def subplot( path, axis, title ): #x = netCDF4.Dataset(path+'/Initial_state.nc').variables['lonh'][:] #e = netCDF4.Dataset(path+'/Initial_state.nc').variables['eta'][:,0,:] #S = netCDF4.Dataset(path+'/Initial_state.nc').variables['Salt'][0,:,0,:] x = netCDF4.Dataset(path+'/prog.nc').variables['xh'][:] e = netCDF4.Dataset(path+'/prog.nc').variables['e'][-1,:,0,:] S = netCDF4.Dataset(path+'/prog.nc').variables['salt'][-1,:,0,:] m6plot.yzplot(S, x, e, axis=axis, title=title, clim=m6plot.linCI(34,35,.05)) plt.plot(x, e.T, hold=True, color='k')
def main(cmdLineArgs,stream=None): if not os.path.exists(cmdLineArgs.gridspec): raise ValueError('Specified gridspec directory/tar file does not exist.') if os.path.isdir(cmdLineArgs.gridspec): xcenter = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['x'][1::2,1::2] y = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['y'][1::2,1::2].max(axis=-1) ycenter = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['y'][1::2,1::2] msk = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_mask.nc').variables['mask'][:] area = msk*netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_hgrid.nc').variables['area'][:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1) depth = netCDF4.Dataset(cmdLineArgs.gridspec+'/ocean_topog.nc').variables['depth'][:] try: basin = netCDF4.Dataset(cmdLineArgs.gridspec+'/basin_codes.nc').variables['basin'][:] except: basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth) elif os.path.isfile(cmdLineArgs.gridspec): xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','x')[1::2,1::2] y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[1::2,1::2].max(axis=-1) ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','y')[1::2,1::2] msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_mask.nc','mask')[:] area = msk*m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_hgrid.nc','area')[:,:].reshape([msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1) depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'ocean_topog.nc','depth')[:] try: basin = m6toolbox.readNCFromTar(cmdLineArgs.gridspec,'basin_codes.nc','basin')[:] except: basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth) else: raise ValueError('Unable to extract grid information from gridspec directory/tar file.') if stream != None: if len(stream) != 4: raise ValueError('If specifying output streams, exactly four (4) streams are needed for this analysis') Sobs = netCDF4.Dataset( cmdLineArgs.woa ).variables['salt'] if len(Sobs.shape)==3: Sobs = Sobs[:] else: Sobs = Sobs[:].mean(axis=0) Zobs = netCDF4.Dataset( cmdLineArgs.woa ).variables['eta'][:] rootGroup = netCDF4.MFDataset( cmdLineArgs.annual_file ) if 'salt' in rootGroup.variables: varName = 'salt' elif 'so' in rootGroup.variables: varName = 'so' else:raise Exception('Could not find "salt" or "so" in file "%s"'%(cmdLineArgs.annual_file)) if len(rootGroup.variables[varName].shape)==4: Smod = rootGroup.variables[varName][:].mean(axis=0) else: Smod = rootGroup.variables[varName][:] if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0] else: Zmod = Zobs # Using model z-output def zonalAverage(S, eta, area, mask=1.): vols = ( mask * area ) * ( eta[:-1] - eta[1:] ) # mask * area * level thicknesses return numpy.sum( vols * S, axis=-1 ) / numpy.sum( vols, axis=-1 ), (mask*eta).min(axis=-1) ci=m6plot.pmCI(0.125,2.25,.25) if cmdLineArgs.suptitle != '': suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label else: suptitle = rootGroup.title + ' ' + cmdLineArgs.label # Global sPlot, z = zonalAverage(Smod, Zmod, area) sObsPlot, _ = zonalAverage(Sobs, Zobs, area) if stream != None: objOut = stream[0] else: objOut = cmdLineArgs.outdir+'/S_global_xave_bias_WOA05.png' m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title='''Global zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is None: m6plot.yzcompare( sPlot, sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1='Global zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir+'/S_global_xave_bias_WOA05.3_panel.png') # Atlantic + Arctic newMask = 1.