def resample(self,system):
"""
A resampling that pulls walker cell assignments from an external file
and then resamples the whole system under MultiColor. Given that the
assignments are left in post-mapping state at the end of the method,
it cannot be used multiple times.
Parameters:
system - a processed aweclasses.System object
Returns:
A new aweclasses.System instance representing the resampled input
system
"""
cellmap = self.cellmap
# Determine the cell that each walker is assigned to so that
# cells can be stored in some arbitrary order (?)
for w in system.walkers:
w.assignment = cellmap[w.assignment]
# Perform MultiColor resampling
newsystem = MultiColor.resample(self,system)
# Save the transition matrix
tmat = os.path.join(OUTPUT_DIR, 'transition-matrix.csv')
makedirs_parent(tmat)
MultiColor.save_transitions(tmat)
return newsystem
def __init__(self, targetwalkers):
self.targetwalkers = targetwalkers
#####
self.histfile = os.path.join(OUTPUT_DIR, 'walker-history.csv')
makedirs_parent(self.histfile)
with open(self.histfile, 'a') as fd:
fd.write('%origID, parentID, currentID \n')
def __init__(self, targetwalkers):
self.targetwalkers = targetwalkers
#####
self.histfile = os.path.join(OUTPUT_DIR, 'walker-history.csv')
makedirs_parent(self.histfile)
with open(self.histfile, 'a') as fd:
fd.write('%origID, parentID, currentID \n')
def resample(self, system):
cellmap = self.cellmap
for w in system.walkers:
w.assignment = cellmap[w.assignment]
newsystem = MultiColor.resample(self, system)
tmat = os.path.join(OUTPUT_DIR, 'transition-matrix.csv')
makedirs_parent(tmat)
MultiColor.save_transitions(tmat)
return newsystem
def resample(self,system):
cellmap = self.cellmap
for w in system.walkers:
w.assignment = cellmap[w.assignment]
newsystem = MultiColor.resample(self,system)
tmat = os.path.join(OUTPUT_DIR, 'transition-matrix.csv')
makedirs_parent(tmat)
MultiColor.save_transitions(tmat)
return newsystem
def __init__(self, targetwalkers):
"""
Initialize a new instance of OneColor.
Parameters:
targetwalkers - a list of target weights to converge to (numeric)
Returns:
None
"""
self.targetwalkers = targetwalkers
#####
self.histfile = os.path.join(OUTPUT_DIR, 'walker-history.csv')
makedirs_parent(self.histfile)
with open(self.histfile, 'a') as fd:
fd.write('%origID, parentID, currentID \n')
def __init__(self, nwalkers, partition):
OneColor.__init__(self, nwalkers)
self.partition = partition
ncolors = partition.ncolors
self.transitions = np.zeros((ncolors, ncolors))
self.iteration = 1
self.cellweights_path = os.path.join(OUTPUT_DIR, 'cell-weights.csv')
makedirs_parent(self.cellweights_path)
of = open(self.cellweights_path, 'a')
of.write('%iteration,cellid,color,total_weight \n')
of.close()
self.tmat_path = os.path.join(OUTPUT_DIR,
'color-transition-matrix.csv')
self.tmat_header = textwrap.dedent("""\
# An ((N+1)*2, 2, 2) matrix, where N is the number of iterations
# Can be loaded like:
# m = np.loadtxt("color-transitions-matrix.csv",delimiter=",")
# itrs = m.shape[0] / 2
# T = m.reshape((itrs, 2, 2))
""")
def __init__(self, nwalkers, partition):
OneColor.__init__(self, nwalkers)
self.partition = partition
ncolors = partition.ncolors
self.transitions = np.zeros((ncolors, ncolors))
self.iteration = 1
self.cellweights_path = os.path.join(OUTPUT_DIR, 'cell-weights.csv')
makedirs_parent(self.cellweights_path)
of = open(self.cellweights_path,'a')
of.write('%iteration,cellid,color,total_weight \n')
of.close()
self.tmat_path = os.path.join(OUTPUT_DIR, 'color-transition-matrix.csv')
self.tmat_header = textwrap.dedent(
"""\
# An ((N+1)*2, 2, 2) matrix, where N is the number of iterations
# Can be loaded like:
# m = np.loadtxt("color-transitions-matrix.csv",delimiter=",")
# itrs = m.shape[0] / 2
# T = m.reshape((itrs, 2, 2))
"""
)
class MultiColor(OneColor):
"""
A resampler for handling multiple macro-states (metastable states)
by following transitions between states and resampling each
individually.
Fields:
targetwalkers - the number of walkers, creates a target weight
histfile - the path to walker-history.csv
partition - awe.aweclasses.SinkStates instance
transitions - a matrix containing transition rates between
macro-states
iteration - the current iteration of the
cellweights_path - the path to cell-weights.csv
tmat_path - the path to color-transition-matrix.csv
tmat_header - the header for the color-transition-matrix.csv file
Methods:
resample - resample across multiple states
save_transitions - output the state transition matrix
"""
def __init__(self, nwalkers, partition):
"""
Initialize a new instance of MultiColor.
Parameters:
nwalkers - the target number of walkers
partition - an aweclasses.SinkStates instance
Returns:
None
"""
# Set up the output filepath and target weights
OneColor.__init__(self, nwalkers)
# Partitioning of the states (e.g. conformation space cells)
self.partition = partition
ncolors = partition.ncolors
# Matrix to store transitions between states
self.transitions = np.zeros((ncolors, ncolors))
self.iteration = 1
# PAths to output files and necessary header information
self.cellweights_path = os.path.join(OUTPUT_DIR, 'cell-weights.csv')
makedirs_parent(self.cellweights_path)
of = open(self.cellweights_path,'a')
of.write('%iteration,cellid,color,total_weight \n')
of.close()
self.tmat_path = os.path.join(OUTPUT_DIR,
'color-transition-matrix.csv')
self.tmat_header = textwrap.dedent(
"""\
# An ((N+1)*2, 2, 2) matrix, where N is the number of iterations
# Can be loaded like:
# m = np.loadtxt("color-transitions-matrix.csv",delimiter=",")
# itrs = m.shape[0] / 2
# T = m.reshape((itrs, 2, 2))
"""
)
