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ift
NIFTy
Commits
91463570
Commit
91463570
authored
Apr 19, 2018
by
Philipp Arras
Browse files
Some plotting tweaks
parent
8b6cf6fc
Pipeline
#27589
passed with stage
in 1 minute and 30 seconds
Changes
1
Pipelines
1
Hide whitespace changes
Inline
Side-by-side
demos/krylov_sampling.py
View file @
91463570
...
...
@@ -3,6 +3,8 @@ import numpy as np
import
matplotlib.pyplot
as
plt
from
nifty4.sugar
import
create_power_operator
np
.
random
.
seed
(
42
)
x_space
=
ift
.
RGSpace
(
1024
)
h_space
=
x_space
.
get_default_codomain
()
...
...
@@ -69,23 +71,27 @@ plt.plot(d.val,'o', label="data")
plt
.
plot
(
s_x
.
val
,
label
=
"original"
)
plt
.
plot
(
m_x
.
val
,
label
=
"reconstruction"
)
plt
.
legend
()
plt
.
show
()
plt
.
savefig
(
'Krylov_reconstruction.png'
)
plt
.
close
()
pltdict
=
{
'alpha'
:
.
2
,
'linewidth'
:
.
2
}
for
i
in
range
(
N_samps
):
plt
.
plot
(
sky
(
samps_old
[
i
]).
val
,
color
=
'b'
)
plt
.
plot
(
sky
(
samps
[
i
]).
val
,
color
=
'r'
)
plt
.
plot
(
sky
(
samps_old
[
i
]).
val
,
color
=
'b'
,
**
pltdict
)
plt
.
plot
(
sky
(
samps
[
i
]).
val
,
color
=
'r'
,
**
pltdict
)
plt
.
plot
((
s_x
-
m_x
).
val
,
color
=
'k'
)
plt
.
legend
()
plt
.
show
()
plt
.
savefig
(
'Krylov_samples.png'
)
plt
.
close
()
D_hat_old
=
ift
.
Field
.
zeros
(
x_space
).
val
D_hat_new
=
ift
.
Field
.
zeros
(
x_space
).
val
for
i
in
range
(
N_samps
):
D_hat_old
+=
sky
(
samps_old
[
i
]).
val
**
2
D_hat_new
+=
sky
(
samps
[
i
]).
val
**
2
plt
.
plot
(
np
.
sqrt
(
D_hat_old
/
N_samps
),
color
=
'b'
)
plt
.
plot
(
np
.
sqrt
(
D_hat_new
/
N_samps
),
color
=
'r'
)
plt
.
plot
(
-
np
.
sqrt
(
D_hat_old
/
N_samps
),
color
=
'b'
)
plt
.
plot
(
-
np
.
sqrt
(
D_hat_new
/
N_samps
),
color
=
'r'
)
plt
.
plot
((
s_x
-
m_x
).
val
,
color
=
'k'
)
plt
.
show
()
plt
.
plot
(
np
.
sqrt
(
D_hat_old
/
N_samps
),
'r--'
,
label
=
'Old uncertainty'
)
plt
.
plot
(
-
np
.
sqrt
(
D_hat_old
/
N_samps
),
'r--'
)
plt
.
fill_between
(
range
(
len
(
D_hat_new
)),
-
np
.
sqrt
(
D_hat_new
/
N_samps
),
np
.
sqrt
(
D_hat_new
/
N_samps
),
facecolor
=
'0.5'
,
alpha
=
0.5
,
label
=
'New unvertainty'
)
plt
.
plot
((
s_x
-
m_x
).
val
,
color
=
'k'
,
label
=
'signal - mean'
)
plt
.
legend
()
plt
.
savefig
(
'Krylov_uncertainty.png'
)
plt
.
close
()
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