def __init__(self, run_number=1, wave_tolerance=1.0, deep_depth=300.0):
super(SweepJob, self).__init__(time=720)
self.omp_num_threads = 16
self.run_number = run_number
self.type = 'sweep'
self.name = 'wave_deep_01'
self.prefix = 'run_%s_wave_%s_deep_%s' % (self.run_number,
wave_tolerance, deep_depth)
self.executable = 'xgeoclaw'
self.group = 'yetiapam'
import setrun
self.rundata = setrun.setrun()
# incorporate storm parameters
self.rundata.add_data(surge.SurgeData(), 'stormdata')
setrun.set_storm(self.rundata)
self.rundata.add_data(surge.FrictionData(), 'frictiondata')
setrun.set_friction(self.rundata)
### modify setrun parameters here ###
refine_data = self.rundata.refinement_data
refine_data.wave_tolerance = wave_tolerance
refine_data.deep_depth = deep_depth
def __init__(self,
run_number=1,
wave_tolerance=1.0,
deep_depth=300.0,
speed_tolerance=False):
super(SweepJob, self).__init__(time=24 * 60, memory=15000)
self.omp_num_threads = 16
self.run_number = run_number
self.type = 'sweep'
if speed_tolerance:
self.name = 'wave_deep_speed_l5'
else:
self.name = 'wave_deep_no_speed_l5'
self.prefix = 'run_%s_wave_%s_deep_%s' % (self.run_number,
wave_tolerance, deep_depth)
self.executable = 'xgeoclaw'
self.group = 'yetiapam'
import setrun
self.rundata = setrun.setrun()
# incorporate storm parameters
self.rundata.add_data(surge.SurgeData(), 'stormdata')
setrun.set_storm(self.rundata)
self.rundata.add_data(surge.FrictionData(), 'frictiondata')
setrun.set_friction(self.rundata)
### modify setrun parameters here ###
refine_data = self.rundata.refinement_data
refine_data.wave_tolerance = wave_tolerance
refine_data.deep_depth = deep_depth
if not speed_tolerance:
refine_data.speed_tolerance = [999999
] #big number so it never triggers
amrdata = self.rundata.amrdata
amrdata.amr_levels_max = 5
def setplot(plotdata):
r"""Setplot function for surge plotting"""
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 = surgedata.SurgeData()
surge_data.read(os.path.join(plotdata.outdir, 'surge.data'))
friction_data = surgedata.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?
return plotdata
def set_friction(rundata):
data = rundata.frictiondata
# Variable friction
data.variable_friction = True
# Region based friction
# Entire domain
data.friction_regions.append([rundata.clawdata.lower,
rundata.clawdata.upper,
[np.infty,0.0,-np.infty],
[0.050, 0.025]])
return data
if __name__ == '__main__':
# Set up run-time parameters and write all data files.
import sys
if len(sys.argv) == 2:
rundata = setrun(sys.argv[1])
else:
rundata = setrun()
rundata.add_data(surge.SurgeData(),'stormdata')
set_storm(rundata)
rundata.add_data(surge.FrictionData(),'frictiondata')
set_friction(rundata)
rundata.write()
def setrun(claw_pkg='geoclaw'):
#------------------------------
"""
Define the parameters used for running Clawpack.
INPUT:
claw_pkg expected to be "geoclaw" for this setrun.
OUTPUT:
rundata - object of class ClawRunData
"""
assert claw_pkg.lower() == 'geoclaw', "Expected claw_pkg = 'geoclaw'"
ndim = 2
rundata = data.ClawRunData(claw_pkg, ndim)
#------------------------------------------------------------------
# Problem-specific parameters to be written to setprob.data:
#------------------------------------------------------------------
rundata.add_data(surge.FrictionData(), 'friction_data')
#------------------------------------------------------------------
# GeoClaw specific parameters:
#------------------------------------------------------------------
rundata = setgeo(rundata) # Defined below
#------------------------------------------------------------------
# Standard Clawpack parameters to be written to claw.data:
# (or to amr2ez.data for AMR)
#------------------------------------------------------------------
clawdata = rundata.clawdata # initialized when rundata instantiated
# Set single grid parameters first.
# See below for AMR parameters.
# ---------------
# Spatial domain:
# ---------------
# Number of space dimensions:
clawdata.num_dim = ndim
# Lower and upper edge of computational domain:
clawdata.lower[0] = 130.
clawdata.upper[0] = 170.
clawdata.lower[1] = 20.
clawdata.upper[1] = 60.
