概述

我如何选择构建我的数据：

首先让我演示一下我对pandas.core.panelnd.creat_nd_panel_factory的使用.

Subject = panelnd.create_nd_panel_factory(
    klass_name='Subject',axis_orders=['setsize','location','vfield','channels','samples'],axis_slices={'labels': 'location','items': 'vfield','major_axis': 'major_axis','minor_axis': 'minor_axis'},slicer=pd.Panel4D,axis_aliases={'ss': 'setsize','loc': 'location','vf': 'vfield','major': 'major_axis','minor': 'minor_axis'}
    # stat_axis=2  # dafuq is this?
    )

从本质上讲,该组织如下：

> setsize：一个实验条件,可以是1或2
> location：一个实验条件,可以是“same”,“diff”或None
> vfield：一个实验条件,可以是“lvf”或“rvf”

最后两个轴对应于DataFrame的major_axis和minor_axis.为清楚起见,它们已重命名：

>频道：列,EEG频道(其中129个)
>样品：行,单个样品.样本可以作为时间轴.

我正在做的事情：

每个实验条件(主题x设置x位置x vfield)存储在它自己的制表符分隔文件中,我用pandas.read_table读取它,获取DataFrame对象.我想为每个主题创建一个5维面板(即主题),其将包含该主题的所有实验条件(即DataFrame).

首先,我正在为每个主题/主题构建一个嵌套字典：

# ... do some boring stuff to get the text files,etc...
for _,factors in df.iterrows():
    # `factors` is a 4-tuple containing
    #  (subject number,setsize,location,vfield,#  and path to the tab-delimited file).
    sn,ss,loc,vf,path = factors
    eeg = pd.read_table(path,sep='\t',names=range(1,129) + ['ref'],header=None)

    # build nested dict
    subjects.setdefault(sn,{}).setdefault(ss,{}).setdefault(loc,{})[vf] = eeg

# and Now attempt to build `Subject`
for sn,d in subjects.iteritems():
    subjects[sn] = Subject(d)

完整堆栈跟踪

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-2-831fa603ca8f> in <module>()
----> 1 import_data()

/home/louist/DropBox/Research/VSTM/scripts/vstmlib.py in import_data()
     64 
     65     import ipdb; ipdb.set_trace()
---> 66     for sn,d in subjects.iteritems():
     67         subjects[sn] = Subject(d)
     68 

/usr/local/lib/python2.7/dist-packages/pandas/core/panelnd.pyc in @R_419_1225@(self,*args,**kwargs)
     65         if 'dtype' not in kwargs:
     66             kwargs['dtype'] = None
---> 67         self._init_data(*args,**kwargs)
     68     klass.@R_419_1225@ = @R_419_1225@
     69 

/usr/local/lib/python2.7/dist-packages/pandas/core/panel.pyc in _init_data(self,data,copy,dtype,**kwargs)
    250             mgr = data
    251         elif isinstance(data,dict):
--> 252             mgr = self._init_dict(data,passed_axes,dtype=dtype)
    253             copy = False
    254             dtype = None

/usr/local/lib/python2.7/dist-packages/pandas/core/panel.pyc in _init_dict(self,axes,dtype)
    293         raxes = [self._extract_axis(self,axis=i)
    294                  if a is None else a for i,a in enumerate(axes)]
--> 295         raxes_sm = self._extract_axes_for_slice(self,raxes)
    296 
    297         # shallow copy

/usr/local/lib/python2.7/dist-packages/pandas/core/panel.pyc in _extract_axes_for_slice(self,axes)
   1477         """ return the slice dictionary for these axes """
   1478         return dict([(self._AXIS_SLICEMAP[i],a) for i,a
-> 1479                      in zip(self._AXIS_ORDERS[self._AXIS_LEN - len(axes):],axes)])
   1480 
   1481     @staticmethod

KeyError: 'location'

我知道panelnd是一个实验性功能,但我很确定我做错了什么.有人可以指点我正确的方向吗？如果它是一个bug,有什么可以做的吗？

像往常一样,非常感谢你！

我会首先创建一个Panel4D,然后像下面一样创建你的主题.

如果你发现更多错误,请在github /这里发帖.这不是一个使用频繁的功能.

产量

<class 'pandas.core.panelnd.Subject'>
Dimensions: 3 (setsize) x 1 (location) x 1 (vfield) x 10 (channels) x 2 (samples)
Setsize axis: level0_0 to level0_2
Location axis: level1_0 to level1_0
Vfield axis: level2_0 to level2_0
Channels axis: level3_0 to level3_9
Samples axis: level4_1 to level4_2

码

import pandas as pd
import numpy as np
from pandas.core import panelnd

Subject = panelnd.create_nd_panel_factory(
    klass_name='Subject',axis_slices={'location' : 'labels','vfield' : 'items','channels' : 'major_axis','samples': 'minor_axis'},'loc': 'labels','vf': 'items','minor': 'minor_axis'})


subjects = dict()
for i in range(3):
    eeg = pd.DataFrame(np.random.randn(10,2),columns=['level4_1','level4_2'],index=[ "level3_%s" % x for x in range(10)])

    loc,vf = ('level1_0','level2_0')
    subjects["level0_%s" % i] = pd.Panel4D({ loc : { vf : eeg }})

print Subject(subjects)

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