Python数组中的零值到nan值

Question

我有一个包含一些零值的数组，我希望将其转换为 nan 值。当我应用代码时
所有的值都变成了 nan

myarray
array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       ..., 
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.]])

myarray.shape
(64L, 52L)
myarray.max()
4563.666015625
myarray.min()
0.0

我希望在 nan 中转换零值。我使用来自stackoverflow的示例

a = np.arange(3.0)
a
array([ 0.,  1.,  2.])
a[a==0] = np.nan
a
array([ nan,   1.,   2.])

当我将示例应用到我的数组时，所有值都变成了 nan

myarray[myarray == 0.] = nan
myarray
array([[ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       ..., 
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan]])

myarray.max()
nan
myarray.min()
nan

Answer 1

并不是所有的值都变成nan，而是（1）你只看那些做的部分，（2）min和max不能很好地与nan一起工作秒。

例如，如果我们制作一个类似于您的数组：

>>> myarray = np.zeros((64, 52))
>>> myarray[3:-3,3:-3] = np.random.uniform(0, 5000, (64-6,52-6))
>>> myarray
array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       ..., 
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.]])
>>> myarray[myarray==0] = np.nan
>>> myarray
array([[ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       ..., 
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan]])

它可能看起来都是nan，但实际上并非如此：

>>> myarray[2:5, 2:5]
array([[           nan,            nan,            nan],
       [           nan,  1500.05326562,  4583.70521213],
       [           nan,  4896.62420284,   892.83210033]])

你也可以使用nanmin和nanmax，忽略nans：

>>> myarray.min()
nan
>>> myarray.max()
nan
>>> np.nanmin(myarray)
0.60474162939361253
>>> np.nanmax(myarray)
4996.8967777356092