|
commit | author | age
|
|
8c3c29
|
1 |
#!/usr/bin/python3 |
| SP |
2 |
from trisurf import tsmgr |
|
3 |
from trisurf import trisurf |
|
4 |
from trisurf import statistics |
|
5 |
|
|
6 |
print("Running trisurf version "+ tsmgr.getTrisurfVersion()) |
|
7 |
Runs=[] |
|
8 |
Nshell=25 |
|
9 |
|
|
10 |
#--------- F = 0 ------------ |
|
11 |
#kapa_list=[10,20,30,40,50] |
|
12 |
#p=[5,10,15,20,25] |
|
13 |
|
|
14 |
#N=5*Nshell**2+2 |
|
15 |
#Nc_list=[int(N*pp/100) for pp in p] |
|
16 |
|
|
17 |
#for kapa in kapa_list: |
|
18 |
# for Nc in Nc_list: |
|
19 |
# run=trisurf.Runner(tape='tape_Nc'+str(Nc)+'_k'+str(kapa)) |
|
20 |
# run.setMaindir(("N", "k", "V", "_Nc", "_c","_w"), ("nshell","xk0","constvolswitch","number_of_vertices_with_c0","c0", "w")) |
|
21 |
# run.setSubdir("run0") |
|
22 |
# Runs.append(run) |
|
23 |
|
|
24 |
#---------------------------- |
|
25 |
#--------- F = 0 ------------ |
|
26 |
kapa_list=[15,16,17,18,19,20,21,22] |
|
27 |
#p=[5,7.5,10,12.5] |
|
28 |
p=[8,8.5,9,9.5,10.5,11,11.5,12] |
|
29 |
|
|
30 |
N=5*Nshell**2+2 |
|
31 |
Nc_list=[int(N*pp/100) for pp in p] |
|
32 |
#print(Nc_list) |
|
33 |
|
|
34 |
#spremenil sem, ker nimam vseh podatkov!!! |
|
35 |
kapa_list=[15,16,18,19,20,21,21,22] |
|
36 |
Nc_list=[156,234,312,390] |
|
37 |
|
|
38 |
for kapa in kapa_list: |
|
39 |
for Nc in Nc_list: |
|
40 |
#print('tape_Nc'+str(Nc)+'_k'+str(kapa)) |
|
41 |
run=trisurf.Runner(tape='tape_Nc'+str(Nc)+'_k'+str(kapa)) |
|
42 |
run.setMaindir(("N", "k", "V", "_Nc", "_c","_w"), ("nshell","xk0","constvolswitch","number_of_vertices_with_c0","c0", "w")) |
|
43 |
run.setSubdir("run0") |
|
44 |
Runs.append(run) |
|
45 |
|
|
46 |
#---------------------------- |
|
47 |
|
|
48 |
#kapa_list=[20,30] |
|
49 |
#p=[10] |
|
50 |
# |
|
51 |
#N=5*Nshell**2+2 |
|
52 |
#Nc_list=[int(N*pp/100) for pp in p] |
|
53 |
# |
|
54 |
#for kapa in kapa_list: |
|
55 |
# for Nc in Nc_list: |
|
56 |
# run=trisurf.Runner(snapshot='is_from_N25k'+str(kapa)+'V0_Nc312_c1.0.vtu') |
|
57 |
# run.setMaindir(("N", "k", "V", "_Nc", "_c","_w","_F"), ("nshell","xk0","constvolswitch","number_of_vertices_with_c0","c0", "w","F")) |
|
58 |
# run.setSubdir("run0") |
|
59 |
# |
|
60 |
# Runs.append(run) |
|
61 |
|
|
62 |
#---------------------------- |
|
63 |
|
|
64 |
|
|
65 |
|
|
66 |
#Nov format: |
|
67 |
#hosts=({'name':'Hestia','address':'127.0.0.1', 'runs':Runs, 'username':'samo'},) |
|
68 |
|
|
69 |
def analyze(run, **kwargs): |
|
70 |
host=kwargs.get('host', None) |
|
71 |
print("Demo analysis") |
|
72 |
print("Analysis on host "+host['name']+" for run "+run.Dir.fullpath()+" completed") |
|
1c8250
|
73 |
