| 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]. |
| """ |
| |
| 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)) |
| |
| |
| itrtimes = np.diff(self.trtimes) |
| badtrtimes = np.nonzero(itrtimes>(itrtimes.mean()*1.5))[0] |
| newtrs = [] |
| for btr in badtrtimes: |
| |
| 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 |
|
|
