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This instance will be upgraded to Heptapod 17.9.0rc1 on 2025-03-27 between 17:00 and 18:00 UTC+2
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fluiddyn
fluidsim
Commits
57493b7f8fe2
Commit
57493b7f8fe2
authored
6 years ago
by
calpe
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Spectrum_kykx.
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scripts/ns2d.strat/compute_spectrum_kykx.py
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scripts/ns2d.strat/compute_spectrum_kykx.py
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57493b7f
"""
compute_spectrum_kykx.py
========================
"""
import
os
import
h5py
import
numpy
as
np
import
matplotlib.pyplot
as
plt
from
glob
import
glob
from
math
import
pi
from
fluidsim
import
load_state_phys_file
# rot_fft tmin=200
# path = "/fsnet/project/meige/2015/15DELDUCA/DataSim/isotropy_forcing/NS2D.strat_1920x480_S2pix1.571_F07_gamma1_2018-11-26_15-56-33"
# rot_fft kz_negative
# path = "/fsnet/project/meige/2015/15DELDUCA/DataSim/isotropy_forcing/NS2D.strat_1920x480_S2pix1.571_F07_gamma1_2018-11-26_15-56-59"
## ap_fft tmin = 160
# path = "/fsnet/project/meige/2015/15DELDUCA/DataSim/isotropy_forcing/NS2D.strat_1920x480_S2pix1.571_F07_gamma1_2018-11-26_15-57-14"
## ap_fft kz tmin= 200
path
=
"
/fsnet/project/meige/2015/15DELDUCA/DataSim/isotropy_forcing/NS2D.strat_1920x480_S2pix1.571_F07_gamma1_2018-11-26_15-57-25
"
# Create list path files
paths_files
=
glob
(
os
.
path
.
join
(
path
,
"
state_phys*
"
))
# Create array of times
times
=
[]
for
path_file
in
paths_files
:
times
.
append
(
float
(
path_file
.
split
(
"
_t
"
)[
1
].
split
(
"
.nc
"
)[
0
]))
times
=
np
.
asarray
(
times
)
tmin
=
100
tmax
=
102
itmin
=
np
.
argmin
(
abs
(
times
-
tmin
))
itmax
=
np
.
argmin
(
abs
(
times
-
tmax
))
if
not
itmax
:
itmax
=
times
.
shape
[
0
]
if
itmax
<
itmin
:
raise
ValueError
(
"
itmax should be larger than itmin
"
)
# Load simulation
sim
=
load_state_phys_file
(
os
.
path
.
dirname
(
paths_files
[
-
1
]))
Lx
=
sim
.
params
.
oper
.
Lx
Lz
=
sim
.
params
.
oper
.
Ly
nx
=
sim
.
params
.
oper
.
nx
nz
=
sim
.
params
.
oper
.
ny
N
=
sim
.
params
.
N
# Array of wave-numbers in m^-1
kx
=
2
*
pi
*
np
.
fft
.
fftfreq
(
nx
,
Lx
/
nx
)
kz
=
2
*
pi
*
np
.
fft
.
fftfreq
(
nz
,
Lz
/
nz
)
KX
,
KZ
=
np
.
meshgrid
(
kx
,
kz
)
omega_k
=
sim
.
params
.
N
*
(
KX
/
np
.
sqrt
(
KX
**
2
+
KZ
**
2
))
# Create 3D_arrays
ux_fft_arr
=
np
.
empty
([
itmax
-
itmin
,
nz
,
nx
],
dtype
=
"
complex
"
)
uz_fft_arr
=
np
.
empty
([
itmax
-
itmin
,
nz
,
nx
],
dtype
=
"
complex
"
)
b_fft_arr
=
np
.
empty
([
itmax
-
itmin
,
nz
,
nx
],
dtype
=
"
complex
"
)
ap_fft_arr
=
np
.
empty
([
itmax
-
itmin
,
nz
,
nx
],
dtype
=
"
complex
"
)
am_fft_arr
=
np
.
empty
([
itmax
-
itmin
,
nz
,
nx
],
dtype
=
"
complex
"
)
for
ifile
,
path_file
in
enumerate
(
paths_files
[
itmin
:
itmax
]):
with
h5py
.
File
(
path_file
,
"
r
"
)
as
f
:
ux
=
f
[
"
state_phys
"
][
"
ux
"
].
value
uz
=
f
[
"
state_phys
"
][
"
uy
"
].
value
b
=
f
[
"
state_phys
"
][
"
b
"
].
value
# Fourier transform of the variables...
ux_fft_arr
[
ifile
,
:,
:]
=
np
.
fft
.
fft2
(
ux
)
uz_fft_arr
[
ifile
,
:,
:]
=
np
.
fft
.
fft2
(
uz
)
b_fft_arr
[
ifile
,
:,
:]
=
np
.
fft
.
fft2
(
b
)
ap_fft_arr
[
ifile
,
:,
:]
=
N
**
2
*
np
.
fft
.
fft2
(
uz
)
-
1j
*
omega_k
*
np
.
fft
.
fft2
(
b
)
am_fft_arr
[
ifile
,
:,
:]
=
N
**
2
*
np
.
fft
.
