In [1]:
# import numpy as np
# # !/usr/bin/env python3
# # -*- coding: utf-8 -*-
# """
# Created on 20181219
# @author: zhangji
# Trajection of a ellipse, Jeffery equation.
# """
# %pylab inline
# pylab.rcParams['figure.figsize'] = (25, 11)
# fontsize = 40
# import numpy as np
# import scipy as sp
# from scipy.optimize import leastsq, curve_fit
# from scipy import interpolate
# from scipy.interpolate import interp1d
# from scipy.io import loadmat, savemat
# # import scipy.misc
# import matplotlib
# from matplotlib import pyplot as plt
# from matplotlib import animation, rc
# import matplotlib.ticker as mtick
# from mpl_toolkits.axes_grid1.inset_locator import inset_axes, zoomed_inset_axes
# from mpl_toolkits.mplot3d import Axes3D, axes3d
# from sympy import symbols, simplify, series, exp
# from sympy.matrices import Matrix
# from sympy.solvers import solve
# from IPython.display import display, HTML
# from tqdm import tqdm_notebook as tqdm
# import pandas as pd
# import re
# from scanf import scanf
# import os
# import glob
# from codeStore import support_fun as spf
# from src.support_class import *
# from src import stokes_flow as sf
# rc('animation', html='html5')
# PWD = os.getcwd()
# font = {'size': 20}
# matplotlib.rc('font', **font)
# np.set_printoptions(linewidth=90, precision=5)
import os
import glob
import re
from scanf import scanf
import natsort
import numpy as np
import scipy as sp
from scipy.optimize import leastsq, curve_fit
from scipy import interpolate
from scipy import spatial
# from scipy.interpolate import interp1d
from scipy.io import loadmat, savemat
# import scipy.misc
import importlib
from IPython.display import display, HTML
import pandas as pd
import matplotlib
from matplotlib import pyplot as plt
from matplotlib import colors as mcolors
from matplotlib import animation, rc
import matplotlib.ticker as mtick
from mpl_toolkits.axes_grid1.inset_locator import inset_axes, zoomed_inset_axes
from mpl_toolkits.mplot3d import Axes3D, axes3d
from matplotlib import cm
from time import time
from src.support_class import *
from src import jeffery_model as jm
from codeStore import support_fun as spf
# %matplotlib notebook
rc('animation', html='html5')
fontsize = 40
PWD = os.getcwd()
In [2]:
def read_data_psi(psi_dir, tcenter):
ecoli_U_list = []
ecoli_norm_list = []
ecoli_center_list = []
ecoli_nodes_list = []
ecoli_u_list = []
ecoli_f_list = []
ecoli_lateral_norm_list = []
norm_phi_list = []
norm_psi_list = []
norm_theta_list = []
file_handle = os.path.basename(psi_dir)
mat_names = natsort.natsorted(glob.glob('%s/%s_*.mat' % (psi_dir, file_handle)))
for mati in mat_names:
mat_contents = loadmat(mati)
ecoli_U = mat_contents['ecoli_U'].flatten()
ecoli_norm = mat_contents['ecoli_norm'].flatten()
ecoli_center = mat_contents['ecoli_center'].flatten()
ecoli_nodes = mat_contents['ecoli_nodes']
ecoli_u = mat_contents['ecoli_u']
ecoli_f = mat_contents['ecoli_f']
planeShearRate = mat_contents['planeShearRate'].flatten()
norm_phi = mat_contents['norm_phi'].flatten()
norm_psi = np.nan
norm_theta = mat_contents['norm_theta'].flatten()
