def test_source_file(filename):
s = Stream('s')
with open(filename, 'r') as input_file:
for line in input_file:
s.append(int(line))
run()
assert recent_values(s) == [1, 2, 3]
def colorCapuaFictaTest():
(n11,n12,n13,n14) = (Note(), Note(), Note(), Note())
(n21,n22,n23,n24) = (Note(), Note(), Note(), Note())
n11.duration.type = "quarter"
n11.name = "D"
n12.duration.type = "quarter"
n12.name = "E"
n13.duration.type = "quarter"
n13.name = "F"
n14.duration.type = "quarter"
n14.name = "G"
n21.name = "C"
n21.duration.type = "quarter"
n22.name = "C"
n22.duration.type = "quarter"
n23.name = "B"
n23.octave = 3
n23.duration.type = "quarter"
n24.name = "C"
n24.duration.type = "quarter"
stream1 = Stream()
stream1.append([n11, n12, n13, n14])
stream2 = Stream()
stream2.append([n21, n22, n23, n24])
### Need twoStreamComparer to Work
capua.evaluateWithoutFicta(stream1, stream2)
assert n13.editorial.harmonicInterval.name == "d5", n13.editorial.harmonicInterval.name
capua.evaluateCapuaTwoStreams(stream1, stream2)
capua.colorCapuaFicta(stream1, stream2, "both")
assert n13.editorial.harmonicInterval.name == "P5", n13.editorial.harmonicInterval.name
assert n11.editorial.color == "yellow"
assert n12.editorial.color == "yellow"
assert n13.editorial.color == "green"
assert n14.editorial.color == "yellow"
assert n11.editorial.harmonicInterval.name == "M2"
assert n21.editorial.harmonicInterval.name == "M2"
assert n13.editorial.harmonicInterval.name == "P5"
assert n13.editorial.misc["noFictaHarmony"] == "perfect cons"
assert n13.editorial.misc["capua2FictaHarmony"] == "perfect cons"
assert n13.editorial.misc["capua2FictaInterval"].name == "P5"
assert n13.editorial.color == "green"
assert stream1.lily.strip() == r'''\clef "treble" \color "yellow" d'4 \color "yellow" e'4 \ficta \color "green" fis'!4 \color "yellow" g'4'''
def match(self, token_stream):
groups = Stream()
while True:
e = token_stream.peek()
if self.filter_func(e):
groups.append(e)
next(token_stream)
else:
break
d = token_stream.peek()
if d == self.delimiter:
next(token_stream)
else:
break
return Match(True, groups=groups)
def match(self, token_stream):
groups = Stream()
try:
for i, p in enumerate(self.pattern):
token = token_stream[i]
if isinstance(p, TokenType) and token.token_type == p:
groups.append(token)
elif isinstance(p, str) and token == Token(p):
continue
else:
break
else:
token_stream.consume(self.pattern_len)
return Match(True, groups=groups)
except StopIteration:
pass
return Match(False)
def sort(lst):
def flip(I, L):
i = I[0]
if lst[i] > lst[i+1]:
lst[i], lst[i+1] = lst[i+1], lst[i]
return (1)
else:
return (_no_value)
x = Stream('x')
for i in range(len(lst) - 1):
signal_element(func=flip, in_stream=x, out_stream=x, name=i, I=[i], L=lst)
scheduler = Stream.scheduler
x.append(1)
scheduler.step()
def shortest_path(D):
def triangle_inequality(triple, D):
i, j, k = triple
if D[i][j] + D[j][k] < D[i][k]:
D[i][k] = D[i][j] + D[j][k]
D[k][i] = D[i][k]
return(1)
else:
return (_no_value)
x = Stream('x')
size = len(D)
for i in range(size):
for j in range(i):
for k in range(size):
signal_element(func=triangle_inequality,
in_stream=x, out_stream=x,
name=str(i)+"_"+str(j)+"_"+str(k),
triple=[i, j, k], D=D)
scheduler = Stream.scheduler
x.append(1)
scheduler.step()
return D
def test_window_agents():
scheduler = Stream.scheduler
q = Stream('q')
qq = Stream('qq')
r = Stream('r')
s = Stream('s')
t = Stream('t')
u = Stream('u')
v = Stream('v')
w = Stream('w')
x = Stream('x')
y = Stream('y')
z = Stream('z')
a = Stream('a')
b = Stream('b')
c = Stream('c')
yy = Stream('yy')
zz = Stream('zz')
#----------------------------------------------------------------
# Test simple window map agent with the same window size and step size
smap = map_window_f(func=sum, in_stream=r, window_size=4, step_size=4)
map_window(func=sum, in_stream=r, out_stream=s, window_size=4, step_size=4)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test simple window list agent with the same window size and step size
def f_map_window_list(lst):
return [max(lst)] * len(lst)
s_list = Stream('s list')
map_window_list(func=f_map_window_list,
in_stream=r,
out_stream=s_list,
window_size=4,
step_size=4)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window map agent with different window and step sizes
map_window(func=sum, in_stream=r, out_stream=t, window_size=3, step_size=2)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window map agent with a NumPy function
map_window(func=np.mean,
in_stream=r,
out_stream=q,
window_size=3,
step_size=2,
name='bb')
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window map agent with arguments
def map_with_args(window, addend):
return np.mean(window) + addend
map_window(func=map_with_args,
in_stream=r,
out_stream=qq,
window_size=3,
step_size=2,
addend=1)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window map agent with user-defined function and no state
map_window(func=lambda v: sum(v) + 1,
in_stream=r,
out_stream=u,
window_size=4,
step_size=4)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window map agent with state
def g(lst, state):
return sum(lst) + state, sum(lst) + state
map_window(func=g,
in_stream=r,
out_stream=v,
window_size=4,
step_size=4,
state=0)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window merge agent with no state
def h(list_of_windows):
return sum([sum(window) for window in list_of_windows])
merge_window(func=h,
in_streams=[r, w],
out_stream=x,
window_size=3,
step_size=3)
merge_stream = merge_window_f(func=h,
in_streams=[r, w],
window_size=3,
step_size=3)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window merge agent with state
def h_with_state(list_of_windows, state):
return (sum([sum(window)
for window in list_of_windows]) + state, state + 1)
merge_window(func=h_with_state,
in_streams=[r, w],
out_stream=a,
window_size=3,
step_size=3,
state=0)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window split agent with no state
def splt(window):
return sum(window), max(window)
split_window(func=splt,
in_stream=r,
out_streams=[y, z],
window_size=3,
step_size=3)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window split agent with state
def split_with_state(window, state):
return (sum(window) + state, max(window) + state), state + 1
split_window(func=split_with_state,
in_stream=r,
out_streams=[yy, zz],
window_size=3,
step_size=3,
state=0)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window many-to-many with state and args
def func_multi_window_with_state_and_args(windows, state, cutoff):
return ((max(max(windows[0]), max(windows[1]), cutoff, state),
min(min(windows[0]), min(windows[1]), cutoff,
state)), state + 2)
multi_window(func=func_multi_window_with_state_and_args,
in_streams=[r, w],
out_streams=[b, c],
state=0,
window_size=3,
step_size=3,
cutoff=15)
multi_window_b, multi_window_c = multi_window_f(
func=func_multi_window_with_state_and_args,
in_streams=[r, w],
num_out_streams=2,
state=0,
window_size=3,
step_size=3,
cutoff=15)
#----------------------------------------------------------------
#----------------------------------------------------------------
r.extend(list(range(16)))
scheduler.step()
assert recent_values(r) == [
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
]
assert recent_values(s) == [
0 + 1 + 2 + 3, 4 + 5 + 6 + 7, 8 + 9 + 10 + 11, 12 + 13 + 14 + 15
]
assert recent_values(smap) == recent_values(s)
assert recent_values(t) == [
0 + 1 + 2, 2 + 3 + 4, 4 + 5 + 6, 6 + 7 + 8, 8 + 9 + 10, 10 + 11 + 12,
12 + 13 + 14
]
assert recent_values(q) == [1, 3, 5, 7, 9, 11, 13]
assert recent_values(qq) == [2, 4, 6, 8, 10, 12, 14]
assert recent_values(u) == [
0 + 1 + 2 + 3 + 1, 4 + 5 + 6 + 7 + 1, 8 + 9 + 10 + 11 + 1,
12 + 13 + 14 + 15 + 1
]
assert recent_values(v) == [6, 28, 66, 120]
assert recent_values(w) == []
assert recent_values(x) == []
assert recent_values(merge_stream) == recent_values(x)
# y is sum of windows of r with window and step size of 3
assert recent_values(y) == [3, 12, 21, 30, 39]
assert recent_values(yy) == [3, 13, 23, 33, 43]
# y is max of windows of r with window and step size of 3
assert recent_values(z) == [2, 5, 8, 11, 14]
assert recent_values(zz) == [2, 6, 10, 14, 18]
assert recent_values(a) == []
assert recent_values(b) == []
assert recent_values(c) == []
#----------------------------------------------------------------
#----------------------------------------------------------------
# Step through the scheduler
#----------------------------------------------------------------
#----------------------------------------------------------------
w.extend([10, 12, 14, 16, 18])
scheduler.step()
assert recent_values(r) == [
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15
]
assert recent_values(s) == [
0 + 1 + 2 + 3, 4 + 5 + 6 + 7, 8 + 9 + 10 + 11, 12 + 13 + 14 + 15
]
assert recent_values(s_list) == [
3, 3, 3, 3, 7, 7, 7, 7, 11, 11, 11, 11, 15, 15, 15, 15
]
assert recent_values(smap) == recent_values(s)
assert recent_values(t) == [
0 + 1 + 2, 2 + 3 + 4, 4 + 5 + 6, 6 + 7 + 8, 8 + 9 + 10, 10 + 11 + 12,
12 + 13 + 14
]
assert recent_values(q) == [1, 3, 5, 7, 9, 11, 13]
assert recent_values(qq) == [2, 4, 6, 8, 10, 12, 14]
assert recent_values(u) == [
0 + 1 + 2 + 3 + 1, 4 + 5 + 6 + 7 + 1, 8 + 9 + 10 + 11 + 1,
12 + 13 + 14 + 15 + 1
]
assert recent_values(v) == [6, 28, 66, 120]
assert recent_values(w) == [10, 12, 14, 16, 18]
assert recent_values(x) == [(0 + 1 + 2) + (10 + 12 + 14)]
assert recent_values(merge_stream) == recent_values(x)
assert recent_values(y) == [3, 12, 21, 30, 39]
assert recent_values(yy) == [3, 13, 23, 33, 43]
assert recent_values(z) == [2, 5, 8, 11, 14]
assert recent_values(zz) == [2, 6, 10, 14, 18]
assert recent_values(a) == [39]
assert recent_values(b) == [15]
assert recent_values(c) == [0]
#----------------------------------------------------------------
r.extend([10, -10, 21, -20])
scheduler.step()
assert recent_values(s) == [6, 22, 38, 54, 1]
assert recent_values(s_list) == \
[3, 3, 3, 3, 7, 7, 7, 7, 11, 11, 11, 11, 15, 15, 15, 15, 21, 21, 21, 21]
assert recent_values(smap) == recent_values(s)
assert recent_values(t) == [
0 + 1 + 2, 2 + 3 + 4, 4 + 5 + 6, 6 + 7 + 8, 8 + 9 + 10, 10 + 11 + 12,
12 + 13 + 14, 14 + 15 + 10, 10 + (-10) + 21
]
assert recent_values(q) == [1, 3, 5, 7, 9, 11, 13, 13, 7]
assert recent_values(qq) == [2, 4, 6, 8, 10, 12, 14, 14, 8]
assert recent_values(u) == [
0 + 1 + 2 + 3 + 1, 4 + 5 + 6 + 7 + 1, 8 + 9 + 10 + 11 + 1,
12 + 13 + 14 + 15 + 1, 10 + (-10) + 21 + (-20) + 1
]
assert recent_values(v) == [6, 28, 66, 120, 121]
assert recent_values(w) == [10, 12, 14, 16, 18]
assert recent_values(x) == [(0 + 1 + 2) + (10 + 12 + 14)]
assert recent_values(merge_stream) == recent_values(x)
assert recent_values(y) == [3, 12, 21, 30, 39, 15]
assert recent_values(yy) == [3, 13, 23, 33, 43, 20]
assert recent_values(z) == [2, 5, 8, 11, 14, 15]
assert recent_values(zz) == [2, 6, 10, 14, 18, 20]
assert recent_values(a) == [39]
assert recent_values(b) == [15]
assert recent_values(c) == [0]
#----------------------------------------------------------------
w.append(20)
scheduler.step()
assert recent_values(s) == [6, 22, 38, 54, 1]
assert recent_values(smap) == recent_values(s)
assert recent_values(t) == [
0 + 1 + 2, 2 + 3 + 4, 4 + 5 + 6, 6 + 7 + 8, 8 + 9 + 10, 10 + 11 + 12,
12 + 13 + 14, 14 + 15 + 10, 10 + (-10) + 21
]
assert recent_values(q) == [1, 3, 5, 7, 9, 11, 13, 13, 7]
assert recent_values(qq) == [2, 4, 6, 8, 10, 12, 14, 14, 8]
assert recent_values(u) == [
0 + 1 + 2 + 3 + 1, 4 + 5 + 6 + 7 + 1, 8 + 9 + 10 + 11 + 1,
12 + 13 + 14 + 15 + 1, 10 + (-10) + 21 + (-20) + 1
]
assert recent_values(v) == [6, 28, 66, 120, 121]
assert recent_values(w) == [10, 12, 14, 16, 18, 20]
assert recent_values(x) == [(0 + 1 + 2) + (10 + 12 + 14),
(3 + 4 + 5) + (16 + 18 + 20)]
assert recent_values(merge_stream) == recent_values(x)
assert recent_values(y) == [3, 12, 21, 30, 39, 15]
assert recent_values(yy) == [3, 13, 23, 33, 43, 20]
assert recent_values(z) == [2, 5, 8, 11, 14, 15]
assert recent_values(zz) == [2, 6, 10, 14, 18, 20]
assert recent_values(a) == [39, 67]
assert recent_values(b) == [15, 20]
assert recent_values(multi_window_b) == recent_values(b)
assert recent_values(c) == [0, 2]
assert recent_values(multi_window_c) == recent_values(c)
#----------------------------------------------------------------
r.extend([-1, 1, 0])
scheduler.step()
assert recent_values(s) == [6, 22, 38, 54, 1]
assert recent_values(smap) == recent_values(s)
assert recent_values(t) == [
0 + 1 + 2, 2 + 3 + 4, 4 + 5 + 6, 6 + 7 + 8, 8 + 9 + 10, 10 + 11 + 12,
12 + 13 + 14, 14 + 15 + 10, 10 + (-10) + 21, 21 - 20 - 1, -1 + 1 + 0
]
assert recent_values(q) == [1, 3, 5, 7, 9, 11, 13, 13, 7, 0, 0]
assert recent_values(qq) == [2, 4, 6, 8, 10, 12, 14, 14, 8, 1, 1]
assert recent_values(u) == [7, 23, 39, 55, 2]
assert recent_values(v) == [6, 28, 66, 120, 121]
assert recent_values(w) == [10, 12, 14, 16, 18, 20]
assert recent_values(x) == [(0 + 1 + 2) + (10 + 12 + 14),
(3 + 4 + 5) + (16 + 18 + 20)]
assert recent_values(merge_stream) == recent_values(x)
assert recent_values(y) == [3, 12, 21, 30, 39, 15, 0]
assert recent_values(yy) == [3, 13, 23, 33, 43, 20, 6]
assert recent_values(z) == [2, 5, 8, 11, 14, 15, 21]
assert recent_values(zz) == [2, 6, 10, 14, 18, 20, 27]
assert recent_values(a) == [39, 67]
assert recent_values(b) == [15, 20]
assert recent_values(multi_window_b) == recent_values(b)
assert recent_values(c) == [0, 2]
assert recent_values(multi_window_c) == recent_values(c)
#----------------------------------------------------------------
#----------------------------------------------------------------
# TEST WINDOW WITH STREAM ARRAY
#----------------------------------------------------------------
#----------------------------------------------------------------
# Simple linear arrays
x = StreamArray('x')
y = StreamArray('y')
#----------------------------------------------------------------
# Test window map agent with stream arrays and a NumPy function
map_window(func=np.mean,
in_stream=x,
out_stream=y,
window_size=3,
step_size=3,
name='window map agent for arrays')
#----------------------------------------------------------------
#----------------------------------------------------------------
x.extend(np.linspace(0.0, 11.0, 12))
scheduler.step()
assert np.array_equal(recent_values(x), np.linspace(0.0, 11.0, 12))
# y[0] = (0+1+2)//3.0, y[1] = (3+4+5)//3.0
assert np.array_equal(recent_values(y), np.array([1.0, 4.0, 7.0, 10.0]))
x = StreamArray('x', dimension=2)
y = StreamArray('y', dimension=2)
z = StreamArray('z', dimension=2)
a = StreamArray('a', dimension=2)
b = StreamArray('b', dimension=2)
c = StreamArray('c', dimension=2)
d = StreamArray('d', dimension=2)
p = StreamArray('p', dimension=2)
q = StreamArray('q', dimension=2)
r = StreamArray('r', dimension=2)
s = StreamArray('s', dimension=2)
t = StreamArray('t', dimension=2)
