Zone Analysis

Another use of the built in framework tools might be a structural analysis of cellular networks. In this case, the previously presented example ( is used to acquire the tissue. Then the connected fragments of the tissue are found with the following function:

def set_influence_zones( wt, **keys):
    def f( wt, directed_cell_edge ):
        return wt.directed_cell_edge_property( directed_cell_edge, "PIN")

    from openalea.stse.structures.algo.walled_tissue_influence_zones import set_property_on_tissue_component
    for i in regions2cells:
        #print zones[ i ]
        for j in regions2cells[ i ]:
            set_property_on_tissue_component( wt=wt,
                                 cell= j,

Then the specific display can be used for presenting the tissue components:

def f_pin( wt ):
    """Function returning function which returns the membrane thickness according
    to PIN cell_edge property.

    <Long description of the function functionality.>

        wt : `WalledTissue`
            Tissue containing cell data
    :rtype: function
    :return: Function which returns the membrane thickness according
    to PIN cell_edge property.

    f1 = f_property2scalar(  wt_property_method=wt.directed_cell_edge_property,
                        property = "PIN",
                        default_value = 0.,
                        segment = (0, 1),
                        factor = 1.)
    def f( cell, edge ):
            ce = wv_edge2cell_edge( wt, edge )
            if ce[ 1 ] == cell: ce=(ce[1],ce[0])
            v = f1( ce )
        except TypeError:
            v = f1( None )
        return v
    return f

# sample visualization using plantGL
def vis( wt, config, props=[], clear=False, save=False ):
    """Displaying of IZ and saving the results.

    for prop in props:
        if clear: pd.SCENES[ pd.CURRENT_SCENE ].clear()
        visualisation_pgl_2D_varried_membrane_thickness( wt,
                                            f_membrane_thickness = f_pin( wt ),
                                            f_cell_marking = [f_cell_marking( properties=config.cell_regions.keys(), property_true_radius=0.2)],
                                            f_material = f_properties2material( [prop] ),
                                            reverse = True
        if save: pgl.Viewer.frameGL.saveImage( config.file_folder+"/"+"iz"+prop+".png" )

The final result is presented here:

Zone Analysis tutorial result 1 Zone Analysis tutorial result 2 Zone Analysis tutorial result 3 Zone Analysis tutorial result 4
Zone Analysis tutorial result 5 Zone Analysis tutorial result 6