import pickle
from StringIO import StringIO
-import matplotlib
-matplotlib.use('Agg') # select backend that doesn't require X Windows
import numpy
-import pylab
from . import log
-from .histogram import Histogram
+from . import PYSAWSIM_LOG_LEVEL_MSG as _PYSAWSIM_LOG_LEVEL_MSG
+from .histogram import Histogram as _Histogram
+from .histogram import FIGURE as _FIGURE
from .sawsim_histogram import sawsim_histogram
from .sawsim import SawsimRunner
+# import after .histogram, which selects an appropriate backend
+import pylab
-FIGURE = pylab.figure() # avoid memory problems.
-"""`pylab` keeps internal references to all created figures, so share
-a single instance.
+_multiprocess_can_split_ = True
+"""Allow nosetests to split tests between processes.
"""
+
EXAMPLE_HISTOGRAM_FILE_CONTENTS = """# Velocity histograms
# Other general comments...
... '-s "unfolded,wlc,{0.39e-9,28e-9}" '
... '-k "folded,unfolded,bell,{%g,%g}" -q folded')
>>> m = ThreadManager()
- >>> sr = SawsimRunner(sawsim='bin/sawsim', manager=m)
+ >>> sr = SawsimRunner(manager=m)
>>> hm = HistogramMatcher(histogram_stream, param_format_string, sr, N=3)
>>> hm.plot([[1e-5,1e-3,3],[0.1e-9,1e-9,3]], logx=True, logy=False)
>>> m.teardown()
"""
def __init__(self, histogram_stream, param_format_string,
sawsim_runner, N=400, residual_type='jensen-shannon',
- plot=True):
+ plot=False):
self.experiment_histograms = self._read_force_histograms(
histogram_stream)
self.param_format_string = param_format_string
self.residual_type = residual_type
self._plot = plot
- def _read_force_histograms(self, stream):
+ @staticmethod
+ def _read_force_histograms(stream):
"""
File format:
for params,block in hist_blocks.iteritems():
if params == None:
continue
- h = Histogram()
+ h = _Histogram()
h.from_stream(StringIO('\n'.join(block)))
histograms[params] = h
return histograms
log().debug('residual %s: %g' % (params, residual))
return residual
- def plot(self, param_ranges, logx=False, logy=False, contour=False):
+ def plot(self, param_ranges, logx=False, logy=False, contour=False,
+ csv=None):
+ if csv:
+ csv.write(','.join(('param 1', 'param 2', 'fit quality')) + '\n')
xranges = param_ranges[0]
yranges = param_ranges[1]
if logx == False:
% (i, j, i*(len(y)-1) + j, (len(x)-1)*(len(y)-1)))
params = (xi,yj)
r = self.residual(params)
+ if csv:
+ csv.write(','.join([str(v) for v in (xi,yj,r)]) + '\n')
C[j,i] = numpy.log(r) # better resolution in valleys
if MEM_DEBUG == True:
log().debug('RSS: %d KB' % rss())
# import pickle
# [X,Y,C] = pickle.load(file("histogram_matcher-XYC.pkl", "rb"))
# ...
- FIGURE.clear()
- axes = FIGURE.add_subplot(111)
+ _FIGURE.clear()
+ axes = _FIGURE.add_subplot(1, 1, 1)
if logx == True:
axes.set_xscale('log')
if logy == True:
else: # pseudocolor plot
p = axes.pcolor(X, Y, C)
axes.autoscale_view(tight=True)
- FIGURE.colorbar(p)
- FIGURE.savefig("figure.png")
+ _FIGURE.colorbar(p)
+ _FIGURE.savefig("figure.png")
def _plot_residual_comparison(self, experiment_hist, theory_hist,
residual, title, filename):
- FIGURE.clear()
- p = pylab.plot(experiment_hist.bin_edges[:-1],
- experiment_hist.probabilities, 'r-',
- theory_hist.bin_edges[:-1],
- theory_hist.probabilities, 'b-')
- pylab.title(title)
- FIGURE.savefig(filename)
+ _FIGURE.clear()
+ axes = _FIGURE.add_subplot(1, 1, 1)
+ axes.hold(True)
+ axes.hist(x=experiment_hist.bin_edges[:-1], # one fake entry for each bin
+ weights=experiment_hist.counts, # weigh the fake entries by count
+ bins=experiment_hist.bin_edges,
+ align='mid', histtype='stepfilled',
+ color='r')
+ axes.hist(x=theory_hist.bin_edges[:-1], # one fake entry for each bin
+ weights=theory_hist.counts, # weigh the fake entries by count
+ bins=theory_hist.bin_edges,
+ align='mid', histtype='stepfilled',
+ color='b', alpha=0.5)
+ axes.set_title(title)
+ _FIGURE.savefig(filename)
def parse_param_ranges_string(string):
>>> f = tempfile.NamedTemporaryFile()
