pyOMA.core.StabilDiagram#

pyOMA - A toolbox for Operational Modal Analysis Copyright (C) 2015 - 2025 Simon Marwitz, Volkmar Zabel, Andrei Udrea et al.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see <https://www.gnu.org/licenses/>.

Based on previous works by Andrei Udrea 2014 and Volkmar Zabel 2015 Modified and Extended by Simon Marwitz 2015 ff.

..TODO::

  • scale markers right on every platform

  • frequency range as argument or from ssi params, sampling freq

  • add switch to choose between “unstable only in …” or “stable in …”

  • (select and merge several poles with a rectangular mouse selection)

  • distinguish beetween stabilization criteria and filtering criteria

  • add zoom and sliders (horizontal/vertical) for the main figure

  • distinguish between “export results” and “save state”

  • rework mask logic (currently it is very difficult to understand)

  • Merge DataCursor and JupyterGUI.SnappingCursor

Functions

nearly_equal(a, b[, sig_fig])

Classes

DataCursor(ax, order_data, f_data[, mask, ...])

StabilCalc(modal_data[, prep_signals])

StabilCluster(modal_data[, prep_signals])

The automatic modal analysis done in three stages clustering.

StabilPlot(stabil_calc[, fig])

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