7.2.4. tobac.themes.tobac_v1.wrapper

Wraps up methods in feature_dection, segmentation and tracking.

Functions

maketrack(field_in[, grid_spacing, …]) Identify features and link them into trajectories.
tracking_wrapper(field_in_features, …[, …])
Parameters:
  • field_in_features (iris.cube.Cube)
tobac.themes.tobac_v1.wrapper.maketrack(field_in, grid_spacing=None, time_spacing=None, target='maximum', v_max=None, d_max=None, memory=0, stubs=5, order=1, extrapolate=0, method_detection='threshold', position_threshold='center', sigma_threshold=0.5, n_erosion_threshold=0, threshold=1, min_num=0, min_distance=0, method_linking='random', cell_number_start=1, subnetwork_size=None, adaptive_stop=None, adaptive_step=None, return_intermediate=False)

Identify features and link them into trajectories.

field_in : iris.cube.Cube
2D input field tracking is performed on.
grid_spacing : float, optional
Grid spacing in input data. Default is None.
time_spacing : float, optional
Time resolution of input data. Default is None.
target : {‘maximum’, ‘minimum’}
Flag to determine if tracking is targetting minima or maxima in the data. Default is ‘maximum’.
v_max : float, optional
Speed at which features are allowed to move. Default is None.
d_max : optional
Default is None.
memory : int, optional

Number of timesteps for which objects can be missed by the algorithm to still give a constistent track. Default is 0.

..warning :: This parameter should be used with caution, as it
can lead to erroneous trajectory linking, espacially for data with low time resolution.
stubs : float, optional
Default is 5.
order : int, optional
Order if interpolation spline to fill gaps in tracking (from allowing memory to be larger than 0).
method_detection: {‘threshold’, ‘threshold_multi’}
Flag choosing method used for feature detection. Default is ‘threshold’.
position_threshold : {‘center’, ‘extreme’, ‘weighted_diff’,
‘weighted_abs’}, optional

Flag choosing method used for the position of the tracked feature. Default is ‘center’.

sigma_threshold: float, optional
Standard deviation for intial filtering step. Default is 0.5.
n_erosion_threshold: int, optional
Number of pixel by which to erode the identified features. Default is 0.
min_num : int, optional
Minimum number of cells above threshold in the feature to be tracked. Default is 0.
min_distance : float, optional
Minimum distance between detected features. Default is 0.
method_linking : {‘random’, ‘predict’}, optional
Flag choosing method used for trajectory linking. Default is ‘random’.
cell_number_start : int, optional
Default is 1.
adaptive_step : optional
Default is None.
adaptive_stop : optional
Default is None.
subnetwork_size : int, optional
Maximim size of subnetwork for linking. Default is None.
return_intermediate: bool, optional
Flag to determine if only final tracjectories are output (False, default) or if detected features, filtered features and unfilled tracks are returned additionally (True).
trajectories_final: pandas.DataFrame
Tracked updrafts, one row per timestep and updraft, includes dimensions ‘time’, ‘latitude’, ‘longitude’, ‘projection_x_variable’, ‘projection_y_variable’ based on w cube. ‘hdim_1’ and ‘hdim_2’ are used for segementation step.

features : pandas.DataFrame

ValueError

If input_cube does not contail projection_x_coord and projection_y_coord or keyword argument grid_spacing.

If method_detection is neither ‘threshold’ nor ‘threshold_multi’.

features needs more information

Optional output: features_filtered: pandas.DataFrame

features_unfiltered: pandas.DataFrame

trajectories_filtered_unfilled: pandas.DataFrame

tobac.themes.tobac_v1.wrapper.tracking_wrapper(field_in_features, field_in_segmentation, time_spacing=None, grid_spacing=None, parameters_features=None, parameters_tracking=None, parameters_segmentation=None)
Parameters:
  • field_in_features (iris.cube.Cube)
  • field_in_segmentation (iris.cube.Cube)
  • grid_spacing (float, optional) – Grid spacing in input data. Default is None.
  • time_spacing (float, optional) – Time resolution of input data. Default is None.
  • parameters_features (optional) – Default is None.
  • parameters_tracking (optional) – Default is None.
  • parameters_segmentation (optional) – Default is None.
Raises:

ValueError – If method_detection is neither ‘threshold’ nor ‘threshold_multi’.

If method_linking is not ‘trackpy’.

Notes

needs short summary unsure about field_in_features, field_in_segmentation and parameters_*