Пример #1
0
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
Пример #2
0
def main( argv ):
    
    import argparse
    
    parser = argparse.ArgumentParser( description = "Create GIMLi parameter mesh for a given datafile" )
        
    parser.add_argument("-v", "--verbose", dest = "verbose", action = "store_true"
                            , help = "Be verbose.", default = False )
    parser.add_argument("-o", "--output", dest = "outFileName"
                            , help = "File name for the resulting mesh. Default is [datafile.bms]"
                            , metavar = "File" )
    parser.add_argument("-d", "--dimension", dest = "dimension"
                            , help = "Dimension of the mesh to be created"
                            , type = int
                            , default = "2" )
    parser.add_argument("--paraDX", dest = "paraDX"
                            , help = "Horizontal distance between sensors, relative regarding sensor distance"
                            , type = float
                            , default = "1" )
    parser.add_argument("--paraDepth", dest = "paraDepth"
                            , help = "Maximum depth (absolute meter) for parametric domain, 0[default] means 0.4 * max sensor range"
                            , type = float
                            , default = "0" )
    parser.add_argument("--grid", dest = "grid"
                            , help = "Use a regular grid for parameter domain"
                            , action = "store_true"
                            , default = False )
    parser.add_argument("--paraDZ", dest = "paraDZ"
                            , help = "Vertical distance to the first depth layer, relative regarding sensor distance. For --grid only"
                            , type = float
                            , default = "1" )
    parser.add_argument("--nLayers", dest = "nLayers"
                            , help = "Number of depth layers [default = 11] For --grid only"
                            , type = int
                            , default = "11" )
                            
    parser.add_argument("--paraBoundary", dest = "paraBoundary"
                            , help = "Boundary offset for parameter domain in absolute sensor distance 2[default]"
                            , type = float
                            , default = "2" )
                            
    parser.add_argument( "--show", dest = "show"
                            , help = "Open a viewer window and show the mesh"
                            , action = "store_true"
                            , default = False )

    parser.add_argument( 'dataFileName' )

    options = parser.parse_args()
    
    # create default output filename
    if options.outFileName == None:
        options.outFileName = options.dataFileName.replace('.dat','') 
    
    if options.verbose: print( options )

    sensorPositions = pg.DataContainer( options.dataFileName ).sensorPositions()
    
    if options.verbose: print(( "Sensorcount = ", len( sensorPositions ) ))
    
    if options.dimension == 3:
        raise Exception
    
    swatch = pg.Stopwatch( True )
    if options.dimension == 2:
        
        mesh = createParaMesh2dGrid( sensors = sensorPositions, 
                                     paraDX = options.paraDX,
                                     paraDZ = options.paraDZ,
                                     paraDepth = options.paraDepth,
                                     nLayers = options.nLayers,
                                     boundary = -1,       
                                     paraBoundary = options.paraBoundary, 
                                     verbose = options.verbose, quality = 30.0, smooth = True)
    
    if options.verbose:
        print(( "generation takes ", swatch.duration(), " s" ))
        print( mesh )
        print(( "writing " + options.outFileName + '.bms' ))
    
    mesh.save( options.outFileName )
    
    if options.show:
        ax = showMesh( mesh, showLater = True  )
        drawModel( ax, mesh, mesh.cellMarker(), alpha = 0.2 )
        xl = ax.get_xlim()
        yl = ax.get_ylim()        
        dx = ( xl[1] - xl[0] ) * 0.01
        dy = ( yl[1] - yl[0] ) * 0.01

        ax.set_xlim( xl[ 0 ] - dx, xl[ 1 ] + dx )
        ax.set_ylim( yl[ 0 ] - dy, yl[ 1 ] + dy )
        
        drawSensors( ax, sensorPositions )
        
        plt.show() 
Пример #3
0
EN = len(sensors) - 3

sensors_n = np.array(sensors)
# Combine two injection - 2 current sources
# sensors_n[EA,0:2]=[-3.5, -1]
# sensors_n[EA,0:2]=[3, -6.25]

# injection in the conductive boday
sensors_n[EA, 0:2] = [0, -3.25]

sensors_n[EB, 0:2] = [-150, 0]
sensors_n[EN, 0:2] = [150, 0]

fig, ax = plt.subplots()
pg.show(geom, ax=ax)
drawSensors(ax, sensors_n, diam=0.6)
# ax.figure.savefig(directoryFig +'/'
#                   +'MeshERTFwd.png',dpi=350)
# mesh_root.save(path_Scheme +'/'+ SimuName + '/'  '/MeshERTFwd.bms')
# drawSensors(ax, sensors=sensors_n, diam=0.01)

# Create suitable mesh for ert forward calculation

World_VRTs = mt.createWorld(
    start=[-160, -160], end=[160, 0]
)  #Extend world if pole pole acquisition in the field ; Take care of boundary conditions !
geom_VRTs = mt.mergePLC([World_VRTs, geom])
# geom = mt.mergePLC([world, block])
pg.show(geom_VRTs)

## --------- create vRTE positions in regular grid 2d --------- ##
Пример #4
0
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
Пример #5
0
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
Пример #6
0
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