class Deaerator:
st_i = Stream()
st_o = Stream()
st_o.quality = 0
def __init__(self, pressure):
self.pressure = pressure
def main():
if len(sys.argv) != 2:
eprint("Error:", "Missing source file name!", sep=" ")
exit(1)
stream = Stream(sys.argv[1])
stream.parse_file()
def main():
def max_of_std(lst, state):
a = np.array(lst)
state = max(a.std(), state)
return (state, state)
print "example_1"
print "example function from list to value: mean_and_sigma() "
window_size = 10
step_size = 10
print "window_size = ", window_size
print "step_size = ", step_size
print ""
x = Stream('x')
# x is the in_stream.
# sum() is the function on the window
z = stream_func(x, f_type='window', f=max_of_std, num_outputs=1, state=0.0,
window_size=window_size, step_size=step_size)
z.set_name('z')
x.extend([random.random() for i in range(30)])
x.print_recent()
z.print_recent()
def run_templater(inputFile, outputDir, tmpF):
templateFile = open(tmpF).read()
env = jinja2.Environment()
env.globals.update(sorted=sorted, to_snake=to_snake_case)
template = env.from_string(templateFile)
s = Stream(inputFile, 'Letter')
# Dirty counter for well-formedness
wf = 0
bf = 0
for key, item in s.stream():
templatedText = template.render(item)
f = open(outputDir+key+".xml", 'w')
f.write(templatedText)
f.close()
# A dirty checker for wellformedness
try:
ET.fromstring(templatedText)
wf += 1
except Exception as e:
print(key, " is BAD:: ", e)
bf += 1
print('GOOD: ', wf)
print('BAD: ', bf)
def __init__(self, A=545, w=5.76, v_min=1.1, v_max=2.9):
self.n = self.n + 1
self.A = A
self.w = w
self.v_min = v_min
self.v_max = v_max
self.rho = 0.94 # Reflectance of the collector
self.shading = 1 # Shading factor of the collector
self.tau = 0.95 # Transmissivity of trough receiver
self.alpha = 0.96 # Absorptivity of the absorber selective
# coating of trough collector
self.Fe = 0.97 # Soiling factor of the trough collector
self.d_i = 0.066 # Inner diameter of the absorber, m
self.d_o = 0.07 # Outer diameter of the absorber, m
self.phi = np.deg2rad(70) # Incidence angle, rad
self.f = 0 # Focal length, m
self.len = 0 # Length of the collector, m
self.tc_type = None # type of the collector
self.gamma = 0.93 # Intercept factor of the collector
self.n_in_a_row = 0
self.st_i = Stream()
self.st_i.fluid = Const.FLUID[3]
self.st_o = Stream()
self.st_o.fluid = Const.FLUID[3]
self.amb = Ambient()
self.v = 0 # Actual average oil speed in the trough collector
def main():
def copy(list_of_in_lists, state):
return ([in_list.list[in_list.start:in_list.stop] for in_list in list_of_in_lists],
state, [in_list.stop for in_list in list_of_in_lists])
input_stream_0 = Stream('input_stream_0', num_in_memory=32)
input_stream_1 = Stream('input_stream_1', num_in_memory=32 )
output_stream_0 = Stream('output_stream_0', num_in_memory=32)
output_stream_1 = Stream('output_stream_1', num_in_memory=32)
A = Agent(in_streams=[input_stream_0, input_stream_1 ],
out_streams=[output_stream_0, output_stream_1],
transition=copy,
name='A')
input_stream_0.extend(range(10))
assert(output_stream_0.stop == 10)
assert(output_stream_1.stop == 0)
assert(output_stream_0.recent[:10] == range(10))
assert(input_stream_0.start == {A:10})
assert(input_stream_1.start == {A:0})
input_stream_1.extend(range(10, 25, 1))
assert(output_stream_0.stop == 10)
assert(output_stream_1.stop == 15)
assert(output_stream_0.recent[:10] == range(10))
assert(output_stream_1.recent[:15] == range(10, 25, 1))
assert(input_stream_0.start == {A:10})
assert(input_stream_1.start == {A:15})
def getValuesFromFile(self): stream = Stream(self.filePath, self.column, sheet="ID") for k, v in stream.stream(): #print(k) if k != 'None' and v["DATE"] < self.date: yield str(k) + '.0'
def main():
def mean_of_window(stream):
def mean(lst, state):
sum_window, next_value_dropped = state
if sum_window is None:
sum_window = sum(lst)
else:
sum_window = sum_window + lst[-1] - next_value_dropped
mean = sum_window/len(lst)
next_value_dropped = lst[0]
state = (sum_window, next_value_dropped)
return (mean, state)
return stream_func(
inputs=stream,
f_type='window',
f=mean,
num_outputs=1,
state=(None, None),
window_size=2,
step_size=2)
def max_of_std(lst, state):
a = np.array(lst).std()
if a > state:
state = a
return (a, state)
else:
return (_no_value, state)
x = Stream('x')
