def prun(tstop, restore=False):
pc.set_maxstep(10 * ms)
h.finitialize(-65 * mV)
if restore == "SaveState":
ns = h.SaveState()
sf = h.File("state%d.bin" % pc.id())
ns.fread(sf)
ns.restore(0) # event queue restored
sf.close()
elif restore == "BBSaveState":
cp_out_to_in() # prepare for restore.
bbss = h.BBSaveState()
bbss.restore_test()
else:
pc.psolve(tstop / 2)
# SaveState save
ss = h.SaveState()
ss.save()
sf = h.File("state%d.bin" % pc.id())
ss.fwrite(sf)
sf.close()
# BBSaveState Save
cnt = h.List("PythonObject").count()
for i in range(1):
bbss = h.BBSaveState()
bbss.save_test()
bbss = None
assert h.List("PythonObject").count() == cnt
pc.psolve(tstop)
def restore_state(self, state_file='state.bin', keep_events=False):
from neuron import h
ns = h.SaveState()
sf = h.File(os.path.join(self.get_permanent_model_directory(), state_file))
ns.fread(sf)
h.stdinit()
if keep_events:
ns.restore(1)
# Workaround - without the fixed step cycle, NEURON crashes with same error as in:
# https://www.neuron.yale.edu/phpBB/viewtopic.php?f=2&t=3845&p=16542#p16542
# Only happens when there is a vector.play added after a state restore
# Running one cycle using the fixed integration method addresses the problem
h.cvode_active(0)
prev_dt = h.dt
h.dt = 0.000001
h.steprun()
h.dt = prev_dt
# END Workaround
else:
ns.restore()
h.cvode_active(self.config.cvode_active)
def savehocstate(filestr):
'''saves the current hoc states (not rxd) of the simulation into file with name filestr.dat
filestr: a string of file path (without file extension)'''
myss = h.SaveState()
#h.initnrn() # to set h.t to zero
myss.save()
myfile = h.File('./data/' + filestr + '_hoc_.dat')
myss.fwrite(myfile)
myfile.close()
def read_state(conf):
state_dir = conf["output"]["state_dir"]
state = h.SaveState()
f = h.File('{}/state_rank-{}'.format(state_dir, int(pc.id())))
# f = h.File(state_dir+'/state_rank-%d' % (int(pc.id())))
state.fread(f, 0)
state.restore()
rlist = h.List('Random')
for r_tmp in rlist:
r_tmp.seq(f.scanvar())
f.close()
def vwrite_type(src, vtype):
f = h.File()
fname = "vwrite.{}.tmp".format(str(vtype))
f.wopen(fname)
src.c().vwrite(f, vtype)
f.close()
f.ropen(fname)
vr = h.Vector(vtype)
vr.vread(f)
f.close()
f.unlink()
assert src.to_python() == vr.to_python()
def save_state(conf):
state = h.SaveState()
state.save()
state_dir = conf["output"]["state_dir"]
f = h.File('{}/state_rank-{}'.format(state_dir, int(pc.id())))
# f = h.File(state_dir + '/state_rank-%d' % (int(pc.id())))
state.fwrite(f, 0)
rlist = h.List('Random')
for r_tmp in rlist:
f.printf('%g\n', r_tmp.seq())
f.close()
def run_to_steady_state(self, tstop):
self._update_current_sources(tstop)
self._pre_run()
self.parallel_context.set_maxstep(self.default_maxstep)
self.tstop = tstop
#logger.info("Running the simulation until steady state: %g ms" % tstop)
if self.tstop > self.t:
self.parallel_context.psolve(self.tstop)
# Make object to save the model state
svstate = h.SaveState()
# Save the model state and write it to file
svstate.save()
f = h.File("steady_state.bin")
svstate.fwrite(f)
def run_from_steady_state(self, tstop):
self._update_current_sources(tstop)
self._pre_run()
self.parallel_context.set_maxstep(self.default_maxstep)
self.tstop = tstop
h.stdinit()
ns = h.SaveState()
sf = h.File('steady_state.bin')
ns.fread(sf)
#print("Time before restore = %g ms" % h.t)
ns.restore(0)
h.cvode_active(0)
#print("Time after restore = %g ms" % h.t)
#logger.info("Running the simulation until %g ms" % tstop)
if self.tstop > self.t:
self.parallel_context.psolve(self.tstop)
def loadhocstate(filestr):
'''loads hoc states (not rxd states) of simulation from file filestr.dat
filestr: a string of file path (without file extension).
