def get_results(config_name, version):
if config_name:
config_name = config_name.upper()
base_config = getattr(configs, config_name)
else:
base_config = {"name": ""}
config = configs.remove_wait_times(base_config)
if not config_name:
config["name"] = ""
if version:
config["version"] = version
results = network.get_results(config)
print "ID TASKID VERSION COMPLETED_TIME WORKER CONFIG_NAME INCIDENTS THROUGPUT"
print "=== ====== ======= ================ ========== ================================================== ========= ========="
for result in results:
print (
"{id:3d} {taskid:6d} {config[version]:7s} {completed_time:%d.%m.%Y %H:%M} "
"{worker:10s} {config[name]:50s} {incidents:9.0f} {avg_throughput:9.0f}".format(**result)
)
def get_results(config_name, version):
if config_name:
config_name = config_name.upper()
base_config = getattr(configs, config_name)
else:
base_config = {'name': ''}
config = configs.remove_wait_times(base_config)
if not config_name:
config['name'] = ''
if version:
config['version'] = version
results = network.get_results(config)
print 'ID TASKID VERSION COMPLETED_TIME WORKER CONFIG_NAME INCIDENTS THROUGPUT'
print '=== ====== ======= ================ ========== ================================================== ========= ========='
for result in results:
print(
'{id:3d} {taskid:6d} {config[version]:7s} {completed_time:%d.%m.%Y %H:%M} '
'{worker:10s} {config[name]:50s} {incidents:9.0f} {avg_throughput:9.0f}'
.format(**result))
def plot(config_name, version, pdf, r, stdout, max_tp, tp, name, wtp):
config_name = config_name.upper()
base_config = getattr(configs, config_name)
config = configs.remove_wait_times(base_config)
if version:
config["version"] = version
if r or stdout:
csvstring = StringIO()
csvwriter = csv.writer(csvstring)
else:
if pdf:
fig = plt.figure(dpi=300)
else:
fig = plt.figure()
if pdf:
latexify()
filename = config_name.lower()
if tp:
data = network.get_plot_data(config, ["results->'avg_throughput'", "results->'incidents'", "config->>'name'"])
logger.info("Got Data")
if max_tp:
data = [(i, x, y, name) for i, x, y, name in data if int(re.findall("\d+", name)[0]) <= max_tp]
logger.info("%d points", len(data))
ids, x, y, name = zip(*data)
if r or stdout:
csvwriter.writerow(["x", "y"])
for row in zip(x, y):
csvwriter.writerow(row)
else:
# fig.suptitle(runid)
ax = fig.add_subplot(111)
def onpick3(event):
ind = event.ind
for i in ind:
print (ids[i])
# get_result(ids[i])
x = np.array(x)
y = np.array(y)
n = 1000
# distance_weight = 0.01
# def rolling_avg(ax):
# indexes = np.logical_and(x > (ax-n), x < (ax + n))
# values = y[indexes]
# #x_values = x[indexes]
# #weights = 1/np.abs((x_values - ax) + 1)
# return np.average(values)
# x2 = np.arange(2000, 14000, 10)
# y2 = []
# for x_val in x2:
# y2.append(rolling_avg(x_val))
# ax.plot(x2, y2)
ax.scatter(x, y, picker=True)
# sns.regplot(x, y, lowess=True, y_jitter=0.3, x_jitter=0, ax=ax, scatter_kws={'picker': True})
fig.canvas.mpl_connect("pick_event", onpick3)
# plt.ylim(-1, 12)
plt.xlabel("Throughput")
plt.ylabel("Incidents")
plt.tight_layout()
elif name:
filename += ".names"
data = network.get_plot_data(config, ["config->>'name'"])
logger.info("%d points", len(data))
ids, names = zip(*data)
counter = Counter()
for name in names:
counter[name] += 1
counts = counter.most_common()
counts = [(int(re.findall("\d+", name)[0]), name, cnt) for name, cnt in counts]
counts.sort()
width = 0.8
numbers, names, counts = zip(*counts)
ind = np.arange(len(names))
plt.title(config["name"])
plt.bar(ind, counts, width=width)
plt.xticks(ind + width / 2, numbers)
# plt.ylim(24, 30)
plt.tight_layout()
elif wtp:
filename += ".wanted_throughputs"
