strid 0.4.3

Installation

Either download the repository to your computer and install, e.g. by pip

pip install .

or install directly from github

pip install git+https://github.com/gunnstein/strid.git

or install directly from the python package index

pip install strid

Usage

The code example below shows how the modes of a combined deterministic-stochastic system can be obtained from measurements of the input u and the output y.

# ..
# Assume that the measured input u and output y and sampling rate is available
#
# First, import the strid module
import strid

# Then instanciate the appropriate subspace identification (SID) object
csid = strid.CombinedDeterministicStochasticSID(u, y, fs)

# If we know the model order we can now perform the SID and obtain the
# state space system matrices. For instance, we can  20 block rows and
# a model order of 100 as shown below
A, B, C, D = csid.perform(100, 20, estimate_B_and_D=True)

# Most often, we do not know the model order, and instead we overestimate
# model order and pick the physical modes with the help of a stabilization
# diagram. Strid also includes a stabilization diagram and functionality to
# pick modes directly from the plot.
# First, we must estimate modes for a range of different model orders
modes = dict()
for order in range(5, 150, 1):
    A, C = csid.perform(order, 20)
    modes[order] = strid.Mode.find_modes_from_ss(A, C, csid.fs)

# Then we can create and plot a stabilization diagram (see image below)
stabdiag = strid.StabilizationDiagram()
stabdiag.plot(modes)

# And we can use the mouse to pick the stable poles from
# the diagram and then access the picked modes with the
# `picked_modes` property of the StabilizationDiagram instance.
picked_modes = stabdiag.picked_modes

Additional examples are found in the examples folder.

Support

Please open an issue for support.

Contributing

Please contribute using Github Flow. Create a branch, add commits, and open a pull request.