def map_array_f(func, in_stream, state=None, *args, **kwargs):
out_stream = StreamArray(func.__name__ + in_stream.name)
map_list(func, in_stream, out_stream, state, None, None, *args, **kwargs)
return out_stream
def make_out_stream(in_stream):
if isinstance(in_stream, Stream):
return Stream()
if isinstance(in_stream, StreamArray):
return StreamArray(dimension=in_stream.dimension,
dtype=in_stream.dtype)
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_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(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)
#----------------------------------------------------------------
# Test window map agent with stream arrays and a NumPy function
def f(input_array):
return np.mean(input_array, axis=0)
map_window(func=f,
in_stream=x,
out_stream=y,
window_size=2,
step_size=2,
name='window map agent for arrays')
#----------------------------------------------------------------
#----------------------------------------------------------------
# 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(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 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
