6. Plotting

class Plotting

Bases: object

WORK IN PROGRESS

Holds many methods for plotting data in Scarabaeus.

Notes

Scarabaeus’ plotting library contains multiple color palettes. See below for the colors contained within each:

(Source code)

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Methods

apply_scale_to_axes([scale])	Method to apply logarithmic or linear scaling to the axes of the plots.
compare_state_errors_norm(solution2, ...[, ...])	Compares the state errors and sigma values of two solutions by plotting them together.
get_fig_handle(fig_handle[, show, save_dir, ...])	Get the figure handle from another class
plot_asteroid_3d([obj_file, scale_factor, ...])	Plot a 3D representation of an asteroid, either from an object file or a simple spherical mesh.
plot_compare_state_error_norm(...[, title, ...])	Plots state errors norm for multiple iterations on the same figure for comparison.
plot_covariance(P_bplane_parameters[, title])	Given a B-plane covariance, plot a graphical representation.
plot_covariance_est(n_sigma[, title, scale, ...])	Plots the covariance history.
plot_gs_visibility(visibility_windows[, ...])	Method to plot when the spacecraft can be seen by a set of ground stations
plot_measurement_availability(...[, scale, ...])	Plots the availability of each measurement over time with x-axis labels as 'time - t_0' in integer days, where t_0 is the last time in combined_times.
plot_measurements_dataset(measurement_data)	Method to plot the radiometric measurements as function of time.
plot_media_coverage([type])	Plot DSN coverage intervals (in Ephemeris Time) from a media correction JSON file.
plot_multiple_covariance(sc_states, ...[, ...])	Plot multiple covariances corresponding to different spacecraft positions and their covariances in the B-plane.
plot_multiple_orbits_3d(positions_list[, ...])	Method for plotting multiple 3D trajectories, with default view as XY-plane.
plot_opnav_measurements(opnav_measurements)	Method to plot opnav measurements as function of time.
plot_orbit_3d(positions[, title, origin, ...])	Method for plotting a single 3D trajectory
plot_parameters_errors(true_trajectory, ...)	Plots the state errors and sigma bounds for each component of parameters.
plot_parameters_errors_norm(true_trajectory, ...)	Plots the state errors and sigma bounds for each component of parameters.
plot_parameters_estimate(epochs, n_sigma[, ...])	Plots the estimated parameters over time with error bars and shaded uncertainty bounds (±nσ).
plot_position_velocity(data[, times, title, ...])	Method to plot the position-velocity as function of time.
plot_postfits_asynchronous(dataset_names, ...)	Plots the postfit residuals for various measurements (e.g., range, range rate, OpNav u, OpNav v) dynamically based on dataset names.
plot_postfits_asynchronous_with_hist(...[, ...])	Plots postfit residuals with histograms for various measurement types.
plot_postfits_histogram(epochs, dataset_names)	Plots the postfit residuals in a histogram for various measurements (e.g., range, range rate, OpNav u, OpNav v) dynamically based on dataset names.
plot_postfits_scatter(epochs, dataset_names)	Plots the postfit residuals in a scatter plot for various measurements (e.g., range, range rate, OpNav u, OpNav v) dynamically based on dataset names.
plot_prefit_residuals(n_sigma[, title, ...])	Plots the prefit residuals for range and range rate measurements.
plot_radiometric_measurements(...[, title, ...])	Method to plot the radiometric measurements as function of time.
plot_scenario_param([scale, x_offset_flag])	Plots the scenario paramters
plot_state_errors(true_trajectory, epochs, ...)	Plots the state errors and sigma bounds for each component of position and velocity.
plot_state_errors_norm(true_trajectory, ...)	Plots the state errors and sigma values over time.
plot_uv_measurements_over_time([scale, ...])	Plot u vs v measurements, colored by time, and add subplots of u and v pixels over time with a semilog y-axis for the time.
plot_with_x_offset([x_offset_flag])	Plot with an offset for x axis.
save_plot([save_dir, save_name, save_format])	Method to save Plotting figures.
set_custom_styling()	Method to seet custom styling for all plots within Plotting.
time_series_basic_line(time, data[, title, ...])	Method for plotting time series data on a line plot.
time_series_basic_scatter(time, data[, ...])	Method for plotting time series data on a scatter plot.

static get_fig_handle(fig_handle, show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None)

Get the figure handle from another class

Parameters:

• fig_handle (matplotlib plt.figure() object) – Figure handle generated outside the Plotting class

• show (bool) – Option to show plot. Defaults to False.

