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.
"""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
from clawpack.visclaw import colormaps, geoplot
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.format = 'ascii' # Format of output
print('Reading all gauges...')
gauge_solutions = particle_tools.read_gauges(gaugenos='all',
outdir=plotdata.outdir)
gaugenos_lagrangian = [k for k in gauge_solutions.keys() \
if gauge_solutions[k].gtype=='lagrangian']
gaugenos_stationary = [k for k in gauge_solutions.keys() \
if gauge_solutions[k].gtype=='stationary']
print('+++ gaugenos_lagrangian: ', gaugenos_lagrangian)
def add_particles(current_data):
t = current_data.t
# plot recent path:
t_path_length = 10. # length of path trailing particle
kwargs_plot_path = {'linewidth': 1, 'color': 'k'}
particle_tools.plot_paths(gauge_solutions,
t1=t - t_path_length,
t2=t,
gaugenos=gaugenos_lagrangian,
kwargs_plot=kwargs_plot_path)
# plot current location:
kwargs_plot_point = {'marker': 'o', 'markersize': 3, 'color': 'k'}
particle_tools.plot_particles(gauge_solutions,
t,
gaugenos=gaugenos_lagrangian,
kwargs_plot=kwargs_plot_point)
# plot any stationary gauges:
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos=gaugenos_stationary, format_string='kx', add_labels=False)
kwargs = {'loc': 'upper left'}
legend_tools.add_legend(['Lagrangian particle', 'Stationary gauge'],
linestyles=['', ''],
markers=['o', 'x'],
loc='lower right',
framealpha=0.5,
fontsize=10)
def speed(current_data):
from pylab import sqrt, where, zeros
from numpy.ma import masked_where, allequal
q = current_data.q
h = q[0, :, :]
hs = sqrt(q[1, :, :]**2 + q[2, :, :]**2)
s = where(h > 1e-3, hs / h, 0.)
s = masked_where(h < 1e-3, s)
s = s * 1.94384 # convert to knots
return s
speed_cmap = colormaps.make_colormap({
0: [0, 1, 1],
0.5: [1, 1, 0],
1: [1, 0, 0]
})
#-----------------------------------------
# Figure for pcolor plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='pcolor', figno=0)
plotfigure.kwargs = {'figsize': (9, 4)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.title = 'Speed'
plotaxes.scaled = True
plotaxes.xlimits = [0, 80]
plotaxes.ylimits = [0, 50]
plotaxes.afteraxes = add_particles
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
#plotitem.plot_var = geoplot.surface_or_depth
plotitem.plot_var = speed
#plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmap = speed_cmap
plotitem.pcolor_cmin = 0.
plotitem.pcolor_cmax = 20
plotitem.add_colorbar = True
plotitem.colorbar_label = 'knots'
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.amr_patchedges_show = [1]
plotitem.amr_patchedges_color = ['m', 'g', 'w']
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.show = False
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]
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(-75, 75, 10)
#plotitem.contour_nlevels = 10
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [1, 1, 1] # show contours only on finest level
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=300, \
type='each_gauge')
plotfigure.clf_each_gauge = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
plotaxes.ylimits = [-100, 100]
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.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
#-----------------------------------------
# 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 = range(40)
plotdata.print_gaugenos = 'all' # 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
plotdata.html_movie_width = 700 # width used in JSAnimation
return plotdata
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.
"""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
from clawpack.visclaw import colormaps, geoplot
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.format = 'ascii' # Format of output
# plotdata.format = 'netcdf'
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
#-----------------------------------------
# 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_celledges_show = [1, 1, 0]
plotitem.amr_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 = [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]
def addgauges(current_data):
from clawpack.visclaw import gaugetools
gaugenos = range(101, 110) # on diagonal
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos=gaugenos, format_string='ko', add_labels=True)
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_celledges_show = [1, 1, 0]
plotitem.amr_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 = [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.celledges_show = 0
plotitem.patchedges_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.celledges_show = 0
plotitem.patchedges_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.celledges_show = 0
plotitem.patchedges_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]
def addgauges(current_data):
from clawpack.visclaw import gaugetools
gaugenos = range(1, 10) # on x-axis
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos=gaugenos, format_string='ko', add_labels=True)
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_celledges_show = [1, 1, 0]
plotitem.amr_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 = [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.celledges_show = 0
plotitem.patchedges_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.celledges_show = 0
plotitem.patchedges_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.celledges_show = 0
plotitem.patchedges_show = 0
plotitem.show = True
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=300, \
type='each_gauge')
plotfigure.clf_each_gauge = True
# 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.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 patches alone
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='patches', 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 = 'patches'
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]
#-----------------------------------------
# Scatter plot of surface for radially symmetric
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Scatter', figno=200)
plotfigure.show = False
# Note: will not look very good unless more of domain is refined
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0., 100.]
plotaxes.ylimits = [-1.5, 2.]
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 = "import pylab; 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.parallel = True # make multiple frame png's at once
plotdata.html_movie_width = 800 # width for js movie
return plotdata
