def setplotfg(fgno=1, outdir='_output'):
from pyclaw.plotters import plotfg, colormaps, geoplot
from numpy import arange
# max used for surface and inundation colormaps below:
etamax = 5.0
fgdata = plotfg.ClawPlotFGData()
#xfgdata.format = 'binary'
# Set attributes as desired:
fgdata.outdir = outdir
fgdata.plotdir = '.'
# Fixed grid to display:
fgdata.fgno = fgno
if fgno>0:
# Could set things differently for each fgno if desired...
# Contour levels for all plots:
fgdata.clines = arange(-20,32,4)
# For plot of surface eta each frame:
fgdata.eta_show = True
my_cmap_surface = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.02: [0.75,0.75,1.0], \
0.0: [1.0,1.0,1.0], \
0.02: [1.0,0.75,0.75], \
1.0: [1.0,0.0,0.0]})
fgdata.water_cmap = my_cmap_surface
fgdata.water_clim = (-etamax,etamax)
fgdata.land_cmap = geoplot.land_colors
fgdata.land_clim = (0,40)
# For plot of inundation region:
fgdata.inundated_show = True
fgdata.inundated_clim =(0,etamax)
# colormap that scales up to etamax:
fgdata.inundated_cmap = colormaps.make_colormap({0:[0,0.3,1],\
0.1*etamax:[0,1,1],1.01*etamax:[0,1,1], \
0.4*etamax:[0,1,0], etamax:[1,0.2,0.2]})
fgdata.inundated_add_colorbar = True
# For plot of exposed seafloor:
fgdata.seafloor_show = True
fgdata.seafloor_cmap = geoplot.seafloor_colormap
fgdata.seafloor_clim = (-1,0)
fgdata.save_png = False
fgdata.seafloor_add_colorbar = True
fgdata.drytol = 1.e-2
fgdata.exposed_tol = 1.e-2
return fgdata
def setplotfg(fgno=1, outdir='_output'):
from pyclaw.plotters import plotfg, colormaps, geoplot
from numpy import arange
# max used for surface and inundation colormaps below:
etamax = 1.0
fgdata = plotfg.ClawPlotFGData()
# Set attributes as desired:
fgdata.outdir = outdir
fgdata.plotdir = '.'
# Fixed grid to display:
fgdata.fgno = fgno
if fgno > 0:
# Could set things differently for each fgno if desired...
# Contour levels for all plots:
fgdata.clines = arange(-20, 32, 4)
# For plot of surface eta each frame:
fgdata.eta_show = True
my_cmap_surface = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.02: [0.75,0.75,1.0], \
0.0: [1.0,1.0,1.0], \
0.02: [1.0,0.75,0.75], \
1.0: [1.0,0.0,0.0]})
fgdata.water_cmap = my_cmap_surface
fgdata.water_clim = (-etamax, etamax)
fgdata.land_cmap = geoplot.land_colors
fgdata.land_clim = (0, 40)
# For plot of inundation region:
fgdata.inundated_show = True
fgdata.inundated_clim = (0, etamax)
# colormap that scales up to etamax:
fgdata.inundated_cmap = colormaps.make_colormap({0:[0,0.3,1],\
0.1*etamax:[0,1,1],1.01*etamax:[0,1,1], \
0.4*etamax:[0,1,0], etamax:[1,0.2,0.2]})
fgdata.inundated_add_colorbar = True
# For plot of exposed seafloor:
fgdata.seafloor_show = True
fgdata.seafloor_cmap = geoplot.seafloor_colormap
fgdata.seafloor_clim = (-1, 0)
fgdata.save_png = False
fgdata.seafloor_add_colorbar = True
fgdata.drytol = 1.e-2
fgdata.exposed_tol = 1.e-2
return fgdata
def setplotfg(fgno=1, outdir='_output'):
from pyclaw.plotters import plotfg, colormaps, geoplot
from numpy import arange
fgdata = plotfg.ClawPlotFGData()
# Set attributes as desired:
fgdata.outdir = outdir
fgdata.plotdir = '.'
# Fixed grid to display:
fgdata.fgno = fgno
if fgno==1:
# Plot parameters for Fixed Grid 1.
# Repeat as needed for other fixed grids.
# Contour levels for all plots:
fgdata.clines = arange(-20,33,4)
# For plot of surface eta each frame:
fgdata.eta_show = True
my_cmap_surface = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.02: [0.75,0.75,1.0], \
0.0: [1.0,1.0,1.0], \
0.02: [1.0,0.75,0.75], \
1.0: [1.0,0.0,0.0]})
fgdata.water_cmap = my_cmap_surface
fgdata.water_clim = (-20,20)
fgdata.land_cmap = geoplot.land_colors
fgdata.land_clim = (0,40)
# For plot of inundation region:
fgdata.inundated_show = True
fgdata.inundated_cmap = colormaps.make_colormap({0:[0,0,1],\
1:[0,1,1],1.01:[0,1,1], 4:[0,1,0], 10:[1,0,0]})
fgdata.inundated_clim =(0,10)
# For plot of exposed seafloor:
fgdata.seafloor_show = False
fgdata.seafloor_cmap = geoplot.seafloor_colormap
fgdata.seafloor_clim = (-1,0)
fgdata.save_png = False
fgdata.drytol = 1.e-2
fgdata.exposed_tol = 1.e-2
return fgdata
def setplotfg(fgno=1, outdir='_output'):
from pyclaw.plotters import plotfg, colormaps, geoplot
from numpy import arange
fgdata = plotfg.ClawPlotFGData()
# Set attributes as desired:
fgdata.outdir = outdir
fgdata.plotdir = '.'
# Fixed grid to display:
fgdata.fgno = fgno
if fgno>0:
# Plot parameters for Fixed Grid 1.
# Repeat as needed for other fixed grids.
# Contour levels for all plots:
fgdata.clines = arange(-20,32,2)
# For plot of surface eta each frame:
fgdata.eta_show = True
my_cmap_surface = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.02: [0.75,0.75,1.0], \
0.0: [1.0,1.0,1.0], \
0.02: [1.0,0.75,0.75], \
1.0: [1.0,0.0,0.0]})
fgdata.water_cmap = my_cmap_surface
fgdata.water_clim = (-20,20)
fgdata.land_cmap = geoplot.land_colors
fgdata.land_clim = (0,40)
# For plot of inundation region:
fgdata.inundated_show = True
fgdata.inundated_cmap = colormaps.make_colormap({0:[0,0.3,1],\
1:[0,1,1],1.01:[0,1,1], 4:[0,1,0], 10:[1,0.2,0.2]})
fgdata.inundated_clim =(0,10)
# For plot of exposed seafloor:
fgdata.seafloor_show = False
fgdata.seafloor_cmap = geoplot.seafloor_colormap
fgdata.seafloor_clim = (-1,0)
fgdata.save_png = False
fgdata.drytol = 1.e-2
fgdata.exposed_tol = 1.e-2
return fgdata
def add_surface_elevation(plotaxes,bounds=None,plot_type='pcolor'):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
# plotitem.plotvar = eta
plotitem.plot_var = geoplot.surface
plotitem.imshow_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
elif plot_type == 'contour':
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.surface
if bounds is None:
plotitem.contour_levels = [-2.5,-1.5,-0.5,0.5,1.5,2.5]
# plotitem.contour_nlevels = 21
# plotitem.contour_min = -2.0
# plotitem.contour_max = 2.0
# plotitem.kwargs = {''}
plotitem.amr_contour_show = [1,1,1]
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
plotitem.amr_contour_colors = 'k'
def __init__(self, fgno=1):
super(ClawPlotFGData, self).__init__()
self.add_attribute("fgno", fgno)
self.add_attribute("drytol", 1.0e-2)
self.add_attribute("exposed_tol", 1.0e-2)
self.add_attribute("clines", linspace(-20, 20, 21))
self.add_attribute("water_cmap", geoplot.tsunami_colormap)
self.add_attribute("land_cmap", geoplot.land_colors)
self.add_attribute("seafloor_cmap", geoplot.seafloor_colormap)
self.add_attribute(
"inundated_cmap",
colormaps.make_colormap({0.0: [1, 0.9, 0.9], 1.0: [1, 0, 0]}),
)
self.add_attribute("water_clim", (-1, 1))
self.add_attribute("land_clim", (0, 10))
self.add_attribute("seafloor_clim", (-1, 0))
self.add_attribute("inundated_clim", (0, 1))
self.add_attribute("water_add_colorbar", True)
self.add_attribute("land_add_colorbar", False)
self.add_attribute("seafloor_add_colorbar", True)
self.add_attribute("inundated_add_colorbar", True)
self.add_attribute("eta_show", True)
self.add_attribute("seafloor_show", True)
self.add_attribute("inundated_show", True)
self.add_attribute("outdir", "_output")
self.add_attribute("plotdir", None)
self.add_attribute("save_png", False)
self.add_attribute("solutions", {})
self.add_attribute("grids", {})
self.add_attribute("combined_figure", True)
def __init__(self, fgno=1):
super(ClawPlotFGData, self).__init__()
self.add_attribute('fgno', fgno)
self.add_attribute('drytol', 1.e-2)
self.add_attribute('exposed_tol', 1.e-2)
self.add_attribute('clines', linspace(-20, 20, 21))
self.add_attribute('water_cmap', geoplot.tsunami_colormap)
self.add_attribute('land_cmap', geoplot.land_colors)
self.add_attribute('seafloor_cmap', geoplot.seafloor_colormap)
self.add_attribute('inundated_cmap', \
colormaps.make_colormap({0.:[1,.9,.9], 1.:[1,0,0]}))
self.add_attribute('water_clim', (-1, 1))
self.add_attribute('land_clim', (0, 10))
self.add_attribute('seafloor_clim', (-1, 0))
