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Changelog

Source: NEWS.md

mnirs 0.6.4

Bug fix

  • Fix a memory allocation bug with resample_mnirs. Downsampling 100k rows now allocates ~11MB rather than ~4.5 GB.

mnirs 0.6.3

CRAN release: 2026-05-07

Plotting improvements

  • Generic plot.mnirs() ncan now be called on a list of “mnirs” data frames. Each data frame will be printed as a facet. This is primarily useful for printing a list of interval data frames exported from extract_intervals():
read_mnirs() |> 
    extract_intervals() |> 
    plot()
## returns a plot with a facet for each interval
  • To faciliate this, extract_intervals() now returns a list of data frames with class = "mnirs". Otherwise, to manually plot a list of data frames, it will need to have class(list) <- c("mnirs", class(list)) edited manually.
read_mnirs() |> 
    extract_intervals() |> 
    class()
#> [1] "mnirs" "list"
  • Backend improvement: print.mnirs() generic created to avoid displaying extra NextMethod() calls when printing lists with class = "mnirs".

Modified lap extraction behaviour

  • extract_intervals():

    • When specifying start and end with by_lap(), start will only refer to the first sample of the lap, and end the last sample.

    • With previous behaviour, start = by_lap() would include the entire specified lap(s). But this resulted in less control over displaying only parts of a lap.

    • Updated behaviour is now more consistent with by_time, by_label, and by_sample() methods, which reference start and end from a single sample. This allows extraction of e.g. only the first 60-sec of lap:

read_mnirs() |> 
    extract_intervals(
        start = by_lap(1, 3),
        span = c(0, 60),
    )
## returns a list of two intervals with the first 60-sec of laps 1 and 3, respectively.

Updated core functions

  • read_mnirs(): Fix detection issue with “PerfPro” file formats, and another small bug fix to improve timestamp parsing.

  • create_mnirs_data() now properly accepts tidy evaluation for nirs_channels, time_channel, and event_channel:

create_mnirs_data(df, nirs_channels = c(o2hb, hhb))

  • resample_mnirs():

    • Now resamples to an inclusive time range around existing data, rounded to the nearest resampled rate. Better handles edge cases where the last sample was being dropped in certain rounding conditions.

    • Fix an edge case error when sample_rate was mis-specified higher than the actual sample_rate of the data. Now more robustly fills non-numeric columns.

mnirs 0.6.2

CRAN release: 2026-04-18

Core updates

  • read_mnirs():

    • Now properly parses time_channel as fractional unix values; i.e. timestamp (e.g. “hh:mm:ss”) values are saved by Excel in all its infinite wisdom as numeric fractional Unix timestamps. Will now be properly coerced to numeric and POSIXct timestamp values can be returned.

    • Timestamps should now be returned in the user’s local time zone.

Core function argument changes

  • resample_mnirs(): Update default method = "none". Less opinionated default to force users to explicitly opt-in to specifying either “linear” or “locf” methods to fill/interpolate across new samples. Updated package documentation.

  • replace_invalid(), replace_outliers(), replace_missing(): Remove bypass_checks arg intended for internal use only, to bypass redundant checks when calling from replace_mnirs().

Small edits

  • plot.mnirs(): No longer coerces to long format data behind the scenes.

  • plot.mnirs(): y-axis title changed from “signal” to “mNIRS”.

  • Fix lap marker inconsistency in train.red_intervals.csv. Updated relevant interval times in documentation.

  • README.md & “reading-mnirs-data.qmd” vignette updates.

  • Small documentation changes.

mnirs 0.6.1

Bug fixes

  • Core functions updated to accept nirs_channel args as a list.

    • An info message will be displayed when a list is not required, instead of erroring.

    • Additional info messages will be displayed for shift_mnirs(), rescale_mnirs(), and extract_intervals() when nirs_channels has not been specified as a list, nor retrieved from metadata. As a reminder of the grouping requirements in those functions.

  • Core functions now properly update nirs_channels metadata when re-specified.

    • Previously, specifying nirs_channels in a function would only add any additional column name strings to the existing metadata rather than overwrite it. Meaning nirs_channels could only be removed from metadata by using create_mnirs_data(nirs_channels = "..."). The updated behaviour should mean channels need to be re-specified less often.

  • filter_mnirs(): Fixed an error matching method arguments when left blank.

  • README and “Reading and Cleaning Data with {mnirs}” vignette updated to fix typos and small edits.

mnirs 0.6.0

CRAN release: 2026-03-30

Prepare for CRAN submission

  • NEWS.md is truncated to the most recent relevant release updates. The full NEWS.md remains in the dev branch.

  • Some development functions have been omitted from the package build in expectation of CRAN review. They are still present in dev branch and can be installed with pak::pak("jemarnold/mnirs").

Updated core functions

  • filter_mnirs(): Method-specific arguments (e.g. order for method = "butterworth", or width for method = "moving_average") removed from the generic function call. Continue to be passed to the appropriate method via .... Documentation and info/warning/abort messages updated.

  • filter_ma() better separates effects of partial and na.rm args:

    • partial = FALSE by default returns NA at edges where insufficient number of samples are available compared to the specified width or span.

    • partial = TRUE calculates mean values at edges, as long as one valid non-NA sample is available.

    • na.rm = FALSE by default behaves as expected with mean(na.rm = FALSE), propagating any NAs in the local window to the calculated mean with a warning.

      • NOTE This differs from the behaviour of na.rm = FALSE in filter_butter(), which errors if there are any internal NAs present. This has not been changed.

    • na.rm = TRUE ignores NAs and calculates local means as long as one valid sample is present.

  • plot.mnirs()

    • Add new arg: points = TRUE will plot points in addition to lines, as a useful quick shortcut.

    • Update na.omit now omits non-valid c(NA, NaN, Inf, -Inf) values from plotting, not just NA.

  • palette_mnirs() can now accept either a single numeric value specifying the number of colours to return, or any number of (valid) character colour names.

mnirs 0.5.2

Shiny app

mnirs 0.5.1

Updated core functions

  • read_mnirs() now has better automated channel detection logic for “Artinis” / “Oxysoft” file formats. nirs_channels and time_channel can be left blank to automatically “sample”, “time” (from sample_rate), and nirs channel “2”.

  • replace_outliers() now accepts numeric outlier_cutoff values for more precise outlier detection thresholds (previously was integers only). Documentation also updated.

mnirs 0.5.0

Updated core functions

  • read_mnirs() expands event_channel to work with integer “lap” numbers, or character event label as previous.

    • Should now work on more .csv file formats; previously read errors may have occured where the file contained header rows above the data table, resulting in improper detection of columns.

    • event_channel can now be specified as an integer lap column, in addition to a character column as previous.

    • Other {mnirs} functions may expect event_channel to be either character or integer-ish.

  • extract_intervals():

    • Function arguments start and end are used to specify one or both of a start and end point to the target interval.

    • Specify start/end values with helper functions by_time(), by_label(), by_lap(), and by_sample().

    • Numeric values are automatically coerced to “time” values; Explicit integer values (e.g. 2L) are coerced to “lap”; Character strings are coerced to event “label”.

Package resources

  • A rough draft {mnirs} hex icon and package cheatsheet have been added.

mnirs 0.4.2 and prior