imucal.ferraris_regions_from_interactive_plot#

imucal.ferraris_regions_from_interactive_plot(data: DataFrame, acc_cols: Iterable[str] = ('acc_x', 'acc_y', 'acc_z'), gyr_cols: Iterable[str] = ('gyr_x', 'gyr_y', 'gyr_z'), title: str | None = None, figsize=(20, 10)) → tuple[FerrarisSignalRegions, DataFrame][source]#

Create a Calibration object by selecting the individual signal sections manually in an interactive GUI.

This will open a Tkinter Window that allows you to label the start and the end all required sections for a Ferraris Calibration. See the class docstring for more detailed explanations of these sections.

Parameters:

data: 6 column dataframe (3 acc, 3 gyro)
acc_cols: The name of the 3 acceleration columns in order x,y,z.
gyr_cols: The name of the 3 acceleration columns in order x,y,z.
title: Optional title of the plot window
figsize: The initial size of the plot window. If you can not see the toolbar at the bottom, it might help to reduce the figure size.

Returns:

ferraris_cal_objFerrarisSignalRegions
section_listpd.DataFrame: Section list representing the start and stop of each section. It is advised to save this to disk to avoid repeated manual labeling. ferraris_regions_from_section_list can be used to recreate the regions object

See also

ferraris_regions_from_section_list
ferraris_regions_from_df

Examples

>>> sampling_rate = 100  # Hz
>>> data = ...  # my data as 6 col pandas dataframe
>>> # This will open an interactive plot, where you can select the start and the stop sample of each region
>>> regions, section_list = ferraris_regions_from_interactive_plot(
...     data, sampling_rate=sampling_rate
... )
>>> section_list.to_csv(
...     "./calibration_sections.csv"
... )  # This is optional, but recommended
>>> regions
FerrarisSignalRegions(x_a=array([...]), ..., z_rot=array([...]))