# Number of grid cells:
clawdata.num_cells[0] = 20
clawdata.num_cells[1] = 20
# ---------------
# Size of system:
# ---------------
# Number of equations in the system:
clawdata.num_eqn = 3
# Number of auxiliary variables in the aux array (initialized in setaux)
clawdata.num_aux = 4
# Index of aux array corresponding to capacity function, if there is one:
clawdata.capa_index = 2
# -------------
# Initial time:
# -------------
clawdata.t0 = 0.0
# Restart from checkpoint file of a previous run?
# Note: If restarting, you must also change the Makefile to set:
# RESTART = True
# If restarting, t0 above should be from original run, and the
# restart_file 'fort.chkNNNNN' specified below should be in
# the OUTDIR indicated in Makefile.
clawdata.restart = False # True to restart from prior results
clawdata.restart_file = 'fort.chk00036' # File to use for restart data
# -------------
# Output times:
#--------------
# Specify at what times the results should be written to fort.q files.
# Note that the time integration stops after the final output time.
# The solution at initial time t0 is always written in addition.
clawdata.output_style = 1
if clawdata.output_style == 1:
# Output nout frames at equally spaced times up to tfinal:
clawdata.num_output_times = 16
clawdata.tfinal = 4 * 3600.
clawdata.output_t0 = True
elif clawdata.output_style == 2:
# Specify a list of output times.
clawdata.output_times = list(numpy.arange(0,3600,360)) \
+ list(3600*numpy.arange(0,21,0.5))
elif clawdata.output_style == 3:
# Output every iout timesteps with a total of ntot time steps:
clawdata.output_step_interval = 2
clawdata.total_steps = 6
clawdata.output_t0 = True
clawdata.output_format = 'binary' # 'ascii' or 'netcdf'
clawdata.output_q_components = 'all' # need all
clawdata.output_aux_components = 'all' # eta=h+B is in q
clawdata.output_aux_onlyonce = False # output aux arrays each frame
# ---------------------------------------------------
# Verbosity of messages to screen during integration:
# ---------------------------------------------------
# The current t, dt, and cfl will be printed every time step
# at AMR levels <= verbosity. Set verbosity = 0 for no printing.
# (E.g. verbosity == 2 means print only on levels 1 and 2.)
clawdata.verbosity = 5
# --------------
# Time stepping:
# --------------
# if dt_variable==1: variable time steps used based on cfl_desired,
# if dt_variable==0: fixed time steps dt = dt_initial will always be used.
clawdata.dt_variable = True
# Initial time step for variable dt.
# If dt_variable==0 then dt=dt_initial for all steps:
clawdata.dt_initial = 0.016
# Max time step to be allowed if variable dt used:
clawdata.dt_max = 1e+99
# Desired Courant number if variable dt used, and max to allow without
# retaking step with a smaller dt:
clawdata.cfl_desired = 0.75
clawdata.cfl_max = 1.0
# Maximum number of time steps to allow between output times:
clawdata.steps_max = 5000
# ------------------
# Method to be used:
# ------------------
# Order of accuracy: 1 => Godunov, 2 => Lax-Wendroff plus limiters
clawdata.order = 2
# Use dimensional splitting? (not yet available for AMR)
clawdata.dimensional_split = 'unsplit'
# For unsplit method, transverse_waves can be
# 0 or 'none' ==> donor cell (only normal solver used)
# 1 or 'increment' ==> corner transport of waves
# 2 or 'all' ==> corner transport of 2nd order corrections too
clawdata.transverse_waves = 2
# Number of waves in the Riemann solution:
clawdata.num_waves = 3
# List of limiters to use for each wave family:
# Required: len(limiter) == num_waves
# Some options:
# 0 or 'none' ==> no limiter (Lax-Wendroff)
# 1 or 'minmod' ==> minmod
# 2 or 'superbee' ==> superbee
# 3 or 'mc' ==> MC limiter
# 4 or 'vanleer' ==> van Leer
clawdata.limiter = ['mc', 'mc', 'mc']
