# save time taken to csv file
np.savetxt(result_dir / "time_taken_yang_48x64x48.csv",
np.asarray(time_taken_yang),
delimiter=",")
np.savetxt(result_dir / "time_taken_default_48x64x48.csv",
np.asarray(time_taken_default),
delimiter=",")
pprint("""
----------------------------------------
Plotting individual error data to {}
----------------------------------------
""".format(result_dir))
# save plot to result dir
Visualize.plot_line(individual_error_default,
fname=str(result_dir / "individual_error_default.png"),
xlabel="frames",
ylabel="MSE")
Visualize.plot_line(individual_error_yang,
fname=str(result_dir / "individual_error_yang.png"),
xlabel="frames",
ylabel="MSE")
fake_res = (512, 512, 512)
pprint("""
----------------------------------------
Testing the speed of NN for resolution: {}
----------------------------------------
""".format(fake_res))
FakeResolution(fake_res, yang_model_path,
result_dir / ("time_taken_" + str(fake_res) + ".csv"))
copyArrayToGridReal(pressure_predcition, pressure)
"""
-------------------------------
End of NN
-------------------------------
"""
# correct velocity using the predicted pressure
correctVelocity(flags=flags, vel=vel, pressure=pressure)
s.step()
np.savetxt(result_dir / "coupling_error.csv",
np.asarray(err_acc[:10]),
delimiter=",")
Visualize.plot_line(np.asarray(err_acc[:10]),
fname=result_dir / "coupling_error.png",
ylabel="Mean Square Error(MSE)",
xlabel="Frames")
# turn it into gif
subprocess.call([
'ffmpeg', '-i',
str(result_dir / "screenshot_%04d.png"), '-y',
result_dir / "simulation.gif"
])
files_in_dir = os.listdir(result_dir)
for item in files_in_dir:
if "screenshot" in item:
os.remove(result_dir / item)