Numpy 查找窗口数组中的最大元组

Question

我从元组列表开始（每个元组都是一个（X，Y））。我的最终结果是我想使用 numpy 找到长度为 4 的每个窗口/bin 内的最大 Y 值。

# List of tuples

[(0.05807200929152149, 9.9720125), (0.34843205574912894, 1.1142874), (0.6387921022067363, 2.0234027), (0.9291521486643438, 1.4435122), (1.207897793263647, 2.3677678), (1.4982578397212543, 1.9457655), (1.7886178861788617, 2.8343441), (2.078977932636469, 5.7816567), ...]

# Convert to numpy array

dt = np.dtype('float,float')

arr = np.asarray(listTuples, dt)

# [(0.05807201, 9.97201252) (0.34843206, 1.11428738)

#  (0.6387921 , 2.02340269) (0.92915215, 1.4435122 )

#  (1.20789779, 2.36776781) (1.49825784, 1.9457655 )

#  (1.78861789, 2.83434415) (2.07897793, 5.78165674)

#  (2.36933798, 3.14842606) ...]

#Create windows/blocks of 4 elements

arr = arr.reshape(-1,4)

# [[(0.05807201, 9.97201252) (0.34843206, 1.11428738)

#   (0.6387921 , 2.02340269) (0.92915215, 1.4435122 )]

#  [(1.20789779, 2.36776781) (1.49825784, 1.9457655 )

#   (1.78861789, 2.83434415) (2.07897793, 5.78165674)]

#  [(2.36933798, 3.14842606) (2.95005807, 2.10357308)

#   (3.24041812, 1.15985966) (3.51916376, 2.03056955)]...]

print(arr.max(axis=1)) <-- ERROR HERE

print(max(arr,key=lambda x:x[1])) <-- ERROR, tried this too but doesn't work

我想要使用最大 y 值从每个窗口/块获得的预期输出如下。或者，格式可以是常规元组列表，并不严格需要是 numpy 数组：

[[(0.05807201, 9.97201252)]

[(2.07897793, 5.78165674)]

[(2.36933798, 3.14842606)]...]

OR other format:

[(0.05807201, 9.97201252),(2.07897793, 5.78165674),(2.36933798, 3.14842606)]...]

Answer 1

这是一种矢量化（可能是最快的）方法：arr = np.asarray(listTuples, np.dtype('float,float'))idx = arr.view(('float',2))[:,1].reshape(-1,4).argmax(1)arr = arr.reshape(-1,4)[np.arange(len(idx)),idx]#[(0.05807201, 9.9720125) (2.07897793, 5.7816567) ...]您基本上使用结构化数组的数组（非结构化）版本，并view沿 查找 Y 的 argmax axis=1。然后使用这些索引来过滤原始数组中的元组arr。

Answer 2

这应该可以解决你的问题。输入：元组列表输出：元组列表，取每个 4 个元素块中 y 值最大的元组 import numpy as np# List of tupleslistTuples = [(1,1),(120,1000),(12,90),(1,1),(0.05807200929152149, 9.9720125),&nbsp;(0.34843205574912894, 1.1142874), (0.6387921022067363, 2.0234027),&nbsp;(0.9291521486643438, 1.4435122), (1.207897793263647, 2.3677678),&nbsp;(1.4982578397212543, 1.9457655), (1.7886178861788617, 2.8343441),&nbsp;(2.078977932636469, 5.7816567)]def extractMaxY(li):&nbsp; &nbsp; result = []&nbsp; &nbsp; index = 0&nbsp; &nbsp; for i in range(0,len(li), 4):&nbsp; &nbsp; &nbsp; &nbsp; max = -100000#find the max Y in blocks of 4&nbsp; &nbsp; &nbsp; &nbsp; for j in range(4):&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; if li[i+j][1] > max:&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; max = li[i+j][1]&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; index = i+j&nbsp; &nbsp; &nbsp; &nbsp; result.append(li[index])&nbsp; &nbsp; return resultprint(extractMaxY(listTuples))然后输出是[(120, 1000), (0.05807200929152149, 9.9720125), (2.078977932636469,&nbsp;5.7816567)]应该如此，对吗？

Answer 3

你可以试试这个import numpy as npans = []for value, comp in zip(x, np.max(x, axis=1)[:,1]):&nbsp; &nbsp; ans.append([(i, j) for i, j in value if np.isclose(j,comp)])print(np.array(ans))将其应用于您的数据x =&nbsp; np.array([[(0.05807201, 9.97201252), (0.34843206, 1.11428738),&nbsp; (0.6387921 , 2.02340269), (0.92915215, 1.4435122 )],&nbsp;[(1.20789779, 2.36776781), (1.49825784, 1.9457655 ),&nbsp; (1.78861789, 2.83434415), (2.07897793, 5.78165674)],&nbsp;[(2.36933798, 3.14842606), (2.95005807, 2.10357308),&nbsp; (3.24041812, 1.15985966), (3.51916376, 2.03056955)]])退货[[[ 0.05807201&nbsp; 9.97201252]]&nbsp;[[ 2.07897793&nbsp; 5.78165674]]&nbsp;[[ 2.36933798&nbsp; 3.14842606]]]