• save_dir (str) – Save directory. Defaults to None.

• save_name (str) – Figure saving name. Defaults to None.

• save_format (str) – Figure saving format. Can be “pickle” or “png”. Defaults to None.

static plot_asteroid_3d(obj_file=None, scale_factor=1.0, ax=None, radius=None, name='Asteroid')

Plot a 3D representation of an asteroid, either from an object file or a simple spherical mesh.

Parameters: - obj_file (str, optional): Path to the asteroid 3D model file (e.g., .obj). If not provided, a simple spherical mesh is plotted. - scale_factor (float): Scaling factor to adjust the size of the asteroid. Default is 1.0. - ax (matplotlib.axes._subplots.Axes3DSubplot, optional): 3D axes to plot the asteroid on. If not provided, a new figure is created. - radius (float, optional): Radius of the asteroid in kilometers if a simple spherical mesh is used. Default is None. - name (str, optional): Name of the asteroid to display in the legend. Default is “Asteroid”.

Returns: - ax: The 3D axes containing the plot.

Raises: - ValueError: If both obj_file and radius are None.

static plot_gs_visibility(visibility_windows: dict, title: str = 'Ground Station Visibility Windows', epoch_start: str = None, show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None, scale: str = 'linxy')

Method to plot when the spacecraft can be seen by a set of ground stations

Parameters:

• visibility_windows (dict) – dictionary of the GS visibilities

• epoch_start (str) – Starting epoch

• show (bool) – Option to show plot. Defaults to False.

• save_dir (str) – Save directory. Defaults to None.

• save_name (str) – Figure saving name. Defaults to None.

• save_format (str) – Figure saving format. Can be “pickle” or “png”. Defaults to None.

• scale (str) – Scaling option [‘logx’, ‘logy’, ‘logxy’, ‘linx’, ‘liny’, ‘linxy’]

static plot_measurements_dataset(measurement_data, title: str = None, show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None)

Method to plot the radiometric measurements as function of time.

static plot_multiple_orbits_3d(positions_list, labels=None, origin=None, title: str = '@Sun, J2000', units: str = 'km', show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None, line_styles=None, colors=None, markers=None, view_xy_plane: bool = True)

Method for plotting multiple 3D trajectories, with default view as XY-plane.

Parameters:

• positions_list (list) – list of several objects positions in X,Y,Z coordinates.

• labels (list) – list of several objects labels. Defaults to None.

• origin (np.array(,3)) – origin of the plot in X,Y,Z coordinates. Defaults to None.

• title (str) – Title of plot. Defaults to “Reference Frame: J2000”.

• units (str) – Units to use in the X,Y,Z labels. Defaults to “km”.

• show (bool) – Option to show plot. Defaults to False.

• save_dir (str) – Save directory. Defaults to None.

• save_name (str) – Figure saving name. Defaults to None.

• save_format (str) – Figure saving format. Defaults to None.

• line_styles (list) – List of line styles for each orbit. Defaults to solid lines.

• colors (list) – List of colors for each orbit. Defaults to default matplotlib colors.

• markers (list) – List of markers for each orbit. Defaults to None (no markers).

• view_xy_plane (bool) – Boolean to set the default view to XY-plane. Defaults to True.

Returns:

Matplotlib figure object.

static plot_opnav_measurements(opnav_measurements, title: str = 'Opnav Measurements', show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None, scale: str = 'linxy', x_offset_flag: bool = False)

Method to plot opnav measurements as function of time.

Parameters:

• opnav_measurements (list[EpochArray,np.array,ArrayWFrame]) – Dictionary of the measurement, generated from the MeasurementDataSet

• title (str) – Title of plot. Defaults to None.

• show (bool) – Option to show plot. Defaults to False.

• save_dir (str) – Save directory. Defaults to None.

• save_name (str) – Figure saving name. Defaults to None.

• save_format (str) – Figure saving format. Can be “pickle” or “png”. Defaults to None.

