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python - numpy: "array_like"对象的正式定义?

转载 作者:行者123 更新时间:2023-12-05 07:39:57 30 4
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在 numpy 中,许多对象的构造函数接受一个“array_like”作为第一个参数。是否有这样的对象的定义,作为抽象元类,或者方法的文档应该包含??

最佳答案

事实证明,从技术上讲,几乎任何东西都是类似数组的。 “类数组”更多的是说明如何解释输入,而不是限制输入的内容;如果参数被记录为类数组,NumPy 将尝试将其解释为数组。

除了the nearly tautological one 之外没有类似数组的正式定义。 -- 类数组是 np.array 可以转换为 ndarray 的任何 Python 对象。要超越这个,你需要研究 source code .

NPY_NO_EXPORT PyObject *
PyArray_FromAny(PyObject *op, PyArray_Descr *newtype, int min_depth,
int max_depth, int flags, PyObject *context)
{
/*
* This is the main code to make a NumPy array from a Python
* Object. It is called from many different places.
*/
PyArrayObject *arr = NULL, *ret;
PyArray_Descr *dtype = NULL;
int ndim = 0;
npy_intp dims[NPY_MAXDIMS];

/* Get either the array or its parameters if it isn't an array */
if (PyArray_GetArrayParamsFromObject(op, newtype,
0, &dtype,
&ndim, dims, &arr, context) < 0) {
Py_XDECREF(newtype);
return NULL;
}
...

特别有趣的是PyArray_GetArrayParamsFromObject ,其注释列举了 np.array 期望的对象类型:

NPY_NO_EXPORT int
PyArray_GetArrayParamsFromObject(PyObject *op,
PyArray_Descr *requested_dtype,
npy_bool writeable,
PyArray_Descr **out_dtype,
int *out_ndim, npy_intp *out_dims,
PyArrayObject **out_arr, PyObject *context)
{
PyObject *tmp;

/* If op is an array */

/* If op is a NumPy scalar */

/* If op is a Python scalar */

/* If op supports the PEP 3118 buffer interface */

/* If op supports the __array_struct__ or __array_interface__ interface */

/*
* If op supplies the __array__ function.
* The documentation says this should produce a copy, so
* we skip this method if writeable is true, because the intent
* of writeable is to modify the operand.
* XXX: If the implementation is wrong, and/or if actual
* usage requires this behave differently,
* this should be changed!
*/

/* Try to treat op as a list of lists */

/* Anything can be viewed as an object, unless it needs to be writeable */

}

所以通过研究源代码我们可以得出类数组是

关于python - numpy: "array_like"对象的正式定义?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/46650537/

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