1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
|
#! /usr/bin/python
import sys
import numpy as np
import matplotlib.pyplot as plt
log_filename = sys.argv[1]
nums,accuracy = np.loadtxt(log_filename,comments=";",delimiter='#',unpack=True,usecols=(0,2))
nums_unique = np.unique(nums)
means = []
mins = []
maxs = []
for i in nums_unique:
filtered = accuracy[nums==i]
mean = np.mean(filtered)
min_value = min(filtered)
max_value = max(filtered)
var = np.var(filtered)
means += [mean]
mins += [mean-min_value]
maxs += [max_value-mean]
print ",".join(map(str,[int(i),mean,min_value,max_value,var]))
x = map(int,list(nums_unique))
axes = plt.subplot(111)
axes.set_xlabel("Group size")
axes.set_ylabel("Accuracy")
a = axes.set_xlim((0,22))
axes.set_ylim((0,100))
axes.set_xticks(x)
plt.errorbar(x,means,yerr=[mins,maxs],linestyle="-",marker="o",ecolor="gray")
plt.savefig("test.png")
|
