##// END OF EJS Templates
Add function to handle u'abc' (Python 2) vs. 'abc' (Python 3) in doctests and similar.
Add function to handle u'abc' (Python 2) vs. 'abc' (Python 3) in doctests and similar.

File last commit:

r4155:a82262e5
r4894:15d093bf
Show More
map.py
165 lines | 5.1 KiB | text/x-python | PythonLexer
MinRK
add map/scatter/gather/ParallelFunction from kernel
r3587 # 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.
MinRK
update recently changed modules with Authors in docstring
r4018
Authors:
* Brian Granger
* MinRK
MinRK
add map/scatter/gather/ParallelFunction from kernel
r3587 """
#-------------------------------------------------------------------------------
MinRK
update recently changed modules with Authors in docstring
r4018 # Copyright (C) 2008-2011 The IPython Development Team
MinRK
add map/scatter/gather/ParallelFunction from kernel
r3587 #
# Distributed under the terms of the BSD License. The full license is in
# the file COPYING, distributed as part of this software.
#-------------------------------------------------------------------------------
#-------------------------------------------------------------------------------
# Imports
#-------------------------------------------------------------------------------
MinRK
update parallel code for py3k...
r4155 from __future__ import division
MinRK
add map/scatter/gather/ParallelFunction from kernel
r3587 import types
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})
class Map:
"""A class for partitioning a sequence using a map."""
def getPartition(self, seq, p, q):
"""Returns the pth partition of q partitions of seq."""
# Test for error conditions here
if p<0 or p>=q:
print "No partition exists."
return
remainder = len(seq)%q
MinRK
update parallel code for py3k...
r4155 basesize = len(seq)//q
MinRK
add map/scatter/gather/ParallelFunction from kernel
r3587 hi = []
lo = []
for n in range(q):
if n < remainder:
lo.append(n * (basesize + 1))
hi.append(lo[-1] + basesize + 1)
else:
lo.append(n*basesize + remainder)
hi.append(lo[-1] + basesize)
result = seq[lo[p]:hi[p]]
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)
# Next try for Python sequence types
if isinstance(testObject, (types.ListType, types.TupleType)):
return utils_flatten(listOfPartitions)
# If we have scalars, just return listOfPartitions
return listOfPartitions
class RoundRobinMap(Map):
"""Partitions a sequence in a roun robin fashion.
This currently does not work!
"""
def getPartition(self, seq, p, q):
# if not isinstance(seq,(list,tuple)):
# raise NotImplementedError("cannot RR partition type %s"%type(seq))
return seq[p:len(seq):q]
#result = []
#for i in range(p,len(seq),q):
# result.append(seq[i])
#return result
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 isinstance(testObject, (types.ListType, types.TupleType)):
return self.flatten_list(listOfPartitions)
return listOfPartitions
def flatten_array(self, klass, listOfPartitions):
test = listOfPartitions[0]
shape = list(test.shape)
shape[0] = sum([ p.shape[0] for p in listOfPartitions])
A = klass(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
return False
dists = {'b':Map,'r':RoundRobinMap}