def test_nested_mapper(self):
# Tests for nested mapping. Setting up the system (some arbitrary values, here)
wexploreMapper = WExploreBinMapper(n_regions=[4,4,4], d_cut=[2, .75, 0.25], dfunc=dfunc)
wexploreMapper.centers = [[2.5, 7.0]]
wexploreMapper.add_bin(None, 0)
outerMapper = FuncBinMapper(fn2,2)
recurseMapper = RecursiveBinMapper(outerMapper)
RectiMapper = RectilinearBinMapper([[10.00, float('inf')], [0.0, float('inf')]])
recurseMapper.add_mapper(wexploreMapper, [9.9, 0])
recurseMapper.add_mapper(RectiMapper, [10, 0])
bin_mapper = recurseMapper
# Now, begin testing setup...
assert bin_mapper.nbins == 2
wexploreMappers = []
for key,i in bin_mapper.mapper_list.iteritems():
if isinstance(i['base_mapper'], WExploreBinMapper) == True:
wexploreMappers.append(i)
self.wexploreMappers = wexploreMappers
wexploreMappers[0]['base_mapper'].add_bin(0,1)
bin_mapper.refresh_mappers()
assert bin_mapper.nbins == 3
class System(WESTSystem):
def initialize(self):
self.pcoord_ndim = 2
self.pcoord_len = 2
self.pcoord_dtype = numpy.float32
minfrag = 90
outer_mapper = RectilinearBinMapper([[0, minfrag - 0.5,
float('inf')], [0,
float('inf')]])
binbounds1 = [1.0 * i - 0.5
for i in xrange(minfrag, 121)] + [float('inf')]
binbounds2 = [15.0 * i * (i - 1) / 2
for i in xrange(1, 20)] + [float('inf')]
self.bin_mapper = RecursiveBinMapper(outer_mapper)
self.bin_mapper.add_mapper(
RectilinearBinMapper([binbounds1, binbounds2]), [minfrag, 1])
self.bin_target_counts = numpy.empty((self.bin_mapper.nbins, ),
numpy.int)
self.bin_target_counts[...] = 4
#this is intended to change the bins where distance < 200 A to 16 simulations per bin
for q1 in xrange(minfrag, 121):
for q2 in [0.5 + 15.0 * i * (i - 1) / 2 for i in xrange(1, 8)]:
print(q1, q2)
bin = self.bin_mapper.assign(numpy.array([(q1, q2)])) #tuple?
self.bin_target_counts[bin] = 16
class System(WESTSystem):
def initialize(self):
self.pcoord_ndim = 2
self.pcoord_len = 11
self.pcoord_dtype = numpy.float32
self.dist_binbounds = [10.00,float('inf')]
self.rmsd_bounds = [0.0, float('inf')]
self.wexploreMapper = wexplore.WExploreBinMapper(n_regions=[4,4,4], d_cut=[2, .75, 0.25], dfunc=dfunc)
self.wexploreMapper.centers = [[2.5, 7.0]]
self.wexploreMapper.add_bin(None, 0)
self.wexploreMapper.mask = np.array([[True, False]])
self.wexploreMapper.bin_target_counts = 64
self.initialize_mappers(self.wexploreMapper)
self.max_replicas = 64
self.bin_mapper.centers = [[2.5, 7.0]]
self.tstates = ['unbound,10.0,1.0']
self.n_regions = [6,4,4]
def initialize_mappers(self,wexploreMapper):
self.outerMapper = FuncBinMapper(fn2,2)
self.recurseMapper = RecursiveBinMapper(self.outerMapper)
self.RectiMapper = RectilinearBinMapper([self.dist_binbounds, self.rmsd_bounds])
self.RectiMapper.bin_target_counts = 3
self.recurseMapper.add_mapper(wexploreMapper, [4.99, 0])
self.recurseMapper.add_mapper(self.RectiMapper, [10, 0])
self.bin_mapper = self.recurseMapper
self.bin_target_counts = numpy.empty((self.bin_mapper.nbins,), numpy.int)
self.bin_target_counts[...] = 64
return self.bin_mapper
class SDASystem(WESTSystem):
'''
Class specify binning schemes, walker counts, and other core weighted
ensemble parameters.
'''
def initialize(self):
# pcoord dimensionality and length. This should match your outside bin
self.pcoord_ndim = 2
self.pcoord_len = pcoordlength
self.pcoord_dtype = pcoord_dtype
# These are your "outer" bins in both dimensions
outer_mapper = RectilinearBinMapper([[0.00, numpy.inf],
[0.00, 8.00, numpy.inf]])
# These define the "inner" adaptive bins. Each one indicates an independent
# adaptive binning scheme. Copy for more. Respects the parameters at the start.
adaptive_mapper0 = FuncBinMapper(function_map,
prod(binsperdim) + numberofdim *
(2 + 2 * splitIsolated) +
activetarget,
kwargs={"multi_idx": 0}) # Bottom bin
adaptive_mapper1 = FuncBinMapper(function_map,
prod(binsperdim) + numberofdim *
(2 + 2 * splitIsolated) +
activetarget,
kwargs={"multi_idx": 1}) # Top bin
# These are the bins where you'll place each adaptive scheme.
self.bin_mapper = RecursiveBinMapper(outer_mapper)
self.bin_mapper.add_mapper(adaptive_mapper0, [5, 1]) #Bottom mapper
self.bin_mapper.add_mapper(adaptive_mapper1, [5, 10]) #Top mapper
######################### JL ##########################################
# This is the what the example looks like.
#
# inf --------------------------------------------------------
# | |
# | adaptive_mapper1 |
# | |
# 8 --------------------------------------------------------
# D2 | | |
# | TARGET | adaptive_mapper0 |
# | STATE | |
# 0 --------------------------------------------------------
# 3.5(soft bound via mincap) inf
# Dimension 1 of pcoord
#
#######################################################################
self.bin_target_counts = numpy.empty((self.bin_mapper.nbins, ),
dtype=numpy.int)
# Number of walkers per bin
self.bin_target_counts[...] = bintargetcount
def initialize_mappers(self,wexploreMapper):
self.outerMapper = FuncBinMapper(fn2,2)
self.recurseMapper = RecursiveBinMapper(self.outerMapper)
self.RectiMapper = RectilinearBinMapper([self.dist_binbounds, self.rmsd_bounds])
self.RectiMapper.bin_target_counts = 3
self.recurseMapper.add_mapper(wexploreMapper, [4.99, 0])
self.recurseMapper.add_mapper(self.RectiMapper, [10, 0])
self.bin_mapper = self.recurseMapper
self.bin_target_counts = numpy.empty((self.bin_mapper.nbins,), numpy.int)
self.bin_target_counts[...] = 64
return self.bin_mapper
