chx_generic_functions.py 文件源码

def get_echos(dat_arr,min_distance=10):
    """
    getting local maxima and minima from 1D data -> e.g. speckle echos
    strategy: using peak_local_max (from skimage) with min_distance parameter to find well defined local maxima
    using np.argmin to find absolute minima between relative maxima
    returns [max_ind,min_ind] -> lists of indices corresponding to local maxima/minima
    by LW 10/23/2018
    """
    from skimage.feature import peak_local_max
    max_ind=peak_local_max(dat_arr, min_distance)   # !!! careful, skimage function reverses the order (wtf?)
    min_ind=[]
    for i in range(len(max_ind[:-1])):
        min_ind.append(max_ind[i+1][0]+np.argmin(dat_arr[max_ind[i+1][0]:max_ind[i][0]]))
    #unfortunately, skimage function fu$$s up the format: max_ind is an array of a list of lists...fix this:
    mmax_ind=[]
    for l in max_ind:
        mmax_ind.append(l[0])
    #return [mmax_ind,min_ind]
    return [list(reversed(mmax_ind)),list(reversed(min_ind))]