def average_com_detrend(n_init, n_fin, off=0.5, nb=5) :
init_array = dm.read_density_file(folder_name+'/'+file_root+str(n_init).zfill(5)+'.dat', bin='y')
left_branch_avg, right_branch_avg, xcom_0 = detect_interface(init_array, off, nb)
for n in range(n_init+1, n_fin+1) :
print("[ interface frame "+str(n)+" ]")
n_array = dm.read_density_file(folder_name+'/'+file_root+str(n).zfill(5)+'.dat', bin='y')
left_branch, right_branch, xcom = detect_interface(n_array, off, nb)
left_branch_avg = left_branch_avg + left_branch - (xcom-xcom_0)
right_branch_avg = right_branch_avg + right_branch - (xcom-xcom_0)
return left_branch_avg/(n_fin-n_init+1), right_branch_avg/(n_fin-n_init+1)
spin_up_steps = 0
n_init = FP.first_stamp + spin_up_steps
n_fin = FP.last_stamp
dt = FP.time_step
n_dump = 10
tot_amu = 0
print("Producing averaged profile ")
for idx in range(n_init, n_fin):
if idx % n_dump == 0:
print("Obtainig frame " + str(idx))
t_label = str(dt * idx) + ' ps'
print("tot amu = " + str(tot_amu))
# Time-averaging window
rho = dm.read_density_file(folder_name + '/' + file_root +
'{:05d}'.format(idx) + '.dat',
bin='y')
U, V = dm.read_velocity_file(folder_name + '/' + file_root +
'{:05d}'.format(idx) + '.dat')
K = 0.5 * np.multiply(rho, np.multiply(U, U) + np.multiply(V, V))
profile_velocity_x = np.add(np.mean(U, axis=0), profile_velocity_x)
profile_velocity_z = np.add(np.mean(V, axis=0), profile_velocity_z)
profile_kinetic_energy = np.add(np.mean(K, axis=0), profile_kinetic_energy)
tot_amu = np.sum(np.sum(rho))
profile_velocity_x /= n_fin - n_init
profile_velocity_z /= n_fin - n_init
profile_kinetic_energy /= n_fin - n_init
Ly = 4.65840
volume = Lx * Ly * Lz
base_name = 'flow_'
# folder_name = '100nm/third_run'
# file_name = 'flow_00900.dat'
# folder_name = 'RawFlowData'
# file_name = 'flow_SOL_00100.dat'
# PARAMETERS TO TUNE
Lx = 60.00000
Lz = 35.37240
# Lx = 300.00000
# Lz = 200.44360
# Lx = 75.60000
# Lz = 28.00000
vel_x, vel_z = dm.read_velocity_file(folder_name + '/' + file_name)
rho = dm.read_density_file(folder_name + '/' + file_name, bin='y')
# p_x = np.multiply(rho, vel_x)
# p_z = np.multiply(rho, vel_z)
Nx = vel_x.shape[0]
Nz = vel_x.shape[1]
hx = Lx / Nx # [nm]
hz = Lz / Nz # [nm]
x = hx * np.arange(0.0, Nx, 1.0, dtype=float)
z = hz * np.arange(0.0, Nz, 1.0, dtype=float)
X, Z = np.meshgrid(x, z, sparse=False, indexing='ij')
kin_ener = 0.5 * np.multiply(
rho,
np.multiply(vel_x, vel_x) + np.multiply(vel_z, vel_z))
# Try to average with values at previous steps
import sys
import densmap as dm
import numpy as np
FP = dm.fitting_parameters(par_file='parameters_shear.txt')
folder_name = FP.folder_name
file_root = 'flow_'
Lx = FP.lenght_x
Lz = FP.lenght_z
# CREATING MESHGRID
print("Creating meshgrid")
dummy_dens = dm.read_density_file(folder_name + '/' + file_root + '00500.dat',
bin='y')
dummy_vel_x, dummy_vel_z = dm.read_velocity_file(folder_name + '/' +
file_root + '00500.dat')
Nx = dummy_dens.shape[0]
Nz = dummy_dens.shape[1]
hx = Lx / Nx
hz = Lz / Nz
x = hx * np.arange(0.0, Nx, 1.0, dtype=float)
z = hz * np.arange(0.0, Nz, 1.0, dtype=float)
X, Z = np.meshgrid(x, z, sparse=False, indexing='ij')