# x is the input stream.
g = partial(stream_func, f_type='window',
f=max_of_std,
num_outputs=1, state=0.0,
window_size=10, step_size=10)
y = g(x)
z = g(y)
means = mean_of_window(x)
y.set_name('y')
z.set_name('z')
means.set_name('means')
x.extend([random.random() for i in range(30)])
x.print_recent()
y.print_recent()
z.print_recent()
means.print_recent()
def create_stream(self, position):
stream = Stream(color=randint(0, 3))
self.streams.append(stream)
self.add_widget(stream)
self.bind(on_ignore_touch=stream.on_ignore_touch)
self.bind(on_acknowledge_touch=stream.on_acknowledge_touch)
self.bind(on_mouse_state_changed=stream.on_mouse_state_changed)
stream.head_position = (position[0], position[1])
stream.active = True
stream.ignore_touch = False
def test():
x = Stream('x')
y,z = exp_smooth_max_and_std_of_windows_in_stream(x)
y.set_name('y')
z.set_name('z')
check(y, [1.6000000000000001, 4.3200000000000003])
check(z, [0.65319726474218087, 0.78383671769061702])
x.extend([1, 2, 3, 4, 5])
x.print_recent()
y.print_recent()
z.print_recent()
print
x.extend([6, 12, 13, 14, 15])
x.print_recent()
y.print_recent()
z.print_recent()
print
check_empty()
def test():
x = Stream('x')
y,z = max_min_of_windows_in_stream(x)
y.set_name('y')
z.set_name('z')
check(y, [5])
check(z, [3])
x.extend([3,5])
x.print_recent()
y.print_recent()
z.print_recent()
print
x.extend([11,15])
x.print_recent()
y.print_recent()
z.print_recent()
print
check_empty()
def main():
# Functions: list -> list
def square(lst):
return [v*v for v in lst]
def double(lst):
return [2*v for v in lst]
def even(lst):
return [v for v in lst if not v%2]
# Functions: stream -> stream.
# Each element of the output stream is f() applied to the corresponding
# element of the input stream.
stream_square = partial(stream_func, f_type='list', f=square, num_outputs=1)
stream_double = partial(stream_func, f_type='list', f=double, num_outputs=1)
stream_even = partial(stream_func, f_type='list', f=even, num_outputs=1)
# Create stream x, and give it name 'x'.
x = Stream('input')
# u is the stream returned by stream_square(x) and
# v is the stream returned by stream_double(x)
# w is the stream returned by stream_square(v) and
# so w could have been defined as:
# stream_square(stream_double(x))
# a is the stream containing only even values of x
u = stream_square(x)
v = stream_double(x)
w = stream_square(v)
a = stream_even(x)
# Give names to streams u, v, and w. This is helpful in reading output.
u.set_name('square of input')
v.set_name('double of input')
w.set_name('square of double of input')
a.set_name('even values in input')
print
print 'add [3, 5] to the tail of the input stream'
# Add values to the tail of stream x.
x.extend([3, 5])
# Print the N most recent values of streams x, u, v, w.
x.print_recent()
u.print_recent()
v.print_recent()
w.print_recent()
a.print_recent()
print
print 'add [2, 6] to the tail of the input stream'
# Add more values to the tail of stream x.
x.extend([2, 6])
# Print the N most recent values of streams x, u, v, w.
x.print_recent()
u.print_recent()
v.print_recent()
w.print_recent()
a.print_recent()
def main():
# Functions: list -> list of lists
def even_odd(list_of_integers):
evens_list = [n for n in list_of_integers if not n%2]
odds_list = [n for n in list_of_integers if n%2]
return (evens_list, odds_list)
# Functions: stream -> stream.
# The n-th element of the output stream is f() applied to the n-th
# elements of each of the input streams.
# Function mean is defined above, and functions sum and max are the
# standard Python functions.
stream_even_odd = partial(stream_func, f_type='list', f=even_odd, num_outputs=2)
# Create stream x, and give it name 'x'.
x = Stream('input_0')
# u is the stream returned by stream_sum([x,y]) and
# v is the stream returned by stream_max([x,y])
# w is the stream returned by stream_mean([x,y]).
# u[i] = sum(x[i],y[i])
# v[i] = max(x[i],y[i])
# w[i] = mean(x[i],y[i])
evens, odds = stream_even_odd(x)
# Give names to streams u, v, and w. This is helpful in reading output.
evens.set_name('even numbers in x')
odds.set_name('odd numbers in x')
print
print 'Adding [3, 5, 8] to input stream'
# Add values to the tail of stream x.
x.extend([3, 5, 8])
# Print recent values of the streams
print 'recent values of input streams'
x.print_recent()
print 'recent values of output streams'
evens.print_recent()
odds.print_recent()
print
print 'Adding [4, 6, 2, 1] to the input stream'
# Add more values to the tail of stream x.
x.extend([4, 6, 2, 1])
# Print recent values of the streams
print 'recent values of input streams'
x.print_recent()
print 'recent values of output streams'
evens.print_recent()
odds.print_recent()
class Filter:
def __init__(self, inputFilePath, outputFilePath):
self.inclusionList = []
self.exclusionList = []
self.stream = Stream(inputFilePath, 'Letter')
self.new_shelve_file = outputFilePath
def inclusionListAdd(self, filterList):
self.inclusionList += filterList()
def exclusionListAdd(self, filterList):
self.exclusionList += filterList()
def filter(self):
print(len(self.inclusionList))
with ShelveManager(self.new_shelve_file) as new_shelf:
for index, fields in self.stream.stream():
#print(str(index)+'.0', str(index)+'.0' in self.inclusionList)
if str(index) + '.0' in self.inclusionList and str(
index) + '.0' not in self.exclusionList:
print('Filtering letter, included ,', index)
new_shelf[index] = self._get_fields(fields)
else:
print('Filtering letter, removed ,', index)
@editLogger('Filtered from Completed List', 'PythonScript')
def _get_fields(self, fields):
return fields
class Filter:
def __init__(self, inputFilePath, outputFilePath):
self.inclusionList = []
self.exclusionList = []
self.stream = Stream(inputFilePath, 'Letter')
self.new_shelve_file = outputFilePath
def inclusionListAdd(self, filterList):
self.inclusionList += filterList()
def exclusionListAdd(self, filterList):
self.exclusionList += filterList()
def filter(self):
with ShelveManager(self.new_shelve_file) as new_shelf:
for index, fields in self.stream.stream():
#print(str(index))
if str(index)+'.0' in self.inclusionList and str(index)+'.0' not in self.exclusionList:
new_shelf[index] = self._get_fields(fields)
@editLogger('Filtered from Completed List', 'PythonScript')
def _get_fields(self, fields):
return fields
def start(self, users):
#users is a list of dictionary type objects
# dict type objects from getConfig()
print "Starting..."