self.add_attribute('inundated_clim', (0, 1))
self.add_attribute('water_add_colorbar', True)
self.add_attribute('land_add_colorbar', False)
self.add_attribute('seafloor_add_colorbar', True)
self.add_attribute('inundated_add_colorbar', True)
self.add_attribute('eta_show', True)
self.add_attribute('seafloor_show', True)
self.add_attribute('inundated_show', True)
self.add_attribute('outdir', '_output')
self.add_attribute('plotdir', None)
self.add_attribute('save_png', False)
self.add_attribute('solutions', {})
self.add_attribute('grids', {})
self.add_attribute('combined_figure', True)
def add_surface_elevation(plotaxes,surface,bounds=None,plot_type='pcolor'):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
# plotitem.plot_var = geoplot.surface
if surface == 1:
plotitem.plot_var = eta1
elif surface == 2:
plotitem.plot_var = eta2
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
# plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
elif plot_type == 'contour':
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = surface + 5
if bounds is not None:
plotitem.contour_levels = bounds
plotitem.amr_contour_show = [1,1,1]
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
plotitem.amr_contour_colors = 'k'
else:
raise NotImplementedError("Plot type %s not implemented" % plot_type)
def __init__(self,fgno=1):
super(ClawPlotFGData,self).__init__()
self.add_attribute('fgno',fgno)
self.add_attribute('drytol',1.e-2)
self.add_attribute('exposed_tol',1.e-2)
self.add_attribute('clines',linspace(-20,20,21))
self.add_attribute('water_cmap', geoplot.tsunami_colormap)
self.add_attribute('land_cmap', geoplot.land_colors)
self.add_attribute('seafloor_cmap', geoplot.seafloor_colormap)
self.add_attribute('inundated_cmap', \
colormaps.make_colormap({0.:[1,.9,.9], 1.:[1,0,0]}))
self.add_attribute('water_clim',(-1,1))
self.add_attribute('land_clim',(0,10))
self.add_attribute('seafloor_clim',(-1,0))
self.add_attribute('inundated_clim',(0,1))
self.add_attribute('water_add_colorbar',True)
self.add_attribute('land_add_colorbar',False)
self.add_attribute('seafloor_add_colorbar',True)
self.add_attribute('inundated_add_colorbar',True)
self.add_attribute('eta_show',True)
self.add_attribute('seafloor_show',True)
self.add_attribute('inundated_show',True)
self.add_attribute('outdir','_output')
self.add_attribute('plotdir',None)
self.add_attribute('save_png',False)
self.add_attribute('solutions',{})
self.add_attribute('grids',{})
self.add_attribute('combined_figure',True)
def add_layer_depth(plotaxes,layer,bounds=None,plot_type='pcolor'):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
if layer == 1:
plotitem.plot_var = 0
elif layer == 2:
plotitem.plot_var = 3
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
plotitem.imshow_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
elif plot_type == 'profile':
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.map_2d_to_1d = upper_surface
if surface == 1:
plotitem.plot_var = 0
elif surface == 2:
plotitem.plot_var = 3
if bounds is not None:
plotitem.ylimits = bounds
plotitem.amr_plotstyle = ['-','-.','+','x','.']
# plotitem.color = (0.2,0.8,1.0)
else:
raise NotImplementedError("Plot type %s not implemented" % plot_type)
def setplot(plotdata):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps
plotdata.clearfigures() # clear any old figures,axes,items data
plotfigure = plotdata.new_plotfigure(name='Pressure', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [-1., 1.]
plotaxes.ylimits = [-1., 1.]
plotaxes.title = 'Pressure'
plotaxes.scaled = True # so aspect ratio is 1
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = 0
plotitem.contour_nlevels = 21
plotitem.contour_min = 0.0
plotitem.contour_max = 3.0
# Use a custom colormap ranging from blue to red:
blue_red_cmap = colormaps.make_colormap({0:'b', 1:'r'})
plotitem.contour_cmap = blue_red_cmap
plotitem.add_colorbar = True
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 = 1 # layout of plots
plotdata.latex_framesperline = 2 # layout of plots
plotdata.latex_makepdf = True # also run pdflatex?
return plotdata
def setplot(plotdata):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps
plotdata.clearfigures() # clear any old figures,axes,items data
plotfigure = plotdata.new_plotfigure(name='Pressure', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [-1., 1.]
plotaxes.ylimits = [-1., 1.]
plotaxes.title = 'Pressure'
plotaxes.scaled = True # so aspect ratio is 1
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = 0
plotitem.contour_nlevels = 21
plotitem.contour_min = 0.0
plotitem.contour_max = 3.0
# Use a custom colormap ranging from blue to red:
blue_red_cmap = colormaps.make_colormap({0: 'b', 1: 'r'})
plotitem.contour_cmap = blue_red_cmap
plotitem.add_colorbar = True
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 = 1 # layout of plots
plotdata.latex_framesperline = 2 # layout of plots
plotdata.latex_makepdf = True # also run pdflatex?
return plotdata
def add_layer_depth(plotaxes,layer,bounds=None,plot_type='pcolor'):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
if layer == 1:
plotitem.plot_var = 0
elif layer == 2:
plotitem.plot_var = 3
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
plotitem.imshow_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
def add_surface_elevation(plotaxes,surface,bounds=None,plot_type='pcolor'):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
# plotitem.plot_var = geoplot.surface
if surface == 1:
plotitem.plot_var = eta1
elif surface == 2:
plotitem.plot_var = eta2
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
# plotitem.pcolor_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
elif plot_type == 'profile':
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
if surface == 1:
plotitem.plot_var = eta1
plotitem.map_2d_to_1d = upper_surface
elif surface == 2:
plotitem.plot_var = eta2
plotitem.map_2d_to_1d = lower_surface
if bounds is not None:
plotitem.ylimits = bounds
plotitem.amr_plotstyle = ['-','-.','+','x','.']
# plotitem.color = (0.2,0.8,1.0)
elif plot_type == 'contour':
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = surface + 5
if bounds is not None:
plotitem.contour_levels = bounds
plotitem.amr_contour_show = [1,1,1]
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
plotitem.amr_contour_colors = 'k'
else:
raise NotImplementedError("Plot type %s not implemented" % plot_type)
def setplot(plotdata):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
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-4
plotdata.beforeframe = set_drytol
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=True)
# ========================================================================
# Water Velocity Helper Functions
# ========================================================================
def water_velocity(current_data,DRY_TOL=1e-6):
r"""Calculate velocity from the momentum and depth
Calculates the x and y velocities from the momenta. A mask is
constructed so that division by a small depth is avoided, controlled
by the optional keyword argument DRY_TOL (default = 1e-6). A check
for NaNs is also made. Any point not satisfying either of these
criteria is set to 0.0.
returns numpy.ndarray, nump.ndarray
"""
h = current_data.q[:,:,0]
hu = current_data.q[:,:,1]
hv = current_data.q[:,:,2]
u = np.zeros(hu.shape)
v = np.zeros(hv.shape)
index = np.nonzero((np.abs(h) > DRY_TOL) * (h != np.nan))
u[index[0],index[1]] = hu[index[0],index[1]] / h[index[0],index[1]]
v[index[0],index[1]] = hv[index[0],index[1]] / h[index[0],index[1]]
return u,v
def vorticity(current_data):
r"""Calculate vorticity of velocity field
Using matrix operations, calculate u_y + v_x, note that second order,
centered differences are used for interior points and forward and
backward differences for the boundary values.
