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