For loading to happen appropriately, this statement has to be called after any initialization (eg h.finitalize)'''
global tstart, tstop
myfile = h.File()
myfile.ropen('./data/' + filestr + '_hoc_.dat')
myss = h.SaveState()
if myfile.isopen():
myss.fread(myfile)
myfile.close()
myss.restore(1)
print 'loaded hoc states from:', myfile.getname()
tstart = h.t
tstop = tstart + simdur # stopping time of simulation
h.tstop = tstop
#for ns in netStimlist: ns.start = nstimStart + tstart
else:
print "file cannot be open to read"
def restoreSS():
svst = h.SaveState()
f = h.File(os.path.join(restoredir, 'save_test_'+str(pcid) + '.dat'))
svst.fread(f)
svst.restore()
def runSS():
svst = h.SaveState()
svst.save()
f = h.File(os.path.join(outdir,'save_test_' + str(pcid) + '.dat'))
svst.fwrite(f)
def restorestate():
s = 'svst.{pcid}'.format(pcid=int(pc.id()))
f = h.File(s)
ss = h.SaveState()
ss.fread(f)
ss.restore()
def savestate():
s = 'svst.{pcid}'.format(pcid=int(pc.id()))
f = h.File(s)
ss = h.SaveState()
ss.save()
ss.fwrite(f)
def save_state(self, state_file='state.bin'):
from neuron import h
ns = h.SaveState()
sf = h.File(os.path.join(self.get_permanent_model_directory(), state_file))
ns.save()
ns.fwrite(sf)
def test_vector_api():
"""
Construction
"""
vi = h.Vector((1, 2, 3))
assert vi.to_python() == [1.0, 2.0, 3.0]
assert vi.get(1) == 2.0
vi.set(1, 2.1)
assert vi.to_python() == [1.0, 2.1, 3.0]
del vi
v = h.Vector(np.array([5, 1, 6], "d"))
assert v.to_python() == [5.0, 1.0, 6.0]
v.clear()
assert v.size() == 0
del v
v = h.Vector(3)
assert v.to_python() == [0.0, 0.0, 0.0]
del v
v = h.Vector(3, 1)
assert v.to_python() == [1.0, 1.0, 1.0]
del v
assert h.Vector().from_python((1, 2, 3)).to_python() == [1.0, 2.0, 3.0]
v = h.Vector()
v.append(3, 3)
v.append(2)
v.append(1)
v.append(5)
"""
Vector size & capacity
"""
assert v.to_python() == [3.0, 3.0, 2.0, 1.0, 5.0]
assert v.size() == 5
v.buffer_size(v.size())
assert v.buffer_size() >= v.size()
v.buffer_size(6)
assert v.buffer_size() >= 6
assert v.to_python() == [3.0, 3.0, 2.0, 1.0, 5.0]
assert v.eq(v.c())
"""
Calculations
"""
assert v.median() == 3.0
assert v.mean() == 2.8
assert v.mean(1, 3) == 2.0
assert np.allclose(v.stdev(), 1.4832396974191326)
assert np.allclose(v.stdev(0, 3), 0.9574271077563381)
assert np.allclose(v.stderr(), 0.6633249580710799)
assert np.allclose(v.stderr(1, 3), 0.5773502691896258)
assert v.sum() == 14.0
assert v.sum(1, 3) == 6.0
assert np.allclose(
v.sumgauss(-1, 1, 0.5, 1).to_python(),
[
0.05869048145253869,
0.14879136924715222,
0.30482687457572216,
0.5166555071584352,
],
)
assert np.allclose(
v.sumgauss(-1, 1, 0.5, 1, h.Vector((1, 3, 2, 5, 4))).to_python(),
