def showMesh(mesh,
data=None,
hold=False,
block=False,
colorBar=None,
label=None,
coverage=None,
ax=None,
savefig=None,
showMesh=False,
showBoundary=None,
markers=False,
**kwargs):
"""2D Mesh visualization.
Create an axis object and plot a 2D mesh with given node or cell data.
Returns the axis and the color bar. The type of data determine the
appropriate draw method.
Parameters
----------
mesh : :gimliapi:`GIMLI::Mesh`
2D or 3D GIMLi mesh
data : iterable [None]
Optionally data to visualize.
. None (draw mesh only)
forward to :py:mod:`pygimli.mplviewer.drawMesh`
or if no cells are given:
forward to :py:mod:`pygimli.mplviewer.drawPLC`
. [[marker, value], ...]
List of Cellvalues per cell marker
forward to :py:mod:`pygimli.mplviewer.drawModel`
. float per cell -- model, patch
forward to :py:mod:`pygimli.mplviewer.drawModel`
. float per node -- scalar field
forward to :py:mod:`pygimli.mplviewer.drawField`
. iterable of type [float, float] -- vector field
forward to :py:mod:`pygimli.mplviewer.drawStreams`
. pg.R3Vector -- vector field
forward to :py:mod:`pygimli.mplviewer.drawStreams`
. pg.stdVectorRVector3 -- sensor positions
forward to :py:mod:`pygimli.mplviewer.drawSensors`
hold : bool [false]
Set interactive plot mode for matplotlib.
If this is set to false [default] your script will open
a window with the figure and draw your content.
If set to true nothing happens until you either force another show with
hold=False, you call plt.show() or pg.wait().
If you want show with stopping your script set block = True.
block : bool [false]
Force show drawing your content and block the script until you
close the current figure.
colorBar : bool [None], Colorbar
Create and show a colorbar. If colorBar is a valid colorbar then only
its values will be updated.
label : str
Set colorbar label. If set colorbar is toggled to True. [None]
coverage : iterable [None]
Weight data by the given coverage array and fadeout the color.
ax : matplotlib.Axes [None]
Instead of create a new and empty ax, just draw into the a given.
Useful to combine draws.
savefig: string
Filename for a direct save to disc.
The matplotlib pdf-output is a little bit big so we try
an epstopdf if the .eps suffix is found in savefig
showMesh : bool [False]
Shows the mesh itself aditional.
showBoundary : bool [None]
Shows all boundary with marker != 0. A value None means automatic
True for cell data and False for node data.
marker : bool [False]
Show mesh and boundary marker.
**kwargs :
* xlabel : str [None]
Add label to the x axis
* ylabel : str [None]
Add label to the y axis
* all remaining
Will be forwarded to the draw functions and matplotlib methods,
respectively.
Examples
--------
>>> import pygimli as pg
>>> import pygimli.meshtools as mt
>>> world = mt.createWorld(start=[-10, 0], end=[10, -10],
... layers=[-3, -7], worldMarker=False)
>>> mesh = mt.createMesh(world, quality=32, area=0.2, smooth=[1, 10])
>>> _ = pg.viewer.showMesh(mesh, markers=True)
Returns
-------
ax : matplotlib.axes
colobar : matplotlib.colorbar
"""
pg.renameKwarg('cmap', 'cMap', kwargs)
if ax is None:
ax = plt.subplots()[1]
# print('1*'*50)
# print(locale.localeconv())
# plt.subplots() resets locale setting to system default .. this went
# horrible wrong for german 'decimal_point': ','
pg.checkAndFixLocaleDecimal_point(verbose=False)
# print('2*'*50)
# print(locale.localeconv())
if block:
hold = True
if hold:
lastHoldStatus = pg.mplviewer.utils.holdAxes__
pg.mplviewer.hold(val=1)
gci = None
validData = False
if markers:
kwargs["boundaryMarker"] = True
if mesh.cellCount() > 0:
uniquemarkers, uniqueidx = np.unique(np.array(mesh.cellMarkers()),
return_inverse=True)
label = "Cell markers"
kwargs["cMap"] = plt.cm.get_cmap("Set3", len(uniquemarkers))
kwargs["logScale"] = False
kwargs["cMin"] = -0.5
kwargs["cMax"] = len(uniquemarkers) - 0.5
data = np.arange(len(uniquemarkers))[uniqueidx]
if data is None:
showMesh = True
if showBoundary is None:
showBoundary = True
elif isinstance(data, pg.stdVectorRVector3):
drawSensors(ax, data, **kwargs)
elif isinstance(data, pg.R3Vector):
drawStreams(ax, mesh, data, **kwargs)
else:
#print('-----------------------------')
#print(data, type(data))
#print('-----------------------------')
