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
from numpy import linspace
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
# plotdata.format = 'forestclaw' # 'ascii' or 'binary' to match setrun.py
# 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=True)
#-----------------------------------------
# Figure for surface
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.title = 'Surface'
plotaxes.scaled = True
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.xticks(fontsize=15)
pylab.yticks(fontsize=15)
plotaxes.afteraxes = fixup
# 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 = -0.2
plotitem.pcolor_cmax = 0.2
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0, 0, 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, 0, 0]
plotitem.patchedges_show = 1
plotaxes.xlimits = [-120, -60]
plotaxes.ylimits = [-60, 0]
# 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(-3000, -3000, 1)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 2}
plotitem.amr_contour_show = [0, 0, 0, 0, 0]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface at gauges', 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 = 'auto'
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')
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, axis, xlabel
t = current_data.t
gaugeno = current_data.gaugeno
if gaugeno == 32412:
try:
plot(TG32412[:, 0], TG32412[:, 1], 'r', label='Obs')
legend(['GeoClaw', 'Obs'], loc='lower right')
except:
pass
axis((0, t.max(), -0.3, 0.3))
plot(t, 0 * t, 'k')
n = int(floor(t.max() / 3600.) + 2)
xticks([3600 * i for i in range(n)], ['%i' % i for i in range(n)])
xlabel('time (hours)')
plotaxes.afteraxes = add_zeroline
#-----------------------------------------
# Plots of timing (CPU and wall time):
def make_timing_plots(plotdata):
from clawpack.visclaw import plot_timing_stats
import os, sys
try:
timing_plotdir = plotdata.plotdir + '/_timing_figures'
os.system('mkdir -p %s' % timing_plotdir)
# adjust units for plots based on problem:
units = {
'comptime': 'seconds',
'simtime': 'hours',
'cell': 'millions'
}
plot_timing_stats.make_plots(outdir=plotdata.outdir,
make_pngs=True,
plotdir=timing_plotdir,
units=units)
except:
print('*** Error making timing plots')
otherfigure = plotdata.new_otherfigure(name='timing plots',
fname='_timing_figures/timing.html')
otherfigure.makefig = make_timing_plots
#-----------------------------------------
# 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 = False # 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 = False # make multiple frame png's at once
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.
"""
from clawpack.visclaw import colormaps, geoplot
from numpy import linspace
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
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=True)
def timeformat(t):
from numpy import mod
hours = int(t/3600.)
tmin = mod(t,3600.)
min = int(tmin/60.)
sec = int(mod(tmin,60.))
timestr = '%s:%s:%s' % (hours,str(min).zfill(2),str(sec).zfill(2))
return timestr
def title_hours(current_data):
from pylab import title
t = current_data.t
timestr = timeformat(t)
title('%s after earthquake' % timestr)
#-----------------------------------------
# Figure for surface
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface', figno=0)
plotfigure.kwargs = {'figsize':(8,5)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Surface'
plotaxes.scaled = False # need to set aspect ratio properly for lat/long
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, savefig
gca().set_aspect(1./cos(48*pi/180.))
title_hours(current_data)
ticklabel_format(useOffset=False)
xticks(rotation=20)
plotaxes.afteraxes = aa
#plotaxes.xlimits = [-122.7,-122.16]
#plotaxes.ylimits = [47.2,48.3]
# 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 = cmin
plotitem.pcolor_cmax = cmax
plotitem.add_colorbar = True
plotitem.colorbar_shrink = 0.8
plotitem.amr_celledges_show = [0]
#plotitem.celledges_show = 0
#plotitem.patchedges_show = 0
plotitem.amr_patchedges_show = [0]
# 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 = cmax_land
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0]
plotitem.patchedges_show = 0
#-----------------------------------------
# Figure for zoom on Eagle Harbor
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name="fgmax region", figno=11)
#plotfigure.show = False
plotfigure.kwargs = {'figsize': (9,6)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.scaled = False
plotaxes.xlimits = [-122.55,-122.48]
plotaxes.ylimits = [47.61,47.64]
if bg_image:
plotaxes.beforeaxes = background_image
plotaxes.afteraxes = aa
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = geoplot.surface_or_depth
plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmin = cmin
plotitem.pcolor_cmax = cmax
plotitem.add_colorbar = True
plotitem.amr_data_show = [0,0,1] # only show on finest
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
# 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 = cmax_land
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0]
plotitem.patchedges_show = 0
# 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 = [0]
plotitem.amr_contour_colors = ['yellow'] # color on each level
plotitem.kwargs = {'linestyles':'solid','linewidths':2}
plotitem.amr_contour_show = [0,0,1]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
#-----------------------------------------
# Figure for zoom on Bainbridge / Seattle
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Bainbridge", figno=12)
# not needed for this small domain
plotfigure.show = False
plotfigure.kwargs = {'figsize': (9,6)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.scaled = False
plotaxes.xlimits = [-122.65, -122.3]
plotaxes.ylimits = [47.5, 47.76]
plotaxes.afteraxes = aa
# 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 = cmin
plotitem.pcolor_cmax = cmax
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 0
# 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 = cmax_land
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0]
plotitem.patchedges_show = 0
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='gauge plot', figno=300, \
type='each_gauge')
plotfigure.kwargs = {'figsize': (11,6)}
#plotfigure.clf_each_gauge = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(2,1,1)'
#plotaxes.ylimits = [-1,10]
plotaxes.title = 'Flow depth'
plotaxes.time_scale = 1./60.