clawdata.use_fwaves = True # True ==> use f-wave version of algorithms
# Source terms splitting:
# src_split == 0 or 'none' ==> no source term (src routine never called)
# src_split == 1 or 'godunov' ==> Godunov (1st order) splitting used,
# src_split == 2 or 'strang' ==> Strang (2nd order) splitting used, not recommended.
clawdata.source_split = 'godunov'
# --------------------
# Boundary conditions:
# --------------------
# Number of ghost cells (usually 2)
clawdata.num_ghost = 2
# Choice of BCs at xlower and xupper:
# 0 => user specified (must modify bcN.f to use this option)
# 1 => extrapolation (non-reflecting outflow)
# 2 => periodic (must specify this at both boundaries)
# 3 => solid wall for systems where q(2) is normal velocity
clawdata.bc_lower[0] = 'extrap'
clawdata.bc_upper[0] = 'extrap'
clawdata.bc_lower[1] = 'extrap'
clawdata.bc_upper[1] = 'extrap'
# --------------
# Checkpointing:
# --------------
# Specify when checkpoint files should be created that can be
# used to restart a computation.
clawdata.checkpt_style = 0
if clawdata.checkpt_style == 0:
# Do not checkpoint at all
pass
elif clawdata.checkpt_style == 1:
# Checkpoint only at tfinal.
pass
elif clawdata.checkpt_style == 2:
# Specify a list of checkpoint times.
clawdata.checkpt_times = [0.1, 0.15]
elif clawdata.checkpt_style == 3:
# Checkpoint every checkpt_interval timesteps (on Level 1)
# and at the final time.
clawdata.checkpt_interval = 5
# ---------------
# AMR parameters:
# ---------------
amrdata = rundata.amrdata
# max number of refinement levels:
amrdata.amr_levels_max = 5
# List of refinement ratios at each level (length at least amr_levels_max-1)
amrdata.refinement_ratios_x = [4, 6, 5, 4]
amrdata.refinement_ratios_y = [4, 6, 5, 4]
amrdata.refinement_ratios_t = [1, 1, 1, 1]
# Specify type of each aux variable in amrdata.auxtype.
# This must be a list of length maux, each element of which is one of:
# 'center', 'capacity', 'xleft', or 'yleft' (see documentation).
amrdata.aux_type = ['center', 'capacity', 'yleft', 'center']
# Flag using refinement routine flag2refine rather than richardson error
amrdata.flag_richardson = False # use Richardson?
amrdata.flag2refine = True
# steps to take on each level L between regriddings of level L+1:
amrdata.regrid_interval = 3
# width of buffer zone around flagged points:
# (typically the same as regrid_interval so waves don't escape):
amrdata.regrid_buffer_width = 2
# clustering alg. cutoff for (# flagged pts) / (total # of cells refined)
# (closer to 1.0 => more small grids may be needed to cover flagged cells)
amrdata.clustering_cutoff = 0.700000
# print info about each regridding up to this level:
amrdata.verbosity_regrid = 0
# ----- For developers -----
# Toggle debugging print statements:
amrdata.dprint = False # print domain flags
amrdata.eprint = False # print err est flags
amrdata.edebug = False # even more err est flags
amrdata.gprint = False # grid bisection/clustering
amrdata.nprint = False # proper nesting output
amrdata.pprint = False # proj. of tagged points
amrdata.rprint = False # print regridding summary
amrdata.sprint = False # space/memory output
