def setplot(plotdata=None):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of clawpack.visclaw.data.ClawPlotData.
Output: a modified version of plotdata.
"""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
print("**** Python plotting tools not yet implemented in 3d")
print("**** No frame plots will be generated.")
#-----------------------------------------
# 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-'
# Parameters used only when creating html and/or latex hardcopy
# e.g., via clawpack.visclaw.frametools.printframes:
plotdata.printfigs = False # print figures
plotdata.print_format = 'png' # file format
plotdata.print_framenos = [] # list of frames to print
plotdata.print_fignos = [] # list of figures to print
plotdata.html = False # 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 = 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 # 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 clawpack.visclaw.data.ClawPlotData.
Output: a modified version of plotdata.
"""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
print("**** Python plotting tools not yet implemented in 3d")
print("**** No plots will be generated.")
# Parameters used only when creating html and/or latex hardcopy
# e.g., via clawpack.visclaw.frametools.printframes:
plotdata.printfigs = False # print figures
plotdata.print_format = 'png' # file format
plotdata.print_framenos = [] # list of frames to print
plotdata.print_fignos = [] # list of figures to print
plotdata.html = False # 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 = 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 # 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_limits = [physics.sea_level - 5.0, physics.sea_level + 5.0]
surface_ticks = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]
surface_labels = [str(value) for value in surface_ticks]
speed_limits = [0.0, 3.0]
speed_ticks = [0, 1, 2, 3]
speed_labels = [str(value) for value in speed_ticks]
wind_limits = [0, 66]
pressure_limits = [909, 1013]
friction_bounds = [0.01, 0.04]
def add_custom_colorbar_ticks_to_axes(axes,
item_name,
ticks,
tick_labels=None):
"""Adjust colorbar ticks and labels"""
axes.plotitem_dict[item_name].colorbar_ticks = ticks
axes.plotitem_dict[item_name].colorbar_tick_labels = tick_labels
def gulf_after_axes(cd):
# plt.subplots_adjust(left=0.08, bottom=0.04, right=0.97, top=0.96)
surge_afteraxes(cd)
def latex_after_axes(cd):
# plt.subplot_adjust()
surge_afteraxes(cd)
def friction_after_axes(cd):
# plt.subplots_adjust(left=0.08, bottom=0.04, right=0.97, top=0.96)
plt.title(r"Manning's $n$ Coefficient")
# surge_afteraxes(cd)
# ==========================================================================
# Plot specifications
# ==========================================================================
regions = {
"Coast": {
"xlimits": (clawdata.lower[0], clawdata.upper[0]),
"ylimits": (clawdata.lower[1], clawdata.upper[1]),
"figsize": (8, 7.5)
},
"Zhapo Station": {
"xlimits": (111.71666667, 111.91666667),
"ylimits": (21.48333333, 21.68333333),
"figsize": (6, 6)
},
"Landfall": {
"xlimits": (112.26, 112.86),
"ylimits": (21.3, 21.7),
"figsize": (6, 4)
},
"Quarry Bay": {
"xlimits": (114.11333333, 114.31333333),
"ylimits": (22.19111111, 22.39111111),
"figsize": (6, 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
add_custom_colorbar_ticks_to_axes(plotaxes, 'surface', surface_ticks,
surface_labels)
# 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
add_custom_colorbar_ticks_to_axes(plotaxes, 'speed', speed_ticks,
speed_labels)
# Hurricane Forcing fields
#
# Pressure field
plotfigure = plotdata.new_plotfigure(name='Pressure')
plotfigure.show = surge_data.pressure_forcing and True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Coast']['xlimits']
plotaxes.ylimits = regions['Coast']['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 True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Coast']['xlimits']
plotaxes.ylimits = regions['Coast']['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 = [-2.25, 0.75]
#plotaxes.xlabel = "Days from landfall"
#plotaxes.ylabel = "Surface (m)"
plotaxes.ylimits = [-1, 4]
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([-2.25, 0.75])
axes.set_ylim([-1, 4])
axes.set_xticks([-2.25, -1.25, -0.25, 0.75])
axes.set_xticklabels([r"$-2.25$", r"$-1.25$", r"$-0.25$", r"$0.75$"])
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)
plt.subplots_adjust(left=0.12, bottom=0.06, right=0.97, top=0.92)
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 = [111.0, 115.0]
plotaxes.ylimits = [21.0, 22.5]
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
# -----------------------------------------
# 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 = [1, 2] # list of gauges to print
plotdata.print_fignos = 'all' # list of figures to print
plotdata.html = True # create html files of plots?
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 # 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
def speed(current_data):
from numpy import ma, where, sqrt, log10
drytol = 1e-3
q = current_data.q
h = q[0, :, :]
hu = q[1, :, :]
hv = q[2, :, :]
u = where(h > 0.0, hu / h, 0.)
v = where(h > 0.0, hv / h, 0.)
speed = sqrt(u**2 + v**2)
return speed
def stress(current_data):
from numpy import ma, where, sqrt, log10
q = current_data.q
h = q[0, :, :]
hu = q[1, :, :]
hv = q[2, :, :]
u = where(h > 0.0, hu / h, 0.)
v = where(h > 0.0, hv / h, 0.)
speed = np.sqrt(u**2 + v**2) #Speed calc, same as above
n = 0.06 #Manning's n
g = 9.8 #gravity
cf = where(
h > 0.0, (g * n**2) / (h**(1. / 3)), 0.
) #calculate friction coefficient, DONT FORGET THE F*****G PERIOD YOU IDIOT (mike)
stress = 1000 * cf * (speed**2)
return stress
# def erodibilityratio(current_data): # ratio of impelling forces (dimensionless shear stress T) to resisting forces (critical shear stress Tc)
# from numpy import ma, where, sqrt, log10
# q=current_data.q
# h=q[0,:,:]
# hu=q[1,:,:]
# hv=q[2,:,:]
# u = where(h>0.0, hu/h, 0.)
# v = where(h>0.0, hv/h, 0.)
# speed = sqrt(u**2 +v**2) #Speed calc, same as above
# n = 0.06 #Manning's n
# g = 9.8 #gravity
# def dsp(current_data): # dsp = depth slope product
# from numpy import ma, where, sqrt, log10
# q = current_data.q
# h=q[0,:,:]
# g = 9.8 # gravity
# dsp = 1000*g*h*0.02 # using a bulk channel gradient of 0.02-- will need to figure out how to make a localized measurement of this
# return dsp
# def froude(current_data):
# from numpy import ma, where, sqrt, log10
# drytol = 1e-3
# q = current_data.q
# h=q[0,:,:]
# hu=q[1,:,:]
# hv=q[2,:,:]
# u = where(h>0.0, hu/h, 0.)
# v = where(h>0.0, hv/h, 0.)
# g = 9.8
# speed = np.sqrt(u**2 +v**2)
# froude = speed/((g*h)**(1.2))
# return froude
# def blocksize(current_data):
# from numpy import ma, where, sqrt, log10
# q = current_data.q
# h=q[0,:,:]
# hu=q[1,:,:]
# hv=q[2,:,:]
# u = where(h>0.0, hu/h, 0.)
# v = where(h>0.0, hv/h, 0.)
# speed = np.sqrt(u**2 +v**2) #Speed calc, same as above
# n = 0.04 #Manning's n
# g = 9.8 #gravity idiot
# cf = where(h>0.0, (g*n**2)/(h**(1./3)), 0.)
# stress = 1000*cf*(speed**2)
# tc = 0.15*((0.02)**(1./4)) #need to choose a slope here, sooooo 0.02
# blocksize = stress/(tc*g*1700)
# return blocksize
#####-----------------------------------------
# Lake (depth)
#-----------------------------------------
#
plotfigure = plotdata.new_plotfigure(name='lake_depth', figno=1)
plotfigure.show = True
plotfigure.kwargs = {'figsize': [15, 15]}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('Depth')
#plotaxes.title = 'Water Surface'
plotaxes.scaled = True
plotaxes.xlimits = [93.0, 95.6]
plotaxes.ylimits = [28.0, 30.0]
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.depth #variable to plot
plotitem.pcolor_cmap = geoplot.custom_river
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 200
plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_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.blank
plotitem.pcolor_cmap = geoplot.bw_colormap
plotitem.pcolor_cmin = 2000.0
plotitem.pcolor_cmax = 6000.0
#plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_show = [0]
#plotaxes.afteraxes = addgauges
#####-----------------------------------------
# Lake (speed)
#-----------------------------------------
#
plotfigure = plotdata.new_plotfigure(name='lake_speed', figno=2)
plotfigure.show = True
plotfigure.kwargs = {'figsize': [15, 15]}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('Speed')
#plotaxes.title = 'Water Surface'
plotaxes.scaled = True
plotaxes.xlimits = [93, 94.96]
plotaxes.ylimits = [28.96, 29.77]
# speed
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = speed
plotitem.pcolor_cmap = geoplot.custom_river
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 80
plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_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.blank
plotitem.pcolor_cmap = geoplot.bw_colormap
plotitem.pcolor_cmin = 2000.0
plotitem.pcolor_cmax = 6000.0
#plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_show = [0]
#plotaxes.afteraxes = addgauges
#####-----------------------------------------
# Lake (stress)
#-----------------------------------------
#
plotfigure = plotdata.new_plotfigure(name='lake_stress', figno=3)
plotfigure.show = True
plotfigure.kwargs = {'figsize': [15, 15]}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('Stress')
#plotaxes.title = 'Water Surface'
plotaxes.scaled = True
plotaxes.xlimits = [93, 94.96]
plotaxes.ylimits = [28.96, 29.77]
# stress
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = stress
plotitem.pcolor_cmap = geoplot.custom_river
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 2500 #make this reasonable max stress
plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_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.blank
plotitem.pcolor_cmap = geoplot.bw_colormap
plotitem.pcolor_cmin = 2000.0
plotitem.pcolor_cmax = 6000.0
#plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_show = [0]
#-----------------------------------------
# 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 = np.arange(0,5,1) # list of frames to print
#plotdata.print_framenos = [9] #frame is a timestep, so this is the way
#plotdata.print_gaugenos = [1,2,3,4] # list of gauges to print
plotdata.print_fignos = 'all' # list of figures to print
plotdata.html = False # 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 = 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 = 'ascii' # '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]
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 = [1,1,0]
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 = [1,0,0]
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')
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
#-----------------------------------------
# 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 clawpack.visclaw.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
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.format = "ascii"
# Figure for pcolor plot
plotfigure = plotdata.new_plotfigure(name='q[0]', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
plotaxes.ylimits = 'auto'
plotaxes.title = 'q[0]'
plotaxes.scaled = True
plotaxes.afteraxes = addgauges
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = 0
plotitem.pcolor_cmap = colormaps.red_yellow_blue
plotitem.pcolor_cmin = -1.
plotitem.pcolor_cmax = 1.
plotitem.add_colorbar = True
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p
plotitem.show = True # show on plot?
# 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 = 'auto'
plotaxes.ylimits = 'auto'
plotaxes.title = 'q[0]'
plotaxes.scaled = True
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = 0
plotitem.contour_levels = np.linspace(-0.9, 0.9, 10)
plotitem.amr_contour_colors = ['k','b']
plotitem.patchedges_show = 1
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p
plotitem.show = True # show on plot?
# Figure for grids
plotfigure = plotdata.new_plotfigure(name='grids', figno=2)
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
plotaxes.ylimits = 'auto'
plotaxes.title = 'grids'
plotaxes.scaled = True
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_patch')
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p
plotitem.amr_celledges_show = [1,1,0]
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-'
# Parameters used only when creating html and/or latex hardcopy
# e.g., via clawpack.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 = 'ascii'
# 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'))
# Calculate landfall time
# Landfall for Ike in Houston was September 13th, at 7 UTC
landfall_dt = datetime.datetime(2008, 9, 13, 7) - \
datetime.datetime(2008, 1, 1, 0)
landfall = landfall_dt.days * 24.0 * 60**2 + landfall_dt.seconds
# Set afteraxes function
def surge_afteraxes(cd):
surgeplot.surge_afteraxes(cd, track, landfall, plot_direction=False,
kwargs={"markersize": 4})
# Color limits
surface_limits = [-5.0, 5.0]
speed_limits = [0.0, 3.0]
wind_limits = [0, 64]
pressure_limits = [935, 1013]
friction_bounds = [0.01, 0.04]
def gulf_after_axes(cd):
# plt.subplots_adjust(left=0.08, bottom=0.04, right=0.97, top=0.96)
surge_afteraxes(cd)
def latex_after_axes(cd):
# plt.subplot_adjust()
surge_afteraxes(cd)
def friction_after_axes(cd):
# plt.subplots_adjust(left=0.08, bottom=0.04, right=0.97, top=0.96)
plt.title(r"Manning's $n$ Coefficient")
# surge_afteraxes(cd)
# ==========================================================================
# Plot specifications
# ==========================================================================
regions = {"Gulf": {"xlimits": (clawdata.lower[0], clawdata.upper[0]),
"ylimits": (clawdata.lower[1], clawdata.upper[1]),
"figsize": (6.4, 4.8)},
"LaTex Shelf": {"xlimits": (-97.5, -88.5),
"ylimits": (27.5, 30.5),
"figsize": (8, 2.7)}}
for (name, region_dict) in regions.iteritems():
# 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 True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Gulf']['xlimits']
plotaxes.ylimits = regions['Gulf']['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 True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Gulf']['xlimits']
plotaxes.ylimits = regions['Gulf']['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 True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Gulf']['xlimits']
plotaxes.ylimits = regions['Gulf']['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, landfall=landfall)
# 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 = [-95.5, -94]
plotaxes.ylimits = [29.0, 30.0]
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
# -----------------------------------------
# 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 = [1, 2, 3, 4] # list of gauges to print
plotdata.print_fignos = 'all' # list of figures to print
plotdata.html = True # create html files of plots?
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 # 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.
"""
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"] = 1.0e-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 clawpack.visclaw 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_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]
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, 0.0, 1.0)
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(0.0, 11.0, 1.0)
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 = [0.0]
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]
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, 0.0, 1.0)
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(0.0, 11.0, 1.0)
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 = [0.0]
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 = [0.0, 100.0]
plotaxes.ylimits = [-1.5, 2.0]
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
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
def setplot(plotdata=None):
#--------------------------
r"""Setplot function for surge plotting"""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.format = 'binary'
fig_num_counter = surgeplot.figure_counter()
# Load data from output
clawdata = clawutil.ClawInputData(2)
clawdata.read(os.path.join(plotdata.outdir,'claw.data'))
amrdata = amrclaw.AmrclawInputData(clawdata)
amrdata.read(os.path.join(plotdata.outdir,'amr.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'))
# Calculate landfall time, off by a day, maybe leap year issue?
landfall_dt = datetime.datetime(2008,9,13,7) - datetime.datetime(2008,1,1,0)
landfall = (landfall_dt.days - 1.0) * 24.0 * 60**2 + landfall_dt.seconds
# Set afteraxes function
surge_afteraxes = lambda cd: surgeplot.surge_afteraxes(cd,
track, landfall, plot_direction=False)
# Color limits
surface_range = 5.0
speed_range = 3.0
eta = physics.sea_level
if not isinstance(eta,list):
eta = [eta]
surface_limits = [eta[0]-surface_range,eta[0]+surface_range]
# surface_contours = numpy.linspace(-surface_range, surface_range,11)
surface_contours = [-5,-4.5,-4,-3.5,-3,-2.5,-2,-1.5,-1,-0.5,0.5,1,1.5,2,2.5,3,3.5,4,4.5,5]
surface_ticks = [-5,-4,-3,-2,-1,0,1,2,3,4,5]
surface_labels = [str(value) for value in surface_ticks]
speed_limits = [0.0,speed_range]
speed_contours = numpy.linspace(0.0,speed_range,13)
speed_ticks = [0,1,2,3]
speed_labels = [str(value) for value in speed_ticks]
wind_limits = [0,64]
# wind_limits = [-0.002,0.002]
pressure_limits = [935,1013]
friction_bounds = [0.01,0.04]
# vorticity_limits = [-1.e-2,1.e-2]
# def pcolor_afteraxes(current_data):
# surge_afteraxes(current_data)
# surge.plot.gauge_locations(current_data,gaugenos=[6])
def contour_afteraxes(current_data):
surge_afteraxes(current_data)
def add_custom_colorbar_ticks_to_axes(axes, item_name, ticks, tick_labels=None):
axes.plotitem_dict[item_name].colorbar_ticks = ticks
axes.plotitem_dict[item_name].colorbar_tick_labels = tick_labels
# ==========================================================================
# ==========================================================================
# Plot specifications
# ==========================================================================
# ==========================================================================
# ========================================================================
# Entire Gulf
# ========================================================================
gulf_xlimits = [clawdata.lower[0],clawdata.upper[0]]
gulf_ylimits = [clawdata.lower[1],clawdata.upper[1]]
gulf_shrink = 0.9
def gulf_after_axes(cd):
plt.subplots_adjust(left=0.08, bottom=0.04, right=0.97, top=0.96)
surge_afteraxes(cd)
#
# Surface
#
plotfigure = plotdata.new_plotfigure(name='Surface - Entire Domain',
figno=fig_num_counter.get_counter())
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Surface'
plotaxes.scaled = True
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_ylimits
plotaxes.afteraxes = gulf_after_axes
surgeplot.add_surface_elevation(plotaxes, plot_type='contourf',
contours=surface_contours,
shrink=gulf_shrink)
surgeplot.add_land(plotaxes,topo_min=-10.0,topo_max=5.0)
# surge.plot.add_bathy_contours(plotaxes)
if article:
plotaxes.plotitem_dict['surface'].add_colorbar = False
else:
add_custom_colorbar_ticks_to_axes(plotaxes, 'surface', surface_ticks, surface_labels)
plotaxes.plotitem_dict['surface'].amr_patchedges_show = [1,1,1,1,1,1,1,1]
#
# Water Speed
#
plotfigure = plotdata.new_plotfigure(name='Currents - Entire Domain',
figno=fig_num_counter.get_counter())
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents'
plotaxes.scaled = True
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_ylimits
plotaxes.afteraxes = gulf_after_axes
# Speed
surgeplot.add_speed(plotaxes, plot_type='contourf',
contours=speed_contours,
shrink=gulf_shrink)
if article:
plotaxes.plotitem_dict['speed'].add_colorbar = False
else:
add_custom_colorbar_ticks_to_axes(plotaxes, 'speed', speed_ticks, speed_labels)
# Land
surgeplot.add_land(plotaxes)
surgeplot.add_bathy_contours(plotaxes)
#
# Friction field
#
plotfigure = plotdata.new_plotfigure(name='Friction',
figno=fig_num_counter.get_counter())
plotfigure.show = friction_data.variable_friction and True
def friction_after_axes(cd):
plt.subplots_adjust(left=0.08, bottom=0.04, right=0.97, top=0.96)
plt.title(r"Manning's $n$ Coefficient")
# surge_afteraxes(cd)
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_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 = [0,0,0,0,0,0,0]
plotaxes.plotitem_dict['friction'].colorbar_label = "$n$"
# ========================================================================
# LaTex Shelf
# ========================================================================
latex_xlimits = [-97.5,-88.5]
latex_ylimits = [27.5,30.5]
latex_shrink = 1.0
def latex_after_axes(cd):
if article:
plt.subplots_adjust(left=0.07, bottom=0.14, right=1.0, top=0.86)
else:
plt.subplots_adjust(right=1.0)
surge_afteraxes(cd)
#
# Surface
#
plotfigure = plotdata.new_plotfigure(name='Surface - LaTex Shelf',
figno=fig_num_counter.get_counter())
plotfigure.show = True
if article:
plotfigure.kwargs = {'figsize':(8,2.7), 'facecolor':'none'}
else:
plotfigure.kwargs = {'figsize':(9,2.7), 'facecolor':'none'}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Surface'
plotaxes.scaled = True
plotaxes.xlimits = latex_xlimits
plotaxes.ylimits = latex_ylimits
plotaxes.afteraxes = latex_after_axes
surgeplot.add_surface_elevation(plotaxes, plot_type='contourf',
contours=surface_contours,
shrink=latex_shrink)
if article:
plotaxes.plotitem_dict['surface'].add_colorbar = False
# plotaxes.afteraxes = lambda cd: article_latex_after_axes(cd, landfall)
else:
add_custom_colorbar_ticks_to_axes(plotaxes, 'surface', [-5,-2.5,0,2.5,5.0],
["-5.0","-2.5"," 0"," 2.5"," 5.0"])
# plotaxes.plotitem_dict['surface'].contour_cmap = plt.get_cmap('OrRd')
# surge.plot.add_surface_elevation(plotaxes,plot_type='contour')
surgeplot.add_land(plotaxes)
# plotaxes.plotitem_dict['surface'].amr_patchedges_show = [1,1,1,0,0,0,0]
plotaxes.plotitem_dict['surface'].amr_patchedges_show = [0,0,0,0,0,0,0]
# plotaxes.plotitem_dict['land'].amr_patchedges_show = [1,1,1,0,0,0,0]
plotaxes.plotitem_dict['land'].amr_patchedges_show = [0,0,0,0,0,0,0]
# Plot using jet and 0.0 to 5.0 to match figgen generated ADCIRC results
# plotaxes.plotitem_dict['surface'].pcolor_cmin = 0.0
# plotaxes.plotitem_dict['surface'].pcolor_cmax = 5.0
# plotaxes.plotitem_dict['surface'].pcolor_cmap = plt.get_cmap('jet')
#
# Water Speed
#
plotfigure = plotdata.new_plotfigure(name='Currents - LaTex Shelf',
figno=fig_num_counter.get_counter())
plotfigure.show = True
if article:
plotfigure.kwargs = {'figsize':(8,2.7), 'facecolor':'none'}
else:
plotfigure.kwargs = {'figsize':(9,2.7), 'facecolor':'none'}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents'
plotaxes.scaled = True
plotaxes.xlimits = latex_xlimits
plotaxes.ylimits = latex_ylimits
plotaxes.afteraxes = latex_after_axes
surgeplot.add_speed(plotaxes, plot_type='contourf',
contours=speed_contours,
shrink=latex_shrink)
if article:
plotaxes.plotitem_dict['speed'].add_colorbar = False
else:
add_custom_colorbar_ticks_to_axes(plotaxes, 'speed', speed_ticks, speed_labels)
# surge.plot.add_surface_elevation(plotaxes,plot_type='contour')
surgeplot.add_land(plotaxes)
# plotaxes.plotitem_dict['speed'].amr_patchedges_show = [1,1,0,0,0,0,0]
# plotaxes.plotitem_dict['land'].amr_patchedges_show = [1,1,1,0,0,0,0]
plotaxes.plotitem_dict['speed'].amr_patchedges_show = [0,0,0,0,0,0,0]
plotaxes.plotitem_dict['land'].amr_patchedges_show = [0,0,0,0,0,0,0]
# ========================================================================
# Houston/Galveston
# ========================================================================
houston_xlimits = [-(95.0 + 26.0 / 60.0), -(94.0 + 25.0 / 60.0)]
houston_ylimits = [29.1, 29.0 + 55.0 / 60.0]
houston_shrink = 0.9
def houston_after_axes(cd):
if article:
plt.subplots_adjust(left=0.05, bottom=0.07, right=0.99, top=0.92)
else:
plt.subplots_adjust(left=0.12, bottom=0.06, right=0.97, top=0.97)
surge_afteraxes(cd)
# surge.plot.gauge_locations(cd)
#
# Surface Elevations
#
plotfigure = plotdata.new_plotfigure(name='Surface - Houston/Galveston',
figno=fig_num_counter.get_counter())
plotfigure.show = True
# if article:
# plotfigure.kwargs['figsize'] =
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Surface'
plotaxes.scaled = True
plotaxes.xlimits = houston_xlimits
plotaxes.ylimits = houston_ylimits
plotaxes.afteraxes = houston_after_axes
surgeplot.add_surface_elevation(plotaxes, plot_type='contourf',
contours=surface_contours,
shrink=houston_shrink)
if article:
plotaxes.plotitem_dict['surface'].add_colorbar = False
else:
add_custom_colorbar_ticks_to_axes(plotaxes, 'surface', surface_ticks, surface_labels)
surgeplot.add_land(plotaxes)
plotaxes.plotitem_dict['surface'].amr_patchedges_show = [0,0,0,0,0,0,0]
plotaxes.plotitem_dict['land'].amr_patchedges_show = [0,0,0,0,0,0,0]
# surge.plot.add_bathy_contours(plotaxes)
# Plot using jet and 0.0 to 5.0 to match figgen generated ADCIRC results
# plotaxes.plotitem_dict['surface'].pcolor_cmin = 0.0
# plotaxes.plotitem_dict['surface'].pcolor_cmax = 5.0
# plotaxes.plotitem_dict['surface'].pcolor_cmap = plt.get_cmap('jet')
#
# Water Speed
#
plotfigure = plotdata.new_plotfigure(name='Currents - Houston/Galveston',
figno=fig_num_counter.get_counter())
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents'
plotaxes.scaled = True
plotaxes.xlimits = houston_xlimits
plotaxes.ylimits = houston_ylimits
plotaxes.afteraxes = houston_after_axes
surgeplot.add_speed(plotaxes, plot_type='contourf',
contours=speed_contours,
shrink=houston_shrink)
if article:
plotaxes.plotitem_dict['speed'].add_colorbar = False
else:
add_custom_colorbar_ticks_to_axes(plotaxes, 'speed', speed_ticks, speed_labels)
surgeplot.add_land(plotaxes)
# surge.plot.add_bathy_contours(plotaxes)
# plotaxes.plotitem_dict['speed'].amr_patchedges_show = [1,1,1,1,1,1,1,1]
# plotaxes.plotitem_dict['land'].amr_patchedges_show = [1,1,1,1,1,1,1,1]
plotaxes.plotitem_dict['speed'].amr_patchedges_show = [0,0,0,0,0,0,0]
plotaxes.plotitem_dict['land'].amr_patchedges_show = [0,0,0,0,0,0,0]
# ==========================
# Hurricane Forcing fields
# ==========================
# Pressure field
plotfigure = plotdata.new_plotfigure(name='Pressure',
figno=fig_num_counter.get_counter())
plotfigure.show = surge_data.pressure_forcing and True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_ylimits
plotaxes.title = "Pressure Field"
plotaxes.afteraxes = gulf_after_axes
plotaxes.scaled = True
surgeplot.add_pressure(plotaxes, bounds=pressure_limits, shrink=gulf_shrink)
surgeplot.add_land(plotaxes)
# Wind field
plotfigure = plotdata.new_plotfigure(name='Wind Speed',
figno=fig_num_counter.get_counter())
plotfigure.show = surge_data.wind_forcing and True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_ylimits
plotaxes.title = "Wind Field"
plotaxes.afteraxes = gulf_after_axes
plotaxes.scaled = True
surgeplot.add_wind(plotaxes, bounds=wind_limits, plot_type='pcolor',
shrink=gulf_shrink)
surgeplot.add_land(plotaxes)
# ========================================================================
# Figures for gauges
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=300, \
type='each_gauge')
plotfigure.show = True
plotfigure.clf_each_gauge = True
# plotfigure.kwargs['figsize'] = (16,10)
def gauge_after_axes(cd):
if cd.gaugeno in [1,2,3,4]:
axes = plt.gca()
# # Add Kennedy gauge data
# kennedy_gauge = kennedy_gauges[gauge_name_trans[cd.gaugeno]]
# axes.plot(kennedy_gauge['t'] - seconds2days(date2seconds(gauge_landfall[0])),
# kennedy_gauge['mean_water'] + kennedy_gauge['depth'], 'k-',
# label='Gauge Data')
# Add GeoClaw gauge data
geoclaw_gauge = cd.gaugesoln
axes.plot(seconds2days(geoclaw_gauge.t - date2seconds(gauge_landfall[1])),
geoclaw_gauge.q[3,:] + gauge_surface_offset[0], 'b--',
label="GeoClaw")
# Add ADCIRC gauge data
# ADCIRC_gauge = ADCIRC_gauges[kennedy_gauge['gauge_no']]
# axes.plot(seconds2days(ADCIRC_gauge[:,0] - gauge_landfall[2]),
# ADCIRC_gauge[:,1] + gauge_surface_offset[1], 'r-.', label="ADCIRC")
# Fix up plot
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)
axes.legend()
plt.hold(False)
# surge.plot.gauge_afteraxes(cd)
# 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'
plotaxes.afteraxes = gauge_after_axes
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
# =====================
# Gauge Location Plot
# =====================
gauge_xlimits = [-95.5, -94]
gauge_ylimits = [29.0, 30.0]
gauge_location_shrink = 0.75
def gauge_after_axes(cd):
plt.subplots_adjust(left=0.12, bottom=0.06, right=0.97, top=0.97)
surge_afteraxes(cd)
surgeplot.gauge_locations(cd, gaugenos=[1, 2, 3, 4])
plt.title("Gauge Locations")
plotfigure = plotdata.new_plotfigure(name='Gauge Locations',
figno=fig_num_counter.get_counter())
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Surface'
plotaxes.scaled = True
plotaxes.xlimits = gauge_xlimits
plotaxes.ylimits = gauge_ylimits
plotaxes.afteraxes = gauge_after_axes
surgeplot.add_surface_elevation(plotaxes, plot_type='contourf',
contours=surface_contours,
shrink=gauge_location_shrink)
# surge.plot.add_surface_elevation(plotaxes, plot_type="contourf")
add_custom_colorbar_ticks_to_axes(plotaxes, 'surface', surface_ticks, surface_labels)
surgeplot.add_land(plotaxes)
# plotaxes.plotitem_dict['surface'].amr_patchedges_show = [0,0,0,0,0,0,0]
# plotaxes.plotitem_dict['surface'].add_colorbar = False
# plotaxes.plotitem_dict['surface'].pcolor_cmap = plt.get_cmap('jet')
# plotaxes.plotitem_dict['surface'].pcolor_cmap = plt.get_cmap('gist_yarg')
# plotaxes.plotitem_dict['surface'].pcolor_cmin = 0.0
# plotaxes.plotitem_dict['surface'].pcolor_cmax = 5.0
plotaxes.plotitem_dict['surface'].amr_patchedges_show = [0,0,0,0,0,0,0]
plotaxes.plotitem_dict['land'].amr_patchedges_show = [0,0,0,0,0,0,0]
# ==============================================================
# Debugging Plots, only really work if using interactive plots
# ==============================================================
#
# Water Velocity Components
#
plotfigure = plotdata.new_plotfigure(name='Velocity Components - Entire Domain',
figno=fig_num_counter.get_counter())
plotfigure.show = False
# X-Component
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = "subplot(121)"
plotaxes.title = 'Velocity, X-Component'
plotaxes.scaled = True
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_ylimits
plotaxes.afteraxes = gulf_after_axes
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = surgeplot.water_u
plotitem.pcolor_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
plotitem.pcolor_cmin = -speed_limits[1]
plotitem.pcolor_cmax = speed_limits[1]
plotitem.colorbar_shrink = gulf_shrink
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.amr_patchedges_show = [1,1,1]
surgeplot.add_land(plotaxes)
# Y-Component
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = "subplot(122)"
plotaxes.title = 'Velocity, Y-Component'
plotaxes.scaled = True
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_ylimits
plotaxes.afteraxes = gulf_after_axes
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = surgeplot.water_v
plotitem.pcolor_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
plotitem.pcolor_cmin = -speed_limits[1]
plotitem.pcolor_cmax = speed_limits[1]
plotitem.colorbar_shrink = gulf_shrink
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.amr_patchedges_show = [1,1,1]
surgeplot.add_land(plotaxes)
#
# Depth
#
plotfigure = plotdata.new_plotfigure(name='Depth - Entire Domain',
figno=fig_num_counter.get_counter())
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'depth'
plotaxes.scaled = True
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_ylimits
plotaxes.afteraxes = gulf_after_axes
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = 0
plotitem.imshow_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
plotitem.imshow_cmin = 0
plotitem.imshow_cmax = 100
plotitem.colorbar_shrink = gulf_shrink
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.amr_patchedges_show = [1,1,1,1,1,1,1,1,1]
# Surge field
plotfigure = plotdata.new_plotfigure(name='Surge Field',
figno=fig_num_counter.get_counter())
plotfigure.show = ((surge_data.wind_forcing or surge_data.pressure_forcing)
and False)
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_ylimits
plotaxes.title = "Storm Surge Source Term S"
plotaxes.afteraxes = gulf_after_axes
plotaxes.scaled = True
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = surgeplot.pressure_field + 1
plotitem.pcolor_cmap = plt.get_cmap('PuBu')
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 1e-3
plotitem.add_colorbar = True
plotitem.colorbar_shrink = gulf_shrink
plotitem.colorbar_label = "Source Strength"
plotitem.amr_celledges_show = [0,0,0]
plotitem.amr_patchedges_show = [1,1,1,1,1,0,0]
surgeplot.add_land(plotaxes)
plotfigure = plotdata.new_plotfigure(name='Friction/Coriolis Source',
figno=fig_num_counter.get_counter())
plotfigure.show = False
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = gulf_xlimits
plotaxes.ylimits = gulf_ylimits
plotaxes.title = "Friction/Coriolis Source"
plotaxes.afteraxes = surge_afteraxes
plotaxes.scaled = True
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = surgeplot.pressure_field + 2
plotitem.pcolor_cmap = plt.get_cmap('PuBu')
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 1e-3
plotitem.add_colorbar = True
plotitem.colorbar_shrink = gulf_shrink
plotitem.colorbar_label = "Source Strength"
plotitem.amr_celledges_show = [0,0,0]
plotitem.amr_patchedges_show = [1,1,1,1,1,0,0]
surgeplot.add_land(plotaxes)
#-----------------------------------------
# Parameters used only when creating html and/or latex hardcopy
# e.g., via pyclaw.plotters.frametools.printframes:
if article:
plotdata.printfigs = True # print figures
plotdata.print_format = 'png' # file format
plotdata.print_framenos = [54,60,66,72,78,84] # list of frames to print
plotdata.print_gaugenos = [1,2,3,4] # list of gauges to print
plotdata.print_fignos = [4,5,6,7,10,3,300] # 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?
else:
plotdata.printfigs = True # print figures
plotdata.print_format = 'png' # file format
plotdata.print_framenos = 'all' # list of frames to print
plotdata.print_gaugenos = [1,2,3,4] # 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):
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures()
mapc2p, mx_edge, xp_edge = make_mapc2p(fname_celledges)
def mapc2p_km(xc):
x_m = mapc2p(xc)
x_km = x_m / 1000. # convert to km
return x_km
def fixticks1(current_data):
from pylab import ticklabel_format, grid
ticklabel_format(useOffset=False)
grid(True)
def fixticks(current_data):
from pylab import ticklabel_format, plot,grid,ones,sqrt, \
legend,title,ylabel,text
ticklabel_format(useOffset=False)
# to plot max elevation over entire computation:
#if xmax is not None:
# plot(xmax, etamax, 'r')
#grid(True)
hl = 3200.
hr = 200.
greens = (hl / hr)**(0.25)
print('greens = ', greens)
#plot(current_data.x, greens*ones(current_data.x.shape),'g--')
plot(xlimits, [greens, greens], 'g--', label='$C_g$, Greens Law')
ctrans = 2 * sqrt(hl) / (sqrt(hl) + sqrt(hr))
crefl = (sqrt(hl) - sqrt(hr)) / (sqrt(hl) + sqrt(hr))
print('ctrans = ', ctrans)
plot(xlimits, [ctrans, ctrans],
'r--',
label='$C_T$, Transmission coefficient')
legend(loc='upper left')
title('')
ylabel('meters', fontsize=14)
if current_data.frameno == 0:
text(-80, -0.4, '$\longrightarrow$', fontsize=20)
text(-80, -0.6, 'Incident')
h = current_data.q[0, :]
mx2 = int(round(len(h) / 2.))
etamax2 = (h[:mx2] - hl).max()
print('mx2 = %i, etamax2 = %g' % (mx2, etamax2))
plotfigure = plotdata.new_plotfigure(name='domain', figno=0)
plotfigure.kwargs = {'figsize': (7, 6.5)}
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'axes([.1,.4,.8,.5])' #'subplot(211)'
plotaxes.xlimits = xlimits
#plotaxes.xlimits = [-100e3,-20e3]
plotaxes.ylimits = [-1, 3]
plotaxes.title = 'Surface displacement'
plotaxes.afteraxes = fixticks
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = geoplot.surface
plotitem.color = 'b'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.color = 'k'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotaxes = plotfigure.new_plotaxes()
plotaxes.show = False
plotaxes.axescmd = 'subplot(312)'
plotaxes.xlimits = xlimits
#plotaxes.xlimits = [-100e3,-20e3]
#plotaxes.ylimits = [-1000, 1000]
#plotaxes.title = 'Full depth'
plotaxes.title = 'momentum'
plotaxes.afteraxes = fixticks1
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotitem = plotaxes.new_plotitem(plot_type='1d_fill_between')
plotitem.show = False
plotitem.plot_var = geoplot.surface
plotitem.plot_var2 = geoplot.topo
plotitem.color = 'b'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.color = 'k'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 1
plotitem.color = 'k'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'axes([.1,.1,.8,.2])' #'subplot(212)'
plotaxes.xlimits = xlimits
#plotaxes.xlimits = [-100e3,-20e3]
#plotaxes.ylimits = [-1000, 1000]
#plotaxes.title = 'Full depth'
#plotaxes.title = 'topography'
def fix_topo_plot(current_data):
from pylab import title, xlabel
title('')
xlabel('kilometers', fontsize=14)
plotaxes.afteraxes = fix_topo_plot
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
#plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.color = 'k'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
#----------
plotfigure = plotdata.new_plotfigure(name='shore', figno=1)
#plotfigure.kwargs = {'figsize':(9,11)}
plotfigure.show = False
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(211)'
plotaxes.xlimits = [0, 80e3]
plotaxes.ylimits = [-4, 4]
plotaxes.title = 'Zoom on shelf'
plotaxes.afteraxes = fixticks
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = geoplot.surface
#plotitem = plotaxes.new_plotitem(plot_type='1d_fill_between')
#plotitem.plot_var = geoplot.surface
#plotitem.plot_var2 = geoplot.topo
plotitem.color = 'b'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = geoplot.topo
plotitem.color = 'k'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(212)'
#plotaxes.xlimits = [-2000,2000]
plotaxes.xlimits = [-1000, 1000]
#plotaxes.ylimits = [-10,40]
plotaxes.ylimits = [-20, 60]
plotaxes.title = 'Zoom around shore'
plotaxes.afteraxes = fixticks
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.show = False
plotitem.plot_var = geoplot.surface
plotitem = plotaxes.new_plotitem(plot_type='1d_fill_between')
plotitem.plot_var = geoplot.surface
plotitem.plot_var2 = geoplot.topo
plotitem.color = 'b'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = geoplot.topo
plotitem.color = 'k'
plotitem.MappedGrid = True
plotitem.mapc2p = mapc2p_km
plotdata.printfigs = True # Whether to output figures
plotdata.print_format = 'png' # What type of output format
plotdata.print_framenos = 'all' # Which frames to output
plotdata.print_fignos = 'all' # Which figures to print
plotdata.html = True # Whether to create HTML files
plotdata.latex = False # Whether to make LaTeX output
plotdata.parallel = True
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' # 'binary' for adjoint
# 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('Adjoint time %s before time of interest' % timestr)
#-----------------------------------------
# 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 = 'Adjoint'
plotaxes.scaled = True
plotaxes.afteraxes = title_hours
# 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 = -0.0005
plotitem.pcolor_cmax = 0.0005
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.amr_patchedges_show = [0, 1, 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 = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 0
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 = [1, 0, 0]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
#-----------------------------------------
# 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):
""""""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
# clear any old figures,axes,items data
plotdata.clearfigures()
plotdata.format = 'ascii'
# 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_limits = [-5.0, 5.0]
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 = {
"Gulf": {
"xlimits": (clawdata.lower[0], clawdata.upper[0]),
"ylimits": (clawdata.lower[1], clawdata.upper[1]),
"figsize": (6.4, 4.8)
},
"LaTex Shelf": {
"xlimits": (-90.5, -85.5),
"ylimits": (22.5, 24.0),
"figsize": (8, 2.7)
}
}
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 True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Gulf']['xlimits']
plotaxes.ylimits = regions['Gulf']['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 True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Gulf']['xlimits']
plotaxes.ylimits = regions['Gulf']['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 True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = regions['Gulf']['xlimits']
plotaxes.ylimits = regions['Gulf']['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 = [-95.5, -94]
plotaxes.ylimits = [29.0, 30.0]
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
# -----------------------------------------
# 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 = [1, 2, 3, 4] # list of gauges to print
plotdata.print_fignos = 'all' # list of figures to print
plotdata.html = True # create html files of plots?
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 # parallel plotting
return plotdata
def setplot(plotdata=None):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of clawpack.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 density - pcolor
plotfigure = plotdata.new_plotfigure(name='Density', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0, 1]
plotaxes.ylimits = [0, 1]
plotaxes.title = 'Density'
plotaxes.scaled = True
plotaxes.afteraxes = addgauges
# 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.
plotitem.pcolor_cmax = 2.
plotitem.add_colorbar = True
plotitem.amr_patchedges_show = [0]
plotitem.amr_celledges_show = [0]
# Figure for density - Schlieren
plotfigure = plotdata.new_plotfigure(name='Schlieren', figno=1)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0, 1]
plotaxes.ylimits = [0, 1]
plotaxes.title = 'Density'
plotaxes.scaled = True # so aspect ratio is 1
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_schlieren')
plotitem.schlieren_cmin = 0.0
plotitem.schlieren_cmax = 1.0
plotitem.plot_var = 0
plotitem.add_colorbar = False
# 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']
plotitem.amr_celledges_show = [1, 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 = [0, 1]
plotaxes.ylimits = [0, 1]
plotaxes.title = 'Density'
# 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 clawpack.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):
#--------------------------
"""
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 = 'ascii' # 'ascii', 'binary', 'netcdf'
# 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)
# To add title with time format hours:minutes:seconds...
def title_hours(current_data):
from pylab import title, mod
t = current_data.t
hours = int(t / 3600.)
tmin = mod(t, 3600.)
min = int(tmin / 60.)
tsec = mod(tmin, 60.)
sec = int(mod(tmin, 60.))
timestr = '%s:%s:%s' % (hours, str(min).zfill(2), str(sec).zfill(2))
title('%s after earthquake' % timestr)
#-----------------------------------------
# Figure for surface
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface', figno=0)
plotfigure.kwargs = {'figsize': (12, 6)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.axescmd = 'subplot(121)'
plotaxes.title = 'Surface'
plotaxes.scaled = True
def fixup(current_data):
addgauges(current_data)
title_hours(current_data)
plotaxes.afteraxes = fixup
# 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 = -0.2
plotitem.pcolor_cmax = 0.2
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 1
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = geoplot.land
plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 0
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 = [1, 0, 0]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
#-----------------------------------------
# Figure for adjoint flagging
#-----------------------------------------
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('adjoint')
plotaxes.axescmd = 'subplot(122)'
plotaxes.scaled = True
plotaxes.title = 'Adjoint flag'
def fixup(current_data):
from pylab import title
addgauges(current_data)
title('Adjoint flagging indicator')
plotaxes.afteraxes = fixup
def masked_inner_product(current_data):
from numpy import ma
aux = current_data.aux
tol = 1e-15
soln = ma.masked_where(aux[3, :, :] < tol, aux[3, :, :])
return soln
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = masked_inner_product
plotitem.pcolor_cmap = colormaps.white_red
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 0.0005
#plotitem.pcolor_cmax = 0.00001 # use for adjoint-error flagging
plotitem.add_colorbar = False # doesn't work when adjoint all masked
plotitem.colorbar_shrink = 0.75
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.amr_data_show = [1, 1,
0] # inner product not computed on finest level
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 = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 0
plotaxes.xlimits = [-120, -60]
plotaxes.ylimits = [-60, 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')
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
#-----------------------------------------
# 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.
"""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
# Figure for q[0]
plotfigure = plotdata.new_plotfigure(name='q[0]', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0,1.5]
plotaxes.ylimits = [-2.,4.]
plotaxes.title = 'q[0]'
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='1d')
plotitem.plot_var = 0
plotitem.plotstyle = '-'
plotitem.color = 'b'
plotitem.show = True # show on plot?
# Figure for q[1]
plotfigure = plotdata.new_plotfigure(name='q[1]', figno=1)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
plotaxes.ylimits = 'auto'
plotaxes.title = 'q[1]'
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='1d')
plotitem.plot_var = 1
plotitem.plotstyle = '-'
plotitem.color = 'b'
plotitem.show = True # show on plot?
# 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_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, bathy_location=0.15, bathy_angle=0.0,
bathy_left=-1.0, bathy_right=-0.2):
"""Setup the plotting data objects.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
returns plotdata object
"""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
# Load data from output
clawdata = clawutil.ClawInputData(2)
clawdata.read(os.path.join(plotdata.outdir, 'claw.data'))
multilayer_data = clawpack.geoclaw.data.MultilayerData()
multilayer_data.read(os.path.join(plotdata.outdir, 'multilayer.data'))
def transform_c2p(x, y, x0, y0, theta):
return ((x+x0)*np.cos(theta) - (y+y0)*np.sin(theta),
(x+x0)*np.sin(theta) + (y+y0)*np.cos(theta))
def transform_p2c(x, y, x0, y0, theta):
return (x*np.cos(theta) + y*np.sin(theta) - x0,
-x*np.sin(theta) + y*np.cos(theta) - y0)
# Setup bathymetry reference lines
with open(os.path.join(plotdata.outdir, "bathy_geometry.data"), 'r') \
as bathy_geometry_file:
bathy_location = float(bathy_geometry_file.readline())
bathy_angle = float(bathy_geometry_file.readline())
x = [0.0, 0.0]
y = [0.0, 1.0]
x1, y1 = transform_c2p(x[0], y[0], bathy_location, 0.0, bathy_angle)
x2, y2 = transform_c2p(x[1], y[1], bathy_location, 0.0, bathy_angle)
if abs(x1 - x2) < 10**-3:
x = [x1, x1]
y = [clawdata.lower[1], clawdata.upper[1]]
else:
m = (y1 - y2) / (x1 - x2)
x[0] = (clawdata.lower[1] - y1) / m + x1
y[0] = clawdata.lower[1]
x[1] = (clawdata.upper[1] - y1) / m + x1
y[1] = clawdata.upper[1]
ref_lines = [((x[0], y[0]), (x[1], y[1]))]
plotdata.clearfigures()
plotdata.save_frames = False
# ========================================================================
# Generic helper functions
def pcolor_afteraxes(current_data):
bathy_ref_lines(current_data)
def contour_afteraxes(current_data):
axes = plt.gca()
pos = -80.0 * (23e3 / 180) + 500e3 - 5e3
axes.plot([pos, pos], [-300e3, 300e3], 'b',
[pos-5e3, pos-5e3], [-300e3, 300e3], 'y')
wind_contours(current_data)
bathy_ref_lines(current_data)
def profile_afteraxes(current_data):
pass
def bathy_ref_lines(current_data):
axes = plt.gca()
for ref_line in ref_lines:
x1 = ref_line[0][0]
y1 = ref_line[0][1]
x2 = ref_line[1][0]
y2 = ref_line[1][1]
axes.plot([x1, x2], [y1, y2], 'y--', linewidth=1)
# ========================================================================
# Axis limits
xlimits = [-0.5, 0.5]
ylimits = [-0.5, 0.5]
eta = [multilayer_data.eta[0], multilayer_data.eta[1]]
top_surface_limits = [eta[0] - 0.03, eta[0] + 0.03]
internal_surface_limits = [eta[1] - 0.015, eta[1] + 0.015]
top_speed_limits = [0.0, 0.1]
internal_speed_limits = [0.0, 0.03]
# ========================================================================
# Surface Elevations
plotfigure = plotdata.new_plotfigure(name='Surface')
plotfigure.show = True
plotfigure.kwargs = {'figsize': (14, 4)}
# Top surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Top Surface'
plotaxes.axescmd = 'subplot(1, 2, 1)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
ml_plot.add_surface_elevation(plotaxes,1,bounds=top_surface_limits)
# ml_plot.add_surface_elevation(plotaxes,1,bounds=[-0.06,0.06])
# ml_plot.add_surface_elevation(plotaxes,1)
ml_plot.add_land(plotaxes, 1)
# Bottom surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Internal Surface'
plotaxes.axescmd = 'subplot(1,2,2)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
# ml_plot.add_surface_elevation(plotaxes,2,bounds=[-300-0.5,-300+0.5])
ml_plot.add_surface_elevation(plotaxes,2,bounds=internal_surface_limits)
# ml_plot.add_surface_elevation(plotaxes,2)
ml_plot.add_land(plotaxes, 2)
# ========================================================================
# Depths
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='Depths', figno=42)
plotfigure.show = False
plotfigure.kwargs = {'figsize':(14,4)}
# Top surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Top Layer Depth'
plotaxes.axescmd = 'subplot(1,2,1)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
ml_plot.add_layer_depth(plotaxes,1,bounds=[-0.1,1.1])
ml_plot.add_land(plotaxes, 1)
# Bottom surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Bottom Layer Depth'
plotaxes.axescmd = 'subplot(1,2,2)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
ml_plot.add_layer_depth(plotaxes,2,bounds=[-0.1,0.7])
ml_plot.add_land(plotaxes, 2)
# ========================================================================
# Water Speed
plotfigure = plotdata.new_plotfigure(name='speed')
plotfigure.show = True
plotfigure.kwargs = {'figsize': (14, 4)}
# Top layer speed
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents - Top Layer'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(1, 2, 1)'
plotaxes.afteraxes = pcolor_afteraxes
ml_plot.add_speed(plotaxes, 1, bounds=top_speed_limits)
ml_plot.add_land(plotaxes, 1)
# Bottom layer speed
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents - Bottom Layer'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(1,2,2)'
plotaxes.afteraxes = pcolor_afteraxes
# add_speed(plotaxes,2,bounds=[0.0,1e-10])
ml_plot.add_speed(plotaxes,2,bounds=internal_speed_limits)
# add_speed(plotaxes,2)
ml_plot.add_land(plotaxes, 2)
# Individual components
plotfigure = plotdata.new_plotfigure(name='speed_components',figno=401)
plotfigure.show = False
plotfigure.kwargs = {'figsize':(14,14)}
# Top layer
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "X-Velocity - Top Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,1)'
plotaxes.afteraxes = pcolor_afteraxes
# add_x_velocity(plotaxes,1,bounds=[-1e-10,1e-10])
ml_plot.add_x_velocity(plotaxes,1)
ml_plot.add_land(plotaxes, 1)
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Y-Velocity - Top Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,2)'
plotaxes.afteraxes = pcolor_afteraxes
# add_y_velocity(plotaxes,1,bounds=[-0.000125,0.000125])
ml_plot.add_y_velocity(plotaxes,1)
ml_plot.add_land(plotaxes, 1)
# Bottom layer
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "X-Velocity - Bottom Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,3)'
plotaxes.afteraxes = pcolor_afteraxes
# add_x_velocity(plotaxes,2,bounds=[-1e-10,1e-10])
ml_plot.add_x_velocity(plotaxes,2)
ml_plot.add_land(plotaxes, 2)
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Y-Velocity - Bottom Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,4)'
plotaxes.afteraxes = pcolor_afteraxes
# add_y_velocity(plotaxes,2,bounds=[-0.8e-6,.8e-6])
ml_plot.add_y_velocity(plotaxes,2)
ml_plot.add_land(plotaxes, 2)
# ========================================================================
# Profile Plots
# Note that these are not currently plotted by default - set
# `plotfigure.show = True` is you want this to be plotted
plotfigure = plotdata.new_plotfigure(name='profile')
plotfigure.show = False
# Top surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = xlimits
plotaxes.ylimits = [-1.1, 0.1]
plotaxes.title = "Profile of depth"
plotaxes.afteraxes = profile_afteraxes
slice_index = 30
# Internal surface
def bathy_profile(current_data):
return current_data.x[:, slice_index], b(current_data)[:, slice_index]
def lower_surface(current_data):
if multilayer_data.init_type == 2:
return current_data.x[:, slice_index], \
eta2(current_data)[:, slice_index]
elif multilayer_data.init_type == 6:
return current_data.y[slice_index, :], \
eta2(current_data)[slice_index, :]
def upper_surface(current_data):
if multilayer_data.init_type == 2:
return current_data.x[:, slice_index], \
eta1(current_data)[:, slice_index]
elif multilayer_data.init_type == 6:
return current_data.y[slice_index, :], \
eta1(current_data)[slice_index, :]
def top_speed(current_data):
if multilayer_data.init_type == 2:
return current_data.x[:, slice_index], \
water_u1(current_data)[:, slice_index]
elif multilayer_data.init_type == 6:
return current_data.y[slice_index, :], \
water_u1(current_data)[slice_index, :]
def bottom_speed(current_data):
if multilayer_data.init_type == 2:
return current_data.x[:, slice_index], \
water_u2(current_data)[:, slice_index]
elif multilayer_data.init_type == 6:
return current_data.y[slice_index, :], \
water_u2(current_data)[slice_index, :]
# Bathy
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.map_2d_to_1d = bathy_profile
plotitem.plot_var = 0
plotitem.amr_plotstyle = ['-', '+', 'x']
plotitem.color = 'k'
plotitem.show = True
# Internal Interface
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.map_2d_to_1d = lower_surface
plotitem.plot_var = 7
plotitem.amr_plotstyle = ['-', '+', 'x']
plotitem.color = 'b'
plotitem.show = True
# Upper Interface
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.map_2d_to_1d = upper_surface
plotitem.plot_var = 6
plotitem.amr_plotstyle = ['-', '+', 'x']
plotitem.color = (0.2, 0.8, 1.0)
plotitem.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Y-Velocity'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
# Water
# plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
# # plotitem.plot_var = geoplot.surface
# plotitem.plot_var = water_v
# plotitem.pcolor_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
# # plotitem.pcolor_cmin = -1.e-10
# # plotitem.pcolor_cmax = 1.e-10
# # plotitem.pcolor_cmin = -2.5 # -3.0
# # plotitem.pcolor_cmax = 2.5 # 3.0
# plotitem.add_colorbar = True
# plotitem.amr_celledges_show = [0,0,0]
# plotitem.amr_patchedges_show = [1,1,1]
# Land
ml_plot.add_land(plotaxes, 1)
# ========================================================================
# Contour plot for surface
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='contour_surface',figno=15)
plotfigure.show = False
plotfigure.kwargs = {'figsize':(14,4)}
# Set up for axes in this figure:
# Top Surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Top Surface'
plotaxes.axescmd = 'subplot(1,2,1)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = contour_afteraxes
ml_plot.add_surface_elevation(plotaxes,plot_type='contour',surface=1,bounds=[-2.5,-1.5,-0.5,0.5,1.5,2.5])
ml_plot.add_land(plotaxes, 1, plot_type='contour')
# Internal Surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Internal Surface'
plotaxes.axescmd = 'subplot(1,2,2)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = contour_afteraxes
ml_plot.add_surface_elevation(plotaxes,plot_type='contour',surface=2,bounds=[-2.5,-1.5,-0.5,0.5,1.5,2.5])
ml_plot.add_land(plotaxes, 2, plot_type='contour')
# ========================================================================
# Contour plot for speed
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='contour_speed',figno=16)
plotfigure.show = False
plotfigure.kwargs = {'figsize':(14,4)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Current'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = contour_afteraxes
# Surface
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = ml_plot.water_speed_depth_ave
plotitem.kwargs = {'linewidths':1}
# plotitem.contour_levels = [1.0,2.0,3.0,4.0,5.0,6.0]
plotitem.contour_levels = [0.5,1.5,3,4.5,6.0]
plotitem.amr_contour_show = [1,1,1]
plotitem.amr_celledges_show = [0,0,0]
plotitem.amr_patchedges_show = [1,1,1]
plotitem.amr_contour_colors = 'k'
# plotitem.amr_contour_colors = ['r','k','b'] # color on each level
# plotitem.amr_grid_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.show = True
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.land
plotitem.contour_nlevels = 40
plotitem.contour_min = 0.0
plotitem.contour_max = 100.0
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.amr_patch_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.amr_celledges_show = 0
plotitem.amr_patchedges_show = 0
plotitem.show = True
# ========================================================================
# Grid Cells
# ========================================================================
# 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 = xlimits
plotaxes.ylimits = ylimits
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']
plotitem.amr_celledges_show = [0,0,0]
plotitem.amr_patchedges_show = [1,1,1]
# ========================================================================
# Vorticity Plot
# ========================================================================
# plotfigure = plotdata.new_plotfigure(name='vorticity',figno=17)
# plotfigure.show = False
# plotaxes = plotfigure.new_plotaxes()
# plotaxes.title = "Vorticity"
# plotaxes.scaled = True
# plotaxes.xlimits = xlimits
# plotaxes.ylimits = ylimits
# plotaxes.afteraxes = pcolor_afteraxes
#
# # Vorticity
# plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
# plotitem.plot_var = 9
# plotitem.imshow_cmap = plt.get_cmap('PRGn')
# # plotitem.pcolor_cmap = plt.get_cmap('PuBu')
# # plotitem.pcolor_cmin = 0.0
# # plotitem.pcolor_cmax = 6.0
# plotitem.imshow_cmin = -1.e-2
# plotitem.imshow_cmax = 1.e-2
# plotitem.add_colorbar = True
# plotitem.amr_celledges_show = [0,0,0]
# 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 = 80.0
# plotitem.add_colorbar = False
# plotitem.amr_celledges_show = [0,0,0]
# ========================================================================
# Figures for gauges
# Top
plotfigure = plotdata.new_plotfigure(name='Surface & topo',
type='each_gauge',
figno=301)
plotfigure.show = True
plotfigure.clf_each_gauge = True
plotfigure.kwargs = {'figsize': (14, 4)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(1, 2, 1)'
plotaxes.xlimits = [0.0, 1.0]
plotaxes.ylimits = top_surface_limits
plotaxes.title = 'Top Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 6
plotitem.plotstyle = 'b-'
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(1, 2, 2)'
plotaxes.xlimits = [0.0, 1.0]
plotaxes.ylimits = internal_surface_limits
plotaxes.title = 'Bottom Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 7
plotitem.plotstyle = 'b-'
# =========================================================================
# Other plots
# Gauge Locations - Enable to see where gauges are located
def locations_afteraxes(current_data, gaugenos='all'):
gaugetools.plot_gauge_locations(current_data.plotdata,
gaugenos=gaugenos,
format_string='kx',
add_labels=True)
pcolor_afteraxes(current_data)
plotfigure = plotdata.new_plotfigure(name='Gauge Locations')
plotfigure.show = False
plotfigure.kwargs = {'figsize': (14, 4)}
# Top surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Top Surface'
plotaxes.axescmd = 'subplot(1, 2, 1)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = locations_afteraxes
ml_plot.add_surface_elevation(plotaxes, 1, bounds=top_surface_limits)
ml_plot.add_land(plotaxes, 1)
# Bottom surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Internal Surface'
plotaxes.axescmd = 'subplot(1, 2, 2)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = locations_afteraxes
ml_plot.add_surface_elevation(plotaxes, 2, bounds=internal_surface_limits)
ml_plot.add_land(plotaxes, 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_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 # 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
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
def set_drytol(current_data):
# The drytol parameter is used in masking land and water and
# affects what color map is used for cells with small water depth h.
# The cell will be plotted as dry if h < drytol.
# The best value to use often depends on the application and can
# be set here (measured in meters):
current_data.user["drytol"] = 1.e-3
plotdata.beforeframe = set_drytol
#-----------------------------------------
# Figure for pcolor plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='pcolor', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.title = 'Surface'
plotaxes.scaled = True
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = geoplot.surface
plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmin = -0.1
plotitem.pcolor_cmax = 0.1
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 1
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = geoplot.land
plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 1
plotaxes.xlimits = [-2, 2]
plotaxes.ylimits = [-2, 2]
# Add contour lines of bathymetry:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = linspace(-.1, 0.5, 20)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [1]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
plotitem.show = True
#-----------------------------------------
# Figure for cross section
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='cross-section', figno=1)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [-2, 2]
plotaxes.ylimits = [-0.15, 0.3]
plotaxes.title = 'Cross section at y=0'
def plot_topo_xsec(current_data):
from pylab import plot, cos, sin, where, legend, nan
t = current_data.t
x = linspace(-2, 2, 201)
y = 0.
