,
Stasia Grinberg [ctb]| Title: | Analysing Density Profiles from Resistance Drilling of Trees |
|---|---|
| Description: | Provides various tools for analysing density profiles obtained by resistance drilling. It can load individual or multiple files and trim the starting and ending part of each density profile. Tools are also provided to trim profiles manually, to remove the trend from measurements using several methods, to plot the profiles and to detect tree rings automatically. Written with a focus on forestry use of resistance drilling in standing trees. |
| Authors: | Luka Krajnc [aut, cre] ,
Stasia Grinberg [ctb] |
| Maintainer: | Luka Krajnc <[email protected]> |
| License: | GPL-3 |
| Version: | 0.2 |
| Built: | 2024-09-17 03:26:40 UTC |
| Source: | https://github.com/krajnc/densitr |
Given a dp object list, this function will extract all density measurement data from all dp objects in a given list and combine them in a single data frame.
combine_data(dp.list)combine_data(dp.list)
dp.list |
A list of dp objects, either from loading several files using dpload or combined manually. Note: the list should include only dp objects! |
A data frame, combining all density data from dp.list
dpload, combine_footer.
## load all files in directory dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) combine_data(dp.list)## load all files in directory dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) combine_data(dp.list)
This function will take a list of trimmed dp objects (a result of dptriml or dptriml_s function) and interactively ask the user to assign starting/ending points manually. Follow-up to automatic trim functions or to be used manually, will display a plot with the density profiles for each failure in trim detection sequentially. The plot title will display whether you are selection start or end positions. Use your mouse to select starting/ending point on the plot, your selection will then be displayed on the plot. Will return a complete list, both with the non-failed automatically trimmed dp objects and those corrected manually. The automatic trim functions should be called with the option "rreport = TRUE", which embeds a trimming report when returning the list of trimmed dp objects.
correct_failures(dp.trimmed)correct_failures(dp.trimmed)
dp.trimmed |
A list of dp objects, trimmed, with the report embedded ("rreport = TRUE"). |
A list of trimmed profiles, including both automatic and manual trimming.
dptrim, dptriml, manual_trim_detect
## load all dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the list dp.trimmed <- dptriml(dp.list, rreport = TRUE) ## manually correct the failures dp.corrected <- correct_failures(dp.trimmed)## load all dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the list dp.trimmed <- dptriml(dp.list, rreport = TRUE) ## manually correct the failures dp.corrected <- correct_failures(dp.trimmed)
The opposite of the dpdetect_s, it will check the mean values
of the last four segments and compare them to the cutoff limit.
Will give a warning if end not detected, which is expected on
measurements where the needle did not exit the tree on the opposite
side of the tree. See return.plot = TRUE to display the
actual process. The function is called on a dp object and returns
either a row number of the measurement ending or a plot displaying
the segmentation and detection. The sensitivity can be adjusted
using the cutoff.sd parameter, which is an indicator on how many
standard deviations the segment mean value can be before cutting it
off.
dpdetect_e( dp, cutoff.sd = 1, return.plot = FALSE, minseglen = 250, span = 0.1, nroll = 100 )dpdetect_e( dp, cutoff.sd = 1, return.plot = FALSE, minseglen = 250, span = 0.1, nroll = 100 )
dp |
A dp object, see dpload. |
cutoff.sd |
How many standard deviations for the cutoff limit? |
return.plot |
If true, will return a plot displaying segment detection for the current dp file. |
minseglen |
Minimum segment length for segment detection, default setting of 250 points is for data resolution of 1/100 mm, test a few options with return.plot = TRUE to find the right value |
span |
Span for loess regression, use to adjust sensitivity of detection detection for the current dp file. |
nroll |
Number of points for rolling mean, use to adjust sensitivity of detection for the current dp file. |
Either a row number where the actual measurement ends or a plot, displaying changepoint segmentation and set limits.
