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# SPDX-FileCopyrightInfo: Copyright © DUNE Project contributors, see file LICENSE.md in module root
# SPDX-License-Identifier: LicenseRef-GPL-2.0-only-with-DUNE-exception
import os
try:
s = os.environ['DUNEPY_BLOCK_PLOTTING']
block = s in ['TRUE','True','true', '1', 't', 'y', 'yes']
except KeyError:
block = True
try:
s = os.environ['DUNEPY_DISABLE_PLOTTING']
disable = s in ['TRUE','True','true', '1', 't', 'y', 'yes']
except KeyError:
disable = False
block = block and (not disable)
try:
import matplotlib
from matplotlib import pyplot
from matplotlib.collections import PolyCollection
import numpy as np
from numpy import amin, amax, linspace, linalg, random
_addPlot = True
def _plotGrid(fig, grid, gridLines="black"):
for p in grid.polygons():
coll = PolyCollection(p, facecolor='none', edgecolor=gridLines, linewidth=0.5, zorder=2)
pyplot.gca().add_collection(coll)
def _plotData(fig, grid, solution, level=0, gridLines="black",
component=None, vectors=None, nofVectors=None,
xlim=None, ylim=None, clim=None, cmap=None, colorbar=True,
on="cell"):
if (gridLines is not None) and (gridLines != ""):
_plotGrid(fig, grid, gridLines=gridLines)
if solution is not None:
if on == "points":
assert not any(gt.isNone for gt in grid.indexSet.types(0)), "Can't plot point data with polygonal grids, use `on=\"cells\" in plotting command"
triangulation = grid.triangulation(level)
data = solution.pointData(level)
try:
x1 = vectors[0]
x2 = vectors[1]
if x1 >= solution.dimRange or x2 >= solution.dimRange:
vectors = None
except:
vectors = None
if not vectors == None:
if nofVectors==0:
nofVector = len(triangulation.x)
idx = random.randint(len(triangulation.x),size=nofVectors)
pyplot.quiver(triangulation.x[idx], triangulation.y[idx],
data[idx][:,x1], data[idx][:,x2],
units='xy', scale=10., zorder=3, color='blue',
width=0.007, headwidth=3., headlength=4.)
else:
if component is None:
if solution.dimRange > 1:
data = linalg.norm(data,axis=1)
else:
data = data[:,0]
else:
data = data[:,component]
minData = amin(data)
maxData = amax(data)
# avoid some weird 'white' patches when value hits min/max
# also if min and max are close together or equal the call
# of tricontourf will raise an Exception
epsData = (maxData - minData)*1e-8
minData -= epsData
maxData += epsData
if clim == None:
clim = [minData, maxData]
if clim[0] > minData and clim[1] < maxData:
extend = 'both'
elif clim[0] > minData:
extend = 'min'
elif clim[1] < maxData:
extend = 'max'
else:
extend = 'neither'
norm = matplotlib.colors.Normalize(vmin=clim[0], vmax=clim[1])
levels = linspace(clim[0], clim[1], 256, endpoint=True)
pyplot.tricontourf(triangulation, data, cmap=cmap, levels=levels,
extend=extend, norm=norm)
if colorbar is not None and colorbar:
if isinstance(colorbar,bool):
colorbar="vertical"
# having extend not 'both' does not seem to work (needs fixing)...
v = linspace(clim[0], clim[1], 10, endpoint=True)
cbar = pyplot.colorbar(orientation=colorbar,shrink=1.0, ticks=v)
cbar.ax.tick_params(labelsize=18)
else:
if not vectors is None: raise ValueError("polygonal data can not plot vector")
polys, values = solution.polygonData()
data = []
for vv in values:
for v in vv:
if component is None:
if solution.dimRange > 1:
d = linalg.norm(v)
else:
d = v[0]
else:
d = v[component]
data += [d]
data = np.array(data)
minData = amin(data)
maxData = amax(data)
if clim == None:
clim = [minData, maxData]
vert = []
for p in polys:
for q in p:
vert.append(q)
coll = PolyCollection(vert, array=data, edgecolor=gridLines, linewidth=0.5, zorder=2, cmap=cmap)
pyplot.gca().add_collection(coll)
if colorbar is not None and colorbar:
if isinstance(colorbar,bool):
colorbar="vertical"
