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laydi/system/dataset.py

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#import logger
from scipy import array,take,asarray,shape
import project
#from sets import Set as set
from itertools import izip
class Dataset:
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"""Dataset base class.
A Dataset is an n-way array with defined string identifiers across
all dimensions.
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"""
def __init__(self,input_array,def_list,parents=None):
self._data = asarray(input_array)
self.dims = shape(self._data)
self.parents = parents
self.def_list = def_list
self._ids_set = set()
self.ids={}
self.children=[]
self._dim_num = {}
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self._dim_names = []
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if parents!=None:
for parent in self.parents:
parent.children.append(self)
if len(def_list)!=len(self.dims):
raise ValueError,"array dims and identifyer mismatch"
for axis,(dim_name,ids) in enumerate(def_list):
enum_ids = {}
if dim_name not in project.c_p.dim_names:
dim_name = project.c_p.suggest_dim_name(dim_name)
if not ids:
ids = self._create_identifiers(axis)
for num,name in enumerate(ids):
enum_ids[name] = num
self.ids[dim_name] = enum_ids
self._ids_set = self._ids_set.union(set(ids))
self._dim_num[dim_name] = axis
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self._dim_names.append(dim_name)
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for df,d in izip(def_list,self.dims):
df=df[1]
if len(df)!=d and df:
raise ValueError,"dim size and identifyer mismatch"
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def names(self,axis=0):
"""Returns identifier names of a dimension. NB: not in any order! """
if type(axis)==int:
dim_name = self._dim_names[axis]
elif type(axis)==str:
dim_name = axis
return self.ids[dim_name].keys()
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def extract_data(self,ids,dim_name):
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"""Extracts data along a dimension by identifiers"""
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new_def_list = self.def_list[:]
ids_index = [self.ids[dim_name][id_name] for id_name in ids]
dim_number = self._dim_num[dim_name]
try:
out_data = take(self._data,ids_index,axis=dim_number)
except:
raise ValueError
new_def_list[dim_number][1] = ids
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extracted_data = Dataset(out_data,def_list=new_def_list,parents=self.parents)
return extracted_data
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def _create_identifiers(self,axis):
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"""Creates identifiers along an axis"""
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n_dim = self.dims[axis]
return [str(axis) + '_' + str(i) for i in range(n_dim)]
class Selection:
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"""Handles selected identifiers along each dimension of a dataset"""
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def __init__(self):
self.current_selection={}