Question

我正在尝试将numpy.array的形状从形状（4,4）更改为形状（2,2,2,2）。我收到的错误是：

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

这使我认为我的形状是向后的，但经过检查却并非如此。

我有一个用户定义的函数，该函数使用np.reshape将数组重新整形为某个形状（如果还不是该形状）。我尝试消除用户定义的函数，仅使用np.reshape，但是它返回了相同的错误。我想念什么？

重塑功能：

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

我在哪里称呼此功能：


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)

在这种情况下，端口= 2，模式= 2。

S[f]是形状（4,4）的np.array：

[[ 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]]

为什么返回错误：

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

何时应将其从（4,4）重塑为（2,2,2,2）？

Answer 1

可以做到

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)

如果您需要存储结果，可以创建一个空列表，然后将重新排列的数组附加到该列表中。

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))

从错误的numpy形状重塑功能广播

1 个答案: