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cPickle ImportError：没有名为 multiarray 的模块

发布于 2024-09-04 20:52:03 字数 15398 浏览 7 评论 0原文

我正在使用 cPickle 将数据库保存到文件中。代码看起来像这样：

def Save_DataBase():
import cPickle
from scipy import *
from numpy import *
a=Results.VersionName
#filename='D:/results/'+a[a.find('/')+1:-a.find('/')-2]+Results.AssType[:3]+str(random.randint(0,100))+Results.Distribution+".lft"
filename='D:/results/pppp.lft'
plik=open(filename,'w')


DataOutput=[[[DataBase.Arrays.Nodes,DataBase.Arrays.Links,DataBase.Arrays.Turns,DataBase.Arrays.Connectors,DataBase.Arrays.Zones],
             [DataBase.Nodes.Data,DataBase.Links.Data,DataBase.Turns.Data,DataBase.OrigConnectors.Data,DataBase.DestConnectors.Data,DataBase.Zones.Data],
             [DataBase.Nodes.DictionaryPy2Vis,DataBase.Links.DictionaryPy2Vis,DataBase.Turns.DictionaryPy2Vis,DataBase.OrigConnectors.DictionaryPy2Vis,DataBase.DestConnectors.DictionaryPy2Vis,DataBase.Zones.DictionaryPy2Vis],
             [DataBase.Nodes.DictionaryVis2Py,DataBase.Links.DictionaryVis2Py,DataBase.Turns.DictionaryVis2Py,DataBase.OrigConnectors.DictionaryVis2Py,DataBase.DestConnectors.DictionaryVis2Py,DataBase.Zones.DictionaryVis2Py],
             [DataBase.Paths.List]],[Results.VersionName,Results.noZones,Results.noNodes,Results.noLinks,Results.noTurns,Results.noTrips,
                                     Results.Times.VersionLoad,Results.Times.GetData,Results.Times.GetCoords,Results.Times.CrossTheTime,Results.Times.Plot_Cylinder,
                                     Results.AssType,Results.AssParam,Results.tStart,Results.tEnd,Results.Distribution,Results.tVector]]



cPickle.dump(DataOutput, plik, protocol=0)
plik.close()`

它工作正常。我的大多数数据库行都是列表、类似矢量或类似数组的数据集的列表。

但是现在当我输入数据时，会发生错误：

def Load_DataBase():
    import cPickle 
    from scipy import *
    from numpy import *  
    filename='D:/results/pppp.lft'
    plik= open(filename, 'rb')
    """ first cPickle load approach """
    A= cPickle.load(plik)
    """ fail """
    """ Another approach - data format exact as in Output step above , also fails"""
    [[[DataBase.Arrays.Nodes,DataBase.Arrays.Links,DataBase.Arrays.Turns,DataBase.Arrays.Connectors,DataBase.Arrays.Zones],
                 [DataBase.Nodes.Data,DataBase.Links.Data,DataBase.Turns.Data,DataBase.OrigConnectors.Data,DataBase.DestConnectors.Data,DataBase.Zones.Data],
                 [DataBase.Nodes.DictionaryPy2Vis,DataBase.Links.DictionaryPy2Vis,DataBase.Turns.DictionaryPy2Vis,DataBase.OrigConnectors.DictionaryPy2Vis,DataBase.DestConnectors.DictionaryPy2Vis,DataBase.Zones.DictionaryPy2Vis],
                 [DataBase.Nodes.DictionaryVis2Py,DataBase.Links.DictionaryVis2Py,DataBase.Turns.DictionaryVis2Py,DataBase.OrigConnectors.DictionaryVis2Py,DataBase.DestConnectors.DictionaryVis2Py,DataBase.Zones.DictionaryVis2Py],
                 [DataBase.Paths.List]],[Results.VersionName,Results.noZones,Results.noNodes,Results.noLinks,Results.noTurns,Results.noTrips,
                                         Results.Times.VersionLoad,Results.Times.GetData,Results.Times.GetCoords,Results.Times.CrossTheTime,Results.Times.Plot_Cylinder,
                                         Results.AssType,Results.AssParam,Results.tStart,Results.tEnd,Results.Distribution,Results.tVector]]= cPickle.load(plik)`

