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SWIFT
SWIFTsim
Commits
ca27c105
Commit
ca27c105
authored
Mar 20, 2017
by
Matthieu Schaller
Browse files
Added script to check accuracy of gravity calculation
parent
090d2479
Changes
1
Hide whitespace changes
Inline
Side-by-side
examples/UniformDMBox/plot_gravity_checks.py
0 → 100644
View file @
ca27c105
#!/usr/bin/env python
import
sys
import
glob
import
re
import
numpy
as
np
import
matplotlib.pyplot
as
plt
params
=
{
'axes.labelsize'
:
14
,
'axes.titlesize'
:
18
,
'font.size'
:
12
,
'legend.fontsize'
:
12
,
'xtick.labelsize'
:
14
,
'ytick.labelsize'
:
14
,
'text.usetex'
:
True
,
'figure.figsize'
:
(
10
,
10
),
'figure.subplot.left'
:
0.06
,
'figure.subplot.right'
:
0.99
,
'figure.subplot.bottom'
:
0.06
,
'figure.subplot.top'
:
0.985
,
'figure.subplot.wspace'
:
0.14
,
'figure.subplot.hspace'
:
0.14
,
'lines.markersize'
:
6
,
'lines.linewidth'
:
3.
,
'text.latex.unicode'
:
True
}
plt
.
rcParams
.
update
(
params
)
plt
.
rc
(
'font'
,
**
{
'family'
:
'sans-serif'
,
'sans-serif'
:[
'Times'
]})
min_error
=
1e-6
max_error
=
1e-1
num_bins
=
51
bin_edges
=
np
.
linspace
(
np
.
log10
(
min_error
),
np
.
log10
(
max_error
),
num_bins
+
1
)
bin_size
=
(
np
.
log10
(
max_error
)
-
np
.
log10
(
min_error
))
/
num_bins
bins
=
0.5
*
(
bin_edges
[
1
:]
+
bin_edges
[:
-
1
])
bin_edges
=
10
**
bin_edges
bins
=
10
**
bins
# Time-step to plot
step
=
int
(
sys
.
argv
[
1
])
# Find the files for the different expansion orders
order_list
=
glob
.
glob
(
"gravity_checks_step%d_order*.dat"
%
step
)
num_order
=
len
(
order_list
)
# Get the multipole orders
order
=
np
.
zeros
(
num_order
)
for
i
in
range
(
num_order
):
order
[
i
]
=
int
(
order_list
[
i
][
26
])
# Start the plot
plt
.
figure
()
# Get the Gadget-2 data if existing
gadget2_file_list
=
glob
.
glob
(
"forcetest_gadget2.txt"
)
if
len
(
gadget2_file_list
)
!=
0
:
data
=
np
.
loadtxt
(
gadget2_file_list
[
0
])
pos
=
data
[:,
1
:
4
]
a_exact
=
data
[:,
4
:
7
]
a_grav
=
data
[:,
7
:
10
]
# Compute the error norm
diff
=
a_exact
-
a_grav
norm_diff
=
np
.
sqrt
(
diff
[:,
0
]
**
2
+
diff
[:,
1
]
**
2
+
diff
[:,
2
]
**
2
)
norm_a
=
np
.
sqrt
(
a_exact
[:,
0
]
**
2
+
a_exact
[:,
1
]
**
2
+
a_exact
[:,
2
]
**
2
)
norm_error
=
norm_diff
/
norm_a
error_x
=
diff
[:,
0
]
/
norm_a
error_y
=
diff
[:,
1
]
/
norm_a
error_z
=
diff
[:,
2
]
/
norm_a
# Bin the error
norm_error_hist
,
_
=
np
.
histogram
(
norm_error
,
bins
=
bin_edges
,
density
=
False
)
/
(
np
.
size
(
norm_error
)
*
bin_size
)
error_x_hist
,
_
=
np
.
histogram
(
error_x
,
bins
=
bin_edges
,
density
=
False
)
/
(
np
.
size
(
norm_error
)
*
bin_size
)
error_y_hist
,
_
=
np
.
histogram
(
error_y
,
bins
=
bin_edges
,
density
=
False
)
/
(
np
.
size
(
norm_error
)
*
bin_size
)
error_z_hist
,
_
=
np
.
histogram
(
error_z
,
bins
=
bin_edges
,
density
=
False
)
/
(
np
.
size
(
norm_error
)
*
bin_size
)
plt
.
subplot
(
221
)
plt
.
semilogx
(
bins
,
norm_error_hist
,
'k--'
,
label
=
"Gadget-2"
)
plt
.
