def plot_fgmax_grid():
fg = fgmax_tools.FGmaxGrid()
fg.read_input_data('fgmax_grid1.txt')
fg.read_output()
#clines_zeta = [0.01] + list(numpy.linspace(0.05,0.3,6)) + [0.5,1.0,10.0]
clines_zeta = [0.001] + list(numpy.linspace(0.05,0.25,10))
colors = geoplot.discrete_cmap_1(clines_zeta)
plt.figure(1)
plt.clf()
zeta = numpy.where(fg.B>0, fg.h, fg.h+fg.B) # surface elevation in ocean
plt.contourf(fg.X,fg.Y,zeta,clines_zeta,colors=colors)
plt.colorbar()
plt.contour(fg.X,fg.Y,fg.B,[0.],colors='k') # coastline
# plot arrival time contours and label:
arrival_t = fg.arrival_time/3600. # arrival time in hours
#clines_t = numpy.linspace(0,8,17) # hours
clines_t = numpy.linspace(0,2,5) # hours
#clines_t_label = clines_t[::2] # which ones to label
clines_t_label = clines_t[::1] # which ones to label
clines_t_colors = ([.5,.5,.5],)
con_t = plt.contour(fg.X,fg.Y,arrival_t, clines_t,colors=clines_t_colors)
plt.clabel(con_t, clines_t_label)
# fix axes:
plt.ticklabel_format(format='plain',useOffset=False)
plt.xticks(rotation=20)
plt.gca().set_aspect(1./numpy.cos(fg.Y.mean()*numpy.pi/180.))
plt.title("Maximum amplitude / arrival times (hrs)")
def plot_fgmax_grid(fgno):
fg = fgmax_tools.FGmaxGrid()
fname = 'fgmax_grid%s.txt' % fgno
fg.read_input_data(fname)
fg.read_output(fgno)
clines_zeta = [0.01] + list(numpy.linspace(.3, 2.1, 7))
colors = geoplot.discrete_cmap_1(clines_zeta)
plt.figure(fgno)
plt.clf()
# set zeta = max depth on shore, max surface elevation offshore:
zeta = numpy.where(fg.B > 0, fg.h, fg.h + fg.B)
plt.contourf(fg.X, fg.Y, zeta, clines_zeta, colors=colors, extend='max')
plt.colorbar(extend='max')
#plt.contour(fg.X,fg.Y,fg.B,[0.],colors='k') # coastline
# plot original coastline extending beyond fgmax region:
theta = numpy.linspace(-numpy.pi / 8., 3 / 8. * numpy.pi, 1000)
plt.plot(90 * numpy.cos(theta), 90 * numpy.sin(theta), 'k')
# fix axes:
plt.ticklabel_format(format='plain', useOffset=False)
plt.xticks(rotation=20)
plt.gca().set_aspect(1. / numpy.cos(fg.Y.mean() * numpy.pi / 180.))
plt.title("Zeta = max depth or surface elevation")
plt.axis('scaled')
if fgno == 1:
plt.axis([85, 95, -5, 5])
else:
plt.axis([59, 69, 59, 69])
def plot_fgmax_grid():
fg = fgmax_tools.FGmaxGrid()
fg.read_input_data('fgmax_grid.txt')
fg.read_output()
clines_zeta = [0.01] + list(numpy.linspace(0.05,0.3,6)) + [0.5,1.0,10.0]
colors = geoplot.discrete_cmap_1(clines_zeta)
plt.figure(1)
plt.clf()
zeta = numpy.where(fg.B>0, fg.h, fg.h+fg.B) # surface elevation in ocean
plt.contourf(fg.X,fg.Y,zeta,clines_zeta,colors=colors)
plt.colorbar()
plt.contour(fg.X,fg.Y,fg.B,[0.],colors='k') # coastline
# plot arrival time contours and label:
arrival_t = fg.arrival_time/3600. # arrival time in hours
clines_t = numpy.linspace(0,8,17) # hours
clines_t_label = clines_t[::2] # which ones to label
clines_t_colors = ([.5,.5,.5],)
con_t = plt.contour(fg.X,fg.Y,arrival_t, clines_t,colors=clines_t_colors)
plt.clabel(con_t, clines_t_label)
# fix axes:
plt.ticklabel_format(format='plain',useOffset=False)
plt.xticks(rotation=20)
plt.gca().set_aspect(1./numpy.cos(fg.Y.mean()*numpy.pi/180.))
plt.title("Maximum amplitude / arrival times")
def plot_fgmax_grid(fname, fgno, xl, xu, yl, yu):
"""Plots the fg_max data using clawpack and creates a figure in the _plots directory"""
xlower = xl
xupper = xu
ylower = yl
yupper = yu
fg = fgmax_tools.FGmaxGrid()
fg.read_fgmax_grids_data(3)
fg.read_output(fgno=fgno)
clines_zeta = [0.01] + list(np.linspace(0.25, 6, 24))
colors = geoplot.discrete_cmap_1(clines_zeta)
zeta = np.where(fg.B > 0, fg.h, fg.h + fg.B) # surface elevation in ocean
fig, ax = gearth_fig(llcrnrlon=xlower,
llcrnrlat=ylower,
urcrnrlon=xupper,
urcrnrlat=yupper,
pixels=1024)
ax.contourf(fg.X, fg.Y, zeta, clines_zeta, colors=colors, alpha=.90)
ax.contour(fg.X, fg.Y, fg.B, [0.], colors='k') # coastline
# fix axes:
ax.ticklabel_format(style='plain', useOffset=False)
plt.xticks(rotation=20)
plt.gca().set_aspect(1. / np.cos(fg.Y.mean() * np.pi / 180.))
plt.title("Maximum amplitude")
cs = ax.contourf(fg.X, fg.Y, zeta, clines_zeta, colors=colors)
return (cs)
def plot_fgmax_grid(fgno):
fg = fgmax_tools.FGmaxGrid()
fname = 'fgmax_grid%s.txt' % fgno
fg.read_input_data(fname)
fg.read_output(fgno)
clines_zeta = [0.01] + list(numpy.linspace(.3, 2.1, 7))
colors = geoplot.discrete_cmap_1(clines_zeta)
plt.figure(fgno)
plt.clf()
# set zeta = max depth on shore, max surface elevation offshore:
zeta = numpy.where(fg.B>0, fg.h, fg.h+fg.B)
plt.contourf(fg.X,fg.Y,zeta,clines_zeta,colors=colors,extend='max')
plt.colorbar(extend='max')
#plt.contour(fg.X,fg.Y,fg.B,[0.],colors='k') # coastline
# plot original coastline extending beyond fgmax region:
theta = numpy.linspace(-numpy.pi/8., 3/8. *numpy.pi, 1000)
plt.plot(90*numpy.cos(theta), 90*numpy.sin(theta), 'k')
# fix axes:
plt.ticklabel_format(format='plain',useOffset=False)
plt.xticks(rotation=20)
plt.gca().set_aspect(1./numpy.cos(fg.Y.mean()*numpy.pi/180.))