plotaxes.time_label = ''
def add_ylabel_depth(current_data):
from pylab import ylabel, grid
ylabel('water depth (m)')
grid(True)
plotaxes.afteraxes = add_ylabel_depth
# Plot depth as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 0
plotitem.plotstyle = 'b-'
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(2,1,2)'
#plotaxes.ylimits = [-1,10]
plotaxes.title = 'Flow speed (m/s)'
plotaxes.time_scale = 1./60.
plotaxes.time_label = 'minutes'
def add_ylabel_speed(current_data):
from pylab import ylabel, tight_layout, grid
ylabel('speed (m/s)')
grid(True)
tight_layout()
plotaxes.afteraxes = add_ylabel_speed
def speed(current_data):
from numpy import sqrt, maximum
q = current_data.q
h = q[0,:]
hu = q[1,:]
hv = q[2,:]
s = sqrt(hu**2 + hv**2) / maximum(h,0.001)
return s
# Plot depth as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = speed
plotitem.plotstyle = 'b-'
#-----------------------------------------
# Figures for fgmax plots
#-----------------------------------------
# Note: need to move fgmax png files into _plots after creating with
# python run_process_fgmax.py
# This just creates the links to these figures...
if 0:
otherfigure = plotdata.new_otherfigure(name='max depth',
fname='depth.png')
otherfigure = plotdata.new_otherfigure(name='max speed',
fname='speed.png')
#-----------------------------------------
# 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?
plotdata.parallel = True # make multiple frame png's at once
return plotdata
def setplot(plotdata=None):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of visclaw.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from clawpack.visclaw import colormaps
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
# Figure for pcolor plot
plotfigure = plotdata.new_plotfigure(name='pcolor', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0, 1]
plotaxes.ylimits = [0, 1]
plotaxes.title = 'Solution'
plotaxes.scaled = True
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = 0
plotitem.pcolor_cmap = colormaps.yellow_red_blue
plotitem.pcolor_cmin = 0.1
plotitem.pcolor_cmax = 1.
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0]
plotitem.amr_patchedges_show = [0]
# Figure for contour plot
plotfigure = plotdata.new_plotfigure(name='contour', figno=1)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0, 1]
plotaxes.ylimits = [0, 1]
plotaxes.title = 'Solution'
plotaxes.scaled = True
plotaxes.afteraxes = addgauges
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = 0
plotitem.contour_nlevels = 20
plotitem.contour_min = 0.01
plotitem.contour_max = 0.99
plotitem.amr_contour_show = [0, 0, 1, 1]
plotitem.amr_contour_colors = ['g', 'g', 'r', 'b'] # color on each level
plotitem.amr_patch_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee', '#ddffff']
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
# Figure for grid cells
plotfigure = plotdata.new_plotfigure(name='cells', figno=2)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0, 1]
plotaxes.ylimits = [0, 1]
plotaxes.title = 'Grid 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', '#ddffff']
plotitem.amr_celledges_show = [1, 0, 0]
plotitem.amr_patchedges_show = [1]
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='q', 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 = 'auto'
plotaxes.title = 'q'
# Plot q as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 0
plotitem.plotstyle = 'b-'
#-----------------------------------------
# Plots of timing (CPU and wall time):
def make_timing_plots(plotdata):
from clawpack.visclaw import plot_timing_stats
import os, sys
try:
timing_plotdir = plotdata.plotdir + '/_timing_figures'
os.system('mkdir -p %s' % timing_plotdir)
# adjust units for plots based on problem:
units = {
'comptime': 'seconds',
'simtime': 'dimensionless',
'cell': 'millions'
}
plot_timing_stats.make_plots(outdir=plotdata.outdir,
make_pngs=True,
plotdir=timing_plotdir,
units=units)
except:
print('*** Error making timing plots')
otherfigure = plotdata.new_otherfigure(name='timing plots',
fname='_timing_figures/timing.html')
otherfigure.makefig = make_timing_plots
# Parameters used only when creating html and/or latex hardcopy
# e.g., via visclaw.frametools.printframes:
plotdata.printfigs = True # print figures
plotdata.print_format = 'png' # file format
plotdata.print_framenos = 'all' # list of frames 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.html_movie = 'JSAnimation' # new style, or "4.x" for old style
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
def setplot(plotdata=None):
""""""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
# clear any old figures,axes,items data
plotdata.clearfigures()
plotdata.format = 'binary'
# Load data from output
clawdata = clawutil.ClawInputData(2)
clawdata.read(os.path.join(plotdata.outdir, 'claw.data'))
physics = geodata.GeoClawData()
physics.read(os.path.join(plotdata.outdir, 'geoclaw.data'))
surge_data = geodata.SurgeData()
surge_data.read(os.path.join(plotdata.outdir, 'surge.data'))
friction_data = geodata.FrictionData()
friction_data.read(os.path.join(plotdata.outdir, 'friction.data'))
