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setplot.py.html |
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Source file: setplot.py
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Directory: /home/rjl/git/rjleveque/clawpack-4.x/apps/tsunami/bowl-radial
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Converted: Tue Jul 26 2011 at 12:58:48
using clawcode2html
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This documentation file will
not reflect any later changes in the source file.
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"""
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.
"""
#--------------------------
def setplot(plotdata):
#--------------------------
"""
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 pyclaw.plotters import colormaps, geoplot
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-2
plotdata.beforeframe = set_drytol
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=True)
#-----------------------------------------
# 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.plot_var = geoplot.surface_or_depth
plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmin = -0.9
plotitem.pcolor_cmax = 0.9
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [1,1,0]
plotitem.amr_gridedges_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_gridlines_show = [1,1,0]
plotaxes.xlimits = [-100,100]
plotaxes.ylimits = [-100,100]
#-----------------------------------------
# Figure for zoom
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Zoom', figno=10)
#plotfigure.show = False
plotfigure.kwargs = {'figsize':[12,7]}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('diag zoom')
plotaxes.axescmd = 'axes([0.0,0.1,0.6,0.6])'
plotaxes.title = 'On diagonal'
plotaxes.scaled = True
plotaxes.xlimits = [55,66]
plotaxes.ylimits = [55,66]
plotaxes.afteraxes = addgauges
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmin = -0.9
plotitem.pcolor_cmax = 0.9
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [1,1,0]
plotitem.amr_gridedges_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_gridlines_show = [1,1,0]
# 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 = arange(-10., 0., 1.)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(0., 11., 1.)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
# Add dashed contour line for shoreline
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'dashed'}
plotitem.amr_contour_show = [0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
#-----------------------------------------
# Figure for zoom near axis
#-----------------------------------------
#plotfigure = plotdata.new_plotfigure(name='Zoom2', figno=11)
# now included in same figure as zoom on diagonal
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('x zoom')
plotaxes.show = True
plotaxes.axescmd = 'axes([0.5,0.1,0.6,0.6])'
plotaxes.title = 'On x-axis'
plotaxes.scaled = True
plotaxes.xlimits = [82,93]
plotaxes.ylimits = [-5,6]
plotaxes.afteraxes = addgauges
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmin = -0.9
plotitem.pcolor_cmax = 0.9
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [1,1,0]
plotitem.amr_gridedges_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_gridlines_show = [1,1,0]
# 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 = arange(-10., 0., 1.)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(0., 11., 1.)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
# Add dashed contour line for shoreline
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'dashed'}
plotitem.amr_contour_show = [0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=300, \
type='each_gauge')
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
plotaxes.ylimits = [-2.0, 2.0]
plotaxes.title = 'Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
# Plot topo as green curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
def gaugetopo(current_data):
q = current_data.q
h = q[:,0]
eta = q[:,3]
topo = eta - h
return topo
plotitem.plot_var = gaugetopo
plotitem.clf_each_gauge = False
plotitem.plotstyle = 'g-'
def add_zeroline(current_data):
from pylab import plot, legend
t = current_data.t
legend(('surface','topography'),loc='lower left')
plot(t, 0*t, 'k')
plotaxes.afteraxes = add_zeroline
#-----------------------------------------
# Figure for grids alone
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='grids', figno=2)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0,1]
plotaxes.ylimits = [0,1]
plotaxes.title = 'grids'
plotaxes.scaled = True
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_grid')
plotitem.amr_grid_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.amr_gridlines_show = [1,1,0]
plotitem.amr_gridedges_show = [1]
#-----------------------------------------
# Scatter plot of surface for radially symmetric
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Scatter', figno=200)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0., 100.]
plotaxes.ylimits = [-.5, 1.]
plotaxes.title = 'Scatter plot of surface'
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.plot_var = geoplot.surface
def q_vs_radius(current_data):
from numpy import sqrt
x = current_data.x
y = current_data.y
r = sqrt(x**2 + y**2)
q = current_data.var
return r,q
plotitem.map_2d_to_1d = q_vs_radius
plotitem.plotstyle = 'o'
plotitem.amr_color=['b','r','g']
plotaxes.afteraxes = "pylab.legend(['Level 1','Level 2'])"
#-----------------------------------------
# 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 = [4,5,104,105] # 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.format = 'ascii' # Format of output
# plotdata.format = 'netcdf'
return plotdata