94 lines
3.2 KiB
Python
94 lines
3.2 KiB
Python
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from sets import Set as set
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set.update = set.union_update
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import dataset
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import scipy
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class AnnotationsException(Exception):
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pass
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class Annotations:
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def __init__(self, *dimensions):
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""" Initializes a new Annotation with the given dimension labels.
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dimensions is a list of dimension labels.
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"""
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if len(dimensions) != 2:
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msg = 'Annotations only supports two dimensions.'
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raise AnnotationsException(msg)
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self.dimensions = {}
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for d in dimensions:
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self.dimensions[d] = {}
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def add_annotations(self, dim, id, ann_dim, annotations):
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""" Adds new annotations.
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dim: the dimension in which the new data should be added.
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id: the identifier that should be annotated.
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ann_dim: the dimension of the annotations to id.
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annotations: the new annotations to id.
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Returns the total set of annotations to id.
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"""
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if not self.has_dimension(dim):
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msg = 'Annotations object does not contain dimension %s' % dim
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raise AnnotationsException(msg)
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if not self.has_dimension(ann_dim):
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msg = 'Annotations object does not contain dimension %s' % ann_dim
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raise AnnotationsException(msg)
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for a in annotations:
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if not self.dimensions[ann_dim].has_key(a):
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self.dimensions[ann_dim][a] = set()
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self.dimensions[ann_dim][a].add(id)
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if not self.dimensions[dim].has_key(id):
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self.dimensions[dim][id] = set()
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self.dimensions[dim][id].update(annotations)
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return self.dimensions[dim][id]
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def get_annotations(self, dim, id, ann_dim):
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"""Returns all annotations to id.
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dim: the dimension where id can be found.
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id: the id to retrieve annotations for.
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"""
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if not self.has_dimension(dim):
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msg = 'Annotations object does not contain dimension %s' % dim
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raise AnnotationsException(msg)
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if self.dimensions[dim].has_key(id):
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return self.dimensions[dim][id]
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return set()
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def has_dimension(self, dim):
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""" Retuns true if the Annotations object indexes dim.
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"""
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return self.dimensions.has_key(dim)
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def to_dataset(self,dim):
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""" Returns a dataset representation of annotations.
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"""
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if self.has_dimension(dim):
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num_dim1 = len(set(self.dimensions[dim])) #number of unique genes
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all_genes = set(self.dimensions[dim])
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all_categories = set()
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for cat in self.dimensions[dim].values():
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all_categories.update(cat)
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num_dim1 = len(all_genes) #number of unique genes
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num_dim2 = len(all_categories) #number of unique categories
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gene_list=[]
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cat_list=[]
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matrix = scipy.zeros((num_dim1,num_dim2),'bwu')
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for i,gene in enumerate(all_genes):
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gene_list.append(gene)
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for j,cat in enumerate(all_categories):
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cat_list.append(cat)
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matrix[i,j] = 1
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def_list = [['genes',gene_list],['go',cat_list]]
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return dataset.Dataset(matrix,def_list)
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