progressreport(i, n, every = min(100,max(1, ceiling(n/100))), tick = 1, nperline = NULL, charsperline = getOption("width"), style = spatstat.options("progress"), showtime = NULL, state=NULL)
n
).
i
is a multiple of every
.
i
is a multiple of tick
.
"tty"
(the default), "tk"
and "txtbar"
.
See Details.
style="tty"
.
state
was NULL
, the result is NULL
.
Otherwise the result is the updated value of state
.
style="tk"
then tcltk::tkProgressBar
is
used to pop-up a new graphics window showing a progress bar.
This requires the package tcltk.
As i
increases from 1 to n
, the bar will lengthen.
The arguments every, tick, nperline, showtime
are ignored.
style="txtbar"
then txtProgressBar
is
used to represent progress as a bar made of text characters in the
R interpreter window.
As i
increases from 1 to n
, the bar will lengthen.
The arguments every, tick, nperline, showtime
are ignored.
style="tty"
(the default),
then progress reports are printed to the
console. This only seems to work well under Linux.
As i
increases from 1 to n
,
the output will be a sequence of dots (one dot for every tick
iterations), iteration numbers (printed when iteration number is
a multiple of every
or is less than 4),
and optionally the estimated time
remaining. For example [etd 1:20:05]
means an estimated time
of 1 hour, 20 minutes and 5 seconds until finished. The estimated time remaining will be printed only if
style="tty"
, and the argument state
is given,
and either showtime=TRUE
, or showtime=NULL
and the
iterations are slow (defined as: the estimated time remaining
is longer than 3 minutes, or the average time per iteration is
longer than 20 seconds).
It is optional, but strongly advisable, to use the argument state
to store and update the internal data for the progress reports
(such as the cumulative time taken for computation)
as shown in the last example below.
This avoids conflicts with other programs that might be
calling progressreport
at the same time.
for(i in 1:40) {
#
# code that does something...
#
progressreport(i, 40)
}
# saving internal state: *recommended*
sta <- list()
for(i in 1:20) {
# some code ...
sta <- progressreport(i, 20, state=sta)
}
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