# Manually tune, crop window [nm]
x0_crop = 87.00
x1_crop = 100.0
z0_crop = 0.000
z1_crop = 6.000
output_file_name = "com.mp4"
folder_name = 'Q4Ca005'
file_root = 'flow_'
# PARAMETERS TO TUNE
Lx = 159.75000
Lz = 30.63400
n_init = 8626
n_fin = 8628
# CREATING MESHGRID
print("Creating meshgrid")
density_array = dm.read_density_file(folder_name + '/' + file_root +
'04000.dat',
bin='y')
Nx = density_array.shape[0]
Nz = density_array.shape[1]
hx = Lx / Nx
hz = Lz / Nz
x = hx * np.arange(0.0, Nx, 1.0, dtype=float)
z = hz * np.arange(0.0, Nz, 1.0, dtype=float)
X, Z = np.meshgrid(x, z, sparse=False, indexing='ij')
# Testing .vtk output function
"""
vtk_folder = "/home/michele/densmap/TestVtk"
dm.export_scalar_vtk(x, z, hx, hz, 2.5, density_array)
"""
import matplotlib.pyplot as plt
from matplotlib import cm
import os
# User inputs
folder_name = 'Q4Ca002'
ni = 683
nf = 1183
Lx = 159.75000
Lz = 30.63400
nbins = 4
ref_order = 7
# Generate meshgrid
file_root = 'flow_'
init_array = dm.read_density_file(folder_name+'/'+file_root+'00001.dat', bin='y')
Nx = init_array.shape[0]
Nz = init_array.shape[1]
hx = Lx/Nx
hz = Lz/Nz
x = hx*(np.arange(0.0,Nx,1.0, dtype=float)+0.5)
z = hz*(np.arange(0.0,Nz,1.0, dtype=float)+0.5)
X, Z = np.meshgrid(x, z, sparse=False, indexing='ij')
def detect_interface(density_array, offset, nband) :
M = int(np.ceil(offset*Nx))
left_branch = np.zeros( Nz, dtype=float )
right_branch = np.zeros( Nz, dtype=float )
mass_strip = np.zeros( Nz, dtype=float )
xcom_strip = np.zeros( Nz, dtype=float )
for j in range(Nz) :
def contact_angle_from_density ( filename, smoother, density_th=2.0, h=1.85 ) :
_, theta = dm.equilibrium_from_density( filename, smoother, density_th, hx, hz, h )
return theta
# a = np.array([0.00, 0.75, 1.00, 1.25, 1.50, 1.75])
a = np.array([0.00, 0.25, 0.50, 0.75, 1.00, 1.25, 1.50, 1.75])
# PARAMETERS TO TUNE
Lx = 60.00000 # [nm]
Lz = 35.37240 # [nm]
r_h2o = 0.09584
# Detecting dimensions
dummy_file = '20nm/flow_sit_f/flow_00125.dat'
density_array = dm.read_density_file(dummy_file, bin='y')
Nx = density_array.shape[0]
Nz = density_array.shape[1]
hx = Lx/Nx
hz = Lz/Nz
nx = Nx
nz = Nz
x = hx*np.arange(0.0, nx, 1.0, dtype=float)
z = hz*np.arange(0.0, nz, 1.0, dtype=float)
X, Z = np.meshgrid(x, z, sparse=False, indexing='ij')
# Smoothing kernel once for all
smoother = dm.smooth_kernel(r_h2o, hx, hz)
master_folder = '20nm/'
folders_sit = 'flow_sit'
# Output file name
output_file_name = "t94_ca01_diff_ds.mp4"
folder_ens1 = 'Theta94Ca010_10nm'
folder_ens2 = 'Theta94Ca01_double'
file_root = 'flow_'
# PARAMETERS TO TUNE
Lx = 159.57001
Lz = 29.04330
# CREATING MESHGRID
print("Creating meshgrid")
density_array = dm.read_density_file(folder_ens1 + '/' + file_root +
'00001.dat',
bin='y')
Nx = density_array.shape[0]
Nz = density_array.shape[1]
hx = Lx / Nx
hz = Lz / Nz
x = hx * np.arange(0.0, Nx, 1.0, dtype=float)
z = hz * np.arange(0.0, Nz, 1.0, dtype=float)
X, Z = np.meshgrid(x, z, sparse=False, indexing='ij')
# Section for density computation
N_low = int(np.floor(70.0 / hx))
N_upp = int(np.ceil(90.0 / hx))
# INITIALIZING SMOOTHING KERNEL
r_mol = 0.39876