def average(source: Observable) -> Observable:
"""Partially applied average operator.
Computes the average of an observable sequence of values that
are in the sequence or obtained by invoking a transform
function on each element of the input sequence if present.
Examples:
>>> res = average(source)
Args:
source: Source observable to average.
Returns:
An observable sequence containing a single element with the
average of the sequence of values.
"""
if key_mapper:
return source.pipe(operators.map(key_mapper), operators.average())
def accumulator(prev, cur):
return AverageValue(sum=prev.sum + cur, count=prev.count + 1)
def mapper(s):
if s.count == 0:
raise Exception('The input sequence was empty')
return s.sum / float(s.count)
seed = AverageValue(sum=0, count=0)
return source.pipe(operators.scan(accumulator, seed), operators.last(),
operators.map(mapper))
def test_average_int32_empty(self):
scheduler = TestScheduler()
msgs = [on_next(150, 1), on_completed(250)]
xs = scheduler.create_hot_observable(msgs)
res = scheduler.start(create=lambda: xs.pipe(_.average())).messages
assert(len(res) == 1)
assert(res[0].value.kind == 'E' and res[0].value.exception != None)
assert(res[0].time == 250)
def test_average_int32_empty(self):
scheduler = TestScheduler()
msgs = [on_next(150, 1), on_completed(250)]
xs = scheduler.create_hot_observable(msgs)
res = scheduler.start(create=lambda: xs.pipe(_.average())).messages
assert (len(res) == 1)
assert (res[0].value.kind == 'E' and res[0].value.exception != None)
assert (res[0].time == 250)
def average(source: Observable) -> Observable:
"""Partially applied average operator.
Computes the average of an observable sequence of values that
are in the sequence or obtained by invoking a transform
function on each element of the input sequence if present.
Examples:
>>> res = average(source)
Args:
source: Source observable to average.
Returns:
An observable sequence containing a single element with the
average of the sequence of values.
"""
if key_mapper:
return source.pipe(
operators.map(key_mapper),
operators.average()
)
def accumulator(prev, cur):
return AverageValue(sum=prev.sum+cur, count=prev.count+1)
def mapper(s):
if s.count == 0:
raise Exception('The input sequence was empty')
return s.sum / float(s.count)
seed = AverageValue(sum=0, count=0)
return source.pipe(
operators.scan(accumulator, seed),
operators.last(),
operators.map(mapper)
)
from rx import of, operators as op
"""this operator will calculate the average from
the source observable given and output an observable that will have the average value.
"""
my_of = of(1,2,3,4,5,6,7,8,9,10)
my_of.pipe(
op.average()
).subscribe(lambda i: print("average is {}".format(i)))
# result
# value is 5.5
import rx
import rx.operators as ops
numbers = rx.from_([1, 2, 3, 4])
numbers.pipe(ops.average()).subscribe(
on_next=lambda i: print("on_next {}".format(i)),
on_error=lambda e: print("on_error: {}".format(e)),
on_completed=lambda: print("on_completed")
)
def create():
return xs.pipe(_.average(len))
import rx
from rx import operators as ops
pipe = rx.range(1, 11) \
.pipe(ops.filter(lambda i: i % 2 == 0),
ops.filter(lambda i: i < 3),
ops.map(lambda i: i + i),
ops.map(lambda i: i ** i),
ops.average(lambda x: x + x),
ops.sum())
pipe.subscribe(lambda x: print("value is {0}".format(x)))
def stream(self):
return self.subject_.pipe(
ops.window_with_time(self.window),
ops.map(lambda x: x.pipe(ops.average(), ops.first())),
ops.merge_all()
)
def create():
return xs.pipe(_.average(len))