错误是（在两种情况下）：

    Traceback (most recent call last):
  File "D:\programy\projekt_eclipse\src\Praca\wx_frame.py", line 342, in LoadDatabase_Handler
    Load_DataBase()
  File "D:\programy\projekt_eclipse\src\Praca\wx_frame.py", line 1804, in Load_DataBase
    A= cPickle.load(plik)
ImportError: No module named multiarray

有什么想法吗？

附言。现在我已经部分解决了问题：/我需要更改数组的格式。我试图追踪错误，但我做不到。导致错误的变量是这个 (long :) ) :

[[  0.00000000e+00   0.00000000e+00   0.00000000e+00   0.00000000e+00
    0.00000000e+00   0.00000000e+00   0.00000000e+00   0.00000000e+00]
 [  1.00000000e+00   0.00000000e+00   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   0.00000000e+00]
 [  2.00000000e+00   0.00000000e+00   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.52875186e+04]
 [  3.00000000e+00   0.00000000e+00   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  4.00000000e+00   0.00000000e+00   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  5.00000000e+00   0.00000000e+00   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  6.00000000e+00   0.00000000e+00   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  7.00000000e+00   0.00000000e+00   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  8.00000000e+00   0.00000000e+00   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.59846476e+04]
 [  9.00000000e+00   0.00000000e+00   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   0.00000000e+00]
 [  1.00000000e+01   1.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.97583022e+04]
 [  1.10000000e+01   1.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.84929461e+04]
 [  1.20000000e+01   1.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.76891311e+03]
 [  1.30000000e+01   1.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   5.10636164e+03]
 [  1.40000000e+01   1.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.45841100e+03]
 [  1.50000000e+01   1.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.22093915e+03]
 [  1.60000000e+01   1.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.20282091e+03]
 [  1.70000000e+01   1.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.86566159e+04]
 [  1.80000000e+01   1.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.80902598e+04]
 [  1.90000000e+01   2.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.23193676e+04]
 [  2.00000000e+01   2.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.16000116e+04]
 [  2.10000000e+01   2.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.05680012e+03]
 [  2.20000000e+01   2.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.89123867e+03]
 [  2.30000000e+01   2.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.98898168e+03]
 [  2.40000000e+01   2.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   7.44216130e+03]
 [  2.50000000e+01   2.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.23593332e+04]
 [  2.60000000e+01   2.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.14424233e+04]
 [  2.70000000e+01   2.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.91864355e+04]
 [  2.80000000e+01   3.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.07766798e+04]
 [  2.90000000e+01   3.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.61849685e+03]
 [  3.00000000e+01   3.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.09785208e+04]
 [  3.10000000e+01   3.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.99736773e+03]
 [  3.20000000e+01   3.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.06209122e+03]
 [  3.30000000e+01   3.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.48702707e+03]
 [  3.40000000e+01   3.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.04653099e+04]
 [  3.50000000e+01   3.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.25314801e+03]
 [  3.60000000e+01   3.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.67608539e+04]
 [  3.70000000e+01   4.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.07766798e+04]
 [  3.80000000e+01   4.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.82241178e+03]
 [  3.90000000e+01   4.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.05149043e+03]
 [  4.00000000e+01   4.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.55692239e+03]
 [  4.10000000e+01   4.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.19199226e+04]
 [  4.20000000e+01   4.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.43876335e+03]
 [  4.30000000e+01   4.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.90454231e+03]
 [  4.40000000e+01   4.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.03525083e+03]
 [  4.50000000e+01   4.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.67608539e+04]
 [  4.60000000e+01   5.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.07766798e+04]
 [  4.70000000e+01   5.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.07842319e+03]
 [  4.80000000e+01   5.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.48191278e+03]
 [  4.90000000e+01   5.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.06547361e+04]
 [  5.00000000e+01   5.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.27500595e+04]
 [  5.10000000e+01   5.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.62319628e+03]
 [  5.20000000e+01   5.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.50364667e+03]
 [  5.30000000e+01   5.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.48651846e+03]
 [  5.40000000e+01   5.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.67608539e+04]
 [  5.50000000e+01   6.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.16862400e+04]
 [  5.60000000e+01   6.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.88311307e+03]
 [  5.70000000e+01   6.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   7.89923519e+03]
 [  5.80000000e+01   6.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.16959736e+03]
 [  5.90000000e+01   6.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.49942081e+03]
 [  6.00000000e+01   6.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.24620368e+03]
 [  6.10000000e+01   6.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.27811830e+03]
 [  6.20000000e+01   6.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.13336356e+04]
 [  6.30000000e+01   6.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.91853045e+04]
 [  6.40000000e+01   7.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.67326624e+04]
 [  6.50000000e+01   7.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.79192625e+04]
 [  6.60000000e+01   7.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.35835049e+03]
 [  6.70000000e+01   7.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.66349011e+03]
 [  6.80000000e+01   7.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.88664273e+03]
 [  6.90000000e+01   7.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.15546726e+03]
 [  7.00000000e+01   7.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.26420582e+03]
 [  7.10000000e+01   7.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.80179725e+04]
 [  7.20000000e+01   7.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.69846102e+04]
 [  7.30000000e+01   8.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   0.00000000e+00]
 [  7.40000000e+01   8.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.66207833e+04]
 [  7.50000000e+01   8.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  7.60000000e+01   8.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  7.70000000e+01   8.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  7.80000000e+01   8.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  7.90000000e+01   8.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  8.00000000e+01   8.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.70098656e+04]
 [  8.10000000e+01   8.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   0.00000000e+00]]