dpdetect_s, dptrim, dptriml, dptrim_s, dptriml_s
## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## get ending point start <- dpdetect_e(dp) ## plot the end detection dpdetect_e(dp, return.plot = TRUE)## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## get ending point start <- dpdetect_e(dp) ## plot the end detection dpdetect_e(dp, return.plot = TRUE)
A typical resistance drilling measurement starts with an increase
in resistance values in between the measurement start and the
immersion of the needle in the wood. These values are not useful
when estimating density and should be removed before further
analysis. This function will detect the starting point
automatically using binary segmentation from the package
changepoint, which separates the measurement in segments
based on their mean and variance. Start is detected, when the
segment mean is outside of the cutoff limit, see return.plot
= TRUE to display the diagnostic plot. This function will only
check the mean values of the first four (4) segments and compare
them to the cutoff value. The function is called on a dp object
and returns either a row number of the starting point or a plot
displaying the segmentation and detection. The sensitivity can be
adjusted using the cutoff.sd parameter, which is an indicator on
how many standard deviations the segment mean value can be before
cutting it off. Will return a warning if start not detected.
dpdetect_s( dp, cutoff.sd = 1, return.plot = FALSE, minseglen = 250, span = 0.1, nroll = 100 )dpdetect_s( dp, cutoff.sd = 1, return.plot = FALSE, minseglen = 250, span = 0.1, nroll = 100 )
dp |
A dp object, see dpload. |
cutoff.sd |
How many standard deviations for the cutoff limit? |
return.plot |
If true, will return a plot displaying segment detection for the current dp file. |
minseglen |
Minimum segment length for segment detection, default setting of 250 points is for data resolution of 1/100 mm, test a few options with return.plot = TRUE to find the right value |
span |
Span for loess regression, use to adjust sensitivity of detection detection for the current dp file. |
nroll |
Number of points for rolling mean, use to adjust sensitivity of detection for the current dp file. |
Either a row number where the actual measurement starts or a plot, displaying changepoint segmentation and set limits.
dpdetect_e, dptrim, dptriml, dptrim_s, dptriml_s
## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## get starting point start <- dpdetect_s(dp) ## plot the start detection dpdetect_s(dp, return.plot = TRUE)## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## get starting point start <- dpdetect_s(dp) ## plot the start detection dpdetect_s(dp, return.plot = TRUE)
This function will take a dp object and remove the trend from the
measurement either by fitting a linear regression or by fitting a
GAM regression using REML. The trend is then subtracted from the
actual data and a detrended dp object is returned. Be advised
detrending should be done on measurements without the starting or
ending point, e.g. they should be trimmed. GAM is more useful in
tree ring detection, while linear regression is more commonly used
for further analysis of the density data. GAM requires mcgv
package to run.
dpdetrend(dp, type = "")dpdetrend(dp, type = "")
dp |
A dp object, see dpload. |
type |
Either "linear" for a fitting linear regression or "gam" for a GAM fit using REML. |
A dp object without the trend.
dptrim, dptriml, dptrim_s, dptriml_s
## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## load several dp objects dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurement dp.trimmed <- dptrim(dp) ## detrend the measurement dp.detrended <- dpdetrend(dp, type = "linear") ## detrend a list without displaying progress dp.list.detrended <- lapply(dp.list, dpdetrend, type = "linear") ## detrend a list with displaying progress and run in parallel to ## speed things up - requires pbapply library, adjust the cl argument to ## desired number of cores dp.list.detrended <- pbapply::pblapply(dp.list, dpdetrend, type = "linear", cl = 1)## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## load several dp objects dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurement dp.trimmed <- dptrim(dp) ## detrend the measurement dp.detrended <- dpdetrend(dp, type = "linear") ## detrend a list without displaying progress dp.list.detrended <- lapply(dp.list, dpdetrend, type = "linear") ## detrend a list with displaying progress and run in parallel to ## speed things up - requires pbapply library, adjust the cl argument to ## desired number of cores dp.list.detrended <- pbapply::pblapply(dp.list, dpdetrend, type = "linear", cl = 1)
Loads either a single .dpa file or a list of .dpa files. If dpa.file is specified, it will load a single file. If dp.directory is specified, it will search for all dpa files in that directory (recursively in all subfolders, can be turned off) and return a list of dp files. It will use pbapply to display progress, if loading a directory.
dpload(dp.file = NULL, dp.directory = "", recursive = TRUE, name = "file")dpload(dp.file = NULL, dp.directory = "", recursive = TRUE, name = "file")
dp.file |
A path to a single file, including file name. |
dp.directory |
A directory with .dpa files. |
recursive |
Also look for density profiles files in subfolders? |
name |
Either |
NOTE: for now this function only supports loading density profiles created by the Rinntech Resistograph® resistance drilling device (*.dpa). It was tested to work on files produced by R650-RC drill.
