python - scipy bisplrep 段错误(核心转储)

Question

我已将问题隔离到一个案例中。这是代码:

import numpy as np
from scipy import interpolate

P = np.array([[-0.32617197, -0.2920095 , -0.46557174, -0.81794844, -1.29219631,-1.81947447, -2.32841281, -2.75178671, -3.03194729, -3.12576901,-3.00960991, -2.6846482 , -2.18283861, -1.57343334, -0.96880183,-0.52132021],[ 0.26979365,  0.21207852, -0.04285966, -0.44843864, -0.93769524,-1.43878605, -1.88334371, -2.21217161, -2.37976096, -2.35832431,-2.14170154, -1.74925879, -1.22957792, -0.66299164, -0.15978676,0.15787639],[ 0.88005791,  0.75688371,  0.45630493,  0.03749351, -0.42869796,-0.87313496, -1.2350965 , -1.46659168, -1.53565157, -1.42914945,-1.15533001, -0.74592665, -0.25731003,  0.230784  ,  0.62261907,0.83078598],[ 1.43941451,  1.27684403,  0.96136466,  0.55966746,  0.14141966,-0.23103704, -0.50731149, -0.65168608, -0.64504881, -0.48640796,-0.19400188,  0.19429156,  0.62197232,  1.017876  ,  1.30628307,1.4313914 ],[ 1.88963563,  1.71157922,  1.40653829,  1.04395233,  0.68826473,0.39234334,  0.19511948,  0.12049842,  0.17675042,  0.35620331,0.63536282,  0.97584839,  1.32687424,  1.6305647 ,  1.83245472,1.90239222],[ 2.18411701,  2.01162102,  1.73714652,  1.42853859,  1.14195763,0.91932419,  0.78821399,  0.76227809,  0.84176998,  1.01419604,1.25532094,  1.53093814,  1.80003031,  2.02024623,  2.15707825,2.19902306],[ 2.29104308,  2.1421795 ,  1.91361664,  1.66775429,  1.4503379 ,1.29192654,  1.20984338,  1.20983398,  1.28741951,  1.4291507 ,1.61406933,  1.8157611 ,  2.00546122,  2.15673162,  2.25214955,2.29158209],[ 2.19592259,  2.08585339,  1.91410389,  1.73433293,  1.58065059,1.47280881,  1.41982043,  1.4224534 ,  1.47500701,  1.56675335,1.68339946,  1.80889599,  1.9278646 ,  2.02875986,  2.10734416,2.16766927],[ 1.90364107,  1.84456778,  1.73613883,  1.62063181,  1.52025046,1.44542853,  1.39954856,  1.38175761,  1.38870078,  1.41571194,1.45783921,  1.51095031,  1.57299489,  1.64516681,  1.73180054,1.83422428],[ 1.44006075,  1.44084294,  1.39747465,  1.33903092,  1.27658655,1.2136941 ,  1.1514551 ,  1.09105368,  1.03495315,  0.98741407,0.95470048,  0.94511938,  0.96877897,  1.03648204,  1.15598539,1.31935859],[ 0.85310219,  0.91835379,  0.93613205,  0.9215548 ,  0.8765544 ,0.80122736,  0.69834088,  0.57492521,  0.44245456,  0.31632919,0.21496974,  0.15854801,  0.16705806,  0.25687478,  0.43359029,0.67392233],[ 0.21307688,  0.34155231,  0.40945286,  0.41859933,  0.36519017,0.25030719,  0.08279525, -0.1207412 , -0.33717397, -0.53865813,-0.69481594, -0.77541611, -0.75400979, -0.61357493, -0.35663432,-0.02737189],[-0.38828494, -0.20618069, -0.10828106, -0.10352304, -0.1963743 ,-0.37937371, -0.63300958, -0.92785655, -1.22745851, -1.49150626,-1.67930326, -1.75379581, -1.686765  , -1.46634547, -1.10937656,-0.68572898],[-0.84138209, -0.62697398, -0.53053551, -0.56670839, -0.73371373,-1.01170006, -1.36634378, -1.75332884, -2.12281348, -2.42382663,-2.60882774, -2.63885557, -2.48994855, -2.16200449, -1.69237297,-1.18012379],[-1.02796263, -0.81797582, -0.76730311, -0.88757639, -1.16219484,-1.55335615, -2.0095011 , -2.47170348, -2.87925404, -3.17486091,-3.30992002, -3.2503765 , -2.98386161, -2.52913175, -1.94957254,-1.37448646],[-0.8453655 , -0.69344726, -0.74272994, -0.98708156, -1.38715991,-1.88505859, -2.41377971, -2.90431974, -3.29154662, -3.51958352,-3.54724604, -3.35404368, -2.94730867, -2.3711353 , -1.71790821,-1.14235009]])
xnew = np.array([[ 0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,  0. ,0. ,  0. ,  0. ,  0. ,  0. ],[ 0.2,  0.2,  0.2,  0.2,  0.2,  0.2,  0.2,  0.2,  0.2,  0.2,  0.2,0.2,  0.2,  0.2,  0.2,  0.2],[ 0.4,  0.4,  0.4,  0.4,  0.4,  0.4,  0.4,  0.4,  0.4,  0.4,  0.4,0.4,  0.4,  0.4,  0.4,  0.4],[ 0.6,  0.6,  0.6,  0.6,  0.6,  0.6,  0.6,  0.6,  0.6,  0.6,  0.6,0.6,  0.6,  0.6,  0.6,  0.6],[ 0.8,  0.8,  0.8,  0.8,  0.8,  0.8,  0.8,  0.8,  0.8,  0.8,  0.8,0.8,  0.8,  0.8,  0.8,  0.8],[ 1. ,  1. ,  1. ,  1. ,  1. ,  1. ,  1. ,  1. ,  1. ,  1. ,  1. ,1. ,  1. ,  1. ,  1. ,  1. ],[ 1.2,  1.2,  1.2,  1.2,  1.2,  1.2,  1.2,  1.2,  1.2,  1.2,  1.2,1.2,  1.2,  1.2,  1.2,  1.2],[ 1.4,  1.4,  1.4,  1.4,  1.4,  1.4,  1.4,  1.4,  1.4,  1.4,  1.4,1.4,  1.4,  1.4,  1.4,  1.4],[ 1.6,  1.6,  1.6,  1.6,  1.6,  1.6,  1.6,  1.6,  1.6,  1.6,  1.6,1.6,  1.6,  1.6,  1.6,  1.6],[ 1.8,  1.8,  1.8,  1.8,  1.8,  1.8,  1.8,  1.8,  1.8,  1.8,  1.8,1.8,  1.8,  1.8,  1.8,  1.8],[ 2. ,  2. ,  2. ,  2. ,  2. ,  2. ,  2. ,  2. ,  2. ,  2. ,  2. ,2. ,  2. ,  2. ,  2. ,  2. ],[ 2.2,  2.2,  2.2,  2.2,  2.2,  2.2,  2.2,  2.2,  2.2,  2.2,  2.2,2.2,  2.2,  2.2,  2.2,  2.2],[ 2.4,  2.4,  2.4,  2.4,  2.4,  2.4,  2.4,  2.4,  2.4,  2.4,  2.4,2.4,  2.4,  2.4,  2.4,  2.4],[ 2.6,  2.6,  2.6,  2.6,  2.6,  2.6,  2.6,  2.6,  2.6,  2.6,  2.6,2.6,  2.6,  2.6,  2.6,  2.6],[ 2.8,  2.8,  2.8,  2.8,  2.8,  2.8,  2.8,  2.8,  2.8,  2.8,  2.8,2.8,  2.8,  2.8,  2.8,  2.8],[ 3. ,  3. ,  3. ,  3. ,  3. ,  3. ,  3. ,  3. ,  3. ,  3. ,  3. ,3. ,  3. ,  3. ,  3. ,  3. ]])
ynew = np.array([[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ],[ 0. ,  0.2,  0.4,  0.6,  0.8,  1. ,  1.2,  1.4,  1.6,  1.8,  2. ,2.2,  2.4,  2.6,  2.8,  3. ]])
tckP=interpolate.bisplrep(xnew,ynew,P,s=0)

