def trigger_callbacks(self, regs=None):
"""
regs = list of addresses that changed
"""
if not self.callbacks:
return
for key, cb in self.callbacks.items():
try:
push = False
if fun.isSequence(cb):
if not regs or any(r in cb for r in regs):
#print('%s: %s.trigger(%s): callback(%s):%s' %
#(fun.time2str(),self,key,cb,regs))
cb, push = cb[-1], True
else:
continue
if fun.isCallable(cb):
cb(key, push=push)
else:
cb = getattr(cb, 'push_event',
getattr(cb, 'event_received', None))
cb and cb(key)
fandango.wait(1.e-4)
except Exception as e:
print(fandango.except2str())
print('%s.callback(%s): %s' % (self, cb, e))
def decorate(self, target):
if isCallable(target):
self.f = target
self.f_name = target.__name__
#self.call = wraps(self.f)(self.__call__) #Not for methods!!
functools.update_wrapper(self, self.f)
else:
self.f = None
def decimation(history, method, window='0', logger_obj=None, N=1080):
"""
Nones and NaNs are always removed if this method is called
history: array of data
method: method or callable
window: string for time
logger_obj: ArchivedTrendLogger or similar
N: max array size to return
"""
t0 = time.time()
l0 = len(history)
if not l0:
return history
trace = getattr(logger_obj, 'warning', fandango.printf)
try:
window = str2time(window or '0')
except:
window = 0
start_date, stop_date = float(history[0][0]), float(history[-1][0])
## Decimation by data_has_changed is ALWAYS done
if len(history): #method is not None
nv = []
#sq = isSequence(history[0][1])
for i, v in enumerate(history):
if (v[1] not in (None, NaN
) # is not None and (sq or not isNaN(v[1]))
#and (i in (0,l0-1,l0-2) or
#data_has_changed(history[i-1],v,history[i+1]))
):
nv.append(v)
t1 = time.time()
trace('Removed %d (None,NaN, Rep) values in %fs' %
(l0 - len(nv), t1 - t0))
t0, i, c, lh = t1, 0, 0, len(history)
while i < len(history):
if history[c] in (None, NaN):
history.pop(c)
else:
c += 1
i += 1
t1 = time.time()
trace('Removed %d (None,NaN, Rep) values in %fs' %
(l0 - len(history), t1 - t0))
history = nv
if (method and isCallable(method) and method != data_has_changed
and len(history)
and type(history[0][-1]) in (int, float, bool)): #type(None)):
# Data is filtered applying an averaging at every "window" interval.
# As range() only accept integers the minimum window is 1 second.
# It means that filtering 3 hours will implicitly prune millis data.
#DATA FROM EVAL IS ALREADY FILTERED; SHOULD NOT PASS THROUGH HERE
wmin = max(1., (stop_date - start_date) / (10 * 1080.))
wauto = max(1., (stop_date - start_date) / (10 * N))
trace('WMIN,WUSER,WAUTO = %s,%s,%s' % (wmin, window, wauto))
window = wauto if not window else max((wmin, window))
if len(history) > (stop_date - start_date) / window:
history = fandango.arrays.filter_array(data=history,
window=window,
method=method)
t2 = time.time()
trace('Decimated %d values to %d in %f seconds '
'(%s,%s)' % (l0, len(history), t2 - t1, method, window))
else:
trace('Decimation is not callable')
return history
def _log(self, msg):
if isCallable(self.log): self.log(msg)
elif self.log: print(msg)