def datatypes(self, genotype):
"""Dict of Numpy data types for each Table in the HDF file."""
li = self.li # save some typing
ftype = dict(genotype=self.genotype.dtype, parameter=li.dtype.p,
convergence=[("period", np.int16), ("intervals", np.int16)],
steady=self.li.dtype.y, quiescent=self.li.dtype.y,
# Hacked by stepping through self.task(0), see comment there
clamppheno=[(k, float) for k in
"i_Na_tau_m40 i_Na_tau_m20 i_Na_tau_0 i_Na_tau_20 i_Na_tau_40 "
"i_CaL_tau_m40 i_CaL_tau_m20 i_CaL_tau_0 i_CaL_tau_20 "
"i_CaL_tau_40 i_CaL_vg_max_m90 i_CaL_vg_thalf_m90 "
"i_CaL_vg_max_m80 i_CaL_vg_thalf_m80 i_CaL_vg_max_m70 "
"i_CaL_vg_thalf_m70".split()],
timing=[(k, float) for k in
"waiting started finished error seconds attempts".split()])
ftype["raw"] = [(k, float, self.raw_nap * self.raw_nthin)
for k in ("t",) + li.dtype.y.names + li.dtype.a.names]
# Ion-current phenotypes: a few phenotypes for many variables.
# Make one array per phenotype, with one column per variable.
# Get field names for current phenotypes
with li.autorestore():
t, y, stats = li.ap_plain()
curph = current_phenotypes_array(t, y.V)
for k in curph.dtype.names:
ftype[k] = [(i, float) for i in li.dtype.y.names + li.dtype.a.names]
ap_stats = ap_cvode.ap_stats_array(stats)
# Action potential and calcium transient statistics, including time
# to recovery.
ftype["ap_stats"] = [(k, typ, self.raw_nap) for k, typ in eval(str(ap_stats.dtype))]
return ftype
def thin_aps(self, aps, nthin, par):
"""Thin action potentials to "nthin" points."""
t = np.concatenate([ti[thin(len(ti), nthin)] for ti, yi, si in aps])
t = t - t[0]
y = np.concatenate([yi[thin(len(ti), nthin)] for ti, yi, si in aps])
rates, a = self.li.rates_and_algebraic(t, y, par)
ap_stats = np.zeros(1, dtype=self.ftype["ap_stats"])
stats = np.concatenate([ap_cvode.ap_stats_array(si) for ti, yi, si in aps])
for k in stats.dtype.names:
ap_stats[k] = stats[k].squeeze()
raw = np.zeros(1, dtype=self.ftype["raw"])
raw["t"] = t
for k in y.dtype.names:
raw[k] = y[k].squeeze()
for k in a.dtype.names:
raw[k] = a[k].squeeze()
return raw, ap_stats