B = h0 * (x**2 + y**2) / a**2 - h0
eta1 = sigma * h0 / a**2 * (2. * x * cos(omega * t) +
2. * y * sin(omega * t) - sigma)
etatrue = where(eta1 > B, eta1, nan)
plot(x, etatrue, 'r', label="true solution", linewidth=2)
plot(x, B, 'g', label="bathymetry")
## plot([0],[-1],'kx',label="Level 1") # shouldn't show up in plots,
## plot([0],[-1],'bo',label="Level 2") # but will produced desired legend
plot([0], [-1], 'bo', label="Computed") ## need to fix plotstyle
legend()
plotaxes.afteraxes = plot_topo_xsec
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
def xsec(current_data):
# Return x value and surface eta at this point, along y=0
from pylab import where, ravel
x = current_data.x
y = ravel(current_data.y)
dy = current_data.dy
q = current_data.q
ij = where((y <= dy / 2.) & (y > -dy / 2.))
x_slice = ravel(x)[ij]
eta_slice = ravel(q[3, :, :])[ij]
return x_slice, eta_slice
plotitem.map_2d_to_1d = xsec
plotitem.plotstyle = 'kx' ## need to be able to set amr_plotstyle
plotitem.kwargs = {'markersize': 3}
plotitem.amr_show = [1] # plot on all levels
#-----------------------------------------
# Figure for grids alone
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='grids', figno=2)
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [-2, 2]
plotaxes.ylimits = [-2, 2]
plotaxes.title = 'grids'
plotaxes.scaled = True
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_patch')
plotitem.amr_patch_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.amr_celledges_show = [1, 1, 0]
plotitem.amr_patchedges_show = [1]
#-----------------------------------------
# Parameters used only when creating html and/or latex hardcopy
# e.g., via pyclaw.plotters.frametools.printframes:
plotdata.printfigs = True # print figures
plotdata.print_format = 'png' # file format
plotdata.print_framenos = 'all' # list of frames to print
plotdata.print_gaugenos = [] # list of gauges to print
plotdata.print_fignos = 'all' # list of figures to print
plotdata.html = True # create html files of plots?
plotdata.html_homelink = '../README.html' # pointer for top of index
plotdata.latex = True # create latex file of plots?
plotdata.latex_figsperline = 2 # layout of plots
plotdata.latex_framesperline = 1 # layout of plots
plotdata.latex_makepdf = False # also run pdflatex?
plotdata.parallel = True # make multiple frame png's at once
return plotdata
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.
"""
import os
import numpy as np
import matplotlib.pyplot as plt
from clawpack.visclaw import geoplot, gaugetools, colormaps
import clawpack.clawutil.data as clawutil
import clawpack.amrclaw.data as amrclaw
import clawpack.geoclaw.data
import clawpack.geoclaw.multilayer.plot as ml_plot
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
from numpy import linspace
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.save_frames = False
# Load data from output
clawdata = clawutil.ClawInputData(2)
clawdata.read(os.path.join(plotdata.outdir,'claw.data'))
amrdata = amrclaw.AmrclawInputData(clawdata)
amrdata.read(os.path.join(plotdata.outdir,'amr.data'))
geodata = clawpack.geoclaw.data.GeoClawData()
geodata.read(os.path.join(plotdata.outdir,'geoclaw.data'))
multilayer_data = clawpack.geoclaw.data.MultilayerData()
multilayer_data.read(os.path.join(plotdata.outdir,'multilayer.data'))
# 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)
# ========================================================================
# Generic helper functions
# ========================================================================
def pcolor_afteraxes(current_data):
# bathy_ref_lines(current_data)
gauge_locations(current_data)
def contour_afteraxes(current_data):
# gauge_locations(current_data)
# m_to_km_labels()
plt.hold(True)
pos = -80.0 * (23e3 / 180) + 500e3 - 5e3
plt.plot([pos,pos],[-300e3,300e3],'b',[pos-5e3,pos-5e3],[-300e3,300e3],'y')
plt.hold(False)
wind_contours(current_data)
bathy_ref_lines(current_data)
def profile_afteraxes(current_data):
pass
def gauge_locations(current_data,gaugenos='all'):
plt.hold(True)
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos=gaugenos, format_string='kx', add_labels=True)
plt.hold(False)
# ========================================================================
# Axis limits
# xlimits = [amrdata.xlower,amrdata.xupper]
xlimits = [-100.0, 100.0]
# ylimits = [amrdata.ylower,amrdata.yupper]
ylimits = [-100.0, 100.0]
eta = [multilayer_data.eta[0],multilayer_data.eta[1]]
top_surface_limits = [eta[0]-10,eta[0]+10]
internal_surface_limits = [eta[1]-5,eta[1]+5]
depth_limits = [0.0, 0.4]
top_speed_limits = [0.0,0.1]
internal_speed_limits = [0.0,0.03]
# ========================================================================
# Surface Elevations
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='Surface', figno=0)
plotfigure.show = True
plotfigure.kwargs = {'figsize':(14,4)}
# Top surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Top Surface'
plotaxes.axescmd = 'subplot(1,2,1)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
ml_plot.add_inundation(plotaxes, 1, bounds=depth_limits)
ml_plot.add_surface_elevation(plotaxes,1,bounds=top_surface_limits)
ml_plot.add_land(plotaxes, 1)
# Bottom surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Internal Surface'
plotaxes.axescmd = 'subplot(1,2,2)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
ml_plot.add_inundation(plotaxes, 2, bounds=depth_limits)
ml_plot.add_surface_elevation(plotaxes,2,bounds=internal_surface_limits)
ml_plot.add_colorbar = True
ml_plot.add_land(plotaxes, 2)
# ========================================================================
# Figure for cross section
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='cross-section', figno=4)
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.title = 'Cross section at y=0'
ml_plot.add_cross_section(plotaxes, 1)
ml_plot.add_cross_section(plotaxes, 2)
ml_plot.add_land_cross_section(plotaxes)
# ========================================================================
# Water Speed
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='speed', figno=1)
plotfigure.show = False
plotfigure.kwargs = {'figsize':(14,4)}
# Top layer speed
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents - Top Layer'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(1,2,1)'
ml_plot.add_speed(plotaxes,1,bounds=top_speed_limits)
ml_plot.add_land(plotaxes, 1)
# Bottom layer speed
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents - Bottom Layer'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(1,2,2)'
ml_plot.add_speed(plotaxes,2,bounds=internal_speed_limits)
ml_plot.add_land(plotaxes, 2)
# Individual components
plotfigure = plotdata.new_plotfigure(name='speed_components',figno=401)
plotfigure.show = False
plotfigure.kwargs = {'figsize':(14,14)}
# Top layer
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "X-Velocity - Top Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,1)'
ml_plot.add_x_velocity(plotaxes,1)
ml_plot.add_land(plotaxes, 1)
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Y-Velocity - Top Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,2)'
ml_plot.add_y_velocity(plotaxes,1)
ml_plot.add_land(plotaxes, 1)
# Bottom layer
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "X-Velocity - Bottom Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,3)'
ml_plot.add_x_velocity(plotaxes,2)
ml_plot.add_land(plotaxes, 2)
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Y-Velocity - Bottom Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,4)'
ml_plot.add_y_velocity(plotaxes,2)
ml_plot.add_land(plotaxes, 2)
#-----------------------------------------
# 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')
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)')
#-----------------------------------------
# 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,
bathy_location=0.15,
bathy_angle=0.0,
bathy_left=-1.0,
bathy_right=-0.2):
"""Setup the plotting data objects.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
returns plotdata object
"""
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
# Load data from output
clawdata = clawutil.ClawInputData(2)
clawdata.read(os.path.join(plotdata.outdir, 'claw.data'))
multilayer_data = clawpack.geoclaw.data.MultilayerData()
multilayer_data.read(os.path.join(plotdata.outdir, 'multilayer.data'))
def transform_c2p(x, y, x0, y0, theta):
return ((x + x0) * np.cos(theta) - (y + y0) * np.sin(theta),
(x + x0) * np.sin(theta) + (y + y0) * np.cos(theta))
def transform_p2c(x, y, x0, y0, theta):
return (x * np.cos(theta) + y * np.sin(theta) - x0,
-x * np.sin(theta) + y * np.cos(theta) - y0)
# Setup bathymetry reference lines
with open(os.path.join(plotdata.outdir, "bathy_geometry.data"), 'r') \
as bathy_geometry_file:
bathy_location = float(bathy_geometry_file.readline())
bathy_angle = float(bathy_geometry_file.readline())
x = [0.0, 0.0]
y = [0.0, 1.0]
x1, y1 = transform_c2p(x[0], y[0], bathy_location, 0.0, bathy_angle)
x2, y2 = transform_c2p(x[1], y[1], bathy_location, 0.0, bathy_angle)
if abs(x1 - x2) < 10**-3:
x = [x1, x1]
y = [clawdata.lower[1], clawdata.upper[1]]
else:
m = (y1 - y2) / (x1 - x2)
x[0] = (clawdata.lower[1] - y1) / m + x1
y[0] = clawdata.lower[1]
x[1] = (clawdata.upper[1] - y1) / m + x1
y[1] = clawdata.upper[1]
ref_lines = [((x[0], y[0]), (x[1], y[1]))]
plotdata.clearfigures()
plotdata.save_frames = False
# ========================================================================
# Generic helper functions
def pcolor_afteraxes(current_data):
bathy_ref_lines(current_data)
def contour_afteraxes(current_data):
axes = plt.gca()
pos = -80.0 * (23e3 / 180) + 500e3 - 5e3
axes.plot([pos, pos], [-300e3, 300e3], 'b', [pos - 5e3, pos - 5e3],
[-300e3, 300e3], 'y')
wind_contours(current_data)
bathy_ref_lines(current_data)
def profile_afteraxes(current_data):
pass
def bathy_ref_lines(current_data):
axes = plt.gca()
for ref_line in ref_lines:
x1 = ref_line[0][0]
y1 = ref_line[0][1]
x2 = ref_line[1][0]
y2 = ref_line[1][1]
axes.plot([x1, x2], [y1, y2], 'y--', linewidth=1)
# ========================================================================
# Axis limits
xlimits = [-0.5, 0.5]
ylimits = [-0.5, 0.5]
eta = [multilayer_data.eta[0], multilayer_data.eta[1]]
top_surface_limits = [eta[0] - 0.03, eta[0] + 0.03]
internal_surface_limits = [eta[1] - 0.015, eta[1] + 0.015]
top_speed_limits = [0.0, 0.1]
internal_speed_limits = [0.0, 0.03]
# ========================================================================
# Surface Elevations
plotfigure = plotdata.new_plotfigure(name='Surface')
plotfigure.show = True
plotfigure.kwargs = {'figsize': (14, 4)}
# Top surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Top Surface'
plotaxes.axescmd = 'subplot(1, 2, 1)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
ml_plot.add_surface_elevation(plotaxes, 1, bounds=top_surface_limits)
# ml_plot.add_surface_elevation(plotaxes,1,bounds=[-0.06,0.06])
# ml_plot.add_surface_elevation(plotaxes,1)
ml_plot.add_land(plotaxes, 1)
# Bottom surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Internal Surface'
plotaxes.axescmd = 'subplot(1,2,2)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
# ml_plot.add_surface_elevation(plotaxes,2,bounds=[-300-0.5,-300+0.5])
ml_plot.add_surface_elevation(plotaxes, 2, bounds=internal_surface_limits)
# ml_plot.add_surface_elevation(plotaxes,2)
ml_plot.add_land(plotaxes, 2)
# ========================================================================
# Depths
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='Depths', figno=42)
plotfigure.show = False
plotfigure.kwargs = {'figsize': (14, 4)}
# Top surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Top Layer Depth'
plotaxes.axescmd = 'subplot(1,2,1)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
ml_plot.add_layer_depth(plotaxes, 1, bounds=[-0.1, 1.1])
ml_plot.add_land(plotaxes, 1)
# Bottom surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Bottom Layer Depth'
plotaxes.axescmd = 'subplot(1,2,2)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
ml_plot.add_layer_depth(plotaxes, 2, bounds=[-0.1, 0.7])