returns numpy.ndarray of shape of u and v
"""
u,v = water_velocity(current_data)
dx = current_data.dx
dy = current_data.dy
u_y = np.zeros(u.shape)
u_y[:,0] = (-3.0*u[:,0] + 4.0 * u[:,1] - u[:,2]) / (2.0 * dy)
u_y[:,-1] = (u[:,-3] - 4.0 * u[:,-2] + 3.0 * u[:,-1]) / (2.0 * dy)
u_y[:,1:-1] = (u[:,2:] - u[:,0:-2]) / (2.0 * dy)
v_x = np.zeros(v.shape)
v_x[0,:] = (-3.0*v[0,:] + 4.0 * v[1,:] - v[2,:]) / (2.0 * dx)
v_x[-1,:] = (u[-3,:] - 4.0 * u[-2,:] + 3.0 * u[-1,:]) / (2.0 * dx)
v_x[1:-1,:] = (v[2:,:] - v[0:-2,:]) / (2.0 * dx)
return v_x - u_y
def water_speed(current_data):
u,v = water_velocity(current_data)
return np.sqrt(u**2+v**2)
def water_quiver(current_data):
u = water_u(current_data)
v = water_v(current_data)
plt.hold(True)
Q = plt.quiver(current_data.x[::2,::2],current_data.y[::2,::2],
u[::2,::2],v[::2,::2])
max_speed = np.max(np.sqrt(u**2+v**2))
label = r"%s m/s" % str(np.ceil(0.5*max_speed))
plt.quiverkey(Q,0.15,0.95,0.5*max_speed,label,labelpos='W')
plt.hold(False)
#-----------------------------------------
# Figure for pcolor plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='pcolor', figno=0)
plotfigure.show = False
# 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 = -0.02
plotitem.pcolor_cmax = 0.02
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_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 = 0.05
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotaxes.xlimits = 'auto'
plotaxes.ylimits = 'auto'
#-----------------------------------------
# Figure for imshow plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface and Gauge 1', figno=20)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('imshow')
plotaxes.axescmd = "axes([.1,.5,.8,.4])"
plotaxes.title = 'Surface'
plotaxes.scaled = True
plotaxes.afteraxes = addgauges
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = -0.03
plotitem.imshow_cmax = 0.03
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 0.05
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotaxes.xlimits = 'auto'
plotaxes.ylimits = 'auto'
# Gauge trace:
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = "axes([.1,.1,.8,.3])"
plotaxes.xlimits = 'auto'
plotaxes.ylimits = [-0.02, 0.05]
plotaxes.title = 'Gauge 1'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_gauge_trace')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
plotitem.gaugeno = 1
#-----------------------------------------
# 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('monai')
#plotaxes.axescmd = 'axes([0.0,0.1,0.6,0.6])'
plotaxes.title = 'Zoom near Monai Valley'
plotaxes.scaled = True
plotaxes.xlimits = [4.0, 5.2]
plotaxes.ylimits = [1.3, 2.5]
# 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 = -0.02
plotitem.pcolor_cmax = 0.02
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0]
plotitem.amr_gridedges_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 = 0.05
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [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(-0.02, 0., .0025)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_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., .2, .01)
plotitem.amr_contour_colors = ['w'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
# Add dashed contour line for shoreline
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'dashed'}
plotitem.amr_contour_show = [1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=300, \
type='each_gauge')
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0,60]
plotaxes.ylimits = [-0.02, 0.05]
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.clf_each_gauge = False
plotitem.plotstyle = 'g-'
def afteraxes(current_data):
from pylab import plot, legend, loadtxt
t = current_data.t
plot(t, 0*t, 'k')
try:
labgage = loadtxt('WaveGages.txt',skiprows=1)
except:
print "*** Did not find WaveGages.txt from benchmark"
gaugeno = current_data.gaugeno
if gaugeno in [1,2,3]:
plot(labgage[:,0],0.01*labgage[:,gaugeno],'r')
legend(('GeoClaw','topography','sea level','lab data'),loc='upper right')
else:
legend(('GeoClaw','topography','sea level'),loc='upper right')
plotaxes.afteraxes = afteraxes
#-----------------------------------------
# Figure for grids alone
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='grids', 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 = 'grids'
plotaxes.scaled = True
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_grid')
plotitem.amr_grid_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.amr_gridlines_show = [1,1,0]
plotitem.amr_gridedges_show = [1]
# ========================================================================
# Water Currents
# ========================================================================
max_speed = 1.0
# ========================================================================
# Full plot
plotfigure = plotdata.new_plotfigure(name='currents', figno=400)
plotfigure.kwargs = {'figsize':[12,7]}
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents Full Domain'
plotaxes.scaled = True
# Speed
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = water_speed
plotitem.imshow_cmap = plt.get_cmap('PuBu')
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = max_speed
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.add_colorbar = False
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 0.05
# ========================================================================
# Zoomed plot
plotfigure = plotdata.new_plotfigure(name='currents_zoomed', figno=401)
plotfigure.kwargs = {'figsize':[12,7]}
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents Zoomed Domain'
plotaxes.scaled = True
plotaxes.xlimits = [4.0, 5.2]
plotaxes.ylimits = [1.3, 2.5]
# Speed
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = water_speed
plotitem.imshow_cmap = plt.get_cmap('PuBu')
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = max_speed
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.add_colorbar = False
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 0.05
# ========================================================================
# Vorticity plot
vorticity_limits = [-3,3]
# Full domain
plotfigure = plotdata.new_plotfigure(name='full_vorticity', figno=500)
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Vorticity'
plotaxes.scaled = True
# Speed
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = vorticity
plotitem.imshow_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
plotitem.imshow_cmin = vorticity_limits[0]
plotitem.imshow_cmax = vorticity_limits[1]
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.add_colorbar = False
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 0.05
#-----------------------------------------
# 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 = [1,2,3,12] # 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
yellow1= [.98,.96,.01];
tan1 = [.98,.83,.01];
tan2 = [.71,.62,.085];
tan3 = [.65,.56,.07];
tan4 = [.58,.50,.064];
tan5 = [.48,.415,.043];
tan6 = [0.42,0.36,0.038];
tan7 = [.36,.233,.029];
brown1=[.42,.167,.03];
# Colormaps
TSUNAMI_MAX_AMPLITUDE = 0.6
tsunami_colormap = colormaps.make_colormap({-TSUNAMI_MAX_AMPLITUDE:blue,
0.0:blue_green,
TSUNAMI_MAX_AMPLITUDE:red})
oso_debris_colormap = colormaps.make_colormap({0.0:white,
10.0: light_blue,
20.0: blue,
30.0: dark_blue})
oso_debris_colormap_invert = colormaps.make_colormap({0.0:dark_blue,
#10.0: blue,
#20.0: light_blue,
30.0: white})
oso_land_colormap_gray = colormaps.make_colormap({0.0: gray8,
1.0: gray5})
def plot_topo_file(topoplotdata):
"""
Read in a topo or bathy file and produce a pcolor map.