#start Twitter stream
streamThreads = []
streamBuffers = []
for user in users:
sr = Stream(user['con_key'], user['con_secret'],
user['key'], user['secret'],
user['name'])
#insert user list into db
list = sr.getUserList(self.parseLists(user['lists']))
self.sql.insert_into_userList(list, user['db'])
track = []
for keyword in user['track'].split(','):
track.append(keyword)
#get buffer and run stream
buff = sr.getTweetsBuffer()
# if list is not None or track is not None:
# stream = sr.run(list, track)
# else:
# stream = sr.run(None)
stream = sr.run(list, track)
#add new buff and stream to list
streamBuffers.append({'buff':buff, 'db':user['db']})
streamThreads.append(stream)
print "Started user: "******"Started user: "******"Exiting..."
os._exit(0)
def main():
b, a = butter_bandpass(lowcut=0.1, highcut=5.0, fs=50, order=5)
y = np.zeros(len(a)-1)
state = (b, a, y)
filename = '20110111000000.2D.OBS34.SXZ.npy'
data_array = np.load(filename)
print 'len(data_array)', len(data_array)
data_array = data_array[:1000000]
x = Stream('x')
print 'a', a
print 'b', b
y = stream_func(x, f_type='window', f=linear_filter, num_outputs=1,
state=state, window_size=len(b), step_size=1)
x.extend(data_array)
y.set_name('y')
plt.plot(y.recent[5000:y.stop])
plt.show()
plt.close()
def get(self):
current_time = datetime.datetime.now()
all_streams = Stream.query()
for stream in all_streams:
for date in stream.view_queue:
minback = current_time - datetime.timedelta(hours=1)
if date < minback:
stream.view_queue.remove(date)
stream.views = stream.views - 1
stream.put()
def __init__(self,config):
self.config = config
# Commands
self.execute['list'] = self.list # list supported commands
self.execute['status'] = self.get_status # send status
self.execute['restart_machine'] = self.restart # restart machine
self.execute['poweroff_machine'] = self.poweroff #
self.execute['update'] = self.update # download files from github
if( config.enable('CAMERA') ) :
self.execute['photo'] = self.photo # take a photo
self.execute['tweet'] = self.tweet # take a photo, send a tweet
if( config.enable('SOUND') ) :
self.execute['beep'] = self.beep # play beep.wav
if( config.enable('RELAY') ) :
self.execute['relay'] = self.relay # trigger RelayEn
if(config.enable('MOTION') and config.enable('CAMERA')) :
self.execute['start_tweet'] = self.start_motion_tweet # tweet triggered by MotionEn
self.execute['stop_tweet'] = self.stop_motion_tweet
self.execute['start_alarm'] = self.start_motion_alarm # alarm triggered by MotionEn
self.execute['stop_alarm'] = self.stop_motion_alarm
if( config.enable('SERVO') ):
self.execute['pos_ventana'] = self.pos_ventana
self.execute['pos_adentro'] = self.pos_adentro
logging.info('Supported commads:')
for k in self.execute:
logging.info('\t%s'%k)
# Common resources
self.sem = threading.BoundedSemaphore(value=1)
if( Config.IS_RPI and config.enable('CAMERA') ):
self.Camera = picamera.PiCamera()
self.Stream = Stream(self.Camera,self.config)
self.Stream.run()
else:
self.Camera = None
self.Stream = None
if( config.enable('DISPLAY') ) : self.Display = Display( pin_rs=7, pin_e=8, pins_db=[25,24,23,18] )
else: self.Display = None
def test():
# Create stream x, and give it name 'x'.
x = Stream('input_0')
# u is the stream returned by stream_sum([x,y]) and
# v is the stream returned by stream_max([x,y])
# w is the stream returned by stream_mean([x,y]).
# u[i] = sum(x[i],y[i])
# v[i] = max(x[i],y[i])
# w[i] = mean(x[i],y[i])
evens, odds = stream_even_odd(x)
# Give names to streams u, v, and w. This is helpful in reading output.
evens.set_name('even numbers in x')
odds.set_name('odd numbers in x')
check(evens, [8, 4, 6, 2])
check(odds, [3,5])
print
print 'Adding [3, 5, 8], [1, 7, 2], [2, 3] to 3 input streams'
# Add values to the tail of stream x.
x.extend([3, 5, 8])
# Print recent values of the streams
print 'recent values of input streams'
x.print_recent()
print 'recent values of output streams'
evens.print_recent()
odds.print_recent()
print
print 'Adding [4, 6, 2], [2, 3, 8], [5, 3, 0, -1] to 3 input streams'
# Add more values to the tail of stream x.
x.extend([4, 6, 2])
# Print recent values of the streams
print 'recent values of input streams'
x.print_recent()
print 'recent values of output streams'
evens.print_recent()
odds.print_recent()
check_empty()
def test():
# Create stream x, and give it name 'x'.
x = Stream('input_0')
id_0_average, id_1_average = stream_split_by_sensor_id(x)
# Give names to streams u, v, and w. This is helpful in reading output.
id_0_average.set_name('average of id_0 sensors in x')
id_1_average.set_name('average of id_1 sensors in x')
check(id_0_average, [2.0, 3.0, 5.0, 4.0, 4.0])
check(id_1_average, [5.0, 3.0, 3.0, 4.0, 5.0, 6.0])
print
print 'Adding ([(0,2), (0,4), (1,5), (1,1), (0,9)]'
print 'to the input stream.'
