-
Notifications
You must be signed in to change notification settings - Fork 0
/
visualization_2dn2d.py
460 lines (416 loc) · 16.3 KB
/
visualization_2dn2d.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
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
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
import numpy as np
import math
import os
import xarray as xr
import sys
import matplotlib.pyplot as plt
import warnings
from datetime import timedelta
from matplotlib.animation import FuncAnimation
from matplotlib.animation import FFMpegWriter
warnings.filterwarnings("ignore")
###############################################################################
### Parameters
###############################################################################
#------ CHOOSE (Note: the same values must also be placed in the Kooi kernel: lines 53 and 54) -----
rho_pl = "920" # density of plastic (kg m-3): DEFAULT FOR FIG 1: 920 but full range is: 840, 920, 940, 1050, 1380 (last 2 are initially non-buoyant)
r_pl = "1e-04" # radius of plastic (m): DEFAULT FOR FIG 1: 10-3 to 10-6 included but full range is: 10 mm to 0.1 um or 10-2 to 10-7
lon = np.array([-161,-159]) #lon release locations
lat = np.array([35,37]) #lat release locations
simdays = 150 #number of days running the sim
secsdt = 60 #timestep of sim
time0 = 0
secsoutdt = 60*60 # seconds in an hour (must be in hours due to algal pickle profiles being hours)
total_secs = secsoutdt*24.*simdays - secsoutdt # total time (in seconds) being run for the sim
dt_secs = total_secs/secsoutdt # time steps
rho_bf = 1388. # density of biofilm ([g m-3]
rho_fr = 2600. # density of frustule [g m-3], Amaral-Zettler, L.A. et al. 2021
v_a = 2.0E-16
r_a = ((3./4.)*(v_a/math.pi))**(1./3.) # radius of algae [m]
r_cy = 59./60. * r_a # radius of cytosplasm [m]
v_cy = (4./3.)*math.pi*r_cy**3. # volume of cytoplasm [m3]
v_fr = v_a - v_cy # volume of frustule [m3]
EZD = -28
a_diss_rate = ''
dead = True
if dead:
death = '_death_'
a_diss_rate = 2.5e-4
else:
death = ''
#%%
###############################################################################
### Visualization
###############################################################################
# load the data
path = '/Users/renjiongqiu/Biofouling-SOAC/outputs/'
fname = 'Kooi1D_'+str(round(simdays,2))+'d_rho'+rho_pl+'_rpl'+r_pl+'_rhofr'+str(int(rho_fr))
ds = xr.open_dataset(path+fname+'.nc')
print(fname)
AR = {}
AR['z'] = np.array(ds.z[:,:])
AR['aa'] = np.array(ds.aa[:,:]) * (v_a*rho_bf)
AR['time'] = np.array(ds.time[:,:])
AR['vs'] = np.array(ds.vs[:,:])
AR['a'] = np.array(ds.a[:,:]) * (v_a*rho_bf)
AR['a_dead'] = np.array(ds.a_dead[:,:]) * (v_fr*rho_fr)
AR['a_diss'] = np.array(ds.a_diss[:,:])
AR['a_mort'] = np.array(ds.a_mort[:,:])
AR['a_resp'] = np.array(ds.a_resp[:,:])
AR['a_coll'] = np.array(ds.a_coll[:,:])