# #dbg
# t_max = np.max(ecoli_nodes, axis=0)
# t_min = np.min(ecoli_nodes, axis=0)
# ecoli_center = (t_max - t_min) / 2 + t_min
# ecoli_U = ecoli_U - np.hstack((planeShearRate[0] * ecoli_center[2], np.zeros(5)))
# #dbg end
ecoli_U_list.append(ecoli_U)
ecoli_norm_list.append(ecoli_norm)
ecoli_center_list.append(ecoli_center)
norm_phi_list.append(norm_phi)
norm_psi_list.append(norm_psi)
norm_theta_list.append(norm_theta)
r0 = ecoli_nodes[-1] - ecoli_center
n0 = np.dot(r0, ecoli_norm) * ecoli_norm / np.dot(ecoli_norm, ecoli_norm)
t0 = r0 - n0
ecoli_lateral_norm_list.append(t0 / np.linalg.norm(t0))
# dbg
# ecoli_nodes_list.append(ecoli_nodes)
# #dbg end
ecoli_U = np.vstack(ecoli_U_list)
ecoli_norm = np.vstack(ecoli_norm_list)
ecoli_center = np.vstack(ecoli_center_list)
ecoli_lateral_norm = np.vstack(ecoli_lateral_norm_list)
norm_phi = np.hstack(norm_phi_list)
norm_psi = np.hstack(norm_psi_list)
norm_theta = np.hstack(norm_theta_list)
norm_tpp = np.vstack((norm_theta, norm_phi, norm_psi)).T
# calculate velocity u000(t,x,y,z) that the location initially at (0, 0, 0): u000(0, 0, 0, 0)
n_u000 = -np.linalg.norm(ecoli_center[0] - tcenter) * ecoli_norm
ecoli_u000 = ecoli_U[:, :3] + np.cross(ecoli_U[:, 3:], n_u000)
# calculate center center000(t,x,y,z) that at initially at (0, 0, 0): center000(0, 0, 0, 0)
ecoli_center000 = ecoli_center + n_u000
using_U = ecoli_U
omega_norm = np.array([np.dot(t1, t2)*t2/np.dot(t2, t2) for t1, t2 in zip(using_U[:, 3:], ecoli_norm)])
omega_tang = using_U[:, 3:] - omega_norm
return ecoli_U, ecoli_norm, ecoli_center, ecoli_lateral_norm, norm_tpp, \
ecoli_u000, ecoli_center000, omega_norm, omega_tang, planeShearRate, file_handle, \
ecoli_nodes_list
In [8]:
# %matplotlib notebook
%matplotlib inline
importlib.reload(spf)
psi_dir = '/home/zhangji/stokes_flow_master/head_Force/loop_table/ellipse_alpha3'
# psi_dir = '/home/zhangji/stokes_flow_master/head_Force/loop_table/ellipse_alpha3_all'
tcenter = np.zeros(3)
ecoli_U, ecoli_norm, ecoli_center, ecoli_lateral_norm, norm_tpp, \
ecoli_u000, ecoli_center000, omega_norm, omega_tang, planeShearRate, file_handle, \
ecoli_nodes_list \
= read_data_psi(psi_dir, tcenter)
norm_theta = norm_tpp[:, 0]
norm_phi = norm_tpp[:, 1]
norm_psi = norm_tpp[:, 2]
data = pd.DataFrame({'norm_theta': norm_theta,
'norm_phi': norm_phi,
'norm_psi': norm_phi * 0,
'ecoli_U0': ecoli_U[:, 0],
'ecoli_U1': ecoli_U[:, 1],
'ecoli_U2': ecoli_U[:, 2],
'ecoli_U3': ecoli_U[:, 3],
'ecoli_U4': ecoli_U[:, 4],
'ecoli_U5': ecoli_U[:, 5],
}).pivot_table(index=['norm_theta', 'norm_phi', 'norm_psi'])
norm_tpp = np.vstack(data.index.get_values())
norm_theta = norm_tpp[:, 0]
norm_phi = norm_tpp[:, 1]
norm_psi = norm_tpp[:, 2]
use_theta = np.unique(norm_theta)
use_phi = np.unique(norm_phi)
use_psi = np.unique(norm_psi)
n_theat, n_phi, n_psi = use_theta.size, use_phi.size, use_psi.size
ui_list = [data.ecoli_U0.unstack()[0].unstack(),
data.ecoli_U1.unstack()[0].unstack(),
data.ecoli_U2.unstack()[0].unstack(),
data.ecoli_U3.unstack()[0].unstack(),
data.ecoli_U4.unstack()[0].unstack(),
data.ecoli_U5.unstack()[0].unstack(), ]
fig = plt.figure(figsize=(38, 20))
fig.patch.set_facecolor('white')
ax0 = fig.add_subplot(2, 3, 1)
ax1 = fig.add_subplot(2, 3, 2)
ax2 = fig.add_subplot(2, 3, 3)
ax3 = fig.add_subplot(2, 3, 4)
ax4 = fig.add_subplot(2, 3, 5)
ax5 = fig.add_subplot(2, 3, 6)