### data=[[marker, val], ....]
if isinstance(data, list) and \
isinstance(data[0], list) and isinstance(data[0][0], int):
data = pg.solver.parseMapToCellArray(data, mesh)
if hasattr(data[0], '__len__') and not \
isinstance(data, np.ma.core.MaskedArray):
if len(data) == 2: # [u,v] x N
data = np.array(data).T
if data.shape[1] == 2:
drawStreams(ax, mesh, data, **kwargs)
elif data.shape[1] == 3: # probably N x [u,v,w]
# if sum(data[:, 0]) != sum(data[:, 1]):
# drawStreams(ax, mesh, data, **kwargs)
drawStreams(ax, mesh, data[:, 0:2], **kwargs)
else:
pg.warn("No valid stream data:", data.shape, data.ndim)
showMesh = True
elif min(data) == max(data): # or pg.haveInfNaN(data):
pg.warn("No valid data: ", min(data), max(data),
pg.haveInfNaN(data))
showMesh = True
else:
validData = True
try:
if len(data) == mesh.cellCount():
gci = drawModel(ax, mesh, data, **kwargs)
if showBoundary is None:
showBoundary = True
elif len(data) == mesh.nodeCount():
gci = drawField(ax, mesh, data, **kwargs)
cMap = kwargs.pop('cMap', None)
if cMap is not None:
gci.set_cmap(cmapFromName(cMap))
except BaseException as e:
print("Exception occured: ", e)
print("Data: ", min(data), max(data), pg.haveInfNaN(data))
print("Mesh: ", mesh)
drawMesh(ax, mesh, **kwargs)
if mesh.cellCount() == 0:
showMesh = False
if mesh.boundaryCount() == 0:
pg.mplviewer.drawPLC(ax,
mesh,
showNodes=True,
fillRegion=False,
showBoundary=False,
**kwargs)
showBoundary = False
#ax.plot(pg.x(mesh), pg.y(mesh), '.', color='black')
else:
pg.mplviewer.drawPLC(ax, mesh, **kwargs)
if showMesh:
if gci is not None and hasattr(gci, 'set_antialiased'):
gci.set_antialiased(True)
gci.set_linewidth(0.3)
gci.set_edgecolor("0.1")
else:
pg.mplviewer.drawSelectedMeshBoundaries(ax,
mesh.boundaries(),
color="0.1",
linewidth=0.3)
#drawMesh(ax, mesh, **kwargs)
if showBoundary is True or showBoundary is 1:
b = mesh.boundaries(mesh.boundaryMarkers() != 0)
pg.mplviewer.drawSelectedMeshBoundaries(ax,
b,
color=(0.0, 0.0, 0.0, 1.0),
linewidth=1.4)
fitView = kwargs.pop('fitView', True)
if fitView:
ax.set_xlim(mesh.xmin(), mesh.xmax())
ax.set_ylim(mesh.ymin(), mesh.ymax())
ax.set_aspect('equal')
cbar = None
if label is not None and colorBar is None:
colorBar = True
if colorBar and validData:
# , **kwargs) # causes problems!
labels = ['cMin', 'cMax', 'nLevs', 'cMap', 'logScale']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
subkwargs['label'] = label
if colorBar is True or colorBar is 1:
cbar = createColorBar(gci,
orientation=kwargs.pop(
'orientation', 'horizontal'),
size=kwargs.pop('size', 0.2),
pad=kwargs.pop('pad', None))
updateColorBar(cbar, **subkwargs)
elif colorBar is not False:
cbar = updateColorBar(colorBar, **subkwargs)
if markers:
ticks = np.arange(len(uniquemarkers))
cbar.set_ticks(ticks)
labels = []
for marker in uniquemarkers:
labels.append(str((marker)))
cbar.set_ticklabels(labels)
if coverage is not None:
if len(data) == mesh.cellCount():
addCoverageAlpha(gci, coverage)
else:
raise BaseException('toImplement')
# addCoverageAlpha(gci, pg.cellDataToPointData(mesh, coverage))
if not hold or block is not False and plt.get_backend() is not "Agg":
if data is not None:
if len(data) == mesh.cellCount():
cb = CellBrowser(mesh, data, ax=ax)
plt.show(block=block)
try:
plt.pause(0.01)
except BaseException as _:
pass
if hold:
pg.mplviewer.hold(val=lastHoldStatus)
if savefig:
print('saving: ' + savefig + ' ...')