# Add values to the tail of stream x.
x.extend([(0,2), (0,4), (1,5), (1,1), (0,9)])
# Print recent values of the streams
print
print 'recent values of input streams'
x.print_recent()
print
print 'recent values of output streams'
id_0_average.print_recent()
id_1_average.print_recent()
print
print
print 'Adding ([(1,3), (1,7), (0,1), (1,9), (1,11), (0,4)])'
print 'to the input stream.'
# Add values to the tail of stream x.
x.extend([(1,3), (1,7), (0,1), (1,9), (1,11), (0,4)])
# Print recent values of the streams
print 'recent values of input streams'
print
x.print_recent()
print 'recent values of output streams'
print
id_0_average.print_recent()
id_1_average.print_recent()
check_empty()
def get(self):
current_time = datetime.datetime.now()
all_streams = Stream.query()
for stream in all_streams:
for date in stream.view_queue:
minback = current_time - datetime.timedelta(hours=1)
if date < minback:
stream.view_queue.remove(date)
stream.views = stream.views - 1
stream.put()
def main():
x = Stream('x')
fs=250
b, a = butter_bandpass(
lowcut=4,
highcut=10,
fs=fs,
order=5)
# Create sine wave with frequency of 8
num_cycles = 4
hertz_1 = 8
hertz_2 = 16
time = 0.25
wavelength = 0.1
t = np.linspace(0, 20, 5000)
z_1 = np.sin(2*np.pi*hertz_1*t)
z_2 = 0.5*np.sin(2*np.pi*hertz_2*t)
z_3 = z_1+z_2
#print 't_1', t_1
#print 'z', z
#x.extend(z)
plt.plot(z_1[4000:])
#plt.title('input')
plt.show()
plt.close()
plt.plot(z_2[4000:])
#plt.title('input')
plt.show()
plt.close()
plt.plot(z_3[4000:])
#plt.title('input')
plt.show()
plt.close()
y = filter(b, a, input_stream=x)
x.extend(z_3)
plt.plot(y.recent[4000:y.stop])
plt.title('output')
plt.show()
plt.close()
def main():
def single_stream_of_random_numbers(trigger_stream):
def ran():
return random.random()
return stream_func(
inputs=None,
f_type='element',
f=ran,
num_outputs=1,
call_streams=[trigger_stream])
def stream_of_normal_and_pareto(clock_stream, b):
from scipy.stats import norm, pareto
def normal_and_pareto():
return [norm.rvs(size=1)[0], pareto.rvs(b, size=1)[0]]
return stream_func(
inputs=None,
f_type='element',
f=normal_and_pareto,
num_outputs=2,
call_streams=[clock_stream]
)
trigger = Stream('trigger')
r = single_stream_of_random_numbers(
trigger_stream=trigger)
u, v = stream_of_normal_and_pareto(
clock_stream=trigger, b=2.62171653214)
r.set_name('random')
u.set_name('normal')
v.set_name('pareto')
trigger.extend(['tick', 'tick'])
trigger.print_recent()
r.print_recent()
u.print_recent()
v.print_recent()
def get(self):
#Get the list of streams
images = {'stream_names': [], 'image_urls': []}
streams = Stream.query().order(-Stream.date_last_added)
for stream in streams:
images['stream_names'].append(stream.name)
images['image_urls'].append(stream.cover_image)
image_json = json.dumps(images,indent=4, separators=(',', ': '))
self.response.write(image_json)
def get(self):
#Get the list of streams
images = {'stream_names': [], 'image_urls': []}
streams = Stream.query().order(-Stream.date_last_added)
for stream in streams:
images['stream_names'].append(stream.name)
images['image_urls'].append(stream.cover_image)
image_json = json.dumps(images, indent=4, separators=(',', ': '))
self.response.write(image_json)
def test():
in_1 = Stream(name='in_1')
out_1 = Stream(name='out_1')
out_2 = Stream(name= 'out_2')
check(out_1, [4, 8])
check(out_2, [3, 5])
stream_agent(
inputs=in_1,
outputs=[out_1, out_2],
f_type='element',
f=number_even_odd)
in_1.extend([3, 4, 5, 8])
out_1.print_recent()
out_2.print_recent()
check_empty()
def start(self, users):
print "Starting..."
#start Twitter stream
streamThreads = []
streamBuffers = []
for user in users:
sr = Stream(user['con_key'], user['con_secret'],
user['key'], user['secret'],
user['name'])
#insert user list into db
list = sr.getUserList(self.parseLists(user['lists']))
self.sql.insert_into_userList(list, user['db'])
#get buffer and run stream
buff = sr.getTweetsBuffer()
if list is not None:
stream = sr.run(list)
else:
stream = sr.run(None)
#add new buff and stream to list
streamBuffers.append({'buff':buff, 'db':user['db']})
streamThreads.append(stream)
print "Started user: "******"Started user: "******"Exiting..."
