numpy argmax,最大值小于某个数字

Question

我有一个numpy数组:

myArray
array([[ 1.    ,     nan,     nan,     nan,     nan],
       [ 1.    ,     nan,     nan,     nan,     nan],
       [ 0.63  ,  0.79  ,  1.    ,     nan,     nan],
       [ 0.25  ,  0.4   ,  0.64  ,  0.84  ,     nan]])

我需要为每一行找到最大值的列数,但最大值必须小于1.

在上面的数组中,第0行应该返回Nan.

第2行应返回1.

第3行应该返回3.

我不知道如何解决这个问题argmax.

Answer 1

这是一种方法np.where-

m = a < 1  # Mask of elems < 1 and non-NaNs

# Set NaNs and elems > 1 to global minimum values minus 1, 
# so that when used with argmax those would be ignored
idx0 = np.where(m, a,np.nanmin(a)-1).argmax(1)

# Look for rows with no non-NaN and < 1 elems and set those in o/p as NaNs
idx = np.where(m.any(1), idx0, np.nan)

样品运行 -

In [97]: a
Out[97]: 
array([[ 1.  ,   nan,   nan,   nan,   nan],
       [ 1.  ,   nan,   nan,   nan,   nan],
       [ 0.63,  0.79,  1.  ,   nan,   nan],
       [ 0.25,  0.4 ,  0.64,  0.84,   nan]])

In [98]: m = a < 1

In [99]: idx0 = np.where(m, a,np.nanmin(a)-1).argmax(1)

In [100]: idx0
Out[100]: array([0, 0, 1, 3])

In [101]: np.where(m.any(1), idx0, np.nan)
Out[101]: array([ nan,  nan,   1.,   3.])