如果我运行这段代码，会出现段错误...为什么？!

提前感谢您的帮助

[编辑]

使用 GDB 得到这个:

...
Program received signal SIGSEGV, Segmentation fault.
0x00007fffed3f53c4 in fprank_ () from /usr/lib64/python2.7/site-packages/scipy/interpolate/_fitpack.so

在 python 中使用详细选项得到这个:

...
dlopen("/usr/lib64/python2.7/site-packages/scipy/spatial/_distance_wrap.so", 2);
import scipy.spatial._distance_wrap # dynamically loaded from /usr/lib64/python2.7/site- packages/scipy/spatial/_distance_wrap.so
import scipy.interpolate.interpnd # dynamically loaded from /usr/lib64/python2.7/site-packages/scipy/interpolate/interpnd.so

我也将报告为错误，感谢您的评论

[编辑#2]

gdb 的回溯说:

(gdb) bt
#0  0x00007fffec7053c4 in fprank_ ()
from /usr/lib64/python2.7/site-packages/scipy/interpolate/_fitpack.so
#1  0x00007fffec6fcee3 in fpsurf_ ()
from /usr/lib64/python2.7/site-packages/scipy/interpolate/_fitpack.so
#2  0x00007fffec6df46b in surfit_ ()
from /usr/lib64/python2.7/site-packages/scipy/interpolate/_fitpack.so
#3  0x00007fffec6c995b in ?? ()
from /usr/lib64/python2.7/site-packages/scipy/interpolate/_fitpack.so
#4  0x0000003d564dd0e1 in PyEval_EvalFrameEx () from /lib64/libpython2.7.so.1.0
#5  0x0000003d564ddb1f in PyEval_EvalCodeEx () from /lib64/libpython2.7.so.1.0
#6  0x0000003d564dc113 in PyEval_EvalFrameEx () from /lib64/libpython2.7.so.1.0
#7  0x0000003d564ddb1f in PyEval_EvalCodeEx () from /lib64/libpython2.7.so.1.0
#8  0x0000003d564ddbf2 in PyEval_EvalCode () from /lib64/libpython2.7.so.1.0
#9  0x0000003d564f6b9a in ?? () from /lib64/libpython2.7.so.1.0
#10 0x0000003d564f7992 in PyRun_FileExFlags () from /lib64/libpython2.7.so.1.0
#11 0x0000003d564f83ab in PyRun_SimpleFileExFlags ()
from /lib64/libpython2.7.so.1.0
#12 0x0000003d56509882 in Py_Main () from /lib64/libpython2.7.so.1.0
#13 0x000000365e221735 in __libc_start_main () from /lib64/libc.so.6
#14 0x00000000004006f1 in _start ()

并且在 stackoverflow 中还有一个类似问题的条目: Segmentation fault in Scipy _fitpack fprank_() 我认为这里的问题是数据太多了

Answer 1

使用 s!=0

s = len(x) +- sqrt(2*len(x))