dagghe / pyoma2 Goto Github PK

Dear @dagghe,

Thanks for your brilliant package, is it possible to add the following mask condition to the SSI poles as well?
MPC<0.7 and MPD>0.3: Typically a mode shape with these values is considered as spurious.

If you could add the plot of 1st singular value as the second Y-axis on the SSI stabilization plot, and the values of MPC, MPD, and MCF on the final selected mode shapes, that'd be wonderful.

Best regards,
Ayubirad

Error in algorithm_init_.py:
from .plscf import pLSCF_algo, pLSCF_algo_MS --> from .pLSCF import pLSCF_algo, pLSCF_algo_MS

Describe the bug

Method oma.BaseSetup.plot_geo2 seems not to handle correctly all Geo2.order_red values

To Reproduce

Call def_geo2 in Example1_SingleSetup.ipynb file with the following order_red:

• None
• xz
• y

it will fail on line 412 cause it is trying to set to np.NaN that is internally a float, some integers number in the pandas dataframe

Desktop (please complete the following information):

• OS: [e.g. iOS] Windows11

Additional context

Some issue can be solved by forcing s_sign and ch_names to float

        s_sign = s_sign.astype(float)  # allow setting nan

        if ord_red is None:
            pass
        # ecc...

Dear @dagghe

When I changed the ordmin, ordmax, and step to 2, 50, 2, or any similar patterns, the following error occurs:

the SSI_funct.py, the SSI_Poles :

Fn[: len(fn), ii] = fn  # save the frequencies

IndexError: index 51 is out of bounds for axis 1 with size 51

Please help me solve it

Dear authors, I'm following with great interest the developments you're making with this new version of pyOMA2. However, I can't install the package using the traditional pip install command. I get the following message:
"Defaulting to user installation because normal site-packages is not writeable
ERROR: Could not find a version that satisfies the requirement pyOMA-2 (from versions: none)
ERROR: No matching distribution found for pyOMA-2"
Can you confirm that the package is available?
Thank you very much.
MArnaud

Dear @dagghe

I have reviewed the current method used in calculating the final values of the modal parameters, which relies on selecting a single stable pole based on the user's input and the defined relative tolerance (rtol). To enhance this approach and potentially improve accuracy, I would like to propose incorporating a method inspired by the CESSIPy project.

The CESSIPy library, as described in its repository (https://github.com/MatheusCarini/CESSIPy), employs a strategy that clusters close stable poles to represent a single mode. This method involves calculating the mean values of natural frequencies (Fn), damping ratios (ξ), and mode shapes (Φ), and it also provides the standard deviation for these parameters.

Could you please consider integrating this methodology into your codebase? Specifically, the stable_modes(FN, ZT, V, stb, tol=0.01, spo=6) function from CESSIPy.py.

Thank you for considering this suggestion. I believe that adopting this method could significantly improve the reliability and effectiveness of the modal parameter calculations.

Best regards,
Ayubirad