data = network.get_plot_data(config, ["config->>'name'", "results->'avg_throughput'"])
logger.info("%d points", len(data))
ids, names, throughputs = zip(*data)
inputs = [int(re.findall("\d+", name)[0]) for name in names]
plt.title(config["name"])
plt.scatter(inputs, throughputs)
# plt.ylim(24, 30)
plt.tight_layout()
plt.show()
filename = filename + ".pdf"
if r:
if not os.path.exists("pdf"):
os.makedirs("pdf")
r_process = subprocess.Popen(["Rscript", "plot.R", os.path.join("pdf", filename)], stdin=subprocess.PIPE)
r_process.communicate(csvstring.getvalue())
elif stdout:
print csvstring.getvalue()
elif pdf:
ax = plt.gca()
format_axes(ax)
if not os.path.exists("pdf"):
os.makedirs("pdf")
plt.savefig(os.path.join("pdf", filename))
else:
plt.show()
def plot(config_name, version, pdf, r, stdout, max_tp, tp, name, wtp):
config_name = config_name.upper()
base_config = getattr(configs, config_name)
config = configs.remove_wait_times(base_config)
if version:
config['version'] = version
if r or stdout:
csvstring = StringIO()
csvwriter = csv.writer(csvstring)
else:
if pdf:
fig = plt.figure(dpi=300)
else:
fig = plt.figure()
if pdf:
latexify()
filename = config_name.lower()
if tp:
data = network.get_plot_data(config, [
"results->'avg_throughput'", "results->'incidents'",
"config->>'name'"
])
logger.info("Got Data")
if max_tp:
data = [(i, x, y, name) for i, x, y, name in data
if int(re.findall('\d+', name)[0]) <= max_tp]
logger.info('%d points', len(data))
ids, x, y, name = zip(*data)
if r or stdout:
csvwriter.writerow(['x', 'y'])
for row in zip(x, y):
csvwriter.writerow(row)
else:
#fig.suptitle(runid)
ax = fig.add_subplot(111)
def onpick3(event):
ind = event.ind
for i in ind:
print(ids[i])
#get_result(ids[i])
x = np.array(x)
y = np.array(y)
n = 1000
#distance_weight = 0.01
# def rolling_avg(ax):
# indexes = np.logical_and(x > (ax-n), x < (ax + n))
# values = y[indexes]
# #x_values = x[indexes]
# #weights = 1/np.abs((x_values - ax) + 1)
# return np.average(values)
# x2 = np.arange(2000, 14000, 10)
# y2 = []
# for x_val in x2:
# y2.append(rolling_avg(x_val))
# ax.plot(x2, y2)
ax.scatter(x, y, picker=True)
#sns.regplot(x, y, lowess=True, y_jitter=0.3, x_jitter=0, ax=ax, scatter_kws={'picker': True})
fig.canvas.mpl_connect('pick_event', onpick3)
#plt.ylim(-1, 12)
plt.xlabel('Throughput')
plt.ylabel('Incidents')
plt.tight_layout()
elif name:
filename += '.names'
data = network.get_plot_data(config, ["config->>'name'"])
logger.info('%d points', len(data))
ids, names = zip(*data)
counter = Counter()
for name in names:
counter[name] += 1
counts = counter.most_common()
counts = [(int(re.findall('\d+', name)[0]), name, cnt)
for name, cnt in counts]
counts.sort()
width = .8
numbers, names, counts = zip(*counts)
ind = np.arange(len(names))
plt.title(config['name'])
plt.bar(ind, counts, width=width)
plt.xticks(ind + width / 2, numbers)
#plt.ylim(24, 30)
plt.tight_layout()
elif wtp:
filename += '.wanted_throughputs'
data = network.get_plot_data(
config, ["config->>'name'", "results->'avg_throughput'"])
logger.info('%d points', len(data))
ids, names, throughputs = zip(*data)
inputs = [int(re.findall('\d+', name)[0]) for name in names]
plt.title(config['name'])
plt.scatter(inputs, throughputs)
#plt.ylim(24, 30)
plt.tight_layout()
plt.show()
filename = filename + '.pdf'
if r:
if not os.path.exists('pdf'):
os.makedirs('pdf')
r_process = subprocess.Popen(
['Rscript', 'plot.R',
os.path.join('pdf', filename)],
stdin=subprocess.PIPE)
r_process.communicate(csvstring.getvalue())
elif stdout:
print csvstring.getvalue()
elif pdf:
ax = plt.gca()
format_axes(ax)
if not os.path.exists('pdf'):
os.makedirs('pdf')
plt.savefig(os.path.join('pdf', filename))
else:
plt.show()
