.. _sec-plot_clip: plot.plot_clip ============== ``plot_clip(clp, fig=None, region=None, show=False, savefile=None, projection="M15c")`` Plots outline of a clipping mask. Arguments: ---------- - **clp** (*pd.DataFrame or str*): clipping mask - **fig** (*pygmt.Figure, optional*): figure object to append features to. Defaults to None. - **region** (*list, optional*): defines the region extent[xmin,xmax,ymin,ymax,zmin,zmax]. Defaults to None. - **show** (*bool, optional*): displays the figure. Defaults to False. - **savefile** (*str, optional*): file path to save figure to - **projection** (*str, optional*): map projection to use. Defaults to "M15c". Returns: ------- *None* Example ------- .. code-block:: python import plot import pygmt # load in the synthetic test model as a slab_model instance model = plot.slab_model("../output/exp_slab2_04-18","surface") # synthetic test slab made with the 04-18 database # initialize figure as pygmt.Figure fig = pygmt.Figure() # making a plot of the model depth plot.plot( model.dep_grid, # specifies which grid object to plot fig=fig, # add this plot to the existing figure contours=True, # add contour lines to the plot basemap=True, # add basemap to the plot nan_transparent=True, # removing nan values to make basemap visible title="exp slab model with 04-18 database", # adding a title to the plot dtype="depth", # specifying the datatype for labeling the colorbar region=model.region, # specifying the region boundaries to use show=False, # do not display the figure ) # plotting the clipping mask on top of the model depth plot plot.plot_clip( model.clp, # using the clipping mask associated with the previously defined model fig=fig, # add this plot to the existing figure region=model.region, # specify the region boundaries show=True, # display the figure now that all features have been added savefile="output/exp_slab2_04-18_depth_with_clip.jpg", # saving the figure to a jpeg file ) .. _plot_clip_example_figure: .. figure:: figures/exp_slab2_04-18_depth_with_clip.jpg Output of example shown above