• scale (str) – Scaling option [‘logx’, ‘logy’, ‘logxy’, ‘linx’, ‘liny’, ‘linxy’]

• x_offset_flag (bool) – Offset value for X axis

static plot_orbit_3d(positions, title: str = '3D Trajectory', origin=None, units: str = 'km', show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None)

Method for plotting a single 3D trajectory

Parameters:

• positions (np.array(N,3)) – object position in X,Y,Z coordinates (no frame assuemd).

• origin (np.array(,3)) – origin of the plot in X,Y,Z coordinates (no frame assumed). Defaults to None.

• title (str) – Title of plot. Defaults to “3D Trajectory”.

• units (str) – Units to use in the X,Y,Z labels. Defaults to “km”.

• show (bool) – Option to show plot. Defaults to False.

• save_dir (str) – Save directory. Defaults to None.

• save_name (str) – Figure saving name. Defaults to None.

• save_format (str) – Figure saving format. Can be “pickle” or “png”. Defaults to None.

static plot_position_velocity(data, times=None, title: str = 'Pos-Vel', show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None, scale: str = 'linxy', x_offset_flag: bool = False)

Method to plot the position-velocity as function of time.

Parameters:

• data (np.array(n,6)) – Array of the state vector made by position and velocity

• times (np.array()) – Time values

• title (str) – Title of plot. Defaults to “Pos-Vel”.

• show (bool) – Option to show plot. Defaults to False.

• save_dir (str) – Save directory. Defaults to None.

• save_name (str) – Figure saving name. Defaults to None.

• save_format (str) – Figure saving format. Can be “pickle” or “png”. Defaults to None.

static plot_radiometric_measurements(radiometric_measurement, title: str = None, show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None, meas_name: str = 'meas_name', scale: str = 'linxy', x_offset_flag: bool = False)

Method to plot the radiometric measurements as function of time.

Parameters:

• radiometric_measurement (list[EpochArray,np.array,ArrayWFrame]) – Dictionary of the measurement, generated from the MeasurementDataSet

• title (str) – Title of plot. Defaults to None.

• show (bool) – Option to show plot. Defaults to False.

• save_dir (str) – Save directory. Defaults to None.

• save_name (str) – Figure saving name. Defaults to None.

• save_format (str) – Figure saving format. Can be “pickle” or “png”. Defaults to None.

• scale (str) – Scaling option [‘logx’, ‘logy’, ‘logxy’, ‘linx’, ‘liny’, ‘linxy’]

• x_offset_flag (bool) – Offset value for X axis

static set_custom_styling()

Method to seet custom styling for all plots within Plotting. ???NEED MORE HERE???

static time_series_basic_line(time, data, title: str = 'Line Plot', x_axis_label: str = 'Time', y_axis_label: str = 'Value', show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None, scale: str = 'linxy', x_offset_flag: bool = False)

Method for plotting time series data on a line plot.

Parameters:

• time (np.array()) – timestamps values

• data (np.array()) – data values

• title (str) – Title of plot. Defaults to “Line Plot”.

• x_axis_label (str) – X-axis label of plot. Defaults to “Time”.

• y_axis_label (str) – Y-axis label of plot. Defaults to “Value”.

• show (bool) – Option to show plot. Defaults to False.

• save_dir (str) – Save directory. Defaults to None.

• save_name (str) – Figure saving name. Defaults to None.

• save_format (str) – Figure saving format. Can be “pickle” or “png”. Defaults to None.

• scale (str) – Scaling option [‘logx’, ‘logy’, ‘logxy’, ‘linx’, ‘liny’, ‘linxy’]

• x_offset_flag (bool) – Offset value for X axis

static time_series_basic_scatter(time, data, title: str = 'Scatter Plot', x_axis_label: str = 'Time', y_axis_label: str = 'Value', show: bool = False, save_dir: str = None, save_name: str = None, save_format: str = None, scale: str = 'linxy', x_offset_flag: bool = False)

Method for plotting time series data on a scatter plot.

Parameters:

• time (np.array()) – timestamps values

• data (np.array()) – data values

• title (str) – Title of plot. Defaults to “Scatter Plot”.

• x_axis_label (str) – X-axis label of plot. Defaults to “Time”.

• y_axis_label (str) – Y-axis label of plot. Defaults to “Value”.

