def main():
plt.figure()
ymax = 100
for file in ut.iglobm('*/nitr.csv'):
if 'fix' in file or 'colab' in file:
continue
label = os.path.dirname(file)
df = pd.read_csv(file)
a = np.asarray(df, dtype=np.float64)
num = 1000
a[:, 1] = np.asarray(
[a[max(i - num + 1, 0):i + 1, 1].mean() for i in range(len(a))])
plt.plot(*a.T, lw=1, label=label)
if a.shape[0] > 5000:
ymax = max(ymax, a[5000:, 1].max() + 10)
plt.xlim(0, 20000)
# plt.ylim(0, ymax)
plt.yscale('log')
plt.xlabel('cycle')
plt.ylabel('itr')
# plt.show()
png = 'nitr.png'
plt.legend()
plt.savefig(png, bbox_inches='tight', pad_inches=0.1, dpi=600)
def comp_main():
def read(files):
for file in files:
name = re.search(r'out_\d+', file)[0]
print(name, end=' \r')
yield name, np.load(file)
for d in ut.fsort(os.listdir('.')):
loc = f'{d}/result'
if not os.path.isdir(loc):
continue
try:
with ut.chdir(loc):
# if any(ut.iglobm('*.npz')):
# continue
if any(ut.iglobm('*.npy')):
print(loc)
for i in range(10):
out = f'out_{i:03d}.npz'
if os.path.isfile(out):
continue
l = i * 100
u = (i + 1) * 100 if i < 9 else 1001
files = [f'out_{j:04d}.plt.npy' for j in range(l, u)]
if not all(map(os.path.isfile, files)):
continue
print(f'{l}=>{u}', ' ' * 20, end='\r')
h = dict(read(files))
try:
np.savez_compressed(out, **h)
except:
if os.path.isfile(out):
os.remove(out)
raise
ck = np.load(out)
for nm in ck.files:
f = f'{nm}.plt.npy'
if os.path.isfile(f):
os.remove(f)
except OSError:
print('OSError')
time.sleep(10)
continue
def main1():
odir = 'test'
with ut.chdir(odir):
times = sorted((os.path.getmtime(file), file)
for file in ut.iglobm('__raw__/*.plt')
if int(re.search(r'\d+', file)[0]) < 1000)
a = np.array([t2[0] - t1[0] for t1, t2 in zip(times[:-1], times[1:])])
list(map(print, (t[1] for t in times)))
plt.plot(a)
plt.xlim(0, len(a) - 1)
# plt.ylim(0, 1000)
plt.show()
def plot(dest, force=False):
flag = False
with ut.chdir(dest):
ut.mkdir(nm)
# files = ut.iglobm('result/*.npy')
files = ut.iglobm('result/*.dat')
for file in files:
basename = ut.basename(file, '.*')
image = f'{nm}/{basename}.png'
if os.path.isfile(image) and not force:
continue
print(dest, basename, end=' \r')
# data = np.load(file)
data = cm.read_raw(file)
# print(data.shape)
val = data[:, :, n] # ((u, v, p, w), ...)