os._exit(0)
def get(self):
self.cache('manage')
JINJA_ENVIRONMENT = jinja2.Environment(
loader=jinja2.FileSystemLoader('templates'),
extensions=['jinja2.ext.autoescape'],
autoescape=True)
user = users.get_current_user()
user_id = user.user_id()
user_email = user.email()
#Get the list of streams
my_streams = Stream.query(Stream.owner_id == user_id)
subscribed_streams = Stream.query(Stream.subscribed_users.IN([user_email]))
template_values = {
'my_streams':my_streams,
'subscribed_streams':subscribed_streams
}
template = JINJA_ENVIRONMENT.get_template('ManagementPage.html')
self.response.write(template.render(template_values))
def test():
# Create stream x and give it names 'x'.
x = Stream('input')
# v is the stream returned by stream_cumulative(x) and
# w is the stream returned by stream_cumulative(v).
v = stream_cumulative(x)
w = stream_cumulative(v)
# avg is the stream returned by stream_average(x)
avg = stream_average(x)
# Give names to streams. This is helpful in reading output.
v.set_name('cumulative sum of input')
w.set_name('cumulative sum of cumulative sum of input')
avg.set_name('average of input')
check(v, [3, 8, 18, 20, 25, 36])
check(w, [3, 11, 29, 49, 74, 110])
check(avg, [3.0, 4.0, 6.0, 5.0, 5.0, 6.0])
print
print 'add values [3, 5, 10] to the tail of the input stream.'
# Add values to the tail of stream x.
x.extend([3, 5, 10])
# Print the N most recent values of streams x, v, w.
x.print_recent()
v.print_recent()
w.print_recent()
avg.print_recent()
print
print 'add values [2, 5, 11] to the tail of the input stream.'
# Add more values to the tail of stream x.
x.extend([2, 5, 11])
# Print the N most recent values of streams x, v, w.
x.print_recent()
v.print_recent()
w.print_recent()
avg.print_recent()
check_empty()
def add_stream(self, component, section, status, enrols, times):
# Create stream object
stream = Stream(component=component,
section=section,
status=status,
enrols=enrols,
times=times)
# Include the stream iff all it's attributes are valid
if stream.included:
self.streams.append(stream)
return stream
def get(self):
self.cache('manage')
JINJA_ENVIRONMENT = jinja2.Environment(
loader=jinja2.FileSystemLoader('templates'),
extensions=['jinja2.ext.autoescape'],
autoescape=True)
user = users.get_current_user()
user_id = user.user_id()
user_email = user.email()
#Get the list of streams
my_streams = Stream.query(Stream.owner_id == user_id)
subscribed_streams = Stream.query(
Stream.subscribed_users.IN([user_email]))
template_values = {
'my_streams': my_streams,
'subscribed_streams': subscribed_streams
}
template = JINJA_ENVIRONMENT.get_template('ManagementPage.html')
self.response.write(template.render(template_values))
def get(self):
user_email = cgi.escape(self.request.get('user_email'))
#Get the list of streams
subscribed_streams = Stream.query(Stream.subscribed_users.IN([user_email]))
images = {'stream_names': [], 'image_urls': [],}
for stream in subscribed_streams:
images['stream_names'].append(stream.name)
images['image_urls'].append(stream.cover_image)
image_json = json.dumps(images,indent=4, separators=(',', ': '))
self.response.write(image_json)
def run(self):
"""
Runs the framework and returns a `Stream` of outputs.
Returns
-------
y_predict : `Stream`
A `Stream` containing outputs as returned by `predict_func`.
"""
self._initialize()
self._init_streams()
self.model_stream = Stream('model')
self.all_stream = Stream('all')
# Continual learning
if isinstance(self.data_train, Stream):
self.stream_filter(self.data_train)
self.stream_train(inputs=self.x_train)
if self.all_func is not None:
self.stream_all(inputs=self.data_train)
# Batch learning with numpy array
elif isinstance(self.data_train, np.ndarray):
x = self.data_train[:, 0:self.num_features]
y = self.data_train[:, self.num_features:]
self.model = self.train_func(x, y, None, None)
self.trained = True
# Batch learning
else:
self.model = self.train_func(self.data_train, None, None, None)
self.trained = True
y_predict = self.stream_predict(self.data_out)
return y_predict
def main():
# EXAMPLE FUNCTIONS ON WINDOWS
# Functions have a single input: a list
# which is the list of values in a window.
# Functions return a scalar value, _no_value
# or a list, _multivalue().
min_window_size = 2
max_window_size = 11
step_size = 2
input_stream = Stream('in')
# output_stream = Stream('out')
current_window_size = 0
steady_state = False
reset = False
state = [current_window_size, steady_state, reset]
def f(lst, state):
print lst
return (lst, state)
f_stream = partial(dynamic_window_func, f = f, state = state, min_window_size = min_window_size, max_window_size = max_window_size, step_size = step_size)
output_stream = f_stream(inputs = input_stream)
# output_stream = dynamic_window_func(
# f, input_stream, state,
# min_window_size, max_window_size, step_size)
for i in range(1, 15):
print "Adding ", i
input_stream.extend([i])
if i == 10:
state[2] = True
# output_stream.print_recent()
print "\n"
def main():
print "example_1"
print
x = Stream('x')
y = stream_func(x, f_type='window', f=ksigma,
num_outputs=1, window_size=WINDOW_SIZE,
step_size=STEP_SIZE)
y.set_name('y')
x.extend(range(20))
x.print_recent()
y.print_recent()
print
x.extend(range(20, 0, -1))
x.print_recent()
y.print_recent()
print
def test():
# Create stream x, and give it name 'input'.
x = Stream('input')
y = g(x)
y.set_name('output')
check(y, [3, 1, 2, 5, 2, 4, 7])
# Add values 3, 2, 5 to the tail of stream x.
x.extend([3, 2, 5])
x.print_recent()
y.print_recent()
