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
Release files for mdof 0.0.22
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mdof-0.0.22.tar.gz | 41.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mdof-0.0.22-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 87.4 kB
Release files / mdof-0.0.22.tar.gz
| Download URL | mdof-0.0.22.tar.gz |
|---|---|
| Size | 41.1 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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| Uploaded via |
twine/5.1.1 CPython/3.9.20
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Release files / mdof-0.0.22-py3-none-any.whl
| Download URL | mdof-0.0.22-py3-none-any.whl |
|---|---|
| Size | 46.3 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.9.20
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