plt.title("Zeta = max depth or surface elevation")
plt.axis('scaled')
if fgno==1:
plt.axis([85,95,-5,5])
else:
plt.axis([59,69,59,69])
def plot_fgmax_grid():
fg = fgmax_tools.FGmaxGrid()
fg.read_input_data('fgmax_grid1.txt')
fg.read_output()
#clines_zeta = [0.01] + list(numpy.linspace(0.05,0.3,6)) + [0.5,1.0,10.0]
clines_zeta = [0.001] + list(numpy.linspace(0.05, 0.25, 10))
colors = geoplot.discrete_cmap_1(clines_zeta)
plt.figure(1)
plt.clf()
zeta = numpy.where(fg.B > 0, fg.h,
fg.h + fg.B) # surface elevation in ocean
plt.contourf(fg.X, fg.Y, zeta, clines_zeta, colors=colors)
plt.colorbar()
plt.contour(fg.X, fg.Y, fg.B, [0.], colors='k') # coastline
# draw better land
import clawpack.geoclaw.topotools as tt
topo = tt.Topography(path='../bathy/atlantic_2min.tt3')
shore = topo.make_shoreline_xy()
plt.plot(shore[:, 0], shore[:, 1], 'k', linewidth=10)
# plot arrival time contours and label:
arrival_t = fg.arrival_time / 3600. # arrival time in hours
#clines_t = numpy.linspace(0,8,17) # hours
clines_t = numpy.linspace(0, 2, 5) # hours
#clines_t_label = clines_t[::2] # which ones to label
clines_t_label = clines_t[::1] # which ones to label
clines_t_colors = ([.5, .5, .5], )
con_t = plt.contour(fg.X,
fg.Y,
arrival_t,
clines_t,
colors=clines_t_colors)
plt.clabel(con_t, clines_t_label)
# fix axes:
plt.ticklabel_format(format='plain', useOffset=False)
plt.xticks(rotation=20)
plt.gca().set_aspect(1. / numpy.cos(fg.Y.mean() * numpy.pi / 180.))
plt.title("Maximum amplitude / arrival times (hrs)")
def plot_fgmax_grid():
fg = fgmax_tools.FGmaxGrid()
fg.read_input_data('fgmax_grid1.txt')
fg.read_output()
#clines_zeta = [0.01] + list(numpy.linspace(0.05,0.3,6)) + [0.5,1.0,10.0]
clines_zeta = [0.001] + list(numpy.linspace(0.05,0.25,10))
colors = geoplot.discrete_cmap_1(clines_zeta)
plt.figure(1)
plt.clf()
zeta = numpy.where(fg.B>0, fg.h, fg.h+fg.B) # surface elevation in ocean
plt.contourf(fg.X,fg.Y,zeta,clines_zeta,colors=colors)
plt.colorbar()
plt.contour(fg.X,fg.Y,fg.B,[0.],colors='k') # coastline
# draw better land
import clawpack.geoclaw.topotools as tt
topo = tt.Topography(path='../bathy/atlantic_2min.tt3')
shore = topo.make_shoreline_xy()
plt.plot(shore[:,0], shore[:,1], 'k', linewidth=10)
# plot arrival time contours and label:
arrival_t = fg.arrival_time/3600. # arrival time in hours
#clines_t = numpy.linspace(0,8,17) # hours
clines_t = numpy.linspace(0,2,5) # hours
#clines_t_label = clines_t[::2] # which ones to label
clines_t_label = clines_t[::1] # which ones to label
clines_t_colors = ([.5,.5,.5],)
con_t = plt.contour(fg.X,fg.Y,arrival_t, clines_t,colors=clines_t_colors)
plt.clabel(con_t, clines_t_label)
# fix axes:
plt.ticklabel_format(format='plain',useOffset=False)
plt.xticks(rotation=20)
plt.gca().set_aspect(1./numpy.cos(fg.Y.mean()*numpy.pi/180.))