# Add values 4, 7 to the tail of stream x.
x.extend([4, 7])
x.print_recent()
y.print_recent()
check_empty()
def main():
lst = [
(0, [3, 4, 1]),
(1, [4, 3, 2]),
(2, [2, 2, 3]),
(3, [1, 2, 1]),
(4, [0, 0, 2]),
(5, [1, 0, 1]),
(6, [0, 1, 1]),
(7, [2, 0, 1]),
(8, [1.5, 2, 1]),
(9, [2, 1.5, 3]),
(10, [3, 4, 1]),
(11, [4, 3, 0]),
]
x = Stream("x")
h, v = pick_h_and_v_in_stream(x)
h_quenched = quench_stream(h)
v_quenched = quench_stream(v)
h.set_name("h")
v.set_name("v")
h_quenched.set_name("h quenched")
v_quenched.set_name("v quenched")
x.extend(lst)
x.print_recent()
print
h.print_recent()
print
v.print_recent()
print
h_quenched.print_recent()
print
v_quenched.print_recent()
def __init__(self,
server_ip,
server_port,
user_interface=None,
is_root=False,
root_address=None):
"""
The Peer object constructor.
Code design suggestions:
1. Initialise a Stream object for our Peer.
2. Initialise a PacketFactory object.
3. Initialise our UserInterface for interaction with user commandline.
4. Initialise a Thread for handling reunion daemon.
Warnings:
1. For root Peer, we need a NetworkGraph object.
2. In root Peer, start reunion daemon as soon as possible.
3. In client Peer, we need to connect to the root of the network, Don't forget to set this connection
as a register_connection.
:param server_ip: Server IP address for this Peer that should be pass to Stream.
:param server_port: Server Port address for this Peer that should be pass to Stream.
:param is_root: Specify that is this Peer root or not.
:param root_address: Root IP/Port address if we are a client.
:type server_ip: str
:type server_port: int
:type is_root: bool
:type root_address: tuple
"""
self.server_address = (server_ip, server_port)
self.stream = Stream(server_ip, server_port)
self.packet_factory = PacketFactory()
self.user_interface = user_interface
def main():
def max_and_min(lst):
return (max(lst), min(lst))
x = Stream('x')
y,z = stream_func(x, f_type='window', f=max_and_min,
num_outputs=2, window_size=2, step_size=2)
y.set_name('y')
z.set_name('z')
x.extend([3,5])
x.print_recent()
y.print_recent()
z.print_recent()
print
x.extend([11,15])
x.print_recent()
y.print_recent()
z.print_recent()
print
def get(self):
user_email = cgi.escape(self.request.get('user_email'))
#Get the list of streams
subscribed_streams = Stream.query(
Stream.subscribed_users.IN([user_email]))
images = {
'stream_names': [],
'image_urls': [],
}
for stream in subscribed_streams:
images['stream_names'].append(stream.name)
images['image_urls'].append(stream.cover_image)
image_json = json.dumps(images, indent=4, separators=(',', ': '))
self.response.write(image_json)
def calc_st2_o(self):
st2_o = Stream()
st2_o.fluid = self.st2_i.fluid
st2_o.flow_rate = self.st2_i.flow_rate
st2_o.pressure = self.st2_i.pressure - self.pressure_drop(
self.st2_i, self.st2_pip)
h = self.st2_i.h - (self.st1_i.h - self.st1_o.h) * self.st1_i.flow_rate[0] \
/ st2_o.flow_rate[0] / self.eta
h_l = PropsSI('H', 'P', st2_o.pressure, 'Q', 0, st2_o.fluid)
h_g = PropsSI('H', 'P', st2_o.pressure, 'Q', 1, st2_o.fluid)
if h_l <= h <= h_g:
st2_o.x = PropsSI('Q', 'P', st2_o.pressure, 'H', h, st2_o.fluid)
else:
st2_o.temperature = PropsSI('T', 'P', st2_o.pressure, 'H', h,
st2_o.fluid)
self.st2_o = st2_o
def calc_st2_i(self):
st2_i = Stream()
st2_i.fluid = self.st2_o.fluid
st2_i.flow_rate = self.st2_o.flow_rate
st2_i.pressure = self.st2_o.pressure + self.pressure_drop(
self.st2_o, self.st2_pip)
h = self.st2_o.h + (self.st1_i.h - self.st1_o.h) * self.st1_i.flow_rate[0] \
/ self.st2_o.flow_rate[0] * self.eta
h_l = PropsSI('H', 'P', st2_i.pressure, 'Q', 0, st2_i.fluid)
h_g = PropsSI('H', 'P', st2_i.pressure, 'Q', 1, st2_i.fluid)
if h_l <= h <= h_g:
st2_i.x = PropsSI('Q', 'P', st2_i.pressure, 'H', h, st2_i.fluid)
else:
st2_i.T = PropsSI('T', 'P', st2_i.pressure, 'H', h,
self.st2_i.fluid)
self.st2_i = st2_i
def get(self):
# self.setup('trending')
self.cache('trending')
JINJA_ENVIRONMENT = jinja2.Environment(
loader=jinja2.FileSystemLoader('templates'),
extensions=['jinja2.ext.autoescape'],
autoescape=True)
#Get the list of streams
streams = Stream.query().order(-Stream.views)
template_values = {
'streams':streams
}
template = JINJA_ENVIRONMENT.get_template('TrendingStreamsPage.html')
self.response.write(template.render(template_values))
def __init__(self):
self.stream_parent_conn, self.stream_child_conn = mp.Pipe()
model_path = '../data/faster_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb'
self.odapi = DetectorAPI(path_to_ckpt=model_path)
self.cal = Calibration()
self.comm = Comm()
self.stream = Stream(self.stream_child_conn)
self.str = mp.Process(target=self.stream.run, args=())
self.eat = None
self.socket_update = None
self.frame_lock = mp.RLock()
self.coords_lock = mp.RLock()
self.coords = []
def get(self):
self.cache('view')
JINJA_ENVIRONMENT = jinja2.Environment(
loader=jinja2.FileSystemLoader('templates'),
extensions=['jinja2.ext.autoescape'],
autoescape=True)
user = users.get_current_user()
user_id = user.user_id()
#Get the list of streams
my_streams = Stream.query(Stream.owner_id == user_id).order(Stream.timestamp)
template_values = {
'my_streams':my_streams,
}
template = JINJA_ENVIRONMENT.get_template('ViewAllStreamsPage.html')
self.response.write(template.render(template_values))
class Processor:
def __init__(self): # f, outputFilePath):
self.stream = Stream(self.inputFilePath, self.dict_key)
self.new_shelf_file = self.outputFilePath
def process(self):
with ShelveManager(self.new_shelf_file) as new_shelf:
for index, fields in self.stream.stream():
if index in new_shelf:
#print('index in new shelf')