*msk; newMask[ (basin!=2) & (basin!=4) ] = 0. sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask) sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask) if stream != None: objOut = stream[1] else: objOut = cmdLineArgs.outdir+'/S_Atlantic_xave_bias_WOA05.png' m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title='''Atlantic zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is None: m6plot.yzcompare( sPlot, sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1='Atlantic zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir+'/S_Atlantic_xave_bias_WOA05.3_panel.png') # Pacific newMask = 1.*msk; newMask[ (basin!=3) ] = 0. sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask) sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask) if stream != None: objOut = stream[2] else: objOut = cmdLineArgs.outdir+'/S_Pacific_xave_bias_WOA05.png' m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title='''Pacific zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is None: m6plot.yzcompare( sPlot, sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1='Pacific zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir+'/S_Pacific_xave_bias_WOA05.3_panel.png') # Indian newMask = 1.*msk; newMask[ (basin!=5) ] = 0. sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask) sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask) if stream != None: objOut = stream[3] else: objOut = cmdLineArgs.outdir+'/S_Indian_xave_bias_WOA05.png' m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title='''Indian zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is None: m6plot.yzcompare( sPlot, sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1='Indian zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir+'/S_Indian_xave_bias_WOA05.3_panel.png')
if len(rootGroup.variables[varName].shape)==4: Tmod = rootGroup.variables[varName][:].mean(axis=0) else: Tmod = rootGroup.variables[varName][:] if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0] else: Zmod = Zobs # Using model z-ou:put def zonalAverage(T, eta, area, mask=1.): vols = ( mask * area ) * ( eta[:-1] - eta[1:] ) # mask * area * level thicknesses return numpy.sum( vols * T, axis=-1 ) / numpy.sum( vols, axis=-1 ), (mask*eta).min(axis=-1) ci=m6plot.pmCI(0.25,4.5,.5) # Global tPlot, z = zonalAverage(Tmod, Zmod, area) tObsPlot, _ = zonalAverage(Tobs, Zobs, area) m6plot.yzplot( tPlot - tObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=rootGroup.title+' '+cmdLineArgs.label, title=r'''Global zonal-average $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=cmdLineArgs.outdir+'/T_global_xave_bias_WOA05.png') m6plot.yzcompare( tPlot, tObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=rootGroup.title+' '+cmdLineArgs.label, title1=r'Global zonal-average $\theta$ [$\degree$C]', title2=r'''WOA'05 $\theta$ [$\degree$C]''', clim=m6plot.linCI(-2,29,.5), colormap='dunneRainbow', extend='max', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir+'/T_global_xave_bias_WOA05.3_panel.png') # Atlantic + Arctic newMask = 1.*msk; newMask[ (basin!=2) & (basin!=4) ] = 0. tPlot, z = zonalAverage(Tmod, Zmod, area, mask=newMask) tObsPlot, _ = zonalAverage(Tobs, Zobs, area, mask=newMask) m6plot.yzplot( tPlot - tObsPlot , y, z, splitscale=[0., -1000., -6500.],
ci = m6plot.pmCI(0.0125, .225, .025) if len(cmdLineArgs.label1): title1 = cmdLineArgs.label1 else: title1 = rootGroup.title if len(cmdLineArgs.label2): title2 = cmdLineArgs.label2 else: title2 = rootGroupRef.title # Global sPlot, z = zonalAverage(Smod, Zmod, area) sRefPlot, _ = zonalAverage(Sref, Zref, area) m6plot.yzplot(sPlot - sRefPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=title1 + ' - ' + title2, title='''Global zonal-average salinity response [ppt] ''' + cmdLineArgs.label, clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=cmdLineArgs.outdir + '/S_global_xave_response.png') m6plot.yzcompare( sPlot, sRefPlot, y, z, splitscale=[0., -1000., -6500.], suptitle='Global zonal-average salinity [ppt] ' + cmdLineArgs.label, title1=title1, title2=title2,
