|
setplot.py.html |
 |
|
Source file: setplot.py
|
|
Directory: /Users/rjl/git/clawpack/geoclaw/examples/tsunami/bowl-slosh
|
|
Converted: Wed Dec 28 2016 at 23:13:25
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, hold, cos,sin,where,legend,nan
t = current_data.t
hold(True)
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()
hold(False)
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 find,ravel
x = current_data.x
y = current_data.y
dy = current_data.dy
q = current_data.q
ij = find((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