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Commits
0c5937f2
Commit
0c5937f2
authored
Feb 15, 2018
by
Jakob Knollmueller
Browse files
plotting routines
parent
c7ac3443
Changes
4
Hide whitespace changes
Inline
Side-by-side
1d_separation.py
View file @
0c5937f2
...
...
@@ -39,45 +39,46 @@ if __name__ == '__main__':
energy2
=
problem_iteration
(
energy2
)
energy3
=
problem_iteration
(
energy3
)
size
=
15
plt
.
figure
()
# plt.plot(data, 'k-')
f
,
(
ax0
,
ax1
,
ax2
)
=
plt
.
subplots
(
3
,
sharex
=
True
,
sharey
=
True
)
plt
.
suptitle
(
'diffuse components'
)
plt
.
suptitle
(
'diffuse components'
,
size
=
size
)
ax0
.
plot
(
exp
(
energy1
.
s
).
val
,
'k-'
)
ax0
.
yaxis
.
set_label_position
(
"right"
)
ax0
.
set_ylabel
(
r
'$\alpha = 1.25$'
)
ax0
.
set_ylabel
(
r
'$\alpha = 1.25$'
,
size
=
size
)
ax0
.
set_ylim
(
1e-1
,
1e3
)
ax0
.
set_yscale
(
"log"
)
ax1
.
plot
(
exp
(
energy2
.
s
).
val
,
'k-'
)
ax1
.
yaxis
.
set_label_position
(
"right"
)
ax1
.
set_ylabel
(
r
'$\alpha = 1.5$'
)
ax1
.
set_ylabel
(
r
'$\alpha = 1.5$'
,
size
=
size
)
ax2
.
plot
(
exp
(
energy3
.
s
).
val
,
'k-'
)
ax2
.
yaxis
.
set_label_position
(
"right"
)
ax2
.
set_ylabel
(
r
'$\alpha = 1.75$'
)
ax2
.
set_ylabel
(
r
'$\alpha = 1.75$'
,
size
=
size
)
plt
.
savefig
(
'1d_diffuse.pdf'
)
plt
.
figure
()
f
,
(
ax0
,
ax1
,
ax2
)
=
plt
.
subplots
(
3
,
sharex
=
True
,
sharey
=
True
)
plt
.
suptitle
(
'point-like components'
)
plt
.
suptitle
(
'point-like components'
,
size
=
size
)
ax0
.
plot
(
exp
(
energy1
.
u
).
val
,
'k-'
)
ax0
.
yaxis
.
set_label_position
(
"right"
)
ax0
.
set_ylabel
(
r
'$\alpha = 1.25$'
)
ax0
.
set_ylabel
(
r
'$\alpha = 1.25$'
,
size
=
size
)
ax0
.
set_ylim
(
1e-1
,
1e3
)
ax0
.
set_yscale
(
"log"
)
ax1
.
plot
(
exp
(
energy2
.
u
).
val
,
'k-'
)
ax1
.
yaxis
.
set_label_position
(
"right"
)
ax1
.
set_ylabel
(
r
'$\alpha = 1.5$'
)
ax1
.
set_ylabel
(
r
'$\alpha = 1.5$'
,
size
=
size
)
ax2
.
plot
(
exp
(
energy3
.
u
).
val
,
'k-'
)
ax2
.
yaxis
.
set_label_position
(
"right"
)
ax2
.
set_ylabel
(
r
'$\alpha = 1.75$'
)
ax2
.
set_ylabel
(
r
'$\alpha = 1.75$'
,
size
=
size
)
ax0
.
set_yscale
(
"log"
)
...
...
@@ -87,21 +88,21 @@ if __name__ == '__main__':
plt
.
savefig
(
'1d_points.pdf'
)
plt
.
figure
()
f
,
(
ax0
,
ax1
,
ax2
)
=
plt
.
subplots
(
3
,
sharex
=
True
,
sharey
=
True
)
plt
.
suptitle
(
'data and true components'
)
plt
.
suptitle
(
'data and true components'
,
size
=
size
)
ax0
.
plot
(
data
,
'k-'
)
ax0
.
set_yscale
(
"log"
)
ax0
.
set_ylim
(
1e-1
,
1e3
)
ax0
.
yaxis
.
set_label_position
(
"right"
)
ax0
.
set_ylabel
(
r
'data'
)
ax0
.
set_ylabel
(
r
'data'
,
size
=
size
)
ax1
.
plot
(
exp
(
s
).
val
,
'k-'
)
ax1
.
yaxis
.
set_label_position
(
"right"
)
ax1
.
set_ylabel
(
r
'diffuse'
)
ax1
.
set_ylabel
(
r
'diffuse'
,
size
=
size
)
ax2
.
plot
(
exp
(
u
).
val
,
'k-'
)
ax2
.
yaxis
.
set_label_position
(
"right"
)
ax2
.
set_ylabel
(
r
'point-like'
)
ax2
.
set_ylabel
(
r
'point-like'
,
size
=
size
)
# plt.ylim(1e-0)
plt
.
savefig
(
'1d_data.pdf'
)
...