• show (bool) – Option to show plot. Defaults to False.

• save_dir (str) – Save directory. Defaults to None.

• save_name (str) – Figure saving name. Defaults to None.

• save_format (str) – Figure saving format. Can be “pickle” or “png”. Defaults to None.

• scale (str) – Scaling option [‘logx’, ‘logy’, ‘logxy’, ‘linx’, ‘liny’, ‘linxy’]

• x_offset_flag (bool) – Offset value for X axis

apply_scale_to_axes(scale='linxy')

Method to apply logarithmic or linear scaling to the axes of the plots.

Parameters:

• ax (Axes) – Matplotlib Axes Object

• scale (str) – The scaling option. - “logx” : log scale on x-axis, linear on y-axis - “logy” : log scale on y-axis, linear on x-axis - “logxy” : log scale on both axes - “linx” : linear scale on x-axis, linear on y-axis - “liny” : linear scale on y-axis, linear on x-axis - “linxy” : linear scale on both axes (default)

Returns:

The axis with applied scaling.

Return type:

Axes

compare_state_errors_norm(solution2, true_trajectory, epochs, n_sigma: int, labels: list[str] = ['w SNC', 'w/o SNC'], t_0: bool = True, use_smoothed: bool = True)

Compares the state errors and sigma values of two solutions by plotting them together.

Parameters:

• solution1 – The first SolutionOD object to compare.

• solution2 – The second SolutionOD object to compare.

• true_trajectory (Trajectory) – The true trajectory.

• epochs (EpochArray) – The array of epochs.

• n_sigma (int) – The number of standard deviations for sigma.

• labels (list[str]) – Labels for the solutions to be compared.

• t_0 (bool) – If True, convert the x-axis to time in days relative to the initial epoch.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed covariance.

Returns:

The figure object.

Return type:

Figure

plot_compare_state_error_norm(true_trajectory, epochs_list, n_sigma, title='State Error Comparison', labels=None, t_0=True, scale='linxy', x_offset_flag=False, use_smoothed=True)

Plots state errors norm for multiple iterations on the same figure for comparison.

Parameters:

• solutions (list) – List of SolutionOD objects.

• true_trajectory (Trajectory) – The true trajectory.

• epochs_list (list) – List of EpochArray objects, one for each solution.

• n_sigma (int) – The number of standard deviations for sigma.

• title (str) – Title of the plot.

• labels (list, optional) – Labels for the solutions (e.g., [‘IT1’, ‘IT2’, ‘IT3’]).

• t_0 (bool, optional) – If True, convert the x-axis to time in days relative to the initial epoch.

• scale (str, optional) – Scale type for plots.

• x_offset_flag (bool, optional) – If True, apply x-axis offset.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed covariance.

Returns:

Figure object.

Return type:

Figure

plot_covariance(P_bplane_parameters, title: str = 'B-plane Covariance')

Given a B-plane covariance, plot a graphical representation. It assumes no correlation between position in the B-plane and linearized time of flight.

Parameters:

• bplane (Bplane) – The Bplane Object

• P_bplane_parameters (ndarray) – The B-plane covariance matrix.

plot_covariance_est(n_sigma, title: str = 'Covariance History', scale: str = 'linxy', x_offset_flag: bool = False, use_smoothed: bool = True)

Plots the covariance history.

Parameters:

• solution_it (SolutionOD) – The SolutionOD object.

• n_sigma (int) – The number of standard deviations to plot.

• title (str) – Title of the plot.

• scale (str, optional) – Scale type for plots.

• x_offset_flag (bool, optional) – If True, apply x-axis offset.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed covariance.

Returns:

Matplotlib figure object.

Return type:

Figure

plot_measurement_availability(measurement_mask, measurement_names, scale: str = 'linxy', x_offset_flag: bool = False)

Plots the availability of each measurement over time with x-axis labels as ‘time - t_0’ in integer days, where t_0 is the last time in combined_times.

Args: - combined_times (np.ndarray): Array of combined unique epochs. - measurement_mask (np.ndarray): Mask array showing the availability of each measurement at each time. - measurement_names (list of str): List of names corresponding to each measurement type.

