c6607119c25d0178245243ef3fdd3d176dd0d8f2,trackpy/linking/utils.py,,coords_from_df,#Any#Any#Any#,36

Before Change

    Empty frames will be returned as empty arrays of shape (0, ndim).
    ndim = len(pos_columns)
    grouped = iter(df.groupby(t_column))  // groupby sorts by default

    // get the first frame to learn first frame number
    cur_frame, frame = next(grouped)
    cur_frame = int(cur_frame)
    yield cur_frame, frame[pos_columns].values
    cur_frame += 1

    for frame_no, frame in grouped:
        frame_no = int(frame_no)
        while cur_frame < frame_no:
            yield cur_frame, np.empty((0, ndim))
            cur_frame += 1

        yield cur_frame, frame[pos_columns].values
        cur_frame += 1


def coords_from_df_iter(df_iter, pos_columns, t_column):
    A generator that returns ndarrays of coords from a generator of
    DataFrames. Also returns the first value of the t_column.
    ndim = len(pos_columns)

After Change

    // This implementation is much faster than using DataFrame.groupby.

    ndim = len(pos_columns)
    times = df[t_column].values
    pos = df[pos_columns].values

    idxs = np.argsort(times, kind="mergesort")  // i.e. stable
    times = times[idxs]
    pos = pos[idxs]

    unique_times, time_counts = np.unique(times, return_counts=True)
    pos_by_frame = np.split(pos, np.cumsum(time_counts)[:-1])

    idx = 0
    for time in range(unique_times[0], unique_times[-1] + 1):
        if time == unique_times[idx]:

Instances