"""
import os
import pylab
from pyclaw.data import Data
fname = topoplotdata.fname
topotype = topoplotdata.topotype
if topoplotdata.climits:
# deprecated option
cmin = topoplotdata.climits[0]
cmax = topoplotdata.climits[1]
else:
cmin = topoplotdata.cmin
cmax = topoplotdata.cmax
figno = topoplotdata.figno
addcolorbar = topoplotdata.addcolorbar
addcontour = topoplotdata.addcontour
contour_levels = topoplotdata.contour_levels
xlimits = topoplotdata.xlimits
ylimits = topoplotdata.ylimits
coarsen = topoplotdata.coarsen
imshow = topoplotdata.imshow
gridedges_show = topoplotdata.gridedges_show
neg_cmap = topoplotdata.neg_cmap
pos_cmap = topoplotdata.pos_cmap
print_fname = topoplotdata.print_fname
if neg_cmap is None:
neg_cmap = colormaps.make_colormap({cmin:[0.3,0.2,0.1],
0:[0.95,0.9,0.7]})
if pos_cmap is None:
pos_cmap = colormaps.make_colormap({ 0:[.5,.7,0],
cmax:[.2,.5,.2]})
if abs(topotype) == 1:
X,Y,topo = topotools.topofile2griddata(fname, topotype)
topo = pylab.flipud(topo)
Y = pylab.flipud(Y)
x = X[0,:]
y = Y[:,0]
xllcorner = x[0]
yllcorner = y[0]
cellsize = x[1]-x[0]
elif abs(topotype) == 3:
file = open(fname, 'r')
lines = file.readlines()
ncols = int(lines[0].split()[0])
nrows = int(lines[1].split()[0])
xllcorner = float(lines[2].split()[0])
yllcorner = float(lines[3].split()[0])
cellsize = float(lines[4].split()[0])
NODATA_value = int(lines[5].split()[0])
print "Loading file ",fname
print " nrows = %i, ncols = %i" % (nrows,ncols)
topo = pylab.loadtxt(fname,skiprows=6,dtype=float)
print " Done loading"
if 0:
topo = []
for i in range(nrows):
topo.append(pylab.array(lines[6+i],))
print '+++ topo = ',topo
topo = pylab.array(topo)
topo = pylab.flipud(topo)
x = pylab.linspace(xllcorner, xllcorner+ncols*cellsize, ncols)
y = pylab.linspace(yllcorner, yllcorner+nrows*cellsize, nrows)
print "Shape of x, y, topo: ", x.shape, y.shape, topo.shape
else:
raise Exception("*** Only topotypes 1 and 3 supported so far")
if coarsen > 1:
topo = topo[slice(0,nrows,coarsen), slice(0,ncols,coarsen)]
x = x[slice(0,ncols,coarsen)]
y = y[slice(0,nrows,coarsen)]
print "Shapes after coarsening: ", x.shape, y.shape, topo.shape
if topotype < 0:
topo = -topo
if figno:
pylab.figure(figno)
if topoplotdata.imshow:
color_norm = Normalize(cmin,cmax,clip=True)
xylimits = (x[0],x[-1],y[0],y[-1])
#pylab.imshow(pylab.flipud(topo.T), extent=xylimits, \
pylab.imshow(pylab.flipud(topo), extent=xylimits, \
cmap=cmap, interpolation='nearest', \
norm=color_norm)
else:
neg_topo = ma.masked_where(topo>0., topo)
all_masked = (ma.count(neg_topo) == 0)
if not all_masked:
pylab.pcolormesh(x,y,neg_topo,cmap=neg_cmap)
pylab.clim([cmin,0])
if addcolorbar:
pylab.colorbar()
pos_topo = ma.masked_where(topo<0., topo)
all_masked = (ma.count(pos_topo) == 0)
if not all_masked:
pylab.pcolormesh(x,y,pos_topo,cmap=pos_cmap)
pylab.clim([0,cmax])
if addcolorbar:
pylab.colorbar()
pylab.axis('scaled')
if addcontour:
pylab.contour(x,y,topo,levels=contour_levels,colors='k')
if gridedges_show:
pylab.plot([x[0],x[-1]],[y[0],y[0]],'k')
pylab.plot([x[0],x[-1]],[y[-1],y[-1]],'k')
pylab.plot([x[0],x[0]],[y[0],y[-1]],'k')
pylab.plot([x[-1],x[-1]],[y[0],y[-1]],'k')
if print_fname:
fname2 = os.path.splitext(fname)[0]
pylab.text(xllcorner+cellsize, yllcorner+cellsize, fname2, color='m')
topodata = Data()
topodata.x = x
topodata.y = y
topodata.topo = topo
return topodata
light_green = [0.8, 1.0, 0.5]
blue = [0.0, 0.0, 1.0]
dark_blue = [0.2, 0.2, 0.7]
light_blue = [0.5, 0.5, 1.0]
blue_green = [0.0, 1.0, 1.0]
tan = [0.9, 0.8, 0.2]
tan = [0.8, 0.5, 0.2]
brown = [0.9, 0.8, 0.2]
gray8 = [0.8, 0.8, 0.8]
purple = [0.8, 0.3, 0.8]
# Colormaps
TSUNAMI_MAX_AMPLITUDE = 0.6
tsunami_colormap = colormaps.make_colormap({
-TSUNAMI_MAX_AMPLITUDE: blue,
0.0: blue_green,
TSUNAMI_MAX_AMPLITUDE: red
})
land1_colormap = colormaps.make_colormap({
0.0: dark_green,
1000.0: green,
2000.0: light_green,
4000.0: tan
})
land2_colormap = colormaps.make_colormap({
0: dark_green,
50: green,
100: light_green,
200: tan
dark_green = [0.1,0.4,0.0];
light_green = [0.8,1.0,0.5];
blue = [0.0,0.0,1.0];
dark_blue = [0.2,0.2,0.7];
light_blue = [0.5,0.5,1.0];
blue_green = [0.0,1.0,1.0];
tan = [0.9,0.8,0.2];
tan = [0.8,0.5,0.2];
brown = [0.9,0.8,0.2];
gray8 = [0.8,0.8,0.8];
purple = [0.8,0.3,0.8];
# Colormaps
TSUNAMI_MAX_AMPLITUDE = 0.6
tsunami_colormap = colormaps.make_colormap({-TSUNAMI_MAX_AMPLITUDE:blue,
0.0:blue_green,
TSUNAMI_MAX_AMPLITUDE:red})
land1_colormap = colormaps.make_colormap({0.0:dark_green,
1000.0:green,
2000.0:light_green,
4000.0:tan})
land2_colormap = colormaps.make_colormap({0:dark_green,
50:green,
100:light_green,
200:tan})
water_land_colormap = colormaps.make_colormap({-1000:dark_blue,
-500:blue,
0:light_blue,
def setplot(plotdata):
# --------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
plotdata.clearfigures() # clear any old figures,axes,items dat
# plotdata.format = "netcdf"
try:
tsudata = open(plotdata.outdir + "/settsunami.data").readlines()
for line in tsudata:
if "sealevel" in line:
sealevel = float(line.split()[0])
print "sealevel = ", sealevel
except:
print "Could not read sealevel, setting to 0."
sealevel = 0.0
# clim_ocean = 2.0
# clim_CC = 2.0
clim_ocean = 5.0
clim_CC = 5.0
cmax_ocean = clim_ocean + sealevel
cmin_ocean = -clim_ocean + sealevel
cmax_CC = clim_CC + sealevel
cmin_CC = -clim_CC + sealevel
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, gaugenos=[0], format_string="ko", add_labels=True)
def timeformat(t):
from numpy import mod
hours = int(t / 3600.0)
tmin = mod(t, 3600.0)
min = int(tmin / 60.0)
sec = int(mod(tmin, 60.0))
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)
def aframe(current_data):
from pylab import figure, savefig
if 0:
tminutes = int(current_data.t / 60.0)
figure(0)
fname = "Pacific%s.png" % tminutes
savefig(fname)
print "Saved ", fname
figure(11)
fname = "GraysHarbor%s.png" % tminutes
savefig(fname)
print "Saved ", fname
figure(12)
fname = "Westport%s.png" % tminutes
savefig(fname)
print "Saved ", fname
figure(13)
fname = "Ocosta%s.png" % tminutes
savefig(fname)
print "Saved ", fname
plotdata.afterframe = aframe
# -----------------------------------------
# Figure for big area
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Pacific", figno=0)
plotfigure.kwargs = {"figsize": (10, 6)}
# plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
# plotaxes.cmd = 'subplot(121)'
plotaxes.title = "Pacific"
plotaxes.scaled = False
# modified for debug:
# plotaxes.xlimits = [231.5,236.5]
# plotaxes.ylimits = [45,49]
# plotaxes.xlimits = [235.8,236.2]
# plotaxes.ylimits = [46.1,46.9]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, savefig
title_hours(current_data)
ticklabel_format(format="plain", useOffset=False)
xticks(rotation=20)
a = gca()
a.set_aspect(1.0 / cos(46.349 * pi / 180.0))
plotaxes.afteraxes = aa
# Water
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap(
{-1.0: [0.0, 0.0, 1.0], -0.5: [0.5, 0.5, 1.0], 0.0: [1.0, 1.0, 1.0], 0.5: [1.0, 0.5, 0.5], 1.0: [1.0, 0.0, 0.0]}
)
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = cmin_ocean
plotitem.imshow_cmax = cmax_ocean
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# plotaxes.afteraxes = addgauges
# Add contour lines of bathymetry:
plotitem = plotaxes.new_plotitem(plot_type="2d_contour")
plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = linspace(-6000, 0, 7)
plotitem.amr_contour_colors = ["g"] # color on each level
plotitem.kwargs = {"linestyles": "solid"}
plotitem.amr_contour_show = [0, 0, 1, 0] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type="2d_contour")
plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(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, 0, 1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# -----------------------------------------
# Figure for line plot
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="line", figno=2)
# plotfigure.show = False
def eta_slice(current_data):
from pylab import find, nan, array
x = current_data.x
y = current_data.y
q = current_data.q
j1 = find(y[0, :] > 47.5)
if len(j1) == 0:
x = eta = array([nan])
else:
j = min(j1)
x = x[:, j]
eta = q[:, j, 3]
return x, eta
def B_slice(current_data):
from pylab import find, nan, array
x = current_data.x
y = current_data.y
q = current_data.q
j1 = find(y[0, :] > 47.5)
if len(j1) == 0:
x = B = array([nan])
else:
j = min(j1)
x = x[:, j]
eta = q[:, j, 3]
h = q[:, j, 0]
B = eta - h
return x, B
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes("line")
plotaxes.axescmd = "subplot(212)"
plotaxes.title = "Bathymetry"
# Water
plotitem = plotaxes.new_plotitem(plot_type="1d_from_2d_data")
plotitem.show = False
plotitem.map_2d_to_1d = eta_slice
plotitem.color = "b"
plotitem.kwargs = {"linewidth": 2}
# Topography
plotitem = plotaxes.new_plotitem(plot_type="1d_from_2d_data")
# plotitem.show = False
plotitem.map_2d_to_1d = B_slice
plotitem.color = "k"
plotitem.plotstyle = "o-"
def aa(current_data):
from pylab import ticklabel_format
ticklabel_format(format="plain", useOffset=False)
plotaxes.afteraxes = aa
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes("linezoom")
# plotaxes.show = False
plotaxes.axescmd = "subplot(211)"
plotaxes.title = "Surface"
# plotaxes.xlimits = [-0.1,0.1]
plotaxes.ylimits = [-4, 6]
# Water
plotitem = plotaxes.new_plotitem(plot_type="1d_from_2d_data")
plotitem.map_2d_to_1d = eta_slice