ml_plot.add_land(plotaxes, 2)
# ========================================================================
# Water Speed
plotfigure = plotdata.new_plotfigure(name='speed')
plotfigure.show = True
plotfigure.kwargs = {'figsize': (14, 4)}
# Top layer speed
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents - Top Layer'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(1, 2, 1)'
plotaxes.afteraxes = pcolor_afteraxes
ml_plot.add_speed(plotaxes, 1, bounds=top_speed_limits)
ml_plot.add_land(plotaxes, 1)
# Bottom layer speed
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents - Bottom Layer'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(1,2,2)'
plotaxes.afteraxes = pcolor_afteraxes
# add_speed(plotaxes,2,bounds=[0.0,1e-10])
ml_plot.add_speed(plotaxes, 2, bounds=internal_speed_limits)
# add_speed(plotaxes,2)
ml_plot.add_land(plotaxes, 2)
# Individual components
plotfigure = plotdata.new_plotfigure(name='speed_components', figno=401)
plotfigure.show = False
plotfigure.kwargs = {'figsize': (14, 14)}
# Top layer
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "X-Velocity - Top Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,1)'
plotaxes.afteraxes = pcolor_afteraxes
# add_x_velocity(plotaxes,1,bounds=[-1e-10,1e-10])
ml_plot.add_x_velocity(plotaxes, 1)
ml_plot.add_land(plotaxes, 1)
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Y-Velocity - Top Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,2)'
plotaxes.afteraxes = pcolor_afteraxes
# add_y_velocity(plotaxes,1,bounds=[-0.000125,0.000125])
ml_plot.add_y_velocity(plotaxes, 1)
ml_plot.add_land(plotaxes, 1)
# Bottom layer
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "X-Velocity - Bottom Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,3)'
plotaxes.afteraxes = pcolor_afteraxes
# add_x_velocity(plotaxes,2,bounds=[-1e-10,1e-10])
ml_plot.add_x_velocity(plotaxes, 2)
ml_plot.add_land(plotaxes, 2)
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Y-Velocity - Bottom Layer"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.axescmd = 'subplot(2,2,4)'
plotaxes.afteraxes = pcolor_afteraxes
# add_y_velocity(plotaxes,2,bounds=[-0.8e-6,.8e-6])
ml_plot.add_y_velocity(plotaxes, 2)
ml_plot.add_land(plotaxes, 2)
# ========================================================================
# Profile Plots
# Note that these are not currently plotted by default - set
# `plotfigure.show = True` is you want this to be plotted
plotfigure = plotdata.new_plotfigure(name='profile')
plotfigure.show = False
# Top surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = xlimits
plotaxes.ylimits = [-1.1, 0.1]
plotaxes.title = "Profile of depth"
plotaxes.afteraxes = profile_afteraxes
slice_index = 30
# Internal surface
def bathy_profile(current_data):
return current_data.x[:, slice_index], b(current_data)[:, slice_index]
def lower_surface(current_data):
if multilayer_data.init_type == 2:
return current_data.x[:, slice_index], \
eta2(current_data)[:, slice_index]
elif multilayer_data.init_type == 6:
return current_data.y[slice_index, :], \
eta2(current_data)[slice_index, :]
def upper_surface(current_data):
if multilayer_data.init_type == 2:
return current_data.x[:, slice_index], \
eta1(current_data)[:, slice_index]
elif multilayer_data.init_type == 6:
return current_data.y[slice_index, :], \
eta1(current_data)[slice_index, :]
def top_speed(current_data):
if multilayer_data.init_type == 2:
return current_data.x[:, slice_index], \
water_u1(current_data)[:, slice_index]
elif multilayer_data.init_type == 6:
return current_data.y[slice_index, :], \
water_u1(current_data)[slice_index, :]
def bottom_speed(current_data):
if multilayer_data.init_type == 2:
return current_data.x[:, slice_index], \
water_u2(current_data)[:, slice_index]
elif multilayer_data.init_type == 6:
return current_data.y[slice_index, :], \
water_u2(current_data)[slice_index, :]
# Bathy
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.map_2d_to_1d = bathy_profile
plotitem.plot_var = 0
plotitem.amr_plotstyle = ['-', '+', 'x']
plotitem.color = 'k'
plotitem.show = True
# Internal Interface
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.map_2d_to_1d = lower_surface
plotitem.plot_var = 7
plotitem.amr_plotstyle = ['-', '+', 'x']
plotitem.color = 'b'
plotitem.show = True
# Upper Interface
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.map_2d_to_1d = upper_surface
plotitem.plot_var = 6
plotitem.amr_plotstyle = ['-', '+', 'x']
plotitem.color = (0.2, 0.8, 1.0)
plotitem.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Y-Velocity'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
# Water
# plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
# # plotitem.plot_var = geoplot.surface
# plotitem.plot_var = water_v
# plotitem.pcolor_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
# # plotitem.pcolor_cmin = -1.e-10
# # plotitem.pcolor_cmax = 1.e-10
# # plotitem.pcolor_cmin = -2.5 # -3.0
# # plotitem.pcolor_cmax = 2.5 # 3.0
# plotitem.add_colorbar = True
# plotitem.amr_celledges_show = [0,0,0]
# plotitem.amr_patchedges_show = [1,1,1]
# Land
ml_plot.add_land(plotaxes, 1)
# ========================================================================
# Contour plot for surface
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='contour_surface', figno=15)
plotfigure.show = False
plotfigure.kwargs = {'figsize': (14, 4)}
# Set up for axes in this figure:
# Top Surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Top Surface'
plotaxes.axescmd = 'subplot(1,2,1)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = contour_afteraxes
ml_plot.add_surface_elevation(plotaxes,
plot_type='contour',
surface=1,
bounds=[-2.5, -1.5, -0.5, 0.5, 1.5, 2.5])
ml_plot.add_land(plotaxes, 1, plot_type='contour')
# Internal Surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Internal Surface'
plotaxes.axescmd = 'subplot(1,2,2)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = contour_afteraxes
ml_plot.add_surface_elevation(plotaxes,
plot_type='contour',
surface=2,
bounds=[-2.5, -1.5, -0.5, 0.5, 1.5, 2.5])
ml_plot.add_land(plotaxes, 2, plot_type='contour')
# ========================================================================
# Contour plot for speed
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='contour_speed', figno=16)
plotfigure.show = False
plotfigure.kwargs = {'figsize': (14, 4)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Current'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = contour_afteraxes
# Surface
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = ml_plot.water_speed_depth_ave
plotitem.kwargs = {'linewidths': 1}
# plotitem.contour_levels = [1.0,2.0,3.0,4.0,5.0,6.0]
plotitem.contour_levels = [0.5, 1.5, 3, 4.5, 6.0]
plotitem.amr_contour_show = [1, 1, 1]
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.amr_patchedges_show = [1, 1, 1]
plotitem.amr_contour_colors = 'k'
# plotitem.amr_contour_colors = ['r','k','b'] # color on each level
# plotitem.amr_grid_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.show = True
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.land
plotitem.contour_nlevels = 40
plotitem.contour_min = 0.0
plotitem.contour_max = 100.0
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.amr_patch_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.amr_celledges_show = 0
plotitem.amr_patchedges_show = 0
plotitem.show = True
# ========================================================================
# Grid Cells
# ========================================================================
# 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 = xlimits
plotaxes.ylimits = ylimits
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']
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.amr_patchedges_show = [1, 1, 1]
# ========================================================================
# Vorticity Plot
# ========================================================================
# plotfigure = plotdata.new_plotfigure(name='vorticity',figno=17)
# plotfigure.show = False
# plotaxes = plotfigure.new_plotaxes()
# plotaxes.title = "Vorticity"
# plotaxes.scaled = True
# plotaxes.xlimits = xlimits
# plotaxes.ylimits = ylimits
# plotaxes.afteraxes = pcolor_afteraxes
#
# # Vorticity
# plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
# plotitem.plot_var = 9
# plotitem.imshow_cmap = plt.get_cmap('PRGn')
# # plotitem.pcolor_cmap = plt.get_cmap('PuBu')
# # plotitem.pcolor_cmin = 0.0
# # plotitem.pcolor_cmax = 6.0
# plotitem.imshow_cmin = -1.e-2
# plotitem.imshow_cmax = 1.e-2
# plotitem.add_colorbar = True
# plotitem.amr_celledges_show = [0,0,0]
# 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 = 80.0
# plotitem.add_colorbar = False
# plotitem.amr_celledges_show = [0,0,0]
# ========================================================================
# Figures for gauges
# Top
plotfigure = plotdata.new_plotfigure(name='Surface & topo',
type='each_gauge',
figno=301)
plotfigure.show = True
plotfigure.clf_each_gauge = True
plotfigure.kwargs = {'figsize': (14, 4)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(1, 2, 1)'
plotaxes.xlimits = [0.0, 1.0]
plotaxes.ylimits = top_surface_limits
plotaxes.title = 'Top Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 6
plotitem.plotstyle = 'b-'
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(1, 2, 2)'
plotaxes.xlimits = [0.0, 1.0]
plotaxes.ylimits = internal_surface_limits
plotaxes.title = 'Bottom Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 7
plotitem.plotstyle = 'b-'
# =========================================================================
# Other plots
# Gauge Locations - Enable to see where gauges are located
def locations_afteraxes(current_data, gaugenos='all'):
gaugetools.plot_gauge_locations(current_data.plotdata,
gaugenos=gaugenos,
format_string='kx',
add_labels=True)
pcolor_afteraxes(current_data)
plotfigure = plotdata.new_plotfigure(name='Gauge Locations')
plotfigure.show = False
plotfigure.kwargs = {'figsize': (14, 4)}
# Top surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Top Surface'
plotaxes.axescmd = 'subplot(1, 2, 1)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = locations_afteraxes
ml_plot.add_surface_elevation(plotaxes, 1, bounds=top_surface_limits)
ml_plot.add_land(plotaxes, 1)
# Bottom surface
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Internal Surface'
plotaxes.axescmd = 'subplot(1, 2, 2)'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = locations_afteraxes
ml_plot.add_surface_elevation(plotaxes, 2, bounds=internal_surface_limits)
ml_plot.add_land(plotaxes, 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_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 # 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 clawpack.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 pressure
# -------------------
plotfigure = plotdata.new_plotfigure(name='Pressure', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
plotaxes.ylimits = 'auto'
plotaxes.title = 'Pressure'
plotaxes.scaled = True # so aspect ratio is 1
plotaxes.afteraxes = addgauges
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = 0
plotitem.pcolor_cmap = colormaps.blue_yellow_red
plotitem.add_colorbar = True
plotitem.show = True # show on plot?
plotitem.pcolor_cmin = -2.0
plotitem.pcolor_cmax = 2.0
plotitem.amr_patchedges_show = [1,1,1]
plotitem.amr_celledges_show = [1,0,0]
# Figure for scatter plot
# -----------------------
plotfigure = plotdata.new_plotfigure(name='scatter', figno=3)
plotfigure.show = (qref_dir is not None)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0,1.5]
plotaxes.ylimits = [-2.,4.]
plotaxes.title = 'Scatter plot'
# Set up for item on these axes: scatter of 2d data
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
def p_vs_r(current_data):
# Return radius of each grid cell and p value in the cell
from pylab import sqrt
x = current_data.x
y = current_data.y
r = sqrt(x**2 + y**2)
q = current_data.q
p = q[0,:,:]
return r,p
plotitem.map_2d_to_1d = p_vs_r
plotitem.plot_var = 0
plotitem.plotstyle = 'o'
plotitem.color = 'b'
plotitem.show = True # show on plot?
