Field

class ESMF.Field

__del__()

Release the memory associated with a Field.

Required Arguments:

None

Optional Arguments:

None

Returns:

None

static __new__(*args, **kwargs)

Create a Field from a Grid or Mesh.

Required Arguments:

grid: either a Grid or a Mesh with coordinates allocated on

at least one stagger location.

name: user friendly name for the Grid or Mesh.

Optional Arguments:

typekind: the type of the Field data.

Argument values are:

TypeKind.I4

TypeKind.I8

TypeKind.R4

(default) TypeKind.R8

staggerloc: the stagger location on which to locate the

Field data, only specify this argument when using a Grid.

Argument values are:

2D:

(default) StaggerLoc.CENTER

StaggerLoc.EDGE1

StaggerLoc.EDGE2

StaggerLoc.CORNER

3D:

(default) StaggerLoc.CENTER_VCENTER

StaggerLoc.EDGE1_VCENTER

StaggerLoc.EDGE2_VCENTER

StaggerLoc.CORNER_VCENTER

StaggerLoc.CENTER_VFACE

StaggerLoc.EDGE1_VFACE

StaggerLoc.EDGE2_VFACE

meshloc: the mesh location on which to locate the Field

data, only specify this argument when using a Mesh.

Argument values are:

(default) MeshLoc.NODE

MeshLoc.ELEMENT

grid_to_field_map: A numpy array (internally cast to

dtype=numpy.int32) which specifies a mapping from the dimensions of the grid to those of the field.

type: np.array

shape: [number of gridded dimensions, 1]

ungridded_lower_bound: A numpy array (internally cast to

dtype=numpy.int32) which specifies the lower bounds of the ungridded dimensions of the field.

type: np.array

shape: [number of ungridded dimensions, 1]

ungridded_upper_bound: A numpy array (internally cast to

dtype=numpy.int32) which specifies the upper bounds of the ungridded dimensions of the field.

type: np.array

shape: [number of ungridded dimensions, 1]

mask_values: A Python list of integer values to use for masking.

type: Python list

shape: [grid.shape, 1]

Returns:

Field

get_area()

Initialize a Field with the areas of the cells of the underlying Grid or Mesh.

Required Arguments:

None

Optional Arguments:

None

Returns:

None