plotitem.color = "b"
plotitem.plotstyle = "o-"
plotitem.kwargs = {"linewidth": 2}
# -----------------------------------------
# Figure for zoom2
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Gray's Harbor", figno=11)
plotfigure.show = False
plotfigure.kwargs = {"figsize": (10, 9)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
# plotaxes.cmd = 'subplot(122)'
plotaxes.title = "Gray's Harbor"
plotaxes.scaled = False
# Water
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap(
{-1.0: [0.0, 0.0, 1.0], -0.5: [0.5, 0.5, 1.0], 0.0: [1.0, 1.0, 1.0], 0.5: [1.0, 0.5, 0.5], 1.0: [1.0, 0.0, 0.0]}
)
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = cmin_CC
plotitem.imshow_cmax = cmax_CC
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [0]
# Land
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [0]
plotaxes.xlimits = [235.8, 236.2]
plotaxes.ylimits = [46.75, 47.1]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, savefig
# addgauges(current_data)
title_hours(current_data)
ticklabel_format(format="plain", useOffset=False)
xticks(rotation=20)
a = gca()
a.set_aspect(1.0 / cos(46.86 * pi / 180.0))
plotaxes.afteraxes = aa
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type="2d_contour")
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.0]
plotitem.amr_contour_colors = ["k"] # color on each level
plotitem.kwargs = {"linestyles": "solid", "linewidths": 2}
plotitem.amr_contour_show = [0, 0, 0, 0, 1, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# -----------------------------------------
# Figure for zoom
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Washington", figno=10)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Washington"
plotaxes.scaled = False
plotaxes.afteraxes = aa
# Water
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap(
{-1.0: [0.0, 0.0, 1.0], -0.1: [0.5, 0.5, 1.0], 0.0: [1.0, 1.0, 1.0], 0.1: [1.0, 0.5, 0.5], 1.0: [1.0, 0.0, 0.0]}
)
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = cmin_ocean
plotitem.imshow_cmax = cmax_ocean
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
plotaxes.xlimits = [235, 236.5]
plotaxes.ylimits = [46, 49]
plotaxes.afteraxes = aa
# -----------------------------------------
# Figure for zoom3
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Long Beach", figno=12)
plotfigure.show = False
plotfigure.kwargs = {"figsize": (8, 7)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Long Beach"
plotaxes.scaled = False
# Water
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
# plotitem.show = False
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap(
{-1.0: [0.0, 0.0, 1.0], -0.5: [0.5, 0.5, 1.0], 0.0: [1.0, 1.0, 1.0], 0.5: [1.0, 0.5, 0.5], 1.0: [1.0, 0.0, 0.0]}
)
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = cmin_ocean
plotitem.imshow_cmax = cmax_ocean
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [0]
# Land
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
plotitem.plot_var = geoplot.land
# plotitem.plot_var = 3
land_cmap = colormaps.make_colormap({0.0: [0.0, 0.0, 1.0], 0.5: [1.0, 0.0, 0.0], 1.0: [0.0, 1.0, 0.0]})
plotitem.imshow_cmap = geoplot.land_colors
# plotitem.imshow_cmap = land_cmap
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 10.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [0]
plotaxes.xlimits = [235.90, 235.98]
plotaxes.ylimits = [46.30, 46.39]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, imshow, savefig, plot
from pyclaw.plotters.plottools import plotbox
# addgauges(current_data)
title_hours(current_data)
ticklabel_format(format="plain", useOffset=False)
xticks(rotation=20)
a = gca()
# a.set_aspect(1./cos(46.86*pi/180.))
a.set_aspect(1.0 / cos(46.349 * pi / 180.0))
plot([235.9499], [46.3490], "wo")
# extent = (235.8756, 235.9116, 46.854, 46.8756)
# plotbox(extent)
# imshow(OcostaGE,extent=extent, alpha=0.5)
# extent = (235.81, 235.95, 46.85, 46.95)
# imshow(WestportGE,extent=extent, alpha=0.8)
plotaxes.afteraxes = aa
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type="2d_contour")
# plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.0]
plotitem.amr_contour_colors = ["k"] # color on each level
plotitem.kwargs = {"linestyles": "solid", "linewidths": 2}
plotitem.amr_contour_show = [0, 0, 0, 0, 1, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# -----------------------------------------
# Figure for zoom4
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Berm", figno=13)
plotfigure.show = False
plotfigure.kwargs = {"figsize": (12, 8)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Berm location"
plotaxes.scaled = False
# Water
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
# plotitem.show=False
plotitem.plot_var = geoplot.depth
# plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({0.0: [1.0, 1.0, 1.0], 0.5: [1.0, 0.8, 0.0], 1.0: [1.0, 0.0, 0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 3.0
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
# plotitem.show=False
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 20.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# plotaxes.xlimits = [235.88, 235.905]
# plotaxes.ylimits = [46.855, 46.87]
plotaxes.xlimits = [235.947, 235.951]
plotaxes.ylimits = [46.347, 46.35]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, imshow, savefig, plot
addgauges(current_data)
title_hours(current_data)
ticklabel_format(format="plain", useOffset=False)
xticks(rotation=20)
plot([235.9499], [46.3490], "wo")
# extent = (235.8756, 235.9116, 46.854, 46.8756)
# imshow(OcostaGE,extent=extent, alpha=0.5)
a = gca()
a.set_aspect(1.0 / cos(46.349 * pi / 180.0))
# extent = (235.81, 235.95, 46.85, 46.95)
# imshow(WestportGE,extent=extent, alpha=0.8)
plotaxes.afteraxes = aa
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type="2d_contour")
# plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.0]
plotitem.amr_contour_colors = ["k"] # color on each level
plotitem.kwargs = {"linestyles": "solid", "linewidths": 2}
plotitem.amr_contour_show = [0, 0, 0, 0, 1, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# -----------------------------------------
# Figure for zoom4 speed
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Ocosta speed", figno=14)
plotfigure.show = False
plotfigure.kwargs = {"figsize": (12, 8)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Ocosta"
plotaxes.scaled = False
# Water
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
# plotitem.show=False
def speed(current_data):
from numpy import sqrt, where
q = current_data.q
h = q[:, :, 0]
hu = q[:, :, 1]
hv = q[:, :, 2]
u = where(h > 0.01, hu / h, 0.0)
v = where(h > 0.01, hv / h, 0.0)
speed = sqrt(u ** 2 + v ** 2)
return v
plotitem.plot_var = speed
# plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({0.0: [0.0, 0.0, 1.0], 0.5: [1.0, 1.0, 1.0], 1.0: [1.0, 0.0, 0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = -3.0
plotitem.imshow_cmax = 3.0
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type="2d_imshow")
# plotitem.show=False
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 20.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# plotaxes.xlimits = [235.88, 235.905]
# plotaxes.ylimits = [46.855, 46.87]
plotaxes.xlimits = [235.88, 235.935]
plotaxes.ylimits = [46.845, 46.875]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, imshow, savefig
addgauges(current_data)
title_hours(current_data)
ticklabel_format(format="plain", useOffset=False)
xticks(rotation=20)
# extent = (235.8756, 235.9116, 46.854, 46.8756)
# imshow(OcostaGE,extent=extent, alpha=0.5)
a = gca()
a.set_aspect(1.0 / cos(46.86 * pi / 180.0))
# extent = (235.81, 235.95, 46.85, 46.95)
# imshow(WestportGE,extent=extent, alpha=0.8)
plotaxes.afteraxes = aa
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type="2d_contour")
# plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.0]
plotitem.amr_contour_colors = ["k"] # color on each level
plotitem.kwargs = {"linestyles": "solid", "linewidths": 2}
plotitem.amr_contour_show = [0, 0, 0, 0, 1, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# -----------------------------------------
# Figures for gauges
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="gauge plot", figno=300, type="each_gauge")
# plotfigure.clf_each_gauge = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.ylimits = [-1, 10]
plotaxes.xlimits = [-1, 10]
plotaxes.title = "Surface"
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type="1d_plot")
plotitem.plot_var = 4
plotitem.plotstyle = "b-"
def axes_gauge(current_data):
from pylab import plot, legend, xticks, floor, yticks, xlabel, savefig, xlim, ylim, xlabel, ylabel
t = current_data.t
gaugeno = current_data.gaugeno
xticks(linspace(0, 1, 7), [str(i) for i in range(0, 7, 10)])
xlabel("time (minutes) after quake", fontsize=15)
ylabel("meters", fontsize=15)
ylim(-1, 10)
plotaxes.afteraxes = axes_gauge
# -----------------------------------------
# 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.print_gaugenos = "all" # list of gauges 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 setplot(plotdata):
# --------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
plotdata.clearfigures() # clear any old figures,axes,items dat
# plotdata.format = "netcdf"
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=True)
def title_hours(current_data):
from pylab import title
t = current_data.t
h = t/3600.
