应用将参数应用于 NDimage 标记数组的函数

Question

我有一个使用 scipy.ndimage 标记的数组，我想将每个元素乘以特定于其相应标签的因子。我以为我可以为此使用 ndimage.labeled_comprehension，但我似乎无法弄清楚如何将参数传递给函数。例如：

a = np.random.random(9).reshape(3,3)
lbls = np.repeat(np.arange(3),3).reshape(3,3)
ndx = np.arange(0,lbls.max()+1)
factors = np.random.randint(10,size=3)
>>> lbls
array([[0, 0, 0],
       [1, 1, 1],
       [2, 2, 2]])
>>> ndx
array([0, 1, 2])
>>> factors
array([5, 4, 8])
def fn(a, x):
    return a*x
>>> b = ndimage.labeled_comprehension(a, labels=lbls, index=ndx, func=fn, out_dtype=float, default=0)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/tgrant/anaconda/envs/python2/lib/python2.7/site-packages/scipy/ndimage/measurements.py", line 416, in labeled_comprehension
    do_map([input], temp)
  File "/Users/tgrant/anaconda/envs/python2/lib/python2.7/site-packages/scipy/ndimage/measurements.py", line 411, in do_map
    output[i] = func(*[inp[l:h] for inp in inputs])
TypeError: fn() takes exactly 2 arguments (1 given)

正如预期的那样，它给出了一个错误，因为fn()需要以某种方式输入factors它。labeled_comprehension能做到这一点吗？

Answer 1

索引成因子，然后简单地乘以图像数组 -

a*factors[lbls]

示例运行 -

In [483]: a    # image/data array
Out[483]: 
array([[ 0.10682998,  0.29631501,  0.08501469],
       [ 0.46944505,  0.88346229,  0.75672908],
       [ 0.11381292,  0.24096868,  0.86438641]])
In [484]: factors  # scaling factors
Out[484]: array([8, 1, 1])
In [485]: lbls  # labels
Out[485]: 
array([[0, 0, 0],
       [1, 1, 1],
       [2, 2, 2]])
In [486]: factors[lbls] # factors populated based on the labels
Out[486]: 
array([[8, 8, 8],
       [1, 1, 1],
       [1, 1, 1]])
In [487]: a*factors[lbls] # finally scale the image array
Out[487]: 
array([[ 0.85463981,  2.37052006,  0.68011752],
       [ 0.46944505,  0.88346229,  0.75672908],
       [ 0.11381292,  0.24096868,  0.86438641]])