Parameters:

• scale (str) – Scaling option [‘logx’, ‘logy’, ‘logxy’, ‘linx’, ‘liny’, ‘linxy’]

• x_offset_flag (bool) – Offset value for X axis

plot_media_coverage(type: str = 'tropo')

Plot DSN coverage intervals (in Ephemeris Time) from a media correction JSON file.

This function is designed to handle both iono and tropo files, which share the same structure but differ in the top-level dictionary key (aux_iono or aux_tropo).

Parameters:

• json_path (str) – Path to the JSON file containing the media corrections (iono or tropo).

• type (str, optional) – Type of file to process, either ‘iono’ or ‘tropo’. The function will look for the corresponding key in the JSON (aux_iono or aux_tropo). Default is ‘tropo’.

• Structure (JSON)

• --------------

• aux_type (The expected JSON has the following fields under the block) –

  • “start_day” : list of strings, format ‘YY/MM/DD’

  • ”start_time” : list of strings, format ‘HH:MM[:SS[.fff]]’

  • ”end_day” : list of strings, same format as start_day

  • ”end_time” : list of strings, same format as start_time

  • ”dsn” : list of DSN identifiers (e.g., “C10”, “C40”, “C60”)

Notes

• In order to compute the CSP UTC day-time to ET conversion you need to use the csp_time_to_et method, which requires a leapsecond kernel to be provided in the script

Example

>>> plot_media_coverage("orex_2018_iono.json", type="iono")
>>> plot_media_coverage("orex_2018_tropo.json", type="tropo")

plot_multiple_covariance(sc_states, sc_covariances, labels=None, zoom_flag=True, ast_covariances=None, scale: str = 'linxy', x_offset_flag: bool = False)

Plot multiple covariances corresponding to different spacecraft positions and their covariances in the B-plane.

Parameters:

• bplane (Bplane) – The Bplane Object

• sc_states (list of ndarray) – List of relative spacecraft states (position and velocity in J2000) at different epochs.

• sc_covariances (list of ndarray) – List of covariance matrices for the spacecraft states in J2000.

• labels (list of str) – List of labels for each ellipse (optional).

• zoom_flag (bool) – Flag to indicate whether to apply zoom on the last ellipse and hide axes when zoomed.

• scale (str, optional) – Scale type for plots.

• x_offset_flag (bool, optional) – If True, apply x-axis offset.

Returns:

None

Return type:

None

plot_parameters_errors(true_trajectory: Trajectory, epochs: EpochArray, n_sigma: int, title: str = 'Parameters Errors', t_f: bool = True, use_smoothed: bool = True)

Plots the state errors and sigma bounds for each component of parameters. :returns: List of figures.

plot_parameters_errors_norm(true_trajectory: Trajectory, epochs: EpochArray, n_sigma: int, title: str = 'Parameters errors norm', t_0: bool = True, scale: str = 'linxy', x_offset_flag: bool = False, use_smoothed: bool = True)

Plots the state errors and sigma bounds for each component of parameters.

Parameters:

• solution_it (SolutionOD) – The SolutionOD object.

• true_trajectory (Trajectory) – The true trajectory of the object.

• epochs (EpochArray) – The array of epochs.

• n_sigma (int) – The number of standard deviations for the sigma bounds.

• title (str) – Title for the plot.

• t_0 (bool) – If True, convert the x-axis to time in days relative to the initial epoch.

• scale (str) – Scale type for plots.

• x_offset_flag (bool) – If True, apply x-axis offset.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed covariance.

Returns:

List of figure objects.

Return type:

list of Figure

plot_parameters_estimate(epochs: EpochArray, n_sigma: int, title='Parameters Errors', sample_points: int = 40, t_0: bool = True, use_smoothed: bool = True)

Plots the estimated parameters over time with error bars and shaded uncertainty bounds (±nσ). Only a sample of sample_points is plotted to reduce clutter.

Parameters:

• solution_it (SolutionOD) – The SolutionOD object.

• epochs (EpochArray) – The array of epochs.

• n_sigma (int) – The number of standard deviations for uncertainty bounds.

• title (str) – Title for the plot.

• sample_points (int) – Number of data points to sample for plotting.

• t_0 (bool) – If True, convert the x-axis to time in days relative to the initial epoch.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed covariance.

Returns:

List of figure objects.