A dp object or a list of dp objects.
## load a single file dpload(system.file("extdata", "00010001.dpa", package = "densitr")) dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## load all files in directory dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr"))## load a single file dpload(system.file("extdata", "00010001.dpa", package = "densitr")) dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## load all files in directory dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr"))
Called on a density profile it will return tree rings, which were
automatically detected in the density profile. For best results,
run on a trimmed and detrended density profile (use GAM for best
results, see dpdetrend). The function will then search for
local peaks and valleys within the profile. Normally works well in
softwood species, where density increases in late wood and
decreases in nearly wood. It will return a data frame containing
peaks and valleys, along with their horizontal position. A
diagnostic plot will be returned instead when return.plot = TRUE.
Green points are valleys, blue points are peaks and red points were
automatically excluded. The algorithm will search for peaks and
valleys, after which it will automatically exclude all repeated
points. Each peak should be followed by a valley and vice versa,
when peak-peak situation is found, it will always take the higher
peak and the opposite in valleys (keeps the lowest values). Adjust
sensitivity by either adjusting pps, which dictates how many
points on each side of the identified peak are the minimum.
Essentially this dictates the minimum width of detected rings, try
adjusting it and display the plot. Minimum peak value can also be
adjusted with the parameter threshold, which dictates how many
stand deviations from the mean amplitude of the profile is the
lowest minimum peak value. Before ring detection the profile can
also be denoised by setting smooth = TRUE, which applies a
loess regression to smooth the data using the span parameter.
dprings( dp, pps = 200, threshold.sd = 0, return.plot = FALSE, smooth = FALSE, span = 0.01 )dprings( dp, pps = 200, threshold.sd = 0, return.plot = FALSE, smooth = FALSE, span = 0.01 )
dp |
An dp object, see |
pps |
Points per peak, the minimum width of a peak, half on each side. A local peak is identified when half of those points are lower on each side of the potential peak. The inverse is true in valleys. |
threshold.sd |
Minimum peak value in standard deviations away from the overall mean of the signal. By default no peaks are allowed to be beneath the overall mean, can be adjusted to negative to lower the minimum peak allowed. |
return.plot |
If TRUE, the function will return a diagnostic plot. Green points are valleys, blue points are peaks and red points were automatically excluded. |
smooth |
Set to TRUE, the profile will be denoised using a LOESS regression. |
span |
Span of the LOESS regression. |
A data frame including the values and positions for all
peaks and values. Usually piped into get_RW to get ring
widths.
get_RW
## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## trim and detrend the measurement dp.trimmed <- dptrim(dp) dp.detrended <- dpdetrend(dp.trimmed, type = "gam") ## identify rings rings <- dprings(dp.detrended) ## plot a diagnostic dprings(dp.detrended, return.plot = TRUE) ## get tree ring widths: get_RW(rings)## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## trim and detrend the measurement dp.trimmed <- dptrim(dp) dp.detrended <- dpdetrend(dp.trimmed, type = "gam") ## identify rings rings <- dprings(dp.detrended) ## plot a diagnostic dprings(dp.detrended, return.plot = TRUE) ## get tree ring widths: get_RW(rings)
Calls dpdetect_s and dpdetect_e on a given dp object and
returns a trimmed dp object with the the row before the starting
point and after the ending removed. If return.plot = TRUE,
it will return a plot displaying the dp object with detected
starting and ending point. If called with the option
return.fail = FALSE and return.plot = FALSE, the
returned object will also include information on whether both
cutoff points were detected. If starting/ending point not detected,
dp object is returned with no changes. When running on a list of
dp objects, use dptriml.
