID" = c( 1,  1,  1,  1,   2,   2,   2,   2),
                   "UD" = c( 0, 20, 40, 60,   0,  15,  45,  80),
                   "LD" = c(10, 30, 50, 70,   5,  30,  60, 100),
                  "VAL" = c( 6,  4,  3, 10, 0.1, 0.9, 2.5,   6),
                   stringsAsFactors = FALSE)
mpspline_compact(obj = dat, var_name = 'VAL')

Spline discrete soils data - single site

Description

This function implements the mass-preserving spline method of Bishop et al (1999) (doi:10.1016/S0016-7061(99)00003-8) for interpolating between measured soil attributes down a single soil profile.

Usage

mpspline_one(
  site = NULL,
  var_name = NULL,
  lam = 0.1,
  d = c(0, 5, 15, 30, 60, 100, 200),
  vlow = 0,
  vhigh = 1000
)

Arguments

site

data frame containing data for a single soil profile. Column 1 must contain site identifiers. Columns 2 and 3 must contain upper and lower sample depths, respectively, measured in centimeters. Subsequent columns will contain measured values for those depths.
var_name

length-1 character or length-1 integer denoting the column in site in which target data is stored. If not supplied, the fourth column of the input object is assumed to contain the target data.
lam

number; smoothing parameter for spline. Defaults to 0.1.
d

sequential integer vector; denotes the output depth ranges in cm. Defaults to c(0, 5, 15, 30, 60, 100, 200) after the GlobalSoilMap specification, giving output predictions over intervals 0-5cm, 5-15cm, etc.
vlow

numeric; constrains the minimum predicted value to a realistic number. Defaults to 0.
vhigh

numeric; constrains the maximum predicted value to a realistic number. Defaults to 1000.

Value

A list with the following elements: Site ID, vector of predicted values over input intervals, vector of predicted values for each cm down the profile to max(d), vector of predicted values over d (output) intervals, and root mean squared error.

Examples

dat <- data.frame("SID" = c( 1,  1,  1,  1),
                   "UD" = c( 0, 20, 40, 60),
                   "LD" = c(10, 30, 50, 70),
                  "VAL" = c( 6,  4,  3, 10),
                   stringsAsFactors = FALSE)
mpspline_one(site = dat, var_name = 'VAL')

Spline discrete soils data - multiple sites, tidy output

Description

This function implements the mass-preserving spline method of Bishop et al (1999) (doi:10.1016/S0016-7061(99)00003-8) for interpolating between measured soil attributes down a soil profile, across multiple sites' worth of data. It returns an output object with tidy data formatting.

Usage

mpspline_tidy(
  obj = NULL,
  var_name = NULL,
  lam = 0.1,
  d = c(0, 5, 15, 30, 60, 100, 200),
  vlow = 0,
  vhigh = 1000
)

Arguments

obj

data.frame or matrix. Column 1 must contain site identifiers. Columns 2 and 3 must contain upper and lower sample depths, respectively, and be measured in centimeters. Subsequent columns will contain measured values for those depths.
var_name

length-1 character or length-1 integer denoting the column in obj in which target data is stored. If not supplied, the fourth column of the input object is assumed to contain the target data.
lam

number; smoothing parameter for spline. Defaults to 0.1.
d

sequential integer vector; denotes the output depth ranges in cm. Defaults to c(0, 5, 15, 30, 60, 100, 200) after the GlobalSoilMap specification, giving output predictions over intervals 0-5cm, 5-15cm, etc.
vlow

numeric; constrains the minimum predicted value to a realistic number. Defaults to 0.
vhigh

numeric; constrains the maximum predicted value to a realistic number. Defaults to 1000.

Value

A four-item list containing data frames of predicted values over the input depth ranges, the output depth ranges, 1cm-increment predictions, and RMSE and IQR-scaled RMSE values.

Examples

dat <- data.frame("SID" = c( 1,  1,  1,  1,   2,   2,   2,   2),
                   "UD" = c( 0, 20, 40, 60,   0,  15,  45,  80),
                   "LD" = c(10, 30, 50, 70,   5,  30,  60, 100),
                  "VAL" = c( 6,  4,  3, 10, 0.1, 0.9, 2.5,   6),
                   stringsAsFactors = FALSE)
mpspline_tidy(obj = dat, var_name = 'VAL')