def __call__(self, plgfile):
"""
Calculate summary statistics for the input file. Returns a
dictionary if the operation succeeded; raises a ValueError object if
not.
"""
import numpy as nx
from chirp.common import plg
estimator = self.options['estimator']
p = plg.read(plgfile)
if estimator not in p.dtype.names: raise ValueError, "estimator %s is missing" % estimator
ind = self.postfilter(p)
ind &= nx.isfinite(p[estimator])
pfilt = p[ind]
pitch = pfilt[estimator]
if pfilt.size == 0: raise ValueError("no valid points after filtering")
return {'nelements': nx.unique(pfilt['element']).size,
'duration': pfilt['time'].max() - pfilt['time'].min(),
'pitch.mean': nx.mean(pitch),
'pitch.std': nx.std(pitch),
'pitch.median': nx.median(pitch),
'pitch.max': nx.max(pitch),
'pitch.min': nx.min(pitch),
'pow.mean': nx.mean(pfilt['stim.pow']),
'dropped.points': p.size - pfilt.size}
def load_data(basename, filterer=None, pitchdir=None):
"""
Load data from wav and plg files. If filterer is not None, filters
pitch trace.
"""
from ewave import wavfile
from chirp.common import plg
fp = wavfile(basename + ".wav")
signal, Fs = fp.read(), fp.sampling_rate
if isinstance(pitchdir, basestring):
plgfile = os.path.join(pitchdir, os.path.split(basename)[1] + '.plg')
else:
plgfile = basename + '.plg'
if not os.path.exists(plgfile):
return signal, Fs / 1000., None, None
pitch = plg.read(plgfile)
if filterer is not None:
ind = postfilter.ind_endpoints(filterer(pitch))
if ind is None:
return signal, Fs / 1000., None, None
pitch = pitch[ind[0]:ind[1] + 1]
t = pitch['time']
if 'p.map' in pitch.dtype.names:
p = pitch['p.map']
else:
p = pitch['p.mmse']
return signal, Fs / 1000., t, p
def _load_plg(locator, filt, estimator):
"""
Load a pitch trace and filters it. If no points are
reliable, returns None.
"""
from chirp.common import plg
pest = plg.read(locator)
ind = filt(pest)
if not any(ind):
return None
else:
ind = postfilter.ind_endpoints(ind)
return pest[estimator][ind[0]:ind[1] + 1]
def plot_plg(self, plgfile):
"""
Read data from a plg file and plot it. This is a single trace
because estimates are collapsed across chains.
"""
pest = plg.read(plgfile)
t = pest['time']
if 'p.map' in pest.dtype.names:
f = pest['p.map']
else:
f = pest['p.mmse']
ind = self.filter(pest)
self.remove_trace()
self.add_trace(t[ind], f[ind])
self.add_trace(t[~ind], f[~ind], color='k')