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
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from numpy import *
import time
import matplotlib
matplotlib.rcParams['backend'] = 'Agg'
matplotlib.rc('font', size='10')
matplotlib.rc('text', usetex=True)
from matplotlib.pyplot import *
import os
from pygolem_lite.modules import list2array,save_adv,saveconst,load_adv
from pygolem_lite import Shot
LineCount=40000;
TriggerLine=3500;
DeltaTs=1e-6;#[s]
Stab_S_Eff=0.08601;#[m^2]
Mirnov_S_Eff=0.003705;#[m^2]
MirnovPosition=93;#[mm]
MirnovPosition_m=0.093;#[m]
R0=0.4;#m
mu0=0.000001256;
a_limiter=0.085;
a_L=0.085;
def narovnani(field):
aver2 = mean(field[32000:32000+TriggerLine])
field[5000:32000]-= (arange(5000,32000)-5000)*aver2/(32000-5000)
field[32000:]-= aver2
return field
def integrace_mc(field):
#print "====", field, TriggerLine
aver = mean(field[:TriggerLine,:],axis = 0)
integr = cumsum(field-aver, axis = 0, out = field)*DeltaTs/Mirnov_S_Eff
return integr
def integrace_bz(field):
aver = mean(field[:TriggerLine,...],axis = 0)
integr = cumsum(field-aver,axis = 0, out = field)*DeltaTs/Stab_S_Eff
return integr
def load_etalons(Ub_limit,Ust_limit):
path = 'Ub'+str(Ub_limit)+'_Ust'+str(Ust_limit)+'_no-plasma'
try:
tvec,etalon = load_adv('./etalon/'+path)
except:
print 'cant open '+path+' etalon'
saveconst('no_etalon', 0)
exit()
return etalon
def load_pygolem():
Data = Shot()
time.sleep(2) # stupid bug fix with loading of nonsaved file
gd = Data.get_data
das, m1 = gd('any', 'mirnov_1', return_channel = True)
das, m5 = gd('any', 'mirnov_5', return_channel = True)
das, m9 = gd('any', 'mirnov_9', return_channel = True)
das, m13 = gd('any', 'mirnov_13', return_channel = True)
mc = list2array( Data[das, [m1, m5, m9, m13]][1] )
Ip = array(Data['plasma_current'], copy = False)[1,:].T
try:
Bz = list2array( Data[das, 5][1] )
except:
Bz = zeros(LineCount)
Ub_limit = int(Data['ub'])
Ust_limit = int(Data['ust'])
plasma = Data['plasma']
#Ub_limit = 600#BUG
#Ust_limit = 0
return mc,Bz,Ip,Ust_limit,Ub_limit
def plot_graphs():
mc,Bz,Ip,Stlim,Btlim = load_pygolem()
#print mc,Bz,Ip,Stlim,Btlim
mc = integrace_mc(mc)
Bz = integrace_bz(Bz)
mc = mc[:LineCount,:]
Bz = Bz[:LineCount]
#remove crosstalks
for i in range(4):
mc[:,i] = narovnani(mc[:,i])
etalon = load_etalons(Btlim,Stlim)
mc-= etalon[:,:4] #time mc1 mc5 mc9 mc13 bz
Bz-= etalon[:,-1]
#make calculations
disZ = MirnovPosition*(mc[:,1]-mc[:,3])/(abs(mc[:,1]+mc[:,3]))
disR = MirnovPosition*(mc[:,0]-mc[:,2])/(abs(mc[:,0]+mc[:,2]))
B0 = (mu0*Ip)/(2*pi*MirnovPosition_m)
Lambda = ((mc[:,2]-mc[:,0])/2 - Bz)*(R0/(B0*MirnovPosition_m))-log(MirnovPosition_m/a_L)+1
disR_upgrade=(mc[:,2]-mc[:,0])*MirnovPosition_m/(2*B0)-0.5*(log(MirnovPosition_m/a_L)-1+(Lambda-0.5)*(1+(MirnovPosition_m/a_L)**2))*MirnovPosition_m**2/R0*1000
disR_upgrade[Ip < 50] = 0
disR[Ip < 50] = 0
disZ[Ip < 50] = 0
#plot graphs
tvec = arange(LineCount)*DeltaTs*1000
class MyFormatter(ScalarFormatter):
def __call__(self, x, pos=None):
if pos==0:
return ''
else: return ScalarFormatter.__call__(self, x, pos)
fig = figure(num=None, figsize=(10, 10), dpi=80, facecolor='w', edgecolor='k')
subplots_adjust(hspace=0, wspace = 0)
for i in arange(4):
ax = fig.add_subplot(5,1,i+1)
ax.xaxis.set_major_formatter( NullFormatter() )
ax.yaxis.set_major_formatter( MyFormatter() )
plot(tvec,1000*mc[:,i], label = 'clear signal')
plot(tvec,1000*etalon[:,i+1], label = 'toroidal field')
plot(tvec,1000*(mc[:,i]+etalon[:,i+1]), label = 'signal with toroidal field')
axhline(y = 0, linestyle = '--')
leg = legend(loc='upper left', fancybox=True)
leg.get_frame().set_alpha(0.8)
ylabel('mc'+str(i*4+1)+' B [mT]')
ax.xaxis.set_major_formatter( ScalarFormatter() )
ax.yaxis.set_major_formatter( ScalarFormatter() )
xlabel('t [ms]')
savefig('./mc.png',bbox_inches='tight')
close()
fig = figure(num=None, figsize=(10, 3), dpi=80, facecolor='w', edgecolor='k')
plot(tvec,-disZ, label = 'disZ')
plot(tvec,-disR, label = 'disR')
plot(tvec,-disR_upgrade, label = 'disR upgrade')
axhline(y = a_L*1000,linestyle = '--',color = 'g')
axhline(y = -a_L*1000,linestyle = '--',color = 'g')
ylim(-100, 100)
xlim(6, 23)
ylabel('R,Z [mm]')
xlabel('t [ms]')
leg = legend( loc='upper right', fancybox=True)
leg.get_frame().set_alpha(0.8)
savefig('./position.png',bbox_inches='tight')
close()
os.system('convert -resize 150x120\! position.png icon.png')
def main():
plot_graphs()
saveconst('status', 0)
if __name__ == "__main__":
main()
|
