import numpy as np
import gzip
import pickle
import json
#
def read_server_results(filename):
	with gzip.GzipFile(filename, 'rb') as f:
		results = pickle.load(f)
		for x in range(len(results)):
			results[x]['deltas']['bytes'] = np.array(results[x]['deltas']['bytes'])
			results[x]['deltas']['timestamps'] = np.array(results[x]['deltas']['timestamps'])
			results[x]['custom_data'] = json.loads(results[x]['custom_data'].decode('utf-8'))
			if np.sum(results[x]['deltas']['bytes']) != results[x]['data_size']:
				print('Note: missing some data')
			#
		#
		return results
	#
#
def read_server_results_brief(filename):
	with open(filename, 'r') as f:
		return json.load(f)
	#
#
def read_remote_cpu_usage(filename):
	with gzip.GzipFile(filename, 'rb') as f:
		return pickle.load(f)
	#
#
def read_client_info(filename):
	with gzip.GzipFile(filename, 'rb') as f:
		return pickle.load(f)
	#
#
def read_relay_throughput(filename):
	with open(filename, 'r') as f:
		header = f.readline()
		data_unprocessed = [[float(x) for x in line.split(',')] for line in f.readlines()]
		data_unprocessed = np.array(data_unprocessed)
	#
	data = {}
	data['timestamps'] = data_unprocessed[:,0]
	data['threads'] = data_unprocessed[:,1:]
	#
	return (header, data)
#
def normalize_relay_throughput(data):
	time_deltas = data['timestamps'][1:]-data['timestamps'][:-1]
	normalized_data = {}
	normalized_data['timestamps'] = np.copy(data['timestamps'][:-1])
	normalized_data['threads'] = data['threads'][:-1,:]/(time_deltas[:,None])
	return normalized_data
#