# Load storm track
track = surgeplot.track_data(os.path.join(plotdata.outdir, 'fort.track'))
# Set afteraxes function
def surge_afteraxes(cd):
surgeplot.surge_afteraxes(cd,
track,
plot_direction=False,
kwargs={"markersize": 4})
# Color limits
surface_range = 5.0
eta = physics.sea_level
if not isinstance(eta, list):
eta = [eta]
surface_limits = [eta[0] - surface_range, eta[0] + surface_range]
speed_limits = [0.0, 3.0]
wind_limits = [0, 64]
pressure_limits = [935, 1013]
friction_bounds = [0.01, 0.04]
def friction_after_axes(cd):
plt.title(r"Manning's $n$ Coefficient")
# ==========================================================================
# Plot specifications
# ==========================================================================
regions = {
"Entire Region": {
"xlimits": (clawdata.lower[0], clawdata.upper[0]),
"ylimits": (clawdata.lower[1], clawdata.upper[1]),
"figsize": (13, 10)
},
"Caribbean Sub-region": {
"xlimits": (-86, -58.0),
"ylimits": (9, 28),
"figsize": (16, 6)
},
}
for (name, region_dict) in regions.items():
# Surface Figure
plotfigure = plotdata.new_plotfigure(name="Surface - %s" % name)
plotfigure.kwargs = {"figsize": region_dict['figsize']}
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Surface"
plotaxes.xlimits = region_dict["xlimits"]
plotaxes.ylimits = region_dict["ylimits"]
plotaxes.afteraxes = surge_afteraxes
surgeplot.add_surface_elevation(plotaxes, bounds=surface_limits)
surgeplot.add_land(plotaxes)
plotaxes.plotitem_dict['surface'].amr_patchedges_show = [0] * 10
plotaxes.plotitem_dict['land'].amr_patchedges_show = [0] * 10
# Speed Figure
plotfigure = plotdata.new_plotfigure(name="Currents - %s" % name)
plotfigure.kwargs = {"figsize": region_dict['figsize']}
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Currents"
plotaxes.xlimits = region_dict["xlimits"]
plotaxes.ylimits = region_dict["ylimits"]
plotaxes.afteraxes = surge_afteraxes
surgeplot.add_speed(plotaxes, bounds=speed_limits)
surgeplot.add_land(plotaxes)
plotaxes.plotitem_dict['speed'].amr_patchedges_show = [0] * 10
plotaxes.plotitem_dict['land'].amr_patchedges_show = [0] * 10
#
# Friction field
#
plotfigure = plotdata.new_plotfigure(name='Friction')
plotfigure.show = friction_data.variable_friction and False
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Entire Region']['xlimits']
plotaxes.ylimits = regions['Entire Region']['ylimits']
# plotaxes.title = "Manning's N Coefficient"
plotaxes.afteraxes = friction_after_axes
plotaxes.scaled = True
surgeplot.add_friction(plotaxes, bounds=friction_bounds, shrink=0.9)
plotaxes.plotitem_dict['friction'].amr_patchedges_show = [0] * 10
plotaxes.plotitem_dict['friction'].colorbar_label = "$n$"
#
# Hurricane Forcing fields
#
# Pressure field
plotfigure = plotdata.new_plotfigure(name='Pressure')
plotfigure.show = surge_data.pressure_forcing and False
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Entire Region']['xlimits']
plotaxes.ylimits = regions['Entire Region']['ylimits']
plotaxes.title = "Pressure Field"
plotaxes.afteraxes = surge_afteraxes
plotaxes.scaled = True
surgeplot.add_pressure(plotaxes, bounds=pressure_limits)
surgeplot.add_land(plotaxes)
# Wind field
plotfigure = plotdata.new_plotfigure(name='Wind Speed')
plotfigure.show = surge_data.wind_forcing and False
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Entire Region']['xlimits']
plotaxes.ylimits = regions['Entire Region']['ylimits']
plotaxes.title = "Wind Field"
plotaxes.afteraxes = surge_afteraxes
plotaxes.scaled = True
surgeplot.add_wind(plotaxes, bounds=wind_limits)
surgeplot.add_land(plotaxes)
# ========================================================================
# Figures for gauges
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='Gauge Surfaces',
figno=300,
type='each_gauge')
plotfigure.show = True
plotfigure.clf_each_gauge = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [-2, 1]
# plotaxes.xlabel = "Days from landfall"
# plotaxes.ylabel = "Surface (m)"
plotaxes.ylimits = [-1, 5]
plotaxes.title = 'Surface'
def gauge_afteraxes(cd):
axes = plt.gca()
surgeplot.plot_landfall_gauge(cd.gaugesoln, axes)
# Fix up plot - in particular fix time labels
axes.set_title('Station %s' % cd.gaugeno)
axes.set_xlabel('Days relative to landfall')
axes.set_ylabel('Surface (m)')
axes.set_xlim([-2, 1])
axes.set_ylim([-1, 5])
axes.set_xticks([-2, -1, 0, 1])
axes.set_xticklabels([r"$-2$", r"$-1$", r"$0$", r"$1$"])
axes.grid(True)
plotaxes.afteraxes = gauge_afteraxes
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
# plotitem.plot_var = 3
# plotitem.plotstyle = 'b-'
#
# Gauge Location Plot
#
def gauge_location_afteraxes(cd):
plt.subplots_adjust(left=0.12, bottom=0.06, right=0.97, top=0.97)
surge_afteraxes(cd)
gaugetools.plot_gauge_locations(cd.plotdata,
gaugenos='all',
format_string='ko',
add_labels=True)
plotfigure = plotdata.new_plotfigure(name="Gauge Locations")
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Gauge Locations'
plotaxes.scaled = True
plotaxes.xlimits = [clawdata.lower[0], clawdata.upper[0]]
