scikit-diveMove is a Python interface to R package diveMove for scientific data analysis, with a focus on diving behaviour analysis. It has utilities to represent, visualize, filter, analyse, and summarize time-depth recorder (TDR) data. Miscellaneous functions for handling position and 3D kinematics data are also provided. scikit-diveMove communicates with a single R instance for access to low-level tools of package diveMove.

The table below shows which features of diveMove are accessible from `scikit-diveMove`:

+----------------------------------+--------------------------+--------------------------------+ | diveMove Notes | +---------------+------------------+ | | Functions/Methods | | | +===============+==================+==========================+================================+ austFilter | | | | | | | | | | | | | +---------------+------------------+--------------------------+--------------------------------+ boutfreqs Fully implemented in Python. | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | +---------------+------------------+--------------------------+--------------------------------+ readTDR Fully implemented. Single | | TDRSource.__init__ | | | +---------------+------------------+--------------------------+--------------------------------+ | TDR.calibrate | | | | | | | | | | | | +---------------+------------------+--------------------------+--------------------------------+ | TDR.calibrate_speed | | | | | | | +---------------+------------------+--------------------------+--------------------------------+ | TDR.dive_stats | TDR.time_budget | | | TDR.stamp_dives | | +---------------+------------------+--------------------------+--------------------------------+ | TDR.plot | TDR.plot_zoc_filters | TDR.plot_phases | | | +---------------+------------------+--------------------------+--------------------------------+ | TDR.tdr | TDR.get_depth | TDR.get_speed | TDR.tdr.index | TDR.src_file | TDR.dtime | | | | | +---------------+------------------+--------------------------+--------------------------------+ | TDR.get_wet_activity | TDR.get_dives_details | | | TDR.get_dive_deriv | | | | | | | | +---------------+------------------+--------------------------+--------------------------------+ | +---------------+------------------+--------------------------+--------------------------------+

scikit-diveMove also provides useful tools for processing signals from tri-axial Inertial Measurement Units (IMU), such as thermal calibration, corrections for shifts in coordinate frames, as well as computation of orientation using a variety of current methods. Analyses are fully tractable by encouraging the use of xarray data structures that can be read from and written to NetCDF file format. Using these data structures, meta-data attributes can be easily appended at all layers as analyses progress.

Type the following at a terminal command line:

pip install scikit-diveMove

Or install from source tree by typing the following at the command line:

python setup.py install

The documentation can also be installed as described in Documentation.

Once installed, skdiveMove can be easily imported as: :

import skdiveMove as skdive

skdiveMove depends primarily on R package diveMove, which must be installed and available to the user running Python. If needed, install diveMove at the R prompt:

install.packages("diveMove")

Available at: https://spluque.github.io/scikit-diveMove

Alternatively, installing the package as follows:

pip install -e .["dev"]

allows the documentation to be built locally (choosing the desired target {"html", "pdf", etc.}):

make -C docs/ html