cPickle 或 pickle 无法加载它。但是当我使用控制台手动执行此操作时，相同的文件结构（ [[ ]] 和所有格式完全相同，值也是 e+00 格式）然后它工作正常????????????我勒个去？ 无论如何，我已经通过更改数据格式解决了问题：/

原文

I'm using cPickle to save my Database into file. The code looks like that:

def Save_DataBase():
import cPickle
from scipy import *
from numpy import *
a=Results.VersionName
#filename='D:/results/'+a[a.find('/')+1:-a.find('/')-2]+Results.AssType[:3]+str(random.randint(0,100))+Results.Distribution+".lft"
filename='D:/results/pppp.lft'
plik=open(filename,'w')


DataOutput=[[[DataBase.Arrays.Nodes,DataBase.Arrays.Links,DataBase.Arrays.Turns,DataBase.Arrays.Connectors,DataBase.Arrays.Zones],
             [DataBase.Nodes.Data,DataBase.Links.Data,DataBase.Turns.Data,DataBase.OrigConnectors.Data,DataBase.DestConnectors.Data,DataBase.Zones.Data],
             [DataBase.Nodes.DictionaryPy2Vis,DataBase.Links.DictionaryPy2Vis,DataBase.Turns.DictionaryPy2Vis,DataBase.OrigConnectors.DictionaryPy2Vis,DataBase.DestConnectors.DictionaryPy2Vis,DataBase.Zones.DictionaryPy2Vis],
             [DataBase.Nodes.DictionaryVis2Py,DataBase.Links.DictionaryVis2Py,DataBase.Turns.DictionaryVis2Py,DataBase.OrigConnectors.DictionaryVis2Py,DataBase.DestConnectors.DictionaryVis2Py,DataBase.Zones.DictionaryVis2Py],
             [DataBase.Paths.List]],[Results.VersionName,Results.noZones,Results.noNodes,Results.noLinks,Results.noTurns,Results.noTrips,
                                     Results.Times.VersionLoad,Results.Times.GetData,Results.Times.GetCoords,Results.Times.CrossTheTime,Results.Times.Plot_Cylinder,
                                     Results.AssType,Results.AssParam,Results.tStart,Results.tEnd,Results.Distribution,Results.tVector]]



cPickle.dump(DataOutput, plik, protocol=0)
plik.close()`

And it works fine. Most of my Database rows are lists of a lists, vecor-like, or array-like data sets.

