-
Notifications
You must be signed in to change notification settings - Fork 0
/
run_prom.py
66 lines (50 loc) · 1.67 KB
/
run_prom.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
"""
Build a parameterized ROM with a global ROB, and compare it to the HDM at an out-of-sample
point
"""
import glob
import pdb
import numpy as np
import matplotlib.pyplot as plt
from hypernet import (load_or_compute_snaps, make_1D_grid, inviscid_burgers_LSPG,
plot_snaps, POD)
def main():
snap_folder = 'param_snaps'
num_vecs = 50
dt = 0.07
num_steps = 500
num_cells = 500
xl, xu = 0, 100
w0 = np.ones(num_cells)
grid = make_1D_grid(xl, xu, num_cells)
mu_samples = [
[4.3, 0.021],
[5.1, 0.030]
]
mu_rom = [4.7, 0.026]
# Generate or retrive HDM snapshots
all_snaps_list = []
for mu in mu_samples:
snaps = load_or_compute_snaps(mu, grid, w0, dt, num_steps, snap_folder=snap_folder)
all_snaps_list += [snaps]
snaps = np.hstack(all_snaps_list)
# construct basis using mu_samples params
basis, sigma = POD(snaps)
basis_trunc = basis[:, :num_vecs]
# evaluate ROM at mu_rom
rom_snaps, times = inviscid_burgers_LSPG(grid, w0, dt, num_steps, mu_rom, basis_trunc)
hdm_snaps = load_or_compute_snaps(mu_rom, grid, w0, dt, num_steps, snap_folder=snap_folder)
fig, ax = plt.subplots()
snaps_to_plot = range(50, 501, 50)
plot_snaps(grid, hdm_snaps, snaps_to_plot,
label='HDM', fig_ax=(fig,ax))
plot_snaps(grid, rom_snaps, snaps_to_plot,
label='PROM', fig_ax=(fig,ax), color='blue', linewidth=1)
ax.set_xlim([grid.min(), grid.max()])
ax.set_xlabel('x')
ax.set_ylabel('w')
ax.set_title('Comparing HDM and ROM')
ax.legend()
plt.show()
if __name__ == "__main__":
main()