def visualize_matplotlib_1d(grid, U, codim=1, title=None, legend=None, separate_plots=False, block=False):
"""Visualize scalar data associated to a one-dimensional |Grid| as a plot.
The grid's |ReferenceElement| must be the line. The data can either
be attached to the subintervals or vertices of the grid.
Parameters
----------
grid
The underlying |Grid|.
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 several plots are made into the same axes. The
lengths of all arrays have to agree.
codim
The codimension of the entities the data in `U` is attached to (either 0 or 1).
title
Title of the plot.
legend
Description of the data that is plotted. Most useful if `U` is a tuple in which
case `legend` has to be a tuple of strings of the same length.
separate_plots
If `True`, use subplots to visualize multiple |VectorArrays|.
block
If `True`, block execution until the plot window is closed.
"""
if not config.HAVE_QT:
raise QtMissing()
if not config.HAVE_MATPLOTLIB:
raise ImportError('cannot visualize: import of matplotlib failed')
class MainWindow(PlotMainWindow):
def __init__(self, grid, U, codim, title, legend, separate_plots):
assert isinstance(U, VectorArrayInterface) \
or (isinstance(U, tuple)
and all(isinstance(u, VectorArrayInterface) for u in U)
and all(len(u) == len(U[0]) for u in U))
U = (U.to_numpy(),) if isinstance(U, VectorArrayInterface) else tuple(u.to_numpy() for u in U)
if isinstance(legend, str):
legend = (legend,)
assert legend is None or isinstance(legend, tuple) and len(legend) == len(U)
plot_widget = Matplotlib1DWidget(None, grid, count=len(U), vmin=[np.min(u) for u in U],
vmax=[np.max(u) for u in U], legend=legend, codim=codim,
separate_plots=separate_plots)
super().__init__(U, plot_widget, title=title, length=len(U[0]))
self.grid = grid
_launch_qt_app(lambda: MainWindow(grid, U, codim, title=title, legend=legend, separate_plots=separate_plots), block)
import sys
from pymor.tools.docopt import docopt
import time
import numpy as np
import OpenGL
from pymor.core.config import is_windows_platform
from pymor.gui.matplotlib import MatplotlibPatchWidget
OpenGL.ERROR_ON_COPY = True
from pymor.core.exceptions import QtMissing
try:
from Qt import QtWidgets
except ImportError as e:
raise QtMissing()
from pymor.algorithms.greedy import greedy
from pymor.analyticalproblems.thermalblock import thermal_block_problem
from pymor.discretizers.cg import discretize_stationary_cg
from pymor.gui.gl import ColorBarWidget, GLPatchWidget
from pymor.reductors.coercive import CoerciveRBReductor
PARAM_STEPS = 10
PARAM_MIN = 0.1
PARAM_MAX = 1
class ParamRuler(QtWidgets.QWidget):
def __init__(self, parent, sim):
super().__init__(parent)
self.sim = sim
def visualize_patch(grid,
U,
bounding_box=([0, 0], [1, 1]),
codim=2,
title=None,
legend=None,
separate_colorbars=False,
rescale_colorbars=False,
backend='gl',
block=False,
columns=2):
"""Visualize scalar data associated to a two-dimensional |Grid| as a patch plot.
The grid's |ReferenceElement| must be the triangle or square. The data can either
be attached to the faces or vertices of the grid.
Parameters
----------
grid
The underlying |Grid|.
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.
bounding_box
A bounding box in which the grid is contained.
codim
The codimension of the entities the data in `U` is attached to (either 0 or 2).
title
Title of the plot.
legend
Description of the data that is plotted. Most useful if `U` is a tuple in which
case `legend` has to be a tuple of strings of the same length.
separate_colorbars
If `True`, use separate colorbars for each subplot.
rescale_colorbars
If `True`, rescale colorbars to data in each frame.
backend
Plot backend to use ('gl' or 'matplotlib').
block
If `True`, block execution until the plot window is closed.
columns
The number of columns in the visualizer GUI in case multiple plots are displayed
at the same time.