if '.' not in savefig:
savefig += '.pdf'
ax.figure.savefig(savefig, bbox_inches='tight')
# rc params savefig.format=pdf
if '.eps' in savefig:
try:
print("trying eps2pdf ... ")
os.system('epstopdf ' + savefig)
except BaseException:
pass
print('..done')
return ax, cbar
# default (natural) BC that are of homogeneous Neumann type
# :math:`\frac{\partial u}{\partial n}=0`
ax = show(grid,
data=u,
filled=True,
colorBar=True,
orientation='vertical',
label='Solution $u$',
levels=np.linspace(min(u), max(u), 14),
hold=1)[0]
###############################################################################
# Instead of the grid we now want to add streamlines to show the gradients of
# the solution (i.e., the flow direction).
drawStreams(ax, grid, u)
ax.text(0.0, 1.01, '$u=1$', horizontalalignment='center') # top -- 3
ax.text(-1.0,
0.0,
'$\partial u/\partial n=-0.5$',
va='center',
ha='right',
rotation='vertical') # left -- 1
ax.text(0.0, -1.01, '$\partial u/\partial n=2.5$', ha='center',
va='top') # bot -- 4
ax.text(1.01,
0.0,
'$\partial u/\partial n=0$',
va='center',
ha='left',
[3, lambda b_: 1. - np.tanh(10.)],
[4, lambda b_: 1. + np.tanh(10 * (2 * b_.center()[0] + 1.))],
]
print ("start", swatch.duration())
uGrid = solveFiniteVolume(grid, a=1./Peclet, f=f, vel=vB,
uBoundary=dirichletBC,
duBoundary=neumannBC,
scheme=scheme)
ax1,cb = show(grid)
drawStreams(ax1, grid, vC, coarseMesh=pg.createGrid(x=np.linspace(-1.0, 1.0, 41),
y=np.linspace(0.0, 1.0, 21)),
)
print(swatch.duration())
#grid2, u2 = createFVPostProzessMesh(grid, u, dirichletBC)
show(grid, data=uGrid,
logScale=False, interpolate=1, tri=1,
colorBar=True, axes=ax1)
#unstructured
boundary = []
boundary.append([-1.0, 0.0])
boundary.append([ 0.0, 0.0])
boundary.append([ 1.0, 0.0])
boundary.append([ 1.0, 1.0])
boundary.append([-1.0, 1.0])
[4, lambda b_: 1. + np.tanh(10 * (2 * b_.center()[0] + 1.))],
]
print ("start", swatch.duration())
uGrid = solveFiniteVolume(grid, a=1./Peclet, f=f, vel=vB,
uBoundary=dirichletBC,
duBoundary=neumannBC,
scheme=scheme)
pg.showLater(1)
ax1,cb = show(grid)
drawStreams(ax1, grid, vC, coarseMesh=pg.createGrid(x=np.linspace(-1.0, 1.0, 41),
y=np.linspace(0.0, 1.0, 21)),
)
print(swatch.duration())
#grid2, u2 = createFVPostProzessMesh(grid, u, dirichletBC)
show(grid, data=uGrid,
logScale=False, interpolate=1, tri=1,
colorBar=True, axes=ax1)
#unstructured
boundary = []
boundary.append([-1.0, 0.0])
boundary.append([ 0.0, 0.0])
boundary.append([ 1.0, 0.0])
boundary.append([ 1.0, 1.0])
boundary.append([-1.0, 1.0])
k = 1e-3
sigma = 1
u = solve(grid, a=sigma, b=sigma * k*k, f=pointSource,
duB=neumannBC,
userData={'sourcePos': sourcePosA, 'k': k},
verbose=True)
u -= solve(grid, a=sigma, b=sigma * k*k, f=pointSource,
duB=neumannBC,
userData={'sourcePos': sourcePosB, 'k': k},
verbose=True)
# uAna = pg.RVector(map(lambda p__: uAnalytical(p__, sourcePosA, k),
# grid.positions()))
# uAna -= pg.RVector(map(lambda p__: uAnalytical(p__, sourcePosB, k),
# grid.positions()))
# err = (1.0 -u/uAna) * 100.0
# print("error min max", min(err), max(err))
ax = show(grid, data=u, filled=True, colorBar=True, cmap="RdBu_r",
orientation='horizontal', label='Solution u', hold=True)[0]
show(grid, ax=ax, hold=True)
gridCoarse = pg.createGrid(x=np.linspace(-10.0, 10.0, 20),
y=np.linspace(-15.0, .0, 20))
# Instead of the grid we want to add streamlines to the plot to show the
# gradients of the solution.
drawStreams(ax, grid, u, coarseMesh=gridCoarse, color='Black')
pg.wait()
def showMesh(mesh, data=None, hold=False, block=False,
colorBar=False, coverage=None,
axes=None, savefig=None, **kwargs):
"""
2D Mesh visualization.
Create an axes and plot node or cell values for the given 2d mesh.
Returns the axes and the color bar.
