Advanced yt visualization, for developers (for plotfiles)

This sections contains yt commands for advanced users. The Particle-In-Cell methods uses a staggered grid (see The electromagnetic Particle-In-Cell method), so that the x, y, and z components of the electric and magnetic fields are all defined at different locations in space. Regular output (see the Visualization with yt (for plotfiles) page, or the notebook at WarpX/Tools/Visualization.ipynb for an example) returns cell-centered data for convenience, which involves an additional operation. It is sometimes useful to access the raw data directly. Furthermore, the WarpX implementation for mesh refinement contains a number of grids for each level (coarse, fine and auxilary, see ../theory/warpx_theory for more details), and it is sometimes useful to access each of them (regular output return the auxiliary grid only). This page provides information to read raw data of all grids.

Dump additional data

In order to dump additional data in WarpX (mostly for debugging purpose), run the simulation with parameters

warpx.plot_raw_fields = 1
warpx.plot_finepatch = 1
warpx.plot_crsepatch = 1
warpx.plot_dive = 1
warpx.plot_rho = 1

see Input parameters for more information on these parameters.

Read raw data

Meta-data relevant to this topic (number and locations of grids in the simulation) are accessed to with

import yt
# get yt dataset
ds = yt.load( './plotfiles/plt00004' )
# Index of data in the plotfile
ds_index = ds.index
# Print the number of grids in the simulation
ds_index.grids.shape
# Left and right physical boundary of each grid
ds_index.grid_left_edge
ds_index.grid_right_edge
# List available fields
ds.field_list

When warpx.plot_raw_fields=1 and warpx.plot_finepatch=1, here are some useful commands to access properties of a grid and the Ex field on the fine patch:

# store grid number 2 into my_grid
my_grid = ds.index.grids[2]
# Get left and right edges of my_grid
my_grid.LeftEdge
my_grid.RightEdge
# Get Level of my_grid
my_grid.Level
# left edge of the grid, in number of points
my_grid.start_index

Return the Ex field on the fine patch of grid my_grid:

my_field = my_grid['raw', 'Ex_fp'].squeeze().v

For a 2D plotfile, my_field has shape (nx,nz,2). The last component stands for the two values on the edges of each cell for the electric field, due to field staggering. Numpy function squeeze removes empty components. While yt arrays are unit-aware, it is sometimes useful to extract the data into unitless numpy arrays. This is achieved with .v. In the case of Ex_fp, the staggering is on direction x, so that my_field[:,:-1,1] == my_field[:,1:,0].

All combinations of the fields (E or B), the component (x, y or z) and the grid (_fp for fine, _cp for coarse and _aux for auxiliary) can be accessed in this way, i.e., my_grid['raw', 'Ey_aux'] or my_grid['raw', 'Bz_cp'] are valid queries.