def cmapFromName(cmapname='jet', ncols=256, bad=None, **kwargs):
"""Get a colormap either from name or from keyworld list.
See http://matplotlib.org/examples/color/colormaps_reference.html
Parameters
----------
cmapname : str
Name for the colormap.
ncols : int
Amount of colors.
bad : [r,g,b,a]
Default color for bad values [nan, inf] [white]
** kwargs :
cMap : str
Name for the colormap
cmap : str
colormap name (old)
Returns
-------
cMap:
matplotlib Colormap
"""
if not bad:
bad = [1.0, 1.0, 1.0, 0.0]
pg.renameKwarg('cmap', 'cMap', kwargs)
if 'cmap' in kwargs:
cmapname = kwargs.pop('cmap', cmapname)
elif 'cMap' in kwargs:
cmapname = kwargs.pop('cMap', cmapname)
cMap = None
if cmapname is None:
cmapname = 'jet'
if cmapname == 'b2r':
pg.warn("Don't use manual b2r cMap, use MPL internal 'RdBu' instead.")
cMap = mpl.colors.LinearSegmentedColormap('my_colormap', cdict, ncols)
# elif cmapname == 'viridis' and \
# LooseVersion(mpl.__version__) < LooseVersion('1.5.0'):
# print("Mpl:", mpl.__version__, " using HB viridis")
# cmap = LinearSegmentedColormap.from_list('viridis', viridis_data[::-1])
# elif cmapname == 'viridis_r':
# print("Using HB viridis_r")
# cmap = LinearSegmentedColormap.from_list('viridis', viridis_data)
else:
try:
cMap = mpl.cm.get_cmap(cmapname, ncols)
except BaseException as e:
pg.warn("Could not retrieve colormap ", cmapname, e)
cMap.set_bad(bad)
return cMap
def simulate(mesh, res, scheme, verbose=False, **kwargs):
"""Forward calculation vor given mesh, data and resistivity."""
fop = ERTModelling(verbose=verbose)
# fop = ERTManager.createFOP(verbose=verbose)
fop.setData(scheme)
fop.setMesh(mesh, ignoreRegionManager=True)
if not scheme.allNonZero('k'):
if min(pg.y(scheme)) != max(pg.y(scheme)) or min(
pg.z(scheme)) != max(pg.z(scheme)):
pg.info(
"Non flat earth topography found. "
"We will set geometric factors to -1 to emulate "
"electrical impedance tomography (EIT). If you want to "
"use ERT will full topography support. "
"Please consider the use of pyBERT.")
scheme.set('k', pg.RVector(scheme.size(), -1))
else:
scheme.set('k', fop.calcGeometricFactors(scheme))
rhoa = None
isArrayData = None
if hasattr(res[0], '__iter__'):
isArrayData = True
rhoa = np.zeros((len(res), scheme.size()))
for i, r in enumerate(res):
rhoa[i] = fop.response(r)
else:
rhoa = fop.response(res)
pg.renameKwarg('noisify', 'noiseLevel', kwargs)
noiseLevel = kwargs.pop('noiseLevel', 0.0)
if noiseLevel > 0:
noiseAbs = kwargs.pop('noiseAbs', 1e-4)
err = noiseLevel + noiseAbs / rhoa
scheme.set('err', err)
if verbose:
pg.info(
"Set noise (" + str(noiseLevel * 100) + "% + " +
str(noiseAbs) + " V) min:", min(err), "max:", max(err))
rhoa *= 1. + pg.randn(scheme.size()) * err
if isArrayData is None:
scheme.set('rhoa', rhoa)
if kwargs.pop('returnArray', False):
return rhoa
return scheme
def cmapFromName(cmapname='jet', ncols=256, bad=None, **kwargs):
"""Get a colormap either from name or from keyworld list.