AR['a_growth'] = np.array(ds.a_growth[:,:])
AR['rho_tot']= np.array(ds.rho_tot[:,:])
AR['rho_sw']= np.array(ds.rho_sw[:,:])
therange = range(2401,3601)
# therange = range(1,len(AR['z'][0,:3601]))
t = AR['time'][0,therange].astype('timedelta64[h]')
dt = 5 # days
tplt = np.arange(t[0].astype(int),t[-1].astype(int)+24*dt,24*dt).astype('float32')
tticks = np.arange(t[0].astype('timedelta64[D]').astype(int),t[-1].astype('timedelta64[D]').astype(int)+dt,dt).astype(int)
zplt = -AR['z'][0,therange]
# t = AR['time'][0,therange]
a_dead = AR['a_dead'][0,therange]
a_diss = AR['a_diss'][0,therange]
a_mort = AR['a_mort'][0,therange]
a_resp = AR['a_resp'][0,therange]
a_coll = AR['a_coll'][0,therange]
a_growth = AR['a_growth'][0,therange]
rho = AR['rho_tot'][0,therange]
rhosw = AR['rho_sw'][0,therange]
a = AR['a'][0,therange]
#%%
fname = 'Kooi1D_'+str(round(simdays,2))+'d_rho'+rho_pl+'_rpl'+r_pl+'_death_'+str(a_diss_rate)+'_rhofr'+str(int(rho_fr))
ds = xr.open_dataset(path+fname+'.nc')
print(fname)
AR = {}
AR['z'] = np.array(ds.z[:,:])
AR['aa'] = np.array(ds.aa[:,:]) * (v_a*rho_bf)
AR['time'] = np.array(ds.time[:,:])
AR['vs'] = np.array(ds.vs[:,:])
AR['a'] = np.array(ds.a[:,:]) * (v_a*rho_bf)
AR['a_dead'] = np.array(ds.a_dead[:,:]) * (v_fr*rho_fr)
AR['a_diss'] = np.array(ds.a_diss[:,:])
AR['a_mort'] = np.array(ds.a_mort[:,:])
AR['a_resp'] = np.array(ds.a_resp[:,:])
AR['a_coll'] = np.array(ds.a_coll[:,:])
AR['a_growth'] = np.array(ds.a_growth[:,:])
AR['rho_tot']= np.array(ds.rho_tot[:,:])
AR['rho_sw']= np.array(ds.rho_sw[:,:])
# therange = range(700,1000)
# therange = range(0,len(AR['z'][0,:]))
zplt_2d = -AR['z'][0,therange]
a_dead_2d = AR['a_dead'][0,therange]
a_diss_2d = AR['a_diss'][0,therange]
a_mort_2d = AR['a_mort'][0,therange]
a_resp_2d = AR['a_resp'][0,therange]
a_coll_2d = AR['a_coll'][0,therange]
a_growth_2d = AR['a_growth'][0,therange]
rho_2d = AR['rho_tot'][0,therange]
rhosw_2d = AR['rho_sw'][0,therange]
a_2d = AR['a'][0,therange]
#%% Fig. 1
day0 = tticks[0]
dayz = tticks[-1]
fig,ax = plt.subplots(1,1,figsize=(16,12))
ax.plot(t,zplt,label='Vertical trajectory - No dead',c='tab:blue')
ax.plot(t,zplt_2d,label='Vertical trajectory - With dead',c='tab:red',alpha=1.)
ax.grid(which='major')
ax.set_ylim([-140,2])
ax.set_ylabel('Depth [m]',fontsize=20)
ax.legend(loc='upper left',fontsize=16)
ax.set_title(f'1D trajectories and total density changes from day {day0} to {dayz}',fontsize=24,fontweight='bold')
ax.set_xlabel('Time [d]',fontsize=20)
ax.set_xlim([t[0].astype(int),t[-1].astype(int)+1])
ax.set_xticks(tplt, labels=tticks,fontsize=16)
# ax[0].axhline(y=EZD,c='gray')
ax.set_yticks(np.arange(-60,1,10),fontsize=16)
ax.tick_params('both',labelsize=14)
ax2 = ax.twinx()
ax2.plot(t,rho,label='Total density - No dead',c='tab:blue')
ax2.plot(t,rho_2d,label='Total density - With dead',c='tab:red',alpha=1.)
