ross.stochastic.ST_TimeResponseResults

class ross.stochastic.ST_TimeResponseResults(t, yout, xout, number_dof, nodes, link_nodes, nodes_pos)

Store stochastic results and provide plots for Time Response and Orbit Response.

Parameters:

t1-dimensional array

Time array.

youtarray

System response.

xoutarray

Time evolution of the state vector.

nodes: array

list with nodes from a rotor model.

link_nodes: array

list with nodes created with “n_link” from a rotor model.

nodes_pos: array

Rotor nodes axial positions.

number_dofint

Number of degrees of freedom per shaft element’s node

Returns:

figPlotly graph_objects.Figure()

The figure object with the plot.

Methods

__init__(t, yout, xout, number_dof, nodes, link_nodes, nodes_pos)

classmethod load(file)

Load results from a .toml or .json file.

This function will load the simulation results from a .toml or .json 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.stochastic as srs

>>> # Running an example
>>> rotors = srs.st_rotor_example()
>>> freq_range = np.linspace(0, 500, 31)
>>> n = 3
>>> m = np.random.uniform(0.001, 0.002, 10)
>>> p = 0.0
>>> results = rotors.run_unbalance_response(n, m, p, freq_range)

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

>>> # Loading file
>>> results2 = srs.ST_ForcedResponseResults.load(file)
>>> results2.forced_resp.all() == results.forced_resp.all()
True

plot_1d(probe, percentile=[], conf_interval=[], probe_units='rad', displacement_units='m', time_units='s', fig=None, **kwargs)

Plot stochastic time response.

This method plots the time response given a tuple of probes with their nodes and orientations.

Parameters:

probelist of tuples

List with tuples (node, orientation angle, tag). node : int

indicate the node where the probe is located.

orientationfloat

probe orientation angle about the shaft. The 0 refers to +X direction.

tagstr, optional

probe tag to be displayed at the legend.

percentilelist, optional

Sequence of percentiles to compute, which must be between 0 and 100 inclusive.

conf_intervallist, optional

Sequence of confidence intervals to compute, which must be between 0 and 100 inclusive.

probe_unitsstr, option

Units for probe orientation. Default is “rad”.

displacement_unitsstr, optional

Displacement units. Default is ‘m’.

time_unitsstr

Time units. Default is ‘s’.

figPlotly graph_objects.Figure()

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.Figure()

The figure object with the plot.

plot_2d(node, percentile=[], conf_interval=[], displacement_units='m', fig=None, **kwargs)

Plot orbit response (2D).

This function plots orbits for a given node on the rotor system in a 2D view.

Parameters:

nodeint

Select the node to display the respective orbit response.

percentilelist, optional

Sequence of percentiles to compute, which must be between 0 and 100 inclusive.

conf_intervallist, optional

Sequence of confidence intervals to compute, which must be between 0 and 100 inclusive.

displacement_unitsstr, optional

Displacement units. Default is ‘m’.

figPlotly graph_objects.Figure()

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.Figure()

The figure object with the plot.

plot_3d(percentile=[], conf_interval=[], displacement_units='m', rotor_length_units='m', fig=None, **kwargs)

Plot orbit response (3D).

This function plots orbits for each node on the rotor system in a 3D view.

Parameters:

percentilelist, optional

Sequence of percentiles to compute, which must be between 0 and 100 inclusive.

conf_intervallist, optional

Sequence of confidence intervals to compute, which must be between 0 and 100 inclusive.

displacement_unitsstr

Displacement units. Default is ‘m’.

rotor_length_unitsstr

Rotor Length units. Default is ‘m’.

figPlotly graph_objects.Figure()

The figure object with the plot.

kwargsoptional

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

Returns:

figPlotly graph_objects.Figure()

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 or .json file.

This function will save the simulation results to a .toml or .json 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. The format is determined by the file extension (.toml or .json).

Examples

>>> # Example running a stochastic unbalance response
>>> from tempfile import tempdir
>>> from pathlib import Path
>>> import ross.stochastic as srs

>>> # Running an example
>>> rotors = srs.st_rotor_example()
>>> freq_range = np.linspace(0, 500, 31)
>>> n = 3
>>> m = np.random.uniform(0.001, 0.002, 10)
>>> p = 0.0
>>> results = rotors.run_unbalance_response(n, m, p, freq_range)

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