Question

我遇到了问题。我在python中调用自构建函数。在函数中，我返回一个数组。我最好显示代码，因为它很难解释。这是代码：

=transpose(unique(query(A2:C,"Select B where A = "&F1&" Order by B Asc")))

所以x数据看起来像这样：

x = []
y = []

for seq, target in sequential_data:
    x.append(seq)
    y.append(target)

return np.array(x), y

y看起来像这样：

array([[-6.32800918e-01,  2.89825783e+00, -1.73310681e-01,
    -4.15661278e-01, -9.33079353e-02, -4.58912725e-01],
   [ 1.07589222e+00, -3.94481134e-01, -1.95411356e+00,
     3.33890284e-01,  8.47644383e-01,  3.54376319e+00],
   [-2.83976404e-02, -4.19161683e-01,  2.38210386e-01,
    -3.94514913e-01, -6.06152332e-01, -9.27321083e-01]]), array([[ 0.09504018, -0.12478065, -0.84749427, -0.41267553,  0.03296391,
    -0.31431189],
   [ 1.48297783,  0.45790544,  1.72273948,  0.71392208,  0.1164553 ,
     1.24876302],
   [-1.54352725,  0.06401262, -0.44148997, -0.36444495,  0.2416613 ,
    -0.6424675 ],
   [ 0.62600517, -0.36715788,  0.09876015, -0.30232469,  0.82585385,
    -0.96059436]])

此数据是函数返回的内容。所以我想做的就是为x数组分配一个变量名称，为y数组分配一个变量名称。我这样尝试过：

[0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 1.0]

输入具有正确的值，所以那不是问题。但是当我执行validation_x, validation_y = function(Input)时，它将返回0。validation_y也是如此。那我在做什么错了？

全功能：

len(validation_x)

全功能呼叫：

def preprocess_df(df):
    for i in df.values:
        prev_days.append([n for n in i[:-1]])
        if len(prev_days) == SEQ_LEN:
            sequential_data.append([np.array(prev_days), i[-1]])

    random.shuffle(sequential_data)

    buys = []
    sells = []

    for seq, target in sequential_data:
        if target == 0:
            sells.append([seq, target])
        elif target == 1:
            buys.append([seq, target])

    random.shuffle(buys)
    random.shuffle(sells)

    lower = min(len(buys), len(sells))


    buys = buys[:lower]
    sells = sells[:lower]


    sequential_data = buys+sells

    random.shuffle(sequential_data)

    x = []
    y = []

    for seq, target in sequential_data:
        x.append(seq)
        y.append(target)

    return np.array(x), y

变量：Validation_main_df

times = sorted(main_df.index.values)
last_5pct = times[-int(0.05*len(times))]

validation_main_df = main_df[(main_df.index >= last_5pct)]
main_df = main_df[(main_df.index < last_5pct)]

train_x, train_y = preprocess_df(main_df)
validation_x, validation_y = preprocess_df(validation_main_df)

print("train data: " + str(len(train_x)) + ", validation: " + str(len(validation_x)))

Answer 1

使用您提供的详细信息，我无法重现此问题：

import numpy as np


def function(sequential_data):

    x = []
    y = []

    for seq, target in sequential_data:
        x.append(seq)
        y.append(target)

    return np.array(x), y


Input = [[1, [1, 2, 3]], [2, [2, 3, 4]]]

validation_x, validation_y = function(Input)

print(len(validation_x))
print(len(validation_y))

输出

2
2

符合预期。

Python函数返回填充数组，但计数为0

1 个答案: