lhlmgr

#source: https://github.com/ericjang/normalizing-flows-tutorial/blob/master/nf_part1_intro.ipynb

import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import tensorflow_probability as tfp
import tensorflow.contrib.eager as tfe
import time

tf.enable_eager_execution()

lhlmgr

def plot_mva():
    # values max throughput
    num_cliens = [12, 24, 30, 60, 90, 105]
    respt = [2.7314, 5.159, 6.2694, 10.1468, 17.0647, 19.718]
    tp = [ 0.9203, 1.9648, 2.271, 3.4444, 3.7277, 3.9695]

    #values scalability client
    tp2 = [662.3,     1272.4688 , 2175.675 ,  2485.525 ,  2857.2188  ,3005.2937 , 3334.4062]
    rt2 = [  1.9611 ,  2.3867 ,  3.9672  , 5.0036  , 5.5203  , 6.9196 , 10.8498]
    num_cliens2 = [6, 12, 24, 30, 36, 42, 60]