amrdata.tprint = True # time step reporting each level
amrdata.uprint = False # update/upbnd reporting
# More AMR parameters can be set -- see the defaults in pyclaw/data.py
# ---------------
# Regions:
# ---------------
rundata.regiondata.regions = []
# to specify regions of refinement append lines of the form
# [minlevel,maxlevel,t1,t2,x1,x2,y1,y2]
rundata.regiondata.regions.append([1, 3, 0., 1e9, 0, 360, -90, 90])
rundata.regiondata.regions.append([4, 5, 0., 1000., 140, 146, 35, 41])
# ---------------
# Gauges:
# ---------------
rundata.gaugedata.gauges = []
# for gauges append lines of the form [gaugeno, x, y, t1, t2]
rundata.gaugedata.gauges.append([21401, 152.583, 42.617, 1800., 1.e10])
rundata.gaugedata.gauges.append([21413, 152.1167, 30.5153, 1800., 1.e10])
# rundata.gaugedata.gauges.append([21414, 178.281, 48.938, 1800., 1.e10])
# rundata.gaugedata.gauges.append([21415, 171.849, 50.183, 1800., 1.e10])
# rundata.gaugedata.gauges.append([21416, 163.505, 48.052, 1800., 1.e10])
rundata.gaugedata.gauges.append([21418, 148.694, 38.711, 0., 1.e10])
rundata.gaugedata.gauges.append([21419, 155.736, 44.455, 1800., 1.e10])
# rundata.gaugedata.gauges.append([51407, 203.484, 19.642, 22000., 1.e10])
# rundata.gaugedata.gauges.append([52402, 154.116, 11.883, 10000., 1.e10])
rundata.gaugedata.gauges.append([1, 140.846971, 36.351141, 0.0, 1e10])
rundata.gaugedata.gauges.append([2, 141.115000, 37.420000, 0.0, 1e10])
rundata.gaugedata.gauges.append([3, 141.100000, 38.160000, 0.0, 1e10])
rundata.gaugedata.gauges.append([4, 141.328223, 38.325000, 0.0, 1e10])
rundata.gaugedata.gauges.append([5, 141.510000, 38.425000, 0.0, 1e10])
rundata.gaugedata.gauges.append([6, 141.525000, 38.575000, 0.0, 1e10])
rundata.gaugedata.gauges.append([7, 141.545000, 38.660000, 0.0, 1e10])
rundata.gaugedata.gauges.append([8, 141.730000, 38.880000, 0.0, 1e10])
rundata.gaugedata.gauges.append([9, 142.115489, 39.752675, 0.0, 1e10])
rundata.gaugedata.gauges.append([10, 142.140317, 39.752675, 0.0, 1e10])
rundata.gaugedata.gauges.append([11, 141.626825, 40.989026, 0.0, 1e10])
rundata.gaugedata.gauges.append([12, 141.133576, 42.133955, 0.0, 1e10])
rundata.gaugedata.gauges.append([13, 143.739806, 42.535828, 0.0, 1e10])
# =====================
# Set friction values
# =====================
set_friction(rundata)
return rundata
def setrun(claw_pkg='geoclaw'):
#------------------------------
"""
Define the parameters used for running Clawpack.
INPUT:
claw_pkg expected to be "geoclaw" for this setrun.
OUTPUT:
rundata - object of class ClawRunData
"""
from clawpack.clawutil import data
assert claw_pkg.lower() == 'geoclaw', "Expected claw_pkg = 'geoclaw'"
num_dim = 2
rundata = data.ClawRunData(claw_pkg, num_dim)
#------------------------------------------------------------------
# GeoClaw specific parameters:
#------------------------------------------------------------------
rundata = setgeo(rundata)
rundata.add_data(multilayer.MultilayerData(), 'multilayer_data')
set_multilayer(rundata)
rundata.add_data(surge.FrictionData(), 'frictiondata')
set_friction(rundata)
rundata.add_data(surge.SurgeData(), 'stormdata')
set_storm(rundata)