plotaxes.ylimits = [clawdata.lower[1], clawdata.upper[1]]
plotaxes.afteraxes = gauge_location_afteraxes
surgeplot.add_surface_elevation(plotaxes, bounds=surface_limits)
surgeplot.add_land(plotaxes)
plotaxes.plotitem_dict['surface'].amr_patchedges_show = [0] * 10
plotaxes.plotitem_dict['land'].amr_patchedges_show = [0] * 10
#-----------------------------------------
# Figures for fgmax plots
#-----------------------------------------
from clawpack.geoclaw import fgmax_tools
fgmax_plotdir = '_plots'
os.system('mkdir -p %s' % fgmax_plotdir)
# Read fgmax data:
fgno = 1
while (True):
fg = fgmax_tools.FGmaxGrid()
try:
fg.read_fgmax_grids_data(fgno)
fg.read_output(outdir=plotdata.outdir)
fg.B0 = fg.B # no seafloor deformation in this problem
fg.h_onshore = np.ma.masked_where(fg.B0 < 0., fg.h)
plt.figure(figsize=(20, 20))
pc = plt.pcolormesh(fg.X, fg.Y, fg.h_onshore, cmap='hot_r')
cb = plt.colorbar(pc, extend='max', shrink=0.7)
cb.set_label('meters')
plt.contour(fg.X, fg.Y, fg.B, [0], colors='g')
plt.gca().set_aspect(1. / np.cos(48 * np.pi / 180.))
plt.ticklabel_format(useOffset=False)
plt.xticks(rotation=20)
plt.title('Maximum Onshore flow depth\nfgmax grid {fgno}')
img_name = f'fgmax{str(fgno).zfill(4)}_h_onshore.png'
plt.savefig(fname=f'{fgmax_plotdir}/{img_name}')
otherfigure = plotdata.new_otherfigure(
name=f'max depth on fgmax grid {fgno}', fname=img_name)
fgno = fgno + 1
except:
break
# -----------------------------------------
# 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.latex = False # 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 # parallel plotting
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.
"""
from clawpack.visclaw import colormaps, geoplot
from numpy import linspace
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.format = 'binary'
def timeformat(t):
from numpy import mod
hours = int(t / 3600.)
tmin = mod(t, 3600.)
min = int(tmin / 60.)
sec = int(mod(tmin, 60.))
timestr = '%s:%s:%s' % (hours, str(min).zfill(2), str(sec).zfill(2))
return timestr
def title_hours(current_data):
from pylab import title
t = current_data.t
timestr = timeformat(t)
title('%s after earthquake' % timestr)
#-----------------------------------------
# Figure for surface
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Computational domain', figno=0)
plotfigure.kwargs = {'figsize': (8, 7)}
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.title = 'Surface'
plotaxes.scaled = True
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, savefig
gca().set_aspect(1.)
title_hours(current_data)
ticklabel_format(useOffset=False)
xticks(rotation=20)
plotaxes.afteraxes = aa
# 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 = cmin
plotitem.pcolor_cmax = cmax
plotitem.add_colorbar = True
plotitem.colorbar_shrink = 0.7
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.amr_patchedges_show = [0, 0, 0, 0]
plotitem.amr_data_show = [1, 1, 1, 1, 1, 0, 0]
# 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 = cmax_land
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0]
plotitem.amr_patchedges_show = [0, 0, 0, 0]
plotitem.amr_data_show = [1, 1, 1, 1, 1, 0, 0]
# 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(-3000, -3000, 1)
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 coastal area
#-----------------------------------------
x1, x2, y1, y2 = [-0.005, 0.016, -0.01, 0.01]
plotfigure = plotdata.new_plotfigure(name="coastal area", figno=11)
plotfigure.show = True
plotfigure.kwargs = {'figsize': (6, 7)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.scaled = False
plotaxes.xlimits = [x1, x2]
plotaxes.ylimits = [y1, y2]
def aa_withbox(current_data):
from pylab import plot
x1, x2, y1, y2 = (-0.009259, 0.013796, -0.005093, 0.005000)
if current_data.t > 5 * 60.:
plot([x1, x1, x2, x2, x1], [y1, y2, y2, y1, y1], 'w--')
aa(current_data)
plotaxes.afteraxes = aa_withbox
# 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 = cmin
plotitem.pcolor_cmax = cmax
plotitem.add_colorbar = True
plotitem.colorbar_shrink = 0.4
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 0
# 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 = cmax_land
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0]
plotitem.patchedges_show = 0
# 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 = [-2, -1, 0, 1, 2]
plotitem.amr_contour_colors = ['yellow'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 1}
plotitem.amr_contour_show = [0, 0, 1, 0]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
# Plots of timing (CPU and wall time):
def make_timing_plots(plotdata):
import os
from clawpack.visclaw import plot_timing_stats
try:
timing_plotdir = plotdata.plotdir + '/_timing_figures'
os.system('mkdir -p %s' % timing_plotdir)
units = {
'comptime': 'minutes',
'simtime': 'minutes',
'cell': 'millions'
}
plot_timing_stats.make_plots(outdir=plotdata.outdir,
make_pngs=True,
plotdir=timing_plotdir,
units=units)
os.system('cp %s/timing.* %s' % (plotdata.outdir, timing_plotdir))
except:
print('*** Error making timing plots')
otherfigure = plotdata.new_otherfigure(name='timing',
fname='_timing_figures/timing.html')
