avoid unnecessary imports of numpy

in IPython.parallel.map

also drop crazy-old numeric / numarray support

IPython/parallel/client/map.py

@@ -1,166 +1,129
 # encoding: utf-8
 
 """Classes used in scattering and gathering sequences.
 
 Scattering consists of partitioning a sequence and sending the various
 pieces to individual nodes in a cluster.
-
-
-Authors:
-
-* Brian Granger
-* MinRK
-
 """
 
-#-------------------------------------------------------------------------------
-#  Copyright (C) 2008-2011  The IPython Development Team
-#
-#  Distributed under the terms of the BSD License.  The full license is in
-#  the file COPYING, distributed as part of this software.
-#-------------------------------------------------------------------------------
-
-#-------------------------------------------------------------------------------
-# Imports
-#-------------------------------------------------------------------------------
+# Copyright (c) IPython Development Team.
+# Distributed under the terms of the Modified BSD License.
 
 from __future__ import division
 
+import sys
 from itertools import islice
 
 from IPython.utils.data import flatten as utils_flatten
 
-#-------------------------------------------------------------------------------
-# Figure out which array packages are present and their array types
-#-------------------------------------------------------------------------------
-
-arrayModules = []
-try:
-    import Numeric
-except ImportError:
-    pass
-else:
-    arrayModules.append({'module':Numeric, 'type':Numeric.arraytype})
-try:
-    import numpy
-except ImportError:
-    pass
-else:
-    arrayModules.append({'module':numpy, 'type':numpy.ndarray})
-try:
-    import numarray
-except ImportError:
-    pass
-else:
-    arrayModules.append({'module':numarray,
-        'type':numarray.numarraycore.NumArray})
+
+numpy = None
+
+def is_array(obj):
+    """Is an object a numpy array?
+    
+    Avoids importing numpy until it is requested
+    """
+    global numpy
+    if 'numpy' not in sys.modules:
+        return False
+    
+    if numpy is None:
+        import numpy
+    return isinstance(obj, numpy.ndarray)
 
 class Map(object):
     """A class for partitioning a sequence using a map."""
     
     def getPartition(self, seq, p, q, n=None):
         """Returns the pth partition of q partitions of seq.
         
         The length can be specified as `n`,
         otherwise it is the value of `len(seq)`
         """
         n = len(seq) if n is None else n
         # Test for error conditions here
         if p<0 or p>=q:
           raise ValueError("must have 0 <= p <= q, but have p=%s,q=%s" % (p, q))
         
         remainder = n % q
         basesize = n // q
         
         if p < remainder:
             low = p * (basesize + 1)
             high = low + basesize + 1
         else:
             low = p * basesize + remainder
             high = low + basesize
         
         try:
             result = seq[low:high]
         except TypeError:
             # some objects (iterators) can't be sliced,
             # use islice:
             result = list(islice(seq, low, high))
             
         return result
            
     def joinPartitions(self, listOfPartitions):
         return self.concatenate(listOfPartitions)
-                    
+    
     def concatenate(self, listOfPartitions):
         testObject = listOfPartitions[0]
         # First see if we have a known array type
-        for m in arrayModules:
-            #print m
-            if isinstance(testObject, m['type']):
-                return m['module'].concatenate(listOfPartitions)
+        if is_array(testObject):
+            return numpy.concatenate(listOfPartitions)
         # Next try for Python sequence types
         if isinstance(testObject, (list, tuple)):
             return utils_flatten(listOfPartitions)
         # If we have scalars, just return listOfPartitions
         return listOfPartitions
 
 class RoundRobinMap(Map):
     """Partitions a sequence in a round robin fashion.
     
     This currently does not work!
     """
 
     def getPartition(self, seq, p, q, n=None):
         n = len(seq) if n is None else n
         return seq[p:n:q]
 
     def joinPartitions(self, listOfPartitions):
         testObject = listOfPartitions[0]
         # First see if we have a known array type
-        for m in arrayModules:
-            #print m
-            if isinstance(testObject, m['type']):
-                return self.flatten_array(m['type'], listOfPartitions)
+        if is_array(testObject):
+            return self.flatten_array(listOfPartitions)
         if isinstance(testObject, (list, tuple)):
             return self.flatten_list(listOfPartitions)
         return listOfPartitions
     
-    def flatten_array(self, klass, listOfPartitions):
+    def flatten_array(self, listOfPartitions):
         test = listOfPartitions[0]
         shape = list(test.shape)
         shape[0] = sum([ p.shape[0] for p in listOfPartitions])
-        A = klass(shape)
+        A = numpy.ndarray(shape)
         N = shape[0]
         q = len(listOfPartitions)
         for p,part in enumerate(listOfPartitions):
             A[p:N:q] = part
         return A
     
     def flatten_list(self, listOfPartitions):
         flat = []
         for i in range(len(listOfPartitions[0])):
             flat.extend([ part[i] for part in listOfPartitions if len(part) > i ])
         return flat
-        #lengths = [len(x) for x in listOfPartitions]
-        #maxPartitionLength = len(listOfPartitions[0])
-        #numberOfPartitions = len(listOfPartitions)
-        #concat = self.concatenate(listOfPartitions)
-        #totalLength = len(concat)
-        #result = []
-        #for i in range(maxPartitionLength):
-        #    result.append(concat[i:totalLength:maxPartitionLength])
-        # return self.concatenate(listOfPartitions)
 
 def mappable(obj):
     """return whether an object is mappable or not."""
     if isinstance(obj, (tuple,list)):
         return True
-    for m in arrayModules:
-        if isinstance(obj,m['type']):
-            return True
+    if is_array(obj):
+        return True
     return False
 
 dists = {'b':Map,'r':RoundRobinMap}