ax2.plot(t,rhosw,c='k',label='Sea water density')
# ax2.set_ylim([1000,1080]) # rho_pl = 1000
ax2.set_ylim([920,1200])
ax2.legend(loc='lower left',fontsize=16)
ax2.set_yticks(np.arange(920,1061,20),fontsize=16)
ax2.set_ylabel('Total density [$kg\cdot m^{-3}$]',fontsize=20)
ax2.tick_params('both',labelsize=16)
ax2.grid()
# plt.savefig('sens_diss1.pdf')
#%% Fig. 1 - Animation
t_data = []
zplt_2d_data = []
rho_2d_data = []
zplt_data = []
rho_data = []
fig,ax = plt.subplots(1,1,figsize=(16,12))
line1z, = ax.plot(t,zplt,label='Vertical trajectory - No dead',c='tab:blue')
line0z, = ax.plot(t,zplt_2d,label='Vertical trajectory - With dead',c='tab:red')
ax.grid(which='major')
ax.set_ylim([-140,2])
ax.set_ylabel('Depth [m]',fontsize=20)
ax.legend(loc='upper left',fontsize=16)
ax.set_title('1D trajectories and total density changes from day 100 to 150',fontsize=24,fontweight='bold')
ax.set_xlabel('Time [d]',fontsize=20)
# ax.set_xlim([t[0].astype(int),t[-1].astype(int)+1])
ax.set_xticks(tplt, labels=tticks,fontsize=16)
# ax[0].axhline(y=EZD,c='gray')
ax.set_yticks(np.arange(-60,1,10),fontsize=16)
ax.tick_params('both',labelsize=16)
ax2 = ax.twinx()
line0r, = ax2.plot(t,rho_2d,label='Total density - With dead',c='tab:red')
line1r, = ax2.plot(t,rho,label='Total density - No dead',c='tab:blue')
ax2.plot(t,rhosw,c='k',label='Sea water density')
ax2.set_ylim([920,1200])
ax2.legend(loc='lower left',fontsize=16)
ax2.set_yticks(np.arange(920,1061,20),fontsize=16)
ax2.set_ylabel('Total density [$kg\cdot m^{-3}$]',fontsize=20)
ax2.tick_params('both',labelsize=16)
ax2.grid()
def animate(i):
t_data.append(t[i])
zplt_2d_data.append(zplt_2d[i])
rho_2d_data.append(rho_2d[i])
zplt_data.append(zplt[i])
rho_data.append(rho[i])
line0z.set_data(t_data,zplt_2d_data)
line0r.set_data(t_data,rho_2d_data)
line1z.set_data(t_data,zplt_data)
line1r.set_data(t_data,rho_data)
# scatter0.set_offsets(np.c_[t[i].astype(int),zplt_2d[i]])
return line0z,line0r,line1z,line1r,
anim = FuncAnimation(fig, animate, frames=len(t), interval=10)
anim.save('anim1_zVSrho.gif', writer='imagemagick', fps=15)
#%% Fig. 1 - Other option 1
day0 = tticks[0]
dayz = tticks[-1]
fig,ax = plt.subplots(1,2,figsize=(32,12))
ax[0].plot(t,zplt,label='Vertical trajectory',c='tab:blue')
# ax[0].plot(t,zplt_2d,label='Vertical trajectory - With dead',c='tab:red',alpha=1.)
ax[0].grid(which='major')
ax[0].set_ylim([-140,2])
ax[0].set_ylabel('Depth [m]',fontsize=28)
ax[0].legend(loc='upper left',fontsize=28)
ax[0].set_title('No dead situation', fontsize=36)
ax[0].set_xlabel('Time [d]',fontsize=28)
ax[0].set_xlim([t[0].astype(int),t[-1].astype(int)+1])
ax[0].set_xticks(tplt, labels=tticks,fontsize=24)
# ax[0].axhline(y=EZD,c='gray')
ax[0].set_yticks(np.arange(-60,1,10),fontsize=24)
ax[0].tick_params('both',labelsize=22)
ax2 = ax[0].twinx()
ax2.plot(t,rho,label='Total density',c='tab:blue')
