Oct 22, 2013 · def my_function(): my_array = np.array([1.,2.,3.]) my_variable = 99. return my_array,my_variable my_function() so that the values calculated in the function can be used later in the code? The above ignores the values calculated in the function. I tried returning a tuple {my_array, my_variable} but got the unhashable type message for np.array

Sep 9, 2019 · I'm trying to understand how to use functions properly. In this code, I want to return 2 arrays for pupil names and percentage scores. However I am unable to return the array variables from the first function. I've tried using different ways of defining the arrays (with and without brackets, both globally and locally)

Sep 19, 2018 · So, if you wanted the last element in array, you would call array[-1]. All your return c.most_common()[-1] statement does is call c.most_common and return the last value in the resulting list, which would give you the least common item in that list. Essentially, this line is equivalent to: temp = c.most_common() return temp[len(temp) - 1]

Nov 20, 2023 · When I try to return the array from the function instead of getting the newly appended array I just get an empty one []. I know the rest of the code works when it is all inside one function however I have been tasked with specifically defining the values outside the function and only appending inside the function.

Oct 11, 2016 · else: for i in range(0,n+1): formula=((x1)**(n-i))*((x2)**(i)) list.append(formula) return mapfeature_binominal_array(x1,x2,n-1,list) A recursive function call is just like any other function call; you still need to do something with the result of that function call; the value it returns does not automatically propagate to be the return value ...

For your first question, find the position of some value in a list x using index(), like so:. x.index(value) For your second question, to check for multiple same values you should split your list into chunks and use the same logic from above.

Feb 15, 2013 · The C++ function should return a pointer to an array. Unfortunately I haven't figured out, how to access the array in Python. I tried numpy.frombuffer, but that was not successful. It just returned an array of arbitrary numbers. Obviously I didn't used it correctly. Here is a simple example with an array of size 10: Content of function.cpp:

View the answers with numpy integration, numpy arrays are far more efficient than Python lists. If the list is short it's no problem making a copy of it from a Python list, if it isn't then perhaps you should consider storing the elements in numpy array in the first place. –

Note that numpy.where will not just return an array of the indices, but will instead return a tuple (the output of condition.nonzero()) containing arrays - in this case, (the array of indices you want,), so you'll need select_indices = np.where(...)[0] to get the result you want and expect. –

Dec 5, 2012 · X[np.array(a)>4]#X needs to be np.array as well Explanation: np.array converts a to an array. np.array(a)>4 gives a bool array with all the elements that should be kept. And X is filtered by the bool array so only the elements where a …