print("here comes info on the run variable:") |
| SP |
74 |
print(run) |
|
75 |
print("here comes info on the host variable:") |
|
76 |
print(host) |
|
77 |
print("here comes info on the args variable:") |
|
78 |
print(kwargs.get('args',None)) |
|
8c3c29
|
79 |
|
| SP |
80 |
def plothbar(run, **kwargs): |
|
81 |
import matplotlib.pyplot as plt |
|
82 |
|
|
83 |
def smooth(y, box_pts): |
|
84 |
import numpy as np |
|
85 |
box = np.ones(box_pts)/box_pts |
|
86 |
y_smooth = np.convolve(y, box, mode='same') |
|
87 |
return y_smooth |
|
88 |
table=trisurf.Statistics(run.Dir.fullpath(),filename='data_tspoststat.csv').getTable() |
|
89 |
plt.plot(table['hbar'], '.') |
|
90 |
plt.title(run.Dir.fullpath()) |
|
91 |
plt.xlabel('Iteration') |
|
92 |
plt.ylabel('hbar') |
|
93 |
smooth_window=10 |
|
94 |
smoothed=smooth(table['hbar'],smooth_window) |
|
95 |
plt.plot(tuple(range(int(smooth_window/2),len(smoothed)-int(smooth_window/2))),smoothed[int(smooth_window/2):-int(smooth_window/2)]) |
|
96 |
plt.show() |
|
97 |
print |
|
98 |
#if return False or no return statement, the analysis will continue with next running instance in the list. if return True, the analysis will stop after this run. |
|
99 |
return False |
|
100 |
|
|
5f0a35
|
101 |
def plotrunningavginteractive(run, **kwargs): |
|
8c3c29
|
102 |
import matplotlib.pyplot as plt |
|
5f0a35
|
103 |
from trisurf import VTKRendering as vtk |
| SP |
104 |
import math |
|
8c3c29
|
105 |
table=trisurf.Statistics(run.Dir.fullpath(),filename='data_tspoststat.csv').getTable() |
| SP |
106 |
def running_avg(col): |
|
107 |
import numpy as np |
|
108 |
avg=[] |
|
109 |
for i in range(0,len(col)): |
|
110 |
avg.append(np.average(col[:-i])) |
|
111 |
return avg |
|
5f0a35
|
112 |
fig=plt.figure(1) |
|
8c3c29
|
113 |
ra=running_avg(table['hbar']) |
| SP |
114 |
plt.plot(ra) |
|
115 |
plt.title('Running average') |
|
116 |
plt.ylabel('1/n sum_i=niter^n(hbar_i)') |
|
117 |
plt.xlabel('n') |
|
5f0a35
|
118 |
def onclick(event): |
| SP |
119 |
print('button=%d, x=%d, y=%d, xdata=%f, ydata=%f' % (event.button, event.x, event.y, event.xdata, event.ydata)) |
|
120 |
vtk.Renderer(kwargs.get('args', None),kwargs.get('host',None),run, math.floor(event.xdata)) |
|
121 |
cid = fig.canvas.mpl_connect('button_press_event', onclick) |
|
8c3c29
|
122 |
plt.show() |
|
5f0a35
|
123 |
plt.close(1) |
|
8c3c29
|
124 |
#start manager with configured runs |
|
5f0a35
|
125 |
tsmgr.start(Runs, analyses={'analyze1':analyze, 'plotrunningavg':plotrunningavginteractive, 'plothbar':plothbar}) |
|
8c3c29
|
126 |
|
| SP |
127 |
#statistics.combine(Runs) |
|
128 |
#statistics.combine([Runs[1],Runs[2]]) |
