diveMove-internal | R Documentation |
Functions used for very particular tasks within larger functions in diveMove
.depthFilter(depth, k, probs, depth.bounds, na.rm)
.derivStats(x, diveNo)
.diveIndices(diveID, diveNo)
.diveMatches(diveID, diveNo)
.getInterval(time)
.speedStats(x, vdist)
.night(time, sunrise.time, sunset.time)
.rleActivity(time, act, interval)
.speedCol(x)
.zoc(time, depth, method, control)
depth |
Numeric vector with depth in m. |
k |
Vector of moving window width integers (coerced to integer by
|
probs |
Vector of quantiles to extract at each step indicated by
|
depth.bounds |
Numeric vector of length two, with minimum and maximum depth to bound the search for the surface. |
na.rm |
Should |
diveID |
Numeric (or character for |
diveNo |
Numeric vector of unique dive indices to extract from
|
time |
|
x |
For |
vdist |
Vertical distance travelled during this time. If
|
sunrise.time , sunset.time |
Passed from |
act |
A numeric vector indicating the activity for every element
of |
interval |
Sampling interval in seconds. |
method |
Character string to indicate the method to use for zero offset correction. One of “visual”, “offset”, or “filter” (see ‘Details’). |
control |
Named list of control parameters to be used for ZOC
method |
These functions are not meant to be called directly by the
user, as he/she could not care less (right?). This may change in the
future. Nonetheless, they can be called in the usual way for
functions that are not exported: diveMove:::.functionName
.
.depthFilter
performs the zero-offset correction with
method=“filter”. It takes a numeric vector and applies a
running quantile to it, and the process is repeated zero or more times
on the filtered/smooth vector from the previous process.
.derivStats
obtains summary statistics (summary() and sd()) of
derivatives for descent, bottom, and ascent phases for each dive.
It takes a TDRcalibrate
object.
.diveIndices
takes a numeric vector with sequences of dive
numbers, and selects the indices of dive numbers listed uniquely in
the vector given as its second argument.
.diveMatches
takes a numeric or character vector with sequences
of dive numbers, and selects the indices of dive numbers listed
uniquely in the vector given as its first argument. Stops if no
matches are found, and warns if some were ignored.
.getInterval
takes a POSIXct
object and
calculates the the most frequent interval between successive elements.
.plotTDR
is the underlying plotting function for
TDR
objects. Arguments are documented in the main S4
method (plotTDR
).
.plotZOCfilters
and plotZOCtdrs
are the underlying
plotting functions for visually assessing the ZOC procedure.
Arguments are documented in the main S4 methods
(plotZOC
).
.speedStats
takes matrix of time and speed, and an optional
vector of vertical distance travelled between segments, and calculates
the total vertical distance travelled, mean speed, and angle. Input
and output correspond to a single section of a dive.
.night
takes a POSIXct
object, sunrise and sunset
time strings to provide a list of sunrise and sunset times for each
day in the POSIXct
input.
.rleActivity
takes a factor indicating different activity
phases, their associated time, and the sampling interval to return a
factor uniquely identifying each phase of activity, i.e. labelling
them. In addition, it returns the duration of each phase, and their
beginning and end times.
.speedNames
is a character vector with possible names for a
speed vector.
.speedCol
takes a data.frame
and checks whether
there is a column with a name matching one of those in
.speedNames
.
.zoc
is the main workhorse for the zero-offset correction
ZOC procedure in calibrateDepth
. It takes a
POSIXct
object, corresponding numeric
depth vector, a string representing a method to use for the procedure,
and a list of control parameters for the chosen method to perform ZOC.
.diveIndices
returns a numeric vector with the indices of dives
(and their beginning/end indices) in diveID
.
.getInterval
returns a scalar, the mode of intervals between
time readings.
.speedStats
returns a 3-column matrix with total distance, mean
speed, and angle for a section of a dive.
.night
returns a list with sunrise and sunset times for dates
in time
.
.speedCol
returns column number where speed is located in x.
.rleActivity
returns a list with components:
time.br
A factor dividing act
into different periods
of activity.
time.peract
The duration of each period of activity.
beg.time, end.time
POSIXct objects indicating the beginning
and ending times of each period of activity.
.zoc
returns a vector with all corrected depths based on
‘method’. Depths < 0 are set to 0.
.depthFilter
returns a matrix
with the filtered
depths at each step, and corrected depth as last column, so it has
dimensions length(depth)
rows by length(k) + 1
columns.
Sebastian P. Luque spluque@gmail.com
data(divesTDR)
times <- getTime(divesTDR)
depths <- getDepth(divesTDR)
## This can take too long
## .depthFilter
d.filter <- diveMove:::.depthFilter(depth=depths, k=c(3, 5760),
probs=c(0.5, 0.02), depth.bounds=c(0, 5),
na.rm=TRUE)
## Set negative depths to zero
d.filter[d.filter[, 3] < 0, 3] <- 0
## Plotting
idx <- seq(95, 6000) # try different slices
idx <- seq(nrow(d.filter))
## Look at the top 10 m only plus a few meters above
ylim <- c(-10, 5)
layout(seq(3))
plot(times[idx], -depths[idx], type="l", col="gray",
ylab="Depth (m)", ylim=ylim)
abline(h=0, lty=2)
legend("topleft", legend="original", lty=1, col="gray")
plot(times[idx], -d.filter[idx, 1], type="l", col=2,
ylab="Depth (m)", ylim=ylim)
abline(h=0, lty=2)
lines(times[idx], -d.filter[idx, 2])
legend("topleft", legend=colnames(d.filter)[-3],
lty=1, col=c(2, 1))
plot(times[idx], -d.filter[idx, 3], type="l", ylim=ylim,
ylab="Depth (m)"); abline(h=0, lty=2)
legend("topleft", legend=paste("Original -", colnames(d.filter)[2]),
lty=1)
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