你可以尝试下面的代码，根据你的高度给出的间隔来细分你的y数组（注意，你的高度数组需要排序）

import numpy as np

heights = np.array([0,4,8,12,20,30])

y = np.array([1,25,30,7,12])

def subdivise(arr,heights):
    # np.digitize will assign each item in arr to its corresponding interval in heights
    # the right = True is to include the right border of the intervals ( heights[i-1] < x <= heights[i])
    intervals = np.digitize(arr,heights,right=True)
    # The number of subdivisions is the number of the intervals given by the peaks
    subdivision = [[] for _ in range(intervals.max())]
    # assign each element in arr to its corresponding interval 
    for index,bin_pos in enumerate(intervals):
        subdivision[bin_pos - 1].append(arr[index])
    return subdivision

test = subdivise(y,heights)

# Reult from subdivise 
# [[1], [7], [12], [], [25, 30]]

UPDATE：用于未排序的高度，并在所有匹配的子数组中包含y的值

import random

def subdivise(arr,peak_heights):
    intervals = [(min(peak_heights[i],peak_heights[i + 1]),max(peak_heights[i],peak_heights[i + 1]))
            for i in range(len(peak_heights) - 1)]
    
    subarrays = [[] for _ in range(len(intervals))]

    for value in arr:
        for subarray_index,interval in enumerate(intervals):
            if value > interval[0] and value <= interval[1]:
                subarrays[subarray_index].append(value)
    
    return subarrays

### TEST 
peak_heights = [0.06,0.1,0.07,0.09,0.08]

y = [random.uniform(0,0.1) for _ in range(20)]
print(subdivise(y,peak_heights))