This is a release with breaking changes due to removal of deprecated arguments. Please review carefully before updating.
This release also supports changes from the new release of m-Path Sense (01/02/2023). Most notably, the accelerometer and gyroscope are no longer samples of a continuous stream, but rather summaries of these streams. Old versions are still supported by all functions.
x_mean: The average acceleration or gyroscopic value
along the x axis within a sample;y_mean: The average acceleration or gyroscopic value
along the y axis within a sample;z_mean: The average acceleration or gyroscopic value
along the z axis within a sample;x_mean_sq: The square root of the x values
within the sample;y_mean_sq: The square root of the y values
within the sample;z_mean_sq: The square root of the z values
within the sample; From these values, one could calculate the
L1 norm and L2 norm like before.timezone to all sensor data.
Confusingly, this is not the timezone of the data itself (as
this is always in UTC), but rather the timezone the participant was in
at the time of the measurement.parallel argument in
fix_jsons(), test_jsons(),
unzip_data(), and import().overwrite_db and dbname
arguments from import().path and db_name
arguments from copy_db().link() no longer adds an extra row before (if
add_before = TRUE) or after (if
add_after = TRUE) if the first or last measurement equals
the start or end time respectively.link_db() lifecycle status to deprecated as
link_db() depends on link(). Eventually,
link() might see changes in its functionality that will
cause link_db() to break, so it is better to deprecate it
already to motivate users to stop using this function.bin_data() incorrectly handled days
occurring after DST change.link() gained 3 new arguments:
time: The name of the column containing the timestamps
in x.end_time: Optionally, the name of the column containing
the end time in x.y_time: The name of the column containing the
timestamps in y.name: The name of the nested y data,
defaulting to "data".end_time, it is now possible to specify custom time
intervals instead of only fixed intervals through
offset_before or offset_after. Note that these
two functionality cannot be specified at the same time.time and y_time in link()
must now be explicitly named, though for the time being default to
‘time’ with a warning.continue argument to add_gaps() that
controls whether the last measurement(s) should be continued after a
gap.link_db() is now soft deprecated as it provides only
marginal added functionality compared to link().decrypt_gps() now takes a vector of encrypted GPS
coordinates instead of a whole data frame with fixed variables names
(latitude and longitude). This allows more
flexibility in its use. Also, parallelisation has been added similar to
other functions in this package (i.e. by setting a future plan,
e.g.future::plan("multisession")).The following functions are now made defunctional and internal:
activity_duration()app_usage()n_screen_on()n_screen_unlocks()screen_duration(),step_count()These functions delivered incorrect output and only allowed summaries by a fixed time frame, e.g. by hour or day. These functions will be reimplemented (some with a different name) in mpathsenser 2.0.0.
add_before or add_after is
TRUE in link(), no extra row is added if there
already is a row with a timestamp exactly equal to the start of the
interval (for add_before = TRUE) or to the end of the
interval (add_after = TRUE).moving_average() now allows a lazy tibble to allow
further computations in-database after having called
moving_average().identify_gaps() is now slightly more efficient.get_data() is now case insensitive. In a future update,
all sensor names throughout all functions will be made case
insensitive.add_before = TRUE, link() no
longer adds an extra measurement if the first measurement in the
interval equals the start time of the interval exactly.get_data() now allows multiple
participant_ids to be used.external_time has been added as an argument to
link_db(), to be able to specify the time column in
external_data in accordance with the change in
link() above.link() now correctly handles natural joins (when
by = NULL) and cross joins (when
by = character()).original_time was not added for any other
nested data row except the first one, if add_before or
add_after was true.link() no longer suffers from future’s max
object restriction (500MB by default).x and y use different time zones in
link() and add_before = TRUE,
link() now correctly leaves all time zones equal to the
input.link() incorrectly assigned the time zone of
x to the nested data of y, if
add_before or add_after was true. This is now
changed to the time zone of y, to ensure consistency. Note
that if the time zones of x and y are
different, matching will be correct but the nested data may seem off as
it will keep y’s input time zone.identify_gaps() now allows multiple sensors to be used.
This is particularly useful when there are no sensors with high
frequency sampling (like accelerometer and gyroscope) or to ensure there
can be no measurements within the gaps from any sensor.copy_db()
from_db and to_db to source_db
and target_db respectively.activity_duration(),
screen_duration(), n_screen_on(),
n_screen_unlocks(), and step_count() to
internal until it is clear how these functions should behave and, more
importantly, what their output should be.moving_average() to work correctly on multiple
participants.create_db() and the other functions, where the latter
implicitly depended on the former. The following arguments are thereby
rendered disabled:
dbname and overwrite_db arguments in
import()path and db_name in
copy_db()parallel argument in several functions.
If you wish to process in parallel, you must now specify this beforehand
using a future plan, e.g.
future::plan("multisession"). As a consequence, the package
future is no longer a dependency (but furrr
is).plot argument in
coverage(). To plot a coverage chart, you can now use the
default plot() function with the output from
coverage().rlang::abort,
rlang::warn, and rlang::inform.import() to be more manageable in
code. As a consequence, the dependency on rjson and
dbx can be dropped in favour of jsonlite and
native SQL.lifecycle as a dependency for deprecating
arguments.identify_gaps() and friends
to inform the user of a possible inconsistency when identifying
gaps.identify_gaps() from using the lag of each
measurements towards using the lead. This makes no difference in the
output but is a little easier to read.link() or
link_gaps() in a session, stating that using external
vectors dplyr::select() is ambiguous.bin_data() now correctly includes measurements in bins
that do not have a stop time. This was in particular a problem with the
last measurement of a series.bin_data().add_gaps() where multiple gaps in
succession (i.e. without other data in between) were incorrectly
handled.app_category() not being able to find the exact
app name in the search results, thereby defaulting to the
nth result (default 1).link_gaps(): For linking gap data to other data,
i.e. how many gaps occur within an interval.add_gaps(): To interleave gaps with other data.bin_data(): To subdivide data into bins, e.g. all
measurements within an hour or day.link() has been revised and expanded:
offset with offset_before and
offset_after, allowing both to be specified at the same
time (#3).add_before and add_after
argument to allow the last row before the measurement and first row
after the measurement respectively to be added to the data.split argument, allowing computation to be
split among many parts thereby lowering computational burden.app_category() is now case insensitive and gained the
new argument exact to be able to match the package name
exactly based on a partial match.get_activity() to
activity_duration().link2() to link_db().link() runs out of memory when there
are too many matches (#2). link() is now much more memory
efficient and slightly faster.get_data() which allowed multiple
sensors to be requested from one function call, sometimes leading to
crashes (#4).link() where column
original_time is missing if no records before or after the
interval are found (#6).import() where sensor data not present
in first file of the batch are dropped for the other files well.app_category() to work with the updated Google
Play website.