def showResult(self, val=None, ax=None, cMin=None, cMax=None,
logScale=False, name='result', **kwargs):
"""show resulting velocity vector"""
mesh = self.paraDomain()
if val is None:
val = self.velocity
if cMin is None or cMax is None:
cMin, cMax = interperc(val, 3)
if ax is None:
fig, ax = plt.subplots()
self.figs[name] = fig
ax, cbar = pg.show(mesh, val, logScale=logScale, axes=ax,
colorBar=True, cMin=cMin, cMax=cMax,
coverage=self.standardizedCoverage(), **kwargs)
self.figs[name] = plt.gcf()
else:
gci = drawModel(ax, mesh, val, logScale=logScale,
colorBar=True, cMin=cMin, cMax=cMax,
coverage=self.standardizedCoverage(), **kwargs)
labels = ['cMin', 'cMax', 'nLevs', 'orientation', 'label']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
cbar = createColorbar(gci, **subkwargs)
browser = CellBrowser(self.mesh, val, ax)
browser.connect()
self.axs[name] = ax
if 'lines' in kwargs:
plotLines(ax, kwargs['lines'])
return ax, cbar
def draw(ax, mesh, model, **kwargs):
model = np.array(model)
tol = 1e-3 # do not hide values that are very close (but below) zero
if not np.isclose(model.min(), 0.0, atol=tol) and (model < 0).any():
model = np.ma.masked_where(model < -tol, model)
if "coverage" in kwargs:
model = np.ma.masked_where(kwargs["coverage"] == 0, model)
gci = drawModel(ax, mesh, model, rasterized=True, nLevs=2, **kwargs)
return gci
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
def showResult(self,
val=None,
ax=None,
cMin=None,
cMax=None,
logScale=False,
name='result',
**kwargs):
"""show resulting velocity vector"""
mesh = self.paraDomain()
if val is None:
val = self.velocity
if cMin is None or cMax is None:
cMin, cMax = interperc(val, 3)
if ax is None:
fig, ax = plt.subplots()
self.figs[name] = fig
ax, cbar = pg.show(mesh,
val,
logScale=logScale,
ax=ax,
colorBar=True,
cMin=cMin,
cMax=cMax,
coverage=self.standardizedCoverage(),
**kwargs)
self.figs[name] = plt.gcf()
else:
gci = drawModel(ax,
mesh,
val,
logScale=logScale,
colorBar=True,
cMin=cMin,
cMax=cMax,
coverage=self.standardizedCoverage(),
**kwargs)
labels = ['cMin', 'cMax', 'nLevs', 'orientation', 'label']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
cbar = createColorbar(gci, **subkwargs)
browser = CellBrowser(self.mesh, val, ax)
browser.connect()
self.axs[name] = ax
if 'lines' in kwargs:
plotLines(ax, kwargs['lines'])
return ax, cbar
def showResult(self, ax=None, cMin=None, cMax=None, logScale=False,
**kwargs):
"""show resulting velocity vector"""
if cMin is None or cMax is None:
cMin, cMax = interperc(self.velocity, 3)
if ax is None:
ax, cbar = pg.show(self.mesh, self.velocity, logScale=logScale,
colorBar=True, cMin=cMin, cMax=cMax, **kwargs)
self.figs['result'] = plt.gcf()
else:
gci = drawModel(ax, self.mesh, self.velocity, logScale=logScale,
colorBar=True, cMin=cMin, cMax=cMax, **kwargs)
createColorbar(gci, **kwargs)
browser = CellBrowser(self.mesh, self.velocity, ax)
browser.connect()
self.axs['result'] = ax
if 'lines' in kwargs:
plotLines(ax, kwargs['lines'])
def showResult(self, ax=None, cMin=None, cMax=None, logScale=False, **kwargs):
"""show resulting velocity vector"""
if cMin is None or cMax is None:
cMin, cMax = interperc(self.velocity, 3)
if ax is None:
ax, cbar = pg.show(
self.mesh, self.velocity, logScale=logScale, colorBar=True, cMin=cMin, cMax=cMax, **kwargs
)
fig, ax = plt.subplots()
self.figs["result"] = fig
else:
gci = drawModel(
ax, self.mesh, self.velocity, logScale=logScale, colorBar=True, cMin=cMin, cMax=cMax, **kwargs
)
cbar = createColorbar(gci, **kwargs)
browser = CellBrowser(self.mesh, self.velocity, ax)
browser.connect()
plt.show() # block=False)
self.axs["result"] = ax
if "lines" in kwargs:
plotLines(ax, kwargs["lines"])
destPos=outmesh.cellCenters(), outVec=outdata)
return outdata
###############################################################################
# Visualization
# -------------
meshes = [coarse, fine]
datasets = [coarse_data, fine_data]
