Fig04.ipynb

Kernel: Python 3 (ipykernel)

import numpy as np
import h5py as h5
import matplotlib.pyplot as plt
from matplotlib import rcParams
from matplotlib.gridspec import GridSpec

rcParams['font.family'] = 'serif'
rcParams['font.serif'] = ['Computer Modern Roman']
rcParams['text.usetex'] = True
rcParams['xtick.major.size']=7
rcParams['ytick.major.size']=7
rcParams['xtick.minor.size']=3.5
rcParams['ytick.minor.size']=3.5
rcParams['xtick.labelsize']=10
rcParams['ytick.labelsize']=10
rcParams['contour.negative_linestyle'] = 'solid'

F = h5.File('../data/C0093.h5','r')
C0093_E_uu_inner    =F['E_uu_inner'][()]
C0093_E_uu_outer    =F['E_uu_outer'][()]
C0093_E_uu          =F['E_uu'][()]
C0093_Re_tau        =F['Re_tau'][()]
F.close()

F = h5.File('../data/C0220.h5','r')
C0220_E_uu_inner    =F['E_uu_inner'][()]
C0220_E_uu_outer    =F['E_uu_outer'][()]
C0220_E_uu          =F['E_uu'][()]
C0220_Re_tau        =F['Re_tau'][()]
F.close()

F = h5.File('../data/C0500.h5','r')
C0500_E_uu_inner    =F['E_uu_inner'][()]
C0500_E_uu_outer    =F['E_uu_outer'][()]
C0500_E_uu          =F['E_uu'][()]
C0500_Re_tau        =F['Re_tau'][()]
F.close()

F = h5.File('../data/P0550.h5','r')
P0550_E_uu_inner    =F['E_uu_inner'][()]
P0550_E_uu_outer    =F['E_uu_outer'][()]
P0550_E_uu          =F['E_uu'][()]
P0550_Re_tau        =F['Re_tau'][()]
F.close()

F = h5.File('../data/P1000.h5','r')
P1000_E_uu_inner    =F['E_uu_inner'][()]
P1000_E_uu_outer    =F['E_uu_outer'][()]
P1000_E_uu          =F['E_uu'][()]
P1000_Re_tau        =F['Re_tau'][()]
F.close()

F = h5.File('../data/P2000.h5','r')
P2000_E_uu_inner    =F['E_uu_inner'][()]
P2000_E_uu_outer    =F['E_uu_outer'][()]
P2000_E_uu          =F['E_uu'][()]
P2000_Re_tau        =F['Re_tau'][()]
F.close()

F = h5.File('../data/P5200.h5','r')
P5200_E_uu_inner    =F['E_uu_inner'][()]
P5200_E_uu_outer    =F['E_uu_outer'][()]
P5200_E_uu          =F['E_uu'][()]
P5200_Re_tau        =F['Re_tau'][()]
F.close()

C_Re = np.array([C0093_Re_tau, C0220_Re_tau, C0500_Re_tau])
P_Re = np.array([P0550_Re_tau, P1000_Re_tau, P2000_Re_tau, P5200_Re_tau])

C_Ew = np.array([C0093_E_uu[0], C0220_E_uu[0], C0500_E_uu[0]])
P_Ew = np.array([P0550_E_uu[0], P1000_E_uu[0], P2000_E_uu[0], P5200_E_uu[0]])
 
C_Ew_inner = np.array([C0093_E_uu_inner[0], C0220_E_uu_inner[0], C0500_E_uu_inner[0]])
P_Ew_inner = np.array([P0550_E_uu_inner[0], P1000_E_uu_inner[0], P2000_E_uu_inner[0], P5200_E_uu_inner[0]])
       
