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import toolshed as ts
lookup = {'ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites': '1000G',
'ExAC.r0.3.sites.vep': 'ExAC'}
data = {'1000G': [], 'ExAC': []}
"""
method procs time query
var 20 888.29 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
var 19 897.02 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
var 18 895.35 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
var 17 909.24 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
var 16 916.43 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
var 15 945.61 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
var 14 981.14 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
var 13 1051.26 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
var 12 1126.58 seconds ALL.wgs.phase3_shapeit2_mvncall_integrated_v5a.20130502.sites
"""
for d in ts.reader(1):
time = float(d['time'].split()[0])
key = lookup[d['query']]
data[key].append(time)
for k in data:
data[k] = data[k][::-1]
from matplotlib import pyplot as plt
import seaborn as sns
sns.set_style('white')
from matplotlib import rcParams
rcParams['font.family'] = 'Arial'
rcParams['font.size'] = 18
N = len(data.values()[0])
N = 16
markers = 'os'
for j, k in enumerate(data):
values = data[k]
plt.plot(range(1, N + 1), [values[0] / values[i] for i in range(N)],
markers[j] + "-", label=k)
plt.ylabel("Speed-up relative to 1 process")
plt.xlabel("Number of processes")
plt.plot(range(1, N + 1), [i for i in range(1, N + 1)], '--',
c="0.78", lw=2)
plt.tight_layout()
plt.legend(loc="upper left")
ax = plt.gca()
for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] +
ax.get_xticklabels() + ax.get_yticklabels()):
item.set_fontsize(16)
for item in ax.get_legend().get_texts():
item.set_fontsize(13)
plt.xlim(xmin=1, xmax=N+0.16)
plt.ylim(ymin=1, ymax=8)
sns.despine(left=True, bottom=True)
plt.savefig('figure-4.pdf')
plt.show()
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