ints = [nearest_neighbor_interpolation,
linear_interpolation]
fig, axes = plt.subplots(2, 2, figsize=(5, 5))
# Coarse data to fine mesh
drawModel(axes[0, 0], fine, ints[0](coarse, coarse_data, fine), showCbar=False)
drawMesh(axes[0, 0], fine)
drawModel(axes[0, 1], fine, ints[1](coarse, coarse_data, fine), showCbar=False)
drawMesh(axes[0, 1], fine)
# Fine data to coarse mesh
drawModel(axes[1, 0], coarse, ints[0](fine, fine_data, coarse), showCbar=False)
drawMesh(axes[1, 0], coarse)
drawModel(axes[1, 1], coarse, ints[1](fine, fine_data, coarse), showCbar=False)
drawMesh(axes[1, 1], coarse)
titles = ["Coarse to fine\nwith nearest neighbors",
"Coarse to fine\nwith linear interpolation",
"Fine to coarse\nwith nearest neighbors",
"Fine to coarse\nwith linear interpolation"]
def main( argv ):
import argparse
parser = argparse.ArgumentParser( description = "Create GIMLi parameter mesh for a given datafile" )
parser.add_argument("-v", "--verbose", dest = "verbose", action = "store_true"
, help = "Be verbose.", default = False )
parser.add_argument("-o", "--output", dest = "outFileName"
, help = "File name for the resulting mesh. Default is [datafile.bms]"
, metavar = "File" )
parser.add_argument("-d", "--dimension", dest = "dimension"
, help = "Dimension of the mesh to be created"
, type = int
, default = "2" )
parser.add_argument("--paraDX", dest = "paraDX"
, help = "Horizontal distance between sensors, relative regarding sensor distance"
, type = float
, default = "1" )
parser.add_argument("--paraDepth", dest = "paraDepth"
, help = "Maximum depth (absolute meter) for parametric domain, 0[default] means 0.4 * max sensor range"
, type = float
, default = "0" )
parser.add_argument("--grid", dest = "grid"
, help = "Use a regular grid for parameter domain"
, action = "store_true"
, default = False )
parser.add_argument("--paraDZ", dest = "paraDZ"
, help = "Vertical distance to the first depth layer, relative regarding sensor distance. For --grid only"
, type = float
, default = "1" )
parser.add_argument("--nLayers", dest = "nLayers"
, help = "Number of depth layers [default = 11] For --grid only"
, type = int
, default = "11" )
parser.add_argument("--paraBoundary", dest = "paraBoundary"
, help = "Boundary offset for parameter domain in absolute sensor distance 2[default]"
, type = float
, default = "2" )
parser.add_argument( "--show", dest = "show"
, help = "Open a viewer window and show the mesh"
, action = "store_true"
, default = False )
parser.add_argument( 'dataFileName' )
options = parser.parse_args()
# create default output filename
if options.outFileName == None:
options.outFileName = options.dataFileName.replace('.dat','')
if options.verbose: print( options )
sensorPositions = pg.DataContainer( options.dataFileName ).sensorPositions()
if options.verbose: print(( "Sensorcount = ", len( sensorPositions ) ))
if options.dimension == 3:
raise Exception
swatch = pg.Stopwatch( True )
if options.dimension == 2:
mesh = createParaMesh2dGrid( sensors = sensorPositions,
paraDX = options.paraDX,
paraDZ = options.paraDZ,
paraDepth = options.paraDepth,
nLayers = options.nLayers,
boundary = -1,
paraBoundary = options.paraBoundary,
verbose = options.verbose, quality = 30.0, smooth = True)
if options.verbose:
print(( "generation takes ", swatch.duration(), " s" ))
print( mesh )
print(( "writing " + options.outFileName + '.bms' ))
mesh.save( options.outFileName )
if options.show:
ax = showMesh( mesh, showLater = True )
drawModel( ax, mesh, mesh.cellMarker(), alpha = 0.2 )
xl = ax.get_xlim()
yl = ax.get_ylim()
dx = ( xl[1] - xl[0] ) * 0.01
dy = ( yl[1] - yl[0] ) * 0.01
ax.set_xlim( xl[ 0 ] - dx, xl[ 1 ] + dx )
ax.set_ylim( yl[ 0 ] - dy, yl[ 1 ] + dy )
drawSensors( ax, sensorPositions )
plt.show()
def showResult(self,
val=None,
ax=None,
cMin=None,
cMax=None,
logScale=False,
rays=False,
name='result',
**kwargs):
"""Show resulting velocity vector.