But now when I input data, an error occurs:

def Load_DataBase():
    import cPickle 
    from scipy import *
    from numpy import *  
    filename='D:/results/pppp.lft'
    plik= open(filename, 'rb')
    """ first cPickle load approach """
    A= cPickle.load(plik)
    """ fail """
    """ Another approach - data format exact as in Output step above , also fails"""
    [[[DataBase.Arrays.Nodes,DataBase.Arrays.Links,DataBase.Arrays.Turns,DataBase.Arrays.Connectors,DataBase.Arrays.Zones],
                 [DataBase.Nodes.Data,DataBase.Links.Data,DataBase.Turns.Data,DataBase.OrigConnectors.Data,DataBase.DestConnectors.Data,DataBase.Zones.Data],
                 [DataBase.Nodes.DictionaryPy2Vis,DataBase.Links.DictionaryPy2Vis,DataBase.Turns.DictionaryPy2Vis,DataBase.OrigConnectors.DictionaryPy2Vis,DataBase.DestConnectors.DictionaryPy2Vis,DataBase.Zones.DictionaryPy2Vis],
                 [DataBase.Nodes.DictionaryVis2Py,DataBase.Links.DictionaryVis2Py,DataBase.Turns.DictionaryVis2Py,DataBase.OrigConnectors.DictionaryVis2Py,DataBase.DestConnectors.DictionaryVis2Py,DataBase.Zones.DictionaryVis2Py],
                 [DataBase.Paths.List]],[Results.VersionName,Results.noZones,Results.noNodes,Results.noLinks,Results.noTurns,Results.noTrips,
                                         Results.Times.VersionLoad,Results.Times.GetData,Results.Times.GetCoords,Results.Times.CrossTheTime,Results.Times.Plot_Cylinder,
                                         Results.AssType,Results.AssParam,Results.tStart,Results.tEnd,Results.Distribution,Results.tVector]]= cPickle.load(plik)`

Error is (in both cases):

    Traceback (most recent call last):
  File "D:\programy\projekt_eclipse\src\Praca\wx_frame.py", line 342, in LoadDatabase_Handler
    Load_DataBase()
  File "D:\programy\projekt_eclipse\src\Praca\wx_frame.py", line 1804, in Load_DataBase
    A= cPickle.load(plik)
ImportError: No module named multiarray

Any Ideas?

PS. Now I've solved the problem, say partially :/ I needed to change the format of arrays. I've tried to trace the error, but I couldn't. The variable causing error is this (long :) ) :