dptrim(dp, return.plot = FALSE, return.fail = FALSE, silent = FALSE, ...)dptrim(dp, return.plot = FALSE, return.fail = FALSE, silent = FALSE, ...)
dp |
An dp object, see |
return.plot |
Return a plot instead of dp object? If TRUE, returns a plot instead of a dp object. When return.fail = TRUE, it returns a list of three: dp object, start trimming success and end trimming success. |
return.fail |
Should information on the success of trimming be included when returning a dp object? |
silent |
Mute detection warnings, used when calling on list. A list of trimmed dp objects, a result of calling dtriml or dptriml_s on a dp list with return.fail = FALSE. |
... |
Parameters minseglen, span and nroll, will get passed through to dpdetect_s, adjust when profile resolution is not 1/100 of a millimeter. |
A trimmed dp object, with the beginning and ending removed, if they were detected. When return.plot = TRUE, it returns a plot displaying the process.
dptriml, dptrim_s, dptriml_s
## load a single dp file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## trim the measurements dp.trimmed <- dptrim(dp) ## plot trimming dptrim(dp, return.plot = TRUE)## load a single dp file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## trim the measurements dp.trimmed <- dptrim(dp) ## plot trimming dptrim(dp, return.plot = TRUE)
Calls dpdetect_s on a given dpa object and returns a trimmed
dpa object with the the rows before the starting point removed. If
return.plot = TRUE, it will return a plot displaying the dp object
with detected starting point. If called with the option
return.fail = FALSE and return.plot = FALSE, the returned
object will also include information on whether starting cutoff
point was detected. If starting point not detected, dp object is
returned with no changes. When running on a list of dp objects,
use dtriml_s.
dptrim_s(dp, return.plot = FALSE, return.fail = FALSE, silent = FALSE, ...)dptrim_s(dp, return.plot = FALSE, return.fail = FALSE, silent = FALSE, ...)
dp |
An dp object, see |
return.plot |
Return a plot instead of dp object? If TRUE, returns a plot instead of a dp object. When return.fail = TRUE, it returns a list of three: dp object, start trimming success and end trimming success. |
return.fail |
Should information on the success of trimming be included when returning a dp object? |
silent |
Mute detection warnings, used when calling on list. A list of trimmed dp objects, a result of calling dptriml or dptriml_s on a dp list with rreport = FALSE. |
... |
Parameters minseglen, span and nroll, will get passed through to dpdetect_s, adjust when profile resolution is not 1/100 of a millimeter. |
A trimmed dp object, with the beginning and ending removed, if they were detected. When return.plot = TRUE, it returns a plot displaying the process.
dptrim, dptriml, dptriml_s
## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## trim the measurement at start dp.trimmed <- dptrim_s(dp) ## plot trimming dptrim_s(dp, return.plot = TRUE)## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## trim the measurement at start dp.trimmed <- dptrim_s(dp) ## plot trimming dptrim_s(dp, return.plot = TRUE)
Calls dptrim on a list of dp objects and return a list of
trimmed objects. If automatic detection fails, the dp objects are
not trimmed. Can be run in parallel on multiple cores, this speeds
up the trimming process significantly.
dptriml(dp.list, rreport = FALSE, cl = 1, ...)dptriml(dp.list, rreport = FALSE, cl = 1, ...)
dp.list |
A list of dp objects, see |
rreport |
Return an embedded report on automatic trim success,
mandatory when using |
cl |
Number of cores to run the trimming in parallel, passed through to |
... |
Parameters minseglen, span and nroll, will get passed through to dpdetect_s, adjust when profile resolution is not 1/100 of a millimeter. |
A list of trimmed dp objects. When rreport = TRUE, it return a two-item list of (i) trimmed dp objects and (ii) trimming report data frame.
dptrim, dptrim_s, dptriml_s,
## load several dpa files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements dp.trimmed <- dptriml(dp.list)## load several dpa files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements dp.trimmed <- dptriml(dp.list)
Calls dptrim on a list of dp objects and returns a list of
trimmed objects. If automatic detection fails, the dp objects are
not trimmed. Can be run in parallel on multiple cores, this speeds
up the trimming process significantly. Only trims the starting
side, see dptriml for trimming both side simultaneously.