### Some sort of check whether self.resolve.. returns anything, otherwise don't set the index?
new_shelf[index] = self.resolve(new_shelf[index], fields)
else:
#print('index not in new shelf')
new_shelf[index] = self.transform(fields)
def get_st2(self, st1, pressure2):
st2 = Stream()
st2.fluid = st1.fluid
st2.flow_rate = st1.flow_rate
st2.pressure = pressure2
s_ideal = st1.s
h2_ideal = PropsSI('H', 'S', s_ideal, 'P', st2.pressure, st2.fluid)
eta = self.calculate_eta(st1.pressure, st2.pressure)
h2 = st1.h - eta * (st1.h - h2_ideal)
# Check whether it is saturated
h2_l = PropsSI('H', 'P', st2.pressure, 'Q', 0, st2.fluid)
h2_g = PropsSI('H', 'P', st2.pressure, 'Q', 1, st2.fluid)
if h2_l <= h2 <= h2_g:
st2.quality = PropsSI('Q', 'P', st2.pressure, 'H', h2, st2.fluid)
else:
st2.temperature = PropsSI('T', 'P', st2.pressure, 'H', h2,
st2.fluid)
return st2
def get(self):
message = mail.EmailMessage()
user = users.get_current_user()
message.sender = user.email()
message.subject = "Trending"
message.to = user.email()
#Get the list of streams
streams = Stream.query().order(-Stream.views)
i = 0
top = []
for stream in streams:
if i == 3:
break
top.append(stream.name)
i = i + 1
if len(top) == 3:
message.body = "'Top 3 Trending Streams: %s %s %s'" % (
top[0], top[1], top[2])
else:
message.body = "'There are not 3 streams in the datastore'"
message.send()
def get(self):
JINJA_ENVIRONMENT = jinja2.Environment(
loader=jinja2.FileSystemLoader('templates'),
extensions=['jinja2.ext.autoescape'],
autoescape=True)
user = users.get_current_user()
login_url = users.create_login_url('/management')
if user:
self.redirect('/management')
#Get the list of streams
streams = Stream.query()
template_values = {
'login_url': login_url,
}
template = JINJA_ENVIRONMENT.get_template('MainPage.html')
self.response.write(template.render(template_values))
def make_timer_streams_for_network(agent_dict):
"""
Returns
-------
agent_timer_dict, a dict where
key: agent_name
value: a stream (note a stream and not a name)
This stream is a call stream of the agent
with the specified name (the key). Usually,
timing messages are sent on this stream.
The agent takes a step when it receives a
message on this stream.
"""
agent_timer_dict = dict()
for agent_name, agent in agent_dict.items():
timer_stream = Stream(agent_name + ':timer')
if agent.call_streams is None:
agent.call_streams = [timer_stream]
agent_timer_dict[agent_name] = timer_stream
return agent_timer_dict
def inlezen_file(checkpublic, file):
f = open(file, "r")
if f.mode == "r":
acl_interface = ""
for line in f:
# Haal alle dubbele spaties weg uit de regel.
line = re.sub('\s+',' ',line)
