molgri.plotting.transition_plots
Plots of ITS, eigenvectors and eigenvalues of transition/rate matrix.
A collection of methods to visualise the SqRA or MSM objects.
Classes
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In the __init__, defaults should be set that will generally be used for an entire class of figures - but it is still possible to not use defaults for some of the plots. |
- class molgri.plotting.transition_plots.TransitionPlot(transition_obj: TransitionModel, *args, **kwargs)
In the __init__, defaults should be set that will generally be used for an entire class of figures - but it is still possible to not use defaults for some of the plots.
- Args:
data_name: keyword that combines all figures of a specific sub-class fig_path: folder to save figures if created, should be set in subclasses ani_path: folder to save animations if created, should be set in subclasses default_context: forwarded to sns.set_context -> should be one of: paper, notebook, talk, poster default_color_style: describes the general color scheme of the plots (dark, white) default_complexity_level: select from full, half_empty, empty
- __init__(transition_obj: TransitionModel, *args, **kwargs)
In the __init__, defaults should be set that will generally be used for an entire class of figures - but it is still possible to not use defaults for some of the plots.
- Args:
data_name: keyword that combines all figures of a specific sub-class fig_path: folder to save figures if created, should be set in subclasses ani_path: folder to save animations if created, should be set in subclasses default_context: forwarded to sns.set_context -> should be one of: paper, notebook, talk, poster default_color_style: describes the general color scheme of the plots (dark, white) default_complexity_level: select from full, half_empty, empty
- make_its_plot(fig=None, ax=None, save=True, num_eigenv=6, as_line=False)
Plot iterative timescales.
- make_eigenvalues_plot(fig=None, ax=None, save=True, num_eigenv=None)
Visualize the eigenvalues of rate matrix.
- make_eigenvectors_plot(ax=None, fig=None, save=True, num_eigenv: int = 5, projection='3d')
Visualize the energy surface and the first num (default=3) eigenvectors
- make_one_eigenvector_plot(eigenvec_index: int, ax=None, fig=None, save=True, projection='3d', animate_rot=False)