Question

我有一个简单的程序，我已粘贴在下面。我有一个问题，因为当我运行该程序时，我收到一个错误。这是我的错误：

Traceback (most recent call last):
  File "C:\Users\Anaconda3\lib\site-packages\pywt\_multilevel.py", line 90, in wavedec
    axes_shape = data.shape[axis]
IndexError: tuple index out of range

During handling of the above exception, another exception occurred:

python
Traceback (most recent call last):
  File "C:/Users/Main.py", line 10, in <module>
    tree = pywt.wavedec(data=record, wavelet='db2', level=5, mode='symmetric')
  File "C:\Users\Anaconda3\lib\site-packages\pywt\_multilevel.py", line 92, in wavedec
    raise ValueError("Axis greater than data dimensions")
ValueError: Axis greater than data dimensions

这是我的代码：

import wfdb
import pywt
import matplotlib.pyplot as plt

record = wfdb.rdsamp('230', sampto = 2000)
annotation = wfdb.rdann('230', 'atr', sampto = 2000)

wfdb.plotrec(record, annotation = annotation, title='Output record', timeunits = 'seconds')

tree = pywt.wavedec(data=record, wavelet='db2', level=5, mode='symmetric')
newTree = [tree[0], tree[1], tree[2], tree[3]*0, tree[4]*0, tree[5]*0]
recSignal = pywt.waverec(newTree, 'db2')

plt.plot(recSignal[:2000])

您认为可以在代码中进行哪些更改以使程序正常运行？

Answer 1

这是第90行的代码

def wavedec(data, wavelet, mode='symmetric', level=None, axis=-1):
    """
    Multilevel 1D Discrete Wavelet Transform of data.

    Parameters
    ----------
    data: array_like
        Input data
    wavelet : Wavelet object or name string
        Wavelet to use
    mode : str, optional
        Signal extension mode, see Modes (default: 'symmetric')
    level : int, optional
        Decomposition level (must be >= 0). If level is None (default) then it
        will be calculated using the ``dwt_max_level`` function.
    axis: int, optional
        Axis over which to compute the DWT. If not given, the
        last axis is used.

    Returns
    -------
    [cA_n, cD_n, cD_n-1, ..., cD2, cD1] : list
        Ordered list of coefficients arrays
        where `n` denotes the level of decomposition. The first element
        (`cA_n`) of the result is approximation coefficients array and the
        following elements (`cD_n` - `cD_1`) are details coefficients arrays.

    Examples
    --------
    >>> from pywt import wavedec
    >>> coeffs = wavedec([1,2,3,4,5,6,7,8], 'db1', level=2)
    >>> cA2, cD2, cD1 = coeffs
    >>> cD1
    array([-0.70710678, -0.70710678, -0.70710678, -0.70710678])
    >>> cD2
    array([-2., -2.])
    >>> cA2
    array([  5.,  13.])

    """
    data = np.asarray(data)

    if not isinstance(wavelet, Wavelet):
        wavelet = Wavelet(wavelet)

    try:
        axes_shape = data.shape[axis]
    except IndexError:
        raise ValueError("Axis greater than data dimensions")
    level = _check_level(axes_shape, wavelet.dec_len, level)

    coeffs_list = []

    a = data
    for i in range(level):
        a, d = dwt(a, wavelet, mode, axis)
        coeffs_list.append(d)

    coeffs_list.append(a)
    coeffs_list.reverse()

    return coeffs_list

“Axis大于数据维度” - Python

1 个答案: