[yt-users] Inspecting gradient of a field at boundary

[Nathan Goldbaum]

Hi Tazkera,

I think what's happening is that the gradient is getting periodically
wrapped. It helps if you take a look at a SlicePlot of your 'psi' and
'psi_gradient_x' fields:

psi: http://i.imgur.com/EK73NNO.png
psi_gradient_x: http://i.imgur.com/wXPpqi9.png

The gradient at the left and right edges of the domain is being calculated
using the periodically wrapped values (i.e. the local difference between
neighboring values of the psi field shoots up from 1 in the middle of the
domain to 12 at the edges). This causes the gradient to have different
values at the edges of the domain.

I guess you are looking for a gradient field that uses forward differences
on the left side of the domain and backward differences on the right side
of the domain rather than being periodically wrapped? Unfortunately right
now yt doesn't have an option to specify that. That said, I think it would
be possible to do e.g. by adding a new keyword argument to
Datset.add_gradient_field and then adding the new difference logic to the
setup_gradient_fields function in yt/fields/fluid_fields.py.

Hope that helps,

Nathan

On Thu, May 18, 2017 at 10:15 AM, tazkera haque <h.tazkera at gmail.com> wrote:

> Hi people,
>
> I am trying to define curl of a vector field in yt, but first I needed to
> see if correct derivatives are taken at the boundary. I am starting with a
> mock data set and followed yt tutorial:
>
> import yt
> from yt import YTArray
> import numpy as np
>
> posx = np.linspace(-1.0,1.0,12)
> posy = np.linspace(-1.0,1.0,12)
> posz = np.linspace(-1.0,1.0,12)
>
> X, Y, Z = np.meshgrid(posx, posy, posz, indexing='ij') # From gradient
> output, yt seems to use ij indexing
>
> psi = X
>
> data_dict = {"psi":(psi,'kg/cm**3'),
>             "number_of_particles":12,
>             "particle_position_x":(posx, 'kg/cm**3'),
>             "particle_position_y":(posy, 'kg/cm**3'),
>             "particle_position_z":(posz, 'kg/cm**3')}
>
> bbox = np.array([[-1.0, 1.0], [-1.0, 1.0], [-1.0, 1.0]])
>
> y  = yt.load_uniform_grid(data_dict,domain_dimensions=(12,12,12),
> bbox=bbox)
>
> grad_fields = y.add_gradient_fields(("stream","psi"))
>
> ad = y.all_data()
>
> print( ad["psi_gradient_x"] )
> print( ad["psi_gradient_y"] )
> print( ad["psi_gradient_z"] )
>
> Output:
> yt : [INFO     ] 2017-05-17 19:40:16,410 Parameters: current_time
>      = 0.0
> yt : [INFO     ] 2017-05-17 19:40:16,410 Parameters: domain_dimensions
>     = [12 12 12]
> yt : [INFO     ] 2017-05-17 19:40:16,411 Parameters: domain_left_edge
>      = [-1. -1. -1.]
> yt : [INFO     ] 2017-05-17 19:40:16,411 Parameters: domain_right_edge
>     = [ 1.  1.  1.]
> yt : [INFO     ] 2017-05-17 19:40:16,412 Parameters:
> cosmological_simulation   = 0.0
> [-5.45454545 -5.45454545 -5.45454545 ..., -5.45454545 -5.45454545
>  -5.45454545] kg/cm**4
> [ 0.  0.  0. ...,  0.  0.  0.] kg/cm**4
> [ 0.  0.  0. ...,  0.  0.  0.] kg/cm**4
>
>
> Now my question is, since psi(x,y,z) = x, the gradient should be
> (1,0,0)...and it is everywhere except the boundaries of the box. Can you
> please explain to me what is going wrong here? I don't
>    think YT is interpreting the bbox and grid points as I am.
>
> Best
>
>
>
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>
>
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