nscanlines = int(input("\tnscanlines (usually 127) "))
npoints = int(input("\tnpoints (usually 1020) "))
junk = int(input("\tjunk (usually 36, or 1020 - 984) "))
# TODO use metadata instead of hard-coded values
header = Header()
header.w = nscanlines # input image width
header.h = npoints - junk # input image height, trimmed
header.sf = 4000000 # magic number, sorry!
probe = Probe()
probe.radius = 10000 # based on '10' in transducer model number
probe.numElements = 128 # based on '128' in transducer model number
probe.pitch = 185 # based on Ultrasonix C9-5/10 transducer
conv = Converter(header, probe)
rdr = RawReader(rf, nscanlines=nscanlines, npoints=npoints)
# define "support" file names based on .raw
wav = os.path.join(parent, str(basename + ".ch1.wav"))
sync = os.path.join(parent, str(basename + '.sync.txt'))
idx_txt = os.path.join(parent, str(basename + ".idx.txt"))
# make destination and copy "support" files for parent file
copy_dir = os.path.join(output_dir, basename)
os.mkdir(copy_dir)
shutil.copy(wav, copy_dir)
shutil.copy(idx_txt, copy_dir)
shutil.copy(stimfile, copy_dir)
# get frame indices
pass
header = Header()
print(header)
# visualize components on (approximately) converted fan, if desired
header.w = 127 # input image width
header.h = 1020 #255 # input image height
header.sf = 4000000 # for ultrasonix this is the vec-freq value
probe = Probe()
probe.radius = 10000 # based on '10' in transducer model number
probe.numElements = 128 # based on '128' in transducer model number
probe.pitch = 185 #205 # guess based on Ultrasonix C9-5/10 transducer
c = Converter(header, probe)
image_shape = (1020,127)#(255,127)
rdr = RawReader(rf, nscanlines=nscanlines, npoints = npoints)
print(rf)
for f in np.arange(0,(last_idx+1)):
d = rdr.get_frame(f).reshape(image_shape)
mag = np.max(d) - np.min(d)
d = (d-np.min(d))/mag*255
pcn = np.flipud(c.as_bmp(np.flipud(d)))
#pcn = c.as_bmp(d)
plt.title("Frame{:}, {:}".format((f+1),stim))
plt.imshow(pcn, cmap="Greys_r")
file_ending = "subj{:}-{:}-{:}.png".format(subject, stim,(f))
ultradir = os.path.join(os.path.basename(barename),file_ending)
savepath = os.path.join(expdir,ultradir)
print(savepath)
plt.savefig(savepath)
postbuf = 4
frameperc = int(last_idx * midperc)
print(frameperc)
frame_start = frameperc - prebuf
frame_end = frameperc + postbuf
print(frame_start)
print(frame_end)
consec_diffs = []
for f in np.arange(frame_start, frame_end):
# old method of getting frames
# minuend = get_frame(rf,f+1, myframesize, med_filter = True)
# subtrahend = get_frame(rf, f, myframesize, med_filter = True)
rdr = RawReader(
rf, nscanlines=nscanlines, npoints=npoints
) # or whatever the appropriate parameters actually are
minuend = rdr.get_frame(f + 1)
subtrahend = rdr.get_frame(f)
cdiff = minuend - subtrahend
cdiffnorm = np.linalg.norm(cdiff)
consec_diffs.append(cdiffnorm)
# print(consec_diffs)
mindiff, mindiff_idx = min(
(val, idx) for (idx, val) in enumerate(consec_diffs))
# print(mindiff)
# print(mindiff_idx)
rl_frame_idx = frame_start + mindiff_idx
print(rl_frame_idx)
# get frame, and check for NaN frames
change = 0
sync_tg = os.path.join(parent, str(acq + ".sync.TextGrid"))
idx_txt = os.path.join(parent, str(acq + ".idx.txt"))
# set up RawReader and frame dimensions
if data is None:
try:
nscanlines, npoints, junk = read_echob_metadata(rf)
except ValueError:
print("WARNING: no data in {}.img.txt, please input:".format(acq))
nscanlines = int(input("\tnscanlines (usually 127) "))
npoints = int(input("\tnpoints (usually 1020) "))
junk = int(input("\tjunk (usually 36, or 1020 - 984) "))
#frame_dim_1 = nscanlines
#frame_dim_2 = npoints - junk
rdr = RawReader(rf, nscanlines=nscanlines, npoints=npoints)
# instantiate LabelManagers
pm = audiolabel.LabelManager(from_file=tg, from_type="praat")
sync_pm = audiolabel.LabelManager(from_file=sync_tg, from_type="praat")
# extract ndarray representations of frames from .raw file
for v, m in pm.tier('phone').search(vre, return_match=True):
pron = pm.tier('word').label_at(v.center).text
# skip any tokens from non-target words
if pron not in target_list:
continue
# get phone label, disambiguating IY and IH based on pronunciation
# skip some IY (diphthongized variants in some words)
if conv is None:
print("Making converter...")
nscanlines, npoints, junk = read_echob_metadata(rf)
header = Header()
header.w = nscanlines # input image width
header.h = npoints - junk # input image height, trimmed
header.sf = 4000000 # magic number, sorry!
probe = Probe()
probe.radius = 10000 # based on '10' in transducer model number
probe.numElements = 128 # based on '128' in transducer model number
probe.pitch = 185 # based on Ultrasonix C9-5/10 transducer
conv = Converter(header, probe)
print("Now working on {}".format(parent))
rdr = RawReader(rf, nscanlines=nscanlines, npoints=npoints)
wav = os.path.join(parent, str(basename + ".ch1.wav"))
tg = os.path.join(parent, str(basename + ".ch1.TextGrid"))
sync_tg = os.path.join(parent, str(basename + ".sync.TextGrid"))
sync = os.path.join(parent, str(basename + '.sync.txt'))
idx_txt = os.path.join(parent, str(basename + ".idx.txt"))
# instantiate LabelManager objects for FA transcript and sync pulses
try:
pm = audiolabel.LabelManager(from_file=tg, from_type="praat")
except FileNotFoundError:
print("No alignment TG in {}; skipping".format(basename))
continue
try:
sync = os.path.join(parent, str(acq + '.sync.txt'))
sync_tg = os.path.join(parent, str(acq + ".sync.TextGrid"))
idx_txt = os.path.join(parent, str(acq + ".idx.txt"))
# instantiate RawReader, which extracts ultrasound data from .raw files
if data is None:
try:
nscanlines, npoints, junk = read_echob_metadata(rf)
except ValueError:
print("WARNING: no data in {}.img.txt".format(acq))
nscanlines = int(
input("\tnscanlines (usually 64) ")) # TODO update values
npoints = int(input("\tnpoints (usually 1024) "))
junk = int(input("\tjunk (usually 78) "))
rdr = RawReader(rf, nscanlines=nscanlines, npoints=npoints)
# instantiate LabelManager objects for FA transcript and sync pulses
try:
pm = audiolabel.LabelManager(from_file=tg, from_type="praat")
except FileNotFoundError:
print("No alignment TG in {}; skipping".format(acq))
continue
try:
sync_pm = audiolabel.LabelManager(from_file=sync_tg, from_type="praat")
except FileNotFoundError:
print("No sync TG in {}; skipping".format(acq))
continue
for seg, match in pm.tier('phones').search(seg_regexp, return_match=True):