def handle_raw_snap():
import load_snap
from half_rho import untangle
import snake
import half_peak
os.chdir(r"D:\tmp")
Lx = 180
Ly = 1000
sigma = [5, 1]
r = np.round(np.logspace(2, 18, 17, base=np.sqrt(2))).astype(int)
G1 = np.zeros(r.size)
G2 = np.zeros(r.size)
count = 0
snap = load_snap.RawSnap(r"so_%g_%g_%d_%d_%d_%d_%d.bin" %
(0.35, 0, Lx, Ly, Lx * Ly, 2000, 1234))
n = snap.get_num_frames()
print("n=", n)
t_beg = 250
t_end = 300
for i, frame in enumerate(snap.gene_frames(t_beg, t_end)):
x, y, theta = frame
rho = load_snap.coarse_grain2(x,
y,
theta,
Lx=Lx,
Ly=Ly,
ncols=Lx,
nrows=Ly).astype(float)
xh1, rho_h = half_peak.find_interface(rho, sigma=sigma)
rho_s = gaussian_filter(rho, sigma=sigma)
xh2, yh2 = snake.find_interface(rho_s,
0.5,
0.1,
0.25,
400,
rho_h,
dx=5)
xh1 = untangle(xh1, Lx)
xh2 = untangle(xh2, Lx)
G1 += cal_G(xh1, r)
G2 += cal_G(xh2, r)
count += 1
print("i = ", i)
G1 /= count
G2 /= count
plt.plot(r, G1)
plt.plot(r, G2)
plt.xscale("log")
plt.yscale("log")
plt.show()
plt.close()
for i in range(G1.size):
print(r[i], G1[i], G2[i])
print(count)
def cal_spectrum(Lx, Ly, sigma_y=10, show=False, out=False, eps=0, dt=1):
file = r"so_0.35_%g_%d_%d_%d_2000_1234.bin" % (eps, Lx, Ly, Lx * Ly)
snap = load_snap.RawSnap(file)
if not isinstance(sigma_y, list):
nrows = 1
sigma_y = [sigma_y]
else:
nrows = len(sigma_y)
ncols = Ly // 2 + 1
q = np.arange(ncols) / Ly
spectrum = np.zeros((nrows, ncols))
count = np.zeros(nrows, int)
for frame in snap.gene_frames(beg_idx=300, interval=dt):
x, y, theta = frame
rho = load_snap.coarse_grain2(x, y, theta, Lx=Lx, Ly=Ly).astype(float)
for i, sy in enumerate(sigma_y):
try:
xh, rho_h = find_interface(rho, sigma=[sy, 1])
xh = untangle(xh, Lx)
h = xh - np.mean(xh)
hq = np.fft.rfft(h) / Ly
A2 = np.abs(hq)**2
spectrum[i] += A2
count[i] += 1
except:
pass
print("t=%d" % (dt * count[-1]))
for i in range(nrows):
spectrum[i] /= count[i]
if show:
plt.loglog(q, spectrum)
plt.show()
plt.close()
if out:
outfile = "hq_%g_%d_%d.dat" % (eps, Lx, Ly)
with open(outfile, "w") as f:
for i in range(q.size):
line = "%f" % (q[i]**2)
for j in range(nrows):
line += "\t%.8f" % (spectrum[j, i])
line += "\n"
f.write(line)
def time_ave(Lx, Ly, sigma_y=100, show=False, out=False, eps=0, dt=1):
file = r"so_0.35_%g_%d_%d_%d_2000_1234.bin" % (eps, Lx, Ly, Lx * Ly)
snap = load_snap.RawSnap(file)
if not isinstance(sigma_y, list):
nrows = 1
sigma_y = [sigma_y]
else:
nrows = len(sigma_y)
ncols = Lx
rho_mean = np.zeros((nrows, ncols))
count = np.zeros(nrows, int)
x0 = np.arange(Lx) + 0.5
for frame in snap.gene_frames(beg_idx=300, interval=dt):
x, y, theta = frame
rho = load_snap.coarse_grain2(x, y, theta, Lx=Lx, Ly=Ly).astype(float)
rho_real = load_snap.coarse_grain(x, y, Lx=Lx, Ly=Ly)
for i, sy in enumerate(sigma_y):
try:
xh, rho_h = find_interface(rho, sigma=[sy, 1])
rho_mean[i] += ave_one_frame(rho_real, xh)
count[i] += 1
except:
pass
print("t=%d" % (dt * count[-1]))
for i in range(nrows):
rho_mean[i] /= count[i]
if show:
for i in range(nrows):
plt.plot(x0, rho_mean[i])
plt.show()
plt.close()
if out:
outfile = "avePeak_%g_%d_%d.dat" % (eps, Lx, Ly)
with open(outfile, "w") as f:
for i in range(ncols):
line = "%f" % (x0[i])
for j in range(nrows):
line += "\t%.8f" % (rho_mean[j, i])
line += "\n"
f.write(line)
start_row,
start_idx_h,
left=leftward,
debug=debug)
xh = get_xh(rho_s, idx_h, rho_h)
return xh, rho_h
if __name__ == "__main__":
import os
import load_snap
import half_rho
os.chdir(r"D:\tmp")
Lx = 180
Ly = 1000
snap = load_snap.RawSnap(r"so_%g_%g_%d_%d_%d_%d_%d.bin" %
(0.35, 0, Lx, Ly, Lx * Ly, 2000, 1234))
debug = 1
t_beg = 1758
t_end = 1759
w1 = []
w2 = []
for i, frame in enumerate(snap.gene_frames(t_beg, t_end)):
x, y, theta = frame
rho = load_snap.coarse_grain2(x, y, theta, Lx=Lx, Ly=Ly).astype(float)
xh, rho_h = find_interface(rho, sigma=[1, 1])
xh2, rho_h2 = half_rho.find_interface(rho, sigma=[5, 1])
xh3, rho_h3 = half_rho.find_interface(rho, sigma=[10, 1])
xh = half_rho.untangle(xh, Lx)
xh2 = half_rho.untangle(xh2, Lx)
xh3 = half_rho.untangle(xh3, Lx)
yh = np.linspace(0, Ly - 1, Ly)
if __name__ == "__main__":
import os
import load_snap
if platform.system() is not "Windows":
os.chdir(r"snap_one")
else:
os.chdir(r"D:\tmp")
Lx = int(sys.argv[1])
Ly = int(sys.argv[2])
eta = 0.35
eps = 0
dt = 2000
seed = 1234
snap = load_snap.RawSnap(r"so_%g_%g_%d_%d_%d_%d_%d.bin" %
(eta, eps, Lx, Ly, Lx * Ly, dt, seed))
file = r"wh_%g_%g_%d_%d_%d_%d_%d.dat" % (eta, eps, Lx, Ly, Lx * Ly, dt,
seed)
f = open(file, "w")
sigma_y = [5, 10, 15, 20, 25]
for i, frame in enumerate(snap.gene_frames()):
x, y, theta = frame
rho = load_snap.coarse_grain2(
x, y, theta, Lx=Lx, Ly=Ly, ncols=Lx, nrows=Ly) * 1.0
line = ""
for sy in sigma_y:
try:
xh, rho_h = find_interface(rho, sigma=[sy, 1])
w = np.var(untangle(xh, Lx))
except:
w = -1