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
# default (natural) BC that are of homogeneous Neumann type # :math:`\frac{\partial u}{\partial n}=0` ax = show(grid, data=u, filled=True, colorBar=True, orientation='vertical', label='Solution $u$', levels=np.linspace(min(u), max(u), 14), hold=1)[0] ############################################################################### # Instead of the grid we now want to add streamlines to show the gradients of # the solution (i.e., the flow direction). drawStreams(ax, grid, u) ax.text(0.0, 1.01, '$u=1$', horizontalalignment='center') # top -- 3 ax.text(-1.0, 0.0, '$\partial u/\partial n=-0.5$', va='center', ha='right', rotation='vertical') # left -- 1 ax.text(0.0, -1.01, '$\partial u/\partial n=2.5$', ha='center', va='top') # bot -- 4 ax.text(1.01, 0.0, '$\partial u/\partial n=0$', va='center', ha='left',
[3, lambda b_: 1. - np.tanh(10.)], [4, lambda b_: 1. + np.tanh(10 * (2 * b_.center()[0] + 1.))], ] print ("start", swatch.duration()) uGrid = solveFiniteVolume(grid, a=1./Peclet, f=f, vel=vB, uBoundary=dirichletBC, duBoundary=neumannBC, scheme=scheme) ax1,cb = show(grid) drawStreams(ax1, grid, vC, coarseMesh=pg.createGrid(x=np.linspace(-1.0, 1.0, 41), y=np.linspace(0.0, 1.0, 21)), ) print(swatch.duration()) #grid2, u2 = createFVPostProzessMesh(grid, u, dirichletBC) show(grid, data=uGrid, logScale=False, interpolate=1, tri=1, colorBar=True, axes=ax1) #unstructured boundary = [] boundary.append([-1.0, 0.0]) boundary.append([ 0.0, 0.0]) boundary.append([ 1.0, 0.0]) boundary.append([ 1.0, 1.0]) boundary.append([-1.0, 1.0])
[4, lambda b_: 1. + np.tanh(10 * (2 * b_.center()[0] + 1.))], ] print ("start", swatch.duration()) uGrid = solveFiniteVolume(grid, a=1./Peclet, f=f, vel=vB, uBoundary=dirichletBC, duBoundary=neumannBC, scheme=scheme) pg.showLater(1) ax1,cb = show(grid) drawStreams(ax1, grid, vC, coarseMesh=pg.createGrid(x=np.linspace(-1.0, 1.0, 41), y=np.linspace(0.0, 1.0, 21)), ) print(swatch.duration()) #grid2, u2 = createFVPostProzessMesh(grid, u, dirichletBC) show(grid, data=uGrid, logScale=False, interpolate=1, tri=1, colorBar=True, axes=ax1) #unstructured boundary = [] boundary.append([-1.0, 0.0]) boundary.append([ 0.0, 0.0]) boundary.append([ 1.0, 0.0]) boundary.append([ 1.0, 1.0]) boundary.append([-1.0, 1.0])
k = 1e-3 sigma = 1 u = solve(grid, a=sigma, b=sigma * k*k, f=pointSource, duB=neumannBC, userData={'sourcePos': sourcePosA, 'k': k}, verbose=True) u -= solve(grid, a=sigma, b=sigma * k*k, f=pointSource, duB=neumannBC, userData={'sourcePos': sourcePosB, 'k': k}, verbose=True) # uAna = pg.RVector(map(lambda p__: uAnalytical(p__, sourcePosA, k), # grid.positions())) # uAna -= pg.RVector(map(lambda p__: uAnalytical(p__, sourcePosB, k), # grid.positions())) # err = (1.0 -u/uAna) * 100.0 # print("error min max", min(err), max(err)) ax = show(grid, data=u, filled=True, colorBar=True, cmap="RdBu_r", orientation='horizontal', label='Solution u', hold=True)[0] show(grid, ax=ax, hold=True) gridCoarse = pg.createGrid(x=np.linspace(-10.0, 10.0, 20), y=np.linspace(-15.0, .0, 20)) # Instead of the grid we want to add streamlines to the plot to show the # gradients of the solution. drawStreams(ax, grid, u, coarseMesh=gridCoarse, color='Black') pg.wait()
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