#----------------------------------------------------------------
# Test window map agent with stream arrays and a NumPy function
# f() and ff() differ only in the axis.
def f(input_array):
return np.mean(input_array, axis=0)
def ff(input_array):
return np.mean(input_array, axis=1)
map_window(func=f,
in_stream=x,
out_stream=y,
window_size=2,
step_size=2,
name='window map agent for arrays')
map_window(func=ff,
in_stream=x,
out_stream=t,
window_size=2,
step_size=2,
name='window map agent for arrays ff')
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window sink with stream arrays
def sum_array(input_array, output_list):
output_list.append(sum(input_array))
sum_array_list = []
sink_window(func=sum_array,
in_stream=x,
window_size=2,
step_size=2,
name='sum array',
output_list=sum_array_list)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window map agent with state
def g(lst, state):
return sum(lst) + state, state + 1
map_window(func=g,
in_stream=x,
out_stream=z,
window_size=2,
step_size=2,
state=0)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window merge agent with state
def h_array(list_of_windows, state):
return (sum([sum(window)
for window in list_of_windows]) + state, state + 1)
merge_window(func=h_array,
in_streams=[x, a],
out_stream=b,
window_size=2,
step_size=2,
state=0)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window split agent with state
def split_with_state(window, state):
return [np.sum(window, axis=0)+state, np.max(window, axis=0)+state], \
state+1.0
split_window(func=split_with_state,
in_stream=x,
out_streams=[c, d],
window_size=2,
step_size=2,
state=0.0)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window many-to-many with state and args
def func_multi_window_with_state_and_args(windows, state, cutoff):
max_value = np.maximum(np.max(windows[0], axis=0),
np.max(windows[1], axis=0))
max_value = np.maximum(max_value, cutoff) + state
min_value = np.minimum(np.min(windows[0], axis=0),
np.min(windows[1], axis=0))
min_value = np.minimum(min_value, cutoff) + state
return (max_value, min_value), state + 1
multi_window(func=func_multi_window_with_state_and_args,
in_streams=[x, a],
out_streams=[r, s],
state=0,
window_size=2,
step_size=2,
cutoff=10)
#----------------------------------------------------------------
x.extend(np.array([[1., 5.], [7., 11.]]))
a.extend(np.array([[0., 1.], [2., 3.]]))
scheduler.step()
# sum_array_list is the sum of x with window size, step size of 2
assert np.array_equal(sum_array_list, [np.array([1. + 7., 5. + 11.])])
# y is the mean of x with window size and step size of 2
assert np.array_equal(recent_values(x), np.array([[1., 5.], [7., 11.]]))
assert np.array_equal(recent_values(y),
np.array([[(1. + 7.) // 2.0, (5. + 11.) // 2.]]))
assert np.array_equal(recent_values(t),
np.array([[(1. + 5.) // 2.0, (7. + 11.) // 2.]]))
assert np.array_equal(recent_values(z), np.array([[1. + 7., 5. + 11]]))
assert np.array_equal(recent_values(b),
[np.array([1. + 7. + 0. + 2., 5. + 11. + 1. + 3.])])
assert np.array_equal(recent_values(c), np.array([[8., 16.]]))
assert np.array_equal(recent_values(d), np.array([[7., 11.]]))
assert np.array_equal(recent_values(r), np.array([[10., 11.]]))
assert np.array_equal(recent_values(s), np.array([[0., 1.]]))
a.extend(np.array([[0., 1.], [1., 0.]]))
scheduler.step()
assert np.array_equal(recent_values(y),
np.array([[(1. + 7.) / 2.0, (5. + 11.) / 2.]]))
assert np.array_equal(recent_values(z), np.array([[1. + 7., 5. + 11]]))
assert np.array_equal(recent_values(b),
[np.array([1. + 7. + 0. + 2., 5. + 11. + 1. + 3.])])
assert np.array_equal(recent_values(c), np.array([[8., 16.]]))
assert np.array_equal(recent_values(d), np.array([[7., 11.]]))
assert np.array_equal(recent_values(r), np.array([[10., 11.]]))
assert np.array_equal(recent_values(s), np.array([[0., 1.]]))
x.extend(np.array([[14., 18.], [18., 30.], [30., 38.], [34., 42.]]))
scheduler.step()
assert np.array_equal(recent_values(y),
np.array([[4., 8.], [16., 24.], [32., 40.]]))
assert np.array_equal(recent_values(z),
np.array([[8., 16.], [33., 49.], [66., 82.]]))
assert np.array_equal(recent_values(c),
np.array([[8., 16.], [33., 49.], [66., 82.]]))
assert np.array_equal(recent_values(d),
np.array([[7., 11.], [19., 31.], [36., 44.]]))
assert np.array_equal(recent_values(r), np.array([[10., 11.], [19., 31.]]))
assert np.array_equal(recent_values(s), np.array([[0., 1.], [1., 1.]]))
print('TEST OF OP (WINDOW) IS SUCCESSFUL')
return
def primes_example_2(N):
"""
Agent used in example 2 in which prime_stream is the sequence of
primes up to the N-th prime
Parameters
----------
N: int
positive integer
Returns: first_N, prime_stream
-------
first_N: list
The first N primes
prime_stream: Stream
Stream of prime numbers. May have more than N primes
Notes
-----
sieve creates a single sink agent. The sink agent has a single
input stream, in_stream. The agent encapsulates stateful function
f which has an initial state of 0. (Sinks have no output streams.)
Let the first element of in_stream be p. This agent assumes that p
is a prime number. So, the agent appends p to prime_stream. Many
agents append prime numbers to prime_stream, but at most one agent
can do so at a time.
When the agent discovers an element of in_stream that is not a
multiple of p, the agent creates a new sieve agent which takes a
new stream out_stream as its input stream. out_stream consists of
elements of in_stream that are not multiples of p.
"""
def execute_until_stop_message(v, state, function):
function_state, finished_execution = state
if finished_execution:
return (_no_value, True)
index, input_value = v
if index == 1:
# This value is from stop_stream
# Make finished_execution become True because a message
# was received on stop_stream.
finished_execution = True
# From now onwards, no messages are appended to the output
# stream, and finished_execution remains True forever.
return (_no_value, (function_state, True))
# index is 0. So, this value is from state_stream.
output_value, next_function_state = function(input_value,
function_state)
# next_state = (next_function_state, finished_execution)
return output_value, (next_function_state, finished_execution)
def generate_numbers_until_stop_message(index_and_value, state):
# state is initially False and switches to True if a message
# is received in stop_stream. If state becomes True then it
# remains True thereafter. After state becomes True no values
# are appended to the output stream.
# The elements of the input stream are tuples: index and
# value.
# index is 0 for state_stream and 1 for stop_stream.
index, value = index_and_value
if index == 1:
# This value is from stop_stream
# Make state True because a message was received on
# stop_stream.
# From now onwards, no messages are appended to the output
# stream, and state remains True.
return (_no_value, True)
# index is 0. So, this value is from state_stream.
if state:
# Do not append values to the output stream, and state
# remains True
return (_no_value, state)
else:
# Append the next value to the output stream, and state
# remains False.
return (value + 1, state)
def detect_finished_then_send_stop(v, state, N):
length, stop = state
# If stop is True then computation must stop
length += 1
if length >= N and not stop:
stop = True
return (True, (length, stop))
else:
return (_no_value, (length, stop))
def first_N_elements(in_stream, N, first_N):
def first_N_elements_of_stream(v, state, N, first_N):
if state < N:
first_N.append(v)
state += 1
return state
sink(func=first_N_elements_of_stream,
in_stream=in_stream,
state=0,
N=N,
first_N=first_N)
#-----------------------------------------------------------------
# Define streams
#-----------------------------------------------------------------
state_stream = Stream(name='numbers 2, 3, 4, ...')
stop_stream = Stream(name='stop!')
prime_stream = Stream(name='prime numbers')
first_N = []
#-----------------------------------------------------------------
# Define agents
#-----------------------------------------------------------------
# Create agent that generates 2, 3, 4... until it receives a
# message on stop_stream
## merge_asynch(func=generate_numbers_until_stop_message,
## in_streams=[state_stream, stop_stream],
## out_stream=state_stream, state=False)
def g(v, state):
return v + 1, state
merge_asynch(func=execute_until_stop_message,
in_streams=[state_stream, stop_stream],
out_stream=state_stream,
state=(None, False),
function=g)
# Create an agent that sieves state_stream to create prime_stream
# which is a sequence of primes.
# We do this by creating a sink agent that encapsulates a stateful
# function f with an initial state of 0. Pass parameters
# prime_stream and out_stream from the sink agent to its
# encapsulated function f.
sieve(in_stream=state_stream, prime_stream=prime_stream)
# Create an agent that sends a message on stop_stream when the
# length of prime_stream exceeds N.
map_element(func=detect_finished_then_send_stop,
in_stream=prime_stream,
out_stream=stop_stream,
state=(0, False),
N=N)
first_N_elements(in_stream=prime_stream, N=N, first_N=first_N)
state_stream.append(2)
return first_N, prime_stream
def test_list():
scheduler = Stream.scheduler
n = Stream('n')
o = Stream('o')
p = Stream('p')
q = Stream('q')
r = Stream('r')
s = Stream('s')
t = Stream('t')
u = Stream('u')
v = Stream('v')
w = Stream('w')
x = Stream('x')
y = Stream('y')
z = Stream('z')
#-------------------------------------------------------------------
# Test simple map
def simple(lst):
return [2 * v for v in lst]
a = map_list(func=simple, in_stream=x, out_stream=y, name='a')
yy = map_list_f(simple, x)
#-------------------------------------------------------------------
#-------------------------------------------------------------------
# Test map with state
# Function that operates on an element and state and returns an
# element and state.
def f(input_list, state):
output_list = [[]] * len(input_list)
for i in range(len(input_list)):
output_list[i] = input_list[i] + state
state += 2
return output_list, state
b = map_list(func=f, in_stream=x, out_stream=z, state=0, name='b')
zz = map_list_f(f, x, 0)
#-------------------------------------------------------------------
#-------------------------------------------------------------------
# Test map with call streams
c = map_list(func=f,
in_stream=x,
out_stream=v,
state=10,
call_streams=[w],
name='c')
#-------------------------------------------------------------------
#-------------------------------------------------------------------
# Test sink with state
def sink_with_state(input_list, output_list):
