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