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:
Or install from source tree by typing the following at the command line:
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:
Available at: https://spluque.github.io/scikit-diveMove
Alternatively, installing the package as follows:
allows the documentation to be built locally (choosing the desired target {"html", "pdf", etc.}):