for axi, ui, zlabeli, (vmin, vmax) in zip((ax0, ax1, ax2, ax3, ax4, ax5),
ui_list,
('Ux', 'Uy', 'Uz', 'Wx', 'Wy', 'Wz'),
((-1e-4, 1e-4), (-1e-4, 1e-4), (-1e-4, 1e-4),
(-0.2, 0.2), (-0.9, 0.9), (-0.2, 0.2))):
print(np.nanmax(ui.values), np.nanmin(ui.values), )
tx = ui.index.values
ty = ui.columns.values
plt.sca(axi)
ticks = np.linspace(vmin, vmax, 15)
im = axi.contourf(ui.index.values / np.pi, ui.columns.values / np.pi, ui.values,
ticks, cmap=cm.coolwarm)
ticks = np.linspace(vmin, vmax, 5)
fig.colorbar(im, ticks=ticks, ax=axi).ax.tick_params(labelsize=fontsize*0.8)
ticks = np.linspace(vmin, vmax, 10)
im = axi.contour(ui.index.values / np.pi, ui.columns.values / np.pi, ui.values,
ticks, linewidths=fontsize*0.1, colors='k')
plt.clabel(im, fmt='%4.2f', colors='k', fontsize=fontsize*0.8, inline=0, rightside_up=1)
axi.set_xlabel('$\\phi / \pi$', size=fontsize)
axi.set_ylabel('$\\theta / \pi$', size=fontsize)
axi.set_title('%s, %s' % (file_handle, zlabeli), size=fontsize*0.8)
plt.xticks(fontsize=fontsize*0.8)
plt.yticks(fontsize=fontsize*0.8)
plt.tight_layout()
In [26]:
import pickle
filename = os.path.basename(psi_dir)
table_data = []
intp_fun_list = []
sign_list = [1, 1, -1, 1, 1, -1]
rename_dict = {}
for t_phi0 in use_phi:
rename_dict[t_phi0] = t_phi0 + np.pi
for tpsi in np.linspace(0, 2*np.pi, 5, endpoint=False): # interpolate over 1d, psi, for ellipse case psi is fake, and it just copy the data.
tintp_fun_list = []
table_psi_data = []
for t1, sign in zip(data.columns.values, sign_list): # interpolate fun for [ux,uy,uz,wx,wy,wz]
tu = data[t1].unstack()
tU1 = tu[0].unstack()
tU2 = tU1.rename(columns=rename_dict).drop([tU1.columns.values[-1]], axis=1) * sign
tU = pd.concat([tU1, tU2], axis=1)
tx = tU.columns.values # norm_phi
ty = tU.index.values # norm_theta
# interpolate over 2d
tfun = interpolate.RectBivariateSpline(ty, tx, tU)
tintp_fun_list.append(tfun)
table_psi_data.append((ty, tx, tU))
table_data.append((tpsi, table_psi_data))
intp_fun_list.append(tintp_fun_list)
with open('%s.pickle' % filename, 'wb') as handle:
pickle.dump(table_data, handle, protocol=pickle.HIGHEST_PROTOCOL)
print('save table_data to %s.pickle' % filename)
In [27]:
import pickle
with open('%s.pickle' % filename, 'rb') as handle:
table_data = pickle.load(handle)
intp_fun_list = []
for tpsi, table_psi_data in table_data:
tintp_fun_list = []
for ty, tx, tU in table_psi_data:
tfun = interpolate.RectBivariateSpline(ty, tx, tU)
tintp_fun_list.append(tfun)
intp_fun_list.append(tintp_fun_list)
for tpsi, table_psi_data in table_data:
fig = plt.figure(figsize=(90, 6))
fig.patch.set_facecolor('white')
axs = fig.subplots(nrows=1, ncols=6)
for (ty, tx, tU), ax0, t_lmt in zip(table_psi_data, axs,
(1e-4, 1e-4, 1e-4, 0.2, 0.9, 0.2)):
levels = np.linspace(-t_lmt, t_lmt, 10)
im = ax0.contourf(tx / np.pi, ty / np.pi, tU.values, levels, cmap=cm.coolwarm)
ax0.set_title('$\\psi=%f \pi$' % (tpsi / np.pi))
ax0.set_xlabel('$\\phi / \pi$')
ax0.set_ylabel('$\\theta / \pi$')
fig.colorbar(im, ax=ax0, orientation='vertical')
In [6]:
with open('%s.pickle' % filename, 'rb') as handle:
table_data = pickle.load(handle)
intp_fun_list = []
intp_psi_list = []
for tpsi, table_psi_data in table_data:
tintp_fun_list = []