Return type:

list of Figure

plot_postfits_asynchronous(dataset_names, n_sigma, title='Postfit Residuals Asynchronous', time_vectors=None, scale: str = 'linxy', x_offset_flag: bool = False, use_smoothed: bool = True)

Plots the postfit residuals for various measurements (e.g., range, range rate, OpNav u, OpNav v) dynamically based on dataset names. It handles residuals from any ground station (e.g., GS1, GS2) and groups them by measurement type. Datasets can have different lengths, and the x-axis will represent either the time vector or the number of measurements if no time vector is provided.

Parameters:

• solution_it (SolutionOD) – The SolutionOD object.

• dataset_names (list) – List of dataset names.

• n_sigma (float) – Number of standard deviations for the sigma lines.

• title (str) – Title of the plot.

• time_vectors (list, optional) – List of time vectors for each measurement type. If only one time vector is provided, it will be used for all measurement types. If not provided, the x-axis will represent the number of measurements.

• scale (str, optional) – Scale type for plots.

• x_offset_flag (bool, optional) – If True, apply x-axis offset.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed postfits.

plot_postfits_asynchronous_with_hist(dataset_names, n_sigma=3, title='', time_vectors=None, scale='linxy', x_offset_flag=False, plot_sigmas=False, iter_num=None, use_smoothed=True)

Plots postfit residuals with histograms for various measurement types.

Parameters:

• solution_it (SolutionOD) – The SolutionOD object.

• dataset_names (list) – List of dataset names.

• n_sigma (int) – Number of standard deviations for the sigma lines.

• title (str) – Title of the plot.

• time_vectors (list, optional) – List of time vectors for each measurement type.

• scale (str) – Scale type for plots.

• x_offset_flag (bool) – If True, apply x-axis offset.

• plot_sigmas (bool) – If True, plot sigma bounds.

• iter_num (int, optional) – Iteration number for file naming.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed postfits.

plot_postfits_histogram(epochs: EpochArray, dataset_names, n_sigma: int = 3, lasso_selection=False, log_scale: bool = True, x_offset_flag: bool = False, use_smoothed: bool = True)

Plots the postfit residuals in a histogram for various measurements (e.g., range, range rate, OpNav u, OpNav v) dynamically based on dataset names. It handles residuals from any ground station (e.g., GS1, GS2) and groups them by measurement type.

Parameters:

• solution_it (SolutionOD) – The SolutionOD object.

• epochs (EpochArray) – Array of epochs.

• dataset_names (list) – List of dataset names.

• n_sigma (int) – Number of standard deviations for the sigma lines.

• lasso_selection (bool) – To enable the lasso selection feature.

• log_scale (bool, optional) – If True, use absolute values for residuals.

• x_offset_flag (bool, optional) – If True, apply x-axis offset.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed postfits.

Returns:

Tuple of (cleaned_dict, list of figures).

Return type:

tuple(dict, list of Figure)

plot_postfits_scatter(epochs: EpochArray, dataset_names, n_sigma=3, lasso_selection=False, scale: str = 'linxy', x_offset_flag: bool = False, use_smoothed: bool = True)

Plots the postfit residuals in a scatter plot for various measurements (e.g., range, range rate, OpNav u, OpNav v) dynamically based on dataset names. It handles residuals from any ground station (e.g., GS1, GS2) and groups them by measurement type.

Parameters:

• solution_it (SolutionOD) – The SolutionOD object.

• epochs (EpochArray) – Array of epochs.

• dataset_names (list) – List of dataset names.

• n_sigma (float) – Number of standard deviations for the sigma lines.

• lasso_selection (bool) – To enable the lasso selection feature.

• scale (str, optional) – Scale type for plots.

• x_offset_flag (bool, optional) – If True, apply x-axis offset.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed postfits.

Returns:

Tuple of (cleaned_dict, list of figures).

Return type:

tuple(dict, list of Figure)

plot_prefit_residuals(n_sigma, title: str = 'Prefit Residuals', scale: str = 'linxy', x_offset_flag: bool = False)

Plots the prefit residuals for range and range rate measurements.

Parameters:

• filterOD (FilterOD) – The FilterOD object.

• n_sigma (float) – The number of standard deviations to use for the sigma bounds.