# sink has no output stream.
# This function only returns the next state.
return output_list.extend(input_list)
out_list = []
# In this simple example, out_list will be the same as the input
# stream.
sink_agent = sink_list(func=sink_with_state,
in_stream=x,
name='sink_agent',
state=out_list)
out_list_stream = []
# Function version of the previous agent example
sink_list_f(sink_with_state, x, out_list_stream)
#-------------------------------------------------------------------
#-------------------------------------------------------------------
# Test merge
# Function that operates on a list of lists
def g(list_of_lists):
return [sum(snapshot) for snapshot in zip(*list_of_lists)]
d = merge_list(func=g, in_streams=[x, u], out_stream=s, name='d')
ss = merge_list_f(g, [x, u])
#-------------------------------------------------------------------
#-------------------------------------------------------------------
# Test split
def h(input_list):
return [[element + 1 for element in input_list],
[element * 2 for element in input_list]]
e = split_list(func=h, in_stream=x, out_streams=[r, t], name='e')
rr, tt = split_list_f(h, x, num_out_streams=2)
#-------------------------------------------------------------------
#-------------------------------------------------------------------
# Test split with state
def h_state(input_list, state):
length = len(input_list)
output_list_0 = [[]] * length
output_list_1 = [[]] * length
for i in range(length):
output_list_0[i] = input_list[i] + state
output_list_1[i] = input_list[i] * state
state += 1
return ([output_list_0, output_list_1], state)
split_list(func=h_state, in_stream=x, out_streams=[p, q], state=0)
pp, qq = split_list_f(h_state, x, num_out_streams=2, state=0)
#-------------------------------------------------------------------
#-------------------------------------------------------------------
# Test many
def f_many(list_of_lists):
snapshots = zip(*list_of_lists)
return [[max(snapshot) for snapshot in snapshots],
[min(snapshot) for snapshot in snapshots]]
multi_agent = multi_list(func=f_many,
in_streams=[x, u],
out_streams=[n, o],
name='multi_agent')
nn, oo = multi_list_f(func=f_many, in_streams=[x, u], num_out_streams=2)
#-------------------------------------------------------------------
#-------------------------------------------------------------------
#-------------------------------------------------------------------
x.extend(range(5))
scheduler.step()
assert recent_values(x) == range(5)
assert recent_values(y) == [0, 2, 4, 6, 8]
assert recent_values(z) == [0, 3, 6, 9, 12]
assert recent_values(v) == []
assert out_list == range(5)
assert out_list == out_list_stream
assert recent_values(s) == []
assert recent_values(r) == [1, 2, 3, 4, 5]
assert recent_values(t) == [0, 2, 4, 6, 8]
assert recent_values(p) == [0, 2, 4, 6, 8]
assert recent_values(q) == [0, 1, 4, 9, 16]
assert recent_values(n) == []
assert recent_values(o) == []
assert recent_values(y) == recent_values(yy)
assert recent_values(z) == recent_values(zz)
assert recent_values(s) == recent_values(ss)
assert recent_values(r) == recent_values(rr)
assert recent_values(t) == recent_values(tt)
assert recent_values(p) == recent_values(pp)
assert recent_values(q) == recent_values(qq)
assert recent_values(n) == recent_values(nn)
assert recent_values(o) == recent_values(oo)
#-------------------------------------------------------------------
#-------------------------------------------------------------------
w.append(0)
scheduler.step()
assert recent_values(x) == range(5)
assert recent_values(y) == [0, 2, 4, 6, 8]
assert recent_values(z) == [0, 3, 6, 9, 12]
assert recent_values(v) == [10, 13, 16, 19, 22]
assert out_list == range(5)
assert recent_values(s) == []
assert recent_values(r) == [1, 2, 3, 4, 5]
assert recent_values(t) == [0, 2, 4, 6, 8]
assert recent_values(p) == [0, 2, 4, 6, 8]
assert recent_values(q) == [0, 1, 4, 9, 16]
assert recent_values(n) == []
assert recent_values(o) == []
assert recent_values(y) == recent_values(yy)
assert recent_values(z) == recent_values(zz)
assert recent_values(s) == recent_values(ss)
assert recent_values(r) == recent_values(rr)
assert recent_values(t) == recent_values(tt)
assert recent_values(p) == recent_values(pp)
assert recent_values(q) == recent_values(qq)
assert recent_values(n) == recent_values(nn)
assert recent_values(o) == recent_values(oo)
#-------------------------------------------------------------------
#-------------------------------------------------------------------
u.extend([10, 15, 18])
scheduler.step()
assert recent_values(s) == [10, 16, 20]
assert recent_values(n) == [10, 15, 18]
assert recent_values(o) == [0, 1, 2]
u.append(37)
scheduler.step()
assert recent_values(s) == [10, 16, 20, 40]
assert recent_values(n) == [10, 15, 18, 37]
assert recent_values(o) == [0, 1, 2, 3]
u.extend([96, 95])
scheduler.step()
assert recent_values(x) == range(5)
assert recent_values(y) == [0, 2, 4, 6, 8]
assert recent_values(z) == [0, 3, 6, 9, 12]
assert recent_values(v) == [10, 13, 16, 19, 22]
assert out_list == range(5)
assert recent_values(s) == [10, 16, 20, 40, 100]
assert recent_values(r) == [1, 2, 3, 4, 5]
assert recent_values(t) == [0, 2, 4, 6, 8]
assert recent_values(p) == [0, 2, 4, 6, 8]
assert recent_values(q) == [0, 1, 4, 9, 16]
assert recent_values(n) == [10, 15, 18, 37, 96]
assert recent_values(o) == [0, 1, 2, 3, 4]
assert recent_values(y) == recent_values(yy)
assert recent_values(z) == recent_values(zz)
assert recent_values(s) == recent_values(ss)
assert recent_values(r) == recent_values(rr)
assert recent_values(t) == recent_values(tt)
assert recent_values(p) == recent_values(pp)
assert recent_values(q) == recent_values(qq)
assert recent_values(n) == recent_values(nn)
assert recent_values(o) == recent_values(oo)
#------------------------------------------------------------------
#------------------------------------------------------------------
# Test NumPy arrays: StreamArray
#------------------------------------------------------------------
#------------------------------------------------------------------
# Test list map on StreamArray (dimension is 0).
a_stream_array = StreamArray(name='a_stream_array')
b_stream_array = StreamArray(name='b_stream_array')
def f_np(input_array):
return input_array + 1
a_np_agent = map_list(func=f_np,
in_stream=a_stream_array,
out_stream=b_stream_array,
name='a_np_agent')
bb_stream_array = map_array_f(f_np, a_stream_array)
scheduler.step()
assert np.array_equal(recent_values(b_stream_array),
np.array([], dtype=np.float64))
assert np.array_equal(recent_values(b_stream_array),
recent_values(bb_stream_array))
a_stream_array.extend(np.arange(5.0))
scheduler.step()
assert np.array_equal(recent_values(b_stream_array), np.arange(5.0) + 1)
assert np.array_equal(recent_values(b_stream_array),
recent_values(bb_stream_array))
a_stream_array.extend(np.arange(5.0, 10.0, 1.0))
scheduler.step()
assert np.array_equal(recent_values(b_stream_array), np.arange(10.0) + 1)
assert np.array_equal(recent_values(b_stream_array),
recent_values(bb_stream_array))
# Test list map with state on StreamArray (dimension is 0)
c_stream_array = StreamArray(name='c_stream_array')
d_stream_array = StreamArray(name='d_stream_array')
def f_np_state(input_array, state):
return np.cumsum(input_array) + state, np.sum(input_array)
b_np_agent = map_list(func=f_np_state,
in_stream=c_stream_array,
out_stream=d_stream_array,
state=0.0,
name='b_np_agent')
dd_stream_array = map_array_f(f_np_state, c_stream_array, state=0.0)
scheduler.step()
assert np.array_equal(recent_values(d_stream_array),
np.array([], dtype=np.float64))
assert np.array_equal(recent_values(d_stream_array),
recent_values(dd_stream_array))
c_stream_array.extend(np.arange(5.0))
scheduler.step()
assert np.array_equal(d_stream_array.recent[:d_stream_array.stop],
np.cumsum(np.arange(5.0)))
assert np.array_equal(recent_values(d_stream_array),
recent_values(dd_stream_array))
c_stream_array.extend(np.arange(5.0, 10.0, 1.0))
scheduler.step()
assert np.array_equal(d_stream_array.recent[:d_stream_array.stop],
np.cumsum(np.arange(10.0)))
assert np.array_equal(recent_values(d_stream_array),
recent_values(dd_stream_array))
# Test list map with positive integer dimension on StreamArray
e_stream_array = StreamArray(name='e_stream_array', dimension=3)
f_stream_array = StreamArray(name='f_stream_array', dimension=2)
def f_np_dimension(input_array):
output_array = np.zeros([len(input_array), 2])
output_array[:, 0] = input_array[:, 0] + input_array[:, 1]
output_array[:, 1] = input_array[:, 2]
return output_array
c_np_agent = map_list(func=f_np_dimension,
in_stream=e_stream_array,
out_stream=f_stream_array,
name='c_np_agent')
e_stream_array.extend(np.array([[1.0, 2.0, 3.0]]))
scheduler.step()
assert np.array_equal(f_stream_array.recent[:f_stream_array.stop],
np.array([[3.0, 3.0]]))
e_stream_array.extend(np.array([[4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]))
scheduler.step()
assert np.array_equal(f_stream_array.recent[:f_stream_array.stop],
np.array([[3.0, 3.0], [9.0, 6.0], [15.0, 9.0]]))
# Test list map with a dimension which is a tuple of integers.
g_stream_array = StreamArray(name='g_stream_array', dimension=(2, 2))
h_stream_array = StreamArray(name='h_stream_array', dimension=(2, 2))
def f_np_tuple_dimension(input_array):
return input_array * 2
d_np_agent = map_list(func=f_np_tuple_dimension,
in_stream=g_stream_array,
out_stream=h_stream_array,
name='d_np_agent')
a_array = np.array([[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0, 8.0]]])
g_stream_array.extend(a_array)
scheduler.step()
assert np.array_equal(h_stream_array.recent[:h_stream_array.stop],
a_array * 2)
b_array = np.array([[[9.0, 10.0], [11.0, 12.0]]])
g_stream_array.extend(b_array)
scheduler.step()
assert np.array_equal(h_stream_array.recent[:h_stream_array.stop],
np.vstack((a_array, b_array)) * 2)
# Test list map with a datatype and dimension of 0.
dt_0 = np.dtype([('time', int), ('value', (float, 3))])
dt_1 = np.dtype([('time', int), ('value', float)])
i_stream_array = StreamArray(name='i_stream_array', dtype=dt_0)
j_stream_array = StreamArray(name='j_stream_array', dtype=dt_1)
def f_datatype(input_array):
output_array = np.zeros(len(input_array), dtype=dt_1)
output_array['time'] = input_array['time']
output_array['value'] = np.sum(input_array['value'], axis=1)
return output_array
e_np_agent = map_list(func=f_datatype,
in_stream=i_stream_array,
out_stream=j_stream_array,
name='e_np_agent')
c_array = np.array([(1, [2.0, 3.0, 4.0])], dtype=dt_0)
assert j_stream_array.stop == 0
i_stream_array.extend(c_array)
scheduler.step()
assert np.array_equal(j_stream_array.recent[:j_stream_array.stop],
f_datatype(c_array))
d_array = np.array([(10, [6.0, 7.0, 8.0]), (20, [10.0, 11.0, 12.0])],
dtype=dt_0)
i_stream_array.extend(d_array)
scheduler.step()
assert np.array_equal(j_stream_array.recent[:j_stream_array.stop],
f_datatype(np.hstack((c_array, d_array))))