Parameters
----------
val : result array [self.velocity]
field to show, usually the velocity vector
ax : matplotlib.axes
axes to plot into, if not give a new one-axis figure is created
cMin/cMax : float
minimum and maximum values for ranging colorbar
logScale : bool [False]
use logarithmic scale
rays : bool [False]
Show ray paths as well.
Other parameters
----------------
useCoverage : bool [True]
use standardized (0 or 1) ray coverage as alpha-shading
label : str
label to write on colorbar
orientaton : str
color bar orientation
nLevs : int [7]
number of level values for color bar
**kwargs : keyword arguments passed to the show function
Returns
-------
ax : maxplotlib axes
cb : matplotlib color bar object
"""
mesh = self.paraDomain()
if val is None:
val = self.velocity
if cMin is None or cMax is None:
cMin, cMax = interperc(val, 3)
coverage = 1
if kwargs.pop('useCoverage', True):
coverage = self.standardizedCoverage()
label = kwargs.pop("label", "Velocity (m/s)")
if ax is None:
fig, ax = plt.subplots()
self.figs[name] = fig
ax, cbar = pg.show(mesh,
val,
logScale=logScale,
ax=ax,
colorBar=True,
cMin=cMin,
cMax=cMax,
coverage=coverage,
label=label,
hold=True,
**kwargs)
self.figs[name] = plt.gcf()
else:
gci = drawModel(ax,
mesh,
val,
logScale=logScale,
colorBar=True,
cMin=cMin,
cMax=cMax,
coverage=coverage,
**kwargs)
labels = ['cMin', 'cMax', 'nLevs', 'orientation']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
cbar = createColorBar(gci, label=label, **subkwargs)
if rays:
self.showRayPaths(ax=ax, alpha=0.5, color="w", linewidths=.8)
browser = CellBrowser(self.mesh, val, ax)
browser.connect()
self.axs[name] = ax
if 'lines' in kwargs:
plotLines(ax, kwargs['lines'])
return ax, cbar
def test2d():
mesh = g.Mesh( 'mesh/world2d.bms' )
print mesh
xMin = mesh.boundingBox( ).min()[0]
yMax = mesh.boundingBox( ).max()[0]
x = P.arange( xMin, yMax, 1. );
mesh.createNeighbourInfos()
rho = g.RVector( len( mesh.cellAttributes() ), 1. ) * 2000.0
rho.setVal( 0.0, g.find( mesh.cellAttributes() == 1.0 ) )
swatch = g.Stopwatch( True )
pnts = []
spnts = g.stdVectorRVector3()
for i in x:
pnts.append( g.RVector3( i, 0.0001 ) )
spnts.append( g.RVector3( i, 0.0001 ) )
#gzC, GC = calcGCells( pnts, mesh, rho, 1 )
gzC = g.calcGCells( spnts , mesh, rho, 1 )
print "calcGCells", swatch.duration( True )
#gzB, GB = calcGBounds( pnts, mesh, rho )
gzB = g.calcGBounds( spnts , mesh, rho )
print "calcGBounds", swatch.duration( True )
gZ_Mesh = gzC
ax1, ax2 = getaxes()
# sphere analytical solution
gAna = analyticalCircle2D( spnts, radius = 2.0, pos = g.RVector3( 0.0, -5.0 ), dDensity = 2000 )
gAna2 = analyticalCircle2D( spnts, radius = 2.0, pos = g.RVector3( 5.0, -5.0 ), dDensity = 2000 )
gAna = gAna + gAna2
ax1.plot( x, gAna, '-x', label= 'Analytisch' )
ax1.plot( x, gZ_Mesh, label= 'WonBevis1987-mesh' )
print gAna / gZ_Mesh
#rho=GB[0]/mesh.cellSizes()
gci = drawModel( ax2, mesh, rho )
drawSelectedMeshBoundaries( ax2, mesh.findBoundaryByMarker( 0 )
, color = ( 1.0, 1.0, 1.0, 1.0 )
, linewidth = 0.3 )
drawSelectedMeshBoundaries( ax2, mesh.findBoundaryByMarker( 1 )
, color = ( 1.0, 1.0, 1.0, 1.0 )
, linewidth = 0.3 )
# sphere polygone
radius = 2.