[
0.2793538745964073,
0.6861357408871805,
1.3355688961479038,
2.0895389620919826,
],
)
assert np.allclose(
v.cl().smhist(v.cl(), 1, 3, 2, 1).to_python(),
[0.9060003240550064, 0.9598574603424295, 0.5071918738793386],
)
assert np.allclose(
v.cl().smhist(v.cl(), 1, 3, 2, 1, h.Vector(
(1, 3, 2, 5, 4))).to_python(),
[3.009095149765841, 2.1896697532507994, 1.8126697992388372],
)
assert v.sumsq() == 48.0
assert v.sumsq(2, 4) == 30.0
assert v.var() == 2.2
assert v.var(2, 3) == 0.5
assert v.min() == 1.0
assert v.min(0, 2) == 2.0
assert h.Vector().min() == 0.0
assert v.min_ind() == 3
assert v.min_ind(0, 2) == 2
assert h.Vector().min_ind() == -1.0
assert v.max() == 5.0
assert v.max(0, 2) == 3.0
assert h.Vector().max() == 0.0
assert v.max_ind() == 4
assert v.max_ind(0, 2) == 0
assert h.Vector().max_ind() == -1.0
assert v.dot(h.Vector((1, 2, 3, 4, 5))) == 44.0
assert np.allclose(v.mag(), 6.928203230275509)
assert v.c().reverse().meansqerr(v) == 3.2
assert v.c().reverse().meansqerr(v, h.Vector((1, 2, 5, 4, 3))) == 8.0
assert (v.c().trigavg(h.Vector((1, 2, 3, 4, 5)), h.Vector((1, 2, 3, 4, 5)),
1, 2) == 2)
"""
Copying
"""
# vdest.copy(vsrc)
copy(v, [3.0, 3.0, 2.0, 1.0, 5.0])
# vdest.copy(vsrc, dest_start)
copy(v, [0.0, 0.0, 3.0, 3.0, 2.0, 1.0, 5.0], 2)
# vdest.copy(vsrc, src_start, src_end)
copy(v, [2.0, 1.0], 2, 3)
copy(v, [2.0, 1.0, 5.0], 2, -1) # -1 for actual end
# vdest.copy(vsrc, dest_start, src_start, src_end)
copy(v, [0.0, 2.0, 1.0], 1, 2, 3)
# vdest.copy(vsrc, dest_start, src_start, src_end, dest_inc, src_inc)
copy(v, [0.0, 3.0, 1.0], 1, 1, -1, 1, 2)
# vdest.copy(vsrc, vsrcdestindex)
copy(v, [0.0, 3.0, 2.0], h.Vector((1, 2)), dest=h.Vector(3, 0.0))
# vdest.copy(vsrc, vsrcindex, vdestindex)copy(v, [3.0, 3.0, 2.0, 1.0, 5.0])
copy(v, [3.0, 2.0, 0.0],
h.Vector((1, 2)),
h.Vector((0, 1)),
dest=h.Vector(3, 0.0))
copy(v, [3.0], h.Vector((1, 2)), h.Vector((0, 1)), dest=h.Vector(1, 0.0))
assert v.c().to_python() == v.to_python()
assert v.c(1).to_python() == [3.0, 2.0, 1.0, 5.0]
assert v.c(1, 3).to_python() == [3.0, 2.0, 1.0]
assert v.at().to_python() == v.to_python()
assert v.at(1).to_python() == [3.0, 2.0, 1.0, 5.0]
assert v.at(1, 3).to_python() == [3.0, 2.0, 1.0]
"""
Data morphing and operations
"""
assert v.resize(4).size() == 4
assert v.fill(1.0).to_python() == [1.0, 1.0, 1.0, 1.0]
assert v.fill(1.1, 1, 2).to_python() == [1.0, 1.1, 1.1, 1.0]
# obj = vsrcdest.indgen()
assert v.indgen().to_python() == [0.0, 1.0, 2.0, 3.0]
# obj = vsrcdest.indgen(stepsize)
assert v.indgen(2).to_python() == [0.0, 2.0, 4.0, 6.0]
# obj = vsrcdest.indgen(start,stepsize)
assert v.indgen(2, 5).to_python() == [2.0, 7.0, 12.0, 17.0]