# Test list map with a datatype and positive integer dimension.
k_stream_array = StreamArray(name='k_stream_array',
dtype=dt_0,
dimension=2)
l_stream_array = StreamArray(name='l_stream_array', dtype=dt_1)
def f_datatype_int_dimension(input_array):
m = len(input_array)
output_array = np.zeros(m, dtype=dt_1)
for i in range(m):
output_array[i]['time'] = np.max(input_array[i]['time'])
output_array[i]['value'] = np.sum(input_array[i]['value'])
return output_array
f_np_agent = map_list(func=f_datatype_int_dimension,
in_stream=k_stream_array,
out_stream=l_stream_array,
name='f_np_agent')
e_array = np.array([[(1, [2.0, 3.0, 4.0]), (2, [5.0, 6.0, 7.0])]],
dtype=dt_0)
assert l_stream_array.stop == 0
k_stream_array.extend(e_array)
scheduler.step()
assert np.array_equal(l_stream_array.recent[:l_stream_array.stop],
f_datatype_int_dimension(e_array))
f_array = np.array([[(3, [8.0, 9.0, 10.0]), (4, [11.0, 12.0, 13.0])],
[(5, [-1.0, 0.0, 1.0]), (6, [-2.0, 2.0, -2.0])]],
dtype=dt_0)
k_stream_array.extend(f_array)
scheduler.step()
assert np.array_equal(
l_stream_array.recent[:l_stream_array.stop],
f_datatype_int_dimension(np.vstack((e_array, f_array))))
# Test list map with a datatype and a dimension which is a tuple
m_stream_array = StreamArray(name='m_stream_array',
dtype=dt_0,
dimension=(2, 2))
n_stream_array = StreamArray(name='n_stream_array', dtype=dt_1)
g_np_agent = map_list(func=f_datatype_int_dimension,
in_stream=m_stream_array,
out_stream=n_stream_array,
name='g_np_agent')
assert n_stream_array.stop == 0
g_array = np.array(
[
# zeroth 2x2 array
[[(1, [2.0, 3.0, 4.0]), (2, [5.0, 6.0, 7.0])],
[(3, [8.0, 9.0, 10.0]), (4, [11.0, 12.0, 13.0])]],
# first 2x2 array
[[(5, [12.0, 13.0, 14.0]), (6, [15.0, 16.0, 17.0])],
[(7, [18.0, 19.0, 20.0]), (8, [21.0, 22.0, 23.0])]]
],
dtype=dt_0)
m_stream_array.extend(g_array)
scheduler.step()
assert np.array_equal(n_stream_array.recent[:n_stream_array.stop],
f_datatype_int_dimension(g_array))
h_array = np.array([[[(9, [0.0, 1.0, -1.0]), (10, [2.0, 2.0, -4.0])],
[(11, [80.0, -71.0, -9.0]), (15, [0.0, 0.0, 0.0])]]],
dtype=dt_0)
m_stream_array.extend(h_array)
scheduler.step()
assert np.array_equal(
n_stream_array.recent[:n_stream_array.stop],
f_datatype_int_dimension(np.vstack((g_array, h_array))))
# Test list merge with StreamArray and no dimension and no data type
a_in_0 = StreamArray(name='a_in_0')
a_in_1 = StreamArray(name='a_in_1')
a_out = StreamArray(name='a_out')
def a_merge(list_of_lists):
array_0, array_1 = list_of_lists
return array_0 + array_1
a_s_agent = merge_list(func=a_merge,
in_streams=[a_in_0, a_in_1],
out_stream=a_out,
name='a_s_agent')
assert a_out.stop == 0
#a_in_0.extend(np.array([1.0, 2.0, 3.0]))
a_in_0.extend(np.array([1.0, 2.0, 3.0]))
scheduler.step()
assert a_out.stop == 0
a_in_0.extend(np.array([4.0, 5.0, 6.0]))
scheduler.step()
assert a_out.stop == 0
a_in_1.extend(np.array([10.0, 20.0]))
scheduler.step()
assert np.array_equal(a_out.recent[:a_out.stop], np.array([11.0, 22.0]))
a_in_1.extend(np.array([30.0, 40.0]))
scheduler.step()
assert np.array_equal(a_out.recent[:a_out.stop],
np.array([11.0, 22.0, 33.0, 44.0]))
# Test list merge with StreamArray and no dimension and data type
a_in_dt_0 = StreamArray(name='a_in_dt_0', dtype=dt_0)
a_in_dt_1 = StreamArray(name='a_in_dt_1', dtype=dt_0)
a_out_dt = StreamArray(name='out', dtype=dt_0)
def a_merge_dtype(list_of_arrays):
input_array_0, input_array_1 = list_of_arrays
output_array = np.zeros(len(input_array_0), dtype=dt_0)
output_array['time'] = \
np.max((input_array_0['time'], input_array_1['time']), axis=0)
output_array['value'] = input_array_0['value'] + input_array_1['value']
return output_array
a_s_dt_agent = merge_list(func=a_merge_dtype,
in_streams=[a_in_dt_0, a_in_dt_1],
out_stream=a_out_dt,
name='a_s_dt_agent')
a_in_dt_0.extend(np.array([(1, [1.0, 2.0, 3.0])], dtype=dt_0))
scheduler.step()
assert a_out_dt.stop == 0
a_in_dt_1.extend(np.array([(2, [10.0, 20.0, 30.0])], dtype=dt_0))
scheduler.step()
assert np.array_equal(a_out_dt.recent[:a_out_dt.stop],
np.array([(2, [11.0, 22.0, 33.0])], dtype=dt_0))
a_in_dt_0.extend(
np.array([(5, [21.0, 23.0, 32.0]), (9, [27.0, 29.0, 31.0])],
dtype=dt_0))
scheduler.step()
assert np.array_equal(a_out_dt.recent[:a_out_dt.stop],
np.array([(2, [11.0, 22.0, 33.0])], dtype=dt_0))
a_in_dt_1.extend(
np.array([(6, [19.0, 17.0, 8.0]), (8, [13.0, 11.0, 9.0]),
(10, [3.0, 1.0, 5.0])],
dtype=dt_0))
scheduler.step()
assert np.array_equal(
a_out_dt.recent[:a_out_dt.stop],
np.array([(2, [11.0, 22.0, 33.0]), (6, [40.0, 40.0, 40.0]),
(9, [40.0, 40.0, 40.0])],
dtype=dt_0))
# Test list split with StreamArray and positive integer dimension and no data type
dim = 2
b_in = StreamArray(name='b_in', dimension=dim)
b_out_0 = StreamArray(name='b_out_0', dimension=dim)
b_out_1 = StreamArray(name='b_out_1')
def b_split(array_of_arrays):
length = len(array_of_arrays)
output_array_0 = np.zeros((
length,
dim,
))
output_array_1 = np.zeros(length)
for i in range(length):
input_array = array_of_arrays[i]
output_array_0[i] = np.array(
[[np.max(input_array),
np.min(input_array)]])
output_array_1[i] = np.array([np.sum(input_array)])
return output_array_0, output_array_1
b_split_agent = split_list(func=b_split,
in_stream=b_in,
out_streams=[b_out_0, b_out_1],
name='b_split_agent')
b_array_0 = np.array([[1.0, 9.0]])
b_in.extend(b_array_0)
scheduler.step()
assert np.array_equal(b_out_0.recent[:b_out_0.stop], np.array([[9.0,
1.0]]))
assert np.array_equal(b_out_1.recent[:b_out_1.stop], np.array([10.0]))
b_array_1 = np.array([[98.0, 2.0]])
b_in.extend(b_array_1)
scheduler.step()
assert np.array_equal(b_out_0.recent[:b_out_0.stop],
np.array([[9.0, 1.0], [98.0, 2.0]]))
assert np.array_equal(b_out_1.recent[:b_out_1.stop],
np.array([10.0, 100.0]))
b_array_3 = np.array([[10.0, 20.0], [3.0, 37.0], [55.0, 5.0]])
b_in.extend(b_array_3)
scheduler.step()
assert np.array_equal(
b_out_0.recent[:b_out_0.stop],
np.array([[9.0, 1.0], [98.0, 2.0], [20.0, 10.0], [37.0, 3.0],
[55.0, 5.0]]))
assert np.array_equal(b_out_1.recent[:b_out_1.stop],
np.array([10.0, 100.0, 30.0, 40.0, 60.0]))
# Test list many with StreamArray and no dimension and no data type
c_in_0 = StreamArray(name='c_in_0')
c_in_1 = StreamArray(name='c_in_1')
c_out_0 = StreamArray(name='c_out_0')
c_out_1 = StreamArray(name='c_out_1')
def c_many(list_of_arrays):
length = len(list_of_arrays)
input_array_0, input_array_1 = list_of_arrays
output_array_0 = np.zeros(length)
output_array_1 = np.zeros(length)
output_array_0 = input_array_0 + input_array_1
output_array_1 = input_array_0 - input_array_1
return [output_array_0, output_array_1]
c_multi_agent = multi_list(func=c_many,
in_streams=[c_in_0, c_in_1],
out_streams=[c_out_0, c_out_1],
name='c_multi_agent')
c_array_0_0 = np.arange(3.0) * 3
c_array_1_0 = np.arange(3.0)
c_in_0.extend(c_array_0_0)
scheduler.step()
c_in_1.extend(c_array_1_0)
scheduler.step()
assert np.array_equal(c_out_0.recent[:c_out_0.stop],
np.array([0.0, 4.0, 8.0]))
assert np.array_equal(c_out_1.recent[:c_out_1.stop],
np.array([0.0, 2.0, 4.0]))
c_array_0_1 = np.array([100.0])
c_array_1_1 = np.array([4.0, 5.0, 6.0])
c_in_0.extend(c_array_0_1)
c_in_1.extend(c_array_1_1)
scheduler.step()
assert np.array_equal(c_out_0.recent[:c_out_0.stop],
np.array([0.0, 4.0, 8.0, 104.0]))
assert np.array_equal(c_out_1.recent[:c_out_1.stop],
np.array([0.0, 2.0, 4.0, 96.0]))
## # Test list many with StreamArray and no dimension and no data type
## z_in_0 = StreamArray(name='z_in_0')
## z_in_1 = StreamArray(name='z_in_1')
## z_out_0 = StreamArray(name='z_out_0')
## z_out_1 = StreamArray(name='z_out_1')
## def execute_list_of_np_func(v, list_of_np_func):
## length = len(list_of_arrays)
## input_array_0, input_array_1 = list_of_arrays
## output_array_0 = np.zeros(length)
## output_array_1 = np.zeros(length)
## output_array_0 = input_array_0 + input_array_1
## output_array_1 = input_array_0 - input_array_1
## return [output_array_0, output_array_1]
# Test list many with StreamArray and positive integer dimension and no data type
dim = 2
d_in_0 = StreamArray(name='d_in_0', dimension=dim)
d_in_1 = StreamArray(name='d_in_1', dimension=dim)
d_out_0 = StreamArray(name='d_out_0', dimension=dim)
d_out_1 = StreamArray(name='d_out_1')
def d_many(list_of_arrays):
length = len(list_of_arrays)
input_array_0, input_array_1 = list_of_arrays
output_array_0 = input_array_0 + input_array_1
output_array_1 = np.array([np.sum(input_array_0 + input_array_1)])
return output_array_0, output_array_1
d_multi_agent = multi_list(func=d_many,
in_streams=[d_in_0, d_in_1],
out_streams=[d_out_0, d_out_1],
name='d_multi_agent')
d_array_0_0 = np.array([[1.0, 2.0]])
d_array_1_0 = np.array([[0.0, 10.0]])
d_in_0.extend(d_array_0_0)
scheduler.step()
d_in_1.extend(d_array_1_0)
scheduler.step()
assert np.array_equal(d_out_0.recent[:d_out_0.stop], np.array([[1.0,
12.0]]))
assert np.array_equal(d_out_1.recent[:d_out_1.stop], np.array([13.0]))
d_array_0_1 = np.array([[4.0, 8.0]])
d_array_1_1 = np.array([[2.0, 4.0]])
d_in_0.extend(d_array_0_1)
d_in_1.extend(d_array_1_1)
scheduler.step()
assert np.array_equal(d_out_0.recent[:d_out_0.stop],
np.array([[1.0, 12.0], [6.0, 12.0]]))
assert np.array_equal(d_out_1.recent[:d_out_1.stop], np.array([13.0,
18.0]))
d_array_0_2 = np.array([[20.0, 30.0], [40.0, 50.0]])
d_array_1_2 = np.array([[-10.0, -20.0]])
d_in_0.extend(d_array_0_2)
d_in_1.extend(d_array_1_2)
scheduler.step()
assert np.array_equal(d_out_0.recent[:d_out_0.stop],
np.array([[1.0, 12.0], [6.0, 12.0], [10.0, 10.0]]))
assert np.array_equal(d_out_1.recent[:d_out_1.stop],
np.array([13.0, 18.0, 20.0]))
# Test list many with StreamArray and tuple dimension and no data type
dim = (2, 2)
e_in_0 = StreamArray(name='e_in_0', dimension=dim)
e_in_1 = StreamArray(name='e_in_1', dimension=dim)
e_out_0 = StreamArray(name='e_out_0', dimension=dim)
e_out_1 = StreamArray(name='e_out_1')
def e_many(list_of_arrays):
input_array_0, input_array_1 = list_of_arrays
output_array_0 = input_array_0 + input_array_1
output_array_1 = \
np.array([np.sum(input_array_0[i]+ input_array_1[i])
for i in range(len(input_array_0))])
return output_array_0, output_array_1
e_multi_agent = multi_list(func=e_many,
in_streams=[e_in_0, e_in_1],
out_streams=[e_out_0, e_out_1],
name='e_multi_agent')
e_array_0_0 = np.array([[[10.0, 20.0], [30.0, 40.0]]])
e_in_0.extend(e_array_0_0)
e_array_1_0 = np.array([[[1.0, 2.0], [3.0, 4.0]]])
e_in_1.extend(e_array_1_0)
scheduler.step()
assert np.array_equal(e_out_0.recent[:e_out_0.stop],
np.array([[[11.0, 22.0], [33.0, 44.0]]]))
assert np.array_equal(e_out_1.recent[:e_out_1.stop], np.array([110.0]))
e_array_0_1 = np.array([[[11.0, 13.0], [17.0, 19.0]],
[[2.0, 4.0], [6.0, 8.0]]])
e_in_0.extend(e_array_0_1)
scheduler.step()
assert np.array_equal(e_out_0.recent[:e_out_0.stop],
np.array([[[11.0, 22.0], [33.0, 44.0]]]))
assert np.array_equal(e_out_1.recent[:e_out_1.stop], np.array([110.0]))
e_array_1_1 = np.array([[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0,
8.0]]])
e_in_1.extend(e_array_1_1)
scheduler.step()
assert np.array_equal(
e_out_0.recent[:e_out_0.stop],
np.array([[[11.0, 22.0], [33.0, 44.0]], [[12.0, 15.0], [20.0, 23.0]],
[[7.0, 10.0], [13.0, 16.0]]]))
assert np.array_equal(e_out_1.recent[:e_out_1.stop],
np.array([110.0, 70.0, 46.0]))
e_array_1_2 = np.array([[[11.0, 12.0], [13.0, 14.0]],
[[15.0, 16.0], [17.0, 18.0]]])
e_in_1.extend(e_array_1_2)
scheduler.step()
e_array_0_2 = np.array([[[-10.0, -11.0], [12.0, 16.0]],
[[-14.0, -15.0], [-16.0, -17.0]]])
e_in_0.extend(e_array_0_2)
scheduler.step()
assert np.array_equal(
e_out_0.recent[:e_out_0.stop],
np.array([[[11.0, 22.0], [33.0, 44.0]], [[12.0, 15.0], [20.0, 23.0]],
[[7.0, 10.0], [13.0, 16.0]], [[1.0, 1.0], [25.0, 30.0]],
[[1.0, 1.0], [1.0, 1.0]]]))
assert np.array_equal(e_out_1.recent[:e_out_1.stop],
np.array([110.0, 70.0, 46.0, 57.0, 4.0]))
#------------------------------------------------------------------
#------------------------------------------------------------------
# Test args and kwargs
#------------------------------------------------------------------
#------------------------------------------------------------------
# Test map
def map_args(lst, multiplicand):
return [multiplicand * element for element in lst]
in_stream_map_args_stream = Stream('in_stream_map_args_stream')
out_stream_map_args_stream = Stream('out_stream_map_args_stream')
out_stream_map_kwargs_stream = Stream('out_stream_map_kwargs_stream')
map_args_agent = map_list(map_args, in_stream_map_args_stream,
out_stream_map_args_stream, None, None,
'map_args_agent', 2)
map_kwargs_agent = map_list(func=map_args,
in_stream=in_stream_map_args_stream,
out_stream=out_stream_map_kwargs_stream,
name='map_args_agent',
multiplicand=2)
scheduler.step()
assert out_stream_map_args_stream.recent[:out_stream_map_args_stream.stop] == \
[]
assert out_stream_map_kwargs_stream.recent[:out_stream_map_kwargs_stream.stop] == \
[]
in_stream_map_args_stream.extend(range(5))
scheduler.step()
assert out_stream_map_args_stream.recent[:out_stream_map_args_stream.stop] == \
[0, 2, 4, 6, 8]
assert out_stream_map_kwargs_stream.recent[:out_stream_map_kwargs_stream.stop] == \
[0, 2, 4, 6, 8]
in_stream_map_args_stream.append(5)
scheduler.step()
assert out_stream_map_args_stream.recent[:out_stream_map_args_stream.stop] == \
[0, 2, 4, 6, 8, 10]
assert out_stream_map_kwargs_stream.recent[:out_stream_map_kwargs_stream.stop] == \
[0, 2, 4, 6, 8, 10]
