ross.ConvergenceResults#

class ross.ConvergenceResults(el_num, eigv_arr, error_arr)#

Class used to store results and provide plots for Convergence Analysis.

This class plots:

Natural Frequency vs Number of Elements Relative Error vs Number of Elements

Parameters
el_numarray

Array with number of elements in each iteraction

eigv_arrarray

Array with the n’th natural frequency in each iteraction

error_arrarray

Array with the relative error in each iteraction

Returns
figPlotly graph_objects.make_subplots()

The figure object with the plot.

Methods

__init__(el_num, eigv_arr, error_arr)#
classmethod load(file)#

Load results from a .toml file.

This function will load the simulation results from a .toml file. The file must have all the argument’s names and values that are needed to reinstantiate the class.

Parameters
filestr, pathlib.Path

The name of the file the results will be loaded from.

Examples

>>> # Example running a stochastic unbalance response
>>> from tempfile import tempdir
>>> from pathlib import Path
>>> import ross as rs
>>> # Running an example
>>> rotor = rs.rotor_example()
>>> freq_range = np.linspace(0, 500, 31)
>>> n = 3
>>> m = 0.01
>>> p = 0.0
>>> results = rotor.run_unbalance_response(n, m, p, freq_range)
>>> # create path for a temporary file
>>> file = Path(tempdir) / 'unb_resp.toml'
>>> results.save(file)
>>> # Loading file
>>> results2 = rs.ForcedResponseResults.load(file)
>>> abs(results2.forced_resp).all() == abs(results.forced_resp).all()
True
plot(fig=None, **kwargs)#

Plot convergence results.

This method plots:

Natural Frequency vs Number of Elements Relative Error vs Number of Elements

Parameters
figPlotly graph_objects.make_subplots()

The figure object with the plot.

kwargsoptional

Additional key word arguments can be passed to change the plot layout only (e.g. width=1000, height=800, …). *See Plotly Python Figure Reference for more information.

Returns
figPlotly graph_objects.make_subplots()

The figure object with the plot.

classmethod read_toml_data(data)#

Read and parse data stored in a .toml file.

The data passed to this method needs to be according to the format saved in the .toml file by the .save() method.

Parameters
datadict

Dictionary obtained from toml.load().

Returns
The result object.
save(file)#

Save results in a .toml file.

This function will save the simulation results to a .toml file. The file will have all the argument’s names and values that are needed to reinstantiate the class.

Parameters
filestr, pathlib.Path

The name of the file the results will be saved in.

Examples

>>> # Example running a unbalance response
>>> from tempfile import tempdir
>>> from pathlib import Path
>>> import ross as rs

>>> # Running an example
>>> rotor = rs.rotor_example()
>>> speed = np.linspace(0, 1000, 101)
>>> response = rotor.run_unbalance_response(node=3,
...                                         unbalance_magnitude=0.001,
...                                         unbalance_phase=0.0,
...                                         frequency=speed)

>>> # create path for a temporary file
>>> file = Path(tempdir) / 'unb_resp.toml'
>>> response.save(file)