NF: new code to slice 4d or 5d data

Author: cindeem

brainx/tests/test_util.py

@@ -17,6 +17,17 @@
 # Functions
 #-----------------------------------------------------------------------------
 
+def test_slice_data():
+    subcond, blocks, subjects, nodes = 5, 10, 20, 4 
+    data_4d = np.ones((blocks, subjects, nodes, nodes))
+    data_5d = np.ones((subcond, blocks, subjects, nodes, nodes))
+    sym_4d = util.slice_data(data_4d, subjects - 1 , blocks - 1 )
+    sym_5d = util.slice_data(data_5d, subjects -1 , blocks-1, subcond-1)
+    npt.assert_equal(sym_4d.shape, (nodes, nodes))
+    npt.assert_equal(sym_5d.shape, (nodes, nodes))
+    npt.assert_raises(IndexError, util.slice_data, data_5d, subjects, blocks)
+
+
 def test_cost_size():
     n_nodes = 5
     npt.assert_warns(DeprecationWarning, util.cost_size, n_nodes)

brainx/util.py

@@ -14,6 +14,31 @@
 #-----------------------------------------------------------------------------
 # Functions
 #-----------------------------------------------------------------------------
+def slice_data(data, sub, block, subcond=None):
+    """ pull symmetric matrix from data block (4D or 5D)
+    
+    Parameters
+    ----------
+    data : numpy array
+        4D array (block, sub, nnode, nnode)
+        5D array (subcond, block, sub, nnode, nnode)
+    sub : int
+        int representing subject to index in data
+    block : int
+        int representing block to index in data
+    subcond : int
+        int representing optional subcondition from 5D array
+
+    Returns
+    -------
+    adjacency_matrix : numpy array
+        symmetric numpy array (innode, nnode)
+    """
+    if subcond:
+        return data[subcond, block, sub]
+    return data[block, sub]
+
+
 def format_matrix(data,s,b,lk,co,idc = [],costlist=[],nouptri = False):
     """ Function which formats matrix for a particular subject and particular block (thresholds, upper-tris it) so that we can make a graph object out of it