[yt-users] Normalized axis

Sushilkumar sushil.sush19us at gmail.com
Fri Jun 9 07:08:36 PDT 2017


Dear yt

How do I label the axis of a plot in normalized values?

On my plot I want to label my x and y axis in terms of the vertical line.

Do I use convert_to_plot under streamlines?

Link to the plot and script is below

https://drive.google.com/open?id=0B4g8shg4DL7oak5PLWVVdG5UMHc

Thanks in advance



On Thu, Jun 8, 2017 at 1:01 PM, <yt-users-request at lists.spacepope.org>
wrote:

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> Today's Topics:
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>    1. Re: selecting data by refinement level (Klaus Weide)
>    2. Re: selecting data by refinement level (Matthew Turk)
>    3. Re: selecting data by refinement level (Nathan Goldbaum)
>    4. Re: selecting data by refinement level (Klaus Weide)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Wed, 7 Jun 2017 13:53:49 -0500 (CDT)
> From: Klaus Weide <klaus at flash.uchicago.edu>
> To: Discussion of the yt analysis package
>         <yt-users at lists.spacepope.org>
> Subject: Re: [yt-users] selecting data by refinement level
> Message-ID: <Pine.LNX.4.64.1706071350010.1322 at flash.uchicago.edu>
> Content-Type: TEXT/PLAIN; charset=US-ASCII
>
> On Wed, 7 Jun 2017, Matthew Turk wrote:
>
> > Hi Klaus,
> >
> > Whoops, I said "grid_collection" but I meant "data_collection".
>
> Thanks Matt. I have not tried the 'collection of grids' approach yet, but
> the following does what I want:
>
>         ds = yt.load(dump_path)
>
>         ad = ds.all_data()
>         if fine_only:
>             maxreflevel = ad.index.grid_levels.max()
>             print '*** Filtering data so that only FLASH refinement level
> {} cells are used'.format(maxreflevel+1)
>             ad.min_level = maxreflevel
>             ad.max_level = maxreflevel
>             print 'These cover a volume of %s' % ad['cell_volume'].sum()
>         # .....
>         data = {}
>         data['dens'] = ad['dens'].to_ndarray()
>         # .....
>
>
> Klaus
>
>
> ------------------------------
>
> Message: 2
> Date: Wed, 7 Jun 2017 13:56:51 -0500
> From: Matthew Turk <matthewturk at gmail.com>
> To: Discussion of the yt analysis package
>         <yt-users at lists.spacepope.org>
> Subject: Re: [yt-users] selecting data by refinement level
> Message-ID:
>         <CALO3=5HbBWfPj8hf5KEwMq1CiU932Q_u+=hHcBzYirQzGYCm3A at mail.
> gmail.com>
> Content-Type: text/plain; charset="UTF-8"
>
> Great!  As a quick note, you can use `.d` as shorthand for
> `to_ndarray()`.  The YTArray it returns is a subclass of ndarray, so
> should in general be usable in both ways; as you probably figured out,
> if you do any manipulation of individual elements it adds overhead and
> (often frustrating, but hopefully ultimately helpful), restrictions on
> combining incorrect units unless you look at it as a strict ndarray.
>
> On Wed, Jun 7, 2017 at 1:53 PM, Klaus Weide <klaus at flash.uchicago.edu>
> wrote:
> > On Wed, 7 Jun 2017, Matthew Turk wrote:
> >
> >> Hi Klaus,
> >>
> >> Whoops, I said "grid_collection" but I meant "data_collection".
> >
> > Thanks Matt. I have not tried the 'collection of grids' approach yet, but
> > the following does what I want:
> >
> >         ds = yt.load(dump_path)
> >
> >         ad = ds.all_data()
> >         if fine_only:
> >             maxreflevel = ad.index.grid_levels.max()
> >             print '*** Filtering data so that only FLASH refinement
> level {} cells are used'.format(maxreflevel+1)
> >             ad.min_level = maxreflevel
> >             ad.max_level = maxreflevel
> >             print 'These cover a volume of %s' % ad['cell_volume'].sum()
> >         # .....
> >         data = {}
> >         data['dens'] = ad['dens'].to_ndarray()
> >         # .....
> >
> >
> > Klaus
> > _______________________________________________
> > yt-users mailing list
> > yt-users at lists.spacepope.org
> > http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
>
>
