1

scipy.sparse.linalg モジュールの eigs 関数を使用していますが、一貫性のない結果が見つかりました。同じコードを 2 回実行すると、異なる結果が得られます。つまり、np.allclose の出力は False になります。その理由を説明できる人はいますか？

from scipy.sparse.linalg import eigs
from scipy.sparse import spdiags
import numpy as np


n1 = 100
x, dx = linspace(0, 2, n1, retstep=True)
e1 = ones(n1)
A = 1./(dx**2)*spdiags([e1, -2*e1, e1], [-1,0,1], n1, n1)

np.allclose(eigs(A, 90)[0], eigs(A, 90)[0])

IPython の例はここで見ることができます(申し訳ありませんが、IPython の出力を投稿する方法がわかりません)。

編集1：

@Kh40tiK で提案されているように、固有値をソートすることは問題ではありません。ここを参照してください。

編集2：

さまざまなバージョンの Scipy を試し、@Kh40tiK によって投稿されたスクリプトを scipy.show_config() への追加呼び出しで実行した後、MKL でコンパイルされた SciPy バージョンに問題があるようです。

MKL の場合:

2.7.6 |Anaconda 1.9.1 (64-bit)| (default, Jan 17 2014, 10:13:17) 
[GCC 4.1.2 20080704 (Red Hat 4.1.2-54)]
('numpy:', '1.8.1')
('scipy:', '0.13.3')
umfpack_info:
  NOT AVAILABLE
lapack_opt_info:
    libraries = ['mkl_lapack95_lp64', 'mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core',         'iomp5', 'pthread']
    library_dirs = ['/home/jpsilva/anaconda/lib']
    define_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/home/jpsilva/anaconda/include']
blas_opt_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/jpsilva/anaconda/lib']
    define_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/home/jpsilva/anaconda/include']
openblas_info:
  NOT AVAILABLE
lapack_mkl_info:
    libraries = ['mkl_lapack95_lp64', 'mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/jpsilva/anaconda/lib']
    define_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/home/jpsilva/anaconda/include']
blas_mkl_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/jpsilva/anaconda/lib']
    define_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/home/jpsilva/anaconda/include']
mkl_info:
    libraries = ['mkl_intel_lp64', 'mkl_intel_thread', 'mkl_core', 'iomp5', 'pthread']
    library_dirs = ['/home/jpsilva/anaconda/lib']
    efine_macros = [('SCIPY_MKL_H', None)]
    include_dirs = ['/home/jpsilva/anaconda/include']
False
False
False
False
False
False
False
False

MKL なし:

2.7.5+ (default, Feb 27 2014, 19:37:08) 
[GCC 4.8.1]
('numpy:', '1.8.1')
('scipy:', '0.13.3')
umfpack_info:
  NOT AVAILABLE
atlas_threads_info:
  NOT AVAILABLE
blas_opt_info:
    libraries = ['f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/atlas-base']
    define_macros = [('ATLAS_INFO', '"\\"3.10.1\\""')]
    language = c
    include_dirs = ['/usr/include/atlas']
atlas_blas_threads_info:
  NOT AVAILABLE
openblas_info:
  NOT AVAILABLE
lapack_opt_info:
    libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/atlas-base/atlas', '/usr/lib/atlas-base']
    define_macros = [('ATLAS_INFO', '"\\"3.10.1\\""')]
    language = f77
    include_dirs = ['/usr/include/atlas']
atlas_info:
    libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/atlas-base/atlas', '/usr/lib/atlas-base']
    define_macros = [('ATLAS_INFO', '"\\"3.10.1\\""')]
    language = f77
    include_dirs = ['/usr/include/atlas']
lapack_mkl_info:
  NOT AVAILABLE
blas_mkl_info:
  NOT AVAILABLE
atlas_blas_info:
    libraries = ['f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/atlas-base']
    define_macros = [('ATLAS_INFO', '"\\"3.10.1\\""')]
    language = c
    include_dirs = ['/usr/include/atlas']
mkl_info:
  NOT AVAILABLE
True
False
True
False
True
False
True
False
4

2 に答える 2