See http://matplotlib.org/examples/color/colormaps_reference.html
Parameters
----------
cmapname : str
Name for the colormap.
ncols : int
Amount of colors.
bad : [r,g,b,a]
Default color for bad values [nan, inf] [white]
** kwargs :
cMap : str
Name for the colormap
cmap : str
colormap name (old)
Returns
-------
cMap:
matplotlib Colormap
"""
if not bad:
bad = [1.0, 1.0, 1.0, 0.0]
pg.renameKwarg('cmap', 'cMap', kwargs)
if 'cmap' in kwargs:
cmapname = kwargs.pop('cmap', cmapname)
elif 'cMap' in kwargs:
cmapname = kwargs.pop('cMap', cmapname)
cMap = None
if cmapname is None:
cmapname = 'jet'
if cmapname == 'b2r':
pg.warn("Don't use manual b2r cMap, use MPL internal 'RdBu' instead.")
cMap = "RdBu_r"
else:
try:
cMap = mpl.cm.get_cmap(cmapname, ncols)
except BaseException as e:
pg.warn("Could not retrieve colormap ", cmapname, e)
cMap.set_bad(bad)
return cMap
def cmapFromName(cmapname='jet', ncols=256, bad=None, **kwargs):
"""Get a colormap either from name or from keyworld list.
See http://matplotlib.org/examples/color/colormaps_reference.html
Parameters
----------
cmapname : str
Name for the colormap.
ncols : int
Amount of colors.
bad : [r,g,b,a]
Default color for bad values [nan, inf] [white]
** kwargs :
cMap : str
Name for the colormap
cmap : str
colormap name (old)
Returns
-------
cMap:
matplotlib Colormap
"""
if not bad:
bad = [1.0, 1.0, 1.0, 0.0]
pg.renameKwarg('cmap', 'cMap', kwargs)
if 'cmap' in kwargs:
cmapname = kwargs.pop('cmap', cmapname)
elif 'cMap' in kwargs:
cmapname = kwargs.pop('cMap', cmapname)
cMap = None
if cmapname is None:
cmapname = 'jet'
if cmapname == 'b2r':
pg.warn("Don't use manual b2r cMap, use MPL internal 'RdBu' instead.")
cMap = "RdBu_r"
else:
try:
cMap = mpl.cm.get_cmap(cmapname, ncols)
except BaseException as e:
pg.warn("Could not retrieve colormap ", cmapname, e)
cMap.set_bad(bad)
return cMap
def simulate(mesh, res, scheme, verbose=False, **kwargs):
"""Forward calculation vor given mesh, data and resistivity."""
fop = ERTModelling(verbose=verbose)
# fop = ERTManager.createFOP(verbose=verbose)
fop.setData(scheme)
fop.setMesh(mesh, ignoreRegionManager=True)
if not scheme.allNonZero('k'):
if min(pg.y(scheme)) != max(pg.y(scheme)) or min(pg.z(scheme)) != max(pg.z(scheme)):
pg.info("Non flat earth topography found. "
"We will set geometric factors to -1 to emulate "
"electrical impedance tomography (EIT). If you want to "
"use ERT will full topography support. "
"Please consider the use of pyBERT.")
scheme.set('k', pg.RVector(scheme.size(), -1))
else:
scheme.set('k', fop.calcGeometricFactors(scheme))
rhoa = None
isArrayData = None
if hasattr(res[0], '__iter__'):
isArrayData = True
rhoa = np.zeros((len(res), scheme.size()))
for i, r in enumerate(res):
rhoa[i] = fop.response(r)
else:
rhoa = fop.response(res)
pg.renameKwarg('noisify', 'noiseLevel', kwargs)
noiseLevel = kwargs.pop('noiseLevel', 0.0)
if noiseLevel > 0:
noiseAbs = kwargs.pop('noiseAbs', 1e-4)
err = noiseLevel + noiseAbs / rhoa
scheme.set('err', err)
if verbose:
pg.info("Set noise (" + str(noiseLevel*100) + "% + " + str(noiseAbs) + " V) min:",
min(err), "max:", max(err))
rhoa *= 1. + pg.randn(scheme.size()) * err
if isArrayData is None:
scheme.set('rhoa', rhoa)
if kwargs.pop('returnArray', False):
return rhoa
return scheme
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 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