# lees regel in en split op spatie.
lineArray = line.split(" ")
# Voeg waardes toe aan variabele voor verdere referentie in de code
source_interface = lineArray[9].split("/")[0]
src_ip_split = lineArray[9].split("/")[1]
src_ip = src_ip_split.split("(")[0]
src_port = src_ip_split.split("(")[1].replace(")"," ").rstrip()
acl_interface = lineArray[6]
protocol = lineArray[8].strip().lower()
dst_ip_split = lineArray[11].split("/")[1]
dst_ip = dst_ip_split.split("(")[0]
dst_port = dst_ip_split.split("(")[1].replace(")", " ").rstrip()
dst_interface = lineArray[11].split("/")[0]
# Haal vanuit de syslog over welke interface ACL het gaat. Dit wordt in de klasse opgeslagen en later gebruikt om ASA CLI uit te printen
Stream.interface = acl_interface
# controleer of stream ping verkeer is
if protocol == "icmp":
src_port = "0"
dst_port = "0"
# controleer of het destination ip-adres publiek of private is. Indien publieke filtering aanstaat wordt het destination adres aangepast naar "any"
if checkpublic is True:
ip = IP(dst_ip)
type_ip = ip.iptype()
if type_ip == "PUBLIC":
dst_ip = "any"
Stream(src_ip,dst_ip,dst_port,protocol)
def cache(self, currentTab):
JINJA_ENVIRONMENT = jinja2.Environment(
loader=jinja2.FileSystemLoader('templates'),
extensions=['jinja2.ext.autoescape'],
autoescape=True)
user = users.get_current_user()
user_id = user.user_id()
logout_url = users.create_logout_url('/')
#welcome to Connexus
userInfo = {'user': user, 'logout_url': logout_url}
template = JINJA_ENVIRONMENT.get_template('Welcome.html')
self.response.write(template.render(userInfo))
#Get the list of streams
streams = Stream.query()
taglist = []
streamNames = []
for stream in streams:
streamNames.append(str(stream.name))
for tag in stream.tags:
if tag not in taglist:
streamNames.append(tag)
taglist.append(tag)
template_values = {'streams': streams}
template = JINJA_ENVIRONMENT.get_template('Search.html')
self.response.write(template.render(streams=json.dumps(streamNames)))
#test search header
searchHead = JINJA_ENVIRONMENT.get_template('Header.html')
self.response.write(searchHead.render(current=currentTab))
def __init__(self,
config,
timestamp,
q=None,
watchdogQueue=None,
marsOnlineQueue=None,
ipAddress=None):
#assign queues
self._watchdogQueue = watchdogQueue
self._marsOnlineQueue = marsOnlineQueue
#Init devices
self._devices = self.initDevices(config)
#Prepare stream
self._devices['Stream'] = Stream(config, timestamp, ipAddress)
logger.info("Connecting Jetson")
self._jetson = Jetson(self._devices, config, timestamp, q)
time.sleep(.5)
logger.info("All devices connected")
logger.info("System initialized.")
if q is None:
try:
answer = raw_input("Would you like to start? Y/n: ")
except KeyboardInterrupt:
self._jetson.exit()
return
if answer.lower() == 'n' or answer.lower() == 'no':
self._jetson.exit()
else:
self._jetson.start()
else:
self._jetson.start()
def _getBuiltInDefaultValue(self, instance):
import pyre.parsing.locators
locator = pyre.parsing.locators.default()
import sys
if hasattr(sys.stdout, 'isatty') and sys.stdout.isatty():
from os import environ
term = environ.get('TERM', 'console')
component = instance.retrieveComponent(term,
factory=self.family,
vault=self.vault)
if component is None:
from Console import Console
component = Console()
else:
component.aliases.append(self.name)
locator = pyre.parsing.locators.chain(component.getLocator(),
locator)
else:
from Stream import Stream
component = Stream(sys.stdout, "stdout")
return component, locator
def start(self, users):
print "Starting..."
#start Twitter stream
streamThreads = []
streamBuffers = []
for user in users:
sr = Stream(user['con_key'], user['con_secret'], user['key'],
user['secret'], user['name'])
#insert user list into db
list = sr.getUserList(self.parseLists(user['lists']))
self.sql.insert_into_userList(list, user['db'])
#get buffer and run stream
buff = sr.getTweetsBuffer()
if list is not None:
stream = sr.run(list)
else:
stream = sr.run(None)
#add new buff and stream to list
streamBuffers.append({'buff': buff, 'db': user['db']})
streamThreads.append(stream)
print "Started user: "******"Started user: "******"Exiting..."
os._exit(0)
def make_process(
input_stream_names, output_stream_names, func,
input_queue, output_queues_list):
""" Makes a process that gets messages on its single
input queue, processes the messages and puts messages
on its output queues. An output queue of this process
is an input queue of another process.
Parameters
----------
input_stream_names : list of str
List of names of input streams
output_stream_names : list of str
List of names of output streams
func : function
The parameters of func are
input_streams, output_streams where
input_streams is a list of streams whose names
are in input_stream_names and where
output_streams is a list of streams whose names
are in output_stream_names. func gets messages
on its input streams and puts messages on its
output streams.
input_queue: multiprocessing.Queue
Each process has a single input queue along
which it receives messages.
output_queues_list : list of list of multiprocessing.Queue
output_queues_list[j] is the list of queues to
which messages that appear on the stream with name
output_stream_names[j] should be sent.
Returns
-------
None
Attributes
----------
input_streams : list of Stream
input_stream[j] is the Stream with name
input_stream_name[j].
output_streams : list of Stream
output_stream[j] is the Stream with name
output_stream_name[j].
map_name_to_input_stream : dict
key : str
name of an input stream
value : Stream
The stream with the specified name.
Notes
-----
make_process carries out the following steps:
(1) Sets up data structures for the next two steps.
(2) Calls func which creates the network of agents
that process messages on its input streams and puts
messages on its output streams.
(3) Makes the output and input managers.
"""
# Create input_streams, output_streams and
# map_name_to_input_stream
input_streams = [Stream(name) for name in input_stream_names]
output_streams = [Stream(name) for name in output_stream_names]
map_name_to_input_stream = dict()
for stream in input_streams:
map_name_to_input_stream[stream.name] = stream
# Call the function that creates a network of agents that
# map input streams to output streams.
func(input_streams, output_streams)
new_output_queues_list = list()
for output_queues in output_queues_list:
new_output_queues = list()
for output_queue in output_queues:
if isinstance(output_queue, tuple):
SERVER, PORT, DESTINATION = output_queue
new_output_queue = RemoteQueue(SERVER, PORT, DESTINATION)
new_output_queues.append(new_output_queue)
else:
new_output_queues.append(output_queue)
new_output_queues_list.append(new_output_queues)
make_output_manager(output_streams, new_output_queues_list)
if isinstance(input_queue, tuple):
SERVER, PORT, DESTINATION = input_queue
input_queue = RemoteQueue(SERVER, PORT, DESTINATION)
make_input_manager(input_queue, input_streams, map_name_to_input_stream)