Parameters
----------
mesh : :gimliapi:`GIMLI::Mesh`
2D or 3D GIMLi mesh
data : iterable [None]
Optionally data to visualize.
. None (draw mesh only)
forward to :py:mod:`pygimli.mplviewer.meshview.drawMesh`
. float per cell -- model, patch
forward to :py:mod:`pygimli.mplviewer.meshview.drawModel`
. float per node -- scalar field
forward to :py:mod:`pygimli.mplviewer.meshview.drawField`
. iterable of type [float, float] -- vector field
forward to :py:mod:`pygimli.mplviewer.meshview.drawStreams`
. pg.stdVectorRVector3 -- sensor positions
forward to :py:mod:`pygimli.mplviewer.meshview.drawSensors`
hold : bool [false]
Set interactive plot mode for matplotlib.
If this is set to false [default] your script will open
a window with the figure and draw your content.
If set to true nothing happens until you either force another show with
hold=False, you call plt.show() or pg.wait().
If you want show with stopping your script set block = True.
block : bool [false]
Force show drawing your content and block the script until you
close the current figure.
colorBar : bool [false]
Create and show a colorbar.
coverage : iterable [None]
Weight data by the given coverage array and fadeout the color.
axes : matplotlib.Axes [None]
Instead of create a new and empty axes, just draw into the a given.
Useful to combine draws.
savefig: string
Filename for a direct save to disc.
The matplotlib pdf-output is a little bit big so we try
an epstopdf if the .eps suffix is found in savefig
**kwargs :
Will be forwarded to the draw functions and matplotlib methods,
respectively.
Returns
-------
axes : matplotlib.axes
colobar : matplotlib.colobar
"""
ax = axes
if block:
hold = 1
if hold:
lastHoldStatus = pg.mplviewer.holdAxes_
pg.mplviewer.holdAxes_ = 1
if ax is None:
fig, ax = plt.subplots()
gci = None
cbar = None
validData = False
if data is None:
drawMesh(ax, mesh)
elif isinstance(data, pg.stdVectorRVector3):
drawSensors(ax, data)
else:
if hasattr(data[0], '__len__') and not isinstance(data,
np.ma.core.MaskedArray):
if len(data) == 2: # [u,v]
data = np.array(data).T
if sum(data[:, 0]) != sum(data[:, 1]):
drawStreams(ax, mesh, data, **kwargs)
else:
print("No valid stream data:", data)
drawMesh(ax, mesh)
elif (min(data) == max(data)): # or pg.haveInfNaN(data):
print("No valid data: ", min(data), max(data), pg.haveInfNaN(data))
drawMesh(ax, mesh)
else:
validData = True
try:
if len(data) == mesh.cellCount():
gci = drawModel(ax, mesh, data, **kwargs)
elif len(data) == mesh.nodeCount():
gci = drawField(ax, mesh, data, **kwargs)
except Exception as e:
print("Exception occured: " + e)
print("Data: ", min(data), max(data), pg.haveInfNaN(data))
print("Mesh: ", mesh)
drawMesh(ax, mesh)
ax.set_aspect('equal')
label = kwargs.pop('label', None)
if colorBar and validData:
# , *args, **kwargs) # causes problems!
cbar = createColorbar(gci, label=label, **kwargs)
plt.tight_layout()
if coverage is not None:
if len(data) == mesh.cellCount():
addCoverageAlpha(gci, coverage)
else:
raise('toImplement')
addCoverageAlpha(gci, pg.cellDataToPointData(mesh, coverage))
if showLater in kwargs:
hold = showLater
print("showLater will be removed in the future. use hold instead")
if not hold or block is not False:
plt.show(block=block)
try:
plt.pause(0.01)
except:
pass
if hold:
pg.mplviewer.holdAxes_ = lastHoldStatus
if savefig:
print('saving: ' + savefig + ' ...')
ax.figure.savefig(savefig, bbox_inches='tight')
if '.eps' in savefig:
try:
print("trying eps2pdf ... ")
os.system('epstopdf ' + savefig)
except:
pass
print('..done')
return ax, cbar
u -= solve(grid, a=sigma, b=-sigma * k*k, f=pointSource(grid, sourcePosB),
bc={'Robin': robBC},
userData={'sourcePos': sourcePosB, 'k': k},
verbose=True)
# uAna = pg.RVector(map(lambda p__: uAnalytical(p__, sourcePosA, k),
# grid.positions()))
# uAna -= pg.RVector(map(lambda p__: uAnalytical(p__, sourcePosB, k),
# grid.positions()))
# err = (1.0 -u/uAna) * 100.0
# print("error min max", min(err), max(err))
ax = show(grid, data=u, fillContour=True, colorBar=True, cMap="RdBu_r",
orientation='horizontal', label='Solution u', nLevs=11,
logScale=False, hold=True, showMesh=True)[0]