title('%5.2f Hours after Quake' % h)
def plotcc(current_data):
from pylab import plot,text
plot([235.8162], [41.745616],'wo')
text(235.8,41.9,'Cr.City',color='w',fontsize=10)
#-----------------------------------------
# Figure for big area
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Pacific', figno=0)
plotfigure.kwargs = {'figsize': (16,4)}
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Pacific'
plotaxes.scaled = True
def aa(current_data):
title_hours(current_data)
if 0:
from pylab import savefig
fname = 'pacific%s.png' % str(current_data.frameno).zfill(4)
savefig(fname)
print 'Saved ',fname
plotaxes.afteraxes = aa
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.1: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.1: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = -0.3
plotitem.imshow_cmax = 0.3
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
plotaxes.xlimits = [132,238]
plotaxes.ylimits = [30,50]
#plotaxes.afteraxes = addgauges
# Add contour lines of bathymetry:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
#plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = linspace(-6000,0,7)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1,0] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(0., 11., 1.)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figure for zoom
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='California', figno=10)
#plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'California'
plotaxes.scaled = True
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.1: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.1: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = -0.3
plotitem.imshow_cmax = 0.3
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
plotaxes.xlimits = [227,237]
plotaxes.ylimits = [35,45]
def af(current_data):
from pylab import savefig,figure
figure(10)
plotcc(current_data)
title_hours(current_data)
addgauges(current_data)
if 0:
fname = '/Users/rjl/OUTPUT/Users/rjl/Dropbox/mygeo/CC/_plots/' +\
'california%s.png' % str(current_data.frameno).zfill(4)
savefig(fname)
print 'Saved ',fname
#plotdata.afterframe = af
plotaxes.afteraxes = af
# Add contour lines of eta:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.surface
from numpy import arange, linspace
plotitem.contour_levels = linspace(-0.3,0.3,13)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1,0] # AMR levels to show contours
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = False
# 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(-4500,0,10)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1,0] # AMR levels to show contours
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(0., 11., 1.)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = False
#-----------------------------------------
# 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.print_gaugenos = 'all' # list of gauges 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
yellow1 = [.98, .96, .01]
tan1 = [.98, .83, .01]
tan2 = [.71, .62, .085]
tan3 = [.65, .56, .07]
tan4 = [.58, .50, .064]
tan5 = [.48, .415, .043]
tan6 = [0.42, 0.36, 0.038]
tan7 = [.36, .233, .029]
brown1 = [.42, .167, .03]
# Colormaps
TSUNAMI_MAX_AMPLITUDE = 0.6
tsunami_colormap = colormaps.make_colormap({
-TSUNAMI_MAX_AMPLITUDE: blue,
0.0: blue_green,
TSUNAMI_MAX_AMPLITUDE: red
})
oso_debris_colormap = colormaps.make_colormap({
0.0: white,
10.0: light_blue,
20.0: blue,
30.0: dark_blue
})
oso_debris_colormap_invert = colormaps.make_colormap({
0.0: dark_blue,
#10.0: blue,
#20.0: light_blue,
30.0: white
def plot_topo_file(topoplotdata):
"""
Read in a topo or bathy file and produce a pcolor map.
"""
import os
import pylab
from pyclaw.data import Data
fname = topoplotdata.fname
topotype = topoplotdata.topotype
if topoplotdata.climits:
# deprecated option
cmin = topoplotdata.climits[0]
cmax = topoplotdata.climits[1]
else:
cmin = topoplotdata.cmin
cmax = topoplotdata.cmax
figno = topoplotdata.figno
addcolorbar = topoplotdata.addcolorbar
addcontour = topoplotdata.addcontour
contour_levels = topoplotdata.contour_levels
xlimits = topoplotdata.xlimits
ylimits = topoplotdata.ylimits
coarsen = topoplotdata.coarsen
imshow = topoplotdata.imshow
gridedges_show = topoplotdata.gridedges_show
neg_cmap = topoplotdata.neg_cmap
pos_cmap = topoplotdata.pos_cmap
print_fname = topoplotdata.print_fname
if neg_cmap is None:
neg_cmap = colormaps.make_colormap({
cmin: [0.3, 0.2, 0.1],
0: [0.95, 0.9, 0.7]
})
if pos_cmap is None:
pos_cmap = colormaps.make_colormap({
0: [.5, .7, 0],
cmax: [.2, .5, .2]
})
if abs(topotype) == 1:
X, Y, topo = topotools.topofile2griddata(fname, topotype)
topo = pylab.flipud(topo)
Y = pylab.flipud(Y)
x = X[0, :]
y = Y[:, 0]
xllcorner = x[0]
yllcorner = y[0]
cellsize = x[1] - x[0]
elif abs(topotype) == 3:
file = open(fname, 'r')
lines = file.readlines()
ncols = int(lines[0].split()[0])
nrows = int(lines[1].split()[0])
xllcorner = float(lines[2].split()[0])
yllcorner = float(lines[3].split()[0])
cellsize = float(lines[4].split()[0])
NODATA_value = int(lines[5].split()[0])
print "Loading file ", fname
print " nrows = %i, ncols = %i" % (nrows, ncols)
topo = pylab.loadtxt(fname, skiprows=6, dtype=float)
print " Done loading"
if 0:
topo = []
for i in range(nrows):
topo.append(pylab.array(lines[6 + i], ))
print '+++ topo = ', topo
topo = pylab.array(topo)
topo = pylab.flipud(topo)
x = pylab.linspace(xllcorner, xllcorner + ncols * cellsize, ncols)
y = pylab.linspace(yllcorner, yllcorner + nrows * cellsize, nrows)
print "Shape of x, y, topo: ", x.shape, y.shape, topo.shape
else:
raise Exception("*** Only topotypes 1 and 3 supported so far")
if coarsen > 1:
topo = topo[slice(0, nrows, coarsen), slice(0, ncols, coarsen)]
x = x[slice(0, ncols, coarsen)]
y = y[slice(0, nrows, coarsen)]
print "Shapes after coarsening: ", x.shape, y.shape, topo.shape
if topotype < 0:
topo = -topo
if figno:
pylab.figure(figno)
if topoplotdata.imshow:
color_norm = Normalize(cmin, cmax, clip=True)
xylimits = (x[0], x[-1], y[0], y[-1])
#pylab.imshow(pylab.flipud(topo.T), extent=xylimits, \
pylab.imshow(pylab.flipud(topo), extent=xylimits, \
cmap=cmap, interpolation='nearest', \
norm=color_norm)
else:
neg_topo = ma.masked_where(topo > 0., topo)
all_masked = (ma.count(neg_topo) == 0)
if not all_masked:
pylab.pcolormesh(x, y, neg_topo, cmap=neg_cmap)
pylab.clim([cmin, 0])
if addcolorbar:
pylab.colorbar()
pos_topo = ma.masked_where(topo < 0., topo)
all_masked = (ma.count(pos_topo) == 0)
if not all_masked:
pylab.pcolormesh(x, y, pos_topo, cmap=pos_cmap)
pylab.clim([0, cmax])
if addcolorbar:
pylab.colorbar()
pylab.axis('scaled')
if addcontour:
pylab.contour(x, y, topo, levels=contour_levels, colors='k')
if gridedges_show:
pylab.plot([x[0], x[-1]], [y[0], y[0]], 'k')
pylab.plot([x[0], x[-1]], [y[-1], y[-1]], 'k')
pylab.plot([x[0], x[0]], [y[0], y[-1]], 'k')
pylab.plot([x[-1], x[-1]], [y[0], y[-1]], 'k')
if print_fname:
fname2 = os.path.splitext(fname)[0]
pylab.text(xllcorner + cellsize,
yllcorner + cellsize,
fname2,
color='m')
topodata = Data()
topodata.x = x
topodata.y = y
topodata.topo = topo
return topodata
def setplot(plotdata):
# --------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
plotdata.clearfigures() # clear any old figures,axes,items dat
# plotdata.format = "netcdf"
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=True)
def title_hours(current_data):
from pylab import title
t = current_data.t
h = t/3600.
