54 lines
1.2 KiB
Python
54 lines
1.2 KiB
Python
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import scipy.io as sio
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import sys
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import numpy as np
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import matplotlib.pyplot as plt
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from mpl_toolkits.axes_grid1.inset_locator import inset_axes
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from IPython import display
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plt.rcParams.update({'font.size': 22})
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plt.rcParams.update({'figure.max_open_warning': 0})
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plt.interactive(True)
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viscos=3.57E-5
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datax= np.loadtxt("x2d.dat")
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x=datax[0:-1]
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ni=int(datax[-1])
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datay= np.loadtxt("y2d.dat")
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y=datay[0:-1]
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nj=int(datay[-1])
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y2d=np.zeros((ni+1,nj+1))
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y2d=np.reshape(y,(ni+1,nj+1))
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x2d=np.zeros((ni+1,nj+1))
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x2d=np.reshape(x,(ni+1,nj+1))
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xp2d=0.25*(x2d[0:-1,0:-1]+x2d[0:-1,1:]+x2d[1:,0:-1]+x2d[1:,1:])
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yp2d=0.25*(y2d[0:-1,0:-1]+y2d[0:-1,1:]+y2d[1:,0:-1]+y2d[1:,1:])
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y=yp2d[1,:]
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x=xp2d[:,1]
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# make ii 2D
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itstep,nk,dz=np.load('itstep.npy')
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u2d=np.load('u_averaged.npy')/itstep
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v2d=np.load('v_averaged.npy')/itstep
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k2d=np.load('k_averaged.npy')/itstep
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eps2d=np.load('eps_averaged.npy')/itstep
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om2d=np.load('om_averaged.npy')/itstep
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vis2d=np.load('vis_averaged.npy')/itstep
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i=ni-10
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u=u2d[i,:]
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v=v2d[i,:]
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k=k2d[i,:]
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eps = eps2d[i,:]
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vis=vis2d[i,:]
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vist=vis-viscos
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dudy=np.gradient(u,y)
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uv=-vist*dudy
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np.savetxt('y_u_v_k_eps_uv_re-theta-2500.txt', np.c_[y, u, v, k, eps, uv])
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