# ax2.plot(t,rho_2d,label='Total density - With dead',c='tab:red',alpha=1.)
ax2.plot(t,rhosw,c='k',label='Sea water density')
# ax2.set_ylim([1000,1080]) # rho_pl = 1000
ax2.set_ylim([920,1200])
ax2.legend(loc='lower left',fontsize=28)
ax2.set_yticks(np.arange(920,1061,20),fontsize=24)
# ax2.set_ylabel('Total density [$kg\cdot m^{-3}$]',fontsize=28)
ax2.tick_params('both',labelsize=22)
ax2.grid()
# ax[1].plot(t,zplt,label='Vertical trajectory - No dead',c='tab:blue')
ax[1].plot(t,zplt_2d,label='Vertical trajectory',c='tab:red',alpha=1.)
ax[1].grid(which='major')
ax[1].set_ylim([-140,2])
# ax[1].set_ylabel('Depth [m]',fontsize=28)
ax[1].legend(loc='upper left',fontsize=28)
ax[1].set_title('With dead situation', fontsize=36)
ax[1].set_xlabel('Time [d]',fontsize=28)
ax[1].set_xlim([t[0].astype(int),t[-1].astype(int)+1])
ax[1].set_xticks(tplt, labels=tticks,fontsize=24)
# ax[0].axhline(y=EZD,c='gray')
ax[1].set_yticks(np.arange(-60,1,10),fontsize=24)
ax[1].tick_params('both',labelsize=22)
ax2 = ax[1].twinx()
# ax2.plot(t,rho,label='Total density - No dead',c='tab:blue')
ax2.plot(t,rho_2d,label='Total density',c='tab:red',alpha=1.)
ax2.plot(t,rhosw,c='k',label='Sea water density')
# ax2.set_ylim([1000,1080]) # rho_pl = 1000
ax2.set_ylim([920,1200])
ax2.legend(loc='lower left',fontsize=28)
ax2.set_yticks(np.arange(920,1061,20),fontsize=24)
ax2.set_ylabel('Total density [$kg\cdot m^{-3}$]',fontsize=28)
ax2.tick_params('both',labelsize=22)
ax2.grid()
plt.text(0.95,0.95,'(a)',ha='center',va='center',fontsize=40,transform=ax[0].transAxes)
plt.text(0.95,0.95,'(b)',ha='center',va='center',fontsize=40,transform=ax[1].transAxes)
# plt.suptitle(f'1D trajectories and total density changes from day {day0} to {dayz}',fontsize=24,fontweight='bold',position=(0.5,0.92))
# plt.tight_layout(w_pad=0.)
plt.savefig('fig_1_oscillation.pdf')
#%% Fig. 1 - Other option 2
fig,ax = plt.subplots(2,1,figsize=(18,24))
# Dead
# ax[0].plot(t,zplt,label='No death')
ax[0].plot(t,zplt_2d,label='Vertical trajectory')
ax[0].grid(which='major')
ax[0].set_ylim([-140,2])
ax[0].set_ylabel('depth [m]',fontsize=14)
ax[0].legend(loc='upper left')
ax[0].set_title('With dead situation',fontsize=16)
ax[0].set_xlabel('time [d]',fontsize=14)
ax[0].set_xlim([t[0].astype(int),t[-1].astype(int)+1])
ax[0].set_xticks(tplt, labels=tticks)
# ax[0].axhline(y=EZD,c='gray')
ax[0].set_yticks(np.arange(-60,1,10))
ax2 = ax[0].twinx()
ax2.plot(t,rho_2d,c='tab:orange',label='Total density')
ax2.plot(t,rhosw_2d,c='gray')
ax2.set_ylim([920,1200])
ax2.legend(loc='lower left')
ax2.set_yticks(np.arange(920,1061,20))
ax2.grid()
# No Dead
ax[1].plot(t,zplt,label='Vertical trajectory')
# ax[0].plot(t,zplt_2d,label='With death')
ax[1].grid(which='major')