"""
if not config.HAVE_QT:
raise QtMissing()
assert backend in {'gl', 'matplotlib'}
if backend == 'gl':
if not config.HAVE_GL:
logger = getLogger('pymor.gui.qt.visualize_patch')
logger.warning(
'import of PyOpenGL failed, falling back to matplotlib; rendering will be slow'
)
backend = 'matplotlib'
elif not config.HAVE_QTOPENGL:
logger = getLogger('pymor.gui.qt.visualize_patch')
logger.warning(
'import of Qt.QtOpenGL failed, falling back to matplotlib; rendering will be slow'
)
backend = 'matplotlib'
if backend == 'matplotlib' and not config.HAVE_MATPLOTLIB:
raise ImportError('cannot visualize: import of matplotlib failed')
else:
if not config.HAVE_MATPLOTLIB:
raise ImportError('cannot visualize: import of matplotlib failed')
# TODO extract class
class MainWindow(PlotMainWindow):
def __init__(self, grid, U, bounding_box, codim, title, legend,
separate_colorbars, rescale_colorbars, backend):
assert isinstance(U, VectorArrayInterface) and hasattr(U, 'data') \
or (isinstance(U, tuple) and all(isinstance(u, VectorArrayInterface) and hasattr(u, 'data') for u in U)
and all(len(u) == len(U[0]) for u in U))
U = (U.data.astype(np.float64, copy=False),) if hasattr(U, 'data') else \
tuple(u.data.astype(np.float64, copy=False) for u in U)
if isinstance(legend, str):
legend = (legend, )
assert legend is None or isinstance(
legend, tuple) and len(legend) == len(U)
if backend == 'gl':
widget = GLPatchWidget
cbar_widget = ColorBarWidget
else:
widget = MatplotlibPatchWidget
cbar_widget = None
if not separate_colorbars and len(U) > 1:
l = getLogger('pymor.gui.qt.visualize_patch')
l.warn(
'separate_colorbars=False not supported for matplotlib backend'
)
separate_colorbars = True
class PlotWidget(QWidget):
def __init__(self):
super().__init__()
if separate_colorbars:
if rescale_colorbars:
self.vmins = tuple(np.min(u[0]) for u in U)
self.vmaxs = tuple(np.max(u[0]) for u in U)
else:
self.vmins = tuple(np.min(u) for u in U)
self.vmaxs = tuple(np.max(u) for u in U)
else:
if rescale_colorbars:
self.vmins = (min(np.min(u[0])
for u in U), ) * len(U)
self.vmaxs = (max(np.max(u[0])
for u in U), ) * len(U)
else:
self.vmins = (min(np.min(u) for u in U), ) * len(U)
self.vmaxs = (max(np.max(u) for u in U), ) * len(U)
layout = QHBoxLayout()
plot_layout = QGridLayout()
self.colorbarwidgets = [
cbar_widget(self, vmin=vmin, vmax=vmax)
if cbar_widget else None
for vmin, vmax in zip(self.vmins, self.vmaxs)
]
plots = [
widget(self,
grid,
vmin=vmin,
vmax=vmax,
bounding_box=bounding_box,
codim=codim)
for vmin, vmax in zip(self.vmins, self.vmaxs)
]
if legend:
for i, plot, colorbar, l in zip(
range(len(plots)), plots, self.colorbarwidgets,
legend):
subplot_layout = QVBoxLayout()
caption = QLabel(l)
caption.setAlignment(Qt.AlignHCenter)
subplot_layout.addWidget(caption)
if not separate_colorbars or backend == 'matplotlib':
subplot_layout.addWidget(plot)
else:
hlayout = QHBoxLayout()
hlayout.addWidget(plot)
if colorbar:
hlayout.addWidget(colorbar)
subplot_layout.addLayout(hlayout)
plot_layout.addLayout(subplot_layout,
int(i / columns),
(i % columns), 1, 1)
else:
for i, plot, colorbar in zip(range(len(plots)), plots,
self.colorbarwidgets):
if not separate_colorbars or backend == 'matplotlib':
plot_layout.addWidget(plot, int(i / columns),
(i % columns), 1, 1)
else:
hlayout = QHBoxLayout()
hlayout.addWidget(plot)
if colorbar:
hlayout.addWidget(colorbar)
plot_layout.addLayout(hlayout,
int(i / columns),
(i % columns), 1, 1)
layout.addLayout(plot_layout)
if not separate_colorbars:
layout.addWidget(self.colorbarwidgets[0])
for w in self.colorbarwidgets[1:]:
w.setVisible(False)
self.setLayout(layout)
self.plots = plots
def set(self, U, ind):
if rescale_colorbars:
if separate_colorbars:
self.vmins = tuple(np.min(u[ind]) for u in U)
self.vmaxs = tuple(np.max(u[ind]) for u in U)
else:
self.vmins = (min(np.min(u[ind])
for u in U), ) * len(U)
self.vmaxs = (max(np.max(u[ind])
for u in U), ) * len(U)
for u, plot, colorbar, vmin, vmax in zip(
U, self.plots, self.colorbarwidgets, self.vmins,
self.vmaxs):
plot.set(u[ind], vmin=vmin, vmax=vmax)
if colorbar:
colorbar.set(vmin=vmin, vmax=vmax)
super().__init__(U, PlotWidget(), title=title, length=len(U[0]))
self.grid = grid
self.codim = codim
def save(self):
if not config.HAVE_PYVTK:
msg = QMessageBox(QMessageBox.Critical, 'Error',
'VTK output disabled. Pleas install pyvtk.')
msg.exec_()
return
filename = QFileDialog.getSaveFileName(self, 'Save as vtk file')[0]
base_name = filename.split('.vtu')[0].split('.vtk')[0].split(
'.pvd')[0]
if base_name:
if len(self.U) == 1:
write_vtk(self.grid,
NumpyVectorSpace.make_array(self.U[0]),
base_name,
codim=self.codim)
else:
for i, u in enumerate(self.U):
write_vtk(self.grid,
NumpyVectorSpace.make_array(u),
'{}-{}'.format(base_name, i),
codim=self.codim)
_launch_qt_app(
lambda: MainWindow(grid,
U,
bounding_box,
codim,
title=title,
legend=legend,
separate_colorbars=separate_colorbars,
rescale_colorbars=rescale_colorbars,
backend=backend), block)
