bounds.py

def bounds(data, max_contiguous_na=5):
    # Returns the start and end indices of the longest
    # valid sequence, that is, containing up to a given
    # number of contiguous missing points
    
    # Gets the indices of the non-null points
    idxs = np.arange(len(data))[~np.isnan(data)]
    max_size = 0
    max_ini = 0
    size = 1
    ini = 0
    # Calculates the size of the gaps of missing data
    gaps = np.diff(idxs) - 1
    for i, v in enumerate(gaps):
        # If there's no gap, the size of valid data is increased by 1
        if v == 0:
            size += 1
        # If that's the long sequence of values containing tolerable 
        # gaps then updates max info
        if size > max_size:
            max_size = size
            max_ini = ini
        # If the gaps is larger than tolerable, resets size and init
        if v > max_contiguous_na:
            ini = i + 1
            size = 1
        # If the gap is tolerable, adds one to the size
        # (that means the next idx)
        elif v > 0:
            size += 1
    # Computes the end of the longest sequence
    max_end = max_ini + max_size
    # Returns the start and end indices of the longest sequence
    ini, end = idxs[max_ini], idxs[max_end-1] + 1
    return ini, end