ax[1].set_ylim([-140,2])
ax[1].set_ylabel('depth [m]',fontsize=14)
ax[1].legend(loc='upper left')
ax[1].set_title('No dead situation',fontsize=16)
ax[1].set_xlabel('time [d]',fontsize=14)
ax[1].set_xticks(tplt, labels=tticks)
ax[1].set_xlim([t[0].astype(int),t[-1].astype(int)+1])
ax[1].axhline(y=EZD,c='gray')
ax[1].set_yticks(np.arange(-60,1,10))
ax2 = ax[1].twinx()
ax2.plot(t,rho,c='tab:orange',label='Total density')
ax2.plot(t,rhosw,c='gray')
ax2.set_ylim([920,1200])
ax2.legend(loc='lower left')
ax2.set_yticks(np.arange(920,1061,20))
ax2.grid()
# plt.savefig('test.pdf')
#%% Fig. 1 - Animation (other option)
# animdt = timedelta(days=1)
fig,ax = plt.subplots(2,1,figsize=(18,24))
t_data = []
zplt_2d_data = []
rho_2d_data = []
zplt_data = []
rho_data = []
# Dead
# ax[0].plot(t,zplt,label='No death')
line0z, = ax[0].plot(t[0],zplt_2d[0],label='Vertical trajectory',c='tab:red')
# scatter0 = ax[0].scatter(t[0].astype(int),zplt_2d[0])
ax[0].grid(which='major')
ax[0].set_ylim([-140,2])
ax[0].set_xlim([t[0].astype(int),t[-1].astype(int)])
ax[0].set_ylabel('depth [m]',fontsize=14)
ax[0].legend(loc='upper left')
ax[0].set_title('With dead situation',fontsize=16)
ax[0].set_xlabel('time [d]',fontsize=14)
ax[0].set_xticks(tplt, labels=tticks)
# ax[0].axhline(y=EZD,c='gray')
ax2 = ax[0].twinx()
line0r, = ax2.plot(t[0],rho_2d[0],label='Total density',c='tab:red')
ax2.plot(t,rhosw_2d,c='k')
ax2.set_ylim([920,1200])
ax2.legend(loc='lower left')
# No Dead
line1z, = ax[1].plot(t[0],zplt[0],label='Vertical trajectory',c='tab:blue')
# ax[0].plot(t,zplt_2d,label='With death')
ax[1].grid(which='major')
ax[1].set_ylim([-140,2])
ax[1].set_xlim([t[0].astype(int),t[-1].astype(int)])
ax[1].set_ylabel('depth [m]',fontsize=14)
ax[1].legend(loc='upper left')
ax[1].set_title('No dead situation',fontsize=16)
ax[1].set_xlabel('time [d]',fontsize=14)
ax[1].set_xticks(tplt, labels=tticks)
# ax[1].axhline(y=EZD,c='gray')
ax2 = ax[1].twinx()
line1r, = ax2.plot(t[0],rho[0],label='Total density',c='tab:blue')
ax2.plot(t,rhosw,c='k')
ax2.set_ylim([920,1200])
ax2.legend(loc='lower left')
def animate(i):
t_data.append(t[i])
zplt_2d_data.append(zplt_2d[i])
rho_2d_data.append(rho_2d[i])
zplt_data.append(zplt[i])
rho_data.append(rho[i])
line0z.set_data(t_data,zplt_2d_data)
line0r.set_data(t_data,rho_2d_data)
line1z.set_data(t_data,zplt_data)
line1r.set_data(t_data,rho_data)
# scatter0.set_offsets(np.c_[t[i].astype(int),zplt_2d[i]])
return line0z,line0r,line1z,line1r,
anim = FuncAnimation(fig, animate, frames=len(t), interval=10)
anim.save('anim1_zVSrho_2.gif', writer='imagemagick', fps=15)
# anim = FuncAnimation(fig, animate, interval=10)
# writer = FFMpegWriter(fps=15)
# anim.save('anim.mp4',writer=writer)
'''
fig,ax = plt.subplots(3,1,figsize=(18,24))