#------------------------------------------------------------------
# Standard Clawpack parameters to be written to claw.data:
# (or to amr2ez.data for AMR)
#------------------------------------------------------------------
clawdata = rundata.clawdata # initialized when rundata instantiated
# Set single grid parameters first.
# See below for AMR parameters.
# ---------------
# Spatial domain:
# ---------------
# Number of space dimensions:
clawdata.num_dim = num_dim
# Lower and upper edge of computational domain:
clawdata.lower[0] = -1 # west longitude
clawdata.upper[0] = 2.0 # east longitude
clawdata.lower[1] = -1.0 # south latitude
clawdata.upper[1] = 2.0 # north latitude
# Number of grid cells: Coarsest grid
clawdata.num_cells[0] = 150
clawdata.num_cells[1] = 150
# ---------------
# Size of system:
# ---------------
# Number of equations in the system:
clawdata.num_eqn = 6
# Number of auxiliary variables in the aux array (initialized in setaux)
clawdata.num_aux = 4 + rundata.multilayer_data.num_layers
if rundata.stormdata.storm_type > 0:
clawdata.num_aux += 3
# Index of aux array corresponding to capacity function, if there is one:
clawdata.capa_index = 0
# -------------
# Initial time:
# -------------
clawdata.t0 = 0.0
# Restart from checkpoint file of a previous run?
# Note: If restarting, you must also change the Makefile to set:
# RESTART = True
# If restarting, t0 above should be from original run, and the
# restart_file 'fort.chkNNNNN' specified below should be in
# the OUTDIR indicated in Makefile.
clawdata.restart = False # True to restart from prior results
clawdata.restart_file = 'fort.chk00036' # File to use for restart data
# -------------
# Output times:
#--------------
# Specify at what times the results should be written to fort.q files.
# Note that the time integration stops after the final output time.
# The solution at initial time t0 is always written in addition.
clawdata.output_style = 1
if clawdata.output_style == 1:
# Output nout frames at equally spaced times up to tfinal:
clawdata.num_output_times = 40
clawdata.tfinal = 1.0
clawdata.output_t0 = True # output at initial (or restart) time?
elif clawdata.output_style == 2:
# Specify a list of output times.
clawdata.output_times = [0.5, 1.0]
elif clawdata.output_style == 3:
# Output every iout timesteps with a total of ntot time steps:
clawdata.output_step_interval = 1
clawdata.total_steps = 10
clawdata.output_t0 = True
clawdata.output_format = 'ascii' # 'ascii' or 'binary'
clawdata.output_q_components = 'all' # need all
clawdata.output_aux_components = 'all' # eta=h+B is in q
clawdata.output_aux_onlyonce = False # output aux arrays each frame
# ---------------------------------------------------
# Verbosity of messages to screen during integration:
# ---------------------------------------------------
# The current t, dt, and cfl will be printed every time step
# at AMR levels <= verbosity. Set verbosity = 0 for no printing.
# (E.g. verbosity == 2 means print only on levels 1 and 2.)
clawdata.verbosity = 1
# --------------
# Time stepping:
# --------------
# if dt_variable==1: variable time steps used based on cfl_desired,
# if dt_variable==0: fixed time steps dt = dt_initial will always be used.
clawdata.dt_variable = True
# Initial time step for variable dt.
# If dt_variable==0 then dt=dt_initial for all steps:
clawdata.dt_initial = 0.00225
# Max time step to be allowed if variable dt used:
clawdata.dt_max = 1e+99
# Desired Courant number if variable dt used, and max to allow without
# retaking step with a smaller dt:
clawdata.cfl_desired = 0.75
clawdata.cfl_max = 1.0
# clawdata.cfl_desired = 0.45
# clawdata.cfl_max = 0.5
# Maximum number of time steps to allow between output times:
clawdata.steps_max = 5000
# ------------------
# Method to be used:
# ------------------
# Order of accuracy: 1 => Godunov, 2 => Lax-Wendroff plus limiters
clawdata.order = 2
# Use dimensional splitting? (not yet available for AMR)
# 0 or 'unsplit' or none' ==> Unsplit
# 1 or 'increment' ==> corner transport of waves
# 2 or 'all' ==> corner transport of 2nd order corrections too
clawdata.dimensional_split = "unsplit"
# For unsplit method, transverse_waves can be
# 0 or 'none' ==> donor cell (only normal solver used)
# 1 or 'increment' ==> corner transport of waves
# 2 or 'all' ==> corner transport of 2nd order corrections too
clawdata.transverse_waves = 2
# Number of waves in the Riemann solution:
clawdata.num_waves = 6
# List of limiters to use for each wave family:
# Required: len(limiter) == num_waves
# Some options:
# 0 or 'none' ==> no limiter (Lax-Wendroff)
# 1 or 'minmod' ==> minmod
# 2 or 'superbee' ==> superbee
# 3 or 'mc' ==> MC limiter
# 4 or 'vanleer' ==> van Leer
clawdata.limiter = ['mc', 'mc', 'mc', 'mc', 'mc', 'mc']
