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View Code? Open in Web Editor NEWSimple and effective tools for the analysis of movement data
Home Page: https://movekit.readthedocs.io/en/latest/
License: GNU General Public License v3.0
Simple and effective tools for the analysis of movement data
Home Page: https://movekit.readthedocs.io/en/latest/
License: GNU General Public License v3.0
Add fuzzy temporal segmentation - e,g, if the dataset is segmented into 10 min intervals. Add a window of 2 minutes the overlaps on either side of the segments.
Add to preprocessing
Resample the movement data of each animal - by downsampling at fixed time intervals.
This can be done systematically (every minute pick a element from an animal) or random downsampling (the same random time intervals for each animal).
Improve styling of all code pages, specifically considering indentation, max line length, blank lines, single vs double quotes etc. Use PEP8 as foundation.
Add general description of the package and its functionalities, list of dependencies, citation with zenodo doi, development statement to the readme
needed for distence_centroid function right afterwards
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then the duration for each animal at that location is computedExtend the demo by depicting the computed features for each animal in a chart
Also display the resulting Json in a readable way in the notebook
Combine mediod and centroid computation in one method
provide the option to calculate this from x,y data (‘heading’) or to actually use a data column where angle is provided from the tracking directly (‘orientation’)
compute turning speed
Replace subsets (segments) of a animals movement based on some indices e.g. time
function to calculate network and hierarchy of the group
Remove dead code - or add comments to the code snippet to with #dead to indicate that the code is currently not used
Document each function with doc-strings that work with SPHINX
Split the trajectory of a single animal into several intervals (segments) according to some specific criterion.
Splitting may be interesting for example to detect different properties in time intervals. E.g. split into segments of 1 minute
Change the imports for the cluster example notebook
Enable the computation of DTW for the trajectories - so a distance matrix between all trajectories
This should be computationally expensive
Write pytest for every submodule - see pytest
Document all ts-fresh parameters for the mkit.ts_feature(data_features, 'autocorrelation')
See example demo for this
Compute the minimum convex polygon to compute the animal homrange using a minimum convex polygon. Compute the mimumum convex polygon for the whole animal group and each animal individually.
Create a documentation and a online page with Sphinx
Compute the distance matrix between the entities for each time step
In addition compute the mean distance between entities
Apply a filter on the temporal dimension to filter specific time intervals
Use scipy distance functions
Compute the maximum distance between two consecutive points in time (largest metric distance between two frames)
Compute the voronoi diagram for each time step and compute also the area for each cell over time
Plot the missing values of an animal id against the time. Add to preprocess
Implement the optional parameter in CSV and excel
Compute the distance to the centroid of the swarm
Movement-based kernel density estimates
There is some indexing issue in the function which produces the same result for each tie frame
This maybe solves the issue
for time in data_time.keys(): final_matrix[time] = pd.DataFrame(distance_matrix(data_time[time].loc[:, ['x', 'y']].values, data_time[time].loc[:, ['x', 'y']]), index = data_time[time].loc[:, 'animal_id'].values, columns = data_time[time].loc[:, 'animal_id'].values)
Incorporate time series clustering for absolute features
*Write a wrapper for the following method Link
function to get distance from each animal to centroid at each time
When installing in new environment, the following error always arises:
ERROR: tsfresh 0.12.0 has requirement pandas<=0.23.4,>=0.20.3, but you'll have pandas 0.24.2 which is incompatible.
Also there are issues with the "init.py" file as it seems not able to load the relative files, like the csv module in the io folder:
>>> import movekit
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/Jolle/.virtualenvs/jolpy3/lib/python2.7/site-packages/movekit/__init__.py", line 1, in <module>
from .io.csv import *
ImportError: No module named io.csv
Multiprocess the compute_absolute_features method.
Acceleration can be currently also minus add another feature which is called pos_acceleration and has only the positive acceleration
Read and parse excel file as input source
Traveled distance between the first point in the animal trajectory and the last point - sum of traveled distance per animal
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