def visualize(self, U, codim=2, **kwargs):
"""Visualize scalar data associated to the grid as a patch plot.
Parameters
----------
U
|NumPy array| of the data to visualize. If `U.dim == 2 and len(U) > 1`, the
data is visualized as a time series of plots. Alternatively, a tuple of
|Numpy arrays| can be provided, in which case a subplot is created for
each entry of the tuple. The lengths of all arrays have to agree.
codim
The codimension of the entities the data in `U` is attached to (either 0 or 2).
kwargs
See :func:`~pymor.gui.qt.visualize_patch`
"""
from pymor.gui.qt import visualize_patch
from pymor.vectorarrays.interfaces import VectorArrayInterface
from pymor.vectorarrays.numpy import NumpyVectorArray
if isinstance(U, (np.ndarray, VectorArrayInterface)):
U = (U,)
assert all(isinstance(u, (np.ndarray, VectorArrayInterface)) for u in U)
U = tuple(NumpyVectorArray(u) if isinstance(u, np.ndarray) else
u if isinstance(u, NumpyVectorArray) else
NumpyVectorArray(u.data)
for u in U)
bounding_box = kwargs.pop('bounding_box', self.domain)
visualize_patch(self, U, codim=codim, bounding_box=bounding_box, **kwargs)
def visualize(self, U, codim=2, **kwargs):
"""Visualize scalar data associated to the grid as a patch plot.
Parameters
----------
U
|VectorArray| of the data to visualize. If `len(U) > 1`, the data is visualized
as a time series of plots. Alternatively, a tuple of |VectorArrays| can be
provided, in which case a subplot is created for each entry of the tuple. The
lengths of all arrays have to agree.
codim
The codimension of the entities the data in `U` is attached to (either 0 or 2).
kwargs
See :func:`~pymor.gui.qt.visualize_patch`
"""
from pymor.gui.qt import visualize_patch
from pymor.la.numpyvectorarray import NumpyVectorArray
if not isinstance(U, NumpyVectorArray):
U = NumpyVectorArray(U, copy=False)
bounding_box = kwargs.pop('bounding_box', self.domain)
visualize_patch(self,
U,
codim=codim,
bounding_box=bounding_box,
**kwargs)
def test_visualize_patch(backend_gridtype):
backend, gridtype = backend_gridtype
domain = LineDomain() if gridtype is OnedGrid else RectDomain()
dim = 1 if gridtype is OnedGrid else 2
rhs = GenericFunction(lambda X: np.ones(X.shape[:-1]) * 10, dim) # NOQA
dirichlet = GenericFunction(lambda X: np.zeros(X.shape[:-1]), dim) # NOQA
diffusion = GenericFunction(lambda X: np.ones(X.shape[:-1]), dim) # NOQA
problem = EllipticProblem(domain=domain, rhs=rhs, dirichlet_data=dirichlet, diffusion_functions=(diffusion,))
grid, bi = discretize_domain_default(problem.domain, grid_type=gridtype)
discretization, data = discretize_elliptic_cg(analytical_problem=problem, grid=grid, boundary_info=bi)
U = discretization.solve()
visualize_patch(data['grid'], U=U, backend=backend)
sleep(2) # so gui has a chance to popup
stop_gui_processes()
def test_visualize_patch(backend_gridtype):
backend, gridtype = backend_gridtype
domain = LineDomain() if gridtype is OnedGrid else RectDomain()
dim = 1 if gridtype is OnedGrid else 2
rhs = GenericFunction(lambda X: np.ones(X.shape[:-1]) * 10, dim) # NOQA
dirichlet = GenericFunction(lambda X: np.zeros(X.shape[:-1]), dim) # NOQA
diffusion = GenericFunction(lambda X: np.ones(X.shape[:-1]), dim) # NOQA
problem = StationaryProblem(domain=domain, rhs=rhs, dirichlet_data=dirichlet, diffusion=diffusion)
grid, bi = discretize_domain_default(problem.domain, grid_type=gridtype)
discretization, data = discretize_stationary_cg(analytical_problem=problem, grid=grid, boundary_info=bi)
U = discretization.solve()
try:
visualize_patch(data['grid'], U=U, backend=backend)
except PySideMissing as ie:
pytest.xfail("PySide missing")
finally:
stop_gui_processes()
def test_visualize_patch(backend_gridtype):
backend, gridtype = backend_gridtype
domain = LineDomain() if gridtype is OnedGrid else RectDomain()
dim = 1 if gridtype is OnedGrid else 2
rhs = GenericFunction(lambda X: np.ones(X.shape[:-1]) * 10, dim) # NOQA
dirichlet = GenericFunction(lambda X: np.zeros(X.shape[:-1]), dim) # NOQA
diffusion = GenericFunction(lambda X: np.ones(X.shape[:-1]), dim) # NOQA
problem = StationaryProblem(domain=domain, rhs=rhs, dirichlet_data=dirichlet, diffusion=diffusion)
grid, bi = discretize_domain_default(problem.domain, grid_type=gridtype)
d, data = discretize_stationary_cg(analytical_problem=problem, grid=grid, boundary_info=bi)
U = d.solve()
try:
visualize_patch(data['grid'], U=U, backend=backend)
except QtMissing as ie:
pytest.xfail("Qt missing")
finally:
stop_gui_processes()
def test_visualize_patch(backend_gridtype):
backend, gridtype = backend_gridtype
domain = LineDomain() if gridtype is OnedGrid else RectDomain()
dim = 1 if gridtype is OnedGrid else 2
rhs = GenericFunction(lambda X: np.ones(X.shape[:-1]) * 10, dim) # NOQA
dirichlet = GenericFunction(lambda X: np.zeros(X.shape[:-1]), dim) # NOQA
diffusion = GenericFunction(lambda X: np.ones(X.shape[:-1]), dim) # NOQA
problem = EllipticProblem(domain=domain,
rhs=rhs,
dirichlet_data=dirichlet,
diffusion_functions=(diffusion, ))
grid, bi = discretize_domain_default(problem.domain, grid_type=gridtype)
discretization, data = discretize_elliptic_cg(analytical_problem=problem,
grid=grid,
boundary_info=bi)
U = discretization.solve()
visualize_patch(data['grid'], U=U, backend=backend)
sleep(2) # so gui has a chance to popup
for child in multiprocessing.active_children():
child.terminate()
def visualize(self, U, codim=2, **kwargs):
"""Visualize scalar data associated to the grid as a patch plot.
Parameters
----------
U
|VectorArray| of the data to visualize. If `len(U) > 1`, the data is visualized
as a time series of plots. Alternatively, a tuple of |VectorArrays| can be
provided, in which case a subplot is created for each entry of the tuple. The
lengths of all arrays have to agree.
codim
The codimension of the entities the data in `U` is attached to (either 0 or 2).
kwargs
See :func:`~pymor.gui.qt.visualize_patch`
"""
from pymor.gui.qt import visualize_patch
from pymor.vectorarrays.numpy import NumpyVectorArray
if not isinstance(U, NumpyVectorArray):
U = NumpyVectorArray(U, copy=False)
bounding_box = kwargs.pop('bounding_box', self.domain)
visualize_patch(self, U, codim=codim, bounding_box=bounding_box, **kwargs)