fbbe3451b053efcfb7568c4594ff36b2bc2b2437,trackpy/preprocessing.py,,bandpass,#Any#Any#Any#Any#,38

Before Change

        else:
            threshold = 1/256.
    lshortfiltered = list(lshort)
    for i in xrange(image.ndim):
        if 2*lshortfiltered[i] > llong[i]:
            lshortfiltered[i] = 0
    settings = dict(mode="nearest", cval=0)
    axes = range(image.ndim)
    sizes = [x*2+1 for x in llong]
    boxcar = np.asarray(image) 

After Change

    
    lshort = validate_tuple(lshort, image.ndim)       
    llong = validate_tuple(llong, image.ndim)
    if np.any([x*2 >= y for (x, y) in zip(lshort,llong)]):
        raise ValueError("The smoothing length scale must be more" +
                          "than twice the noise length scale.")
    if threshold is None:

Instances