ValueError: data type <class 'numpy.object_'> not inexact ValueError: data type <class 'numpy.object_'> not inexact 这个错误通常发生在尝试使用需要精确数值数据类型的NumPy函数时,却传入了object类型的数组。这种类型通常出现在Pandas的DataFrame中,尤其是当DataFrame的列包含混合数据类型(如字符串和数...
build doc fail on main: data type <class 'numpy.object_'> not inexact#4474 #4475 2 examples are failing with the same error https://github.com/nilearn/nilearn/actions/runs/9667098813/job/26755326067#step:13:14419 ../examples/08_experimental/plot_surf_stat_map_experimental.py failed leaving ...
inexact): --> 382 raise ValueError("data type %r not inexact" % (dtype)) 383 obj = cls._finfo_cache.get(dtype, None) 384 if obj is not None: ValueError: data type <class 'numpy.object_'> not inexact 像这样的函数期望数值的dtype数组。先清理你的数据! 收藏分享票数3 EN 页面原文内容...
According to the standard, iinfo and finfo are supposed to accept an array (not just a type) for the first argument, but: import array_api_strict as xp xp.finfo(xp.asarray([1.])) # ValueError: data type <class 'numpy.object_'> not inexact xp.iinfo(xp.asarray([1])) # ...
StaticFrame uses NumPy types to define the columnar types of a Frame, or the values of a Series or Index. This permits narrowly specifying sized numerical types, such as np.uint8 or np.complex128; or broadly specifying categories of types, such as np.integer or np.inexact. As StaticFr...
xarray offers extremely flexible indexing routines that combine the best features of NumPy and pandas for data selection. The most basic way to access elements of a :py:class:`~xarray.DataArray` object is to use Python's [] syntax, such as array[i, j], where i and j are both integers...
The use of a superpixel-based scheme also impacts the prediction stage, where all the members of a segment are assigned the same class label. This proposal makes extensive use of the segment map to remove regions of the patches and later generate new pixel vectors through the application of ...