# obj = vsrcdest.indgen(start,stop,stepsize)
assert v.indgen(1, 20, 5).to_python() == [1.0, 6.0, 11.0, 16.0]
assert v.append(h.Vector(1, 17.0), 18.0, 19.0).to_python() == [
1.0,
6.0,
11.0,
16.0,
17.0,
18.0,
19.0,
]
assert v.insrt(
1, 3.0).to_python() == [1.0, 3.0, 6.0, 11.0, 16.0, 17.0, 18.0, 19.0]
assert v.insrt(3, h.Vector(1, 9.0)).to_python() == [
1.0,
3.0,
6.0,
9.0,
11.0,
16.0,
17.0,
18.0,
19.0,
]
assert v.remove(4).to_python() == [
1.0, 3.0, 6.0, 9.0, 16.0, 17.0, 18.0, 19.0
]
assert v.remove(1, 5).to_python() == [1.0, 18.0, 19.0]
h("double px[3]")
h.px[0] = 5
h.px[2] = 2
assert v.from_double(3, h._ref_px[0]).to_python() == [5.0, 0.0, 2.0]
a = np.array([5, 1, 6], "d")
assert v.from_double(3, npyref(a, 0)).to_python() == [5.0, 1.0, 6.0]
v.indgen(1, 30, 5)
assert v.to_python() == [1.0, 6.0, 11.0, 16.0, 21.0, 26.0]
assert v.contains(6.0)
assert not v.contains(7.0)
assert h.Vector().where(v, ">=",
10).to_python() == [11.0, 16.0, 21.0, 26.0]
assert h.Vector().where(v, "<=", 11).to_python() == [1.0, 6.0, 11.0]
assert h.Vector().where(v, "!=",
11).to_python() == [1.0, 6.0, 16.0, 21.0, 26.0]
assert h.Vector().where(v, "==", 11).to_python() == [11.0]
assert h.Vector().where(v, "<", 11).to_python() == [1.0, 6.0]
assert h.Vector().where(v, ">", 11).to_python() == [16.0, 21.0, 26.0]
assert h.Vector().where(v, "[)", 9, 21).to_python() == [11.0, 16.0]
assert h.Vector().where(v, "[]", 9, 21).to_python() == [11.0, 16.0, 21.0]
assert h.Vector().where(v, "(]", 11, 21).to_python() == [16.0, 21.0]
assert h.Vector().where(v, "()", 11, 21).to_python() == [16.0]
assert v.where(">", 1.0).to_python() == [6.0, 11.0, 16.0, 21.0, 26.0]
assert v.where("[)", 6.0, 26.0).to_python() == [6.0, 11.0, 16.0, 21.0]
assert v.indwhere(">", 11.0) == 2
assert v.indwhere("<", 11.0) == 0
assert v.indwhere("!=", 11.0) == 0
assert v.indwhere(">=", 11.0) == 1
assert v.indwhere("<=", 11.0) == 0
assert v.indwhere("[)", 11.1, 16.0) == -1
assert v.indwhere("[)", 11.0, 16.0) == 1
assert v.indwhere("(]", 11.0, 16.0) == 2
assert v.indwhere("[]", 11.0, 16.0) == 1
assert v.indwhere("()", 16.0, 11.0) == -1
assert h.Vector().indvwhere(v, "()", 11, 21).to_python() == [2.0]
assert h.Vector().indvwhere(v, "==", 11).to_python() == [1.0]
assert h.Vector().indvwhere(v, "[]", 1, 17).to_python() == [0.0, 1.0, 2.0]
assert h.Vector().indvwhere(v, "(]", 1, 16).to_python() == [0.0, 1.0, 2.0]
assert h.Vector().indvwhere(v, "[)", 1, 16).to_python() == [0.0, 1.0]
assert h.Vector().indvwhere(v, "!=", 11).to_python() == [0.0, 2.0, 3.0]
assert h.Vector().indvwhere(v, "<", 11).to_python() == [0.0]
assert h.Vector().indvwhere(v, "<=", 11).to_python() == [0.0, 1.0]