# Test list map on StreamArray (dimension is 0).
a_stream_array_args = StreamArray(name='a_stream_array_args')
b_stream_array_args = StreamArray(name='b_stream_array_args')
c_stream_array_args_kwargs = StreamArray(name='c_stream_array_args_kwargs')
def f_np_args(input_array_args, addend):
return input_array_args + addend
def f_np_args_kwargs(input_array_args_kwargs, multiplicand, addend):
return input_array_args_kwargs * multiplicand + addend
a_np_agent_args = map_list(f_np_args, a_stream_array_args,
b_stream_array_args, None, None,
'a_np_agent_args', 1)
a_np_agent_args_kwargs = map_list(f_np_args_kwargs,
a_stream_array_args,
c_stream_array_args_kwargs,
None,
None,
'a_np_agent_args_kwargs',
2,
addend=10)
scheduler.step()
assert np.array_equal(
b_stream_array_args.recent[:b_stream_array_args.stop], np.array([]))
assert np.array_equal(
c_stream_array_args_kwargs.recent[:c_stream_array_args_kwargs.stop],
np.array([]))
a_stream_array_args.extend(np.arange(5.0))
scheduler.step()
assert np.array_equal(
b_stream_array_args.recent[:b_stream_array_args.stop],
np.arange(5.0) + 1)
assert np.array_equal(
c_stream_array_args_kwargs.recent[:c_stream_array_args_kwargs.stop],
np.arange(5.0) * 2 + 10)
a_stream_array_args.extend(np.arange(5.0, 10.0, 1.0))
scheduler.step()
assert np.array_equal(
b_stream_array_args.recent[:b_stream_array_args.stop],
np.arange(10.0) + 1)
assert np.array_equal(
c_stream_array_args_kwargs.recent[:c_stream_array_args_kwargs.stop],
np.arange(10.0) * 2 + 10)
print 'TEST OF OP (LISTS) IS SUCCESSFUL'
def test_kmeans_streams():
s = Stream()
t = Stream()
km = kmeans_stream(n_clusters=2)
@map_e
def g(v):
return km.process_element(v)
g(in_stream=s, out_stream=t)
s.append(('add', [1, 2]))
s.append(('add', [1, 4]))
s.append(('add', [1, 0]))
s.append(('add', [10, 4]))
s.append(('add', [10, 0]))
s.append(('add', [10, 2]))
s.append('cluster')
s.append('show')
## s.extend([('add', [1, 2]), ('add', [1, 4]), ('add', [1, 0]),
## ('add', [10, 4]), ('add', [10, 0]), ('add', [10, 2])])
run()
print(recent_values(t))
def stop_agent_when_enough_elements(N):
"""
Shows how shared variables can be used to stop agents.
One agent generates a sequence until stopped by another agent.
Parameters
----------
N: int (positive)
"""
#----------------------------------------------------------------
# STEP 1. DEFINE FUNCTIONS TO BE ENCAPSULATED
def generate_numbers(v, state, stop):
"""
This function generates the sequence 0, 1, 2, ... starting
with the specified initial state. The function stops execution
when stop becomes True.
Parameters
----------
v: The element in the sequence, 0,1,2,.. read from the input
stream.
state: The last element of the sequence
stop: array of length 1. This is a shared variable of the agent.
"""
if not stop[0]:
return state, state + 1
else:
return _no_value, state
def call_halt(v, N, stop):
if v > N:
stop[0] = True
#----------------------------------------------------------------
# STEP 2. CREATE STREAMS AND SHARED VARIABLES
# stop is a variable shared by both agents that are created
# below. It is initially False and set to True and then remains
# True.
stop = [False]
numbers = Stream('numbers')
#----------------------------------------------------------------
# STEP 3. CREATE AGENTS
# Create an agent that reads and writes the same stream: numbers.
# The agent executes its action when a new value appears on
# numbers. The action puts the next value on numbers if stop is
# False. The action has no effect (it is a skip operation) if stop
# is True.
map_element(func=generate_numbers,
in_stream=numbers,
out_stream=numbers,
state=1,
stop=stop)
# Create an agent that sets stop to True after it reads more than
# N values.
N = 3
sink(func=call_halt, in_stream=numbers, N=N, stop=stop)
#----------------------------------------------------------------
#STEP 4. START COMPUTATION
# Get the scheduler and execute a step.
scheduler = Stream.scheduler
# Start the computation by putting a value into the numbers stream.
numbers.append(0)
scheduler.step()
# The stream numbers will be 0, 1, ... up to N-1 and possibly may
# contain additional values. For example, if N = 3 then numbers
# could be 0, 1, 2 or 0, 1, 2, 3, 4, 5.
return numbers
assert list(range(N)) == recent_values(numbers)[:N]
def test_split_agents():
import numpy as np
scheduler = Stream.scheduler
s = Stream('s')
u = Stream('u')
v = Stream('v')
w = Stream('w')
y = Stream('y')
z = Stream('z')
# Test split
# func operates on a single element of the single input stream and
# return a list of elements, one for each output stream.
def h(element):
return [element+1, element*2]
def h_args(element, addend, multiplier):
return [element+addend, element*multiplier]
in_stream_split = Stream('in_stream_split')
r = Stream('r')
t = Stream('t')
e = split_element(func=h, in_stream=in_stream_split,
out_streams=[r, t], name='e')
r_split, t_split = split_element_f(function=h, in_stream=in_stream_split,
num_out_streams=2, )
r_args, t_args = split_element_f(
h_args, in_stream_split, 2, addend=1, multiplier=2)
scheduler.step()
assert recent_values(r) == []
assert recent_values(t) == []
assert recent_values(r_split) == recent_values(r)
assert recent_values(t_split) == recent_values(t)
assert recent_values(r_args) == recent_values(r)
assert recent_values(t_args) == recent_values(t)
in_stream_split.extend(range(5))
scheduler.step()
assert recent_values(r) == [1, 2, 3, 4, 5]
assert recent_values(t) == [0, 2, 4, 6, 8]
assert recent_values(r_split) == recent_values(r)
assert recent_values(t_split) == recent_values(t)
assert recent_values(r_args) == recent_values(r)
assert recent_values(t_args) == recent_values(t)
in_stream_split.append(10)
scheduler.step()
assert recent_values(r) == [1, 2, 3, 4, 5, 11]
assert recent_values(t) == [0, 2, 4, 6, 8, 20]
in_stream_split.extend([20, 100])
scheduler.step()
assert recent_values(r) == [1, 2, 3, 4, 5, 11, 21, 101]
assert recent_values(t) == [0, 2, 4, 6, 8, 20, 40, 200]
assert recent_values(r_split) == recent_values(r)
assert recent_values(t_split) == recent_values(t)
assert recent_values(r_args) == recent_values(r)
assert recent_values(t_args) == recent_values(t)
# Test split with kwargs
def f_list(element, list_of_functions):
return [f(element) for f in list_of_functions]
def f_0(element):
return element*2
def f_1(element):
return element+10
x = Stream('x')
rr = Stream('rr')
tt = Stream('tt')
ee = split_element(func=f_list, in_stream=x, out_streams=[rr, tt], name='ee',
list_of_functions=[f_0, f_1])
x.extend(range(5))
scheduler.step()
assert recent_values(rr) == [0, 2, 4, 6, 8]
assert recent_values(tt) == [10, 11, 12, 13, 14]
# ------------------------------------
# Test split with state
# func operates on an element of the single input stream and state.
# func returns a list with one element for each output stream.
def h_state(element, state):
return ([element+state, element*state], state+1)
r_state = Stream(name='r_state')
t_state = Stream(name='t_state')
in_stream_split_state = Stream('in_stream_split_state')
e_state = split_element(
func=h_state, in_stream=in_stream_split_state,
out_streams=[r_state, t_state], name='e', state=0)
scheduler.step()
assert recent_values(r_state) == []
assert recent_values(t_state) == []
in_stream_split_state.extend(range(5))
scheduler.step()
assert recent_values(r_state) == [0, 2, 4, 6, 8]
assert recent_values(t_state) == [0, 1, 4, 9, 16]
in_stream_split_state.append(20)
scheduler.step()
assert recent_values(r_state) == [0, 2, 4, 6, 8, 25]
assert recent_values(t_state) == [0, 1, 4, 9, 16, 100]
in_stream_split_state.extend([44, 93])
scheduler.step()
assert recent_values(r_state) == [0, 2, 4, 6, 8, 25, 50, 100]
assert recent_values(t_state) == [0, 1, 4, 9, 16, 100, 264, 651]
# ------------------------------------
# Test split with state and args
def hh_state(element, state, increment):
return ([element+state, element*state], state+increment)
rr_state = Stream(name='rr_state')
tt_state = Stream(name='tt_state')
in_stream_split_state_funcargs = Stream('in_stream_split_state_funcargs')
ee_state_agent = split_element(
func=hh_state,
in_stream=in_stream_split_state_funcargs,
out_streams=[rr_state, tt_state],
name='ee_state_agent', state=0, increment=10)
scheduler.step()
assert recent_values(rr_state) == []
assert recent_values(tt_state) == []
in_stream_split_state_funcargs.extend(range(5))
scheduler.step()
assert recent_values(rr_state) == [0, 11, 22, 33, 44]
assert recent_values(tt_state) == [0, 10, 40, 90, 160]
#------------------------------------------------------------------------------------------------
# UNZIP AGENT TESTS
#------------------------------------------------------------------------------------------------
s_unzip = Stream('s_unzip')
u_unzip = Stream('u_unzip')
x_unzip = Stream('x_unzip')
# ------------------------------------
# Test unzip
unzip(in_stream=s_unzip, out_streams=[x_unzip, u_unzip])
d_unzip_fn = unzip_f(s_unzip, 2)
s_unzip.extend([(1,10), (2,15), (3,18)])
scheduler.step()
assert recent_values(x_unzip) == [1, 2, 3]
assert recent_values(u_unzip) == [10, 15, 18]
assert recent_values(d_unzip_fn[0]) == x_unzip.recent[:3]
assert recent_values(d_unzip_fn[1]) == u_unzip.recent[:3]
s_unzip.extend([(37,96)])
scheduler.step()
assert recent_values(x_unzip) == [1, 2, 3, 37]
assert recent_values(u_unzip) == [10, 15, 18, 96]
assert recent_values(d_unzip_fn[0]) == x_unzip.recent[:4]
assert recent_values(d_unzip_fn[1]) == u_unzip.recent[:4]
#------------------------------------------------------------------------------------------------
# SEPARATE AGENT TESTS
#------------------------------------------------------------------------------------------------
s_separate = Stream('s separate')
u_separate = Stream('u separate')
x_separate = Stream('x separate')
d_separate = separate(
in_stream=s_separate, out_streams=[x_separate,u_separate],
name='d separate')
x_sep_func, u_sep_func = separate_f(s_separate, 2)
s_separate.extend([(0,10), (1,15), (0,20)])
scheduler.step()
assert recent_values(x_separate) == [10, 20]
assert recent_values(u_separate) == [15]
assert x_sep_func.recent == x_separate.recent
assert u_sep_func.recent == u_separate.recent
s_separate.extend([(1,96)])
scheduler.step()
assert recent_values(x_separate) == [10, 20]
assert recent_values(u_separate) == [15, 96]
assert recent_values(x_sep_func) == recent_values(x_separate)
assert recent_values(u_sep_func) == recent_values(u_separate)
#------------------------------------------------------------------------------------------------
# TIMED_UNZIP TESTS
#------------------------------------------------------------------------------------------------
# timed_unzip tests
t_unzip = Stream()
a_unzip = Stream('a_unzip')
b_unzip = Stream('b_unzip')
timed_unzip(t_unzip, [a_unzip, b_unzip])
t_unzip_0, t_unzip_1 = timed_unzip_f(in_stream=t_unzip, num_out_streams=2)
t_unzip.extend(
[(1, ["A", None]), (5, ["B", "a"]), (7, [None, "b"]),
(9, ["C", "c"]), (10, [None, "d"])])
scheduler.step()
assert recent_values(t_unzip_0) == [(1, 'A'), (5, 'B'), (9, 'C')]
assert recent_values(t_unzip_1) == [(5, 'a'), (7, 'b'), (9, 'c'), (10, 'd')]
assert recent_values(a_unzip) == recent_values(t_unzip_0)
assert recent_values(b_unzip) == recent_values(t_unzip_1)
#------------------------------------------------------------------------------------------------
# TEST SPLIT WITH STREAM_ARRAY
#------------------------------------------------------------------------------------------------
# Test split_element with StreamArray
x = StreamArray('x')
y = StreamArray('y')
z = StreamArray('z')
def h_args(element, addend, multiplier):
return [element+addend, element*multiplier]
this_agent = split_element(func=h_args, in_stream=x, out_streams=[y,z],
addend=1.0 , multiplier=2.0, name='this_agent')
add_to_x = np.linspace(0.0, 4.0, 5)
x.extend(add_to_x)
scheduler.step()
assert np.array_equal(recent_values(y), add_to_x+1.0)
assert np.array_equal(recent_values(z), add_to_x*2.0)
# Test separate with StreamArray
x = StreamArray('x', dimension=2)
y = StreamArray('y')
z = StreamArray('z')
separate(x, [y,z])
x.append(np.array([1.0, 10.0]))
scheduler.step()
assert np.array_equal(recent_values(z), np.array([10.0]))
assert np.array_equal(recent_values(y), np.array([]))
x.extend(np.array([[0.0, 2.0], [1.0, 20.0], [0.0, 4.0]]))
scheduler.step()
assert np.array_equal(recent_values(z), np.array([10.0, 20.0]))
assert np.array_equal(recent_values(y), np.array([2.0, 4.0]))
# ------------------------------------------------------
# TEST split_list
# ------------------------------------------------------
x = Stream('x')
y = Stream('y')
z = Stream('z')
def f(lst):
return [v*2 for v in lst], [v*10 for v in lst]
split_list(f, x, [y, z])
x.extend(range(3))
scheduler.step()
assert recent_values(y) == [v*2 for v in recent_values(x)]
assert recent_values(z) == [v*10 for v in recent_values(x)]
x.append(100)
scheduler.step()
assert recent_values(y) == [v*2 for v in recent_values(x)]
assert recent_values(z) == [v*10 for v in recent_values(x)]
# ------------------------------------------------------
# TEST split_window
# ------------------------------------------------------
def f(window):
return max(window), min(window)
x = Stream('x')
y = Stream('y')
z = Stream('z')
split_window(
func=f, in_stream=x, out_streams=[y, z], window_size=2, step_size=2)
x.extend(range(7))
scheduler.step()
assert recent_values(y) == [1, 3, 5]
assert recent_values(z) == [0, 2, 4]
# ------------------------------------------------------
# TEST split_tuple
# ------------------------------------------------------
x = Stream('x')
y = Stream('y')
z = Stream('z')
split_tuple(in_stream=x, out_streams=[y, z])
x.append((0, 'A'))
x.extend([(1, 'B'), (2, 'C')])
scheduler.step()
print 'TEST OF SPLIT IS SUCCESSFUL'
def stream_test():
# Numpy type for testing stream array.
txyz_dtype = np.dtype([('time', 'int'), ('data', '3float')])
#--------------------------------------------
# Testing StreamArray with positive dimension
s = StreamArray(name='s', dimension=3)
