mdof
The mdof package solves inverse problems. It is tailored for the identification of system properties from structural vibrations.
Modal identification:
periods, modeshapes = modes(input_motion, output_motion, dt)
State space system identification:
A,B,C,D = sysid(input_motion, output_motion)
Response reconstruction:
output = reconstruct(realization, dt, input_motion)
Create beautiful visuals for historical modal property documentation with integration of the osmg and opensees packages.
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Getting Started
- Documentation
- Examples:
- JupyterLab on DataHub (UC Berkeley users)
(non-UC Berkeley users)
Support
1 maintainer
Metadata
1 maintainer
Release files for mdof 0.0.23
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| mdof-0.0.23.tar.gz | 68.4 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mdof-0.0.23-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 139.7 kB
Release files / mdof-0.0.23.tar.gz
| Download URL | mdof-0.0.23.tar.gz |
|---|---|
| Size | 68.4 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/7.0.0 CPython/3.10.12
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Release files / mdof-0.0.23-py3-none-any.whl
| Download URL | mdof-0.0.23-py3-none-any.whl |
|---|---|
| Size | 71.3 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
1b04fcb512c34a0eefa2a4053fbdb650c032049aebfe785a5553921c76b5f94c
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
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twine/7.0.0 CPython/3.10.12
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Security for mdof 0.0.23
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