plt.title("Maximum amplitude / arrival times (hrs)")
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 clawpack.visclaw import colormaps, geoplot
from numpy import linspace
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.format = 'binary'
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from clawpack.visclaw import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=False)
def fixup(current_data):
import pylab
#addgauges(current_data)
t = current_data.t
t = t / 3600. # hours
pylab.title('Surface at %4.2f hours' % t, fontsize=20)
pylab.ticklabel_format(format='plain',useOffset=False)
mean_lat = 19.7
pylab.gca().set_aspect(1.0 / pylab.cos(pylab.pi / 180.0 * mean_lat))
#pylab.xticks(fontsize=15)
#pylab.yticks(fontsize=15)
#-----------------------------------------
# Figure for imshow plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Pacific', figno=1)
#plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('imshow')
plotaxes.title = 'Surface'
#plotaxes.scaled = True
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
# plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = -0.2
plotitem.imshow_cmax = 0.2
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
plotaxes.xlimits = [135,210]
plotaxes.ylimits = [9,53]
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = linspace(-2000,0,5)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles':'solid','linewidths':2}
plotitem.amr_contour_show = [1,0,0]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
#-----------------------------------------
# Figure for zoom plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Hawaii', figno=20)
#plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('imshow')
plotaxes.title = 'Surface'
#plotaxes.scaled = True
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
# plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = -0.2
plotitem.imshow_cmax = 0.2
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
plotaxes.xlimits = [200., 208.]
plotaxes.ylimits = [17, 25]
#-----------------------------------------
# Figure for zoom plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='zoom', figno=2)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('imshow')
plotaxes.title = 'Surface'
#plotaxes.scaled = True
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
# plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = -0.2
plotitem.imshow_cmax = 0.2
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
plotaxes.xlimits = [204.8, 205.]
plotaxes.ylimits = [19.7, 19.9]
#-----------------------------------------
# Figure for zoom plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Hilo', figno=3)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('imshow')
plotaxes.title = 'Surface'
#plotaxes.scaled = True
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.show = False
# plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = -0.5
plotitem.imshow_cmax = 0.5
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
plotaxes.xlimits = [204.9, 204.96]
plotaxes.ylimits = [19.72, 19.76]
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = linspace(-2000,0,5)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles':'solid','linewidths':2}
plotitem.amr_contour_show = [1,0,0]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
#-----------------------------------------
# Figure for speed
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='speed1', figno=4)
plotfigure.show = False
def speed(current_data):
from numpy import ma, where, sqrt
drytol = 1e-3
q = current_data.q
h = q[0,:,:]
hu = q[1,:,:]
hv = q[2,:,:]
speed = where(h > drytol, sqrt(hu**2 + hv**2)/h**2, 0.)
speed = ma.masked_where(h<=drytol, speed)
return speed
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Speed'
#plotaxes.scaled = True
def fixup(current_data):
import pylab
#addgauges(current_data)
t = current_data.t
t = t / 3600. # hours
pylab.title('Speed at %4.2f hours' % t, fontsize=20)
pylab.ticklabel_format(format='plain',useOffset=False)
mean_lat = 19.7
pylab.gca().set_aspect(1.0 / pylab.cos(pylab.pi / 180.0 * mean_lat))
plotaxes.afteraxes = fixup
# Water (contourf not working)
plotitem = plotaxes.new_plotitem(plot_type='2d_contourf')
plotitem.show = False
plotitem.plot_var = speed
clines = [0, 0.01, 0.02, 0.04, 0.06, 0.08, 0.1, 0.2]
plotitem.contour_levels = clines
from clawpack.geoclaw.geoplot import discrete_cmap_1
plotitem.fill_colors = discrete_cmap_1(clines)
plotitem.kwargs = {'extend':'max'}
plotitem.add_colorbar = True
plotitem.amr_celledges_show = 0
plotitem.patchedges_show = 0
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = speed
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 0.3
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.show = False
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
plotaxes.xlimits = [204.9, 204.96]
plotaxes.ylimits = [19.72, 19.76]
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = linspace(-2000,0,5)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles':'solid','linewidths':2}
plotitem.amr_contour_show = [1,0,0]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
#-----------------------------------------
# Figure for velocity plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Speed', figno=10)
#plotfigure.show = False
# Set up for axes for velocity
plotaxes = plotfigure.new_plotaxes()
#plotaxes.axescmd = 'subplot(212)'
plotaxes.title = 'Speed'
plotaxes.scaled = True
def fixup(current_data):
import pylab
addgauges(current_data)
t = current_data.t
t = t / 3600. # hours
pylab.title('Speed at %4.2f hours' % t, fontsize=20)
pylab.ticklabel_format(format='plain',useOffset=False)
mean_lat = 19.7
pylab.gca().set_aspect(1.0 / pylab.cos(pylab.pi / 180.0 * mean_lat))
pylab.xticks(rotation=20)
plotaxes.afteraxes = fixup
plotaxes.xlimits = [204.9, 204.96]
plotaxes.ylimits = [19.72, 19.76]
def speed(current_data):
from pylab import where,sqrt
q = current_data.q
h = q[0,:,:]
dry_tol = 0.001
u = where(h>dry_tol, q[1,:,:]/h, 0.)
