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import matplotlib.pyplot as plt

import numpy as np

import matplotlib.mlab as mlab

import matplotlib.gridspec as gridspec

# Fixing random state for reproducibility

costs = [5326, 1608, 920]

plt.subplot(131)

x = np.arange(3)

#plt.plot(costs, label='v1 (OpenMP)', color='black')

plt.bar(x, costs)

plt.title('Development Cost', fontsize=22)

plt.xlabel('task model', fontsize=18)

plt.ylabel('$USD', fontsize=16)

plt.xticks(x, ('OpenMP', 'TBB', 'Cpp-Taskflow'))

plt.legend()

# Fixing random state for reproducibility

raw = [line.strip() for line in open("graph_algorithm.txt")]

graph_sizes = []

omp_runtimes = []

tbb_runtimes = []

ctf_runtimes = []

# extract the output data

i = 0

for line in raw:

token = line.split();

assert(len(token) == 4)

graph_sizes.append(int(token[0]))

omp_runtimes.append(float(token[1]))

tbb_runtimes.append(float(token[2]))

ctf_runtimes.append(float(token[3]))

i = i+1

plt.subplot(132)

plt.plot(graph_sizes, omp_runtimes, label='OpenMP')

plt.plot(graph_sizes, tbb_runtimes, label='TBB')

plt.plot(graph_sizes, ctf_runtimes, label='Cpp-Taskflow')

plt.title('Graph Algorithm', fontsize=22)

plt.xlabel('graph size (|V|+|E| ~ # tasks)', fontsize=18)

plt.ylabel('cpu runtime (ms)', fontsize=16)

#plt.xticks(np.arange(len(graph_sizes)), graph_sizes)

plt.legend(fontsize=16)

# Fixing random state for reproducibility

raw = [line.strip() for line in open("matrix_operation.txt")]

graph_sizes = []

omp_runtimes = []

tbb_runtimes = []

ctf_runtimes = []

# extract the output data

i = 0

for line in raw:

token = line.split();

assert(len(token) == 4)

graph_sizes.append(int(token[0]))

omp_runtimes.append(float(token[1]))

tbb_runtimes.append(float(token[2]))

ctf_runtimes.append(float(token[3]))

i = i+1

plt.subplot(133)

plt.plot(graph_sizes, omp_runtimes, label='OpenMP')

plt.plot(graph_sizes, tbb_runtimes, label='TBB')

plt.plot(graph_sizes, ctf_runtimes, label='Cpp-Taskflow')

plt.title('Matrix Operation', fontsize=22)

plt.xlabel('partition count (# tasks)', fontsize=18)

plt.ylabel('cpu runtime (ms)', fontsize=16)

#plt.xticks(np.arange(len(graph_sizes)), graph_sizes)

plt.legend(fontsize=16)

plt.show()