从错误的numpy形状重塑功能广播

Question

I am trying to reshape a numpy.array from shape (4,4) to shape (2,2,2,2). The error I am receiving is:

ValueError: could not broadcast input array from shape (2,2,2,2) into shape (4,4).

This makes me think I have the shapes backwards, but after checking that is not the case.

I have a user defined function that uses np.reshape to reshape an array to a certain shape if it is not already that shape. I have tried eliminating the user defined function and using only np.reshape, but it returned the same error. What am I missing?

The reshape function:

def reshape(matrix, ports, modes):
    shape = (ports, ports, modes, modes)
    if(np.shape(matrix) != shape): #reshape if necessary
        return np.reshape(matrix, shape)
    else:
        return matrix

Where I call this function:

def plot(S, F, ports, modes, x_range, y_range, title, f_units, 
         multi_modal = True):
    data = {} #create dictionary to store S-parameters
    if(not multi_modal): #if we want average
        for f in range(0, len(F)): #iterate through frequencies
            print(np.shape(S[f]))
            S[f] = reshape(S[f], ports, modes)

In this instance, ports = 2 and modes = 2.

S[f] is a np.array of shape (4,4):

[[ 1.00000000e+00+0.00000000e+00j -1.02728868e-19+1.64952184e-22j
  -1.37762998e-20+2.40441793e-24j -4.18063430e-24-1.18287261e-21j]
 [ 0.00000000e+00-0.00000000e+00j -1.00000000e+00+1.22464680e-16j
   3.03393173e-26-1.77961140e-24j  1.57277027e-25+2.06062998e-23j]
 [-1.95100984e-27+3.66506948e-24j  2.38762635e-25+1.48052807e-22j
   1.00000000e+00+0.00000000e+00j  2.90518731e-20+1.33913685e-17j]
 [-3.47614015e-25-4.08540212e-23j -3.30653510e-21+2.87402660e-23j
   1.77338192e-21+2.27000073e-19j -1.00000000e+00+1.22464680e-16j]]

Why is it returning the error:

ValueError: could not broadcast input array from shape (2,2,2,2) into shape (4,4)

when it should be reshaping from (4,4) to (2,2,2,2)?

Answer 1

This would do

def plot(S, F, ports, modes, x_range, y_range, title, f_units, 
         multi_modal = True):
    data = {} #create dictionary to store S-parameters
    if(not multi_modal): #if we want average
        for f in range(0, len(F)): #iterate through frequencies
            print(np.shape(S[f]))
            S_reshaped = reshape(S[f], ports, modes)

If you need to store your results you can create an empty list and then append the reshaped array to it.

def plot(S, F, ports, modes, x_range, y_range, title, f_units, 
         multi_modal = True):
    data = {} #create dictionary to store S-parameters
    S_reshaped=[]
    if(not multi_modal): #if we want average
        for f in range(0, len(F)): #iterate through frequencies
            print(np.shape(S[f]))
            S_reshaped.append(reshape(S[f], ports, modes))