def test_wc_add_stim_current():
u2 = WCUnit(name="u2")
stim = np.ones(10)
u2.add_stim_current(stimulus=stim, weight=.5)
assert u2.currents["stim"].weight == .5
u2.currents["stim"].update()
assert u2.stim[0] == 1
def test_wc_unit_init():
wc = WCUnit()
assert wc.tauNMDA == 100
wc2 = WCUnit(tau=200, foo="bar")
assert wc2.tau == 200
assert wc2.foo == "bar"
assert wc2.tauNMDA == 100
def __init__(self, name=None, best_frequency=440., spread=4., **kwargs):
"""
all the same things as WCUnit, but also has a bf and selectivity
Args:
best_frequency (float): the frequency (in hz) that best excites the cell
spread (float): inverse of selectivity, in terms of semitones to standard deviations
**kwargs:
"""
if not name:
name = "S" + str(best_frequency) + "-" + str(spread)
WCUnit.__init__(self, name=name, **kwargs)
key = music.frequency_to_key(best_frequency)
if music.key_to_frequency(key) != best_frequency:
print(
"warning- cell's response has been shifted to nearest semitone"
)
self.best_frequency = best_frequency
self.spread = spread
self.tuning_curve = self.fq_tuning_curve()
def test_add_SFA_current():
u2 = WCUnit(name="u2")
u2.add_SFA_current(weight=.8)
u2.r[0] = 1
u2.currents['SFA'].update()
assert u2.a[0] > 0
assert u2.currents['SFA'].weight < 0
assert u2.currents['SFA'].value > 0
u2.update()
assert u2.r[0] < 1
def test_update_all():
eps = .00001
u1 = WCUnit(name="u1", tauA=300, gSFA=0.8)
stim = np.ones(10)
u1.add_stim_current(stimulus=stim, weight=.9)
for ind in xrange(10):
u1.update_all()
assert u1.a[0] > 0
def test_no_negative_firing_rates_bugfix():
# TODO: if i get rid of my f0 offset so i can have f(0)=0 this breaks
u1 = WCUnit(name="u1", tauA=300, gSFA=0.8)
stim = np.ones(10) * -100
u1.add_stim_current(stimulus=stim, weight=.9)
for ind in xrange(10):
u1.update_all()
assert u1.r > 0
def test_wc_higher_weight_update():
u2 = WCUnit(name="u2")
stim = np.ones(10)
u2.add_stim_current(stimulus=stim, weight=.9)
assert u2.currents["stim"].weight == .9
u2.currents["stim"].t = 1
u2.currents["stim"].update()
u2.update()
assert u2.r[0] < 0.1
assert u2.r[0] > 0.098
def test_add_intrinsic_currents_SFA():
"""
i could wind up changing the defaults; i should just check that
the logical relationships follow
"""
eps = .00001
u1 = WCUnit(name="u1", tauA=300, gSFA=0.8, gee=0)
stim = np.ones(10)
u1.add_stim_current(stimulus=stim, weight=.9)
for ind in xrange(10):
u1.update_all()
assert u1.a[0] > 0
assert u1.currents["SFA"].value > 0
u2 = WCUnit(tauA=30, gSFA=0.8, gee=0)
stim = np.ones(10)
u2.add_stim_current(stimulus=stim, weight=.9)
for ind in xrange(10):
u2.update_all()
# tauA is shorter so there should be more
assert u2.a[0] > u1.a[0]
u3 = WCUnit(tauA=30, gSFA=0.5, gee=0)
stim = np.ones(10)
u3.add_stim_current(stimulus=stim, weight=.9)
for ind in xrange(10):
u3.update_all()
assert abs(u3.currents["SFA"].value -\
u2.currents["SFA"].value) < eps
assert abs(u3.a[0] - u2.a[0]) < eps
assert u1.r[0] - u2.r[0] > eps
assert u3.r[0] - u2.r[0] > eps
def test_stim_current_init():
u3 = WCUnit(name="u3")
stim = np.ones(10)
curr = StimCurrent(stim, .5, u3)
assert curr.target.name == "u3"
def test_non_default_pars():
pars = {"foos": "bars", "gee": 42}
u1 = WCUnit(**pars)
assert u1.gee == 42
u2 = WCUnit()
assert u2.gee == .57
# drive the stimulus forward
u1.currents["stim"].set_time(self.t_i)
for current in self.unit.currents.values():
current.update()
# update response
self.unit.update()
# update traces
for trace in self.traces.values():
trace.update_trace()
self.t_i += 1
if __name__ == '__main__':
tic = time.time()
u1 = WCUnit(name="u1", gSFA=0.3)
# TODO: the stimulus should get made with the same dt as sim
triplet = aba_triplet(iti=.08)
u1.add_stim_current(stimulus=triplet, weight=0.8)
#u1.add_SFA_current(weight=5)
sim = WCTripletsSimulation(wc_unit=u1, T=0.32)
sim.run()
traces = [[t.trace] for t in sim.traces.values()]
#print(traces)
# print(np.concatenate(traces))
generic_plot(sim.tax, np.concatenate(traces))
toc = time.time()
print toc - tic
plt.show()