if len(rootGroup.variables[varName].shape)==4: Smod = rootGroup.variables[varName][:].mean(axis=0) else: Smod = rootGroup.variables[varName][:] if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0] else: Zmod = Zobs # Using model z-output def zonalAverage(S, eta, area, mask=1.): vols = ( mask * area ) * ( eta[:-1] - eta[1:] ) # mask * area * level thicknesses return numpy.sum( vols * S, axis=-1 ) / numpy.sum( vols, axis=-1 ), (mask*eta).min(axis=-1) ci=m6plot.pmCI(0.125,2.25,.25) # Global sPlot, z = zonalAverage(Smod, Zmod, area) sObsPlot, _ = zonalAverage(Sobs, Zobs, area) m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=rootGroup.title+' '+cmdLineArgs.label, title='''Global zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=cmdLineArgs.outdir+'/S_global_xave_bias_WOA05.png') m6plot.yzcompare( sPlot, sObsPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=rootGroup.title+' '+cmdLineArgs.label, title1='Global zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir+'/S_global_xave_bias_WOA05.3_panel.png') # Atlantic + Arctic newMask = 1.*msk; newMask[ (basin!=2) & (basin!=4) ] = 0. sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask) sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask) m6plot.yzplot( sPlot - sObsPlot , y, z, splitscale=[0., -1000., -6500.],
def main(cmdLineArgs, stream=False): if not os.path.exists(cmdLineArgs.gridspec): raise ValueError( 'Specified gridspec directory/tar file does not exist.') if os.path.isdir(cmdLineArgs.gridspec): xcenter = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_hgrid.nc').variables['x'][1::2, 1::2] y = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_hgrid.nc').variables['y'][1::2, 1::2].max( axis=-1) ycenter = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_hgrid.nc').variables['y'][1::2, 1::2] msk = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_mask.nc').variables['mask'][:] area = msk * netCDF4.Dataset( cmdLineArgs.gridspec + '/ocean_hgrid.nc').variables['area'][:, :].reshape( [msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1) depth = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_topog.nc').variables['depth'][:] try: basin = netCDF4.Dataset(cmdLineArgs.gridspec + '/basin_codes.nc').variables['basin'][:] except: basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth) elif os.path.isfile(cmdLineArgs.gridspec): xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'x')[1::2, 1::2] y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'y')[1::2, 1::2].max(axis=-1) ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'y')[1::2, 1::2] msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_mask.nc', 'mask')[:] area = msk * m6toolbox.readNCFromTar( cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'area')[:, :].reshape( [msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1) depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_topog.nc', 'depth')[:] try: basin = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'basin_codes.nc', 'basin')[:] except: basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth) else: raise ValueError( 'Unable to extract grid information from gridspec directory/tar file.' ) Sobs = netCDF4.Dataset(cmdLineArgs.woa).variables['salt'] if len(Sobs.shape) == 3: Sobs = Sobs[:] else: Sobs = Sobs[:].mean(axis=0) Zobs = netCDF4.Dataset(cmdLineArgs.woa).variables['eta'][:] rootGroup = netCDF4.MFDataset(cmdLineArgs.infile) if 'salt' in rootGroup.variables: varName = 'salt' elif 'so' in rootGroup.variables: varName = 'so' else: raise Exception('Could not find "salt" or "so" in file "%s"' % (cmdLineArgs.infile)) if len(rootGroup.variables[varName].shape) == 4: Smod = rootGroup.variables[varName][:].mean(axis=0) else: Smod = rootGroup.variables[varName][:] if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0] else: Zmod = Zobs # Using model z-output def zonalAverage(S, eta, area, mask=1.): vols = (mask * area) * (eta[:-1] - eta[1:] ) # mask * area * level thicknesses return numpy.sum(vols * S, axis=-1) / numpy.sum(vols, axis=-1), ( mask * eta).min(axis=-1) ci = m6plot.pmCI(0.125, 2.25, .25) if cmdLineArgs.suptitle != '': suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label else: suptitle = rootGroup.title + ' ' + cmdLineArgs.label imgbufs = [] # Global sPlot, z = zonalAverage(Smod, Zmod, area) sObsPlot, _ = zonalAverage(Sobs, Zobs, area) if stream is True: objOut = io.BytesIO() else: objOut = cmdLineArgs.outdir + '/S_global_xave_bias_WOA05.png' m6plot.yzplot( sPlot - sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title='''Global zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is True: imgbufs.append(objOut) if stream is None: m6plot.yzcompare(sPlot, sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1='Global zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20, 30, 10, 31, 39, .5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir + '/S_global_xave_bias_WOA05.3_panel.png') # Atlantic + Arctic newMask = 1. * msk newMask[(basin != 2) & (basin != 4)] = 0. sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask) sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask) if stream is True: objOut = io.BytesIO() else: objOut = cmdLineArgs.outdir + '/S_Atlantic_xave_bias_WOA05.png' m6plot.yzplot( sPlot - sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title='''Atlantic zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is True: imgbufs.append(objOut) if stream is None: m6plot.yzcompare(sPlot, sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1='Atlantic zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20, 30, 10, 31, 39, .5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir + '/S_Atlantic_xave_bias_WOA05.3_panel.png') # Pacific newMask = 1. * msk newMask[(basin != 3)] = 0. sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask) sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask) if stream is True: objOut = io.BytesIO() else: objOut = cmdLineArgs.outdir + '/S_Pacific_xave_bias_WOA05.png' m6plot.yzplot( sPlot - sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title='''Pacific zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is True: imgbufs.append(objOut) if stream is None: m6plot.yzcompare(sPlot, sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1='Pacific zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20, 30, 10, 31, 39, .5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir + '/S_Pacific_xave_bias_WOA05.3_panel.png') # Indian newMask = 1. * msk newMask[(basin != 5)] = 0. sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask) sObsPlot, _ = zonalAverage(Sobs, Zobs, area, mask=newMask) if stream is True: objOut = io.BytesIO() else: objOut = cmdLineArgs.outdir + '/S_Indian_xave_bias_WOA05.png' m6plot.yzplot( sPlot - sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title='''Indian zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is True: imgbufs.append(objOut) if stream is None: m6plot.yzcompare(sPlot, sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1='Indian zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20, 30, 10, 31, 39, .5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir + '/S_Indian_xave_bias_WOA05.3_panel.png') if stream is True: return imgbufs
if len(rootGroup.variables[varName].shape)==4: need_time_average = True else: need_time_average = False if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'] else: Zmod = Zobs # Using model z-output ci=m6plot.pmCI(0.1,0.5,.2, 1.0,4.5,1.) # Pacific equator j = numpy.abs( y[:,0] - 0. ).argmin() i0 = numpy.abs( numpy.mod( x[j,:] - 117. + 360., 360. ) ).argmin() i1 = numpy.abs( numpy.mod( x[j,:] + 78. + 360., 360. ) ).argmin() tPlot = rootGroup.variables[varName][0,:,j,i0:i1] tObsPlot = obsRootGroup.variables[OTvar][0,:,j,i0:i1] zi = Zobs[:,j,i0:i1]; z = 0.5 * ( zi[:-1] + zi[1:] ) m6plot.yzplot( tPlot - tObsPlot , x[j,i0:i1][:], zi, ylabel='Longitude', suptitle=rootGroup.title+' '+cmdLineArgs.label, title=r'''Pacific equator $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both') cs1 = plt.contour( x[j,i0:i1][:] + 0*z, z, tObsPlot, levels=numpy.arange(0.,45,2.), colors='k' ); plt.clabel(cs1,fmt='%.0f') cs2 = plt.contour( x[j,i0:i1][:] + 0*z, z, tPlot, levels=numpy.arange(0.,45,2.), colors='g' ); plt.clabel(cs2,fmt='%.0f') plt.ylim(-1200,0) plt.savefig(cmdLineArgs.outdir+'/T_Pacific_equator_bias_WOA05.png') m6plot.yzcompare( tPlot, tObsPlot , x[j,i0:i1], zi, splitscale=[0., -1000., -6500.], suptitle=rootGroup.title+' '+cmdLineArgs.label, ylabel='Longitude', title1=r'Pacific equator $\theta$ [$\degree$C]', title2=r'''WOA'05 $\theta$ [$\degree$C]''', clim=m6plot.linCI(-2,29,.5), colormap='dunneRainbow', extend='max', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir+'/T_Pacific_equator_bias_WOA05.3_panel.png')
ci = m6plot.pmCI(0.025, .45, .05) if len(cmdLineArgs.label1): title1 = cmdLineArgs.label1 else: title1 = rootGroup.title if len(cmdLineArgs.label2): title2 = cmdLineArgs.label2 else: title2 = rootGroupRef.title # Global tPlot, z = zonalAverage(Tmod, Zmod, area) tRefPlot, _ = zonalAverage(Tref, Zref, area) m6plot.yzplot( tPlot - tRefPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=title1 + ' - ' + title2, title=r'''Global zonal-average $\theta$ response [$\degree$C] ''' + cmdLineArgs.label, clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=cmdLineArgs.outdir + '/T_global_xave_response.png') m6plot.yzcompare(tPlot, tRefPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=r'Global zonal-average $\theta$ [$\degree$C] ' + cmdLineArgs.label, title1=title1,
def zonalAverage(T, eta, area, mask=1.): vols = ( mask * area ) * ( eta[:-1] - eta[1:] ) # mask * area * level thicknesses return numpy.sum( vols * T, axis=-1 ) / numpy.sum( vols, axis=-1 ), (mask*eta).min(axis=-1) ci=m6plot.pmCI(0.025,.45,.05) if len(cmdLineArgs.label1): title1 = cmdLineArgs.label1 else: title1 = rootGroup.title if len(cmdLineArgs.label2): title2 = cmdLineArgs.label2 else: title2 = rootGroupRef.title # Global tPlot, z = zonalAverage(Tmod, Zmod, area) tRefPlot, _ = zonalAverage(Tref, Zref, area) m6plot.yzplot( tPlot - tRefPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=title1+' - '+title2, title=r'''Global zonal-average $\theta$ response [$\degree$C] '''+cmdLineArgs.label, clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=cmdLineArgs.outdir+'/T_global_xave_response.png') m6plot.yzcompare( tPlot, tRefPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=r'Global zonal-average $\theta$ [$\degree$C] '+cmdLineArgs.label, title1=title1, title2=title2, clim=m6plot.linCI(-2,29,.5), colormap='dunneRainbow', extend='max', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir+'/T_global_xave_response.3_panel.png') # Atlantic + Arctic newMask = 1.*msk; newMask[ (basin!=2) & (basin!=4) ] = 0. tPlot, z = zonalAverage(Tmod, Zmod, area, mask=newMask) tRefPlot, _ = zonalAverage(Tref, Zref, area, mask=newMask) m6plot.yzplot( tPlot - tRefPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=title1+' - '+title2, title=r'''Atlantic zonal-average $\theta$ response [$\degree$C] '''+cmdLineArgs.label,
) # mask * area * level thicknesses return numpy.sum(vols * S, axis=-1) / numpy.sum(vols, axis=-1), ( mask * eta).min(axis=-1) ci = m6plot.pmCI(0.125, 2.25, .25) # Global sPlot, z = zonalAverage(Smod, Zmod, area) sObsPlot, _ = zonalAverage(Sobs, Zobs, area) m6plot.yzplot( sPlot - sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=rootGroup.title + ' ' + cmdLineArgs.label, title='''Global zonal-average salinity bias (w.r.t. WOA'05) [ppt]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=cmdLineArgs.outdir + '/S_global_xave_bias_WOA05.png') m6plot.yzcompare(sPlot, sObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=rootGroup.title + ' ' + cmdLineArgs.label, title1='Global zonal-average salinity [ppt]', title2='''WOA'05 salinity [ppt]''', clim=m6plot.linCI(20, 30, 10, 31, 39, .5),