# Each element of s is a numpy array with with 3 elements
# Initially s is empty. So s.stop == 0
assert s.stop == 0
# If num_in_memory is not specified in the declaration for
# s, the default value, DEFAULT_NUM_IN_MEMORY, is used.
# The length of s.recent is twice num_in_memory
assert len(s.recent) == 2 * DEFAULT_NUM_IN_MEMORY
# Append a numpy array with 3 zeros to s
s.append(np.zeros(3))
assert (s.stop == 1)
# Thus s.recent[:s.stop] is an array with 1 row and 3 columns.
assert (np.array_equal(s.recent[:s.stop], np.array([[0.0, 0.0, 0.0]])))
# Extend s by an array with 2 rows and 3 columns. The number of
# columns must equal the dimension of the stream array.
s.extend(np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]))
# s.stop is incremented to account for the addition of two elements.
assert s.stop == 3
# s.recent[:s.stop] includes all the elements added to s.
# Thus s.recent[:s.stop] is an array with 3 rows and 3 columns.
assert (np.array_equal(
s.recent[:s.stop],
np.array([[0.0, 0.0, 0.0], [1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])))
# Extend s by an array with 1 row and 3 columns. The number of
# columns must equal the dimension of the stream array.
s.extend(np.array([[7.0, 8.0, 9.0]]))
# s.stop is incremented to account for the addition of a single row.
assert s.stop == 4
# Thus s.recent[:s.stop] is an array with 4 rows and 3 columns.
assert np.array_equal(
s.recent[:s.stop],
np.array([[0.0, 0.0, 0.0], [1.0, 2.0, 3.0], [4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]]))
# Note the difference between EXTENDING s with an array consisting
# of 1 row and 3 columns, versus APPENDING a rank-1 array consisting
# of 3 elements, as in the following example.
s.append(np.array([10.0, 11.0, 12.0]))
# s.stop is incremented to account for the addition of a single row.
assert s.stop == 5
# Thus s.recent[:s.stop] is an array with 5 rows and 3 columns.
assert np.array_equal(
s.recent[:s.stop],
np.array([[0.0, 0.0, 0.0], [1.0, 2.0, 3.0], [4.0, 5.0, 6.0],
[7.0, 8.0, 9.0], [10.0, 11.0, 12.0]]))
#---------------------------------------------------------------
# Testing StreamArray with zero dimension and user-defined dtype
t = StreamArray(name='t', dimension=0, dtype=txyz_dtype)
# Each element of t is an object of dtype txyz_dtype
# t[i]['time'] is an int.
# t[i]['data'] is a 3-tuple consisting of 3 floats.
# Nothing has been appended to t, and so t.stop == 0.
assert (t.stop == 0)
# Append an object with 'time' = 1, and 'data' = [0.0, 1.0, 2.0].
t.append(np.array((1, [0.0, 1.0, 2.0]), dtype=txyz_dtype))
# Increase t.stop to account for the element that has just been
# added to t.
assert t.stop == 1
# t.recent[:t.stop] contains all elements appended to t.
assert t.recent[:t.stop] == np.array([(1, [0.0, 1.0, 2.0])],
dtype=txyz_dtype)
assert t.recent[0]['time'] == np.array(1)
assert np.array_equal(t.recent[0]['data'], np.array([0., 1., 2.]))
# Append another element to t.
t.append(np.array((2, [11.0, 12.0, 13.0]), dtype=txyz_dtype))
# Increase t.stop to account for the element that has just been
# added to t.
assert (t.stop == 2)
# t.recent[:t.stop] contains all elements appended to t.
a = np.array([(1, [0.0, 1.0, 2.0]), (2, [11.0, 12.0, 13.0])],
dtype=txyz_dtype)
assert np.array_equal(t.recent[:t.stop], a)
# Extend t by a list of 2 elements each of which consists of
# zeroes of txyz_dtype
t.extend(np.zeros(2, dtype=txyz_dtype))
# Increase t.stop to account for the element that has just been
# added to t.
assert (t.stop == 4)
# t.recent[:t.stop] contains all elements appended to t.
a = np.array([(1, [0.0, 1.0, 2.0]), (2, [11.0, 12.0, 13.0]),
(0, [0.0, 0.0, 0.0]), (0, [0.0, 0.0, 0.0])],
dtype=txyz_dtype)
assert np.array_equal(t.recent[:t.stop], a)
#---------------------------------------------------------------
# Testing simple Stream
u = Stream('u')
v = Stream('v')
# Add elements 0, 1, 2, 3 to stream u.
u.extend(list(range(4)))
# Increase u.stop to account for the element that has just been
# added to u.
assert u.stop == 4
# u.recent[:t.stop] contains all elements appended to u.
assert u.recent[:u.stop] == [0, 1, 2, 3]
# No change to v.
assert v.stop == 0
# Append element 10 to v and then append the list [40, 50]
v.append(10)
v.append([40, 50])
# Increase v.stop by 2 to account for the 2 new elements appended
# to v.
assert v.stop == 2
# v.recent[:v.stop] contains all elements appended to v.
assert v.recent[:v.stop] == [10, [40, 50]]
# Extend stream v
v.extend([60, 70, 80])
# Increase v.stop by 3 to account for the 3 new elements appended
# to v.
assert v.stop == 5
# v.recent[:v.stop] contains all elements appended to v.
assert v.recent[:v.stop] == [10, [40, 50], 60, 70, 80]
#------------------------------------------
# Test helper functions: get_contents_after_column_value()
# Also test StreamArray
y = StreamArray(name='y', dimension=0, dtype=txyz_dtype, num_in_memory=64)
# y[i]['time'] is a time (int).
# y[i]['data'] is 3-tuple usually with directional data
# for x, y, z.
# y.recent length is twice num_in_memory
assert len(y.recent) == 128
# y has no elements, so y.stop == 0
assert y.stop == 0
# Test data for StreamArray with user-defined data type.
test_data = np.zeros(128, dtype=txyz_dtype)
assert len(test_data) == 128
# Put random numbers for test_data[i]['time'] and
# test_data[i]['data'][xyx] for xyz in [0, 1, 2]
for i in range(len(test_data)):
test_data[i]['time'] = random.randint(0, 1000)
for j in range(3):
test_data[i]['data'][j] = random.randint(2000, 9999)
# ordered_test_data has time in increasing order.
ordered_test_data = np.copy(test_data)
for i in range(len(ordered_test_data)):
ordered_test_data[i]['time'] = i
y.extend(ordered_test_data[:60])
# extending y does not change length of y.recent
assert (len(y.recent) == 128)
# y.stop increases to accommodate the extension of y by 60.
assert (y.stop == 60)
# y.recent[:y.stop] now contains all the values put into y.
assert np.array_equal(y.recent[:y.stop], ordered_test_data[:60])
assert np.array_equal(
y.get_contents_after_column_value(column_number=0, value=50),
ordered_test_data[50:60])
assert np.array_equal(y.get_contents_after_time(start_time=50),
ordered_test_data[50:60])
assert (y.get_index_for_column_value(column_number=0, value=50) == 50)
yz = StreamArray(name='yz',
dimension=0,
dtype=txyz_dtype,
num_in_memory=64)
c = np.array((1, [0., 1., 2.]), dtype=txyz_dtype)
yz.append(c)
assert np.array_equal(yz.recent[:yz.stop],
np.array([(1, [0., 1., 2.])], dtype=txyz_dtype))
d = np.array([(2, [3., 4., 5.]), (3, [6., 7., 8.])], dtype=txyz_dtype)
yz.extend(d)
assert np.array_equal(
yz.recent[:yz.stop],
np.array([(1, [0., 1., 2.]), (2, [3., 4., 5.]), (3, [6., 7., 8.])],
dtype=txyz_dtype))
#------------------------------------------
# TESTING regular Stream class
x = Stream(name='x', num_in_memory=8)
# The length of x.recent is twice num_in_memory
assert (len(x.recent) == 16)
# No values have been appended to stream x; so x.stop == 0
assert (x.stop == 0)
# Test append
x.append(10)
# Appending values to x does not change len(x.recent)
assert (len(x.recent) == 16)
# x.stop increases to accomodate the value appended.
assert (x.stop == 1)
# x.recent[:x.stop] includes the latest append
assert (x.recent[:x.stop] == [10])
x.append(20)
assert (len(x.recent) == 16)
# x.stop increases to accomodate the value appended.
assert (x.stop == 2)
# x.recent[:x.stop] includes the latest append
assert (x.recent[:2] == [10, 20])
# Test extend
x.extend([30, 40])
assert (len(x.recent) == 16)
# x.stop increases to accomodate the values extended.
assert (x.stop == 4)
# x.recent[:x.stop] includes the latest extend
assert (x.recent[:x.stop] == [10, 20, 30, 40])
# Checking extension with the empty list.
x.extend([])
assert (len(x.recent) == 16)
# extending a stream with the empty list does not change
# the stream.
assert (x.stop == 4)
assert (x.recent[:4] == [10, 20, 30, 40])
# Checking extending a stream with a singleton list
x.extend([50])
assert (len(x.recent) == 16)
assert (x.stop == 5)
assert (x.recent[:5] == [10, 20, 30, 40, 50])
# Check registering a reader.
# Register a reader called 'a' for stream x starting
# to read from x[3] onwards.
x.register_reader('a', 3)
# Register a reader called 'b' for stream x starting
# to read from x[4] onwards.
x.register_reader('b', 4)
