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Project: JFM-2024-0272
Views: 9Visibility: Unlisted (only visible to those who know the link)
Image: ubuntu2204Kernel: Python 3 (system-wide)
In [6]:
import os import numpy as np import scipy.interpolate as intp import scipy.integrate as intg import h5py import matplotlib.pyplot as pl from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes, mark_inset from matplotlib.gridspec import GridSpec from matplotlib.colors import LogNorm from matplotlib.lines import Line2D from matplotlib.collections import LineCollection from matplotlib.legend_handler import HandlerTuple,HandlerLineCollection # from colormaps import rbw,baw from matplotlib import rc rc('font',**{'family':'STIXGeneral','serif':['stix']}) rc('text', usetex=True) rc('font',**{'size':13}) class HandlerDashedLines(HandlerLineCollection): """ Custom Handler for LineCollection instances. """ def create_artists(self, legend, orig_handle, xdescent, ydescent, width, height, fontsize, trans): # figure out how many lines there are numlines = len(orig_handle.get_segments()) xdata, xdata_marker = self.get_xdata(legend, xdescent, ydescent, width, height, fontsize) leglines = [] # divide the vertical space where the lines will go # into equal parts based on the number of lines ydata = np.full_like(xdata, height / (numlines + 1)) # for each line, create the line at the proper location # and set the dash pattern for i in range(numlines): legline = Line2D(xdata, ydata * (numlines - i) - ydescent) self.update_prop(legline, orig_handle, legend) # set color, dash pattern, and linewidth to that # of the lines in linecollection try: color = orig_handle.get_colors()[i] except IndexError: color = orig_handle.get_colors()[0] try: dashes = orig_handle.get_dashes()[i] except IndexError: dashes = orig_handle.get_dashes()[0] try: lw = orig_handle.get_linewidths()[i] except IndexError: lw = orig_handle.get_linewidths()[0] if dashes[1] is not None: legline.set_dashes(dashes[1]) legline.set_color(color) legline.set_transform(trans) legline.set_linewidth(lw) leglines.append(legline) return leglines def ISRE(foldername): if (foldername[:3]=='Re_'): return(True) else: return(False) def GET_NU(folder,tavg=100): try: stafield = h5py.File('{}/stafield_master.h5'.format(folder),'r') xm = stafield['xm'][:] xm = np.pad(xm,(1,1),'constant',constant_values=(0,1)) xc = stafield['xc'][:] avg_t = stafield['temp_m1'][0] tp_m1 = stafield['temp_m1'][:]/avg_t tp_m1 = np.pad(tp_m1,(0,1),'constant',constant_values=0) Nu = np.gradient(tp_m1,xc,edge_order=2) Nu = np.fabs(0.5*(Nu[0] + Nu[-1])) mean = Nu stdv = 0 except Exception as e: data = np.genfromtxt('{}/nu_plate.out'.format(folder),comments='#') tavg = data[-1,0]-tavg data = data[data[:,0]>=tavg] time = data[:,0] data = data[:,1:3] data = np.mean(data,axis=1) mean = intg.trapz(data,x=time)/(time[-1]-time[0]) stdv = (data-mean)**2 stdv = intg.trapz(stdv,x=time)/(time[-1]-time[0]) stdv = abs(stdv)**0.5 stdv = (stdv/mean)*100 return(mean) fig = pl.figure(figsize=(8.25,7.5),constrained_layout=True) gsp = GridSpec(3, 3, figure=fig) ax1 = fig.add_subplot(gsp[:2, 0]) ax2 = fig.add_subplot(gsp[0, 1]) ax3 = fig.add_subplot(gsp[0, 2]) ax4 = fig.add_subplot(gsp[1, 1]) ax5 = fig.add_subplot(gsp[1, 2]) ax6 = fig.add_subplot(gsp[2, 0]) ax7 = fig.add_subplot(gsp[2, 1]) ax8 = fig.add_subplot(gsp[2, 2]) alx = [ax1,ax2,ax3,ax4,ax5,ax6,ax7,ax8] lcx = [0.02,0.02,0.02,0.02,0.02,0.02,0.02,0.02] lcy = [0.94,0.88,0.88,0.88,0.88,0.88,0.88,0.88] clr = ['k','k','k','k','k','k','k','k'] ax1.set_title('Rayleigh-Bénard') ax2.set_title('Buoyancy-dominated regime') ax3.set_title('Shear-dominated regime') bx3 = ax3.twinx() bx5 = ax5.twinx() bx3.set_ylabel('Couette-RB') bx5.set_ylabel('Poiseuille-RB') bx3.set_yticks([]) bx5.set_yticks([]) alphabet = 'abcdefghijklmnopqrstuvwxyz' for i,axi in enumerate(alx): axi.text(lcx[i],lcy[i],'$({})$'.format(alphabet[i]),transform=axi.transAxes,color=clr[i]) axs = [ax1,ax2,ax3,ax4,ax5] Cases = [ '../raw_data/CRB_Large/Ra1E+07_Pr1E+00/Ri_Inf', '../raw_data/CRB_Large/Ra1E+07_Pr1E+00/Ri_1E+00', '../raw_data/CRB_Large/Ra1E+07_Pr1E+00/Ri_1E-01', '../raw_data/PRB/Ra1E+07_Pr1E+00/Re_01414', '../raw_data/PRB/Ra1E+07_Pr1E+00/Re_10000' ] maxes = [] minis = [] for Case,axi in zip(Cases,axs): dfl = Case + '/angle.h5' dat = h5py.File(dfl,'r') nus = GET_NU(Case) tbl = 0.5/nus img = axi.contourf(dat['bins'][:],dat['xm'][:]/tbl,dat['fluct'][:],levels=np.linspace(0,0.5,51),cmap='bone_r') for c in img.collections: c.set_edgecolor("face") axi.set_yscale('log') axi.set_yticks([1E-2,1E-1,1E0,1E1]) axi.set_xticks([-np.pi/2,-np.pi/4,0,np.pi/4,np.pi/2]) axi.set_xticklabels([r'$-\pi$',r'$-\pi/2$',0,r'$\pi/2$',r'$\pi$']) axi.set_xlabel(r'$\alpha$') axi.set_ylabel(r'$z/\lambda_{\theta}$') axi.axhline(1,color='k',linestyle='--') maxes += [np.amax(dat['fluct'][:])] minis += [np.amin(dat['fluct'][:])] cbr = pl.colorbar(img,ax=fig.axes[:5],orientation='horizontal',aspect=60,pad=0.025) cbr.ax.set_xticks(np.linspace(0,0.5,11)) cbr.ax.set_xlabel(r'$\phi(\alpha)$'+'\n\n') cbr.ax.xaxis.set_label_coords(-0.05, 1) Buoys = [ '../raw_data/CRB_Large/Ra1E+07_Pr1E+00/Ri_Inf', '../raw_data/RBP/Ra1E+06_Pr1E+00', '../raw_data/RBP/Ra1E+07_Pr5E-01', '../raw_data/RBP/Ra1E+07_Pr1E+00', '../raw_data/RBP/Ra1E+07_Pr3E+00', '../raw_data/RBP/Ra1E+07_Pr5E+00', '../raw_data/RBP/Ra1E+08_Pr1E+00', '../raw_data/RBP/Ra1E+06_Pr1E+00', '../raw_data/RBP/Ra1E+07_Pr5E-01', '../raw_data/RBP/Ra1E+07_Pr1E+00', '../raw_data/RBP/Ra1E+07_Pr3E+00', '../raw_data/RBP/Ra1E+07_Pr5E+00', '../raw_data/RBP/Ra1E+08_Pr1E+00' ] Trans = [ '../raw_data/CRB_Large/Ra1E+07_Pr1E+00/Ri_5E+00', '../raw_data/CRB/Ra1E+06_Pr1E+00/Re_00400', '../raw_data/CRB/Ra1E+07_Pr5E-01/Re_02000', '../raw_data/CRB/Ra1E+07_Pr1E+00/Re_01414', '../raw_data/CRB/Ra1E+07_Pr3E+00/Re_00700', '../raw_data/CRB/Ra1E+07_Pr5E+00/Re_00500', '../raw_data/CRB/Ra1E+08_Pr1E+00/Re_05000', '../raw_data/PRB/Ra1E+06_Pr1E+00/Re_00400', '../raw_data/PRB/Ra1E+07_Pr5E-01/Re_02000', '../raw_data/PRB/Ra1E+07_Pr1E+00/Re_01414', '../raw_data/PRB/Ra1E+07_Pr3E+00/Re_00700', '../raw_data/PRB/Ra1E+07_Pr5E+00/Re_00500', '../raw_data/PRB/Ra1E+08_Pr1E+00/Re_05000' ] Shears = [ '../raw_data/CRB_Large/Ra1E+07_Pr1E+00/Ri_1E-01', '../raw_data/CRB/Ra1E+06_Pr1E+00/Re_10000', '../raw_data/CRB/Ra1E+07_Pr5E-01/Re_10000', '../raw_data/CRB/Ra1E+07_Pr1E+00/Re_10000', '../raw_data/CRB/Ra1E+07_Pr3E+00/Re_10000', '../raw_data/CRB/Ra1E+07_Pr5E+00/Re_10000', '../raw_data/CRB/Ra1E+08_Pr1E+00/Re_10000', '../raw_data/PRB/Ra1E+06_Pr1E+00/Re_10000', '../raw_data/PRB/Ra1E+07_Pr5E-01/Re_10000', '../raw_data/PRB/Ra1E+07_Pr1E+00/Re_10000', '../raw_data/PRB/Ra1E+07_Pr3E+00/Re_10000', '../raw_data/PRB/Ra1E+07_Pr5E+00/Re_10000', '../raw_data/PRB/Ra1E+08_Pr1E+00/Re_10000', ] Colors = ['g','r','darkorange','g','deepskyblue','b','saddlebrown','r','darkorange','g','deepskyblue','b','saddlebrown'] Lines = ['-','--','--','--','--','--','--',':',':',':',':',':',':'] for Buoy,Tran,Shear,Color,Line in zip(Buoys,Trans,Shears,Colors,Lines): sta = Buoy + '/stafield_master.h5' sta = h5py.File(sta,'r') pra = sta['Prandtl Number'][0] try: rey = sta['Wall Reynolds Number'][0] except: rey = sta['Bulk Reynolds Number'][0] dfl = Buoy + '/angle.h5' dat = h5py.File(dfl,'r') nus = GET_NU(Buoy) nu0 = nus rl0 = 3.9246*(nu0**2)/(pra**(2/3)) tbl = 0.5/nus bns = dat['bins'][:] xms = dat['xm'][:] pdf = dat['fluct'][:] pdf = intp.interp1d(xms,pdf,axis=0,kind='cubic') pdf = pdf(tbl) plt = ax6.plot(bns,pdf,color=Color,linestyle=Line) ax6.set_xticks([-np.pi/2,-np.pi/4,0,np.pi/4,np.pi/2]) ax6.set_xticklabels([r'$-\pi$',r'$-\pi/2$',0,r'$\pi/2$',r'$\pi$']) ax6.set_ylim(0,0.6) ax6.set_xlabel(r'$\alpha$') ax6.set_ylabel(r'$\left.\phi(\alpha)\right|_{z=\lambda_{\theta}}$') ax6.set_title('Rayleigh-Bénard',pad=10.0) sta = Tran + '/stafield_master.h5' sta = h5py.File(sta,'r') try: rey = sta['Wall Reynolds Number'][0] except: rey = sta['Bulk Reynolds Number'][0] dfl = Tran + '/angle.h5' dat = h5py.File(dfl,'r') nus = GET_NU(Tran) rlt = rey/rl0 tbl = 0.5/nus bns = dat['bins'][:] xms = dat['xm'][:] pdf = dat['fluct'][:] pdf = intp.interp1d(xms,pdf,axis=0,kind='cubic') pdf = pdf(tbl) plt = ax7.plot(bns,pdf,color=Color,linestyle=Line) ax7.set_xticks([-np.pi/2,-np.pi/4,0,np.pi/4,np.pi/2]) ax7.set_xticklabels([r'$-\pi$',r'$-\pi/2$',0,r'$\pi/2$',r'$\pi$']) ax7.set_ylim(0,0.6) ax7.set_xlabel(r'$\alpha$') ax7.set_ylabel(r'$\left.\phi(\alpha)\right|_{z=\lambda_{\theta}}$') ax7.set_title('Buoyancy-dominated regime',pad=10.0) sta = Shear + '/stafield_master.h5' sta = h5py.File(sta,'r') try: rey = sta['Wall Reynolds Number'][0] except: rey = sta['Bulk Reynolds Number'][0] dfl = Shear + '/angle.h5' dat = h5py.File(dfl,'r') nus = GET_NU(Shear) rls = rey/rl0 tbl = 0.5/nus bns = dat['bins'][:] xms = dat['xm'][:] pdf = dat['fluct'][:] pdf = intp.interp1d(xms,pdf,axis=0,kind='cubic') pdf = pdf(tbl) if (rls>10): plt = ax8.plot(bns,pdf,color=Color,linestyle=Line) ax8.set_xticks([-np.pi/2,-np.pi/4,0,np.pi/4,np.pi/2]) ax8.set_xticklabels([r'$-\pi$',r'$-\pi/2$',0,r'$\pi/2$',r'$\pi$']) ax8.set_ylim(0,0.6) ax8.set_xlabel(r'$\alpha$') ax8.set_ylabel(r'$\left.\phi(\alpha)\right|_{z=\lambda_{\theta}}$') ax8.set_title('Shear-dominated regime',pad=10.0) handles = [] labels = [r'$Ra= 10^6, \ Pr = 1.0$',r'$Ra= 10^7, \ Pr = 0.5$',r'$Ra= 10^7, \ Pr = 1.0$',r'$Ra= 10^7, \ Pr = 3.0$',r'$Ra= 10^7, \ Pr = 5.0$',r'$Ra= 10^8, \ Pr = 1.0$'] for i in range(1,7): if (i==3): line = [[(0, 0)]] styles = [Lines[0],Lines[i],Lines[i+6]] colors = [Colors[0],Colors[i],Colors[i+6]] handles += [LineCollection(3 * line, linestyles=styles, colors=colors)] else: line = [[(0, 0)]] styles = [Lines[i],Lines[i+6]] colors = [Colors[i],Colors[i+6]] handles += [LineCollection(2 * line, linestyles=styles, colors=colors)] pl.figlegend(handles,labels,loc='lower center',bbox_to_anchor=(0.5,-0.12),ncol=3,handler_map={type(handles[0]): HandlerDashedLines()},handlelength=2.5,handleheight=1.5) # pl.savefig('PdF.png',bbox_inches='tight') # pl.savefig('PdF.pdf',bbox_inches='tight') # pl.savefig('PdF.eps',bbox_inches='tight') pl.show()
The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.
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