File size: 2,733 Bytes
0b416c6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | import os
import numpy as np
from os.path import join, dirname
from ridge_utils.textgrid import TextGrid
def load_textgrids(stories, data_dir: str):
""" TODO (shailee): Add description."""
base = join(data_dir, "ds003020/derivative/TextGrids")
grids = {}
for story in stories:
grid_path = os.path.join(base, "%s.TextGrid"%story)
grids[story] = TextGrid(open(grid_path).read())
return grids
class TRFile(object):
def __init__(self, trfilename, expectedtr=2.0045):
"""Loads data from [trfilename], should be output from stimulus presentation code.
"""
self.trtimes = []
self.soundstarttime = -1
self.soundstoptime = -1
self.otherlabels = []
self.expectedtr = expectedtr
if trfilename is not None:
self.load_from_file(trfilename)
def load_from_file(self, trfilename):
"""Loads TR data from report with given [trfilename].
"""
## Read the report file and populate the datastructure
for ll in open(trfilename):
timestr = ll.split()[0]
label = " ".join(ll.split()[1:])
time = float(timestr)
if label in ("init-trigger", "trigger"):
self.trtimes.append(time)
elif label=="sound-start":
self.soundstarttime = time
elif label=="sound-stop":
self.soundstoptime = time
else:
self.otherlabels.append((time, label))
## Fix weird TR times
itrtimes = np.diff(self.trtimes)
badtrtimes = np.nonzero(itrtimes>(itrtimes.mean()*1.5))[0]
newtrs = []
for btr in badtrtimes:
## Insert new TR where it was missing..
newtrtime = self.trtimes[btr]+self.expectedtr
newtrs.append((newtrtime,btr))
for ntr,btr in newtrs:
self.trtimes.insert(btr+1, ntr)
def simulate(self, ntrs):
"""Simulates [ntrs] TRs that occur at the expected TR.
"""
self.trtimes = list(np.arange(ntrs)*self.expectedtr)
def get_reltriggertimes(self):
"""Returns the times of all trigger events relative to the sound.
"""
return np.array(self.trtimes)-self.soundstarttime
@property
def avgtr(self):
"""Returns the average TR for this run.
"""
return np.diff(self.trtimes).mean()
def load_simulated_trfiles(respdict, tr=2.0, start_time=10.0, pad=5):
trdict = dict()
for story, resps in respdict.items():
trf = TRFile(None, tr)
trf.soundstarttime = start_time
trf.simulate(resps - pad)
trdict[story] = [trf]
return trdict
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