# x.start is a dict which identifies the readers of x
# and where they are starting to read from.
assert (x.start == {'a': 3, 'b': 4})
x.extend([1, 2, 3, 4, 5])
assert (len(x.recent) == 16)
assert (x.stop == 10)
assert (x.recent[:10] == [10, 20, 30, 40, 50, 1, 2, 3, 4, 5])
assert (x.start == {'a': 3, 'b': 4})
x.register_reader('a', 7)
x.register_reader('b', 7)
assert (x.start == {'a': 7, 'b': 7})
#------------------------------------------
# Test helper functions
assert (x.get_last_n(n=2) == [4, 5])
v = StreamArray(dimension=(3, 4), dtype=int)
v.append(np.array([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]))
a = np.array([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])
np.array_equal(v.recent[:v.stop],
np.array([[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]]))
v.extend(
np.array([[[12, 13, 14, 15], [16, 17, 18, 19], [20, 21, 22, 23]],
[[24, 25, 26, 27], [28, 29, 30, 31], [32, 33, 34, 35]]]))
np.array_equal(
v.recent[:v.stop],
np.array([[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]],
[[12, 13, 14, 15], [16, 17, 18, 19], [20, 21, 22, 23]],
[[24, 25, 26, 27], [28, 29, 30, 31], [32, 33, 34, 35]]]))
u = StreamArray(name='u', dimension=2, dtype=int)
a = np.array([0, 1])
u.append(a)
np.array_equal(u.recent[:u.stop], np.array([[0, 1]]))
u.extend(np.array([[2, 3], [4, 5], [6, 7]]))
np.array_equal(u.recent[:u.stop], np.array([[0, 1], [2, 3], [4, 5], [6,
7]]))
t = StreamArray('t')
t.append(np.array(1.0))
t.extend(np.array([2.0, 3.0]))
np.array_equal(t.recent[:t.stop], np.array([1.0, 2.0, 3.0]))
def test_timed_mix_agents():
scheduler = Stream.scheduler
x = Stream('x')
y = Stream('y')
z = Stream('z')
timed_mix([x, y], z)
x.append((0, 'a'))
scheduler.step()
assert recent_values(z) == [(0, (0, 'a'))]
x.append((1, 'b'))
scheduler.step()
assert recent_values(z) == [(0, (0, 'a')), (1, (0, 'b'))]
y.append((2, 'A'))
scheduler.step()
assert recent_values(z) == \
[(0, (0, 'a')), (1, (0, 'b')), (2, (1, 'A'))]
y.append((5, 'B'))
scheduler.step()
assert recent_values(z) == \
[(0, (0, 'a')), (1, (0, 'b')), (2, (1, 'A')), (5, (1, 'B'))]
x.append((3, 'c'))
scheduler.step()
assert recent_values(z) == \
[(0, (0, 'a')), (1, (0, 'b')), (2, (1, 'A')), (5, (1, 'B'))]
x.append((4, 'd'))
scheduler.step()
assert recent_values(z) == \
[(0, (0, 'a')), (1, (0, 'b')), (2, (1, 'A')), (5, (1, 'B'))]
x.append((8, 'e'))
scheduler.step()
assert recent_values(z) == \
[(0, (0, 'a')), (1, (0, 'b')), (2, (1, 'A')), (5, (1, 'B')), (8, (0, 'e'))]
def test_some_merge_agents():
import numpy as np
scheduler = Stream.scheduler
#----------------------------------------------------
# Declare streams
s = Stream('s')
t = Stream('t')
u = Stream('u')
v_stream = Stream('v')
x = Stream('x')
#----------------------------------------------------
# Define functions
def g(lst):
return sum(lst)
def g_args(lst, multiplier):
return sum(lst) * multiplier
def general_f(lst, f):
return f(lst)
def fff(lst, f, addend):
return f(lst, addend)
def hhh(lst, addend):
return sum(lst) + addend
#----------------------------------------------------
# Define agents
d = zip_map(func=sum, in_streams=[x, u], out_stream=s, name='d')
def magnitude(vector):
return math.sqrt(sum([w * w for w in vector]))
ssssss = Stream()
ddd = zip_map(func=magnitude, in_streams=[x, u], out_stream=ssssss)
zipxu = zip_stream_f([x, u])
zip_map_xu = zip_map_f(sum, [x, u])
zip_map_xu_merge = Stream('zip map xu merge')
zip_map(sum, [x, u], zip_map_xu_merge)
zip_map_g_args = zip_map_f(g_args, [x, u], multiplier=2)
dd = zip_map(func=general_f,
in_streams=[x, u],
out_stream=t,
name='dd',
f=np.mean)
zip_map_ss = zip_map_f(np.mean, [x, u])
dddd = zip_map(func=fff,
in_streams=[x, u],
out_stream=v_stream,
name='dddd',
f=hhh,
addend=10)
#----------------------------------------------------
#----------------------------------------------------
# Append values to stream
x.extend(list(range(3)))
u.extend([10, 15, 18])
scheduler.step()
assert recent_values(s) == [10, 16, 20]
assert recent_values(zip_map_g_args) == [2 * v for v in recent_values(s)]
assert recent_values(zipxu) == [(0, 10), (1, 15), (2, 18)]
assert recent_values(t) == [5, 8, 10]
assert recent_values(zip_map_ss) == [5.0, 8.0, 10.0]
assert recent_values(v_stream) == [20, 26, 30]
assert recent_values(zip_map_xu) == s.recent[:s.stop]
assert recent_values(zip_map_xu) == recent_values(zip_map_xu_merge)
#----------------------------------------------------
u.append(37)
x.extend(list(range(3, 5, 1)))
scheduler.step()
assert recent_values(s) == [10, 16, 20, 40]
assert recent_values(zip_map_g_args) == [2 * v for v in recent_values(s)]
assert recent_values(zipxu) == [(0, 10), (1, 15), (2, 18), (3, 37)]
assert recent_values(t) == [5, 8, 10, 20]
assert recent_values(v_stream) == [20, 26, 30, 50]
assert recent_values(zip_map_xu) == recent_values(zip_map_xu_merge)
assert recent_values(ssssss) == [
10.0, 15.033296378372908, 18.110770276274835, 37.12142238654117
]
#----------------------------------------------------
u.extend([96, 95])
scheduler.step()
assert recent_values(s) == [10, 16, 20, 40, 100]
assert recent_values(zipxu) == [(0, 10), (1, 15), (2, 18), (3, 37),
(4, 96)]
assert recent_values(t) == [5, 8, 10, 20, 50]
assert recent_values(v_stream) == [20, 26, 30, 50, 110]
assert recent_values(zip_map_xu) == recent_values(zip_map_xu_merge)
#----------------------------------------------------
# TEST MERGE_ASYNCH AND MIX
#----------------------------------------------------
x = Stream('x')
y = Stream('y')
z = Stream('z')
w = Stream('w')
def g_asynch(pair):
index, value = pair
if index == 0:
return value * 10
elif index == 1:
return value * 2
else:
raise Exception()
merge_asynch(func=lambda v: v, in_streams=[x, y], out_stream=z)
merge_asynch(func=g_asynch, in_streams=[x, y], out_stream=w)
mix_z = mix_f([x, y])
scheduler.step()
assert recent_values(z) == []
assert recent_values(mix_z) == []
assert recent_values(w) == []
x.append(10)
scheduler.step()
assert recent_values(z) == [(0, 10)]
assert recent_values(mix_z) == recent_values(z)
assert recent_values(w) == [100]
y.append('A')
scheduler.step()
assert recent_values(z) == [(0, 10), (1, 'A')]
assert recent_values(mix_z) == recent_values(z)
assert recent_values(w) == [100, 'AA']
y.append('B')
scheduler.step()
assert recent_values(z) == [(0, 10), (1, 'A'), (1, 'B')]
assert recent_values(mix_z) == recent_values(z)
assert recent_values(w) == [100, 'AA', 'BB']
x.append(20)
scheduler.step()
assert recent_values(z) == [(0, 10), (1, 'A'), (1, 'B'), (0, 20)]
assert recent_values(z) == recent_values(mix_z)
assert recent_values(w) == [100, 'AA', 'BB', 200]
fahrenheit = Stream('fahrenheit')
celsius = Stream('celsius')
def fahrenheit_and_celsius(pair):
index, value = pair
if index == 0:
return (value - 32.0) / 1.8
elif index == 1:
return value
else:
raise Exception()
fahrenheit_stream = Stream('fahrenheit temperatures')
celsius_stream = Stream('celsius temperatures')
centigrade_stream = Stream('centigrade temperatures')
merge_asynch(func=fahrenheit_and_celsius,
in_streams=[fahrenheit_stream, celsius_stream],
out_stream=centigrade_stream)
fahrenheit_stream.append(32)
scheduler.step()
assert recent_values(centigrade_stream) == [0.0]
fahrenheit_stream.append(50)
scheduler.step()
assert recent_values(centigrade_stream) == [0.0, 10.0]
fahrenheit_stream.append(68)
scheduler.step()
assert recent_values(centigrade_stream) == [0.0, 10.0, 20.0]
celsius_stream.append(-10.0)
scheduler.step()
assert recent_values(centigrade_stream) == [0.0, 10.0, 20.0, -10.0]
#----------------------------------------------------
# TEST BLEND
#----------------------------------------------------
x = Stream('x')
y = Stream('y')
z = Stream('z')
z_addend = Stream('z_addend')
def double(v):
return 2 * v
def double_add(v, addend):
return 2 * v + addend
blend(func=double, in_streams=[x, y], out_stream=z)
blend(func=double, in_streams=[x, y], out_stream=z_addend)
blend_z = blend_f(double, [x, y])
blend_add_z = blend_f(double_add, [x, y], addend=10)
x.append(1)
scheduler.step()
assert recent_values(z) == [2]
assert recent_values(blend_z) == recent_values(z)
assert recent_values(blend_add_z) == [v + 10 for v in recent_values(z)]
x.extend(list(range(2, 4)))
scheduler.step()
assert recent_values(z) == [2, 4, 6]
assert recent_values(blend_z) == recent_values(z)
assert recent_values(blend_add_z) == [v + 10 for v in recent_values(z)]
y.extend(list(range(100, 102)))
scheduler.step()
assert recent_values(z) == [2, 4, 6, 200, 202]
assert recent_values(blend_z) == recent_values(z)
assert recent_values(blend_add_z) == [v + 10 for v in recent_values(z)]
x.extend([10, 20])
scheduler.step()
assert recent_values(z) == [2, 4, 6, 200, 202, 20, 40]
assert recent_values(blend_z) == recent_values(z)
assert recent_values(blend_add_z) == [v + 10 for v in recent_values(z)]
#----------------------------------------------------
# TEST MANY
#----------------------------------------------------
# func operates on a list with one element for each input stream.
# func returns a list with one element for each output stream.
def f_many(lst):
return [sum(lst), sum(lst) + 1]
u_stream = Stream(name='u_stream')
v_stream = Stream(name='v_stream')
w_stream = Stream(name='w_stream')
x_stream = Stream(name='x_stream')
multi_agent = multi_element(func=f_many,
in_streams=[u_stream, v_stream],
out_streams=[w_stream, x_stream],
name='multi_agent')
ww_stream, xx_stream = multi_element_f(func=f_many,
in_streams=[u_stream, v_stream],
num_out_streams=2)
u_stream.extend(list(range(5)))
v_stream.extend(list(range(0, 40, 4)))
scheduler.step()
assert recent_values(w_stream) == [0, 5, 10, 15, 20]
assert recent_values(x_stream) == [1, 6, 11, 16, 21]
assert recent_values(ww_stream) == recent_values(w_stream)
assert recent_values(xx_stream) == recent_values(x_stream)
# ------------------------------------
# Test many with args and kwargs
# func operates on a list with one element for each input stream.
# func returns a list with one element for each output stream.
def f_multi_args_kwargs(lst, multiplicand, addend):
return sum(lst) * multiplicand, sum(lst) + addend
u_args_kwargs_stream = Stream(name='u_args_kwargs_stream')
v_args_kwargs_stream = Stream(name='v_args_kwargs_stream')
w_args_kwargs_stream = Stream(name='w_args_kwargs_stream')
x_args_kwargs_stream = Stream(name='x_args_kwargs_stream')
multi_args_kwargs_agent = multi_element(
func=f_multi_args_kwargs,
in_streams=[u_args_kwargs_stream, v_args_kwargs_stream],
out_streams=[w_args_kwargs_stream, x_args_kwargs_stream],
name='multi_args_kwargs_agent',
multiplicand=2,
addend=10)
ww_args_kwargs_stream, xx_args_kwargs_stream = multi_element_f(
func=f_multi_args_kwargs,
in_streams=[u_args_kwargs_stream, v_args_kwargs_stream],
num_out_streams=2,
multiplicand=2,
addend=10)
assert (recent_values(ww_args_kwargs_stream) == recent_values(
w_args_kwargs_stream))
assert (recent_values(xx_args_kwargs_stream) == recent_values(
x_args_kwargs_stream))
u_args_kwargs_stream.extend(list(range(5)))
v_args_kwargs_stream.extend(list(range(0, 40, 4)))
scheduler.step()
assert recent_values(w_args_kwargs_stream) == [0, 10, 20, 30, 40]
assert recent_values(x_args_kwargs_stream) == [10, 15, 20, 25, 30]
assert (recent_values(ww_args_kwargs_stream) == recent_values(
w_args_kwargs_stream))
assert (recent_values(xx_args_kwargs_stream) == recent_values(
x_args_kwargs_stream))
u_args_kwargs_stream.append(100)
v_args_kwargs_stream.extend(list(range(40, 80, 4)))
scheduler.step()
assert recent_values(w_args_kwargs_stream) == \
[0, 10, 20, 30, 40, 240]
assert recent_values(x_args_kwargs_stream) == \
[10, 15, 20, 25, 30, 130]
assert (recent_values(ww_args_kwargs_stream) == recent_values(
w_args_kwargs_stream))
assert (recent_values(xx_args_kwargs_stream) == recent_values(
x_args_kwargs_stream))
u_args_kwargs_stream.extend([200, 300])
scheduler.step()
v_args_kwargs_stream.append(100)
scheduler.step()
assert recent_values(w_args_kwargs_stream) == \
[0, 10, 20, 30, 40, 240, 448, 656]
assert recent_values(x_args_kwargs_stream) == \
[10, 15, 20, 25, 30, 130, 234, 338]
assert (recent_values(ww_args_kwargs_stream) == recent_values(
w_args_kwargs_stream))
assert (recent_values(xx_args_kwargs_stream) == recent_values(
x_args_kwargs_stream))
#----------------------------------------------------
#----------------------------------------------------
# TEST STREAM ARRAY
#----------------------------------------------------
#----------------------------------------------------
#----------------------------------------------------
# Test zip_map with StreamArray
#----------------------------------------------------
x = StreamArray('x')
y = StreamArray('y')
z = StreamArray('z')
a = StreamArray('a')
def sum_array_axis_0(a_list_of_arrays):
return np.sum(a_list_of_arrays, axis=0)
merge_list(func=sum_array_axis_0, in_streams=[x, y], out_stream=z)
def mean_array_axis_0(a_list_of_arrays):
return np.mean(a_list_of_arrays, axis=0)
zip_map_list(func=mean_array_axis_0, in_streams=[x, y], out_stream=a)
x.extend(np.linspace(0.0, 9.0, 10))
scheduler.step()
y.extend(np.linspace(0.0, 4.0, 5))
scheduler.step()
expected_array = np.sum(
[np.linspace(0.0, 4.0, 5),
np.linspace(0.0, 4.0, 5)], axis=0)
assert isinstance(z, StreamArray)
assert np.array_equal(recent_values(z), expected_array)
expected_means = np.linspace(0.0, 4.0, 5)
assert np.array_equal(recent_values(a), expected_means)
#----------------------------------------------------
# Test blend with StreamArray
#----------------------------------------------------
x = StreamArray('x')
y = StreamArray('y')
z = StreamArray('z')
a = StreamArray('a')
def double(v):
return 2 * v
def double_add(v, addend):
return 2 * v + addend
## blend(func=double, in_streams=[x, y], out_stream=z)
## blend(func=double_add, in_streams=[x, y], out_stream=a, addend=10.0)
## x.append(np.array(1.0))
## scheduler.step()
## assert np.array_equal(recent_values(z), np.array([2.0]))
## assert np.array_equal(recent_values(a), recent_values(z)+10.0)
## x.extend(np.linspace(2.0, 3.0, 2))
## scheduler.step()
## assert np.array_equal(recent_values(z), np.array([2., 4., 6.]))
## assert np.array_equal(recent_values(a), recent_values(z)+10.0)
## y.extend(np.linspace(100.0, 101.0, 2))
## scheduler.step()
## assert np.array_equal(recent_values(z), [2., 4., 6., 200., 202.])
## assert np.array_equal(recent_values(a), recent_values(z)+10.0)
## x.extend([10., 20.])
## scheduler.step()
## assert np.array_equal(recent_values(z), [2., 4., 6., 200., 202., 20., 40.])
## assert np.array_equal(recent_values(a), recent_values(z)+10.0)
#----------------------------------------------------
# Test merge_asynch with StreamArray
#----------------------------------------------------
x = StreamArray('x')
y = StreamArray('y')
dt_0 = np.dtype([('time', int), ('value', float)])
z = StreamArray('z', dimension=2)
merge_asynch(func=lambda v: v, in_streams=[x, y], out_stream=z)
scheduler.step()
assert np.array_equal(recent_values(z), np.empty(shape=(0, 2)))
x.append(np.array(10.0))
scheduler.step()
assert np.array_equal(recent_values(z), np.array([(0, 10.0)]))
y.append(np.array(1.0))
scheduler.step()
assert np.array_equal(recent_values(z), [(0, 10.), (1, 1.0)])
y.append(np.array(2.0))
scheduler.step()
assert np.array_equal(recent_values(z), [(0, 10.), (1, 1.0), (1, 2.0)])
x.append(np.array(20.0))
scheduler.step()
assert np.array_equal(recent_values(z), [(0, 10.), (1, 1.), (1, 2.),
(0, 20.)])
