IPython/parallel/client/map.py

# 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.
"""

# 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


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
        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
        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, listOfPartitions):
        test = listOfPartitions[0]
        shape = list(test.shape)
        shape[0] = sum([ p.shape[0] for p in listOfPartitions])
        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

def mappable(obj):
    """return whether an object is mappable or not."""
    if isinstance(obj, (tuple,list)):
        return True
    if is_array(obj):
        return True
    return False

dists = {'b':Map,'r':RoundRobinMap}