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Backport PR #5584: more semantic icons...
Backport PR #5584: more semantic icons This adds classes to customize the folder and notebook document icons in the dashboard view. I've also changed the notebook icon to have it better distinguished from the folders and match e.g. Github's approach to this issue. For the pixel-perfectionist, I've also made these icons a fixed width (they weren't before, I'm sure, like me, it's made you angry ; ) screenshot is coming. closes #5555

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map.py
166 lines | 5.1 KiB | text/x-python | PythonLexer
# 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
#-------------------------------------------------------------------------------
from __future__ import division
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})
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)
# 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 isinstance(testObject, (list, tuple)):
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}