def plot()

in scripts/throughput.py [0:0]

• 32 lines of code
• 1 McCabe index (conditional complexity)

def plot(parsed_log_file, x_label='Number of shards', z_label='tx in-flight', legend_position='lower right', style='plot'):
	with open(parsed_log_file, 'r') as f:
		orders = eval(f.read())

	for (orders_type, order) in orders.items():
		fig = plt.figure()
		width = 2
		i = -3
		for (z_value, items) in sorted(order.items(), reverse=True):
			x_values = []
			y_values = []
			y_err = []
			for item in items:
				x, y = list(zip(*item))
				x = int(x[0])
				y = np.array(y).astype(np.int)
				x_values.append(x)
				y_values.append(np.mean(y))
				y_err.append(np.std(y))
			if style == 'bar':
				plt.bar(np.array(x_values) + i, y_values, width, yerr=y_err,
	            	label='%s %s' % (z_value, z_label))
				i = i + width
				plt.xticks(x_values, x_values)
			else:
				#plt.plot(x_values, y_values)
				plt.ylim(0, 180000)
				plt.errorbar(x_values, y_values, yerr=y_err, uplims=True, lolims=True,
	            	label='%s %s' % (z_value, z_label), marker='.', alpha=1, dashes=None)

		plt.legend(loc=legend_position)
		plt.xlabel(x_label)
		plt.ylabel('Observed throughput (tx / sec)')
		plt.savefig('%s.pdf' % orders_type)
		print('created figure "%s.pdf".' % orders_type)