otherfigure.makefig = make_timing_plots
#-----------------------------------------
# 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?
plotdata.parallel = True # make multiple frame png's at once
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.
"""
from clawpack.visclaw import colormaps, geoplot
from numpy import linspace
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.format = 'binary'
def timeformat(t):
from numpy import mod
hours = int(t / 3600.)
tmin = mod(t, 3600.)
min = int(tmin / 60.)
sec = int(mod(tmin, 60.))
timestr = '%s:%s:%s' % (hours, str(min).zfill(2), str(sec).zfill(2))
return timestr
def title_hours(current_data):
from pylab import title
t = current_data.t
timestr = timeformat(t)
title('%s after earthquake' % timestr)
#-----------------------------------------
# Figure for surface
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Domain and transects', figno=0)
plotfigure.kwargs = {'figsize': (11, 7)}
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
#plotaxes.axescmd = 'axes([.1,.4,.8,.5])'
plotaxes.axescmd = 'axes([.1,.1,.4,.8])'
plotaxes.title = 'Surface'
#plotaxes.xlimits = [-122.4, -122.16]
#plotaxes.ylimits = [47.4, 47.8]
x1_tr1 = -122.29
x2_tr1 = -122.215
y1_tr1 = 47.57
y2_tr1 = 47.705
x1_tr2 = -122.21
x2_tr2 = -122.265
y1_tr2 = 47.4925
y2_tr2 = 47.545
def aa_transects(current_data):
from pylab import ticklabel_format, xticks, plot, text, gca, cos, pi
title_hours(current_data)
ticklabel_format(useOffset=False)
xticks(rotation=20)
plot([x1_tr1, x2_tr1], [y1_tr1, y2_tr1], 'w')
plot([x1_tr2, x2_tr2], [y1_tr2, y2_tr2], 'w')
text(x2_tr1 - 0.01,
y2_tr1 + 0.005,
'Transect 1',
color='w',
fontsize=8)
text(x1_tr2 - 0.01,
y1_tr2 - 0.008,
'Transect 2',
color='w',
fontsize=8)
gca().set_aspect(1. / cos(48 * pi / 180.))
#addgauges(current_data)
plotaxes.afteraxes = aa_transects
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = surface_or_depth_lake
plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmin = cmin
plotitem.pcolor_cmax = cmax
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.amr_patchedges_show = [0, 0, 0, 0]
plotitem.amr_data_show = [1, 1, 1, 1, 1, 0, 0]
# 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 = cmax_land
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0]
plotitem.amr_patchedges_show = [0, 0, 0, 0]
plotitem.amr_data_show = [1, 1, 1, 1, 1, 0, 0]
# 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 = [sea_level]
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 0.5}
plotitem.amr_contour_show = [0, 1, 0, 0] # only on finest level
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
#-----------------------------------------
# Plots along transect:
#-----------------------------------------
eta1 = lambda q: q[3, :, :]
B1 = lambda q: q[3, :, :] - q[0, :, :]
def plot_xsec(current_data):
import matplotlib.pyplot as plt
import numpy
import gridtools
from clawpack.pyclaw import Solution
framesoln = current_data.framesoln
topo_color = [.8, 1, .8]
water_color = [.5, .5, 1]
plt.figure(0)
# Transect 1:
plt.axes([.55, .5, .4, .3])
xout = numpy.linspace(x1_tr1, x2_tr1, 1000)
yout = numpy.linspace(y1_tr1, y2_tr1, 1000)
eta = gridtools.grid_output_2d(framesoln, eta1, xout, yout)
topo = gridtools.grid_output_2d(framesoln, B1, xout, yout)
eta = numpy.where(eta > topo, eta, numpy.nan)
plt.fill_between(yout, eta, topo, color=water_color)
plt.fill_between(yout, topo, -10000, color=topo_color)
plt.plot(yout, eta, 'b')
plt.plot(yout, topo, 'g')
plt.plot(yout, sea_level + 0 * topo, 'k--')
#plt.xlim(47.5,47.8)
plt.ylim(ylim_transects)
plt.ylabel('meters')
plt.grid(True)
timestr = timeformat(framesoln.t)
plt.title('Elevation on Transect 1')
# Transect 2:
plt.axes([.55, .1, .4, .3])
xout = numpy.linspace(x1_tr2, x2_tr2, 1000)
yout = numpy.linspace(y1_tr2, y2_tr2, 1000)
eta = gridtools.grid_output_2d(framesoln, eta1, xout, yout)
topo = gridtools.grid_output_2d(framesoln, B1, xout, yout)
eta = numpy.where(eta > topo, eta, numpy.nan)
topo_color = [.8, 1, .8]
water_color = [.5, .5, 1]
plt.fill_between(yout, eta, topo, color=water_color)
plt.fill_between(yout, topo, -10000, color=topo_color)
plt.plot(yout, eta, 'b')
plt.plot(yout, topo, 'g')
plt.plot(yout, sea_level + 0 * topo, 'k--')
#plt.xlim(47.5,47.8)
plt.ylim(ylim_transects)
plt.ylabel('meters')
plt.grid(True)
timestr = timeformat(framesoln.t)
plt.title('Elevation on Transect 2')
plotdata.afterframe = plot_xsec
#-----------------------------------------
# Figure for zoomed area
#-----------------------------------------
# To use, set the limits as desired and set `plotfigure.show = True`
x1, x2, y1, y2 = [-122.23, -122.2, 47.69, 47.71]
plotfigure = plotdata.new_plotfigure(name="zoomed area", figno=11)
plotfigure.show = False
plotfigure.kwargs = {'figsize': (8, 7)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.scaled = False
plotaxes.xlimits = [x1, x2]
plotaxes.ylimits = [y1, y2]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi
title_hours(current_data)
ticklabel_format(useOffset=False)
xticks(rotation=20)
gca().set_aspect(1. / cos(48 * pi / 180.))