# Depth
ax[0].plot(t,zplt,label='No death')
ax[0].plot(t,zplt_2d,label='With death')
ax[0].grid(which='major')
ax[0].set_ylim([-70,2])
ax[0].set_ylabel('depth [m]',fontsize=14)
ax[0].legend(loc='lower left')
ax[0].set_title('1D vertical trajectories',fontsize=16)
ax[0].set_xlabel('time [d]',fontsize=14)
ax[0].set_xticks(tplt, labels=tticks)
# No death
# ax[1].plot(t,rho,label='rho')
ax[1].plot(t,a_resp,c='purple',label='respiration')
ax[1].plot(t,a_mort,c='blue',label='mortality')
ax[1].plot(t,a_coll,c='orange',label='collision')
# ax[1].plot(t,a_growth,c='green',label='growth')
# ax[1].set_yscale('log')
# ax[1].plot(t,a_diss,c='gray',label='dissolution')
ax[1].set_ylabel('terms [no.]',fontsize=14)
ax[1].legend(loc='upper left')
# ax[1].set_ylim([-0.2e7,13e7])
ax[1].grid()
ax[1].set_xticks(tplt, labels=tticks)
ax[1].set_title('Contributions of different processes - No dead',fontsize=16)
ax[1].set_xlabel('time [d]',fontsize=14)
# ax2=ax[1].twinx()
# ax2.plot(t,a,c='darkred',label='attached living')
# ax2.plot(t,a_dead,c='k',label='attached dead')
# ax2.legend()
# ax2.set_ylim([-0.0001,0.0250])
# With death
# ax[2].plot(t,rho_2d,label='rho')
ax[2].plot(t,a_resp_2d,c='purple',label='respiration')
ax[2].plot(t,a_mort_2d,c='blue',label='mortality')
ax[2].plot(t,a_coll_2d,c='orange',label='collision')
ax[2].plot(t,a_growth_2d,c='green',label='growth')
# ax[2].set_yscale('log')
# ax[2].plot(t,a_diss_2d,c='gray',label='dissolution, rate='+str(a_diss_rate))
ax[2].set_ylabel('terms [no.]',fontsize=14)
ax[2].legend(loc='upper left')
# ax[2].set_ylim([-0.2e7,10e7])
ax[2].grid()
ax[2].set_xticks(tplt, labels=tticks)
ax[2].set_title('Contributions of different processes - With dead',fontsize=16)
ax[2].set_xlabel('time [d]',fontsize=14)
ax2=ax[2].twinx()
ax2.plot(t,a_2d,c='darkred',label='attached living')
ax2.plot(t,a_dead_2d,c='k',label='attached dead')
ax2.legend()
ax2.set_ylim([-0.0001,0.0200])
'''
# # Rho
# ax[3].plot(t,rho,label='respiration')
# ax[3].plot(t,rho_2d,label='mortality')
# # ax[2].plot(t,a_coll_2d,c='orange',label='collision')
# # ax[2].plot(t,a_growth_2d,c='green',label='growth')
# # ax[2].plot(t,a_diss_2d,c='gray',label='dissolution, rate='+str(a_diss_rate))
# # ax[2].set_ylabel('terms [no.]',fontsize=14)
# # ax[2].legend(loc='upper left')
# ax[3].set_ylim([900,1100])
# ax[3].grid()
# ax[3].set_xticks(tplt, labels=tticks)
# # ax[2].set_title('Contributions of different processes - With dead',fontsize=16)
# # ax[2].set_xlabel('time [d]',fontsize=14)
# # ax2=ax[2].twinx()
# # ax2.plot(t,a_2d,c='darkred',label='attached living')
# # ax2.plot(t,a_dead_2d,c='k',label='attached dead')
# # ax2.legend()
# # ax2.set_ylim([-0.0001,0.0250])
# plt.savefig(path+'2dn2d.pdf')
# plt.show()