# Additional to the image of the potential we want to see the current flow too.
# The current flows along the gradient of our solution and can be plotted as
# stream lines. On default the drawStreams method draws one segment of a
# stream line per cell of the mesh. This can be a little confusing for dense
# meshes so we can give a second (coarse) mesh as a new cell basis to draw the
# streams. If the drawStreams get scalar data the gradients will be calculated.
gridCoarse = pg.createGrid(x=np.linspace(-10.0, 10.0, 20),
y=np.linspace(-15.0, .0, 20))
drawStreams(ax, grid, u, coarseMesh=gridCoarse, color='Black')
pg.wait()
# or natural BC that are of homogeneous Neumann type
# :math:`\frac{\partial u}{\partial n}=0`
ax = show(
grid,
data=u,
filled=True,
colorBar=True,
orientation="vertical",
label="Solution $u$",
levels=np.linspace(min(u), max(u), 14),
hold=1,
)[0]
###############################################################################
# Instead of the grid we now want to add streamlines to the plot to show the
# gradients of the solution (i.e., the flow direction).
drawStreams(ax, grid, u)
ax.text(0.0, 1.01, "$u=1$", horizontalalignment="center") # top -- 3
ax.text(-1.0, 0.0, "$\partial u/\partial n=-0.5$", va="center", ha="right", rotation="vertical") # left -- 1
ax.text(0.0, -1.01, "$\partial u/\partial n=2.5$", ha="center", va="top") # bot -- 4
ax.text(1.01, 0.0, "$\partial u/\partial n=0$", va="center", ha="left", rotation="vertical") # right -- 2
ax.set_title("$\\nabla\cdot(1\\nabla u)=0$")
ax.set_xlim([-1.1, 1.1])
ax.set_ylim([-1.1, 1.1])
pg.wait()
def showMesh(mesh,
data=None,
hold=False,
block=False,
colorBar=None,
label=None,
coverage=None,
ax=None,
savefig=None,
**kwargs):
"""2D Mesh visualization.
Create an axis object and plot a 2D mesh with given node or cell data.
Returns the axis and the color bar. The type of data determine the
appropriate draw method.
Parameters
----------
mesh : :gimliapi:`GIMLI::Mesh`
2D or 3D GIMLi mesh
data : iterable [None]
Optionally data to visualize.
. None (draw mesh only)
forward to :py:mod:`pygimli.mplviewer.drawMesh`
or if no cells are given:
forward to :py:mod:`pygimli.mplviewer.drawPLC`
. float per cell -- model, patch
forward to :py:mod:`pygimli.mplviewer.drawModel`
. float per node -- scalar field
forward to :py:mod:`pygimli.mplviewer.drawField`
. iterable of type [float, float] -- vector field
forward to :py:mod:`pygimli.mplviewer.drawStreams`
. pg.stdVectorRVector3 -- sensor positions
forward to :py:mod:`pygimli.mplviewer.drawSensors`
hold : bool [false]
Set interactive plot mode for matplotlib.
If this is set to false [default] your script will open
a window with the figure and draw your content.
If set to true nothing happens until you either force another show with
hold=False, you call plt.show() or pg.wait().
If you want show with stopping your script set block = True.
block : bool [false]
Force show drawing your content and block the script until you
close the current figure.
colorBar : bool [None], Colorbar
Create and show a colorbar. If colorBar is a valid colorbar then only
his values will be updated.
label : str
Set colorbar label. If set colorbar is toggled to True. [None]
coverage : iterable [None]
Weight data by the given coverage array and fadeout the color.
ax : matplotlib.Axes [None]
Instead of create a new and empty ax, just draw into the a given.
Useful to combine draws.
savefig: string
Filename for a direct save to disc.
The matplotlib pdf-output is a little bit big so we try
an epstopdf if the .eps suffix is found in savefig
**kwargs :
* xlabel : str [None]
Add label to the x axis
* ylabel : str [None]
Add label to the y axis
* all remaining
Will be forwarded to the draw functions and matplotlib methods,
respectively.
