Index of element in NumPy array

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.

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.

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]),)