v = where(h>dry_tol, q[2,:,:]/h, 0.)
s = sqrt(u**2 + v**2)
return s
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = speed
#plotitem.imshow_cmap = colormaps.white_red
#plotitem.imshow_cmap = colormaps.yellow_red_blue
plotitem.imshow_cmap = \
colormaps.make_colormap({0:[1,1,1],0.5:[0.1,0.1,1],1:[1,0.1,0.1]})
plotitem.imshow_cmin = 0.
plotitem.imshow_cmax = 1.0
plotitem.add_colorbar = True
plotitem.colorbar_shrink = 0.6
plotitem.amr_celledges_show = [0]
plotitem.amr_patchedges_show = [0]
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface', figno=300, \
type='each_gauge')
plotfigure.clf_each_gauge = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
#plotaxes.axescmd = 'subplot(2,1,1)'
plotaxes.title = 'Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
plotitem.kwargs = {'linewidth':2}
# Plot topo as green curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.show = False
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, xticks, floor, xlim,ylim
t = current_data.t
#legend(('surface','topography'),loc='lower left')
plot(t, 0*t, 'k')
n = int(floor(t.max()/1800.)) + 2
xticks([1800*i for i in range(n)],[str(0.5*i) for i in range(n)])
xlim(25000,t.max())
#ylim(-0.5,0.5)
print "+++ gaugeno = ",current_data.gaugeno
#plotaxes.ylimits = [-0.5, 0.5]
plotaxes.afteraxes = add_zeroline
plotfigure = plotdata.new_plotfigure(name='Velocities', figno=301, \
type='each_gauge')
plotfigure.clf_each_gauge = True
plotaxes = plotfigure.new_plotaxes()
#plotaxes.axescmd = 'subplot(2,1,2)'
plotaxes.title = 'Velocities'
#plotaxes.afteraxes = add_zeroline
# Plot velocity as red curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.show = False
def speed(current_data):
from numpy import where, sqrt
h = current_data.q[0,:]
h = where(h>0.01, h, 1.e6)
u = 100. * current_data.q[1,:] / h
v = 100. * current_data.q[2,:] / h
s = sqrt(u**2 + v**2)
return s
plotitem.plot_var = speed
plotitem.plotstyle = 'k-'
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
def uvel(current_data):
from numpy import where, sqrt
h = current_data.q[0,:]
h = where(h>0.01, h, 1.e6)
u = 100. * current_data.q[1,:] / h
return u
plotitem.plot_var = uvel
plotitem.plotstyle = 'r-'
plotitem.kwargs = {'linewidth':2}
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
def vvel(current_data):
from numpy import where, sqrt
h = current_data.q[0,:]
h = where(h>0.01, h, 1.e6)
v = 100. * current_data.q[2,:] / h
return v
plotitem.plot_var = vvel
plotitem.plotstyle = 'g-'
plotitem.kwargs = {'linewidth':2}
def add_legend(current_data):
from pylab import legend
legend(['u','v'],'upper left')
#legend(['Speed','u','v'],'upper left')
add_zeroline(current_data)
plotaxes.ylimits = [-50,50]
plotaxes.afteraxes = add_legend
#-----------------------------------------
# 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 = '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?
return plotdata