depth = 5.
poly1 = g.stdVectorRVector3()
poly2 = g.stdVectorRVector3()
nSegment=124
for i in range( nSegment ):
xp = np.sin( (i+1) * ( 2. * np.pi ) / nSegment )
yp = np.cos( (i+1) * ( 2. * np.pi ) / nSegment )
poly1.append( g.RVector3( xp * radius, yp * radius - depth ) )
poly2.append( g.RVector3( xp * radius + 5., yp * radius - depth ) )
gZ_Poly = calcPolydgdz( spnts, poly1, 2000 )
gZ_Poly += calcPolydgdz( spnts, poly2, 2000 )
ax1.plot( x, gZ_Poly, label= 'WonBevis1987-Poly' )
ax2.plot( g.x( poly1 ), g.y( poly1 ), color = 'red' )
ax2.plot( g.x( poly2 ), g.y( poly2 ), color = 'red' )
ax2.plot( g.x( spnts ), g.y( spnts ), marker = 'x', color = 'black' )
# test some special case
for i, p in enumerate( poly1 ):
poly1[i] = g.RVector3( poly1[i] - g.RVector3( 5.0, -6. ) )
ax2.plot( g.x( poly1 ), g.y( poly1 ), color = 'green' )
gz = calcPolydgdz( spnts, poly1, 2000 )
ax1.plot( x, gz, label= 'Special Case', color = 'green' )
ax1.set_ylabel( 'dg/dz [mGal]' )
ax2.set_ylabel( 'Tiefe [m]' )
ax1.legend()
ax2.set_xlim( [ x[0], x[-1] ] )
ax2.grid()
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 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
def test2d():
mesh = pg.Mesh('mesh/world2d.bms')
print(mesh)
xMin = mesh.boundingBox().min()[0]
yMax = mesh.boundingBox().max()[0]
x = np.arange(xMin, yMax, 1.)
mesh.createNeighbourInfos()
rho = pg.RVector(len(mesh.cellAttributes()), 1.) * 2000.0
rho.setVal(0.0, pg.find(mesh.cellAttributes() == 1.0))
swatch = pg.Stopwatch(True)
pnts = []
spnts = pg.stdVectorRVector3()
for i in x:
pnts.append(pg.RVector3(i, 0.0001))
spnts.append(pg.RVector3(i, 0.0001))
# gzC, GC = calcGCells(pnts, mesh, rho, 1)
gzC = pg.calcGCells(spnts, mesh, rho, 1)
print("calcGCells", swatch.duration(True))
# gzB, GB = calcGBounds(pnts, mesh, rho)
# gzB = pg.calcGBounds(spnts, mesh, rho)
# print("calcGBounds", swatch.duration(True))
gZ_Mesh = gzC
ax1, ax2 = getaxes()
# sphere analytical solution
gAna = analyticalCircle2D(spnts,
radius=2.0,
pos=pg.RVector3(0.0, -5.0),
dDensity=2000)
gAna2 = analyticalCircle2D(spnts,
radius=2.0,
pos=pg.RVector3(5.0, -5.0),
dDensity=2000)
gAna = gAna + gAna2
ax1.plot(x, gAna, '-x', label='analytical')
ax1.plot(x, gZ_Mesh, label='WonBevis1987-mesh')
print(gAna / gZ_Mesh)
# rho=GB[0]/mesh.cellSizes()
drawModel(ax2, mesh, rho)
for i in (0, 1):
drawSelectedMeshBoundaries(ax2,
mesh.findBoundaryByMarker(i),
color=(1.0, 1.0, 1.0, 1.0),
linewidth=0.3)
# sphere polygone
radius = 2.
