AbstractGrid

class plasmapy.plasma.grids.AbstractGrid(*seeds, num=100, **kwargs)

Bases: abc.ABC

Abstract grid represents a 3D grid of positions. The grid is stored as an np.ndarray, while the units associated with each dimension are stored separately.

Attributes Summary

ax0

First axis of the grid, only valid for uniform grids

ax1

Second axis of the grid, only valid for uniform grids

ax2

Third axis of the grid, only valid for uniform grids

dax0

Grid step size along axis ax0, only valid for uniform grids.

dax1

Grid step size along axis ax1, only valid for uniform grids.

dax2

Grid step size along axis ax2, only valid for uniform grids.

grid

A single grid of vertex positions of shape (N0, N1, N2, 3)

grid_resolution

A scalar estimate of the grid resolution.

grids

Three grids of vertex positions (in each coordinate), each having shape (N0, N1, N2)

interpolator

A nearest-neighbor interpolator that returns the nearest grid index to a position.

pts0

Array of positions in dimension 1

pts1

Array of positions in dimension 2

pts2

Array of positions in dimension 3

quantities

A list of the keys corresponding to the quantities currently defined on the grid.

recognized_quantities

A dictionary of standard key names representing particular physical quantities.

shape

Shape of the grid

unit

The unit for the entire grid.

unit0

Unit of dimension 1

unit1

Unit of dimension 2

unit2

Unit of dimension 3

units

Returns a list of the units of each dimension

Methods Summary

add_quantities(**kwargs)

Adds a quantity to the dataset as a new DataArray

interpolate_indices(pos)

Interpolate the nearest grid indices to a position using a nearest-neighbor interpolator

nearest_neighbor_interpolator(pos, *args[, …])

Interpolate values on the grid using a nearest-neighbor scheme with no higher-order weighting.

on_grid(pos)

Given a list of positions, determines which are in the region bounded by the grid points.

vector_intersects(p1, p2)

Returns True if the vector from p1 to p2 intersects the grid.

volume_averaged_interpolator(pos, *args[, …])

Interpolate values on the grid using a volume-averaged scheme with no higher-order weighting.

Attributes Documentation

ax0

First axis of the grid, only valid for uniform grids

Raises

ValueError – If grid is non-uniform.

ax1

Second axis of the grid, only valid for uniform grids

Raises

ValueError – If grid is non-uniform.

ax2

Third axis of the grid, only valid for uniform grids

Raises

ValueError – If grid is non-uniform.

dax0

Grid step size along axis ax0, only valid for uniform grids.

Raises

ValueError – If grid is non-uniform.

dax1

Grid step size along axis ax1, only valid for uniform grids.

Raises

ValueError – If grid is non-uniform.

dax2

Grid step size along axis ax2, only valid for uniform grids.

Raises

ValueError – If grid is non-uniform.

grid

A single grid of vertex positions of shape (N0, N1, N2, 3)

Only defined for grids for which the unit property is defined.

grid_resolution

A scalar estimate of the grid resolution.

For uniform grids, this is the minima of [dax0, dax1, dax2].

For non-uniform grids, it is the closest spacing between any two points.

grids

Three grids of vertex positions (in each coordinate), each having shape (N0, N1, N2)

interpolator

A nearest-neighbor interpolator that returns the nearest grid index to a position.

pts0

Array of positions in dimension 1

pts1

Array of positions in dimension 2

pts2

Array of positions in dimension 3

quantities

A list of the keys corresponding to the quantities currently defined on the grid.

recognized_quantities

A dictionary of standard key names representing particular physical quantities. Using these keys allows these quantities to be recognized automatically by other PlasmaPy functions. Each entry contains a tuple containing a description and the unit associated with the quantity.

shape

Shape of the grid

unit

The unit for the entire grid. Only valid if all dimensions of the grid have the same units.

Raises

ValueError – If all grid dimensions do not have identical units.

unit0

Unit of dimension 1

unit1

Unit of dimension 2

unit2

Unit of dimension 3

units

Returns a list of the units of each dimension

Methods Documentation

add_quantities(**kwargs)

Adds a quantity to the dataset as a new DataArray

Parameters
  • key – The key will be used as the dataset key, while the array holds the quantity.

  • pairs as keyword arguments (array) – The key will be used as the dataset key, while the array holds the quantity.

Returns

Return type

None.

interpolate_indices(pos: Union[numpy.ndarray, astropy.units.quantity.Quantity])

Interpolate the nearest grid indices to a position using a nearest-neighbor interpolator

Parameters

pos (np.ndarray or u.Quantity array, shape (n,3)) – An array of positions in space, where the second dimension corresponds to the three dimensions of the grid. If an np.ndarray is provided, units will be assumed to match those of the grid.

Returns

i – An array of indices corresponding to the positions such that i[n,:] = ix,iy,iz such that grid[ix,iy,iz,:] ~ pos[n,:]

Return type

np.ndarray, shape (n,3)

nearest_neighbor_interpolator(pos: Union[numpy.ndarray, astropy.units.quantity.Quantity], *args, persistent=False)

Interpolate values on the grid using a nearest-neighbor scheme with no higher-order weighting.

Parameters
  • pos (np.ndarray or u.Quantity array, shape (n,3)) – An array of positions in space, where the second dimension corresponds to the three dimensions of the grid. If an np.ndarray is provided, units will be assumed to match those of the grid.

  • *args (str) – Strings that correspond to DataArrays in the dataset

  • persistent (bool) – If true, the interpolator will assume the grid and its contents have not changed since the last interpolation. This substantially speeds up the interpolation when many interpolations are performed on the same grid in a loop. persistent overrides to False if the arguments list has changed since the last call.

on_grid(pos)

Given a list of positions, determines which are in the region bounded by the grid points.

For non-uniform grids, “on grid” is defined as being bounded by grid points in all axes.

Parameters

pos (np.ndarray or u.Quantity array, shape (n,3)) – An array of positions in space, where the second dimension corresponds to the three dimensions of the grid.

vector_intersects(p1, p2)

Returns True if the vector from p1 to p2 intersects the grid. Otherwise, returns false. This is a standard ray-box intersection algorithm.

volume_averaged_interpolator(pos: Union[numpy.ndarray, astropy.units.quantity.Quantity], *args, persistent=False)

Interpolate values on the grid using a volume-averaged scheme with no higher-order weighting.

Parameters
  • pos (np.ndarray or u.Quantity array, shape (n,3)) – An array of positions in space, where the second dimension corresponds to the three dimensions of the grid. If an np.ndarray is provided, units will be assumed to match those of the grid.

  • *args (str) – Strings that correspond to DataArrays in the dataset

  • persistent (bool) – If true, the interpolator will assume the grid and its contents have not changed since the last interpolation. This substantially speeds up the interpolation when many interpolations are performed on the same grid in a loop. persistent overrides to False if the arguments list has changed since the last call.