Returns
-------
ax : matplotlib.ax
colobar : matplotlib.colobar
"""
ax = ax
if block:
hold = 1
if hold:
lastHoldStatus = pg.mplviewer.utils.holdAxes__
pg.mplviewer.hold(val=1)
# print('1*'*50)
# print(locale.localeconv())
if ax is None:
ax = plt.subplots()[1]
# plt.subplots() resets locale setting to system default .. this went
# horrible wrong for german 'decimal_point': ','
pg.checkAndFixLocaleDecimal_point(verbose=False)
# print('2*'*50)
# print(locale.localeconv())
gci = None
validData = False
if data is None:
drawMesh(ax, mesh, **kwargs)
elif isinstance(data, pg.stdVectorRVector3):
drawSensors(ax, data, **kwargs)
else:
# print(data, type(data))
if (hasattr(data[0], '__len__')
and not isinstance(data, np.ma.core.MaskedArray)):
if len(data) == 2: # [u,v]
data = np.array(data).T
if sum(data[:, 0]) != sum(data[:, 1]):
drawStreams(ax, mesh, data, **kwargs)
else:
print("No valid stream data:", data)
drawMesh(ax, mesh, **kwargs)
elif min(data) == max(data): # or pg.haveInfNaN(data):
print("No valid data: ", min(data), max(data), pg.haveInfNaN(data))
drawMesh(ax, mesh, **kwargs)
else:
validData = True
try:
if len(data) == mesh.cellCount():
gci = drawModel(ax, mesh, data, **kwargs)
elif len(data) == mesh.nodeCount():
gci = drawField(ax, mesh, data, **kwargs)
cmap = kwargs.pop('cmap', None)
cMap = kwargs.pop('cMap', None)
if cMap is not None:
cmap = cMap
if cmap is not None:
gci.set_cmap(cmapFromName(cmap))
except BaseException as e:
print("Exception occured: " + e)
print("Data: ", min(data), max(data), pg.haveInfNaN(data))
print("Mesh: ", mesh)
drawMesh(ax, mesh, **kwargs)
ax.set_aspect('equal')
cbar = None
if label is not None and colorBar is None:
colorBar = True
if colorBar and validData:
# , **kwargs) # causes problems!
labels = ['cMin', 'cMax', 'nLevs', 'orientation', 'pad']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
if colorBar is True or colorBar is 1:
cbar = createColorBar(gci, label=label, **subkwargs)
elif colorBar is not False:
cbar = updateColorBar(colorBar, gci, label=label, **subkwargs)
if coverage is not None:
if len(data) == mesh.cellCount():
addCoverageAlpha(gci, coverage)
else:
raise BaseException('toImplement')
# addCoverageAlpha(gci, pg.cellDataToPointData(mesh, coverage))
if not hold or block is not False:
if data is not None:
if len(data) == mesh.cellCount():
cb = CellBrowser(mesh, data, ax=ax)
cb.connect()
plt.show(block=block)
try:
plt.pause(0.01)
except BaseException as _:
pass
if hold:
pg.mplviewer.hold(val=lastHoldStatus)
if savefig:
print('saving: ' + savefig + ' ...')
if '.' not in savefig:
savefig += '.pdf'
ax.figure.savefig(savefig, bbox_inches='tight')
# rc params savefig.format=pdf
if '.eps' in savefig:
try:
print("trying eps2pdf ... ")
os.system('epstopdf ' + savefig)
except BaseException as _:
pass
print('..done')
return ax, cbar
def showMesh(mesh, data=None, hold=False, block=False, colorBar=None,
label=None, coverage=None, ax=None, savefig=None,
showMesh=False, showBoundary=None,
markers=False, **kwargs):
"""2D Mesh visualization.
Create an axis object and plot a 2D mesh with given node or cell data.
Returns the axis and the color bar. The type of data determines the
appropriate draw method.
Parameters
----------
mesh : :gimliapi:`GIMLI::Mesh`
2D or 3D GIMLi mesh
data : iterable [None]
Optionally data to visualize.
. None (draw mesh only)
forward to :py:mod:`pygimli.mplviewer.drawMesh`
or if no cells are given:
forward to :py:mod:`pygimli.mplviewer.drawPLC`
. [[marker, value], ...]
List of Cellvalues per cell marker
forward to :py:mod:`pygimli.mplviewer.drawModel`
. float per cell -- model, patch
forward to :py:mod:`pygimli.mplviewer.drawModel`
. float per node -- scalar field
forward to :py:mod:`pygimli.mplviewer.drawField`
. iterable of type [float, float] -- vector field
forward to :py:mod:`pygimli.mplviewer.drawStreams`
. pg.R3Vector -- vector field
forward to :py:mod:`pygimli.mplviewer.drawStreams`
. pg.stdVectorRVector3 -- sensor positions
forward to :py:mod:`pygimli.mplviewer.drawSensors`
hold : bool [false]
Set interactive plot mode for matplotlib.
If this is set to false [default] your script will open
a window with the figure and draw your content.
If set to true nothing happens until you either force another show with
hold=False, you call plt.show() or pg.wait().
