low-level API¶
Grid generation¶
-
cem_gridtools.gridgen(x, y, beta, ni, nj, ulidx=0)¶ This is the low-level interface function to the gridgen-c library.
For general use, see
cem_gridtools.cem_gridtools.CGrid.gen_grid()- Parameters
x (array) – x boundary points
y (array) – y boundary values
b (array) – beta values (corner status)
ni (int) – Number of required grid points in the i-direction
nj (int) – Number of required grid points in the j-direction
ulidx (int) – The idx of the upper left corner of the grid
- Returns
(gx,gy) output 2d arrays
- Return type
tuple
import numpy
from cem_gridtools.gridgen import gridgen
# Note that the ordering is important to make a 'simple' shape
x = numpy.array([0, 1, 1, 0], dtype='d')
y = numpy.array([0, 0, 1, 1], dtype='d')
beta = numpy.ones(x.shape, dtype='d')
(gx,gy) = gridgen(x,y,beta,3,2,0)
Interpolation¶
-
cem_gridtools.grid_interp.init(x, y, z, rule)¶ Initialises the interpolation routine with the given source data
- Parameters
x (array) – x values of input data
y (array) – y values of input data
z (array) – input data values
rule (str) – interpolation type (“nn_sibson, nn_non_sibson”)
- Returns
handle of interpolant
- Return type
void pointer
-
cem_gridtools.grid_interp.on_point(h, x, y)¶ Perform the interpolation on the given point
- Parameters
h – handle from output of the init function
x (float) – target x value
y (float) – target y value
- Returns
interpolated value
- Return type
float
import numpy
from cem_gridtools.grid_interp import init,on_point
x = numpy.array([0, 1, 0.4], dtype='d')
y = numpy.array([0, 0.2, 0.8], dtype='d')
z = numpy.array([1, 2, 3], dtype='d')
H = init(x,y,z,"nn_sibson")
# Now interpolate on any point
v = on_point(H, 0.5, 0.2)