[[  0.00000000e+00   0.00000000e+00   0.00000000e+00   0.00000000e+00
    0.00000000e+00   0.00000000e+00   0.00000000e+00   0.00000000e+00]
 [  1.00000000e+00   0.00000000e+00   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   0.00000000e+00]
 [  2.00000000e+00   0.00000000e+00   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.52875186e+04]
 [  3.00000000e+00   0.00000000e+00   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  4.00000000e+00   0.00000000e+00   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  5.00000000e+00   0.00000000e+00   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  6.00000000e+00   0.00000000e+00   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  7.00000000e+00   0.00000000e+00   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.24880978e+04]
 [  8.00000000e+00   0.00000000e+00   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.59846476e+04]
 [  9.00000000e+00   0.00000000e+00   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   0.00000000e+00]
 [  1.00000000e+01   1.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.97583022e+04]
 [  1.10000000e+01   1.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.84929461e+04]
 [  1.20000000e+01   1.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.76891311e+03]
 [  1.30000000e+01   1.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   5.10636164e+03]
 [  1.40000000e+01   1.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.45841100e+03]
 [  1.50000000e+01   1.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.22093915e+03]
 [  1.60000000e+01   1.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.20282091e+03]
 [  1.70000000e+01   1.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.86566159e+04]
 [  1.80000000e+01   1.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.80902598e+04]
 [  1.90000000e+01   2.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.23193676e+04]
 [  2.00000000e+01   2.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.16000116e+04]
 [  2.10000000e+01   2.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.05680012e+03]
 [  2.20000000e+01   2.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.89123867e+03]
 [  2.30000000e+01   2.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.98898168e+03]
 [  2.40000000e+01   2.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   7.44216130e+03]
 [  2.50000000e+01   2.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.23593332e+04]
 [  2.60000000e+01   2.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.14424233e+04]
 [  2.70000000e+01   2.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.91864355e+04]
 [  2.80000000e+01   3.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.07766798e+04]
 [  2.90000000e+01   3.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.61849685e+03]
 [  3.00000000e+01   3.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.09785208e+04]
 [  3.10000000e+01   3.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.99736773e+03]
 [  3.20000000e+01   3.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.06209122e+03]
 [  3.30000000e+01   3.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.48702707e+03]
 [  3.40000000e+01   3.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.04653099e+04]
 [  3.50000000e+01   3.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.25314801e+03]
 [  3.60000000e+01   3.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.67608539e+04]
 [  3.70000000e+01   4.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.07766798e+04]
 [  3.80000000e+01   4.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.82241178e+03]
 [  3.90000000e+01   4.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.05149043e+03]
 [  4.00000000e+01   4.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.55692239e+03]
 [  4.10000000e+01   4.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.19199226e+04]
 [  4.20000000e+01   4.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.43876335e+03]
 [  4.30000000e+01   4.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.90454231e+03]
 [  4.40000000e+01   4.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.03525083e+03]
 [  4.50000000e+01   4.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.67608539e+04]
 [  4.60000000e+01   5.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.07766798e+04]
 [  4.70000000e+01   5.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.07842319e+03]
 [  4.80000000e+01   5.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.48191278e+03]
 [  4.90000000e+01   5.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.06547361e+04]
 [  5.00000000e+01   5.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.27500595e+04]
 [  5.10000000e+01   5.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.62319628e+03]
 [  5.20000000e+01   5.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.50364667e+03]
 [  5.30000000e+01   5.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.48651846e+03]
 [  5.40000000e+01   5.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.67608539e+04]
 [  5.50000000e+01   6.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.16862400e+04]
 [  5.60000000e+01   6.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.88311307e+03]
 [  5.70000000e+01   6.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   7.89923519e+03]
 [  5.80000000e+01   6.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   8.16959736e+03]
 [  5.90000000e+01   6.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.49942081e+03]
 [  6.00000000e+01   6.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   6.24620368e+03]
 [  6.10000000e+01   6.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.27811830e+03]
 [  6.20000000e+01   6.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.13336356e+04]
 [  6.30000000e+01   6.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.91853045e+04]
 [  6.40000000e+01   7.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.67326624e+04]
 [  6.50000000e+01   7.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.79192625e+04]
 [  6.60000000e+01   7.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.35835049e+03]
 [  6.70000000e+01   7.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.66349011e+03]
 [  6.80000000e+01   7.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.88664273e+03]
 [  6.90000000e+01   7.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   4.15546726e+03]
 [  7.00000000e+01   7.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   9.26420582e+03]
 [  7.10000000e+01   7.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   1.80179725e+04]
 [  7.20000000e+01   7.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.69846102e+04]
 [  7.30000000e+01   8.00000000e+03   0.00000000e+00   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   0.00000000e+00]
 [  7.40000000e+01   8.00000000e+03   1.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.66207833e+04]
 [  7.50000000e+01   8.00000000e+03   2.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  7.60000000e+01   8.00000000e+03   3.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  7.70000000e+01   8.00000000e+03   4.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  7.80000000e+01   8.00000000e+03   5.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  7.90000000e+01   8.00000000e+03   6.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   2.32529854e+04]
 [  8.00000000e+01   8.00000000e+03   7.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   3.70098656e+04]
 [  8.10000000e+01   8.00000000e+03   8.00000000e+03   2.00000000e+01
    0.00000000e+00   5.00000000e+02   2.00000000e+01   0.00000000e+00]]