if n == 2:
# a = val[val.shape[0]//2, val.shape[1]//4]
val -= val.mean()
fig, ax = plt.subplots(figsize=(6, 4))
fig.subplots_adjust(left=0.08, right=1, bottom=0, top=1)
colors = [(0, '#ff0000'), (0.5, '#000000'), (1, '#00ff00')]
cmap = plc.LinearSegmentedColormap.from_list('custom_cmap', colors)
im = ax.imshow(val, cmap=cmap, vmin=-vr, vmax=vr)
cax = fig.colorbar(im)
ax_pos = ax.get_position()
cax_pos0 = cax.ax.get_position()
cax_pos1 = [
cax_pos0.x0, ax_pos.y0, cax_pos0.x1 - cax_pos0.x0,
ax_pos.y1 - ax_pos.y0
]
cax.ax.set_position(cax_pos1)
# plt.show()
fig.savefig(image, bbox_inches='tight', pad_inches=0.1)
plt.close('all')
flag = True
return flag
def zip_main():
for loc in ut.fsort(ut.iglobm('**/image_*')):
# loc = f'{d}/image_w'
if not os.path.isdir(loc):
continue
with ut.chdir(loc):
file = f'{ut.basename(loc)}.zip'
if os.path.isfile(file):
continue
print(loc)
# subprocess.run('zip image_w *.png', shell=True)
try:
def f_():
for png in ut.fsort(ut.iglobm('*.png')):
print(png, os.path.getsize(png), end='\r')
with open(png, 'rb'):
yield png
pngs = list(f_())
if not pngs:
continue
with ZipFile(file, 'w', compression=ZIP_DEFLATED) as z:
for png in pngs:
z.write(png)
except:
if os.path.isfile(file):
os.remove(file)
raise
assert os.path.isfile(file)
if os.path.isfile(file):
with ZipFile(file) as z:
for png in z.namelist():
if os.path.isfile(png):
print(png)
os.remove(png)
def f_():
for png in ut.fsort(ut.iglobm('*.png')):
print(png, os.path.getsize(png), end='\r')
with open(png, 'rb'):
yield png
def main(opts=None):
parser = argparse.ArgumentParser()
parser.add_argument('--cycle', '-n', type=int, default=None,
help='number of cycles')
parser.add_argument('--out', '-o', type=str, default=None,
help='output directory name')
parser.add_argument('--resume', '-r', type=str, default=None,
help='filename for resume calculation')
args = parser.parse_args(args=opts)
conf = read_inputfile('in2d.txt')
if args.cycle:
cycle = args.cycle
else:
cycle = conf.cycle
if args.out:
out = args.out
else:
out = conf.dest
itr_max = conf.nitr
save_interval = conf.save
nx = np.array(conf.nx, dtype=np.int32)
ny = np.array(conf.ny, dtype=np.int32)
u = np.zeros((2, ny+2, nx+1), dtype=np.float64) # x方向速度
v = np.zeros((2, ny+1, nx+2), dtype=np.float64) # y方向速度
p = np.zeros((ny+2, nx+2), dtype=np.float64) # 圧力
t = np.zeros((ny+2, nx+2), dtype=np.float64) # 温度
f = np.ones((ny+2, nx+2), dtype=np.float64) # 流れ場情報（0=>物体上, 1=>流体）
m = np.zeros((120,), dtype=np.uint8) # メッセージ格納用配列
flg = np.array(0, dtype=np.int32) # 圧力計算収束確認用
itr_hist = []
save_count = 0
register_functions()
f_read_inputfile()
f_initialize()
with open('grid.csv') as fp:
f[1:-1, 1:-1] = np.array(list(csv.reader(fp)), dtype=np.float64)
if args.resume:
u[0], v[0], p[:] = load_value(args.resume)
for file in ut.iglobm('image/*.png'):
os.remove(file)
with ut.stopwatch('calc'):
with ut.chdir(out):
with tqdm(total=cycle, mininterval=1) as bar:
for i in range(1, cycle+1):
f_calc_velociry(u[0], v[0], p, t, u[1], v[1], nx, ny)
f_bind_velocity(u[1], v[1], f, nx, ny)
for j in range(1, itr_max+1):
itr = np.array(j, dtype=np.int32)
m.fill(ord(' '))
f_calc_pressure(u[1], v[1], p, itr, flg, nx, ny, m)
f_bind_velocity(u[1], v[1], f, nx, ny)
if j % 100 == 0:
msg = ''.join(map(chr, m)).rstrip()
bar.write(f'cycle={i} {msg}')
if flg == 0:
if i % 100 == 0:
msg = ''.join(map(chr, m)).rstrip()
bar.write(f'cycle={i} {msg}')
break
itr_hist.append(j)
u[0] = u[1]
v[0] = v[1]
if i % save_interval == 0:
k = save_count
with ut.chdir('result'):
dump_data(f'out_{k:05d}.npy', u[0], v[0], p)
with ut.chdir('image'):
plot_w(vorticity(u[0], v[0]), f'out_{k:05d}.png')
plot_nitr(itr_hist, 'nitr.png')
save_count += 1
bar.update()