plotaxes.afteraxes = aa
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = surface_or_depth_lake
plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmin = cmin
plotitem.pcolor_cmax = cmax
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 0
# 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 = cmax_land
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0]
plotitem.patchedges_show = 0
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
time_scale = 1. / 3600.
time_label = 'hours'
plotfigure = plotdata.new_plotfigure(name='gauge depth', figno=300, \
type='each_gauge')
#plotfigure.clf_each_gauge = False
def setglimits_depth(current_data):
from pylab import xlim, ylim, title, argmax, show, array, ylabel
gaugeno = current_data.gaugeno
q = current_data.q
depth = q[0, :]
t = current_data.t
g = current_data.plotdata.getgauge(gaugeno)
level = g.level
maxlevel = max(level)
#find first occurrence of the max of levels used by
#this gauge and set the limits based on that time
argmax_level = argmax(level)
xlim(time_scale * array(t[argmax_level], t[-1]))
ylabel('meters')
min_depth = depth[argmax_level:].min()
max_depth = depth[argmax_level:].max()
ylim(min_depth - 0.5, max_depth + 0.5)
title('Gauge %i : Flow Depth (h)\n' % gaugeno + \
'max(h) = %7.3f, max(level) = %i' %(max_depth,maxlevel))
#show()
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.time_scale = time_scale
plotaxes.time_label = time_label
# Plot depth as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 0
plotitem.plotstyle = 'b-'
## Set the limits and the title in the function below
plotaxes.afteraxes = setglimits_depth
plotfigure = plotdata.new_plotfigure(name='gauge surface eta', figno=301, \
type='each_gauge')
#plotfigure.clf_each_gauge = False
def setglimits_eta(current_data):
from pylab import xlim, ylim, title, argmax, show, array, ylabel
gaugeno = current_data.gaugeno
q = current_data.q
eta = q[3, :]
t = current_data.t
g = current_data.plotdata.getgauge(gaugeno)
level = g.level
maxlevel = max(level)
#find first occurrence of the max of levels used by
#this gauge and set the limits based on that time
argmax_level = argmax(level) #first occurrence of it
xlim(time_scale * array(t[argmax_level], t[-1]))
ylabel('meters')
min_eta = eta[argmax_level:].min()
max_eta = eta[argmax_level:].max()
ylim(min_eta - 0.5, max_eta + 0.5)
title('Gauge %i : Surface Elevation (eta)\n' % gaugeno + \
'max(eta) = %7.3f, max(level) = %i' %(max_eta,maxlevel))
#show()
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.time_scale = time_scale
plotaxes.time_label = time_label
# Plot surface (eta) as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
## Set the limits and the title in the function below
plotaxes.afteraxes = setglimits_eta
plotfigure = plotdata.new_plotfigure(name='speed', figno=302, \
type='each_gauge')
#plotfigure.clf_each_gauge = False
def speed(current_data):
from numpy import sqrt, maximum, where
q = current_data.q
h = q[0, :]
hu = q[1, :]
hv = q[2, :]
s = sqrt(hu**2 + hv**2) / maximum(h, 0.001)
s = where(h > 0.001, s, 0.0)
return s
def setglimits_speed(current_data):
from pylab import xlim, ylim, title, argmax, show, array, ylabel
gaugeno = current_data.gaugeno
s = speed(current_data)
t = current_data.t
g = current_data.plotdata.getgauge(gaugeno)
level = g.level
maxlevel = max(level)
#find first occurrence of the max of levels used by
#this gauge and set the limits based on that time
argmax_level = argmax(level) #first occurrence of it
xlim(time_scale * array(t[argmax_level], t[-1]))
ylabel('meters/sec')
min_speed = s[argmax_level:].min()
max_speed = s[argmax_level:].max()
ylim(min_speed - 0.5, max_speed + 0.5)
title('Gauge %i : Speed (s)\n' % gaugeno + \
'max(s) = %7.3f, max(level) = %i' %(max_speed,maxlevel))
#show()
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.time_scale = time_scale
plotaxes.time_label = time_label
# Plot speed (s) as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = speed
plotitem.plotstyle = 'b-'
