First commit

system/dataset.py

@@ -0,0 +1,61 @@
+#import logger
+from scipy import array,take,asarray,shape
+import project
+#from sets import Set as set
+from itertools import izip 
+
+
+class Dataset:
+    """
+    Dataset base class
+    """
+    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 = {}
+        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
+        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"
+
+            
+    def extract_data(self,ids,dim_name):
+        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
+        D = Dataset(out_data,def_list=new_def_list,parents=self.parents)
+        return D
+
+    def _create_identifiers(self,axis):
+        n_dim = self.dims[axis]
+        return [str(axis) + '_' + str(i) for i in range(n_dim)]
+        
+class Selection:
+    def __init__(self):
+        self.current_selection={}

system/project.py

@@ -0,0 +1,49 @@
+#import logger 
+import dataset
+
+class Project:
+    def __init__(self,name="Testing"):
+        self.name = name
+        self.dim_names = []
+        self._selection_observers = []
+        self.current_selection = {}
+        self.current_data=[]
+        self.datasets=[]
+        
+    def attach(self, observer):
+        if not observer in self._selection_observers:
+            self._selection_observers.append(observer)
+
+    def detach(self, observer):
+       try:
+           self.selection_observers.remove(observer)
+       except ValueError:
+           pass
+
+    def notify(self, modifier=None):
+        for observer in self.selection_observers:
+            if modifier != observer:
+                observer.update(self)
+
+    def set_selection(self,dim_name,selection):
+        current_selection = set(selection)
+        self.current_selection[dim_name] = current_selection
+        self.notify()
+
+    def get_selection(self,sel_obj):
+        return sel_obj.current_selection
+
+    
+    def add_dataset(self,dataset):
+        self.datasets.append(dataset)
+        for dim_name in dataset.ids.keys():
+            if dim_name not in self.dim_names:
+                self.dim_names.append(dim_name)
+
+    def suggest_dim_name(self,dim_name):
+        if dim_name in self.dim_names:
+            dim_name = dim_name + "_t" 
+        return dim_name
+        
+            
+c_p = Project()

test/system/datasettest.py

@@ -0,0 +1,33 @@
+import unittest
+import sys
+sys.path.append('../../system')
+from dataset import *
+from scipy import rand,shape
+
+class DatasetTest(unittest.TestCase):
+    def setUp(self):
+        self.dim_0_ids = ['sample_a','sample_b']
+        self.dim_1_ids = ['gene_a','gene_b','gene_c']
+        self.dim_labels = ['samples','genes']
+        self.def_list = [[self.dim_labels[0],self.dim_0_ids],[self.dim_labels[1],self.dim_1_ids]]
+        self.array = rand(2,3)
+        self.testdata = Dataset(self.array,self.def_list)
+
+    def testCreation(self):
+        assert self.testdata._data == self.array
+        assert 'sample_a' in self.testdata.ids['samples'].keys()
+        assert 'gene_b' in self.testdata.ids['genes'].keys()
+
+        
+        
+    def testExtraction(self):
+        ids = ['gene_a','gene_b']
+        dim_name = 'genes'
+        subset = self.testdata.extract_data(ids,dim_name)
+        assert shape(subset._data) == (2,2)
+        assert subset.ids[dim_name].keys() == ids
+        assert subset.ids[dim_name].values() == [0,1]
+
+
+if __name__ == '__main__':
+    unittest.main()