clawdata.use_fwaves = True # True ==> use f-wave version of algorithms
# Source terms splitting:
# src_split == 0 or 'none' ==> no source term (src routine never called)
# src_split == 1 or 'godunov' ==> Godunov (1st order) splitting used,
# src_split == 2 or 'strang' ==> Strang (2nd order) splitting used, not recommended.
clawdata.source_split = 'godunov'
# --------------------
# Boundary conditions:
# --------------------
# Number of ghost cells (usually 2)
clawdata.num_ghost = 2
# Choice of BCs at xlower and xupper:
# 0 => user specified (must modify bcN.f to use this option)
# 1 => extrapolation (non-reflecting outflow)
# 2 => periodic (must specify this at both boundaries)
# 3 => solid wall for systems where q(2) is normal velocity
clawdata.bc_lower[0] = 'extrap'
clawdata.bc_upper[0] = 'extrap'
clawdata.bc_lower[1] = 'extrap'
clawdata.bc_upper[1] = 'extrap'
# --------------
# Checkpointing:
# --------------
# Specify when checkpoint files should be created that can be
# used to restart a computation.
clawdata.checkpt_style = 0
if clawdata.checkpt_style == 0:
# Do not checkpoint at all
pass
elif clawdata.checkpt_style == 1:
# Checkpoint only at tfinal.
pass
elif clawdata.checkpt_style == 2:
# Specify a list of checkpoint times.
clawdata.checkpt_times = [0.1, 0.15]
elif clawdata.checkpt_style == 3:
# Checkpoint every checkpt_interval timesteps (on Level 1)
# and at the final time.
clawdata.checkpt_interval = 5
# ---------------
# AMR parameters:
# ---------------
amrdata = rundata.amrdata
# max number of refinement levels:
amrdata.amr_levels_max = 1
# List of refinement ratios at each level (length at least mxnest-1)
amrdata.refinement_ratios_x = [2, 6]
amrdata.refinement_ratios_y = [2, 6]
amrdata.refinement_ratios_t = [2, 6]
# Specify type of each aux variable in amrdata.auxtype.
# This must be a list of length maux, each element of which is one of:
# 'center', 'capacity', 'xleft', or 'yleft' (see documentation).
amrdata.aux_type = [
'center', 'center', 'yleft', 'center', 'center', 'center'
]
# Flag using refinement routine flag2refine rather than richardson error
amrdata.flag_richardson = False # use Richardson?
amrdata.flag2refine = True
# steps to take on each level L between regriddings of level L+1:
amrdata.regrid_interval = 3
# width of buffer zone around flagged points:
# (typically the same as regrid_interval so waves don't escape):
amrdata.regrid_buffer_width = 2
# clustering alg. cutoff for (# flagged pts) / (total # of cells refined)
# (closer to 1.0 => more small grids may be needed to cover flagged cells)
amrdata.clustering_cutoff = 0.700000
# print info about each regridding up to this level:
amrdata.verbosity_regrid = 0
# ----- For developers -----
# Toggle debugging print statements:
amrdata.dprint = False # print domain flags
amrdata.eprint = False # print err est flags
amrdata.edebug = False # even more err est flags
amrdata.gprint = False # grid bisection/clustering
amrdata.nprint = False # proper nesting output
amrdata.pprint = False # proj. of tagged points
amrdata.rprint = False # print regridding summary
amrdata.sprint = False # space/memory output
amrdata.tprint = True # time step reporting each level
amrdata.uprint = False # update/upbnd reporting
# More AMR parameters can be set -- see the defaults in pyclaw/data.py
# ---------------
# Regions:
# ---------------
rundata.regiondata.regions = []
# to specify regions of refinement append lines of the form
# [minlevel,maxlevel,t1,t2,x1,x2,y1,y2]
# ---------------
# Gauges:
# ---------------
rundata.gaugedata.gauges = []
# for gauges append lines of the form [gaugeno, x, y, t1, t2]
gauge_locations = [-0.1, 0.0, 0.1, 0.2, 0.3]
for (i, x_c) in enumerate(gauge_locations):
# y0 = (self.run_data.clawdata.yupper - self.run_data.clawdata.ylower) / 2.0
# x_p,y_p = transform_c2p(x_c,0.0,location[0],location[1],angle)
x_p = x_c * numpy.cos(0.0)
y_p = x_c * numpy.sin(0.0)
# print "+=====+"
# print x_c,0.0
# print x_p,y_p
if (rundata.clawdata.lower[0] < x_p < rundata.clawdata.upper[0] and