>>> f.write(EXAMPLE_HISTOGRAM_FILE_CONTENTS)
>>> f.flush()
- >>> main(['-s', 'bin/sawsim',
- ... '-r', '[1e-5,1e-3,3],[0.1e-9,1e-9,3]',
+ >>> main(['-r', '[1e-5,1e-3,3],[0.1e-9,1e-9,3]',
... '-N', '2',
... f.name])
>>> f.close()
'`<bin_edge>` should mark the left-hand side of the bin, and',
'all bins should be of equal width (so we know where the last',
'one ends).',
+ _PYSAWSIM_LOG_LEVEL_MSG,
])
parser = OptionParser(usage, epilog=epilog)
parser.format_epilog = lambda formatter: epilog+'\n'
if option.dest == 'param_string':
continue
parser.add_option(option)
- parser.add_option("-f","--param-format", dest="param_format",
- metavar="FORMAT",
- help="Convert params to sawsim options (%default).",
+ parser.add_option('-f','--param-format', dest='param_format',
+ metavar='FORMAT',
+ help='Convert params to sawsim options (%default).',
default=('-s cantilever,hooke,0.05 -N1 -s folded,null -N8 -s "unfolded,wlc,{0.39e-9,28e-9}" -k "folded,unfolded,bell,{%g,%g}" -q folded'))
- parser.add_option("-p","--initial-params", dest="initial_params",
- metavar="PARAMS",
- help="Initial params for fitting (%default).",
+ parser.add_option('-p','--initial-params', dest='initial_params',
+ metavar='PARAMS',
+ help='Initial params for fitting (%default).',
default='3.3e-4,0.25e-9')
- parser.add_option("-r","--param-range", dest="param_range",
- metavar="PARAMS",
- help="Param range for plotting (%default).",
+ parser.add_option('-r','--param-range', dest='param_range',
+ metavar='PARAMS',
+ help='Param range for plotting (%default).',
default='[1e-5,1e-3,20],[0.1e-9,1e-9,20]')
- parser.add_option("--logx", dest="logx",
- help="Use a log scale for the x range.",
- default=False, action="store_true")
- parser.add_option("--logy", dest="logy",
- help="Use a log scale for the y range.",
- default=False, action="store_true")
- parser.add_option("-R","--residual", dest="residual",
- metavar="STRING",
- help="Residual type (from %s; default: %%default)."
- % ', '.join(Histogram().types()),
+ parser.add_option('--logx', dest='logx',
+ help='Use a log scale for the x range.',
+ default=False, action='store_true')
+ parser.add_option('--logy', dest='logy',
+ help='Use a log scale for the y range.',
+ default=False, action='store_true')
+ parser.add_option('-R','--residual', dest='residual',
+ metavar='STRING',
+ help='Residual type (from %s; default: %%default).'
+ % ', '.join(_Histogram().types()),
default='jensen-shannon')
- parser.add_option("-P","--plot-residuals", dest="plot_residuals",
- help="Generate residual difference plots for each point in the plot range.",
- default=False, action="store_true")
- parser.add_option("-c","--contour-plot", dest="contour_plot",
- help="Select contour plot (vs. the default pseudocolor plot).",
- default=False, action="store_true")
+ parser.add_option('-P','--plot-residuals', dest='plot_residuals',
+ help='Generate residual difference plots for each point in the plot range.',
+ default=False, action='store_true')
+ parser.add_option('-c','--contour-plot', dest='contour_plot',
+ help='Select contour plot (vs. the default pseudocolor plot).',
+ default=False, action='store_true')
+ parser.add_option('--csv', dest='csv', metavar='FILE',
+ help='Save fit qualities to a comma-separated value file FILE.'),
options,args = parser.parse_args(argv)
initial_params = [float(p) for p in options.initial_params.split(",")]
param_ranges = parse_param_ranges_string(options.param_range)
histogram_file = args[0]
+ csv = None
sr_call_params = sr.initialize_from_options(options)
try:
sawsim_runner=sr, residual_type=options.residual,
plot=options.plot_residuals, **sr_call_params)
#hm.fit(initial_params)
+ if options.csv:
+ csv = open(options.csv, 'w')
hm.plot(param_ranges, logx=options.logx, logy=options.logy,
- contour=options.contour_plot)
+ contour=options.contour_plot, csv=csv)
finally:
sr.teardown()
+ if csv:
+ csv.close()
projects / sawsim.git / blobdiff