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 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 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
)
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"])
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