assert h.Vector().indvwhere(v, ">", 16).to_python() == [3.0]
assert h.Vector().indvwhere(v, ">=", 16).to_python() == [2.0, 3.0]
assert v.histogram(1.0, 20.0, 10).to_python() == [0.0, 1.0, 2.0]
assert h.Vector().hist(v, 1.0, 2.0, 10).to_python() == [1.0, 2.0]
assert v.ind(h.Vector((1, 3))).to_python() == [11.0, 21.0]
assert h.Vector().spikebin(v.c(), 12.0).to_python() == [0.0, 0.0, 1.0, 0.0]
"""
Vector metadata
"""
assert v.label() == ""
v.label("v")
assert v.label() == "v"
assert v.cl().label() == "v"
v.label("v2")
assert v.label() == "v2"
"""
Transformations
"""
v = h.Vector((3, 2, 15, 16))
assert np.allclose(
v.c().apply("sin").to_python(),
[
0.1411200080598672,
0.9092974268256817,
0.6502878401571169,
-0.2879033166650653,
],
)
assert np.allclose(
v.c().apply("sin", 1, 2).to_python(),
[3.0, 0.9092974268256817, 0.6502878401571169, 16.0],
)
h("func sq(){return $1*$1}")
assert np.allclose(v.c().apply("sq").to_python(), [9.0, 4.0, 225.0, 256.0])
assert v.reduce("sq", 100) == 594.0
assert h.Vector().deriv(v, 0.1).to_python() == [-10.0, 60.0, 70.0, 10.0]
assert h.Vector().deriv(v, 1, 1).to_python() == [-1.0, 13.0, 1.0]
assert h.Vector().deriv(v, 1, 2).to_python() == [-1.0, 6.0, 7.0, 1.0]
assert np.allclose(
v.c().interpolate(v.c(),
v.c().apply("sqrt")).to_python(),
[10.384365150689874, 5.097168242109362, 16.0, 16.0],
)
assert np.allclose(
v.c().interpolate(v.c(),
v.c().apply("sqrt"), h.Vector(
(1, 2, 3, 4))).to_python(),
[2.644951165437683, 2.2382437109314894, 4.0, 4.0],
)
assert h.Vector().integral(v).to_python() == [3.0, 5.0, 20.0, 36.0]
assert np.allclose(h.Vector().integral(v, 0.1).to_python(),
[3.0, 3.2, 4.7, 6.300000000000001])
assert v.c().medfltr().to_python() == [3.0, 3.0, 3.0, 3.0]
assert v.c().medfltr(h.Vector(
(1, 2, 3, 4))).to_python() == [2.0, 2.0, 2.0, 2.0]
assert v.c().sort().to_python() == [2.0, 3.0, 15.0, 16.0]
assert v.sortindex().to_python() == [1.0, 0.0, 2.0, 3.0]
assert v.c().reverse().to_python() == [16.0, 15.0, 2.0, 3.0]
assert v.c().rotate(3).to_python() == [2.0, 15.0, 16.0, 3.0]
assert v.c().rotate(3, 0).to_python() == [0.0, 0.0, 0.0, 3.0]
assert h.Vector().rebin(v, 2).to_python() == [5.0, 31.0]
assert v.c().rebin(2).to_python() == [5.0, 31.0]
assert h.Vector().pow(v, 2).to_python() == [9.0, 4.0, 225.0, 256.0]
assert np.allclose(v.c().pow(v, 0).to_python(), [1.0, 1.0, 1.0, 1.0])
assert np.allclose(
v.c().pow(v, 0.5).to_python(),
[1.7320508075688772, 1.4142135623730951, 3.872983346207417, 4.0],
)
assert np.allclose(
v.c().pow(v, -1).to_python(),
[0.3333333333333333, 0.5, 0.06666666666666667, 0.0625],
)
assert np.allclose(v.c().pow(v, 1).to_python(), [3.0, 2.0, 15.0, 16.0])
