问题
In Python we can get the index of a value in an array by using .index(). How can I do it with a NumPy array?
When I try to do
decoding.index(i)
it says that the NumPy library doesn't support this function. Is there a way to do it?
回答1:
Use np.where
to get the indices where a given condition is True
.
Examples:
For a 2D np.ndarray
called a
:
i, j = np.where(a == value) # when comparing arrays of integers
i, j = np.where(np.isclose(a, value)) # when comparing floating-point arrays
For a 1D array:
i, = np.where(a == value) # integers
i, = np.where(np.isclose(a, value)) # floating-point
Note that this also works for conditions like >=
, <=
, !=
and so forth...
You can also create a subclass of np.ndarray
with an index()
method:
class myarray(np.ndarray):
def __new__(cls, *args, **kwargs):
return np.array(*args, **kwargs).view(myarray)
def index(self, value):
return np.where(self == value)
Testing:
a = myarray([1,2,3,4,4,4,5,6,4,4,4])
a.index(4)
#(array([ 3, 4, 5, 8, 9, 10]),)
回答2:
You can convert a numpy array to list and get its index .
for example:
tmp = [1,2,3,4,5] #python list
a = numpy.array(tmp) #numpy array
i = list(a).index(2) # i will return index of 2, which is 1
this is just what you wanted.
回答3:
I'm torn between these two ways of implementing an index of a NumPy array:
idx = list(classes).index(var)
idx = np.where(classes == var)
Both take the same number of characters, but the first method returns an int
instead of a numpy.ndarray
.
回答4:
This problem can be solved efficiently using the numpy_indexed library (disclaimer: I am its author); which was created to address problems of this type. npi.indices can be viewed as an n-dimensional generalisation of list.index. It will act on nd-arrays (along a specified axis); and also will look up multiple entries in a vectorized manner as opposed to a single item at a time.
a = np.random.rand(50, 60, 70)
i = np.random.randint(0, len(a), 40)
b = a[i]
import numpy_indexed as npi
assert all(i == npi.indices(a, b))
This solution has better time complexity (n log n at worst) than any of the previously posted answers, and is fully vectorized.
回答5:
You can use the function numpy.nonzero()
, or the nonzero()
method of an array
import numpy as np
A = np.array([[2,4],
[6,2]])
index= np.nonzero(A>1)
OR
(A>1).nonzero()
Output:
(array([0, 1]), array([1, 0]))
First array in output depicts the row index and second array depicts the corresponding column index.
回答6:
If you are interested in the indexes, the best choice is np.argsort(a)
a = np.random.randint(0, 100, 10)
sorted_idx = np.argsort(a)
来源:https://stackoverflow.com/questions/18079029/index-of-element-in-numpy-array