def average(norm_img: Stream, reset: Stream = None, **kwargs):
"""Perform a running average
Parameters
----------
norm_img : Stream
The data to be averaged as a stream
reset : Stream, optional
If provided, when data comes from this stream reset the averaging
Returns
-------
locals : dict
The locals
"""
img_sum = norm_img.accumulate(op.add, reset_stream=reset)
img_count = norm_img.accumulate(sum_state, start=0, reset_stream=reset)
ave_img = img_sum.zip(img_count).starmap(op.truediv)
return locals()
def test_accumulate():
a = Stream()
b = a.accumulate(lambda x, y: x + y)
L = b.sink_to_list()
LL = []
for i in range(10):
a.emit(i)
if len(LL) == 0:
LL.append(i)
else:
LL.append(i + LL[-1])
assert L == LL
def test_accumulate_reset():
a = Stream()
rn = Stream()
b = a.accumulate(lambda x, y: x + y, reset_stream=rn)
L = b.sink_to_list()
LL = []
for i in range(10):
if i == 5:
rn.emit('hi')
a.emit(i)
if len(LL) == 0 or i == 5:
LL.append(i)
else:
LL.append(i + LL[-1])
assert L == LL
def test_accumulate_errors_raises():
a = Stream()
b = a.accumulate(lambda x, y: x / y)
with pytest.raises(ZeroDivisionError):
a.emit(1)
a.emit(0)