intp_psi_list.append(tpsi)
for ty, tx, tU in table_psi_data:
tfun = interpolate.RectBivariateSpline(ty, tx, tU)
# tfun = interpolate.interp2d(tx, ty, tU.T, kind='quintic', copy=False, )
tintp_fun_list.append(tfun)
intp_fun_list.append(tintp_fun_list)
def intp_U_fun(t_theta, t_phi, t_psi):
# # version 3
sign_list = np.ones(6)
intp_U = []
for tfun in intp_fun_list:
t_U = []
for intp_fun, sign in zip(tfun, sign_list):
t_U.append(intp_fun(t_theta, t_phi) * sign)
intp_U.append(np.hstack(t_U).flatten())
intp_U.append(intp_U[0].copy())
intp_U = np.vstack(intp_U)
intp_psi = np.hstack([intp_psi_list, np.pi * 2])
intp_fun1d = interpolate.interp1d(intp_psi, intp_U, kind='quadratic',
copy=False, axis=0, bounds_error=True)
return intp_fun1d(t_psi)
intp_U_fun(0, 0, 0)
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In [7]:
# contour plot for the table result
importlib.reload(jm)
eval_dt = 0.1
max_iter = 300
update_order = 3
ellipse_speed = 0
planeShearRate = np.array((1, 0, 0))
talpha = 1 / 0.3
tnorm = np.array((1, 0, 0))
lateral_norm = np.array((0, 1, 0))
tcenter = np.array((0, 0, 0))
# Table result
ellipse_kwargs = {'name': 'ellipse',
'center': tcenter,
'norm': tnorm / np.linalg.norm(tnorm),
'lateral_norm': lateral_norm / np.linalg.norm(lateral_norm),
'speed': ellipse_speed,
'lbd': (talpha ** 2 - 1) / (talpha ** 2 + 1),
'table_name': 'ellipse_alpha3', }
fileHandle = 'ShearTableProblem'
ellipse_obj = jm.TableObj(**ellipse_kwargs)
ellipse_obj.set_update_para(fix_x=False, fix_y=False, fix_z=False, update_order=update_order)
problem = jm.ShearTableProblem(name=fileHandle, planeShearRate=planeShearRate)
problem.add_obj(ellipse_obj)
intp_n_theta, intp_n_phi = 21, 21
txx, tyy = np.meshgrid(np.linspace(0, np.pi, intp_n_theta), np.linspace(0, np.pi, intp_n_phi))
tU = []
for i0, (tx1, ty1) in enumerate(zip(txx.flatten(), tyy.flatten())):
tU.append(ellipse_obj.intp_U_fun(tx1, ty1, 0))
tU = np.vstack(tU)
fig = plt.figure(figsize=(38, 20))
fig.patch.set_facecolor('white')
ax0 = fig.add_subplot(2, 3, 1)
ax1 = fig.add_subplot(2, 3, 2)
ax2 = fig.add_subplot(2, 3, 3)
ax3 = fig.add_subplot(2, 3, 4)
ax4 = fig.add_subplot(2, 3, 5)
ax5 = fig.add_subplot(2, 3, 6)
for axi, ui, zlabeli, (vmin, vmax) in zip((ax0, ax1, ax2, ax3, ax4, ax5),
tU.T,
('Ux', 'Uy', 'Uz', 'Wx', 'Wy', 'Wz'),
((-0.24, 0.24), (-0.12, 0.12), (-0.24, 0.24),
(-0.2, 0.2), (-0.9, 0.9), (-0.2, 0.2))):
plt.sca(axi)
ticks = np.linspace(vmin, vmax, 300)
im = axi.contourf(tyy / np.pi,
txx / np.pi,
ui.reshape((intp_n_theta, intp_n_phi)), ticks,
cmap=cm.coolwarm)
ticks = np.linspace(vmin, vmax, 5)
fig.colorbar(im, ticks=ticks, ax=axi).ax.tick_params(labelsize=fontsize*0.8)
ticks = np.linspace(vmin, vmax, 10)
im = axi.contour(tyy / np.pi,
txx / np.pi,
ui.reshape((intp_n_theta, intp_n_phi)), ticks,
linewidths=fontsize*0.1, colors='k')
plt.clabel(im, fmt='%4.2f', colors='k', fontsize=fontsize*0.8, inline=0, rightside_up=1)
axi.set_xlabel('$\\phi / \pi$', size=fontsize)
axi.set_ylabel('$\\theta / \pi$', size=fontsize)
axi.set_title('%s, %s' % (file_handle, zlabeli), size=fontsize*0.8)
plt.xticks(fontsize=fontsize*0.8)
plt.yticks(fontsize=fontsize*0.8)
plt.tight_layout()
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