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output.py
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from collections import Iterable
import operator
import sys
import numpy
def drift_velocity(sde, *args):
ret = []
for starting, final in args:
a = starting.astype(numpy.float64)
b = final.astype(numpy.float64)
ret.append((numpy.average(b) - numpy.average(a)) /
(sde.sim_t - sde.start_t))
return ret
def abs_drift_velocity(sde, *args):
ret = []
for starting, final in args:
a = starting.astype(numpy.float64)
b = final.astype(numpy.float64)
ret.append(numpy.average(numpy.abs(b - a)) /
(sde.sim_t - sde.start_t))
return ret
def diffusion_coefficient(sde, *args):
ret = []
for starting, final in args:
a = starting.astype(numpy.float64)
b = final.astype(numpy.float64)
deff1 = numpy.average(numpy.square(b)) - numpy.average(b)**2
deff2 = numpy.average(numpy.square(a)) - numpy.average(a)**2
# ret.append((deff1 - deff2) / (2.0 * (sde.sim_t - sde.start_t)))
ret.append(deff1 / (2.0 * sde.sim_t))
ret.append(deff2 / (2.0 * sde.start_t))
return ret
def avg_moments(sde, *args):
ret = []
for arg in args:
ret.append(numpy.average(arg))
ret.append(numpy.average(numpy.square(arg)))
return ret
class TextOutput(object):
def __init__(self, sde, subfiles):
self.sde = sde
self.subfiles = subfiles
self.out = {}
if sde.options.output is not None:
self.out['main'] = open(sde.options.output, 'w')
for sub in subfiles:
if sub == 'main':
continue
self.out[sub] = open('%s_%s' % (sde.options.output, sub), 'w')
else:
if len(subfiles) > 1:
raise ValueError('Output file name required so that auxiliary data stream can be saved.')
self.out['main'] = sys.stdout
def finish_block(self):
print >>self.out['main'], ''
def flush(self):
self.out['main'].flush()
def data(self, **kwargs):
for name, val in kwargs.iteritems():
def my_rep(val):
if isinstance(val, Iterable):
return ' '.join(my_rep(x) for x in val)
else:
return str(val)
rep = [my_rep(x) for x in val]
print >>self.out[name], ' '.join(rep)
def header(self):
out = self.out['main']
print >>out, '# %s' % ' '.join(sys.argv)
if self.sde.options.seed is not None:
print >>out, '# seed = %d' % self.sde.options.seed
print >>out, '# sim periods = %d' % self.sde.options.simperiods
print >>out, '# transient periods = %d' % self.sde.options.transients
print >>out, '# samples = %d' % self.sde.options.samples
print >>out, '# paths = %d' % self.sde.options.paths
print >>out, '# spp = %d' % self.sde.options.spp
for par in self.sde.parser.par_single:
print >>out, '# %s = %f' % (par, self.sde.options.__dict__[par])
for par in self.sde.par_multi_ordered:
print >>out, '# %s = %s' % (par, ' '.join(str(x) for x in self.sde.options.__dict__[par]))
for par in self.sde.scan_vars:
print >>out, '# %s = %s' % (par, ' '.join(str(x) for x in self.sde.options.__dict__[par]))
def close(self):
pass
class NpyOutput(object):
def __init__(self, sde, subfiles):
self.sde = sde
self.subfiles = subfiles
# This dictionary maps the subfile name to a list of lists.
# Every entry in the outer list represents one point in the
# parameter space. The inner list represents the results for
# a particular set of parameters.
self.cache = {}
def finish_block(self):
pass
def flush(self):
self.close()
def data(self, **kwargs):
for name, val in kwargs.iteritems():
self.cache.setdefault(name, []).append(val)
def header(self):
self.cmdline = '%s' % ' '.join(sys.argv)
self.scan_vars = self.sde.scan_vars
self.par_multi_ordered = self.sde.par_multi_ordered
def close(self):
out = {}
shape = []
for par in self.par_multi_ordered:
out[par] = getattr(self.sde.options, par)
shape.append(len(out[par]))
for sv in self.scan_vars:
out[sv] = getattr(self.sde.options, sv)
shape.append(len(out[sv]))
for name, val in self.cache.iteritems():
inner_len = max(len(x) for x in val)
out[name] = numpy.array(val, dtype=self.sde.float)
if shape and reduce(operator.mul, shape) * inner_len == reduce(operator.mul, out[name].shape):
out[name] = numpy.reshape(out[name], shape + [inner_len])
numpy.savez(self.sde.options.output, cmdline=self.cmdline, scan_vars=self.scan_vars,
par_multi=self.par_multi_ordered, options=self.sde.options, **out)
class StoreOutput(object):
def __init__(self, sde, subfiles):
self.sde = sde
self.subfiles = subfiles
self.cache = {}
def finish_block(self):
pass
def flush(self):
pass
def data(self, **kwargs):
for name, val in kwargs.iteritems():
self.cache.setdefault(name, []).append(val)
def header(self):
self.scan_vars = self.sde.scan_vars
self.par_multi_ordered = self.sde.par_multi_ordered
def close(self):
out = {}
shape = []
for par in self.par_multi_ordered:
out[par] = getattr(self.sde.options, par)
shape.append(len(out[par]))
for sv in self.scan_vars:
out[sv] = getattr(self.sde.options, sv)
shape.append(len(out[sv]))
for name, val in self.cache.iteritems():
inner_len = max(len(x) for x in val)
out[name] = numpy.array(val, dtype=self.sde.float)
if shape and reduce(operator.mul, shape) * inner_len == reduce(operator.mul, out[name].shape):
out[name] = numpy.reshape(out[name], shape + [inner_len])
self.out = out