setplot.py.html | |
Source file: setplot.py | |
Directory: /Users/rjl/clawpack_src/clawpack_master/geoclaw/examples/tsunami/bowl-slosh | |
Converted: Fri Aug 23 2024 at 11:39:34 using clawcode2html | |
This documentation file will not reflect any later changes in the source file. |
""" Set up the plot figures, axes, and items to be done for each frame. This module is imported by the plotting routines and then the function setplot is called to set the plot parameters. """ from __future__ import absolute_import import numpy a = 1. sigma = 0.5 h0 = 0.1 grav = 9.81 omega = numpy.sqrt(2.*grav*h0) / a #-------------------------- def setplot(plotdata=None): #-------------------------- """ Specify what is to be plotted at each frame. Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData. Output: a modified version of plotdata. """ from clawpack.visclaw import colormaps, geoplot if plotdata is None: from clawpack.visclaw.data import ClawPlotData plotdata = ClawPlotData() plotdata.clearfigures() # clear any old figures,axes,items data def set_drytol(current_data): # The drytol parameter is used in masking land and water and # affects what color map is used for cells with small water depth h. # The cell will be plotted as dry if h < drytol. # The best value to use often depends on the application and can # be set here (measured in meters): current_data.user["drytol"] = 1.e-3 plotdata.beforeframe = set_drytol #----------------------------------------- # Figure for pcolor plot #----------------------------------------- plotfigure = plotdata.new_plotfigure(name='pcolor', figno=0) # Set up for axes in this figure: plotaxes = plotfigure.new_plotaxes('pcolor') plotaxes.title = 'Surface' plotaxes.scaled = True # Water plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor') plotitem.plot_var = geoplot.surface plotitem.pcolor_cmap = geoplot.tsunami_colormap plotitem.pcolor_cmin = -0.1 plotitem.pcolor_cmax = 0.1 plotitem.add_colorbar = True plotitem.amr_celledges_show = [0,0,0] plotitem.patchedges_show = 1 # Land plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor') plotitem.plot_var = geoplot.land plotitem.pcolor_cmap = geoplot.land_colors plotitem.pcolor_cmin = 0.0 plotitem.pcolor_cmax = 100.0 plotitem.add_colorbar = False plotitem.amr_celledges_show = [0,0,0] plotitem.patchedges_show = 1 plotaxes.xlimits = [-2,2] plotaxes.ylimits = [-2,2] # Add contour lines of bathymetry: plotitem = plotaxes.new_plotitem(plot_type='2d_contour') plotitem.plot_var = geoplot.topo from numpy import arange, linspace plotitem.contour_levels = linspace(-.1, 0.5, 20) plotitem.amr_contour_colors = ['k'] # color on each level plotitem.kwargs = {'linestyles':'solid'} plotitem.amr_contour_show = [1] plotitem.celledges_show = 0 plotitem.patchedges_show = 0 plotitem.show = True #----------------------------------------- # Figure for cross section #----------------------------------------- plotfigure = plotdata.new_plotfigure(name='cross-section', figno=1) # Set up for axes in this figure: plotaxes = plotfigure.new_plotaxes() plotaxes.xlimits = [-2,2] plotaxes.ylimits = [-0.15,0.3] plotaxes.title = 'Cross section at y=0' def plot_topo_xsec(current_data): from pylab import plot, cos,sin,where,legend,nan t = current_data.t x = linspace(-2,2,201) y = 0. B = h0*(x**2 + y**2)/a**2 - h0 eta1 = sigma*h0/a**2 * (2.*x*cos(omega*t) + 2.*y*sin(omega*t) -sigma) etatrue = where(eta1>B, eta1, nan) plot(x, etatrue, 'r', label="true solution", linewidth=2) plot(x, B, 'g', label="bathymetry") ## plot([0],[-1],'kx',label="Level 1") # shouldn't show up in plots, ## plot([0],[-1],'bo',label="Level 2") # but will produced desired legend plot([0],[-1],'bo',label="Computed") ## need to fix plotstyle legend() plotaxes.afteraxes = plot_topo_xsec plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data') def xsec(current_data): # Return x value and surface eta at this point, along y=0 from pylab import where,ravel x = current_data.x y = ravel(current_data.y) dy = current_data.dy q = current_data.q ij = where((y <= dy/2.) & (y > -dy/2.)) x_slice = ravel(x)[ij] eta_slice = ravel(q[3,:,:])[ij] return x_slice, eta_slice plotitem.map_2d_to_1d = xsec plotitem.plotstyle = 'kx' ## need to be able to set amr_plotstyle plotitem.kwargs = {'markersize':3} plotitem.amr_show = [1] # plot on all levels #----------------------------------------- # Figure for grids alone #----------------------------------------- plotfigure = plotdata.new_plotfigure(name='grids', figno=2) plotfigure.show = True # Set up for axes in this figure: plotaxes = plotfigure.new_plotaxes() plotaxes.xlimits = [-2,2] plotaxes.ylimits = [-2,2] plotaxes.title = 'grids' plotaxes.scaled = True # Set up for item on these axes: plotitem = plotaxes.new_plotitem(plot_type='2d_patch') plotitem.amr_patch_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee'] plotitem.amr_celledges_show = [1,1,0] plotitem.amr_patchedges_show = [1] #----------------------------------------- # Parameters used only when creating html and/or latex hardcopy # e.g., via pyclaw.plotters.frametools.printframes: plotdata.printfigs = True # print figures plotdata.print_format = 'png' # file format plotdata.print_framenos = 'all' # list of frames to print plotdata.print_gaugenos = [] # list of gauges to print plotdata.print_fignos = 'all' # list of figures to print plotdata.html = True # create html files of plots? plotdata.html_homelink = '../README.html' # pointer for top of index plotdata.latex = True # create latex file of plots? plotdata.latex_figsperline = 2 # layout of plots plotdata.latex_framesperline = 1 # layout of plots plotdata.latex_makepdf = False # also run pdflatex? plotdata.parallel = True # make multiple frame png's at once return plotdata