rundata.clawdata.lower[1] < y_p < rundata.clawdata.upper[1]):
rundata.gaugedata.gauges.append([i, x_p, y_p, 0.0, 1e10])
# print "Gauge %s: (%s,%s)" % (i,x_p,y_p)
# print "+=====+"
return rundata
def setplot(plotdata):
r"""Setplot function for surge plotting"""
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 = surgedata.SurgeData()
surge_data.read(os.path.join(plotdata.outdir, 'surge.data'))
friction_data = surgedata.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
# 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
]
speed_limits = [0.0, speed_range]
speed_contours = numpy.linspace(0.0, speed_range, 13)
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]
# ==========================================================================
# ==========================================================================
# Plot specifications
# ==========================================================================
# ==========================================================================
#-----------------------------------------
# Some global kml flags
#-----------------------------------------
plotdata.kml_name = "Ike"
plotdata.kml_starttime = [2008, 9, 3, 15, 0,
0] # Time of event in UTC [None]
plotdata.kml_tz_offset = 5 # Time zone offset (in hours) of event. [None]
plotdata.kml_index_fname = "Ike" # name for .kmz and .kml files ["_GoogleEarth"]
# Set to path where KMZ files will be stored; KML file will then
# link to this path.
# plotdata.kml_publish = 'http://www.domain.edu/path/to/kmz/files'
# ========================================================================
# Entire Gulf
# ========================================================================
gulf_xlimits = [clawdata.lower[0], clawdata.upper[0]]
gulf_ylimits = [clawdata.lower[1], clawdata.upper[1]]
gulf_shrink = 1.0
# --------------------------
# Surface - entire gulf
# --------------------------
plotfigure = plotdata.new_plotfigure(name='Surface - Entire Domain',
figno=0)
plotfigure.show = True
plotfigure.use_for_kml = True
plotfigure.kml_use_for_initial_view = True
# These override axes limits set below in plotitems
plotfigure.kml_xlimits = gulf_xlimits
plotfigure.kml_ylimits = gulf_ylimits
# Resolution - needs to be set carefully for the transparent colormap
rcl = 40
plotfigure.kml_dpi = rcl * 2
plotfigure.kml_figsize = [11.6, 9.6]
plotfigure.kml_tile_images = False # Tile images for faster loading. Requires GDAL [False]
plotaxes = plotfigure.new_plotaxes()
plotitem = plotaxes.new_plotitem(name='surface', plot_type='2d_pcolor')
plotitem.plot_var = geoplot.surface_or_depth
plotitem.pcolor_cmap = geoplot.googleearth_transparent
plotitem.pcolor_cmin = -surface_range
plotitem.pcolor_cmax = surface_range
def kml_colorbar(filename):
cmin = -surface_range
cmax = surface_range
geoplot.kml_build_colorbar(filename, geoplot.googleearth_transparent,
cmin, cmax)
plotfigure.kml_colorbar = kml_colorbar
# --------------------------
# Water Speed - entire gulf
# --------------------------
plotfigure = plotdata.new_plotfigure(name='Currents - Entire Domain',
figno=1)
plotfigure.show = True
plotfigure.use_for_kml = True
plotfigure.kml_use_for_initial_view = False
# These override axes limits set below in plotitems
plotfigure.kml_xlimits = gulf_xlimits
plotfigure.kml_ylimits = gulf_ylimits
plotfigure.kml_figsize = [11.6, 9.6]
plotfigure.kml_dpi = 80 # size not so important with contourf
plotfigure.kml_tile_images = False # Tile images for faster loading. Requires GDAL [False]
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotitem = plotaxes.new_plotitem(name='surface', plot_type='2d_contourf')
plotitem.plot_var = geoplot.surface_or_depth
plotitem.contour_levels = speed_contours
plotitem.fill_cmin = min(speed_contours)
plotitem.fill_cmax = max(speed_contours)
cmap = plt.get_cmap('OrRd')
cmap._rgba_under = (0.0, 0.0, 0.0, 0.0)
plotitem.fill_cmap = cmap
def cbar_speeds(filename):
cmin = min(speed_contours)
cmax = max(speed_contours)
geoplot.kml_build_colorbar(filename, cmap, cmin, cmax)