dptriml_s(dp.list, rreport = FALSE, cl = 1, ...)dptriml_s(dp.list, rreport = FALSE, cl = 1, ...)
dp.list |
A list of dp objects, see |
rreport |
Return an embedded report on automatic trim success,
mandatory when using |
cl |
Number of cores to run the trimming in parallel, passed
through to |
... |
Parameters minseglen, span and nroll, will get passed through to dpdetect_s, adjust when profile resolution is not 1/100 of a millimeter. |
A list of trimmed dp objects. When rreport = TRUE, it return a two-item list of (i) trimmed dp objects and (ii) trimming report data frame.
dptrim, dptrim_s, dptriml_s,
## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements dp.trimmed <- dptriml_s(dp.list)## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements dp.trimmed <- dptriml_s(dp.list)
A wrapper function for regex extraction of filename. Given a character string ("data/0005/00/00050060.dpa"), it will return only the file name without the extension ("00050060").
extract_dpa_name(string)extract_dpa_name(string)
string |
A path to file, including file name. Can be nested in many directories or in none. |
An extracted filename, a character string.
https://stackoverflow.com/questions/47678725/how-to-do-str-extract-with-base-r
Called on an object returned by dprings, it will return ring
widths for all detected rings. The units are determined by the
xUnit from the footer of density profile.
get_RW(rings)get_RW(rings)
rings |
A data frame with the identified rings, a result of the dprings() call on an individual profile |
A vector of ring widths, which are peak-to-peak differences.
dprings
## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## trim and detrend the measurement dp.trimmed <- dptrim(dp) dp.detrended <- dpdetrend(dp.trimmed, type = "gam") ## identify rings rings <- dprings(dp.detrended) ## get tree ring widths: get_RW(rings)## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## trim and detrend the measurement dp.trimmed <- dptrim(dp) dp.detrended <- dpdetrend(dp.trimmed, type = "gam") ## identify rings rings <- dprings(dp.detrended) ## get tree ring widths: get_RW(rings)
Follow-up to automatic trim functions or to be used manually, will
display a plot with the density profiles. Most commonly used in
automatic failure corrections by the function correct_failures. Use
your mouse to select starting/ending point on the plot, your
selection will then be displayed on the plot. Either returns a
numeric value or NA in case of errors. There are two special cases:
when encountering an error with a label = " - PICK START" it will
return the starting position, and with label " - PICK STOP" it will
return the ending position. These labels are used when correcting
several density profiles at once using correct_failures.
This function uses graphics::locator, which only works on
screen devices X11, windows and quartz. It will not work on other
devices, returning NA.
manual_trim_detect(failure, label = "")manual_trim_detect(failure, label = "")
failure |
A dp object, usually see dpload. |
label |
Optional label to be displayed on the plot after the file |
The x position selected on the graph, row number in the dp$data data frame.
dptrim, dptriml
## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## get a starting point on the plot manual_trim_detect(dp)## load a single file dp <- dpload(system.file("extdata", "00010001.dpa", package = "densitr")) ## get a starting point on the plot manual_trim_detect(dp)
Plot a list of dp objects, one by one. Press any key to move to the next dp object. Returns nothing.
plot_all(dp.list)plot_all(dp.list)
dp.list |
A list of dp objects, see |
dptrim, dptrim_s, dptriml_s,
## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements if(interactive()){ plot_all(dp.list) }## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements if(interactive()){ plot_all(dp.list) }
Display an automatic end detection of dp list, each dp object individually. Press any key to move to the next dp object. Returns nothing.
plot_end_detection(dp.list)plot_end_detection(dp.list)
dp.list |
A list of dp objects, see |
dptrim, dptrim_s, dptriml_s,
## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements if(interactive()){ plot_end_detection(dp.list) }## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements if(interactive()){ plot_end_detection(dp.list) }
Plot each failed trimming detection, one by one. Press any key to move to the next dp object. Returns nothing. The entry list of dp trimmed objects must include the trimming report (rreport = TRUE).