assert np.allclose(v.c().pow(v, 3).to_python(),
[27.0, 8.0, 3375.0, 4096.0])
assert v.c().pow(2).to_python() == [9.0, 4.0, 225.0, 256.0]
assert np.allclose(
h.Vector().sqrt(v).to_python(),
[1.7320508075688772, 1.4142135623730951, 3.872983346207417, 4.0],
)
assert np.allclose(
v.c().sqrt().to_python(),
[1.7320508075688772, 1.4142135623730951, 3.872983346207417, 4.0],
)
assert np.allclose(
h.Vector().log(v).to_python(),
[
1.0986122886681098, 0.6931471805599453, 2.70805020110221,
2.772588722239781
],
)
assert np.allclose(
v.c().log().to_python(),
[
1.0986122886681098, 0.6931471805599453, 2.70805020110221,
2.772588722239781
],
)
assert np.allclose(
h.Vector().log10(v).to_python(),
[
0.47712125471966244,
0.3010299956639812,
1.1760912590556813,
1.2041199826559248,
],
)
assert np.allclose(
v.c().log10().to_python(),
[
0.47712125471966244,
0.3010299956639812,
1.1760912590556813,
1.2041199826559248,
],
)
assert np.allclose(
h.Vector().tanh(v).to_python(),
[
0.9950547536867305,
0.9640275800758169,
0.9999999999998128,
0.9999999999999747,
],
)
assert np.allclose(
v.c().tanh().to_python(),
[
0.9950547536867305,
0.9640275800758169,
0.9999999999998128,
0.9999999999999747,
],
)
assert h.Vector([1.2312414, 3.1231, 5.49554,
6.5000000001]).floor().to_python() == [
1.0,
3.0,
5.0,
6.0,
]
assert h.Vector([-1.0, -3.0, -5.0,
-6.0]).abs().to_python() == [1.0, 3.0, 5.0, 6.0]
assert v.c().add(h.Vector((1.1, 2.2, 3.3, 4.4))).to_python() == [
4.1,
4.2,
18.3,
20.4,
]
assert v.c().add(1.3).to_python() == [4.3, 3.3, 16.3, 17.3]
assert v.c().sub(h.Vector(
(1.1, 2, 3.3, 4))).to_python() == [1.9, 0.0, 11.7, 12.0]
assert v.c().sub(1.3).to_python() == [1.7, 0.7, 13.7, 14.7]
assert v.c().mul(h.Vector(
(1.5, 2, 3, 4))).to_python() == [4.5, 4.0, 45.0, 64.0]
assert v.c().mul(2.5).to_python() == [7.5, 5.0, 37.5, 40.0]
assert v.c().div(h.Vector(
(1.5, 2, 3, 4))).to_python() == [2.0, 1.0, 5.0, 4.0]
assert v.c().div(2.5).to_python() == [1.2, 0.8, 6.0, 6.4]
vs = v.c()
assert np.allclose(vs.scale(2, 5), 0.21428571428571427)
assert np.allclose(vs.to_python(),
[2.2142857142857144, 2.0, 4.785714285714286, 5.0])
assert np.allclose(
v.c().sin(1, 1).to_python(),
[
0.8414709848078965, 0.844849172063764, 0.8481940061209319,
0.8515053549310787
],
)
assert np.allclose(
v.c().sin(1, 1, 2).to_python(),
[
0.8414709848078965,
0.8481940061209319,
0.8547830877678237,
0.8612371892561972,
],
)
"""
Fourier
"""
assert v.to_python() == [3.0, 2.0, 15.0, 16.0]
assert h.Vector(
v.size()).correl(v).to_python() == [494.0, 324.0, 154.0, 324.0]
assert h.Vector(v.size()).convlv(v,
v.c().reverse()).to_python() == [
294.0,
122.0,