def zonalAverage(T, eta, area, mask=1.): vols = ( mask * area ) * ( eta[:-1] - eta[1:] ) # mask * area * level thicknesses return numpy.sum( vols * T, axis=-1 ) / numpy.sum( vols, axis=-1 ), (mask*eta).min(axis=-1) ci=m6plot.pmCI(0.0125,.225,.025) if len(cmdLineArgs.label1): title1 = cmdLineArgs.label1 else: title1 = rootGroup.title if len(cmdLineArgs.label2): title2 = cmdLineArgs.label2 else: title2 = rootGroupRef.title # Global sPlot, z = zonalAverage(Smod, Zmod, area) sRefPlot, _ = zonalAverage(Sref, Zref, area) m6plot.yzplot( sPlot - sRefPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=title1+' - '+title2, title='''Global zonal-average salinity response [ppt] '''+cmdLineArgs.label, clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=cmdLineArgs.outdir+'/S_global_xave_response.png') m6plot.yzcompare( sPlot, sRefPlot , y, z, splitscale=[0., -1000., -6500.], suptitle='Global zonal-average salinity [ppt] '+cmdLineArgs.label, title1=title1, title2=title2, clim=m6plot.linCI(20,30,10, 31,39,.5), colormap='dunneRainbow', extend='both', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir+'/S_global_xave_response.3_panel.png') # Atlantic + Arctic newMask = 1.*msk; newMask[ (basin!=2) & (basin!=4) ] = 0. sPlot, z = zonalAverage(Smod, Zmod, area, mask=newMask) sRefPlot, _ = zonalAverage(Sref, Zref, area, mask=newMask) m6plot.yzplot( sPlot - sRefPlot , y, z, splitscale=[0., -1000., -6500.], suptitle=title1+' - '+title2, title='''Atlantic zonal-average salinity response [ppt] '''+cmdLineArgs.label,
def main(cmdLineArgs, stream=None): if not os.path.exists(cmdLineArgs.gridspec): raise ValueError( 'Specified gridspec directory/tar file does not exist.') if os.path.isdir(cmdLineArgs.gridspec): xcenter = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_hgrid.nc').variables['x'][1::2, 1::2] y = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_hgrid.nc').variables['y'][1::2, 1::2].max( axis=-1) ycenter = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_hgrid.nc').variables['y'][1::2, 1::2] msk = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_mask.nc').variables['mask'][:] area = msk * netCDF4.Dataset( cmdLineArgs.gridspec + '/ocean_hgrid.nc').variables['area'][:, :].reshape( [msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1) depth = netCDF4.Dataset(cmdLineArgs.gridspec + '/ocean_topog.nc').variables['depth'][:] try: basin = netCDF4.Dataset(cmdLineArgs.gridspec + '/basin_codes.nc').variables['basin'][:] except: basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth) elif os.path.isfile(cmdLineArgs.gridspec): xcenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'x')[1::2, 1::2] y = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'y')[1::2, 1::2].max(axis=-1) ycenter = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'y')[1::2, 1::2] msk = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_mask.nc', 'mask')[:] area = msk * m6toolbox.readNCFromTar( cmdLineArgs.gridspec, 'ocean_hgrid.nc', 'area')[:, :].reshape( [msk.shape[0], 2, msk.shape[1], 2]).sum(axis=-3).sum(axis=-1) depth = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'ocean_topog.nc', 'depth')[:] try: basin = m6toolbox.readNCFromTar(cmdLineArgs.gridspec, 'basin_codes.nc', 'basin')[:] except: basin = m6toolbox.genBasinMasks(xcenter, ycenter, depth) else: raise ValueError( 'Unable to extract grid information from gridspec directory/tar file.' ) if stream != None: if len(stream) != 4: raise ValueError( 'If specifying output streams, exactly four (4) streams are needed for this analysis' ) Tobs = netCDF4.Dataset(cmdLineArgs.woa) if 'temp' in Tobs.variables: Tobs = Tobs.variables['temp'] else: Tobs = Tobs.variables['ptemp'] if len(Tobs.shape) == 3: Tobs = Tobs[:] else: Tobs = Tobs[:].mean(axis=0) Zobs = netCDF4.Dataset(cmdLineArgs.woa).variables['eta'][:] rootGroup = netCDF4.MFDataset(cmdLineArgs.annual_file) if 'temp' in rootGroup.variables: varName = 'temp' elif 'ptemp' in rootGroup.variables: varName = 'ptemp' elif 'thetao' in rootGroup.variables: varName = 'thetao' else: raise Exception( 'Could not find "temp", "ptemp" or "thetao" in file "%s"' % (cmdLineArgs.annual_file)) if len(rootGroup.variables[varName].shape) == 4: Tmod = rootGroup.variables[varName][:].mean(axis=0) else: Tmod = rootGroup.variables[varName][:] if 'e' in rootGroup.variables: Zmod = rootGroup.variables['e'][0] else: Zmod = Zobs # Using model z-ou:put def zonalAverage(T, eta, area, mask=1.): vols = (mask * area) * (eta[:-1] - eta[1:] ) # mask * area * level thicknesses return numpy.sum(vols * T, axis=-1) / numpy.sum(vols, axis=-1), ( mask * eta).min(axis=-1) ci = m6plot.pmCI(0.25, 4.5, .5) if cmdLineArgs.suptitle != '': suptitle = cmdLineArgs.suptitle + ' ' + cmdLineArgs.label else: suptitle = rootGroup.title + ' ' + cmdLineArgs.label # Global tPlot, z = zonalAverage(Tmod, Zmod, area) tObsPlot, _ = zonalAverage(Tobs, Zobs, area) if stream != None: objOut = stream[0] else: objOut = cmdLineArgs.outdir + '/T_global_xave_bias_WOA05.png' m6plot.yzplot( tPlot - tObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title= r'''Global zonal-average $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is None: m6plot.yzcompare(tPlot, tObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1=r'Global zonal-average $\theta$ [$\degree$C]', title2=r'''WOA'05 $\theta$ [$\degree$C]''', clim=m6plot.linCI(-2, 29, .5), colormap='dunneRainbow', extend='max', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir + '/T_global_xave_bias_WOA05.3_panel.png') # Atlantic + Arctic newMask = 1. * msk newMask[(basin != 2) & (basin != 4)] = 0. tPlot, z = zonalAverage(Tmod, Zmod, area, mask=newMask) tObsPlot, _ = zonalAverage(Tobs, Zobs, area, mask=newMask) if stream != None: objOut = stream[1] else: objOut = cmdLineArgs.outdir + '/T_Atlantic_xave_bias_WOA05.png' m6plot.yzplot( tPlot - tObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title= r'''Atlantic zonal-average $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is None: m6plot.yzcompare( tPlot, tObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1=r'Atlantic zonal-average $\theta$ [$\degree$C]', title2=r'''WOA'05 $\theta$ [$\degree$C]''', clim=m6plot.linCI(-2, 29, .5), colormap='dunneRainbow', extend='max', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir + '/T_Atlantic_xave_bias_WOA05.3_panel.png') # Pacific newMask = 1. * msk newMask[(basin != 3)] = 0. tPlot, z = zonalAverage(Tmod, Zmod, area, mask=newMask) tObsPlot, _ = zonalAverage(Tobs, Zobs, area, mask=newMask) if stream != None: objOut = stream[2] else: objOut = cmdLineArgs.outdir + '/T_Pacific_xave_bias_WOA05.png' m6plot.yzplot( tPlot - tObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title= r'''Pacific zonal-average $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is None: m6plot.yzcompare(tPlot, tObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1=r'Pacific zonal-average $\theta$ [$\degree$C]', title2=r'''WOA'05 $\theta$ [$\degree$C]''', clim=m6plot.linCI(-2, 29, .5), colormap='dunneRainbow', extend='max', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir + '/T_Pacific_xave_bias_WOA05.3_panel.png') # Indian newMask = 1. * msk newMask[(basin != 5)] = 0. tPlot, z = zonalAverage(Tmod, Zmod, area, mask=newMask) tObsPlot, _ = zonalAverage(Tobs, Zobs, area, mask=newMask) if stream != None: objOut = stream[3] else: objOut = cmdLineArgs.outdir + '/T_Indian_xave_bias_WOA05.png' m6plot.yzplot( tPlot - tObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title= r'''Indian zonal-average $\theta$ bias (w.r.t. WOA'05) [$\degree$C]''', clim=ci, colormap='dunnePM', centerlabels=True, extend='both', save=objOut) if stream is None: m6plot.yzcompare(tPlot, tObsPlot, y, z, splitscale=[0., -1000., -6500.], suptitle=suptitle, title1=r'Indian zonal-average $\theta$ [$\degree$C]', title2=r'''WOA'05 $\theta$ [$\degree$C]''', clim=m6plot.linCI(-2, 29, .5), colormap='dunneRainbow', extend='max', dlim=ci, dcolormap='dunnePM', dextend='both', centerdlabels=True, save=cmdLineArgs.outdir + '/T_Indian_xave_bias_WOA05.3_panel.png')