# Set up for item on these axes: 1d reference solution
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.outdir = qref_dir
plotitem.plot_var = 0
plotitem.plotstyle = '-'
plotitem.color = 'r'
plotitem.kwargs = {'linewidth': 2}
plotitem.show = True # show on plot?
plotaxes.afteraxes = "import pylab; pylab.legend(('2d data', '1d reference solution'))"
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='q', figno=300, \
type='each_gauge')
plotfigure.clf_each_gauge = True
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
plotaxes.ylimits = 'auto'
plotaxes.title = 'Pressure'
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 0
plotitem.plotstyle = 'b-'
# Parameters used only when creating html and/or latex hardcopy
# e.g., via clawpack.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):
#--------------------------
"""
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
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
def set_drytol(current_data):
# The drytol parameter is used in masking land and water and
# affects what color map is used for cells with small water depth h.
# The cell will be plotted as dry if h < drytol.
# The best value to use often depends on the application and can
# be set here (measured in meters):
current_data.user["drytol"] = 1.e-3
plotdata.beforeframe = set_drytol
#-----------------------------------------
# Figure for pcolor plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='pcolor', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.title = 'Surface'
plotaxes.scaled = True
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = geoplot.surface
plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmin = -0.1
plotitem.pcolor_cmax = 0.1
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 1
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = geoplot.land
plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0,0,0]
plotitem.patchedges_show = 1
plotaxes.xlimits = [-2,2]
plotaxes.ylimits = [-2,2]
# Add contour lines of bathymetry:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = linspace(-.1, 0.5, 20)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [1]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
plotitem.show = True
#-----------------------------------------
# Figure for cross section
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='cross-section', figno=1)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [-2,2]
plotaxes.ylimits = [-0.15,0.3]
plotaxes.title = 'Cross section at y=0'
def plot_topo_xsec(current_data):
from pylab import plot, cos,sin,where,legend,nan
t = current_data.t
x = linspace(-2,2,201)
y = 0.
B = h0*(x**2 + y**2)/a**2 - h0
eta1 = sigma*h0/a**2 * (2.*x*cos(omega*t) + 2.*y*sin(omega*t) -sigma)
etatrue = where(eta1>B, eta1, nan)
plot(x, etatrue, 'r', label="true solution", linewidth=2)
plot(x, B, 'g', label="bathymetry")
## plot([0],[-1],'kx',label="Level 1") # shouldn't show up in plots,
## plot([0],[-1],'bo',label="Level 2") # but will produced desired legend
plot([0],[-1],'bo',label="Computed") ## need to fix plotstyle
legend()
plotaxes.afteraxes = plot_topo_xsec
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
def xsec(current_data):
# Return x value and surface eta at this point, along y=0
from pylab import find,ravel
x = current_data.x
y = current_data.y
dy = current_data.dy
q = current_data.q
ij = find((y <= dy/2.) & (y > -dy/2.))
x_slice = ravel(x)[ij]
eta_slice = ravel(q[3,:,:])[ij]
return x_slice, eta_slice
plotitem.map_2d_to_1d = xsec
plotitem.plotstyle = 'kx' ## need to be able to set amr_plotstyle
plotitem.kwargs = {'markersize':3}
plotitem.amr_show = [1] # plot on all levels
#-----------------------------------------
# Figure for grids alone
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='grids', figno=2)
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [-2,2]
plotaxes.ylimits = [-2,2]
plotaxes.title = 'grids'
plotaxes.scaled = True
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_patch')
plotitem.amr_patch_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.amr_celledges_show = [1,1,0]
plotitem.amr_patchedges_show = [1]
#-----------------------------------------
# Parameters used only when creating html and/or latex hardcopy
# e.g., via pyclaw.plotters.frametools.printframes:
plotdata.printfigs = True # print figures
plotdata.print_format = 'png' # file format
plotdata.print_framenos = 'all' # list of frames to print
plotdata.print_gaugenos = [] # list of gauges to print
plotdata.print_fignos = 'all' # list of figures to print
plotdata.html = True # create html files of plots?
plotdata.html_homelink = '../README.html' # pointer for top of index
plotdata.latex = True # create latex file of plots?
plotdata.latex_figsperline = 2 # layout of plots
plotdata.latex_framesperline = 1 # layout of plots
plotdata.latex_makepdf = False # also run pdflatex?
plotdata.parallel = True # make multiple frame png's at once
return plotdata
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
import math
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
def speed(current_data):
from numpy import ma, where, sqrt, log10
drytol = 1e-3
q = current_data.q
h = q[0, :, :]
hu = q[1, :, :]
hv = q[2, :, :]
u = where(h > 0.0, hu / h, 0.)
v = where(h > 0.0, hv / h, 0.)
speed = sqrt(u**2 + v**2)
return speed
def stress(current_data):
from numpy import ma, where, sqrt, log10
q = current_data.q
h = q[0, :, :]
hu = q[1, :, :]
hv = q[2, :, :]
u = where(h > 0.0, hu / h, 0.)
v = where(h > 0.0, hv / h, 0.)
speed = np.sqrt(u**2 + v**2) #Speed calc, same as above
n = 0.06 #Manning's n
g = 9.8 #gravity
cf = where(
h > 0.0, (g * n**2) / (h**(1. / 3)), 0.
) #calculate friction coefficient, DONT FORGET THE F*****G PERIOD YOU IDIOT (mike)
stress = 1000 * cf * (speed**2)
return stress
#####-----------------------------------------
# Gorge depth
#-----------------------------------------
#
plotfigure = plotdata.new_plotfigure(name='Gorgetesting_depth', figno=21)
plotfigure.show = False
plotfigure.kwargs = {'figsize': [15, 15]}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('Depth')
#plotaxes.title = 'Water Surface'
plotaxes.scaled = True
plotaxes.xlimits = [95.0, 95.45]
plotaxes.ylimits = [29.5, 30.0]
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.depth #variable to plot
plotitem.pcolor_cmap = geoplot.custom_river
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 300
plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_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.blank
plotitem.pcolor_cmap = geoplot.bw_colormap
plotitem.pcolor_cmin = 2000.0
plotitem.pcolor_cmax = 6000.0
#plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_show = [0]
#plotaxes.afteraxes = addgauges
#####-----------------------------------------
# Gorge speed
#-----------------------------------------
#
plotfigure = plotdata.new_plotfigure(name='Gorgetesting_speed', figno=22)
plotfigure.show = False
plotfigure.kwargs = {'figsize': [15, 15]}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('Speed')
#plotaxes.title = 'Water Surface'
plotaxes.scaled = True
plotaxes.xlimits = [95.0, 95.45]
plotaxes.ylimits = [29.5, 30.0]
# speed
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = speed
plotitem.pcolor_cmap = geoplot.custom_river
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 80
plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_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.blank
plotitem.pcolor_cmap = geoplot.bw_colormap
plotitem.pcolor_cmin = 2000.0
plotitem.pcolor_cmax = 6000.0
#plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_show = [0]
#plotaxes.afteraxes = addgauges
#####-----------------------------------------
# Gorge stress
#-----------------------------------------
#
plotfigure = plotdata.new_plotfigure(name='Gorgetesting_stress', figno=23)
plotfigure.show = False
plotfigure.kwargs = {'figsize': [15, 15]}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('Stress')
#plotaxes.title = 'Water Surface'
plotaxes.scaled = True
plotaxes.xlimits = [95.0, 95.45]
plotaxes.ylimits = [29.5, 30.0]
# stress
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = stress
plotitem.pcolor_cmap = geoplot.custom_river
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 30000 #make this reasonable max stress
plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_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.blank
plotitem.pcolor_cmap = geoplot.bw_colormap
plotitem.pcolor_cmin = 2000.0
plotitem.pcolor_cmax = 6000.0
#plotitem.add_colorbar = True #turn off for making movies
plotitem.amr_celledges_show = [0]
#-----------------------------------------
# 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 = np.arange(0,5,1) # list of frames to print
#plotdata.print_framenos = [1,2,3,4,5] #frame is a timestep, so this is the way
#plotdata.print_gaugenos = [1,2,3,4] # list of gauges to print
plotdata.print_fignos = 'all' # list of figures to print
plotdata.html = False # 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 = 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 clawpack.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 density - pcolor
plotfigure = plotdata.new_plotfigure(name='Density', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0,1]
plotaxes.ylimits = [0,1]
plotaxes.title = 'Density'
plotaxes.scaled = True
plotaxes.afteraxes = addgauges
# 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.
plotitem.pcolor_cmax = 2.
plotitem.add_colorbar = True
plotitem.amr_patchedges_show = [0]
plotitem.amr_celledges_show = [0]
# Figure for density - Schlieren
plotfigure = plotdata.new_plotfigure(name='Schlieren', figno=1)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0,1]
plotaxes.ylimits = [0,1]
plotaxes.title = 'Density'
plotaxes.scaled = True # so aspect ratio is 1
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_schlieren')
plotitem.schlieren_cmin = 0.0
plotitem.schlieren_cmax = 1.0
plotitem.plot_var = 0
plotitem.add_colorbar = False
# 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']
plotitem.amr_celledges_show = [1,0]
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 = [0,1]
plotaxes.ylimits = [0,1]
plotaxes.title = 'Density'
# Plot q as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 0
plotitem.plotstyle = 'b-'
# Parameters used only when creating html and/or latex hardcopy
# e.g., via clawpack.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):
#--------------------------
"""
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 bay import Bay
mobile = Bay('bay.info')
if plotdata is None:
from clawpack.visclaw.data import ClawPlotData
plotdata = ClawPlotData()
plotdata.clearfigures() # clear any old figures,axes,items data
def set_drytol(current_data):
# The drytol parameter is used in masking land and water and
# affects what color map is used for cells with small water depth h.
# The cell will be plotted as dry if h < drytol.
# The best value to use often depends on the application and can
# be set here (measured in meters):
current_data.user["drytol"] = 1.e-3
plotdata.beforeframe = set_drytol
#-----------------------------------------
# Figure for pcolor plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='pcolor', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.title = 'Surface'
plotaxes.scaled = True
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = geoplot.surface
plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.pcolor_cmin = -0.5
plotitem.pcolor_cmax = 0.5
plotitem.add_colorbar = True
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 1
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.plot_var = geoplot.land
plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = mobile.z0
plotitem.pcolor_cmax = mobile.z_r
plotitem.add_colorbar = False
plotitem.amr_celledges_show = [0, 0, 0]
plotitem.patchedges_show = 1
plotaxes.xlimits = [mobile.x_o1, mobile.x_o2]
plotaxes.ylimits = [mobile.y0, mobile.y_r]
# Add contour lines of bathymetry:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = linspace(mobile.z0, mobile.z_r, 10)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [1]
plotitem.celledges_show = 0
plotitem.patchedges_show = 0
plotitem.show = True
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface & topo',
figno=1,
type='each_gauge')
plotfigure.clf_each_gauge = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
plotaxes.ylimits = [-1.5, 1.5]
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 = '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