Fields

import mefikit as mf
import numpy as np
import pyvista as pv

pv.set_plot_theme("dark")
pv.set_jupyter_backend("static")

Field expressions

FieldExpr are composition of floats and mf.sel.field(“fieldname”) or custom fields :

field(“toto”) * field(“tata”)
field(“toto”) + field(“tata”)
field(“toto”) - field(“tata”)
field(“toto”) / field(“tata”)
field(“toto”) ** field(“tata”)
field(“toto”).dot(field(“tata”))
field(“toto”) @ field(“tata”)
sin(field(“toto”))
cos(field(“toto”))
abs(field(“toto”))
log(field(“toto”))
log10(field(“toto”))
exp(field(“toto”))
field(“toto”)[0]
normals()
x()
y()
z()
centroids()

x = np.logspace(-5, 0.0, 1000)
mesh2 = mf.build_cmesh(x, x)

mesh2.measure_update()

mesh2.to_pyvista().plot()

png

m = mf.Field("Measure")

Field operations evaluation

mesh2.eval_update("4 * M2", m * m * 4.0)

mesh2.to_pyvista().plot()

png

mesh2.fields()

{'4 * M2': {'QUAD4': array([7.22038631e-28, 7.38874101e-28, 7.56102117e-28, ...,
         6.58446349e-08, 6.73799065e-08, 6.89509753e-08], shape=(998001,))},
 'Measure': {'QUAD4': array([1.34353883e-14, 1.35911194e-14, 1.37486555e-14, ...,
         1.28301047e-04, 1.29788199e-04, 1.31292589e-04], shape=(998001,))}}

m2 = mf.Field("4 * M2")
mesh2.eval(m2 - 4.0 * m.square())

{'QUAD4': array([0., 0., 0., ..., 0., 0., 0.], shape=(998001,))}

How does it work ?

print(4.0 * m * m)

BinarayExpr {
    operator: Mul,
    left: BinarayExpr {
        operator: Mul,
        left: Array(
            4.0, shape=[], strides=[], layout=CFcf (0xf), dynamic ndim=0,
        ),
        right: Field(
            "Measure",
        ),
    },
    right: Field(
        "Measure",
    ),
}

Why is it awesome ?

This enables two patterns :

reusability and composition of filters
evaluation optimizations, some selection filters are evaluated in parallel, some are evaluated first if they are discriminant

Field to Selection

Fields can be converted to threshold selections :

th = (m > 3.25e-5) & (m < 1e-4)

m2sel = mesh2.select(th)
pvm2: pv.UnstructuredGrid = m2sel.to_pyvista()
pvm2.active_scalars_name = "Measure"
pvm2.plot()

png

Thoses threasholds selections can be combined with other selections.

r = mf.sel.rect([0.25, 0.25], [0.7, 0.7])
c = mf.sel.circle([0.875, 0.875], 0.05)

mesh2.select((m2 > 4e-9) - r - c).to_pyvista().plot()

png