我正在关注如何在 Python 中处理多精度算术的教程。
最后，我想要一个numpy具有任意高精度浮点数的数组，我需要对该矩阵求逆。
因此我们有：
import sys
import numpy as np
import gmpy2
print(sys.version)
print(np.__version__)
print(gmpy2.version)
3.6.10 | packaged by conda-forge | (default, Apr 24 2020, 16:27:41)
[GCC Clang 9.0.1 ]
1.12.1
<built-in function version>
其次是数据生成：
A = np.ones((3,3));
B = A/gmpy2.mpfr("1.0")
print(A)
print(B)
[[ 1. 1. 1.]
[ 1. 1. 1.]
[ 1. 1. 1.]]
[[mpfr('1.0') mpfr('1.0') mpfr('1.0')]
[mpfr('1.0') mpfr('1.0') mpfr('1.0')]
[mpfr('1.0') mpfr('1.0') mpfr('1.0')]]
和有问题的部分：
print(np.linalg.pinv(B))
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-23-3a70ff54e53d> in <module>
----> 1 print(np.linalg.pinv(B))
~/conda-envs/Python_Jupyter/env/lib/python3.6/site-packages/numpy/linalg/linalg.py in pinv(a, rcond)
1660 _assertNoEmpty2d(a)
1661 a = a.conjugate()
-> 1662 u, s, vt = svd(a, 0)
1663 m = u.shape[0]
1664 n = vt.shape[1]
~/conda-envs/Python_Jupyter/env/lib/python3.6/site-packages/numpy/linalg/linalg.py in svd(a, full_matrices, compute_uv)
1402
1403 signature = 'D->DdD' if isComplexType(t) else 'd->ddd'
-> 1404 u, s, vt = gufunc(a, signature=signature, extobj=extobj)
1405 u = u.astype(result_t, copy=False)
1406 s = s.astype(_realType(result_t), copy=False)
TypeError: No loop matching the specified signature and casting
was found for ufunc svd_n_s
有人知道如何实现我正在努力的目标吗？