def test_chirp():
f0 = 13.5
f1 = f0 * 100
dur = 0.8
amp = 0.1
off = 0.5
ph = 2.1
stim = stimuli.Chirp(start_time=0.1,
start_frequency=f0,
end_frequency=f1,
duration=dur,
amplitude=amp,
offset=off,
phase=ph)
npts = 10000
dt = 0.0001
eval_data = stim.eval(t0=0, n_pts=npts, dt=dt).data
mask_data = stim.mask(t0=0, n_pts=npts, dt=dt).data
test_data = np.zeros(npts)
# sin[2 pi f(0) d (f(d) / f(0))^(t / d) / ln(f(d) / f(0)]
t = np.arange(8000) * dt
w = 2 * np.pi * f0 * dur * (f1 / f0)**(t / dur) / np.log(f1 / f0)
test_data[1000:9000] = off + amp * np.sin(w + ph - w[0])
assert np.allclose(eval_data, test_data)
assert np.all(mask_data == (eval_data != 0))
# test eval with first timepoint not at beginning of chirp
t2 = np.arange(5000, 10000) * dt
assert np.allclose(stim.eval(time_values=t2).data, eval_data[5000:])
# measure approximate frequency by interpolated zero-crossings
d = eval_data[1000:9000] - off
inds = np.where(np.diff(np.sign(d)))[0]
d0 = d[inds]
d1 = d[inds + 1]
s = abs(d0) / abs(d1 - d0)
zeros = (inds + s) * dt
freqs = 0.5 / np.diff(zeros)
# check endpoints
assert (abs(freqs[0] / f0) - 1.0) < 0.3
assert (abs(freqs[-1] / f1) - 1.0) < 0.1
# check center
ind = np.argwhere(zeros > 0.4)[0, 0]
assert (abs(freqs[ind] / (f0 * 10)) - 1.0) < 0.1
# test analytically determined frequencies
freqs = f0**np.linspace(1, np.log(f1) / np.log(f0), len(t) + 1)[:-1]
assert np.allclose(freqs, stim.frequency_at(t))
def load_stimulus_items(self, rec):
items = []
# Add holding offset, determine units
if rec.clamp_mode == 'ic':
units = 'A'
items.append(
stimuli.Offset(
start_time=0,
amplitude=rec.holding_current,
description="holding current",
units=units,
))
elif rec.clamp_mode == 'vc':
units = 'V'
items.append(
stimuli.Offset(
start_time=0,
amplitude=rec.holding_potential,
description="holding potential",
units=units,
))
else:
units = None
# inserted test pulse?
#if rec.has_inserted_test_pulse:
# self.append_item(rec.inserted_test_pulse.stimulus)
if rec.test_pulse is not None:
items.append(rec.test_pulse.stimulus)
notebook = rec.meta['notebook']
if 'Stim Wave Note' in notebook:
# Stim Wave Note format is explained here:
# https://alleninstitute.github.io/MIES/file/_m_i_e_s___wave_builder_8ipf.html#_CPPv319WB_GetWaveNoteEntry4wave8variable6string8variable8variable
# read stimulus structure from notebook
#version, epochs = rec._stim_wave_note()
version, epochs = parser.parse_stim_wave_note(notebook)
assert len(epochs) > 0
scale = (1e-3 if rec.clamp_mode == 'vc' else
1e-12) * notebook['Stim Scale Factor']
t = (notebook['Delay onset oodDAQ'] + notebook['Delay onset user']
+ notebook['Delay onset auto']) * 1e-3
# if dDAQ is active, add delay from previous channels
if notebook['Distributed DAQ'] == 1.0:
ddaq_delay = notebook['Delay distributed DAQ'] * 1e-3
for dev in rec.parent.devices:
other_rec = rec.parent[dev]
if other_rec is rec:
break
#_, epochs = rec._stim_wave_note()
if 'Stim Wave Note' in other_rec.meta['notebook']:
_, other_epochs = parser.parse_stim_wave_note(
other_rec.meta['notebook'])
for ep in other_epochs:
dt = float(ep.get('Duration', 0)) * 1e-3
t += dt
t += ddaq_delay
for epoch_n, epoch in enumerate(epochs):
try:
if epoch['Epoch'] == 'nan':
# Sweep-specific entry; not sure if we need to do anything with this.
continue
stim_type = epoch.get('Type')
duration = float(epoch.get('Duration', 0)) * 1e-3
name = "Epoch %d" % int(epoch['Epoch'])
if stim_type == 'Square pulse':
item = stimuli.SquarePulse(
start_time=t,
amplitude=float(epoch['Amplitude']) * scale,
duration=duration,
description=name,
units=units,
)
elif stim_type == 'Pulse Train':
assert epoch[
'Poisson distribution'] == 'False', "Poisson distributed pulse train not supported"
assert epoch[
'Mixed frequency'] == 'False', "Mixed frequency pulse train not supported"
assert epoch[
'Pulse Type'] == 'Square', "Pulse train with %s pulse type not supported"
item = stimuli.SquarePulseTrain(
start_time=t,
n_pulses=int(epoch['Number of pulses']),
pulse_duration=float(epoch['Pulse duration']) *
1e-3,
amplitude=float(epoch['Amplitude']) * scale,
interval=float(epoch['Pulse To Pulse Length']) *
1e-3,
description=name,
units=units,
)
elif stim_type == 'Sin Wave':
# bug in stim wave note version 2: log chirp field is inverted
is_chirp = epoch['Log chirp'] == (
'False' if version <= 2 else 'True')
if is_chirp:
assert epoch[
'FunctionType'] == 'Sin', "Chirp wave function type %s not supported" % epoch[
'Function type']
item = stimuli.Chirp(
start_time=t,
start_frequency=float(epoch['Frequency']),
end_frequency=float(epoch['End frequency']),
duration=duration,
amplitude=float(epoch['Amplitude']) * scale,
phase=0,
offset=float(epoch['Offset']) * scale,
description=name,
units=units,
)
else:
if epoch['FunctionType'] == 'Sin':
phase = 0
elif epoch['FunctionType'] == 'Cos':
phase = np.pi / 2.0
else:
raise ValueError(
"Unsupported sine wave function type: %r" %
epoch['FunctionType'])
item = stimuli.Sine(
start_time=t,
frequency=float(epoch['Frequency']),
duration=duration,
amplitude=float(epoch['Amplitude']) * scale,
phase=phase,
offset=float(epoch['Offset']) * scale,
description=name,
units=units,
)
else:
print(epoch)
print(
"Warning: unknown stimulus type %s in %s sweep %s"
% (stim_type, self._file_path,
rec.meta['sweep_name']))
item = None
except Exception as exc:
print(
"Warning: error reading stimulus epoch %d in %s sweep %s: %s"
% (epoch_n, self._file_path, rec.meta['sweep_name'],
str(exc)))
t += duration
if item is not None:
items.append(item)
return items