318.0,
490.0,
]
assert np.allclose(
h.Vector(v.size()).convlv(v,
v.c().reverse(), -1).to_python(),
[305.9999866504336, 306.0, 306.0000133495664, 306.0],
)
assert v.c().spctrm(v).to_python() == [60.625, 2.0, 15.0, 16.0]
assert h.Vector(v.size()).filter(v,
v.c().reverse()).to_python() == [
308.0,
-66.0,
376.0,
750.0,
]
assert h.Vector(v.size()).fft(
v, -1).to_python() == [17.5, 16.5, -12.5, -15.5]
assert v.c().fft(-1).to_python() == h.Vector(v.size()).fft(v,
-1).to_python()
"""
I/O
"""
assert v.to_python() == [3.0, 2.0, 15.0, 16.0]
f = h.File()
f.wopen("temp.tmp")
v.vwrite(f)
f.close()
assert v.to_python() == [3.0, 2.0, 15.0, 16.0]
vr = h.Vector()
f.ropen("temp.tmp")
vr.vread(f)
assert vr.to_python() == v.to_python()
f.close()
f.unlink()
f.wopen("temp.tmp")
f.printf("%d %d %d %d\n", 3, 2, 15, 16)
f.close()
f.ropen("temp.tmp")
vr.resize(0)
vr.scanf(f)
assert vr.to_python() == v.to_python()
f.seek(0)
vr2 = h.Vector(4)
vr2.scanf(f)
assert vr.to_python() == vr2.to_python()
f.seek(0)
vr.resize(0)
vr.scanf(f, 1)
assert vr.to_python() == [3.0]
vr.scanf(f, 1)
assert vr.to_python() == [2.0]
vr.resize(0)
f.seek(0)
vr.scantil(f, 15.0)
assert vr.to_python() == [3.0, 2.0]
f.close()
f.unlink()
# Columns
f.wopen("col.tmp")
f.printf("%d %d %d %d\n", 3, 2, 15, 16)
f.printf("%d %d %d %d\n", 6, 9, 7, 21)
f.printf("%d %d %d %d\n", 1, 4, 5, 22)
f.printf("%d %d %d %d\n", 3, 8, 14, 23)
f.close()
f.ropen("col.tmp")
vc = h.Vector()
vc.scanf(f, 3, 2, 4)
assert vc.to_python() == [2.0, 9.0, 4.0]
vc.scanf(f, 3, 2, 4)
assert vc.to_python() == [8.0]
f.close()
f.ropen("col.tmp")
vc = h.Vector()
vc.scanf(f, 3, 4)
assert vc.to_python() == [15.0, 7.0, 5.0, 14.0]
f.seek(0)
vc.scantil(f, 5.0, 3, 4)
assert vc.to_python() == [15.0, 7.0]
vc.printf() # code cov
vc.printf("%8.4f ")
vc.printf("%8.4f ", 0, 1)
f.close()
f.unlink()
# Vwrite types
vwrite_type(h.Vector([1, 2, 3, 4]), 1)
vwrite_type(h.Vector([4, 3, 2, 1]), 2)
vwrite_type(h.Vector([4, 5, 6, 7]), 3)
vwrite_type(h.Vector([7, 8, 9, 10]), 4)
vwrite_type(h.Vector([0, 1, 2, 33]), 5)
"""
Random
"""
vrand = h.Vector((1, 2, 3))
r = h.Random()
r.poisson(12)
assert vrand.cl().setrand(r).to_python() == [10.0, 16.0, 11.0]
assert vrand.cl().setrand(r, 1, 2).to_python() == [1.0, 9.0, 18.0]
assert vrand.cl().addrand(r).to_python() == [9.0, 9.0, 16.0]
assert vrand.cl().addrand(r, 0, 1).to_python() == [13.0, 16.0, 3.0]
"""
Misc
"""
assert h.Vector().inf(h.Vector((3, 2, 4)), 2, 3, 4, 5, 6,
7).to_python() == [
4.0,
5.2,
4.56,
]
assert h.Vector().resample(h.Vector((3, 2, 4, 6, 7)), 2).to_python() == [
3.0,
3.0,
2.0,
2.0,
4.0,
4.0,
6.0,
6.0,
7.0,
7.0,
]
assert h.Vector().psth(h.Vector((3, 2, 4, 6, 7, 6, 7, 8)), 1, 2,
