[MITgcm-support] Barotropic ocean gyre tutorial
Jeremy Miller
jeremysharonmiller at gmail.com
Sun Apr 4 10:21:42 EDT 2021
Dear Oliver,
Thanks. That appears to have worked. The plots I got look similar to the
ones in the tutorial.
I ran Jeff Scott's code in the exact same form (but
with h.astype('>f4').tofile('bathy.bin')
and tau.astype('>f4').tofile('windx_cosy.bin') commented).
I still get a mismatch between the outputs from snippet tauMax*sin(Y*pi)
and np.fromfile('windx_siny.bin',dtype='f4').
Why is that?
Best
Jeremy
On Sun, 4 Apr 2021 at 16:41, Oliver Jahn <jahn at mit.edu> wrote:
> This
>
> [X,Y]=np.meshgrid(x,y,indexing='ij')
>
> should be
>
> [Y,X]=np.meshgrid(y,x,indexing='ij')
>
> (with indexing 'ij' it is y,x, with indexing 'xy' it is x,y)
>
> I am attaching the script from Jeff's pull request where this is all
> done correctly.
>
> Oliver
>
>
> On 2021-04-04 09:00, Jeremy Miller wrote:
> > Dear Oliver,
> >
> > Thanks for coming back to me. I did just that. I now get a plot for
> > "eta" that appears to be two sets of constant values, on the left and
> > right of the line x=0.6*1e6 m (see the attached plot in
> > fig_bar_gyre_windx_siny.png). I also notice that the output bin file
> > (tau_2_1) still shows different values to the original numpy array
> > (tau_2). I have attached the latest version of the python script used to
> > generate the data (gendata_tut4.1.py <http://gendata_tut4.1.py>) and the
> > script used to generate the plots (tut_4.1_plots.py
> > <http://tut_4.1_plots.py>).
> >
> > Best
> > Jeremy
> >
> > On Sun, 4 Apr 2021 at 13:48, Oliver Jahn <jahn at mit.edu
> > <mailto:jahn at mit.edu>> wrote:
> >
> > Hi Jeremy,
> >
> > this will not work:
> >
> > > if sys.byteorder == 'little': tau_2.byteswap(True)
> > > fid = open('windx_siny.bin', 'wb')
> > > tau_2.astype('float32').tofile(fid)
> >
> > Can you instead try Jeff's suggestion:
> >
> > tau_2.astype('>f4').tofile('windx_siny.bin')
> >
> > and NOT use the byteswap command? Mixing byteswap and astype is a
> bad
> > idea as byteswap will create a mismatch between the data in memory
> and
> > numpy's assumption of the data type.
> >
> > Best,
> > Oliver
> >
> >
> > > as you suggested, the plot still came out blank.
> > > Regarding Jeffrey Scott's comment that the reason I could not read
> > back
> > > the bin file was due to a mismatch between float32 and float64, I
> > > followed his advice and read in the
> > > bin file using the snippet
> > >
> > > tau_2_1 = np.fromfile('windx_siny.bin',dtype='float32')
> > >
> > > and I got back an array with every entry being 'inf' except the
> > > penultimate column, being all '0'.
> > >
> > > Is it possible that the snippet
> > >
> > > # X=X.astype('float128')
> > > # Y=Y.astype('float128')
> > >
> > > (which is commented) needs to be included but with 'float128'
> replaced
> > > with 'float32'?
> > >
> > > Best
> > > Jeremy
> > >
> > >
> > >
> > >
> > >
> > > On Thu, 1 Apr 2021 at 16:47, Jan Klaus Rieck
> > <jan.rieck at mail.mcgill.ca <mailto:jan.rieck at mail.mcgill.ca>
> > > <mailto:jan.rieck at mail.mcgill.ca
> > <mailto:jan.rieck at mail.mcgill.ca>>> wrote:
> > >
> > > Hello Jeremy Miller,
> > >
> > > I also use python to to generate input data for the MITgcm. I
> > found
> > > that, to generate files that can be read by the MITgcm
> > consistently,
> > > I needed to specify the type explicitly.
> > > My way of saving the files would look like this in your case:
> > >
> > > if sys.byteorder == 'little': tau_2.byteswap(True)
> > > fid = open(''windx_siny.bin', 'wb')
> > > tau_2.astype('float32').tofile(fid)
> > >
> > > Of course, 'float32' could be replaced by 'float64' if you
> require
> > > double precision.
> > >
> > > I hope this helps,
> > > Jan Rieck
> > >
> > > On Thu, 2021-04-01 at 10:22 +0300, Jeremy Miller wrote:
> > >> Dear MITGCM forum,
> > >>
> > >> I am Jeremy Miller, I am new to MITgcm and I've been going
> > through
> > >> the tutorials. I have a question about the "Barotropic Ocean
> > Gyre"
> > >> tutorial (section 4.1).
> > >>
> > >> I managed to compile and run the code, and re-produce the
> first
> > >> two plots shown in section 4.1.5 for wind stress of τ = τ0
> cos(
> > >> πy/Ly), for both the advection and non-advection cases (with
> the
> > >> provided input binary files).
> > >> I ran into problems when trying to produce the third plot,
> > for the
> > >> case where τ = τ0 sin( πy/Ly). I am a python user, so I
> > translated
> > >> gendata.m into python to write the input binary
> > >> files 'windx_cosy.bin' 'windx_siny.bin' (see the file
> > >> gendata_tut4.1py attached). As explained in section 3.9 I've
> > >> included the snippet
> > >>
> > >> if sys.byteorder == 'little': tau_2.byteswap(True)
> > >>
> > >> where "tau2" is the array to be output. There was no issue in
> the
> > >> cosine wind stress, and I managed to reproduce the results
> that I
> > >> got with the original 'windx_cosy.bin' provided in the
> tutorial.
> > >> However, with the sine wind stress case, the output in
> > >> 'Eta.0000077760.001.001' is all zeros.
> > >>
> > >> When I attempt to read 'windx_siny.bin' with python into a
> new
> > >> array called tau2_1. I get absurdly big numbers back, which
> > do not
> > >> match the original array tau2 that I created. If I Remove the
> > >> snippet " if sys.byteorder == 'little': tau_2.byteswap(True)
> > ", in
> > >> the python gendata code, tau2_1 and tau2 match. But, then
> when I
> > >> run the code again, the file output.txt contains a long list
> > of NaNs.
> > >>
> > >> I have also included the python code used to generate the
> > plots in
> > >> the file tut_4.1_plots.py <http://tut_4.1_plots.py>
> > <http://tut_4.1_plots.py/>
> > >>
> > >> Look forward to hearing from you.
> > >> Yours sincerely
> > >> Jeremy Miller
> > >> _______________________________________________
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