def scrape_ending(self, topic):
if not self.scalability_test:
return
try:
self.waiting_to_finish.remove(topic)
except KeyError:
_log.warning(topic + " published twice before test finished, increase the length of scrape interval and rerun test")
if not self.waiting_to_finish:
end = datetime.now()
delta = end - self.current_test_start
delta = delta.total_seconds()
self.test_results.append(delta)
self.test_iterations += 1
_log.info("publish {} took {} seconds".format(self.test_iterations, delta))
if self.test_iterations >= self.scalability_test_iterations:
#Test is now over. Button it up and shutdown.
mean = math_utils.mean(self.test_results)
stdev = math_utils.stdev(self.test_results)
_log.info("Mean total publish time: "+str(mean))
_log.info("Std dev publish time: "+str(stdev))
sys.exit(0)
def scrape_ending(self, topic):
if not self.scalability_test:
return
try:
self.waiting_to_finish.remove(topic)
except KeyError:
_log.warning(
topic +
" published twice before test finished, increase the length of scrape interval and rerun test"
)
if not self.waiting_to_finish:
end = datetime.now()
delta = end - self.current_test_start
delta = delta.total_seconds()
self.test_results.append(delta)
self.test_iterations += 1
_log.info("publish {} took {} seconds".format(
self.test_iterations, delta))
if self.test_iterations >= self.scalability_test_iterations:
#Test is now over. Button it up and shutdown.
mean = math_utils.mean(self.test_results)
stdev = math_utils.stdev(self.test_results)
_log.info("Mean total publish time: " + str(mean))
_log.info("Std dev publish time: " + str(stdev))
sys.exit(0)
def determine_prices(self):
try:
if self.prices:
avg_price = mean(self.prices)
std_price = stdev(self.prices)
price_min = avg_price - self.price_multiplier * std_price
price_max = avg_price + self.price_multiplier * std_price
else:
price_min = self.default_min_price
price_max = self.default_max_price
except:
price_min = self.default_min_price
price_max = self.default_max_price
return price_min, price_max
def determine_prices(self):
if self.prices:
avg_price = mean(self.prices)
std_price = stdev(self.prices)
price_min = avg_price - self.price_multiplier * std_price
price_max = avg_price + self.price_multiplier * std_price
_log.debug(
'{}: price debug avg {} - std_dev: {} - min: {} - max: {}'.
format(self.agent_name, avg_price, std_price, price_min,
price_max))
else:
price_min = self.default_min_price
price_max = self.default_max_price
price_array = np.linspace(price_min, price_max, 11)
return price_array
def determine_prices(self):
"""
Determine minimum and maximum price from 24-hour look ahead prices. If the TNS
market architecture is not utilized, this function must be overwritten in the child class.
:return:
"""
if self.market_prices:
avg_price = mean(self.market_prices)
std_price = stdev(self.market_prices)
price_min = avg_price - self.price_multiplier * std_price
price_max = avg_price + self.price_multiplier * std_price
else:
avg_price = None
std_price = None
price_min = self.default_min_price
price_max = self.default_max_price
_log.debug("Prices: {} - avg: {} - std: {}".format(self.market_prices, avg_price, std_price))
price_array = np.linspace(price_min, price_max, 11)
return price_array
def publish_to_historian(self, to_publish_list):
for item in to_publish_list:
if self._gather_timing_data:
turnaround_time = add_timing_data_to_header(item["headers"],
self.core.agent_uuid or self.core.identity,
"published")
self._turnaround_times.append(turnaround_time)
if len(self._turnaround_times) > 10000:
# Test is now over. Button it up and shutdown.
mean = math_utils.mean(self._turnaround_times)
stdev = math_utils.stdev(self._turnaround_times)
_log.info("Mean time from collection to publish: " + str(mean))
_log.info("Std dev time from collection to publish: " + str(stdev))
self._turnaround_times = []
#_log.debug("publishing {}".format(item))
_log.debug("recieved {} items to publish"
.format(len(to_publish_list)))
self.report_all_handled()
def publish_to_historian(self, to_publish_list):
for item in to_publish_list:
if self._gather_timing_data:
turnaround_time = add_timing_data_to_header(item["headers"],
self.core.agent_uuid or self.core.identity,
"published")
self._turnaround_times.append(turnaround_time)
if len(self._turnaround_times) > 10000:
# Test is now over. Button it up and shutdown.
mean = math_utils.mean(self._turnaround_times)
stdev = math_utils.stdev(self._turnaround_times)
_log.info("Mean time from collection to publish: " + str(mean))
_log.info("Std dev time from collection to publish: " + str(stdev))
self._turnaround_times = []
#_log.debug("publishing {}".format(item))
_log.debug("recieved {} items to publish"
.format(len(to_publish_list)))
self.report_all_handled()