depth = 5.
poly1 = pg.stdVectorRVector3()
poly2 = pg.stdVectorRVector3()
nSegment = 124
for i in range(nSegment):
xp = np.sin((i + 1) * (2. * np.pi) / nSegment)
yp = np.cos((i + 1) * (2. * np.pi) / nSegment)
poly1.append(pg.RVector3(xp * radius, yp * radius - depth))
poly2.append(pg.RVector3(xp * radius + 5., yp * radius - depth))
gZ_Poly = calcPolydgdz(spnts, poly1, 2000)
gZ_Poly += calcPolydgdz(spnts, poly2, 2000)
ax1.plot(x, gZ_Poly, label='WonBevis1987-Poly')
ax2.plot(pg.x(poly1), pg.y(poly1), color='red')
ax2.plot(pg.x(poly2), pg.y(poly2), color='red')
ax2.plot(pg.x(spnts), pg.y(spnts), marker='x', color='black')
# test some special case
for i, p in enumerate(poly1):
poly1[i] = pg.RVector3(poly1[i] - pg.RVector3(5.0, -6.))
ax2.plot(pg.x(poly1), pg.y(poly1), color='green')
gz = calcPolydgdz(spnts, poly1, 2000)
ax1.plot(x, gz, label='Special Case', color='green')
ax1.set_ylabel('dg/dz [mGal]')
ax2.set_ylabel('Tiefe [m]')
ax1.legend()
ax2.set_xlim([x[0], x[-1]])
ax2.grid()
def showResult(self, val=None, ax=None, cMin=None, cMax=None,
logScale=False, rays=False, name='result', **kwargs):
"""Show resulting velocity vector.
Parameters
----------
val : result array [self.velocity]
field to show, usually the velocity vector
ax : matplotlib.axes
axes to plot into, if not give a new one-axis figure is created
cMin/cMax : float
minimum and maximum values for ranging colorbar
logScale : bool [False]
use logarithmic scale
rays : bool [False]
Show ray paths as well.
Other parameters
----------------
useCoverage : bool [True]
use standardized (0 or 1) ray coverage as alpha-shading
label : str
label to write on colorbar
orientaton : str
color bar orientation
nLevs : int [7]
number of level values for color bar
**kwargs : keyword arguments passed to the show function
Returns
-------
ax : maxplotlib axes
cb : matplotlib color bar object
"""
mesh = self.paraDomain()
if val is None:
val = self.velocity
if cMin is None or cMax is None:
cMin, cMax = interperc(val, 3)
coverage = 1
if kwargs.pop('useCoverage', True):
coverage = self.standardizedCoverage()
label = kwargs.pop("label", "Velocity (m/s)")
if ax is None:
fig, ax = plt.subplots()
self.figs[name] = fig
ax, cbar = pg.show(mesh, val, logScale=logScale, ax=ax,
colorBar=True, cMin=cMin, cMax=cMax,
coverage=coverage, label=label, hold=True,
**kwargs)
self.figs[name] = plt.gcf()
else:
gci = drawModel(ax, mesh, val, logScale=logScale,
colorBar=True, cMin=cMin, cMax=cMax,
coverage=coverage, **kwargs)
labels = ['cMin', 'cMax', 'nLevs', 'orientation']
subkwargs = {key: kwargs[key] for key in labels if key in kwargs}
cbar = createColorBar(gci, label=label, **subkwargs)
if rays:
self.showRayPaths(ax=ax, alpha=0.5, color="w", linewidths=.8)
browser = CellBrowser(self.mesh, val, ax)
browser.connect()
self.axs[name] = ax
if 'lines' in kwargs:
plotLines(ax, kwargs['lines'])
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 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
def test2d():
mesh = pg.Mesh("mesh/world2d.bms")
print (mesh)
xMin = mesh.boundingBox().min()[0]
yMax = mesh.boundingBox().max()[0]
x = np.arange(xMin, yMax, 1.0)