# having extend not 'both' does not seem to work (needs fixing)...
if clim[0] > minData and clim[1] < maxData:
extend = 'both'
elif clim[0] > minData:
extend = 'min'
elif clim[1] < maxData:
extend = 'max'
else:
extend = 'neither'
v = linspace(clim[0], clim[1], 10, endpoint=True)
norm = matplotlib.colors.Normalize(vmin=clim[0], vmax=clim[1])
cbar = pyplot.colorbar(coll, orientation=colorbar,shrink=1.0,
# extend=extend, norm=norm,
ticks=v)
cbar.ax.tick_params(labelsize=18)
fig.gca().set_aspect('equal')
fig.gca().autoscale()
if xlim:
fig.gca().set_xlim(xlim)
if ylim:
fig.gca().set_ylim(ylim)
except ImportError or ModuleNotFoundError:
_addPlot = False
def plotGrid(grid, gridLines="black", figure=None,
xlim=None, ylim=None, figsize=None):
if not _addPlot:
print("plotting disabled since 'matplotlib' could not be imported")
return
if disable: return
if figure is None:
figure = pyplot.figure(figsize=figsize)
show = True
else:
try:
subPlot = figure[1]
figure = figure[0]
pyplot.subplot(subPlot)
except:
pass
show = False
_plotGrid(figure, grid, gridLines=gridLines)
figure.gca().set_aspect('equal')
figure.gca().autoscale()
if xlim:
figure.gca().set_xlim(xlim)
if ylim:
figure.gca().set_ylim(ylim)
if show:
pyplot.show(block=block)
def plotPointData(solution, level=0, gridLines="black",
vectors=None, nofVectors=None, figure=None,
xlim=None, ylim=None, clim=None, figsize=None, cmap=None,
colorbar=True):
if not _addPlot:
print("plotting disabled since 'matplotlib' could not be imported")
return
if disable: return
try:
grid = solution.grid
except:
grid = solution
solution = None
if not grid.dimension == 2:
raise ValueError("inline plotting so far only available for 2d grids")
if figure is None:
figure = pyplot.figure(figsize=figsize)
show = True
else:
try:
subPlot = figure[1]
figure = figure[0]
pyplot.subplot(subPlot)
except:
pass
show = False
_plotData(figure,grid,solution,level,gridLines,None,
vectors,nofVectors,xlim,ylim,clim,cmap,
colorbar=colorbar,on="points")
if show:
pyplot.show(block=block)
def plotCellData(solution, level=0, gridLines="black",
vectors=None, nofVectors=None, figure=None,
xlim=None, ylim=None, clim=None, figsize=None, cmap=None,
colorbar=True):
if not _addPlot:
print("plotting disabled since 'matplotlib' could not be imported")
return
if disable: return
try:
grid = solution.grid
except:
grid = solution
solution = None
if not grid.dimension == 2:
raise ValueError("inline plotting so far only available for 2d grids")
if figure is None:
figure = pyplot.figure(figsize=figsize)
show = True
else:
try:
subPlot = figure[1]
figure = figure[0]
pyplot.subplot(subPlot)
except:
pass
show = False
_plotData(figure,grid,solution,level,gridLines,None,vectors,nofVectors,xlim,ylim,clim,cmap,
colorbar=colorbar,on="cells")
if show:
pyplot.show(block=block)
def plotComponents(solution, level=0, show=None, gridLines="black", figure=None,
xlim=None, ylim=None, clim=None, figsize=None, cmap=None):
if not _addPlot:
print("plotting disabled since 'matplotlib' could not be imported")
return
if disable: return
try:
grid = solution.grid
except:
grid = solution
solution = None
if not grid.dimension == 2:
raise ValueError("inline plotting so far only available for 2d grids")
if not show:
show = range(solution.dimRange)
if figure is None:
figure = pyplot.figure(figsize=figsize)
offset = 1 if (gridLines is not None) and (gridLines != "") else 0
subfig = 101+(len(show)+offset)*10
# first the grid if required
if (gridLines is not None) and (gridLines != ""):
pyplot.subplot(subfig)
_plotData(figure,grid,None,level,gridLines,None,False,None,xlim,ylim,clim,cmap,
on="points")
# add the data
for p in show:
pyplot.subplot(subfig+offset+p)
_plotData(figure,grid,solution,level,"",p,False,None,xlim,ylim,clim,cmap,False,
on="points")
pyplot.show(block=block)
def plot(solution,*args,**kwargs):
if not _addPlot:
print("plotting disabled since 'matplotlib' could not be imported")
return
if disable: return
try:
grid = solution.grid
except:
grid = solution
defaultOn = "cells" if any(gt.isNone for gt in grid.indexSet.types(0)) else "points"
use = kwargs.pop("on",defaultOn)
if use == "points":
plotPointData(solution,*args,**kwargs)
elif use == "components-points":
plotComponents(solution,*args,**kwargs)
elif use == "cells":
plotCellData(solution,*args,**kwargs)
else:
raise ValueError("wrong value for 'on' parameter should be one of 'points','cells','components-points'")
def mayaviPointData(solution, level=0, component=0):
if disable: return
grid = solution.grid
from mayavi import mlab
triangulation = grid.triangulation(level)
z = solution.pointData(level)[:,component]
s = mlab.triangular_mesh(triangulation.x, triangulation.y, z,
triangulation.triangles)
mlab.show(block=block)
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