If you want show with stopping your script set block = True.
block : bool [false]
Force show drawing your content and block the script until you
close the current figure.
colorBar : bool [None], Colorbar
Create and show a colorbar. If colorBar is a valid colorbar then only
its values will be updated.
label : str
Set colorbar label. If set colorbar is toggled to True. [None]
coverage : iterable [None]
Weight data by the given coverage array and fadeout the color.
ax : matplotlib.Axes [None]
Instead of creating a new and empty ax, just draw into the given one.
Useful to combine multiple plots into one figure.
savefig: string
Filename for a direct save to disc.
The matplotlib pdf-output is a little bit big so we try
an epstopdf if the .eps suffix is found in savefig
showMesh : bool [False]
Shows the mesh itself aditional.
showBoundary : bool [None]
Shows all boundary with marker != 0. A value None means automatic
True for cell data and False for node data.
marker : bool [False]
Show mesh and boundary marker.
**kwargs :
* xlabel : str [None]
Add label to the x axis
* ylabel : str [None]
Add label to the y axis
* all remaining
Will be forwarded to the draw functions and matplotlib methods,
respectively.
Examples
--------
>>> import pygimli as pg
>>> import pygimli.meshtools as mt
>>> world = mt.createWorld(start=[-10, 0], end=[10, -10],
... layers=[-3, -7], worldMarker=False)
>>> mesh = mt.createMesh(world, quality=32, area=0.2, smooth=[1, 10])
>>> _ = pg.viewer.showMesh(mesh, markers=True)
Returns
-------
ax : matplotlib.axes
colobar : matplotlib.colorbar
"""
pg.renameKwarg('cmap', 'cMap', kwargs)
if ax is None:
ax = plt.subplots()[1]
# print('1*'*50)
# print(locale.localeconv())
# plt.subplots() resets locale setting to system default .. this went
# horrible wrong for german 'decimal_point': ','
pg.checkAndFixLocaleDecimal_point(verbose=False)
# print('2*'*50)
# print(locale.localeconv())
if block:
hold = True
lastHoldStatus = pg.mplviewer.utils.holdAxes__
if not lastHoldStatus or hold:
pg.mplviewer.hold(val=1)
hold = True
gci = None
validData = False
if markers:
kwargs["boundaryMarker"] = True
if mesh.cellCount() > 0:
uniquemarkers, uniqueidx = np.unique(
np.array(mesh.cellMarkers()), return_inverse=True)
label = "Cell markers"
kwargs["cMap"] = plt.cm.get_cmap("Set3", len(uniquemarkers))
kwargs["logScale"] = False
kwargs["cMin"] = -0.5
kwargs["cMax"] = len(uniquemarkers) - 0.5
data = np.arange(len(uniquemarkers))[uniqueidx]
if data is None:
showMesh = True
if showBoundary is None:
showBoundary = True
elif isinstance(data, pg.stdVectorRVector3):
drawSensors(ax, data, **kwargs)
elif isinstance(data, pg.R3Vector):
drawStreams(ax, mesh, data, **kwargs)
else:
### data=[[marker, val], ....]
if isinstance(data, list) and \
isinstance(data[0], list) and isinstance(data[0][0], int):
data = pg.solver.parseMapToCellArray(data, mesh)
if hasattr(data[0], '__len__') and not \
isinstance(data, np.ma.core.MaskedArray):
if len(data) == 2: # [u,v] x N
data = np.array(data).T
if data.shape[1] == 2:
drawStreams(ax, mesh, data, **kwargs)
elif data.shape[1] == 3: # probably N x [u,v,w]
# if sum(data[:, 0]) != sum(data[:, 1]):
# drawStreams(ax, mesh, data, **kwargs)
drawStreams(ax, mesh, data[:, 0:2], **kwargs)
else:
pg.warn("No valid stream data:", data.shape, data.ndim)
showMesh = True
elif min(data) == max(data): # or pg.haveInfNaN(data):
pg.warn("No valid data: ", min(data), max(data), pg.haveInfNaN(data))
showMesh = True
else:
validData = True
try:
cMap = kwargs.pop('cMap', None)
if len(data) == mesh.cellCount():
gci = drawModel(ax, mesh, data, **kwargs)
if showBoundary is None:
showBoundary = True
elif len(data) == mesh.nodeCount():
gci = drawField(ax, mesh, data, **kwargs)
if cMap is not None:
gci.set_cmap(cmapFromName(cMap))
#gci.cmap.set_under('k')
except BaseException as e:
print("Exception occured: ", e)
print("Data: ", min(data), max(data), pg.haveInfNaN(data))
print("Mesh: ", mesh)
drawMesh(ax, mesh, **kwargs)
if mesh.cellCount() == 0:
showMesh = False
if mesh.boundaryCount() == 0:
pg.mplviewer.drawPLC(ax, mesh, showNodes=True,
fillRegion=False, showBoundary=False,
**kwargs)
showBoundary = False
#ax.plot(pg.x(mesh), pg.y(mesh), '.', color='black')
else:
pg.mplviewer.drawPLC(ax, mesh, **kwargs)
if showMesh:
if gci is not None and hasattr(gci, 'set_antialiased'):
gci.set_antialiased(True)
gci.set_linewidth(0.3)
gci.set_edgecolor("0.1")
else:
pg.mplviewer.drawSelectedMeshBoundaries(ax, mesh.boundaries(),
color="0.1", linewidth=0.3)
#drawMesh(ax, mesh, **kwargs)
if showBoundary is True or showBoundary is 1:
b = mesh.boundaries(mesh.boundaryMarkers() != 0)
pg.mplviewer.drawSelectedMeshBoundaries(ax, b,
color=(0.0, 0.0, 0.0, 1.0),
linewidth=1.4)
fitView = kwargs.pop('fitView', True)
if fitView:
ax.set_xlim(mesh.xmin(), mesh.xmax())
ax.set_ylim(mesh.ymin(), mesh.ymax())
ax.set_aspect('equal')
cbar = None
if label is not None and colorBar is None:
colorBar = True
if colorBar and validData:
# , **kwargs) # causes problems!
labels = ['cMin', 'cMax', 'nLevs', 'cMap', 'logScale']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
subkwargs['label'] = label
if colorBar is True or colorBar is 1:
cbar = createColorBar(gci,
orientation=kwargs.pop('orientation',
'horizontal'),
size=kwargs.pop('size', 0.2),
pad=kwargs.pop('pad', None)
)
updateColorBar(cbar, **subkwargs)
elif colorBar is not False:
cbar = updateColorBar(colorBar, **subkwargs)
if markers:
ticks = np.arange(len(uniquemarkers))
cbar.set_ticks(ticks)
labels = []
for marker in uniquemarkers:
labels.append(str((marker)))
cbar.set_ticklabels(labels)
if coverage is not None:
if len(data) == mesh.cellCount():
addCoverageAlpha(gci, coverage)
else:
raise BaseException('toImplement')
# addCoverageAlpha(gci, pg.cellDataToPointData(mesh, coverage))
if not hold or block is not False and plt.get_backend() is not "Agg":
if data is not None:
if len(data) == mesh.cellCount():
cb = CellBrowser(mesh, data, ax=ax)
plt.show(block=block)
try:
plt.pause(0.01)
except BaseException as _:
pass
if hold:
pg.mplviewer.hold(val=lastHoldStatus)
if savefig:
print('saving: ' + savefig + ' ...')
if '.' not in savefig:
savefig += '.pdf'
ax.figure.savefig(savefig, bbox_inches='tight')
# rc params savefig.format=pdf
if '.eps' in savefig:
try:
print("trying eps2pdf ... ")
os.system('epstopdf ' + savefig)
except BaseException:
pass
print('..done')
return ax, cbar
grid=pg.createGrid(x,y)
fig = plt.figure()
ax1 = fig.add_subplot(1, 3, 1)
ax2 = fig.add_subplot(1, 3, 2)
ax3 = fig.add_subplot(1, 3, 3)
pl = pg.logTransDropTol(np.array((p.T).flat), 1e-2)
ul = pg.logTransDropTol(np.array((u.T).flat), 1e-2)
vl = pg.logTransDropTol(np.array((v.T).flat), 1e-2)
show(grid, pl, logScale=False, showLater=True, colorBar=True, axes=ax1, cmap='b2r')
show(grid, ul, logScale=False, showLater=True, colorBar=True, axes=ax2)
show(grid, vl, logScale=False, showLater=True, colorBar=True, axes=ax3)
vel = np.vstack([np.array((u.T).flat), np.array((v.T).flat)]).T
drawStreams(ax1, grid, vel)
#im1 = ax1.contourf(X,Y,p,alpha=0.5) ###plnttong the pressure field as a contour
#divider1 = make_axes_locatable(ax1)
#cax1 = divider1.append_axes("right", size="20%", pad=0.05)
#cbar1 = plt.colorbar(im1, cax=cax1)
#im2 = ax2.contourf(X,Y,u,alpha=0.5) ###plnttong the pressure field as a contour
#divider2 = make_axes_locatable(ax2)
#cax2 = divider2.append_axes("right", size="20%", pad=0.05)
#cbar2 = plt.colorbar(im2, cax=cax2)
#im3 = ax3.contourf(X,Y,v,alpha=0.5) ###plnttong the pressure field as a contour
#divider3 = make_axes_locatable(ax3)
#cax3 = divider3.append_axes("right", size="20%", pad=0.05)
#cbar3 = plt.colorbar(im3, cax=cax3)