#----------------------------------------------------------------
# Test window merge agent with no state
r = Stream('r')
w = Stream('w')
x = Stream('x')
a = Stream('a')
def h(list_of_windows):
return sum([sum(window) for window in list_of_windows])
merge_window(func=h,
in_streams=[r, w],
out_stream=x,
window_size=3,
step_size=3)
merge_stream = merge_window_f(func=h,
in_streams=[r, w],
window_size=3,
step_size=3)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test window merge agent with state
def h_with_state(list_of_windows, state):
return (sum([sum(window)
for window in list_of_windows]) + state, state + 1)
merge_window(func=h_with_state,
in_streams=[r, w],
out_stream=a,
window_size=3,
step_size=3,
state=0)
#----------------------------------------------------------------
#----------------------------------------------------------------
r.extend(list(range(16)))
scheduler.step()
assert recent_values(r) == list(range(16))
assert recent_values(x) == []
assert recent_values(merge_stream) == recent_values(x)
assert recent_values(a) == []
w.extend([10, 12, 14, 16, 18])
scheduler.step()
assert recent_values(r) == list(range(16))
assert recent_values(w) == [10, 12, 14, 16, 18]
assert recent_values(x) == [(0 + 1 + 2) + (10 + 12 + 14)]
assert recent_values(a) == [39]
#----------------------------------------------------------------
r.extend([10, -10, 21, -20])
scheduler.step()
assert recent_values(x) == [(0 + 1 + 2) + (10 + 12 + 14)]
assert recent_values(a) == [39]
#----------------------------------------------------------------
w.append(20)
scheduler.step()
assert recent_values(x) == [(0 + 1 + 2) + (10 + 12 + 14),
(3 + 4 + 5) + (16 + 18 + 20)]
assert recent_values(a) == [39, 67]
#----------------------------------------------------------------
r.extend([-1, 1, 0])
scheduler.step()
assert recent_values(x) == [(0 + 1 + 2) + (10 + 12 + 14),
(3 + 4 + 5) + (16 + 18 + 20)]
assert recent_values(a) == [39, 67]
#----------------------------------------------------------------
# TEST MERGE_WINDOW WITH STREAM ARRAY
#----------------------------------------------------------------
x = StreamArray('x', dimension=2)
b = StreamArray('b', dimension=2)
a = StreamArray('a', dimension=2)
#----------------------------------------------------------------
# Test window merge agent with state
def h_array(list_of_windows, state):
return (sum([sum(window)
for window in list_of_windows]) + state, state + 1)
merge_window(func=h_array,
in_streams=[x, a],
out_stream=b,
window_size=2,
step_size=2,
state=0)
#----------------------------------------------------------------
x.extend(np.array([[1., 5.], [7., 11.]]))
a.extend(np.array([[0., 1.], [2., 3.]]))
scheduler.step()
np.array_equal(recent_values(b), np.empty(shape=(0, 2)))
a.extend(np.array([[0., 1.], [1., 0.]]))
scheduler.step()
np.array_equal(recent_values(b), np.empty(shape=(0, 2)))
x.extend(np.array([[14., 18.], [18., 30.], [30., 38.], [34., 42.]]))
scheduler.step()
#-------------------------------------------------------------------
# TEST MERGE_LIST
#-------------------------------------------------------------------
# Function g operates on a list of lists, one list for each input
# stream, to return a single list for the output stream.
x = Stream('x list merge')
u = Stream('u list merge')
s = Stream('s list merge')
def g(list_of_lists):
return [sum(snapshot) for snapshot in list(zip(*list_of_lists))]
d = merge_list(func=g, in_streams=[x, u], out_stream=s, name='d')
ss = merge_list_f(g, [x, u])
x.extend(list(range(4)))
u.extend(list(range(10, 20, 2)))
scheduler.step()
assert recent_values(x) == [0, 1, 2, 3]
assert recent_values(u) == [10, 12, 14, 16, 18]
assert recent_values(s) == [10, 13, 16, 19]
x = StreamArray()
y = StreamArray()
z = StreamArray(dtype='bool')
def f(two_lists):
return np.array(two_lists[0]) > np.array(two_lists[1])
merge_list(f, [x, y], z)
x.extend(np.array([3.0, 5.0, 7.0]))
y.extend(np.array([4.0, 3.0, 10.0]))
run()
def test_element_simple():
m = Stream('m')
n = Stream('n')
o = Stream('o')
q = Stream('q')
r = Stream('r')
s = Stream('s')
t = Stream('t')
u = Stream('u')
v = Stream('v')
w = Stream('w')
x = Stream('x')
y = Stream('y')
z = Stream('z')
#----------------------------------------------------------------
# Test simple map using map_element
# func operates on an element of the input stream and returns an element of
# the output stream.
def double(v):
return 2 * v
a = map_element(func=double, in_stream=x, out_stream=y, name='a')
ymap = map_element_f(func=double, in_stream=x)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test filtering
def filtering(v):
return v <= 2
# yfilter is a stream consisting of those elements in stream x with
# values greater than 2.
# The elements of stream x that satisfy the boolean, filtering(), are
# filtered out.
yfilter = filter_element_f(func=filtering, in_stream=x)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test map with state using map_element
# func operates on an element of the input stream and state and returns an
# element of the output stream and the new state.
def f(x, state):
return x + state, state + 2
b = map_element(func=f, in_stream=x, out_stream=z, state=0, name='b')
bmap = map_element_f(func=f, in_stream=x, state=0)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test map with call streams
# The agent executes a state transition when a value is added to call_streams.
c = map_element(func=f,
in_stream=x,
out_stream=v,
state=10,
call_streams=[w],
name='c')
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test _no_value
# func returns _no_value to indicate that no value
# is placed on the output stream.
def f_no_value(v):
""" Filters out odd values
"""
if v % 2:
# v is odd. So filter it out.
return _no_value
else:
# v is even. So, keep it in the output stream.
return v
no_value_stream = Stream(name='no_value_stream')
no_value_agent = map_element(func=f_no_value,
in_stream=x,
out_stream=no_value_stream,
name='no_value_agent')
no_value_map = map_element_f(func=f_no_value, in_stream=x)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test _multivalue
# func returns _multivalue(output_list) to indicate that
# the list of elements in output_list should be placed in the
# output stream.
def f_multivalue(v):
if v % 2:
return _no_value
else:
return _multivalue([v, v * 2])
multivalue_stream = Stream('multivalue_stream')
multivalue_agent = map_element(func=f_multivalue,
in_stream=x,
out_stream=multivalue_stream,
name='multivalue_agent')
multivalue_map = map_element_f(func=f_multivalue, in_stream=x)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test map_element with args
def function_with_args(x, multiplicand, addition):
return x * multiplicand + addition
## EXPLANATION FOR agent BELOW
## agent_test_args = map_element(
## func=function_with_args, in_stream = x, out_stream=r,
## state=None, call_streams=None, name='agent_test_args',
## multiplicand=2, addition=10)
agent_test_args = map_element(function_with_args, x, r, None, None,
'agent_test_args', 2, 10)
stream_test_args = map_element_f(function_with_args, x, None, 2, 10)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test map_element with kwargs
agent_test_kwargs = map_element(func=function_with_args,
in_stream=x,
out_stream=u,
state=None,
call_streams=None,
name='agent_test_kwargs',
multiplicand=2,
addition=10)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test map_element with state and kwargs
# func operates on an element of the input stream and state and returns an
# element of the output stream and the new state.
def f_map_args_kwargs(u, state, multiplicand, addend):
return u * multiplicand + addend + state, state + 2
agent_test_kwargs_and_state = map_element(
func=f_map_args_kwargs,
in_stream=x,
out_stream=s,
state=0,
name='agent_test_kwargs_and_state',
multiplicand=2,
addend=10)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test map_element with state and args
aa_map_args_agent = map_element(f_map_args_kwargs, x, t, 0, None,
'aa_map_args_agent', 2, 10)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test filter_element
def is_even_number(v):
return not v % 2
filter_element(func=is_even_number, in_stream=x, out_stream=q)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test filter_element with state
def less_than_n(v, state):
return v <= state, state + 1
x0 = Stream('x0')
q0 = Stream('q0')
# state[i] = i
# Discard elements in x0 where x0[i] <= state[i]
filter_element(func=less_than_n, in_stream=x0, out_stream=q0, state=0)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test filter_element_stream
# p is a stream consisting of odd-numbered elements of x
# Even-numbered elements are filtered out.
p = filter_element_f(is_even_number, x)
#----------------------------------------------------------------
#----------------------------------------------------------------
# Test cycles in the module connection graph
filter_element(func=lambda v: v >= 5, in_stream=o, out_stream=n)
map_element(func=lambda v: v + 2, in_stream=n, out_stream=o)
#----------------------------------------------------------------
#----------------------------------------------------------------
# PUT VALUES INTO STREAMS
#----------------------------------------------------------------
# FIRST STEP
x.extend(range(3))
x0.extend([0, 1, 3, 3, 6, 8])
n.append(0)
scheduler = Stream.scheduler
scheduler.step()
assert recent_values(x) == [0, 1, 2]
assert recent_values(y) == [0, 2, 4]
assert recent_values(q0) == [3, 6, 8]
assert recent_values(ymap) == recent_values(y)
assert recent_values(yfilter) == []
assert recent_values(z) == [0, 3, 6]
assert recent_values(bmap) == recent_values(z)
assert recent_values(v) == []
assert recent_values(no_value_stream) == [0, 2]
assert recent_values(no_value_map) == recent_values(no_value_stream)
assert recent_values(multivalue_stream) == [0, 0, 2, 4]
assert recent_values(multivalue_map) == recent_values(multivalue_stream)
assert recent_values(r) == [10, 12, 14]
assert recent_values(stream_test_args) == recent_values(r)
assert recent_values(u) == recent_values(r)
assert recent_values(s) == [10, 14, 18]
assert recent_values(s) == recent_values(t)
assert recent_values(q) == [1]
assert recent_values(q) == recent_values(p)
assert recent_values(n) == [0, 2, 4]
assert recent_values(o) == [2, 4, 6]
#----------------------------------------------------------------
#----------------------------------------------------------------
x.extend(range(3, 5, 1))
scheduler.step()
assert recent_values(x) == [0, 1, 2, 3, 4]
assert recent_values(y) == [0, 2, 4, 6, 8]
assert recent_values(ymap) == recent_values(y)
assert recent_values(yfilter) == [3, 4]
assert recent_values(z) == [0, 3, 6, 9, 12]
assert recent_values(bmap) == recent_values(z)
assert recent_values(no_value_stream) == [0, 2, 4]
assert recent_values(no_value_map) == recent_values(no_value_stream)
assert recent_values(multivalue_stream) == [0, 0, 2, 4, 4, 8]
assert recent_values(multivalue_map) == recent_values(multivalue_stream)
assert recent_values(r) == [10, 12, 14, 16, 18]
assert recent_values(stream_test_args) == recent_values(r)
assert recent_values(u) == recent_values(r)
assert recent_values(s) == [10, 14, 18, 22, 26]
assert recent_values(s) == recent_values(t)
assert recent_values(q) == [1, 3]
assert recent_values(q) == recent_values(p)
#----------------------------------------------------------------
#----------------------------------------------------------------
w.append(0)
scheduler.step()
assert recent_values(x) == [0, 1, 2, 3, 4]
assert recent_values(y) == [0, 2, 4, 6, 8]
assert recent_values(ymap) == recent_values(y)
assert recent_values(yfilter) == [3, 4]
assert recent_values(z) == [0, 3, 6, 9, 12]
assert recent_values(bmap) == recent_values(z)
assert recent_values(v) == [10, 13, 16, 19, 22]
assert recent_values(no_value_stream) == [0, 2, 4]
assert recent_values(no_value_map) == recent_values(no_value_stream)
assert recent_values(multivalue_stream) == [0, 0, 2, 4, 4, 8]
assert recent_values(multivalue_map) == recent_values(multivalue_stream)
assert recent_values(r) == [10, 12, 14, 16, 18]
assert recent_values(stream_test_args) == recent_values(r)
assert recent_values(u) == recent_values(r)
assert recent_values(s) == [10, 14, 18, 22, 26]
assert recent_values(s) == recent_values(t)
assert recent_values(q) == [1, 3]
assert recent_values(q) == recent_values(p)
#----------------------------------------------------------------
#------------------------------------------------------------------------------------------------
# ELEMENT AGENT TESTS FOR STREAM ARRAY
#------------------------------------------------------------------------------------------------
import numpy as np
m = StreamArray('m')
n = StreamArray('n')
o = StreamArray('o')
map_element(func=np.sin, in_stream=m, out_stream=n)
filter_element(func=lambda v: v <= 0.5, in_stream=n, out_stream=o)
input_array = np.linspace(0.0, 2 * np.pi, 20)
m.extend(input_array)
scheduler.step()
expected_output = np.sin(input_array)
assert np.array_equal(recent_values(n), expected_output)
expected_output = expected_output[expected_output > 0.5]
assert np.array_equal(recent_values(o), expected_output)
return