plotfigure.kml_colorbar = cbar_speeds
# ========================================================================
# 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
#No need to worry about fitting the plot exactly if we are not using
# the transparent colormap with pcolor.
#num_cells = [116, 96]
#dx = (gulf_xlimits[1] - float(gulf_xlimits[0]))/num_cells[0] # = 0.25
#dy = (gulf_ylimits[1] - float(gulf_ylimits[0]))/num_cells[1] # = 0.25
#houston_xlimits = [gulf_xlimits[0] + 14*dx, gulf_xlimits[0] + 21*dx] # [-95.25, -94.5]
#houston_ylimits = [gulf_ylimits[0] + 82*dy, gulf_ylimits[0] + 88*dy] # [-95.25, -94.5]
#figsize = [(21-14)*dx,(88-82)*dy] # relative to [11.6, 9.6] occupied by larger grid
figsize = [
houston_xlimits[1] - houston_xlimits[0],
houston_ylimits[1] - houston_ylimits[0]
]
dpi = 400
# --------------------------------------
# Surface Elevations - Houston/Galveston
# --------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface - Houston/Galveston',
figno=2)
plotfigure.show = True
plotfigure.use_for_kml = True
plotfigure.kml_xlimits = houston_xlimits
plotfigure.kml_ylimits = houston_ylimits
plotfigure.kml_dpi = dpi # data is not more resolve than this
plotfigure.kml_figsize = figsize
plotfigure.kml_tile_images = False
# pcolor for water.
plotaxes = plotfigure.new_plotaxes()
plotitem = plotaxes.new_plotitem(name='surface', plot_type='2d_contourf')
plotitem.contour_levels = surface_contours
plotitem.fill_cmin = min(surface_contours)
plotitem.fill_cmax = max(surface_contours)
# what is the colormap used here?
#plotfigure.kml_colorbar = cbar_houston
# --------------------------------
# Water Speed - Houston/Galveston
# --------------------------------
plotfigure = plotdata.new_plotfigure(name='Currents - Houston/Galveston',
figno=3)
plotfigure.show = True
plotfigure.use_for_kml = True
# These override axes limits set below in plotitems
plotfigure.kml_xlimits = houston_xlimits
plotfigure.kml_ylimits = houston_ylimits
plotfigure.kml_figsize = figsize
plotfigure.kml_dpi = dpi # data is not more resolve than this
plotfigure.kml_tile_images = False # Tile images for faster loading. Requires GDAL [False]
# Water
plotaxes = plotfigure.new_plotaxes()
plotitem = plotaxes.new_plotitem(name='surface', plot_type='2d_contourf')
plotitem.plot_var = geoplot.surface_or_depth
plotitem.contour_levels = speed_contours
plotitem.fill_cmin = min(speed_contours)
plotitem.fill_cmax = max(speed_contours)
cmap = plt.get_cmap('OrRd')
cmap._rgba_under = (0.0, 0.0, 0.0, 0.0)
plotitem.fill_cmap = cmap
# ========================================================================
# 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)
surgeplot.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-'
#-----------------------------------------
# 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 = [0, 1, 2, 3] # list of figures to print
plotdata.html_homelink = '../README.html' # pointer for top of index
plotdata.latex_figsperline = 2 # layout of plots
plotdata.latex_framesperline = 1 # layout of plots
plotdata.latex_makepdf = False # also run pdflatex?
plotdata.html = False # create html files of plots?
plotdata.latex = False # create latex file of plots?
plotdata.kml = True
return plotdata