subplot
(
222
)
plt
.
semilogx
(
bins
,
error_x_hist
,
'k--'
,
label
=
"Gadget-2"
)
plt
.
subplot
(
223
)
plt
.
semilogx
(
bins
,
error_y_hist
,
'k--'
,
label
=
"Gadget-2"
)
plt
.
subplot
(
224
)
plt
.
semilogx
(
bins
,
error_z_hist
,
'k--'
,
label
=
"Gadget-2"
)
# Plot the different histograms
for
i
in
range
(
num_order
):
data
=
np
.
loadtxt
(
order_list
[
i
])
pos
=
data
[:,
1
:
4
]
a_exact
=
data
[:,
4
:
7
]
a_grav
=
data
[:,
7
:
10
]
# Compute the error norm
diff
=
a_exact
-
a_grav
norm_diff
=
np
.
sqrt
(
diff
[:,
0
]
**
2
+
diff
[:,
1
]
**
2
+
diff
[:,
2
]
**
2
)
norm_a
=
np
.
sqrt
(
a_exact
[:,
0
]
**
2
+
a_exact
[:,
1
]
**
2
+
a_exact
[:,
2
]
**
2
)
norm_error
=
norm_diff
/
norm_a
error_x
=
diff
[:,
0
]
/
norm_a
error_y
=
diff
[:,
1
]
/
norm_a
error_z
=
diff
[:,
2
]
/
norm_a
# Bin the error
norm_error_hist
,
_
=
np
.
histogram
(
norm_error
,
bins
=
bin_edges
,
density
=
False
)
/
(
np
.
size
(
norm_error
)
*
bin_size
)
error_x_hist
,
_
=
np
.
histogram
(
error_x
,
bins
=
bin_edges
,
density
=
False
)
/
(
np
.
size
(
norm_error
)
*
bin_size
)
error_y_hist
,
_
=
np
.
histogram
(
error_y
,
bins
=
bin_edges
,
density
=
False
)
/
(
np
.
size
(
norm_error
)
*
bin_size
)
error_z_hist
,
_
=
np
.
histogram
(
error_z
,
bins
=
bin_edges
,
density
=
False
)
/
(
np
.
size
(
norm_error
)
*
bin_size
)
plt
.
subplot
(
221
)
plt
.
semilogx
(
bins
,
norm_error_hist
,
label
=
"SWIFT Multipoles order %d"
%
order
[
i
])
plt
.
subplot
(
222
)
plt
.
semilogx
(
bins
,
error_x_hist
,
label
=
"SWIFT Multipoles order %d"
%
order
[
i
])
plt
.
subplot
(
223
)
plt
.
semilogx
(
bins
,
error_y_hist
,
label
=
"SWIFT Multipoles order %d"
%
order
[
i
])
plt
.
subplot
(
224
)
plt
.
semilogx
(
bins
,
error_z_hist
,
label
=
"SWIFT Multipoles order %d"
%
order
[
i
])
plt
.
subplot
(
221
)
plt
.
xlabel
(
"$|\delta \overrightarrow{a}|/|\overrightarrow{a}_{exact}|$"
)
plt
.
ylabel
(
"Density"
)
plt
.
xlim
(
min_error
,
2
*
max_error
)
plt
.
ylim
(
0
,
3
)
plt
.
legend
(
loc
=
"upper left"
)
plt
.
subplot
(
222
)
plt
.
xlabel
(
"$\delta a_x/|\overrightarrow{a}_{exact}|$"
)
plt
.
ylabel
(
"Density"
)
plt
.
xlim
(
min_error
,
2
*
max_error
)
plt
.
ylim
(
0
,
1
)
plt
.
legend
(
loc
=
"upper left"
)
plt
.
subplot
(
223
)
plt
.
xlabel
(
"$\delta a_y/|\overrightarrow{a}_{exact}|$"
)
plt
.
ylabel
(
"Density"
)
plt
.
xlim
(
min_error
,
2
*
max_error
)
plt
.
ylim
(
0
,
1
)
plt
.
legend
(
loc
=
"upper left"
)
plt
.
subplot
(
224
)
plt
.
xlabel
(
"$\delta a_z/|\overrightarrow{a}_{exact}|$"
)
plt
.
ylabel
(
"Density"
)
plt
.
xlim
(
min_error
,
2
*
max_error
)
plt
.
ylim
(
0
,
1
)
plt
.
legend
(
loc
=
"upper left"
)
plt
.
savefig
(
"gravity_checks_step%d.png"
%
step
)
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