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 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 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,
**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.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
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
showMesh : bool [False]
Shows the the mesh itself aditional.
**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.axes
colobar : matplotlib.colorbar
"""
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)
elif isinstance(data, pg.R3Vector):
drawStreams(ax, mesh, 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] 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:
print("No valid stream data:", data.shape, data.ndim)
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 showMesh:
pg.show(mesh, ax=ax)
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 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 type(data) is list and \
type(data[0]) is list and type(data[0][0]) is 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:
pg.mplviewer.drawPLC(ax, mesh, **kwargs)
showMesh = False
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)
if kwargs.pop('fitView', True):
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))
#print('show.ticks ********************', ticks)
cbar.set_ticks(ticks)
labels = []
for marker in uniquemarkers:
labels.append(str((marker)))
#print('show.labels ********************', labels)
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 showMesh:
drawMesh(ax, mesh, **kwargs)
if showBoundary is True or showBoundary is 1:
b = mesh.boundaries(pg.find(mesh.boundaryMarkers() != 0))
pg.mplviewer.drawSelectedMeshBoundaries(ax,
b,
color=(0.0, 0.0, 0.0, 1.0),
linewidth=1.4)
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 as _:
pass
print('..done')
return ax, cbar
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