rose.post_processing package

Submodules

rose.post_processing.plot_profile module

rose.post_processing.plot_profile.compute_cumulative_distance(coords)

computes cumulative distance of the track

Parameters:

coords – array of sorted coordinates

Returns:

rose.post_processing.plot_profile.compute_distance(coord_1, coord_2)
rose.post_processing.plot_profile.find_nearest(array, value)
rose.post_processing.plot_profile.plot_profile(data_list: list, time: float, data_type: list, fct: float = 1.96, xlabel: str = 'Distance [km]', ylabel: str = 'Value [-]', xlim: list = None, ylim: list = None, output_file: str = './result.png', are_coords_inverted: bool = True) → None
Parameters:

  • label –

  • data_list –

  • time –

  • data_type –

  • fct –

  • xlabel –

  • ylabel –

  • xlim –

  • ylim –

  • output_file –

Returns:

rose.post_processing.plot_profile.weighted_avg_and_std(values: ndarray, weights: ndarray) → List[ndarray]

Return the weighted average and standard deviation.

Parameters:

  • values – data values

  • weights – weights of the data values

Returns:

mean, standard deviation

rose.post_processing.plot_utils module

rose.post_processing.plot_utils.create_animation(filename, x_data: ~typing.Tuple | ~numpy.array, y_data: ~typing.Tuple | ~numpy.array, format='html', fps=60, fig: ~matplotlib.figure.Figure = <Figure size 640x480 with 0 Axes>, **kwargs)

Creates an animation of y data vs xdata

Parameters:

  • filename – name of the animation file

  • x_data – tuple of multiple x_data np arrays or 1 np.array of x_data

  • y_data – tuple of multiple y_data np arrays or 1 np.array of y_data

  • format – video format

  • fps – frames per second

  • fig – existing figure with custom axis information or data

  • kwargs – Line2d properties

Returns:

rose.post_processing.plot_utils.plot_2d_geometry(elements)

Module contents