> ------------------------------
>
> Message: 3
> Date: Wed, 7 Jun 2017 12:00:44 -0700
> From: Nathan Goldbaum <nathan12343 at gmail.com>
> To: Discussion of the yt analysis package
>         <yt-users at lists.spacepope.org>
> Subject: Re: [yt-users] selecting data by refinement level
> Message-ID:
>         <CAJXewO=gk4Fqrh_fKxmgKVu9vgu53TVQd0P0-Ra5wBBSPm-_Gg at mail.
> gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> On Wed, Jun 7, 2017 at 11:56 AM, Matthew Turk <matthewturk at gmail.com>
> wrote:
>
> > Great!  As a quick note, you can use `.d` as shorthand for
> > `to_ndarray()`.  The YTArray it returns is a subclass of ndarray, so
> > should in general be usable in both ways; as you probably figured out,
> > if you do any manipulation of individual elements it adds overhead and
> > (often frustrating, but hopefully ultimately helpful), restrictions on
> > combining incorrect units unless you look at it as a strict ndarray.
> >
>
> One tiny note:
>
> YTArray.d is short for YTArray.ndarray_view(), which returns a view onto
> the array. This doesn't copy the underlying data.
>
> YTArray.to_ndarray() is equivalend to YTArray.value or YTArray.v, whcih
> returns an ndarray containing a copy of the underlying array data. Getting
> a copy sometimes adds overhead.
>
> Choosing whether or now you want a copy comes down to what exactly you are
> doing, since copying adds overhead, but it also prevents silently
> overwriting data in an unexpected, nonlocal fashion.
>
>
> >
> > On Wed, Jun 7, 2017 at 1:53 PM, Klaus Weide <klaus at flash.uchicago.edu>
> > wrote:
> > > On Wed, 7 Jun 2017, Matthew Turk wrote:
> > >
> > >> Hi Klaus,
> > >>
> > >> Whoops, I said "grid_collection" but I meant "data_collection".
> > >
> > > Thanks Matt. I have not tried the 'collection of grids' approach yet,
> but
> > > the following does what I want:
> > >
> > >         ds = yt.load(dump_path)
> > >
> > >         ad = ds.all_data()
> > >         if fine_only:
> > >             maxreflevel = ad.index.grid_levels.max()
> > >             print '*** Filtering data so that only FLASH refinement
> > level {} cells are used'.format(maxreflevel+1)
> > >             ad.min_level = maxreflevel
> > >             ad.max_level = maxreflevel
> > >             print 'These cover a volume of %s' %
> ad['cell_volume'].sum()
> > >         # .....
> > >         data = {}
> > >         data['dens'] = ad['dens'].to_ndarray()
> > >         # .....
> > >
> > >
> > > Klaus
> > > _______________________________________________
> > > yt-users mailing list
> > > yt-users at lists.spacepope.org
> > > http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
> > _______________________________________________
> > yt-users mailing list
> > yt-users at lists.spacepope.org
> > http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org
> >
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> ------------------------------
>
> Message: 4
> Date: Wed, 7 Jun 2017 14:45:52 -0500 (CDT)
> From: Klaus Weide <klaus at flash.uchicago.edu>
> To: Discussion of the yt analysis package
>         <yt-users at lists.spacepope.org>
> Subject: Re: [yt-users] selecting data by refinement level
> Message-ID: <Pine.LNX.4.64.1706071443510.1322 at flash.uchicago.edu>
> Content-Type: TEXT/PLAIN; charset=US-ASCII
>
> On Wed, 7 Jun 2017, Nathan Goldbaum wrote:
> > On Wed, Jun 7, 2017 at 11:56 AM, Matthew Turk <matthewturk at gmail.com>
> wrote:
> >
> > > Great!  As a quick note, you can use `.d` as shorthand for
> > > `to_ndarray()`.
>
> > One tiny note:
> >
> > YTArray.d is short for YTArray.ndarray_view(), which returns a view onto
> > the array. This doesn't copy the underlying data.
>
> Matt and Nathan,
>
> Thanks for the additional info, I think it's very useful to know.
>
> Klaus
>
>
> ------------------------------
>
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> ------------------------------
>
> End of yt-users Digest, Vol 112, Issue 5
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