-
Notifications
You must be signed in to change notification settings - Fork 301
/
plot_variance_mpl.py
72 lines (53 loc) · 1.84 KB
/
plot_variance_mpl.py
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
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
import glob
from pylab import *
# import colors
from palettable.colorbrewer.qualitative import Set2_7
colors = Set2_7.mpl_colors
params = {
'axes.labelsize': 8,
'font.size': 8,
'legend.fontsize': 10,
'xtick.labelsize': 10,
'ytick.labelsize': 10,
'text.usetex': False,
'figure.figsize': [4.5, 4.5]
}
rcParams.update(params)
def load(dir):
f_list = glob.glob(dir + '/*/*/bestfit.dat')
num_lines = sum(1 for line in open(f_list[0]))
i = 0
data = np.zeros((len(f_list), num_lines))
for f in f_list:
data[i, :] = np.loadtxt(f)[:, 1]
i += 1
return data
def perc(data):
median = np.zeros(data.shape[1])
perc_25 = np.zeros(data.shape[1])
perc_75 = np.zeros(data.shape[1])
for i in range(0, len(median)):
median[i] = np.median(data[:, i])
perc_25[i] = np.percentile(data[:, i], 25)
perc_75[i] = np.percentile(data[:, i], 75)
return median, perc_25, perc_75
data_low_mut = load('data/low_mut')
data_high_mut = load('data/high_mut')
n_generations = data_low_mut.shape[1]
x = np.arange(0, n_generations)
med_low_mut, perc_25_low_mut, perc_75_low_mut = perc(data_low_mut)
med_high_mut, perc_25_high_mut, perc_75_high_mut = perc(data_high_mut)
axes(frameon=0)
grid(axis='y', color="0.9", linestyle='-', linewidth=1)
fill_between(x, perc_25_low_mut, perc_75_low_mut, alpha=0.25, linewidth=0, color=colors[0])
fill_between(x, perc_25_high_mut, perc_75_high_mut, alpha=0.25, linewidth=0, color=colors[1])
plot(x, med_low_mut, linewidth=2, color=colors[0])
plot(x, med_high_mut, linewidth=2, linestyle='--', color=colors[1])
xlim(-5, 400)
ylim(-5000, 300)
xticks(np.arange(0, 500, 100))
legend = legend(["Low mutation rate", "High Mutation rate"], loc=4)
frame = legend.get_frame()
frame.set_facecolor('1.0')
frame.set_edgecolor('1.0')
savefig('variance_colors.png')