## Set the limits and the title in the function below
plotaxes.afteraxes = setglimits_speed
#-----------------------------------------
# Figures for fgmax plots
#-----------------------------------------
# Note: need to move fgmax png files into _plots after creating with
# python run_process_fgmax.py
# This just creates the links to these figures...
if 0:
### Putting them in _other_figures with the proper name as a link
### Can run process fgmax either before or after setplot now.
otherfigure = plotdata.new_otherfigure(name='max depth',
fname='_other_figures/%s_%s_h_onshore.png' \
% (params.loc,params.event))
otherfigure = plotdata.new_otherfigure(name='max depth on GE image',
fname='_other_figures/%s_%s_h_onshore_GE.png' \
% (params.loc,params.event))
otherfigure = plotdata.new_otherfigure(name='max speed',
fname='_other_figures/%s_%s_speed.png' \
% (params.loc,params.event))
# Plots of timing (CPU and wall time):
def make_timing_plots(plotdata):
import os
from clawpack.visclaw import plot_timing_stats
try:
timing_plotdir = plotdata.plotdir + '/_timing_figures'
os.system('mkdir -p %s' % timing_plotdir)
units = {
'comptime': 'hours',
'simtime': 'hours',
'cell': 'billions'
}
plot_timing_stats.make_plots(outdir=plotdata.outdir,
make_pngs=True,
plotdir=timing_plotdir,
units=units)
os.system('cp %s/timing.* %s' % (plotdata.outdir, timing_plotdir))
except:
print('*** Error making timing plots')
otherfigure = plotdata.new_otherfigure(name='timing',
fname='_timing_figures/timing.html')
otherfigure.makefig = make_timing_plots
#-----------------------------------------
# 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?
plotdata.parallel = True # make multiple frame png's at once
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.
"""
from clawpack.visclaw import colormaps, geoplot
from numpy import linspace
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.format = 'binary'
def timeformat(t):
from numpy import mod
hours = int(t / 3600.)
tmin = mod(t, 3600.)
min = int(tmin / 60.)
sec = int(mod(tmin, 60.))
timestr = '%s:%s:%s' % (hours, str(min).zfill(2), str(sec).zfill(2))
return timestr
def title_hours(current_data):
from pylab import title
t = current_data.t
timestr = timeformat(t)
title('%s after earthquake' % timestr)
#-----------------------------------------
# Figure for surface
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Computational domain', figno=0)
plotfigure.kwargs = {'figsize': (8, 7)}
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.title = 'Surface'
plotaxes.scaled = True
def fixup(current_data):
import pylab
#addgauges(current_data)
t = current_data.t
t = t / 60. # minutes
pylab.title('Surface at %4.2f minutes' % t, fontsize=10)
#pylab.xticks(fontsize=15)
#pylab.yticks(fontsize=15)
#plotaxes.afteraxes = fixup
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, savefig
gca().set_aspect(1. / cos(48 * pi / 180.))
title_hours(current_data)
ticklabel_format(useOffset=False)
xticks(rotation=20)
def aa_topo(current_data):
from pylab import contour, plot
aa(current_data)
#addgauges(current_data)
#contour(topo.X, topo.Y, topo.Z, [0], colors='k')
def aa_topo_nogauges(current_data):
from pylab import contour, plot
aa(current_data)
#addgauges(current_data)
#contour(topo.X, topo.Y, topo.Z, [0], colors='k')
#plotaxes.afteraxes = aa_topo
plotaxes.afteraxes = aa_topo_nogauges
## Limits below never used for AK, CSZ_L1 or SFL
#plotaxes.xlimits = [-129.16,-122.16]
#plotaxes.ylimits = [46.0,51.0]
# 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 = cmin
plotitem.pcolor_cmax = cmax
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.amr_patchedges_show = [0, 0, 0, 0]
plotitem.amr_data_show = [1, 1, 1, 1, 1, 0, 0]
# 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 = cmax_land
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0]
plotitem.amr_patchedges_show = [0, 0, 0, 0]
plotitem.amr_data_show = [1, 1, 1, 1, 1, 0, 0]
# 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(-3000, -3000, 1)
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 fgmax area
#-----------------------------------------
x1, x2, y1, y2 = [-122.54, -122.4, 47.9, 48.04]
plotfigure = plotdata.new_plotfigure(name="fgmax area", figno=11)
plotfigure.show = True
plotfigure.kwargs = {'figsize': (6, 7)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.scaled = False
plotaxes.xlimits = [x1 - 0.01, x2 + 0.01]
plotaxes.ylimits = [y1 - 0.01, y2 + 0.01]
plotaxes.afteraxes = aa_topo
# 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 = cmin
plotitem.pcolor_cmax = cmax
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 0
# 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 = cmax_land
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0]
plotitem.patchedges_show = 0
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
time_scale = 1. / 3600.
