def __init__(self, parent, instance_name, status):
BasicApp.__init__(self, parent, instance_name, status)
self.code = ""
self.__plot = None
self.__plotter = Plotter(create_plot_function=self.create_plot,
plot_ready_function=self.replot)
self.q = Queue()
def __init__(self, parent, instance_name, status):
BasicApp.__init__(self, parent, instance_name, status)
self.code = ""
self.__plot = None
self.__plotter = Plotter(create_plot_function=self.create_plot, plot_ready_function=self.replot)
self.q = Queue()
class PythonCmd(BasicApp):
app_name = "PythonCmd"
input_types = ["file"]
output_types = ["file"]
def __init__(self, parent, instance_name, status):
BasicApp.__init__(self, parent, instance_name, status)
self.code = ""
self.__plot = None
self.__plotter = Plotter(create_plot_function=self.create_plot,
plot_ready_function=self.replot)
self.q = Queue()
@classmethod
def accepts_input_app(cls, app):
return True
def set_code(self, code):
self.code = code
with open(self.config_path("code.py"), "w") as pf:
pf.write(self.code)
def get_code(self):
if self.code.strip() == "" and os.path.exists(
self.config_path("code.py")):
with open(self.config_path("code.py")) as pf:
self.code = pf.read()
return self.code
def run(self):
self.debug(str(self.code))
try:
exec(self.code)
return True
except Exception as ex:
self.debug("exception: \n" + str(ex))
return False
def replot(self):
self.signal("plotChanged")
def get_plot(self):
# if self.__plot is None:
# self.__plot = self.create_plot()
# plotter = Plotter(plot=self.__plot)
self.debug("get_plot")
return self.__plotter.result()
def clear_plot(self):
if self.__plot:
self.__plot.clf()
self.__plot.cla()
def create_plot(self):
"""
example plot data
"""
mu = 100 # mean of distribution
sigma = 15 # standard deviation of distribution
x = mu + sigma * numpy.random.randn(10000)
plt.cla()
plt.clf()
num_bins = 50
# the histogram of the data
n, bins, patches = plt.hist(x,
num_bins,
normed=1,
facecolor='green',
alpha=0.5)
# add a 'best fit' line
y = mlab.normpdf(bins, mu, sigma)
plt.plot(bins, y, 'r--')
plt.xlabel('Smarts')
plt.ylabel('Probability')
plt.title(r'Histogram of IQ: $\mu=100$, $\sigma=15$')
# Tweak spacing to prevent clipping of ylabel
plt.subplots_adjust(left=0.15)
return plt
def run_thread(self):
from _thread import start_new_thread
def f():
while True:
self.log(self.q.get())
start_new_thread(f, ())
def run_multi(self):
from multiprocessing import Process
def f(name, q):
from time import sleep
i = 0
while True:
sleep(2)
q.put("hello from process " + str(i))
i += 1
p = Process(target=f, args=('bob', self.q))
p.start()
class PythonCmd(BasicApp):
app_name = "PythonCmd"
input_types = ["file"]
output_types = ["file"]
def __init__(self, parent, instance_name, status):
BasicApp.__init__(self, parent, instance_name, status)
self.code = ""
self.__plot = None
self.__plotter = Plotter(create_plot_function=self.create_plot, plot_ready_function=self.replot)
self.q = Queue()
@classmethod
def accepts_input_app(cls, app):
return True
def set_code(self, code):
self.code = code
with open(self.config_path("code.py"), "w") as pf:
pf.write(self.code)
def get_code(self):
if self.code.strip() == "" and os.path.exists(self.config_path("code.py")):
with open(self.config_path("code.py")) as pf:
self.code = pf.read()
return self.code
def run(self):
self.debug(str(self.code))
try:
exec(self.code)
return True
except Exception as ex:
self.debug("exception: \n"+str(ex))
return False
def replot(self):
self.signal("plotChanged")
def get_plot(self):
# if self.__plot is None:
# self.__plot = self.create_plot()
# plotter = Plotter(plot=self.__plot)
self.debug("get_plot")
return self.__plotter.result()
def clear_plot(self):
if self.__plot:
self.__plot.clf()
self.__plot.cla()
def create_plot(self):
"""
example plot data
"""
mu = 100 # mean of distribution
sigma = 15 # standard deviation of distribution
x = mu + sigma * numpy.random.randn(10000)
plt.cla()
plt.clf()
num_bins = 50
# the histogram of the data
n, bins, patches = plt.hist(x, num_bins, normed=1, facecolor='green', alpha=0.5)
# add a 'best fit' line
y = mlab.normpdf(bins, mu, sigma)
plt.plot(bins, y, 'r--')
plt.xlabel('Smarts')
plt.ylabel('Probability')
plt.title(r'Histogram of IQ: $\mu=100$, $\sigma=15$')
# Tweak spacing to prevent clipping of ylabel
plt.subplots_adjust(left=0.15)
return plt
def run_thread(self):
from _thread import start_new_thread
def f():
while True:
self.log(self.q.get())
start_new_thread(f, () )
def run_multi(self):
from multiprocessing import Process
def f(name, q):
from time import sleep
i=0
while True:
sleep(2)
q.put("hello from process "+str(i))
i+=1
p = Process(target=f, args=('bob', self.q))
p.start()
# p.join()