u -= solve(grid, a=sigma, b=-sigma * k*k, f=pointSource(grid, sourcePosB), bc={'Robin': robBC}, userData={'sourcePos': sourcePosB, 'k': k}, verbose=True) # uAna = pg.RVector(map(lambda p__: uAnalytical(p__, sourcePosA, k), # grid.positions())) # uAna -= pg.RVector(map(lambda p__: uAnalytical(p__, sourcePosB, k), # grid.positions())) # err = (1.0 -u/uAna) * 100.0 # print("error min max", min(err), max(err)) ax = show(grid, data=u, fillContour=True, colorBar=True, cMap="RdBu_r", orientation='horizontal', label='Solution u', nLevs=11, logScale=False, hold=True, showMesh=True)[0] # Additional to the image of the potential we want to see the current flow too. # The current flows along the gradient of our solution and can be plotted as # stream lines. On default the drawStreams method draws one segment of a # stream line per cell of the mesh. This can be a little confusing for dense # meshes so we can give a second (coarse) mesh as a new cell basis to draw the # streams. If the drawStreams get scalar data the gradients will be calculated. gridCoarse = pg.createGrid(x=np.linspace(-10.0, 10.0, 20), y=np.linspace(-15.0, .0, 20)) drawStreams(ax, grid, u, coarseMesh=gridCoarse, color='Black') pg.wait()
# or natural BC that are of homogeneous Neumann type # :math:`\frac{\partial u}{\partial n}=0` ax = show( grid, data=u, filled=True, colorBar=True, orientation="vertical", label="Solution $u$", levels=np.linspace(min(u), max(u), 14), hold=1, )[0] ############################################################################### # Instead of the grid we now want to add streamlines to the plot to show the # gradients of the solution (i.e., the flow direction). drawStreams(ax, grid, u) ax.text(0.0, 1.01, "$u=1$", horizontalalignment="center") # top -- 3 ax.text(-1.0, 0.0, "$\partial u/\partial n=-0.5$", va="center", ha="right", rotation="vertical") # left -- 1 ax.text(0.0, -1.01, "$\partial u/\partial n=2.5$", ha="center", va="top") # bot -- 4 ax.text(1.01, 0.0, "$\partial u/\partial n=0$", va="center", ha="left", rotation="vertical") # right -- 2 ax.set_title("$\\nabla\cdot(1\\nabla u)=0$") ax.set_xlim([-1.1, 1.1]) ax.set_ylim([-1.1, 1.1]) pg.wait()
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
grid=pg.createGrid(x,y) fig = plt.figure() ax1 = fig.add_subplot(1, 3, 1) ax2 = fig.add_subplot(1, 3, 2) ax3 = fig.add_subplot(1, 3, 3) pl = pg.logTransDropTol(np.array((p.T).flat), 1e-2) ul = pg.logTransDropTol(np.array((u.T).flat), 1e-2) vl = pg.logTransDropTol(np.array((v.T).flat), 1e-2) show(grid, pl, logScale=False, showLater=True, colorBar=True, axes=ax1, cmap='b2r') show(grid, ul, logScale=False, showLater=True, colorBar=True, axes=ax2) show(grid, vl, logScale=False, showLater=True, colorBar=True, axes=ax3) vel = np.vstack([np.array((u.T).flat), np.array((v.T).flat)]).T drawStreams(ax1, grid, vel) #im1 = ax1.contourf(X,Y,p,alpha=0.5) ###plnttong the pressure field as a contour #divider1 = make_axes_locatable(ax1) #cax1 = divider1.append_axes("right", size="20%", pad=0.05) #cbar1 = plt.colorbar(im1, cax=cax1) #im2 = ax2.contourf(X,Y,u,alpha=0.5) ###plnttong the pressure field as a contour #divider2 = make_axes_locatable(ax2) #cax2 = divider2.append_axes("right", size="20%", pad=0.05) #cbar2 = plt.colorbar(im2, cax=cax2) #im3 = ax3.contourf(X,Y,v,alpha=0.5) ###plnttong the pressure field as a contour #divider3 = make_axes_locatable(ax3) #cax3 = divider3.append_axes("right", size="20%", pad=0.05) #cbar3 = plt.colorbar(im3, cax=cax3)