• scale (str, optional) – Scale type for plots.

• x_offset_flag (bool, optional) – If True, apply x-axis offset.

Returns:

None

Return type:

None

plot_scenario_param(scale: str = 'linxy', x_offset_flag: bool = False)

Plots the scenario paramters

Parameters:

• scenario (ScenarioSetup) – The ScenarioSetup object.

• title (str) – Title of the plot.

• scale (str, optional) – Scale type for plots.

• x_offset_flag (bool, optional) – If True, apply x-axis offset.

Returns:

None

Return type:

None

plot_state_errors(true_trajectory: Trajectory, epochs: EpochArray, n_sigma: int, title: str = 'State Errors', t_0: bool = True, scale: str = 'linxy', x_offset_flag: bool = False, use_smoothed: bool = True)

Plots the state errors and sigma bounds for each component of position and velocity.

Parameters:

• solution_it (SolutionOD) – Solution OD Object.

• true_trajectory (Trajectory) – The true trajectory of the object.

• epochs (EpochArray) – The array of epochs.

• n_sigma (int) – The number of standard deviations for the sigma bounds.

• title (str) – Title for the plot.

• t_0 (bool) – If True, convert the x-axis to time in days relative to the initial epoch.

• scale (str) – Scale type for axes (‘linxy’, ‘logxy’, etc.).

• x_offset_flag (bool) – If True, apply x-axis offset.

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed covariance.

Returns:

Figure object.

Return type:

fig

plot_state_errors_norm(true_trajectory: Trajectory, epochs: EpochArray, n_sigma: int, title: str = 'State Errors Norm', t_0: bool = True, scale: str = 'linxy', x_offset_flag: bool = False, use_smoothed: bool = True)

Plots the state errors and sigma values over time.

Parameters:

• solution_it (SolutionOD) – Solution OD Object.

• true_trajectory (Trajectory) – The true trajectory.

• epochs (EpochArray) – The array of epochs.

• n_sigma (int) – The number of standard deviations for sigma.

• title (str) – Title for the plot.

• t_0 (bool) – If True, convert the x-axis to time in days relative to the initial epoch.

• scale (str) – Scaling option [‘logx’, ‘logy’, ‘logxy’, ‘linx’, ‘liny’, ‘linxy’]

• x_offset_flag (bool) – Offset value for X axis

• use_smoothed (bool) – If True and smoothed solution is available, uses smoothed covariance.

Returns:

Figure object.

Return type:

fig

plot_uv_measurements_over_time(scale: str = 'linxy', x_offset_flag: bool = False)

Plot u vs v measurements, colored by time, and add subplots of u and v pixels over time with a semilog y-axis for the time.

Parameters: measurements (MeasurementDataSet): A dataset containing opnav measurements.

Parameters:

• scale (str) – Scaling option [‘logx’, ‘logy’, ‘logxy’, ‘linx’, ‘liny’, ‘linxy’]

• x_offset_flag (bool) – Offset value for X axis

plot_with_x_offset(x_offset_flag: bool = False)

Plot with an offset for x axis.

Parameters:

• values (list) – A list of values to adjust.

• x_offset_flag – The offset flag for X axis

:type x_offset_flag

Returns:

A new list with the offset applied to each value.

Return type:

list

save_plot(save_dir=None, save_name: str = 'default', save_format: str = 'png')

Method to save Plotting figures.

Parameters:

• fig_handle (???) –

  ???

• sav_dir (???, optional) – ???. Defaults to None.

• save_name (str, optional) – The name of the saved file. . Defaults to default.

• save_format (str, optional) – The desired format to save the figure as. Accepts 'png' or 'pickle'. Defaults to 'png'.

Return type:

None

color_palettes = {'colorblind_friendly_palette': ['#E69F00', '#56B4E9', '#009E73', '#F0E442', '#0072B2', '#D55E00', '#CC79A7'], 'cu_palette': ['#E4B542', '#000000'], 'cyanR_palette': ['#17BECF', '#D95F02'], 'matplot_default_palette': ['#1f77b4', '#ff7f0e', '#2ca02c', '#8c564b', '#9467bd', '#d62728', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'], 'scb_palette': ['#4067BE', '#15788c', '#E4B542', '#000000']}