C_Ew_outer = np.array([C0093_E_uu_outer[0], C0220_E_uu_outer[0], C0500_E_uu_outer[0]])
P_Ew_outer = np.array([P0550_E_uu_outer[0], P1000_E_uu_outer[0], P2000_E_uu_outer[0], P5200_E_uu_outer[0]])

fig = plt.figure(figsize=(8.3,5),layout="constrained")

gs = GridSpec(2, 6, figure=fig)
ax1 = fig.add_subplot(gs[0, :3])
plt.plot(C_Re, C_Ew - C_Ew_inner, 'k--o', markerfacecolor='none')#,label=r'$\epsilon_{\mathrm{w},\lambda^+ < 1000}^+$ , Couette')
plt.plot(P_Re, P_Ew - P_Ew_inner, 'k--s', markerfacecolor='none')#,label=r'$\epsilon_{\mathrm{w},\lambda^+ < 1000}^+$ , Poiseuille')
plt.plot(C_Re, C_Ew, 'k-o', markerfacecolor='none')#,label=r'$\epsilon_{\mathrm{w}}^+$ , Couette')
plt.plot(P_Re, P_Ew, 'k-s', markerfacecolor='none')#,label=r'$\epsilon_{\mathrm{w}}^+$ , Poiseuille')
plt.plot([-1,0],[0,0], 'k--', markerfacecolor='none',label=r'$\epsilon_{\mathrm{w},\lambda^+ < 1000}^+$')
plt.plot([-1,0],[0,0], 'k-', markerfacecolor='none',label=r'$\epsilon_{\mathrm{w}}^+$')

plt.xscale('log')
plt.xlabel(r'$Re_\tau$')
plt.legend(frameon=False,ncol=1,loc='upper right')
plt.ylabel(r'$\epsilon_\mathrm{w}^+$')
plt.ylim([0.3,0.5])
plt.text(30,0.5,'(a)')

fig.add_subplot(gs[0, 3:6])
plt.plot(C_Re, C_Ew - C_Ew_inner, 'k-o', markerfacecolor='none',label=r'Couette')
plt.plot(P_Re, P_Ew - P_Ew_inner, 'k-s', markerfacecolor='none',label=r'Poiseuille')
plt.xscale('log')
plt.xlabel(r'$Re_\tau$')
#plt.legend(frameon=False,ncol=1,loc='lower left')
plt.ylabel(r'$\epsilon_{\mathrm{w},\lambda^+ < 1000}^+$')
plt.ylim([0.30,0.35])
plt.text(30,0.35,'(b)')

ax3 = fig.add_subplot(gs[1, :2])
plt.plot(C_Re, C_Ew_outer, 'k-o', markerfacecolor='none',label=r'Couette')
plt.xscale('log')
plt.xlabel(r'$Re_\tau$')
#plt.legend(frameon=False,ncol=2,loc='upper right')
plt.ylabel(r'$\epsilon_{\mathrm{w},\lambda \ge \delta}^+$')
plt.ylim([0.05,0.25])
plt.xlim([50,1e3])
plt.text(14,0.25,'(c)')

ax4 = fig.add_subplot(gs[1, 2:4])
plt.plot(P_Re, P_Ew_outer, 'k-s', markerfacecolor='none',label=r'Poiseuille')
plt.xscale('log')
plt.xlabel(r'$Re_\tau$')
#plt.legend(frameon=False,ncol=2,loc='upper right')
plt.ylabel(r'$\epsilon_{\mathrm{w},\lambda \ge \delta}^+$')
plt.ylim([0.02,0.04])
plt.xlim([300,1e4])
plt.text(60,0.04,'(d)')

ax4 = fig.add_subplot(gs[1, 4:6])
#plt.plot(C_Re, -C_Ew_outer+C_Ew_inner, 'k-o', markerfacecolor='none',label=r'Couette')
plt.plot(P_Re[-3:], -P_Ew_outer[-3:]+P_Ew_inner[-3:], 'k-s', markerfacecolor='none',label=r'Poiseuille')
plt.xscale('log')
plt.xlabel(r'$Re_\tau$')
#plt.legend(frameon=False,ncol=1,loc='lower right')
plt.ylabel(r'$\epsilon_{\mathrm{w},1000\delta_v < \lambda < \delta}^+ $')
plt.ylim([-0.05,0.1])
plt.xlim([5e2,1e4])
plt.text(100,0.1,'(e)')

plt.savefig('figure04.eps',dpi=300,bbox_inches='tight')
plt.show()
plt.close()