Utilities
- saspt.utils.track_length(detections: pandas.DataFrame) pandas.DataFrame
Add a new column to a detection-level DataFrame with the length of each trajectory in frames.
Example:
>>> from saspt import sample_detections >>> detections = sample_detections() >>> from saspt.utils import track_length # Calculate length of each trajectory in frames >>> detections = track_length(detections) >>> print(detections) y x frame trajectory track_length 0 575.730202 84.828673 0 13319 247 1 538.416604 485.924667 0 1562 13 2 107.647631 61.892363 0 363 3 3 151.893969 63.246361 0 992 8 4 538.737277 485.856905 1 1562 13 .. ... ... ... ... ... 491 365.801274 70.689108 296 14458 7 492 409.236744 10.312949 296 14375 1 493 366.475688 70.559735 297 14458 7 494 363.350134 67.585339 298 14458 7 495 360.006572 70.511980 299 14458 7 [496 rows x 5 columns] # All detections in each trajectory have the same track length >>> print(detections.groupby('trajectory')['track_length'].nunique()) trajectory 363 1 413 1 439 1 542 1 580 1 .. 14174 1 14324 1 14360 1 14375 1 14458 1 Name: track_length, Length: 100, dtype: int64 # Mean trajectory length is ~5 frames >>> print(detections.groupby('trajectory')['track_length'].first().mean()) 4.96
- Parameters
detections (pandas.DataFrame) –
- Returns
pandas.DataFrame, the input DataFrame with a new column track_length (
saspt.constants.TRACK_LENGTH)
- saspt.utils.assign_index_in_track(detections: pandas.DataFrame) pandas.DataFrame
Given a set of detections, determine the index of each detection in its respective trajectory.
Sorts the input.
- Parameters
detections (pandas.DataFrame) – input set of detections
- Returns
pandas.DataFrame, input with the index_in_track column
- saspt.utils.cartesian_product(*arrays: numpy.ndarray) numpy.ndarray
Take the Cartesian product of multiple 1D arrays.
- Parameters
arrays (numpy.ndarray) – one or more 1D arrays
- Returns
product (numpy.ndarray), 2D array. Each corresponds to a unique combination of the elements of arrays.