def test_basic(self):
lo = np.array([1, 2])
hi = np.array([3, 4])
ans = np.array([1, 2, 2, 3])
assert np.array_equal(mcolon(lo, hi), ans)
def test_stride(self):
lo = np.array([1, 2])
hi = np.array([6, 14])
s = np.array([2, 3])
ans = np.array([1,3,5, 2,5,8,11])
assert np.array_equal(mcolon(lo, hi, s), ans)
def boundaryFaceIndices(G, side, I0, I1, I2):
"""
Retrieve face indices belonging to a subset of global outer faces.
Synopsis:
ix = boundaryFaceIndices(G, side, I0, I1, I2)
Arguments:
G (Grid):
pyrst.gridprocessing.Grid
side (str):
Global side from which to extract face indices. String. Must (case
insensitively) match one of six alias groups:
0) ["west", "xmin", "left" ]
1) ["east", "xmax", "right" ]
2) ["south", "ymin", "back" ]
3) ["north", "ymax", "front" ]
4) ["upper", "zmin", "top" ]
5) ["lower", "zmax", "bottom"]
These groups correspond to the cardinal directions mentiond as the
first alternative in each group.
I0, I1 (list or ndarray):
Index ranges for local (in-plane) axes one and two, respectively.
No index range given (I1 or I2 is None) is interpreted as covering
the entire corresponding local axis of `side` in the grid `G`. The
local axes on a side in G are ordered `X` before `Y` before `Z`.
I2 (list or ndarray):
Index range for global axis perpendicular to `side`. The primary
purpose of this parameter is to exclude faces *within* a reservoir
from being added to the return value `ix`. Such faces typically
occur in faulted reservoirs where a given face may be considered
external by virtue of being connected to a single reservoir cell
only.
Returns:
ix - Required face indices as a column array.
Note:
This function is mainly intended for internal use in this file. Its
calling interface may change more frequently than functions in the
BoundaryCondition class.
See also:
prst.params.wells_and_bc.BoundaryCondition
"""
try:
I0 = I0.ravel()
except AttributeError:
pass
try:
I1 = I1.ravel()
except AttributeError:
pass
try:
I2 = I2.ravel()
except AttributeError:
pass
## Extract all faces of cells within the given subset.
cells, faceTag, isOutF = _boundaryCellsSubset(G, side, I0, I1, I2)
fIX = G.cells.facePos
hfIX = mcolon(fIX[cells], fIX[cells + 1])
faces = G.cells.faces[hfIX, 0]
tags = G.cells.faces[hfIX, 1]
ix = faces[np.logical_and(isOutF[faces], tags == faceTag)]
# return as column array
return ix[:, np.newaxis]
