def history_update(self, insn):
time_slow = self.var_time_level[insn.slow_arg]
time_fast = self.var_time_level[insn.fast_arg]
assert abs(time_slow - time_fast) < 1e-10, str(
(abs(time_slow - time_fast), self.stepper.method_name,
self.stepper.substep_count, self.insn_counter))
t = (self.t_start +
self.stepper.large_dt * time_slow / self.stepper.substep_count)
rhs = self.rhss[HIST_NAMES.index(insn.which)]
hist = self.stepper.histories[insn.which]
hist.pop()
hist.insert(
0, rhs(t, self.context[insn.fast_arg],
self.context[insn.slow_arg]))
if self.stepper.hist_is_fast[insn.which]:
self.hist_head_time_level[insn.which] += 1
else:
self.hist_head_time_level[insn.which] += self.stepper.substep_count
MRABProcessor.history_update(self, insn)
def integrate_in_time(self, insn):
from hedge.timestep.multirate_ab.methods import CO_FAST
from hedge.timestep.multirate_ab.methods import HIST_F2F, HIST_S2F, HIST_F2S, HIST_S2S
if insn.component == CO_FAST:
self_hn, cross_hn = HIST_F2F, HIST_S2F
else:
self_hn, cross_hn = HIST_S2S, HIST_F2S
start_time_level = self.eval_expr(insn.start)
end_time_level = self.eval_expr(insn.end)
self_coefficients = self.stepper.get_coefficients(
self.stepper.hist_is_fast[self_hn],
self.hist_head_time_level[self_hn],
start_time_level,
end_time_level,
self.stepper.orders[self_hn],
)
cross_coefficients = self.stepper.get_coefficients(
self.stepper.hist_is_fast[cross_hn],
self.hist_head_time_level[cross_hn],
start_time_level,
end_time_level,
self.stepper.orders[cross_hn],
)
if start_time_level == 0 or (insn.result_name not in self.context):
my_y = self.last_y[insn.component]
assert start_time_level == 0
else:
my_y = self.context[insn.result_name]()
assert start_time_level == self.var_time_level[insn.result_name]
hists = self.stepper.histories
self_history = hists[self_hn][:]
cross_history = hists[cross_hn][:]
if False:
my_integrated_y = memoize(
lambda: my_y
+ self.stepper.large_dt
* (_linear_comb(self_coefficients, self_history) + _linear_comb(cross_coefficients, cross_history))
)
else:
my_new_y = my_y + self.stepper.large_dt * (
_linear_comb(self_coefficients, self_history) + _linear_comb(cross_coefficients, cross_history)
)
my_integrated_y = lambda: my_new_y
self.context[insn.result_name] = my_integrated_y
self.var_time_level[insn.result_name] = end_time_level
MRABProcessor.integrate_in_time(self, insn)
def integrate_in_time(self, insn):
from hedge.timestep.multirate_ab.methods import CO_FAST
from hedge.timestep.multirate_ab.methods import \
HIST_F2F, HIST_S2F, HIST_F2S, HIST_S2S
if insn.component == CO_FAST:
self_hn, cross_hn = HIST_F2F, HIST_S2F
else:
self_hn, cross_hn = HIST_S2S, HIST_F2S
start_time_level = self.eval_expr(insn.start)
end_time_level = self.eval_expr(insn.end)
self_coefficients = self.stepper.get_coefficients(
self.stepper.hist_is_fast[self_hn],
self.hist_head_time_level[self_hn], start_time_level,
end_time_level, self.stepper.orders[self_hn])
cross_coefficients = self.stepper.get_coefficients(
self.stepper.hist_is_fast[cross_hn],
self.hist_head_time_level[cross_hn], start_time_level,
end_time_level, self.stepper.orders[cross_hn])
if start_time_level == 0 or (insn.result_name not in self.context):
my_y = self.last_y[insn.component]
assert start_time_level == 0
else:
my_y = self.context[insn.result_name]()
assert start_time_level == \
self.var_time_level[insn.result_name]
hists = self.stepper.histories
self_history = hists[self_hn][:]
cross_history = hists[cross_hn][:]
if False:
my_integrated_y = memoize(lambda: my_y + self.stepper.large_dt * (
_linear_comb(self_coefficients, self_history) + _linear_comb(
cross_coefficients, cross_history)))
else:
my_new_y = my_y + self.stepper.large_dt * (
_linear_comb(self_coefficients, self_history) +
_linear_comb(cross_coefficients, cross_history))
my_integrated_y = lambda: my_new_y
self.context[insn.result_name] = my_integrated_y
self.var_time_level[insn.result_name] = end_time_level
MRABProcessor.integrate_in_time(self, insn)
def __init__(self, stepper, y, t, rhss):
MRABProcessor.__init__(self, stepper.method, stepper.substep_count)
self.stepper = stepper
self.t_start = t
self.context = {}
self.var_time_level = {}
self.rhss = rhss
y_fast, y_slow = y
from hedge.timestep.multirate_ab.methods import CO_FAST, CO_SLOW
self.last_y = {CO_FAST: y_fast, CO_SLOW: y_slow}
self.hist_head_time_level = dict((hn, 0) for hn in HIST_NAMES)
def __init__(self, stepper, y, t, rhss):
MRABProcessor.__init__(self, stepper.method, stepper.substep_count)
self.stepper = stepper
self.t_start = t
self.context = {}
self.var_time_level = {}
self.rhss = rhss
y_fast, y_slow = y
from hedge.timestep.multirate_ab.methods import CO_FAST, CO_SLOW
self.last_y = {CO_FAST: y_fast, CO_SLOW: y_slow}
self.hist_head_time_level = dict((hn, 0) for hn in HIST_NAMES)
def history_update(self, insn):
time_slow = self.var_time_level[insn.slow_arg]
time_fast = self.var_time_level[insn.fast_arg]
assert abs(time_slow - time_fast) < 1e-10, str(
(abs(time_slow - time_fast), self.stepper.method_name, self.stepper.substep_count, self.insn_counter)
)
t = self.t_start + self.stepper.large_dt * time_slow / self.stepper.substep_count
rhs = self.rhss[HIST_NAMES.index(insn.which)]
hist = self.stepper.histories[insn.which]
hist.pop()
hist.insert(0, rhs(t, self.context[insn.fast_arg], self.context[insn.slow_arg]))
if self.stepper.hist_is_fast[insn.which]:
self.hist_head_time_level[insn.which] += 1
else:
self.hist_head_time_level[insn.which] += self.stepper.substep_count
MRABProcessor.history_update(self, insn)
