我正在尝试使用numba jit编写我的第一个函数,我有一个熊猫数据框,我需要对其进行遍历并找到每350个点的均方根,因为python的for循环非常慢,因此我决定尝试numba jit,代码是:
@jit(nopython=True)
def find_rms(data, length):
res = []
for i in range(length, len(data)):
interval = np.array(data[i-length:i])
interval =np.power(interval, 2)
sum = interval.sum()
resI = sum/length
resI = np.sqrt(res)
res.appennd(resI)
return res
mydf = np.array(df.iloc[:]['c0'], dtype=np.float64)
df.iloc[350:]['rms'] = find_rms(mydf, 350)
我在某处读取了需要指定数据类型的内容,因此我写了“ dtype = np.float64”,但仍然收到错误消息:
---------------------------------------------------------------------------
TypingError Traceback (most recent call last)
<ipython-input-39-4d388f72efdc> in <module>
----> 1 df.iloc[350:]['rms'] = find_rms(mydf, 350.0)
c:\users\1\appdata\local\programs\python\python35\lib\site-packages\numba\dispatcher.py in _compile_for_args(self, *args, **kws)
346 e.patch_message(msg)
347
--> 348 error_rewrite(e, 'typing')
349 except errors.UnsupportedError as e:
350 # Something unsupported is present in the user code, add help info
c:\users\1\appdata\local\programs\python\python35\lib\site-packages\numba\dispatcher.py in error_rewrite(e, issue_type)
313 raise e
314 else:
--> 315 reraise(type(e), e, None)
316
317 argtypes = []
c:\users\1\appdata\local\programs\python\python35\lib\site-packages\numba\six.py in reraise(tp, value, tb)
656 value = tp()
657 if value.__traceback__ is not tb:
--> 658 raise value.with_traceback(tb)
659 raise value
660
TypingError: Failed in nopython mode pipeline (step: nopython frontend)
Invalid use of Function(<built-in function array>) with argument(s) of type(s): (array(float64, 1d, C))
* parameterized
In definition 0:
TypingError: array(float64, 1d, C) not allowed in a homogeneous sequence
raised from c:\users\1\appdata\local\programs\python\python35\lib\site-packages\numba\typing\npydecl.py:463
In definition 1:
TypingError: array(float64, 1d, C) not allowed in a homogeneous sequence
raised from c:\users\1\appdata\local\programs\python\python35\lib\site-packages\numba\typing\npydecl.py:463
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: resolving callee type: Function(<built-in function array>)
[2] During: typing of call at <ipython-input-34-edd252715b2d> (5)
File "<ipython-input-34-edd252715b2d>", line 5:
def find_rms(data, length):
<source elided>
for i in range(length, len(data)):
interval = np.array(data[i-length:i])
^
This is not usually a problem with Numba itself but instead often caused by
the use of unsupported features or an issue in resolving types.
To see Python/NumPy features supported by the latest release of Numba visit:
http://numba.pydata.org/numba-doc/dev/reference/pysupported.html
and
http://numba.pydata.org/numba-doc/dev/reference/numpysupported.html
For more information about typing errors and how to debug them visit:
http://numba.pydata.org/numba-doc/latest/user/troubleshoot.html#my-code-doesn-t-compile
If you think your code should work with Numba, please report the error message
and traceback, along with a minimal reproducer at:
https://github.com/numba/numba/issues/new
有人知道是什么问题吗?
答案 0 :(得分:0)
您在 {
“product”: {
“id”: 6711230070957,
“variants”: [
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]
}
}
中有一个错字,而且我认为您在取平方根时也犯了一个错误(我认为 append
不是 resI
)。
除此之外,唯一的问题是 res
的初始化。 interval
不希望您将 numpy 数组传递给 numpy 数组。将 Numba
包裹在数组的切片周围没有任何帮助,python 根本不在乎您是否这样做,并且在 nopython 模式下像对待 np.array
一样对待代码确实关心并抛出错误。去掉那部分就解决了问题。
Numba