def test_plot_point_cloud_2d_large(self):
spheres = PointCloud(
Sphere(wrap([(2, 4), (9, 8), (7, 8)], instance('points'),
channel('vector')),
radius=1))
cells = PointCloud(
geom.pack_dims(
CenteredGrid(0, 0, x=3, y=3, bounds=Box[4:6, 2:4]).elements,
'x,y', instance('points')))
cloud = field.stack([spheres, cells], instance('stack'))
self._test_plot(cloud)
def test_plot_point_cloud_2d(self):
spheres = PointCloud(
Sphere(wrap([(.2, .4), (.9, .8), (.7, .8)], instance('points'),
channel('vector')),
radius=.1))
cells = PointCloud(
geom.pack_dims(
CenteredGrid(0, 0, x=3, y=3,
bounds=Box[.4:.6, .2:.4]).elements, 'x,y',
instance('points')))
cloud = field.stack([spheres, cells], instance('stack'))
self._test_plot(cloud)
def points(self,
points: Tensor or Number or tuple or list,
values: Tensor or Number = None,
radius: Tensor or float or int or None = None,
extrapolation: math.Extrapolation = math.extrapolation.ZERO,
color: str or Tensor or tuple or list or None = None) -> PointCloud:
"""
Create a `phi.field.PointCloud` from the given `points`.
The created field has no channel dimensions and all points carry the value `1`.
Args:
points: point locations in physical units
values: (optional) values of the particles, defaults to 1.
radius: (optional) size of the particles
extrapolation: (optional) extrapolation to use, defaults to extrapolation.ZERO
color: (optional) color used when plotting the points
Returns:
`phi.field.PointCloud` object
"""
extrapolation = extrapolation if isinstance(extrapolation, math.Extrapolation) else self.boundaries[extrapolation]
if radius is None:
radius = math.mean(self.bounds.size) * 0.005
# --- Parse points: tuple / list ---
if isinstance(points, (tuple, list)):
if len(points) == 0: # no points
points = math.zeros(instance(points=0), channel(vector=1))
elif isinstance(points[0], Number): # single point
points = math.tensor([points], instance('points'), channel('vector'))
else:
points = math.tensor(points, instance('points'), channel('vector'))
elements = Sphere(points, radius)
if values is None:
values = math.tensor(1.)
return PointCloud(elements, values, extrapolation, add_overlapping=False, bounds=self.bounds, color=color)
def test_plot_multiple(self):
grid = CenteredGrid(Noise(batch(b=2)), 0, Box[0:1, 0:1], x=50, y=10)
grid2 = CenteredGrid(grid, 0, Box[0:2, 0:1], x=20, y=50)
points = wrap([(.2, .4), (.9, .8)], instance('points'),
channel('vector'))
cloud = PointCloud(Sphere(points, radius=0.1), bounds=Box(0, [1, 1]))
titles = math.wrap([['b=0', 'b=0', 'points'], ['b=1', 'b=1', '']],
spatial('rows,cols'))
self._test_plot(grid, grid2, cloud, row_dims='b', title=titles)
def test_convert_point_cloud(self):
loc = math.random_uniform(instance(points=4), channel(vector=2))
val = math.random_normal(instance(points=4), channel(vector=2))
points = PointCloud(Sphere(loc, radius=1), val)
for backend in BACKENDS:
converted = field.convert(points, backend)
self.assertEqual(converted.values.default_backend, backend)
self.assertEqual(converted.elements.center.default_backend,
backend)
self.assertEqual(converted.elements.radius.default_backend,
backend)
def test_overlay(self):
grid = CenteredGrid(Noise(),
extrapolation.ZERO,
x=64,
y=8,
bounds=Box(0, [1, 1]))
points = wrap([(.2, .4), (.9, .8)], instance('points'),
channel('vector'))
cloud = PointCloud(Sphere(points, radius=.1))
self._test_plot(overlay(grid, grid * (0.1, 0.02), cloud),
title='Overlay')
def test_plot_point_cloud_3d_points(self):
self._test_plot(
PointCloud(
math.random_normal(instance(points=5),
channel(vector='x,y,z'))))
def test_plot_point_cloud_3d(self):
points = math.random_uniform(instance(points=50), channel(vector=3))
cloud = PointCloud(Sphere(points, radius=.1),
bounds=Box(x=2, y=1, z=1))
self._test_plot(cloud)
def test_plot_point_cloud_vector_field_2d_bounded(self):
points = math.random_uniform(instance(points='a,b,c,d,e'),
channel(vector='x,y'))
velocity = PointCloud(Sphere(points, radius=.1), bounds=Box(x=1, y=1))
self._test_plot(velocity * (.05, 0))
def test_plot_point_cloud_2d_bounded(self):
points = wrap([(.2, .4), (.9, .8)], instance('points'),
channel('vector'))
self._test_plot(
PointCloud(Sphere(points, radius=0.1), bounds=Box(0, [1, 1])))