mesh.createNeighbourInfos()
rho = pg.RVector(len(mesh.cellAttributes()), 1.0) * 2000.0
rho.setVal(0.0, pg.find(mesh.cellAttributes() == 1.0))
swatch = pg.Stopwatch(True)
pnts = []
spnts = pg.stdVectorRVector3()
for i in x:
pnts.append(pg.RVector3(i, 0.0001))
spnts.append(pg.RVector3(i, 0.0001))
# gzC, GC = calcGCells(pnts, mesh, rho, 1)
gzC = pg.calcGCells(spnts, mesh, rho, 1)
print ("calcGCells", swatch.duration(True))
# gzB, GB = calcGBounds(pnts, mesh, rho)
# gzB = pg.calcGBounds(spnts, mesh, rho)
# print("calcGBounds", swatch.duration(True))
gZ_Mesh = gzC
ax1, ax2 = getaxes()
# sphere analytical solution
gAna = analyticalCircle2D(spnts, radius=2.0, pos=pg.RVector3(0.0, -5.0), dDensity=2000)
gAna2 = analyticalCircle2D(spnts, radius=2.0, pos=pg.RVector3(5.0, -5.0), dDensity=2000)
gAna = gAna + gAna2
ax1.plot(x, gAna, "-x", label="analytical")
ax1.plot(x, gZ_Mesh, label="WonBevis1987-mesh")
print (gAna / gZ_Mesh)
# rho=GB[0]/mesh.cellSizes()
drawModel(ax2, mesh, rho)
for i in (0, 1):
drawSelectedMeshBoundaries(ax2, mesh.findBoundaryByMarker(i), color=(1.0, 1.0, 1.0, 1.0), linewidth=0.3)
# sphere polygone
radius = 2.0
depth = 5.0
poly1 = pg.stdVectorRVector3()
poly2 = pg.stdVectorRVector3()
nSegment = 124
for i in range(nSegment):
xp = np.sin((i + 1) * (2.0 * np.pi) / nSegment)
yp = np.cos((i + 1) * (2.0 * np.pi) / nSegment)
poly1.append(pg.RVector3(xp * radius, yp * radius - depth))
poly2.append(pg.RVector3(xp * radius + 5.0, yp * radius - depth))
gZ_Poly = calcPolydgdz(spnts, poly1, 2000)
gZ_Poly += calcPolydgdz(spnts, poly2, 2000)
ax1.plot(x, gZ_Poly, label="WonBevis1987-Poly")
ax2.plot(pg.x(poly1), pg.y(poly1), color="red")
ax2.plot(pg.x(poly2), pg.y(poly2), color="red")
ax2.plot(pg.x(spnts), pg.y(spnts), marker="x", color="black")
# test some special case
for i, p in enumerate(poly1):
poly1[i] = pg.RVector3(poly1[i] - pg.RVector3(5.0, -6.0))
ax2.plot(pg.x(poly1), pg.y(poly1), color="green")
gz = calcPolydgdz(spnts, poly1, 2000)
ax1.plot(x, gz, label="Special Case", color="green")
ax1.set_ylabel("dg/dz [mGal]")
ax2.set_ylabel("Tiefe [m]")
ax1.legend()
ax2.set_xlim([x[0], x[-1]])
ax2.grid()
pg.cellDataToPointData(inmesh, indata)
return outdata
###############################################################################
# Visualization
# -------------
meshes = [coarse, fine]
datasets = [coarse_data, fine_data]
ints = [nearest_neighbor_interpolation, linear_interpolation]
fig, ax = plt.subplots(2, 2, figsize=(5, 5))
# Coarse data to fine mesh
drawModel(ax[0, 0], fine, ints[0](coarse, coarse_data, fine), showCbar=False)
drawMesh(ax[0, 0], fine)
drawModel(ax[0, 1], fine, ints[1](coarse, coarse_data, fine), showCbar=False)
drawMesh(ax[0, 1], fine)
# Fine data to coarse mesh
drawModel(ax[1, 0], coarse, ints[0](fine, fine_data, coarse), showCbar=False)
drawMesh(ax[1, 0], coarse)
drawModel(ax[1, 1], coarse, ints[1](fine, fine_data, coarse), showCbar=False)
drawMesh(ax[1, 1], coarse)
titles = [
"Coarse to fine\nwith nearest neighbors",
"Coarse to fine\nwith linear interpolation",
"Fine to coarse\nwith nearest neighbors",
"Fine to coarse\nwith linear interpolation"