...
hubble_separation.py
0 → 100644
View file @
0c5937f2
from
point_separation
import
build_problem
,
problem_iteration
,
load_data
from
nifty2go
import
*
import
numpy
as
np
from
matplotlib
import
rc
rc
(
'font'
,
**
{
'family'
:
'serif'
,
'serif'
:[
'Palatino'
]})
rc
(
'text'
,
usetex
=
True
)
from
matplotlib
import
pyplot
as
plt
from
matplotlib.colors
import
LogNorm
np
.
random
.
seed
(
42
)
if
__name__
==
'__main__'
:
path
=
'hst_05195_01_wfpc2_f702w_pc_sci.fits'
data
=
load_data
(
path
)
alpha
=
1.3
myEnergy
=
build_problem
(
data
,
alpha
=
alpha
)
for
i
in
range
(
10
):
myEnergy
=
problem_iteration
(
myEnergy
)
size
=
15
vmin
=
data
.
min
()
+
0.01
vmax
=
0.1
*
data
.
max
()
plt
.
figure
()
plt
.
imshow
(
np
.
exp
(
myEnergy
.
s
.
val
),
norm
=
LogNorm
(
vmin
=
vmin
,
vmax
=
vmax
))
cbar
=
plt
.
colorbar
()
cbar
.
set_label
(
'flux'
,
size
=
size
)
plt
.
title
(
'diffuse emission'
,
size
=
size
)
plt
.
axis
(
'off'
)
plt
.
savefig
(
'hubble_diffuse.pdf'
)
plt
.
figure
()
plt
.
imshow
(
np
.
exp
(
myEnergy
.
u
.
val
),
norm
=
LogNorm
(
vmin
=
vmin
,
vmax
=
vmax
))
cbar
=
plt
.
colorbar
()
cbar
.
set_label
(
'flux'
,
size
=
size
)
plt
.
title
(
'point-like emission'
,
size
=
size
)
plt
.
axis
(
'off'
)
plt
.
savefig
(
'hubble_point.pdf'
)
plt
.
figure
()
plt
.
imshow
(
data
,
norm
=
LogNorm
(
vmin
=
vmin
,
vmax
=
vmax
))
cbar
=
plt
.
colorbar
()
cbar
.
set_label
(
'flux'
,
size
=
size
)
plt
.
title
(
'data'
,
size
=
size
)
plt
.
axis
(
'off'
)
plt
.
savefig
(
'hubble_data.pdf'
)
plt
.
close
()
point_separation.py
View file @
0c5937f2
...
...
@@ -40,8 +40,8 @@ def build_problem(data, alpha):
separationEnergy
=
SeparationEnergy
(
position
=
initial_x
,
parameters
=
parameters
)
return
separationEnergy
def
problem_iteration
(
energy
):
controller
=
GradientNormController
(
verbose
=
True
,
tol_abs_gradnorm
=
0.00000001
,
iteration_limit
=
3
)
def
problem_iteration
(
energy
,
iterations
=
3
):
controller
=
GradientNormController
(
verbose
=
True
,
tol_abs_gradnorm
=
0.00000001
,
iteration_limit
=
iterations
)
minimizer
=
RelaxedNewton
(
controller
=
controller
)
energy
,
convergence
=
minimizer
(
energy
)
new_position
=
energy
.
position
...
...
@@ -69,28 +69,7 @@ def multi_problem_iteration(energy_list):
return
new_energy
if
__name__
==
'__main__'
:
path
=
'hst_05195_01_wfpc2_f702w_pc_sci.fits'
data
=
load_data
(
path
)
alpha
=
1.3
myEnergy
=
build_problem
(
data
,
alpha
=
alpha
)
x
=
np
.
arange
(
0
,
100
)
y
=
np
.
sin
(
x
/
12.
)
y
**=
2
y
[
50
]
=
10
y
[
4
]
=
5
y
[
70
]
=
3
y
+=
0.1
myEnergy
=
build_problem
(
y
,
alpha
=
alpha
)
for
i
in
range
(
100
):
myEnergy
=
problem_iteration
(
myEnergy
)
# plt.viridis()
# plt.imsave('points0.png',myEnergy.u.val)
# plt.imsave('maps0.png',(myEnergy.s).val)
# plt.imsave('data0.png',myEnergy.d.val)
pass
rgb_separation.py
View file @
0c5937f2
...
...
@@ -3,10 +3,11 @@ from matplotlib import pyplot as plt
import
numpy
as
np
if
__name__
==
'__main__'
:
data
=
plt
.
imread
(
'eso1242a.jpg'
)
# data = plt.imread('eso1242a.jpg')
data
=
plt
.
imread
(
'10Keso1242a.tif'
)
data
=
data
.
astype
(
float
)
data
=
data
.
clip
(
0.0001
)
energy_list
=
build_multi_problem
(
data
,
1.
35
)
energy_list
=
build_multi_problem
(
data
,
1.
2
)
for
i
in
range
(
10
):
energy_list
=
multi_problem_iteration
(
energy_list
)
...
...
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