cPickle, or pickle are unable to load it. But when I do it manually with the console, the same file structure ( [[ ]] and all formats exaclty the same, values also e+00 format) Then it works fine ??????????? What the hell?
Anyway I've solved the problem by changign data format :/

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评论（5）

情绪失控 2024-09-11 20:52:03

我在 Windows XP 机器上遇到了同样的问题，代码在 Linux 下运行良好。这可能与文本和二进制文件的不同处理有关。当写入数据时，尝试创建文件对象，明确说明您想要二进制模式，即而

plik=open(filename,'wb')

不是

plik=open(filename,'w')

对我有用。

I had the same problem on a Windows XP machine with Code that worked fine under Linux. It may have to do with the different handling of text and binary files. When writing your data try to create the file object explicitly stating that you want binary mode, i.e.

plik=open(filename,'wb')

instead of

plik=open(filename,'w')

That worked for me.

回复 原文
我要还你自由 2024-09-11 20:52:03

首先检查 $YOUR_PYTHON_INSTALLATION/lib/python-xx/site-packages/numpy/core/multiarray.so 文件是否存在。

如果您发布完整的回溯，而不仅仅是错误消息，这将非常有用。

First of all check if $YOUR_PYTHON_INSTALLATION/lib/python-x.x/site-packages/numpy/core/multiarray.so file exists.

And it would be very useful if you posted full traceback, not only the error message.

回复 原文
烟酉 2024-09-11 20:52:03

您是否尝试过显式导入多数组？ pickle 需要定义所有类才能导入数据。

Have you tried importing multiarray explicitly? pickle needs all the classes to be defined in order to import the data.

回复 原文
沫尐诺 2024-09-11 20:52:03

这可能是由于 git 使用 autocrlf 在 Windows 计算机上更改行结尾造成的。您会注意到，除非您更改分支或执行任何其他删除和重写磁盘上文件的操作，否则这不会成为问题。
将此行添加到您的 .gitattributes 文件中，以避免重写类似文本（但实际上是二进制！）pickle 文件中的行结尾：

# .gitattributes
# Pickle files are to be treated as binary. 
*.p binary
*.lft binary

This can be caused by git changing line endings on a Windows machine with autocrlf. You'll notice that it won't be a problem until you change branches or do anything else that deletes and rewrites the file on disk.
Add this line to your .gitattributes file to avoid rewriting line endings in the text-like (but actually binary!) pickle files:

# .gitattributes
# Pickle files are to be treated as binary. 
*.p binary
*.lft binary
回复 原文
偏爱你一生 2024-09-11 20:52:03

您使用的一定是非常古老的 Python。因为“import *”仅在模块级别可用。不管怎样，回答你的问题：

将这些语句

import cPickle 
from scipy import *
from numpy import *

移出 Load_DataBase 定义，就可以了。引发异常是因为 cPickle 找不到 plik 内容的元信息。

You must be using a very old Python. Because 'import *' is only available at module level. Anyway, to answer your question:

Move these statements

import cPickle 
from scipy import *
from numpy import *

out of the Load_DataBase definition and you'll be fine. The exception was raised because cPickle can't find the meta information for the content of plik.

回复 原文
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