def showMesh(mesh, data=None, showLater=False, colorBar=False, axes=None,
*args, **kwargs):
"""
Syntactic sugar, short-cut to create axes and plot node or cell values
return axes, cbar
Parameters
----------
"""
ret = []
ax = axes
if ax == None:
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
gci = None
cbar = None
validData = False
if data is None:
drawMesh(ax, mesh)
else:
#print(data[0], type(data[0]))
if hasattr(data[0], '__len__') and type(data) != np.ma.core.MaskedArray:
if sum(data[:,0]) != sum(data[:,1]):
drawStreamLines2(ax, mesh, data, *args, **kwargs)
else:
print("No valid stream data:", data)
drawMesh(ax, mesh)
elif min(data) == max(data):
print(("No valid data", min(data), max(data)))
drawMesh(ax, mesh)
else:
validData = True
if len(data) == mesh.cellCount():
gci = drawModel(ax, mesh, data, *args, **kwargs)
elif len(data) == mesh.nodeCount():
gci = drawField(ax, mesh, data, *args, **kwargs)
ax.set_aspect('equal')
if colorBar and validData:
cbar = createColorbar(gci, *args, **kwargs)
if not showLater:
plt.show()
#fig.show()
#fig.canvas.draw()
return ax, cbar
while len(downwind) > 0:
fastMarch(mesh, downwind, times, upTags, downTags)
print(time.time() - tic, "s")
# compare with analytical solution along the x axis
x = np.arange(0., 100., 0.5)
t = pg.interpolate(mesh, times, pg.asvector(x), x * 0., x * 0.)
tdirect = x / v[0] # direct wave
alfa = asin(v[0] / v[1]) # critically refracted wave angle
xreflec = tan(alfa) * zlay * 2. # first critically refracted
trefrac = (x - xreflec) / v[1] + xreflec * v[1] / v[0]**2
tana = np.where(trefrac < tdirect, trefrac, tdirect) # minimum of both
print("min(dt)=",
min(t - tana) * 1000,
"ms max(dt)=",
max(t - tana) * 1000,
"ms")
# plot traveltime field, a few lines
fig = plt.figure()
a = fig.add_subplot(211)
drawMesh(a, mesh)
drawField(a, mesh, times, True, 'Spectral')
drawStreamLines(a, mesh, times, nx=50, ny=50)
# plot calculated and measured travel times
a2 = fig.add_subplot(212)
plt.plot(x, t, 'b.-', x, tdirect, 'r-', x, trefrac, 'g-')
plt.show()
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
#a.plot( n.pos()[0], n.pos()[1], 'o', color='white')
#if n.pos().distance( source ) < mindist:
#mindist = n.pos().distance( source )
#nextPredict = n
#print "next predicted ", n.id(), mindist
#a.plot( nextPredict.pos()[0], nextPredict.pos()[1], 'o', color='green')
#drawField( a, mesh, times )
###drawField( a, mesh, anaTimes, colors = 'white' )
#a.figure.canvas.draw()
#a.figure.show()
##raw_input('Press Enter...')
#a.clear()
fastMarch( mesh, downwind, times, upTags, downTags)
print(time.time()-tic, "s")
drawMesh( a, mesh )
drawField( a, mesh, times, filled=True )
#drawStreamCircular( a, mesh, times, source, 30., nLines = 50, step = 0.1, showStartPos = True )
#ax1.streamplot(X, Y, U, V, density=[0.5, 1])
drawStreamLinear( a, mesh, times, pg.RVector3(-100., -10.0 ), pg.RVector3(100., -10.0 ), nLines = 50, step = 0.01, showStartPos = True )
plt.show()
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
def test():
"""WRITEME."""
mesh = pg.Mesh('mesh/test2d')
mesh.createNeighbourInfos()
print(mesh)
source = pg.RVector3(-80, 0.)
times = pg.RVector(mesh.nodeCount(), 0.)
for c in mesh.cells():
if c.marker() == 1:
c.setAttribute(1.)
elif c.marker() == 2:
c.setAttribute(0.5)
# c.setAttribute(abs(1./c.center()[1]))
fig = plt.figure()
ax = fig.subplot(1, 1, 1)
anaTimes = pg.RVector(mesh.nodeCount(), 0.0)
for n in mesh.nodes():
anaTimes[n.id()] = source.distance(n.pos())
# d = pg.DataContainer()
# dijk = pg.TravelTimeDijkstraModelling(mesh, d)
# upwind = set()
downwind = set()
upTags = np.zeros(mesh.nodeCount())
downTags = np.zeros(mesh.nodeCount())
# define initial condition
cell = mesh.findCell(source)
for n in cell.nodes():
times[n.id()] = cell.attribute() * n.pos().distance(source)
upTags[n.id()] = 1
for n in cell.nodes():
tmpNodes = pg.commonNodes(n.cellSet())
for nn in tmpNodes:
if not upTags[nn.id()] and not downTags[nn.id()]:
downwind.add(nn)
downTags[nn.id()] = 1
# start fast marching
tic = time.time()
while len(downwind) > 0:
# model = pg.RVector(mesh.cellCount(), 0.0)
# for c in upwind: model.setVal(2, c.id())
# for c in downwind: model.setVal(1, c.id())
# drawMesh(a, mesh)
# a.plot(source[0], source[1], 'x')
# for c in mesh.cells():
# a.text(c.center()[0],c.center()[1], str(c.id()))
# for n in mesh.nodes():
# if upTags[n.id()]:
# a.plot(n.pos()[0], n.pos()[1], 'o', color='black')
# mindist = 9e99
# for n in downwind:
# a.plot(n.pos()[0], n.pos()[1], 'o', color='white')
# if n.pos().distance(source) < mindist:
# mindist = n.pos().distance(source)
# nextPredict = n
# print "next predicted ", n.id(), mindist
# a.plot(nextPredict.pos()[0], nextPredict.pos()[1],
# 'o', color='green')
# drawField(a, mesh, times)
# drawField(a, mesh, anaTimes, colors = 'white')
# a.figure.canvas.draw()
# a.figure.show()
# raw_input('Press Enter...')
# a.clear()
fastMarch(mesh, downwind, times, upTags, downTags)
print(time.time() - tic, "s")
drawMesh(ax, mesh)
drawField(ax, mesh, times, filled=True)
###############################################################################
# Then we start marching until all fields are filled.
tic = time.time()
while len(downwind) > 0:
fastMarch(mesh, downwind, times, upTags, downTags)
print(time.time() - tic, "s")
###############################################################################
# First, we plot the traveltime field and streamlines
fig, ax = plt.subplots(figsize=(10, 5))
drawMesh(ax, mesh)
ax.set_xlabel('x [m]')
ax.set_ylabel('y [m]')
drawField(ax, mesh, times, cmap='Spectral', fillContour=True)
drawStreamLines(ax, mesh, -times, nx=50, ny=50)
###############################################################################
# We compare the result with the analytical solution along the x axis
x = np.arange(0., 140., 0.5)
tFMM = pg.interpolate(mesh, times, x, x * 0., x * 0.)
tAna = analyticalSolution2Layer(x)
print("min(dt)={} ms max(dt)={} ms".format(
min(tFMM - tAna) * 1000,
max(tFMM - tAna) * 1000))
###############################################################################
# In order to use the Dijkstra, we extract the surface positions >0
mx = pg.x(mesh.positions())
my = pg.y(mesh.positions())
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
# start fast marching
tic = time.time()
while len(downwind) > 0:
fastMarch(mesh, downwind, times, upTags, downTags)
print(time.time() - tic, "s")
# compare with analytical solution along the x axis
x = np.arange(0., 100., 0.5)
t = pg.interpolate(mesh, times, x, x * 0., x * 0.)
tdirect = x / v[0] # direct wave
alfa = asin(v[0] / v[1]) # critically refracted wave angle
xreflec = tan(alfa) * zlay * 2. # first critically refracted
trefrac = (x - xreflec) / v[1] + xreflec * v[1] / v[0]**2
tana = np.where(trefrac < tdirect, trefrac, tdirect) # minimum of both
print("min(dt)=",
min(t - tana) * 1000, "ms max(dt)=",
max(t - tana) * 1000, "ms")
# plot traveltime field, a few lines
fig = plt.figure()
a = fig.add_subplot(211)
drawMesh(a, mesh)
drawField(a, mesh, times, True, 'Spectral')
drawStreamLines(a, mesh, times, nx=50, ny=50)
# plot calculated and measured travel times
a2 = fig.add_subplot(212)
plt.plot(x, t, 'b.-', x, tdirect, 'r-', x, trefrac, 'g-')
plt.show()
for nn in tmpNodes:
if not upTags[nn.id()] and not downTags[nn.id()]:
downwind.add(nn)
downTags[nn.id()] = 1
# start fast marching
tic = time.time()
while len(downwind) > 0:
fastMarch(mesh, downwind, times, upTags, downTags)
print(time.time() - tic, "s")
# compare with analytical solution along the x axis
x = np.arange(-20., 150., 0.5)
t = pg.interpolate(mesh, times, pg.asvector(x), x * 0., x * 0.)
tdirect = np.abs(x) / v[0] # direct wave
alfa = asin(v[0] / v[1]) # critically refracted wave angle
xreflec = tan(alfa) * zlay * 2. # first critically refracted
trefrac = (np.abs(x) - xreflec) / v[1] + xreflec * v[1] / v[0]**2
tana = np.where(trefrac < tdirect, trefrac, tdirect) # minimum of both
print("min(dt)=", min(t-tana)*1e3, "ms max(dt)=", max(t-tana)*1e3, "ms")
# %% plot traveltime field, a few lines
fig, ax = plt.subplots(nrows=2, sharex=True)
drawMesh(ax[0], mesh)
drawField(ax[0], mesh, times, True)
drawStreamLines(ax[0], mesh, times, color='white')
# plot calculated and measured travel times
ax[1].plot(x, t, 'b.-', x, tdirect, 'r-', x, trefrac, 'g-')
plt.show()