plot_failures(dp.trimmed)plot_failures(dp.trimmed)
dp.trimmed |
A list of trimmed dp objects, see |
dptrim, dptrim_s, dptriml_s,
## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements ## Not run: plot_failures(dp.list) ## End(Not run)## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements ## Not run: plot_failures(dp.list) ## End(Not run)
Display an automatic start detection of dp list, each dp object individually. Press any key to move to the next dp object. Returns nothing.
plot_start_detection(dp.list)plot_start_detection(dp.list)
dp.list |
A list of dp objects, see |
dptrim, dptrim_s, dptriml_s,
## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements if(interactive()){ plot_start_detection(dp.list) }## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements if(interactive()){ plot_start_detection(dp.list) }
Display an automatic trimming of dp list, each dp object individually. Press any key to move to the next dp object. Returns nothing.
plot_trimming(dp.list)plot_trimming(dp.list)
dp.list |
A list of dp objects, see |
dptrim, dptrim_s, dptriml_s,
## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## plot trimming the measurements if(interactive()){ plot_trimming(dp.list) }## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## plot trimming the measurements if(interactive()){ plot_trimming(dp.list) }
Reads a single *.dpa file and returns a dp object,
constructed from two lists: data and footer. The
former one contains actual measurement values, the latter includes
supplementary data recorded by the Resistograph® device, such as
time, firmware number...
read_dpa(file)read_dpa(file)
file |
A path to file, including file name. |
A dp object.
dpload
Returns a dp list of trimmed dp objects without the failed trim objects. Trimmed dp list should be a result of either calling dtriml on a list of dp objects or calling dtriml_s to remove the starting portions of the measurement. Both functions should be called with the option "return.fail = FALSE", which embeds a trimming report when returning the list of trimmed dp objects.
remove_trim_failures(dp.trimmed)remove_trim_failures(dp.trimmed)
dp.trimmed |
A list of trimmed dp objects, a result of calling dtriml or dtriml_s on a dp list with "return.fail = FALSE". |
A dp list of trimmed objects with failures removed.
dptriml, dptriml_s
## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements dp.trimmed <- dptriml(dp.list, rreport = TRUE) ## remove trimming failures dp.nofailures <- remove_trim_failures(dp.trimmed)## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements dp.trimmed <- dptriml(dp.list, rreport = TRUE) ## remove trimming failures dp.nofailures <- remove_trim_failures(dp.trimmed)
An inverse of remove_trim_failures, return a list of failed trimming objects from a trimmed dp list. Trimmed dp list should be a result of either calling dtriml on a list of dp objects or calling dtriml_s to remove the starting portions of the measurement. Both functions should be called with the option "rreport = FALSE", which embeds a trimming report when returning the list of trimmed dp objects. If no failures found, it will return a list of trimmed profiles without the report attached.
separate_trim_failures(dp.trimmed)separate_trim_failures(dp.trimmed)
dp.trimmed |
A list of trimmed dp objects, a result of calling dptriml or dptriml_s on a dp list with "rreport = FALSE". |
Two lists, one with start failures and one with end failures.
dptriml, dptriml_s
## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements dp.trimmed <- dptriml(dp.list, rreport = TRUE) ## separate trimming failures dp.nofailures <- separate_trim_failures(dp.trimmed)## load several dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## trim the measurements dp.trimmed <- dptriml(dp.list, rreport = TRUE) ## separate trimming failures dp.nofailures <- separate_trim_failures(dp.trimmed)
This function will take a list of dp objects and interactively ask the user to assign starting/ending points manually for all density profiles in sequentially. Used as alternative to automatic trim functions. The plot title will display whether you are selecting start or end position. Use your mouse to select starting/ending points on the plot.
trim_manually(dp.list)trim_manually(dp.list)
dp.list |
A list of dp objects. |
A list of trimmed density profiles.
dptrim, dptriml, manual_trim_detect
## load all dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## manually trim the list dp.trimmed <- trim_manually(dp.list)## load all dp files dp.list <- dpload(dp.directory = system.file("extdata", package = "densitr")) ## manually trim the list dp.trimmed <- trim_manually(dp.list)