Metadata-Version: 1.1
Name: fsm-load-modal-composites
Version: 1.0.0
Summary: Python library that loads modal composites from the file containing the parametric model of buckling and free vibration in prismatic shell structures, as computed by the fsm_eigenvalue project.
Home-page: https://bitbucket.org/petar/fsm_load_modal_composites
Author: Petar Maric
Author-email: petarmaric@uns.ac.rs
License: BSD
Description-Content-Type: UNKNOWN
Description: About
        =====
        
        Python library that loads modal composites from the file containing the
        parametric model of buckling and free vibration in prismatic shell structures,
        as computed by the `fsm_eigenvalue project`_.
        
        This work is a part of the investigation within the research project
        [ON174027]_, supported by the Ministry for Science and Technology, Republic of
        Serbia. This support is gratefully acknowledged.
        
        References
        ----------
        
        .. [ON174027]
           "Computational Mechanics in Structural Engineering"
        
        .. _`fsm_eigenvalue project`: http://bitbucket.org/petar/fsm_eigenvalue
        
        Installation
        ============
        
        To install fsm_load_modal_composites run::
        
            $ pip install fsm_load_modal_composites
        
        Usage examples
        ==============
        
        Quick start::
        
            >>> import logging
            >>> logging.basicConfig(level=logging.DEBUG)
        
            >>> from pprint import pprint
            >>> from fsm_load_modal_composites import load_modal_composites
        
            >>> results_file = 'examples/barbero-viscoelastic.hdf5'
            >>> modal_composites, column_units, column_descriptions = load_modal_composites(
            ...     results_file, a_max=600, t_b_min=6.0
            ... )
        
            >>> modal_composites.shape
            (143,)
        
            >>> pprint(modal_composites.dtype)
            [('a', '<f8'),
             ('t_b', '<f8'),
             ('m_dominant', '<i4'),
             ('omega', '<f8'),
             ('omega_approx', '<f8'),
             ('omega_rel_err', '<f8'),
             ('sigma_cr', '<f8'),
             ('sigma_cr_approx', '<f8'),
             ('sigma_cr_rel_err', '<f8')]
        
             >>> pprint(column_descriptions)
             {'a': 'strip length',
              'm_dominant': 'dominant mode, modal composite via sigma_cr',
              'omega': 'natural frequency',
              'omega_approx': 'natural frequency approximated from critical buckling stress',
              'omega_rel_err': 'natural frequency relative approximation error',
              'sigma_cr': 'critical buckling stress',
              'sigma_cr_approx': 'critical buckling stress approximated from natural frequency',
              'sigma_cr_rel_err': 'critical buckling stress relative approximation error',
              't_b': 'base strip thickness'}
        
        Please see the `fsm_modal_analysis`_ source code for more examples.
        
        .. _`fsm_modal_analysis`: https://bitbucket.org/petar/fsm_modal_analysis/src/
        
        Contribute
        ==========
        
        If you find any bugs, or wish to propose new features `please let us know`_.
        
        If you'd like to contribute, simply fork `the repository`_, commit your changes
        and send a pull request. Make sure you add yourself to `AUTHORS`_.
        
        .. _`please let us know`: https://bitbucket.org/petar/fsm_load_modal_composites/issues/new
        .. _`the repository`: http://bitbucket.org/petar/fsm_load_modal_composites
        .. _`AUTHORS`: https://bitbucket.org/petar/fsm_load_modal_composites/src/default/AUTHORS
        
Platform: any
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Database
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