time_label = 'hours'
plotfigure = plotdata.new_plotfigure(name='gauge depth', figno=300, \
type='each_gauge')
#plotfigure.clf_each_gauge = False
def setglimits_depth(current_data):
from pylab import xlim, ylim, title, argmax, show, array, ylabel
gaugeno = current_data.gaugeno
q = current_data.q
depth = q[0, :]
t = current_data.t
g = current_data.plotdata.getgauge(gaugeno)
level = g.level
maxlevel = max(level)
#find first occurrence of the max of levels used by
#this gauge and set the limits based on that time
argmax_level = argmax(level)
xlim(time_scale * array(t[argmax_level], t[-1]))
ylabel('meters')
min_depth = depth[argmax_level:].min()
max_depth = depth[argmax_level:].max()
ylim(min_depth - 0.5, max_depth + 0.5)
title('Gauge %i : Flow Depth (h)\n' % gaugeno + \
'max(h) = %7.3f, max(level) = %i' %(max_depth,maxlevel))
#show()
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.time_scale = time_scale
plotaxes.time_label = time_label
# Plot depth as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 0
plotitem.plotstyle = 'b-'
## Set the limits and the title in the function below
plotaxes.afteraxes = setglimits_depth
plotfigure = plotdata.new_plotfigure(name='gauge surface eta', figno=301, \
type='each_gauge')
#plotfigure.clf_each_gauge = False
def setglimits_eta(current_data):
from pylab import xlim, ylim, title, argmax, show, array, ylabel
gaugeno = current_data.gaugeno
q = current_data.q
eta = q[3, :]
t = current_data.t
g = current_data.plotdata.getgauge(gaugeno)
level = g.level
maxlevel = max(level)
#find first occurrence of the max of levels used by
#this gauge and set the limits based on that time
argmax_level = argmax(level) #first occurrence of it
xlim(time_scale * array(t[argmax_level], t[-1]))
ylabel('meters')
min_eta = eta[argmax_level:].min()
max_eta = eta[argmax_level:].max()
ylim(min_eta - 0.5, max_eta + 0.5)
title('Gauge %i : Surface Elevation (eta)\n' % gaugeno + \
'max(eta) = %7.3f, max(level) = %i' %(max_eta,maxlevel))
#show()
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.time_scale = time_scale
plotaxes.time_label = time_label
# Plot surface (eta) as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
## Set the limits and the title in the function below
plotaxes.afteraxes = setglimits_eta
plotfigure = plotdata.new_plotfigure(name='speed', figno=302, \
type='each_gauge')
#plotfigure.clf_each_gauge = False
def speed(current_data):
from numpy import sqrt, maximum, where
q = current_data.q
h = q[0, :]
hu = q[1, :]
hv = q[2, :]
s = sqrt(hu**2 + hv**2) / maximum(h, 0.001)
s = where(h > 0.001, s, 0.0)
return s
def setglimits_speed(current_data):
from pylab import xlim, ylim, title, argmax, show, array, ylabel
gaugeno = current_data.gaugeno
s = speed(current_data)
t = current_data.t
g = current_data.plotdata.getgauge(gaugeno)
level = g.level
maxlevel = max(level)
#find first occurrence of the max of levels used by
#this gauge and set the limits based on that time
argmax_level = argmax(level) #first occurrence of it
xlim(time_scale * array(t[argmax_level], t[-1]))
ylabel('meters/sec')
min_speed = s[argmax_level:].min()
max_speed = s[argmax_level:].max()
ylim(min_speed - 0.5, max_speed + 0.5)
title('Gauge %i : Speed (s)\n' % gaugeno + \
'max(s) = %7.3f, max(level) = %i' %(max_speed,maxlevel))
#show()
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.time_scale = time_scale
plotaxes.time_label = time_label
# Plot speed (s) as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = speed
plotitem.plotstyle = 'b-'
## Set the limits and the title in the function below
plotaxes.afteraxes = setglimits_speed
#-----------------------------------------
# Figures for fgmax plots
#-----------------------------------------
# Note: You need to move fgmax png files into _plots/_other_figures after
# creating them, e.g., by running the process_fgmax notebook or script.
# The lines below just create links to these figures from _PlotIndex.html
otherfigure = plotdata.new_otherfigure(
name='max depth', fname='_other_figures/h_onshore.png')
otherfigure = plotdata.new_otherfigure(name='max speed',
fname='_other_figures/speed.png')
# add additional lines for any other figures you want added to the index.
# Plots of timing (CPU and wall time):
def make_timing_plots(plotdata):
import os
from clawpack.visclaw import plot_timing_stats
try:
timing_plotdir = plotdata.plotdir + '/_timing_figures'
os.system('mkdir -p %s' % timing_plotdir)
units = {
'comptime': 'hours',
'simtime': 'hours',
'cell': 'billions'
}
plot_timing_stats.make_plots(outdir=plotdata.outdir,
make_pngs=True,
plotdir=timing_plotdir,
units=units)
os.system('cp %s/timing.* %s' % (plotdata.outdir, timing_plotdir))
except:
print('*** Error making timing plots')
# create a link to this webpage from _PlotIndex.html:
otherfigure = plotdata.new_otherfigure(name='timing',
fname='_timing_figures/timing.html')
otherfigure.makefig = make_timing_plots
#-----------------------------------------
# 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?
plotdata.parallel = True # make multiple frame png's at once
return plotdata