3).to_python() == [
1500.0,
1500.0,
2000.0,
3000.0,
3500.0,
3000.0,
3500.0,
4000.0,
]
h("func fun () { return ($1 - 0.5) * 2 + ($2 - 0.5) * 2 }")
dvec = h.Vector(2)
fvec = h.Vector(2)
fvec.fill(1)
ivec = h.Vector(2)
ivec.indgen()
a = h.ref(2)
b = h.ref(1)
error = dvec.fit(fvec, "fun", ivec, a, b)
assert np.allclose([error], [1.0005759999999997])
assert np.allclose(fvec.to_python(), [-0.976, 1.024])
assert ivec.to_python() == [0.0, 1.0]
assert dvec.to_python() == [0.0, 0.0]
aftau = np.array([5, 1, 6, 8], "d")
error = dvec.fit(
fvec,
"exp2",
ivec,
npyref(aftau, 0),
npyref(aftau, 1),
npyref(aftau, 2),
npyref(aftau, 3),
)
assert np.allclose([error], [8.442756842706686])
error = dvec.fit(
fvec,
"exp1",
ivec,
npyref(aftau, 0),
npyref(aftau, 1),
npyref(aftau, 2),
npyref(aftau, 3),
)
assert np.allclose([error], [2.5653639385348724e-06])
error = dvec.fit(
fvec,
"charging",
ivec,
npyref(aftau, 0),
npyref(aftau, 1),
npyref(aftau, 2),
npyref(aftau, 3),
)
assert np.allclose([error], [7.288763182752445e-08])
error = dvec.fit(fvec, "quad", ivec, npyref(aftau, 0), npyref(aftau, 1),
npyref(aftau, 2))
assert np.allclose([error], [0.0010239221022848835])
error = dvec.fit(fvec, "line", ivec, npyref(aftau, 0), npyref(aftau, 1))
assert np.allclose([error], [6.593786238758728e-06])
from neuron import h
try:
#Most HocObject have no length
print(([len(h), bool(h)] == [0, True]))
except:
pass
o = h.Vector(0)
print(([len(o), bool(o)] == [0, False]))
o.resize(2)
print(([len(o), bool(o)] == [2, True]))
o = h.List()
print(([len(o), bool(o)] == [0, False]))
o.append([])
print(([len(o), bool(o)] == [1, True]))
h('double a[2][3]')
print(([len(h.a), len(h.a[1]), bool(h.a), bool(h.a[1])] == [2, 3, True, True]))
print(([len(h.Vector), bool(h.Vector)] == [0, False]))
b = []
for x in range(4):
b.append(h.Vector())
print(([len(h.Vector), bool(h.Vector)] == [4, True]))
b = h.File()
print(([len(b), bool(b)] == [0, True]))
"""
Read function tables for tabchannels.
Needed for kfasttab.mod, kslowtab.mod and nagran.mod.
All data now in a single file, tabchannels.dat.
Author: Andrew Davison, July 2003, converted to Python November 2010
"""
npoints = 1001
from neuron import h, load_mechanisms
load_mechanisms("Channels")
datafile = h.File()
datafile.ropen("tabchannels.dat")
datafile.seek(0)
vvec = h.Vector(npoints)
vvec.scanf(datafile,1,13)
datafile.seek() # goes to beginning of file
datavec = []
for i in range(12):
datavec.append(h.Vector(npoints))
datavec[i].scanf(datafile,i+2,13)
datafile.seek()
datafile.close()
assert vvec.size() == npoints
h.table_tabninf_kfasttab(datavec[0]._ref_x[0], npoints, vvec._ref_x[0])
