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statistics.py
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Sun, May 12, 20:44
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text/x-python
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Tue, May 14, 20:44 (2 d)
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rTAMAAS tamaas
statistics.py
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#!/usr/bin/env python3
#
# Copyright (©) 2016-2023 EPFL (École Polytechnique Fédérale de Lausanne),
# Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import
os
import
numpy
as
np
import
matplotlib.pyplot
as
plt
import
tamaas
as
tm
from
tamaas.utils
import
publications
,
radial_average
from
matplotlib.colors
import
LogNorm
tm
.
set_log_level
(
tm
.
LogLevel
.
info
)
# Show progression of solver
# Surface size
n
=
512
# Surface generator
sg
=
tm
.
SurfaceGeneratorFilter2D
([
n
,
n
])
sg
.
random_seed
=
1
# Spectrum
sg
.
spectrum
=
tm
.
Isopowerlaw2D
()
# Parameters
sg
.
spectrum
.
q0
=
16
sg
.
spectrum
.
q1
=
16
sg
.
spectrum
.
q2
=
128
sg
.
spectrum
.
hurst
=
0.8
# Generating surface
surface
=
sg
.
buildSurface
()
# Computing PSD and shifting for plot
psd
=
tm
.
Statistics2D
.
computePowerSpectrum
(
surface
)
psd
=
np
.
fft
.
fftshift
(
psd
,
axes
=
0
)
.
real
plt
.
imshow
(
np
.
clip
(
psd
.
real
,
1e-10
,
np
.
inf
),
norm
=
LogNorm
())
plt
.
gca
()
.
set_title
(
'Power Spectrum Density'
)
plt
.
gcf
()
.
tight_layout
()
# Computing autocorrelation and shifting for plot
acf
=
tm
.
Statistics2D
.
computeAutocorrelation
(
surface
)
acf
=
np
.
fft
.
fftshift
(
acf
)
plt
.
figure
()
plt
.
imshow
(
acf
)
plt
.
gca
()
.
set_title
(
'Autocorrelation'
)
plt
.
gcf
()
.
tight_layout
()
# Computing radial averages
fig
,
axs
=
plt
.
subplots
(
1
,
2
,
figsize
=
(
6
,
3
))
qx
=
np
.
fft
.
fftshift
(
np
.
fft
.
fftfreq
(
surface
.
shape
[
0
],
d
=
1
/
surface
.
shape
[
0
]))
qy
=
np
.
fft
.
rfftfreq
(
surface
.
shape
[
1
],
d
=
1
/
surface
.
shape
[
1
])
r
=
np
.
linspace
(
0
,
qy
.
max
()
-
1
)
theta
=
np
.
linspace
(
0
,
np
.
pi
,
30
)
psd_rad
=
radial_average
(
qx
,
qy
,
psd
,
r
,
theta
,
method
=
'nearest'
,
endpoint
=
True
)
axs
[
0
]
.
plot
(
r
,
psd_rad
)
x
=
np
.
linspace
(
-.
5
,
.
5
,
surface
.
shape
[
0
])
y
=
np
.
linspace
(
-.
5
,
.
5
,
surface
.
shape
[
1
])
r
=
np
.
linspace
(
0
,
.
5
,
surface
.
shape
[
0
]
//
2
)
theta
=
np
.
linspace
(
0
,
2
*
np
.
pi
,
60
)
acf_rad
=
radial_average
(
x
,
y
,
acf
,
r
,
theta
)
axs
[
1
]
.
plot
(
r
,
acf_rad
)
axs
[
0
]
.
set_xlabel
(
"q"
)
axs
[
0
]
.
set_ylabel
(
"PSD"
)
axs
[
0
]
.
set_xscale
(
'log'
)
axs
[
0
]
.
set_yscale
(
'log'
)
axs
[
0
]
.
set_ylim
(
1e-5
,
1
)
axs
[
1
]
.
set_xlabel
(
"r"
)
axs
[
1
]
.
set_ylabel
(
"ACF"
)
fig
.
tight_layout
()
plt
.
show
()
# Write the rough surface in paraview's VTK format
try
:
import
uvw
try
:
os
.
mkdir
(
'paraview'
)
except
FileExistsError
:
pass
x
=
np
.
linspace
(
0
,
1
,
n
,
endpoint
=
True
)
y
=
x
.
copy
()
with
uvw
.
RectilinearGrid
(
os
.
path
.
join
(
'paraview'
,
'surface.vtr'
),
(
x
,
y
))
as
grid
:
grid
.
addPointData
(
uvw
.
DataArray
(
surface
,
range
(
2
),
'surface'
))
except
ModuleNotFoundError
:
print
(
"uvw not installed, will not write VTK file"
)
pass
publications
()
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