fft2
(
uz
)
+
1j
*
omega_k
*
np
.
fft
.
fft2
(
b
)
# Time average
ux_fft_arr
=
np
.
mean
(
ux_fft_arr
,
axis
=
0
)
uz_fft_arr
=
np
.
mean
(
uz_fft_arr
,
axis
=
0
)
b_fft_arr
=
np
.
mean
(
b_fft_arr
,
axis
=
0
)
ap_fft_arr
=
np
.
mean
(
ap_fft_arr
,
axis
=
0
)
am_fft_arr
=
np
.
mean
(
am_fft_arr
,
axis
=
0
)
# Parameters figure
fig1
,
ax1
=
plt
.
subplots
()
ax1
.
set_xlabel
(
"
$k_x$
"
)
ax1
.
set_ylabel
(
"
$k_z$
"
)
ax1
.
set_title
(
"
abs(uz_fft_arr)**2 + abs(ux_fft_arr)**2
"
)
ax1
.
set_xlim
([
-
sim
.
params
.
oper
.
coef_dealiasing
*
kx
.
max
(),
sim
.
params
.
oper
.
coef_dealiasing
*
kx
.
max
()])
ax1
.
set_ylim
([
-
sim
.
params
.
oper
.
coef_dealiasing
*
kz
.
max
(),
sim
.
params
.
oper
.
coef_dealiasing
*
kz
.
max
()])
data
=
abs
(
ux_fft_arr
)
**
2
+
abs
(
uz_fft_arr
)
**
2
data
=
abs
(
b_fft_arr
)
**
2
data
=
abs
(
ap_fft_arr
)
**
2
data
=
abs
(
am_fft_arr
)
**
2
ax1
.
pcolormesh
(
KX
[
0
:
KZ
.
shape
[
0
]
//
2
,
0
:
KX
.
shape
[
1
]
//
2
],
KZ
[
0
:
KZ
.
shape
[
0
]
//
2
,
0
:
KX
.
shape
[
1
]
//
2
],
data
[
0
:
KZ
.
shape
[
0
]
//
2
,
0
:
KX
.
shape
[
1
]
//
2
],
vmin
=
0
,
vmax
=
1e6
)
ax1
.
pcolormesh
(
KX
[
KZ
.
shape
[
0
]
//
2
:,
KX
.
shape
[
1
]
//
2
:],
KZ
[
KZ
.
shape
[
0
]
//
2
:,
KX
.
shape
[
1
]
//
2
:],
data
[
KZ
.
shape
[
0
]
//
2
:,
KX
.
shape
[
1
]
//
2
:],
vmin
=
0
,
vmax
=
1e6
)
ax1
.
pcolormesh
(
KX
[
KZ
.
shape
[
0
]
//
2
:,
0
:
KX
.
shape
[
1
]
//
2
],
KZ
[
KZ
.
shape
[
0
]
//
2
:,
0
:
KX
.
shape
[
1
]
//
2
],
data
[
KZ
.
shape
[
0
]
//
2
:,
0
:
KX
.
shape
[
1
]
//
2
],
vmin
=
0
,
vmax
=
1e6
)
ax1
.
pcolormesh
(
KX
[
0
:
KZ
.
shape
[
0
]
//
2
,
KX
.
shape
[
1
]
//
2
:],
KZ
[
0
:
KZ
.
shape
[
0
]
//
2
,
KX
.
shape
[
1
]
//
2
:],
data
[
0
:
KZ
.
shape
[
0
]
//
2
,
KX
.
shape
[
1
]
//
2
:],
vmin
=
0
,
vmax
=
1e6
)
# ax1.imshow(data, vmin=0, vmax=1e6)
# ax1.contourf(data)
# ax1.pcolormesh(
# data,
# vmin=0,
# vmax=1e6
# )
# # Parameters figure
# fig2, ax2 = plt.subplots()
# ax2.set_xlabel("$k_x$")
# ax2.set_ylabel("$k_z$")
# ax2.set_title("abs(b_fft_arr)**2")
# ax2.set_xlim([-sim.params.oper.coef_dealiasing * kx.max(),
# sim.params.oper.coef_dealiasing * kx.max()])
# ax2.set_ylim([-sim.params.oper.coef_dealiasing * kz.max(),
# sim.params.oper.coef_dealiasing * kz.max()])
# data = abs(b_fft_arr)**2
# ax2.pcolormesh(
# KX, KZ,
# data,
# vmin=0,
# vmax=1e6
# )
# # Parameters figure
# fig3, ax3 = plt.subplots()
# ax3.set_xlabel("$k_x$")
# ax3.set_ylabel("$k_z$")
# ax3.set_title("abs(ap_fft_arr)**2")
# ax3.set_xlim([-sim.params.oper.coef_dealiasing * kx.max(),
# sim.params.oper.coef_dealiasing * kx.max()])
# ax3.set_ylim([-sim.params.oper.coef_dealiasing * kz.max(),
# sim.params.oper.coef_dealiasing * kz.max()])
# data = abs(ap_fft_arr)**2
# ax3.pcolormesh(
# KX, KZ,
# data,
# vmin=0,
# vmax=1e6
# )
plt
.
show
()
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