IndexError: 数组的索引太多

我知道有很多这样的线程，但是所有这些线程都是针对非常简单的情况，比如3x3矩阵之类的东西，解决方案甚至不适用于我的情况。所以我试图把 G 和 L1(不是11，而是 L1)画成图。数据在我从 Excel 文件加载的文件中。Excel 文件是14x250，因此有14个参数，每个参数有250个数据点。我还有另外一个用户(对休 · 博思韦尔大声呼喊!)帮助我解决代码中的一个错误，但是现在又出现了一个错误。

下面是我们讨论的代码:

# format for CSV file:
header = ['l1', 'l2', 'l3', 'l4', 'l5', 'EI',
'S', 'P_right', 'P1_0', 'P3_0',
'w_left', 'w_right', 'G_left', 'G_right']


def loadfile(filename, skip=None, *args):
skip = set(skip or [])
with open(filename, *args) as f:
cr = csv.reader(f, quoting=csv.QUOTE_NONNUMERIC)
return np.array(row for i,row in enumerate(cr) if i not in skip)
#plot data
outputs_l1 = [loadfile('C:\\Users\\Chris\\Desktop\\Work\\Python Stuff\\BPCROOM - Shingles analysis\\ERR analysis\\l_1 analysis//BS(1) ERR analysis - l_1 - P_3 = {}.csv'.format(p)) for p in p3_arr]


col = {name:i for i,name in enumerate(header)}


fig = plt.figure()
for data,color in zip(outputs_l1, colors):
xs  = data[:, col["l1"     ]]
gl = data[:, col["G_left" ]] * 1000.0    # column 12
gr = data[:, col["G_right"]] * 1000.0    # column 13
plt.plot(xs, gl, color + "-", gr, color + "--")
for output, col in zip(outputs_l1, colors):
plt.plot(output[:,0], output[:,11]*1E3, col+'--')
plt.ticklabel_format(axis='both', style='plain', scilimits=(-1,1))
plt.xlabel('$l1 (m)$')
plt.ylabel('G $(J / m^2) * 10^{-3}$')
plt.xlim(xmin=.2)
plt.ylim(ymax=2, ymin=0)


plt.subplots_adjust(top=0.8, bottom=0.15, right=0.7)

运行完整个程序后，我收到了错误消息:

Traceback (most recent call last):
File "C:/Users/Chris/Desktop/Work/Python Stuff/New Stuff from Brenday 8 26 2014/CD_ssa_plot(2).py", line 115, in <module>
xs  = data[:, col["l1"     ]]
IndexError: too many indices for array

在我遇到这个问题之前，我还遇到了另一个问题，它涉及到上述错误消息所指的那行下面的几行:

Traceback (most recent call last): File "FILE", line 119, in <module>
gl = data[:, col["G_left" ]] * 1000.0 # column 12
IndexError: index 12 is out of bounds for axis 1 with size 12

我理解第一个错误，但是我在修复它时遇到了问题。不过，第二个错误让我感到困惑。我的老板真的在紧盯着我，所以任何帮助都会非常感激！

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小开

I think the problem is given in the error message, although it is not very easy to spot:

IndexError: too many indices for array
xs  = data[:, col["l1"     ]]

'Too many indices' means you've given too many index values. You've given 2 values as you're expecting data to be a 2D array. Numpy is complaining because data is not 2D (it's either 1D or None).

This is a bit of a guess - I wonder if one of the filenames you pass to loadfile() points to an empty file, or a badly formatted one? If so, you might get an array returned that is either 1D, or even empty (np.array(None) does not throw an Error, so you would never know...). If you want to guard against this failure, you can insert some error checking into your loadfile function.

I highly recommend in your for loop inserting:

print(data)

This will work in Python 2.x or 3.x and might reveal the source of the issue. You might well find it is only one value of your outputs_l1 list (i.e. one file) that is giving the issue.

小开

The message that you are getting is not for the default Exception of Python:

For a fresh python list, IndexError is thrown only on index not being in range (even docs say so). 

>>> l = []
>>> l[1]
IndexError: list index out of range

If we try passing multiple items to list, or some other value, we get the TypeError:

>>> l[1, 2]
TypeError: list indices must be integers, not tuple


>>> l[float('NaN')]
TypeError: list indices must be integers, not float

However, here, you seem to be using ABC0 that internally uses numpy for handling arrays. On digging deeper through the codebase for numpy, we see:

static NPY_INLINE npy_intp
unpack_tuple(PyTupleObject *index, PyObject **result, npy_intp result_n)
{
npy_intp n, i;
n = PyTuple_GET_SIZE(index);
if (n > result_n) {
PyErr_SetString(PyExc_IndexError,
"too many indices for array");
return -1;
}
for (i = 0; i < n; i++) {
result[i] = PyTuple_GET_ITEM(index, i);
Py_INCREF(result[i]);
}
return n;
}

where, the unpack method will throw an error if it the size of the index is greater than that of the results.

So, Unlike Python which raises a TypeError on incorrect Indexes, Numpy raises the IndexError because it supports multidimensional arrays.

小开

Before transforming the data into a list, I transformed the data into a list

data = list(data) data = np.array(data)


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