title('%5.2f Hours after Quake' % h)
def plotcc(current_data):
from pylab import plot,text
plot([235.8162], [41.745616],'wo')
text(235.8,41.9,'Cr.City',color='w',fontsize=10)
#-----------------------------------------
# Figure for big area
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Pacific', figno=0)
plotfigure.kwargs = {'figsize': (16,4)}
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Pacific'
plotaxes.scaled = True
def aa(current_data):
title_hours(current_data)
if 0:
from pylab import savefig
fname = 'pacific%s.png' % str(current_data.frameno).zfill(4)
savefig(fname)
print 'Saved ',fname
plotaxes.afteraxes = aa
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.1: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.1: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = -0.3
plotitem.imshow_cmax = 0.3
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
plotaxes.xlimits = [132,238]
plotaxes.ylimits = [30,50]
#plotaxes.afteraxes = addgauges
# Add contour lines of bathymetry:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
#plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = linspace(-6000,0,7)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1,0] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(0., 11., 1.)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figure for zoom
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='California', figno=10)
#plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'California'
plotaxes.scaled = True
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.1: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.1: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = -0.3
plotitem.imshow_cmax = 0.3
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
plotaxes.xlimits = [227,237]
plotaxes.ylimits = [35,45]
def af(current_data):
from pylab import savefig,figure
figure(10)
plotcc(current_data)
title_hours(current_data)
addgauges(current_data)
if 0:
fname = '/Users/rjl/OUTPUT/Users/rjl/Dropbox/mygeo/CC/_plots/' +\
'california%s.png' % str(current_data.frameno).zfill(4)
savefig(fname)
print 'Saved ',fname
#plotdata.afterframe = af
plotaxes.afteraxes = af
# Add contour lines of eta:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.surface
from numpy import arange, linspace
plotitem.contour_levels = linspace(-0.3,0.3,13)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1,0] # AMR levels to show contours
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = False
# 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(-4500,0,10)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,1,0] # AMR levels to show contours
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(0., 11., 1.)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles':'solid'}
plotitem.amr_contour_show = [0,0,0,1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = False
#-----------------------------------------
# Figure for zoom2
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Crescent City', figno=11)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Crescent City'
plotaxes.scaled = True
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.1: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.1: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = -1.0
plotitem.imshow_cmax = 1.0
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
plotaxes.xlimits = [235.76,235.84]
plotaxes.ylimits = [41.72,41.77]
plotaxes.afteraxes = addgauges
# # Add contour lines of bathymetry:
# plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
# plotitem.plot_var = geoplot.topo
# from numpy import arange, linspace
# plotitem.contour_levels = arange(-10., 0., 1.)
# plotitem.amr_contour_colors = ['k'] # color on each level
# plotitem.kwargs = {'linestyles':'solid'}
# plotitem.amr_contour_show = [0,0,0,1] # show contours only on finest level
# plotitem.gridlines_show = 0
# plotitem.gridedges_show = 0
# plotitem.show = True
# # Add contour lines of topography:
# plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
# plotitem.plot_var = geoplot.topo
# from numpy import arange, linspace
# plotitem.contour_levels = arange(0., 11., 1.)
# plotitem.amr_contour_colors = ['g'] # color on each level
# plotitem.kwargs = {'linestyles':'solid'}
# plotitem.amr_contour_show = [0,0,0,1] # show contours only on finest level
# plotitem.gridlines_show = 0
# plotitem.gridedges_show = 0
# plotitem.show = True
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='gauge plot', figno=300, \
type='each_gauge')
plotfigure.clf_each_gauge = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [9*3600, 13*3600]
#plotaxes.xlimits = [8*3600, 15*3600]
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 fix_gauge(current_data):
from pylab import plot, legend, xticks, floor, yticks
t = current_data.t
gaugeno = current_data.gaugeno
if gaugeno == 19750:
plot(TG_19750[:,0],TG_19750[:,1],'r')
legend(('GeoClaw','Tide Gauge'),loc='lower left')
#plot([0,10800],[0,0],'k')
n = int(floor(t.max()/3600.) + 2)
xticks([3600*i for i in range(n)],[str(i) for i in range(n)],\
fontsize=15)
yticks(fontsize=15)
plotaxes.afteraxes = fix_gauge
#-----------------------------------------
# Figure for contour plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='contour', figno=1)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0,1]
plotaxes.ylimits = [0,1]
plotaxes.title = 'Solution'
plotaxes.scaled = True
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.surface
plotitem.contour_nlevels = 40
plotitem.contour_min = -0.1
plotitem.contour_max = 0.1
plotitem.amr_contour_colors = ['r','k','b'] # color on each level
plotitem.amr_contour_show = [0,1] # show lines on each level?
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
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_grid_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = False
# Fixed grid plots:
# -----------------
if setplotfg is not None:
# Repeat as desired for other fixed grids...
# These show up when using 'make .plots'
otherfig = plotdata.new_otherfigure('Fixed Grid 1')
fgno = 1
sfgno = str(fgno).zfill(2) # e.g. '01'
otherfig.fname = '_PlotIndex_FixedGrid%s.html' % sfgno
def make_fgplots(plotdata):
fgdata = setplotfg(fgno, outdir=plotdata.outdir)
# See the setplotfg function for setting up fixed grid plots
fgdata.fg2html(framenos='all')
otherfig.makefig = make_fgplots
#-----------------------------------------
# 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.print_gaugenos = 'all' # list of gauges 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 setplot(plotdata):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
import os
import numpy as np
import matplotlib.pyplot as plt
from pyclaw.plotters import colormaps, geoplot
from pyclaw.data import Data
amrdata = Data(os.path.join(plotdata.outdir,'amr2ez.data'))
hurricane_data = Data(os.path.join(plotdata.outdir,'hurricane.data'))
multilayer_data = Data(os.path.join(plotdata.outdir,'multilayer.data'))
if multilayer_data.bathy_type == 1:
ref_lines = [multilayer_data.bathy_location]
elif multilayer_data.bathy_type == 2:
ref_lines = [multilayer_data.x0,multilayer_data.x1,multilayer_data.x2]
else:
ref_lines = []
plotdata.clearfigures()
plotdata.clear_frames = False
plotdata.clear_figs = True
plotdata.save_frames = False
# ========================================================================
# Generic helper functions
# ========================================================================
def bathy_ref_lines(current_data):
plt.hold(True)
y = [amrdata.ylower,amrdata.yupper]
for ref_line in ref_lines:
plt.plot([ref_line,ref_line],y,'y--')
plt.hold(False)
def day_figure_title(current_data):
t = current_data.t
title = current_data.plotaxes.title
plt.title('%s at time t = %s days' % (title,str(t/(3600.0*24.0))))
def m_to_km_labels(current_data=None):
plt.xlabel('km')
plt.ylabel('km')
locs,labels = plt.xticks()
labels = locs/1.e3
plt.xticks(locs,labels)
locs,labels = plt.yticks()
labels = locs/1.e3
plt.yticks(locs,labels)
def pcolor_afteraxes(current_data):
day_figure_title(current_data)
m_to_km_labels()
bathy_ref_lines(current_data)
# gauge_locations(current_data)
def contour_afteraxes(current_data):
day_figure_title(current_data)
m_to_km_labels()
bathy_ref_lines(current_data)
# ========================================================================
# Gauge functions
# ========================================================================
def gauge_locations(current_data,gaugenos='all'):
from pyclaw.plotters import gaugetools
plt.hold(True)
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos=gaugenos, format_string='kx', add_labels=True)
plt.hold(False)
def gaugetopo(current_data):
q = current_data.q
h = q[:,0]
eta = q[:,3]
topo = eta - h
return topo
def gauge_afteraxes(current_data):
# Change time to hours
plt.xlabel('t (days)')
plt.ylabel('m')
locs,labels = plt.xticks()
# import pdb; pdb.set_trace()
labels = np.trunc(locs/(24.0*3600.0))
# locs = np.linspace(-12.0,40,52)
# labels = range(-12,41)
plt.xticks(locs,labels)
# Add sea level line
# t = current_data.t
plt.hold(True)
plt.plot([0,0],[0,40],'k-')
plt.hold(False)
# ========================================================================
# Water helper functions
# ========================================================================
def b(cd):
return cd.q[:,:,3] - cd.q[:,:,0]
def extract_eta(h,eta,DRY_TOL=10**-3):
index = np.nonzero((np.abs(h) < DRY_TOL) + (h == np.nan))
eta[index[0],index[1]] = np.nan
return eta
def extract_velocity(h,hu,DRY_TOL=10**-8):
# u = np.ones(hu.shape) * np.nan
u = np.zeros(hu.shape)
index = np.nonzero((np.abs(h) > DRY_TOL) * (h != np.nan))
u[index[0],index[1]] = hu[index[0],index[1]] / h[index[0],index[1]]
return u
def eta(cd):
return extract_eta(cd.q[:,:,0],cd.q[:,:,3])
def water_u(cd):
# index = np.nonzero(current_data.q[:,:,0] > 1e-6)
# u = np.zeros(current_data.q[:,:,1].shape)
# u[index] = current_data.q[index,1] / current_data.q[index,0]
# return u
return extract_velocity(cd.q[:,:,0],cd.q[:,:,1])
# return np.where(abs(current_data.q[:,:,0]) > 10**-16,
# current_data.q[:,:,1] / current_data.q[:,:,0],
# 0.0)
def water_v(cd):
# index = np.nonzero(current_data.q[:,:,0] > 1e-6)
# v = np.zeros(current_data.q[:,:,2].shape)
# v[index] = current_data.q[index,2] / current_data.q[index,0]
# return u
return extract_velocity(cd.q[:,:,0],cd.q[:,:,2])
# return np.where(abs(current_data.q[:,:,0]) > 10**-16,
# current_data.q[:,:,2] / current_data.q[:,:,0],
# 0.0)
def water_speed(current_data):
u = water_u(current_data)
v = water_v(current_data)
return np.sqrt(u**2+v**2)
def water_quiver(current_data):
u = water_u(current_data)
v = water_v(current_data)
plt.hold(True)
Q = plt.quiver(current_data.x[::2,::2],current_data.y[::2,::2],
u[::2,::2],v[::2,::2])
max_speed = np.max(np.sqrt(u**2+v**2))
label = r"%s m/s" % str(np.ceil(0.5*max_speed))
plt.quiverkey(Q,0.15,0.95,0.5*max_speed,label,labelpos='W')
plt.hold(False)
def wind_x(cd):
return cd.q[:,:,4]
def wind_y(cd):
return cd.q[:,:,5]
def wind_speed(cd):
return np.sqrt(wind_x(cd)**2 + wind_y(cd)**2)
# ========================================================================
# Profile functions
# ========================================================================
class PlotProfile(object):
def __init__(self,slice_value = 0.0):
self.slice_value = slice_value
def slice_index(self,cd):
if cd.grid.y.lower < self.slice_value < cd.grid.y.upper:
return int((self.slice_value - cd.grid.y.lower) / cd.dy - 0.5)
else:
return None
def bathy_profile(self,current_data):
index = self.slice_index(current_data)
if index:
return current_data.x[:,index], b(current_data)[:,index]
else:
return None, None
def surface_profile(self,current_data):
index = self.slice_index(current_data)
if index:
return current_data.x[:,index], eta(current_data)[:,index]
else:
return None, None
# ========================================================================
# Plot items
# ========================================================================
def add_surface_elevation(plotaxes,bounds=None,plot_type='pcolor'):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
# plotitem.plotvar = eta
plotitem.plot_var = geoplot.surface
plotitem.imshow_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
elif plot_type == 'contour':
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.surface
if bounds is None:
plotitem.contour_levels = [-2.5,-1.5,-0.5,0.5,1.5,2.5]
# plotitem.contour_nlevels = 21
# plotitem.contour_min = -2.0
# plotitem.contour_max = 2.0
# plotitem.kwargs = {''}
plotitem.amr_contour_show = [1,1,1]
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_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']
def add_speed(plotaxes,bounds=None,plot_type='pcolor'):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = water_speed
# plotitem.plot_var = 1
plotitem.imshow_cmap = plt.get_cmap('PuBu')
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
elif plot_type == 'quiver':
plotitem = plotaxes.new_plotitem(plot_type='2d_quiver')
plotitem.quiver_var_x = water_u
plotitem.quiver_var_y = water_v
plotitem.amr_quiver_show = [4,10,10]
plotitem.amr_show_key = [True,True,False]
plotitem.key_units = 'm/s'
elif plot_type == 'contour':
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = water_speed
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_gridlines_show = [0,0,0]
plotitem.amr_gridedges_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']
def add_x_velocity(plotaxes,plot_type='pcolor',bounds=None):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = water_u
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
plotitem.add_colorbar = True
plotitem.imshow_cmap = plt.get_cmap('PiYG')
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
elif plot_type == 'contour':
pass
def add_y_velocity(plotaxes,plot_type='pcolor',bounds=None):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = water_v
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
plotitem.imshow_cmap = plt.get_cmap('PiYG')
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
elif plot_type == 'contour':
pass
def add_wind(plotaxes,bounds=None,plot_type='pcolor'):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = wind_speed
plotitem.imshow_cmap = plt.get_cmap('PuBu')
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
plotitem.add_colorbar = True
plotitem.amr_imshow_show = [1,1,1]
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
elif plot_type == 'contour':
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = wind_speed
plotitem.contour_nlevels = hurricane_data.max_wind_nest
plotitem.countour_min = hurricane_data.wind_refine[0]
plotitem.gridedges_show = 1
elif plot_type == 'quiver':
plotitem = plotaxes.new_plotitem(plot_type='2d_quiver')
plotitem.quiver_var_x = wind_x
plotitem.quiver_var_y = wind_y
plotitem.amr_quiver_show = [0,0,1]
plotitem.amr_quiver_key_show = [True,False,False]
plotitem.amr_quiver_key_units = 'm/s'
def add_vorticity(plotaxes,bounds=None,plot_type="pcolor"):
if plot_type == 'pcolor' or plot_type == 'imshow':
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = 9
plotitem.imshow_cmap = plt.get_cmap('PRGn')
if bounds is not None:
plotitem.imshow_cmin = bounds[0]
plotitem.imshow_cmax = bounds[1]
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
def add_land(plotaxes,plot_type='pcolor'):
if plot_type == 'pcolor':
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
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_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
elif plot_type == 'contour':
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_grid_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# Limits
xlimits = [amrdata.xlower,amrdata.xupper]
ylimits = [amrdata.ylower,amrdata.yupper]
multilayer_data.eta = eta
# surface_limits = [-0.15,0.15]
# speed_limits = [0.0,0.1]
surface_limits = None
speed_limits = None
vorticity_limits = [-1.e-2,1.e-2]
# ========================================================================
# Surface Elevation
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='Surface', figno=0)
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Surface'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
add_surface_elevation(plotaxes,bounds=surface_limits)
add_land(plotaxes)
# ========================================================================
# Water Speed
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='speed', figno=100)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
# Speed
add_speed(plotaxes,bounds=speed_limits)
# Land
add_land(plotaxes)
# X-Velocity
plotfigure = plotdata.new_plotfigure(name='velocity_x',figno=101)
plotfigure.show = True
plotfigure.kwargs = {'figsize':(14,4)}
# X Velocity
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(121)'
plotaxes.title = 'X-Velocity'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
add_x_velocity(plotaxes,bounds=speed_limits)
add_land(plotaxes)
# Y Velocity
plotaxes = plotfigure.new_plotaxes()
plotaxes.axescmd = 'subplot(122)'
plotaxes.title = 'Y-Velocity'
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
add_y_velocity(plotaxes,bounds=speed_limits)
add_land(plotaxes)
# ========================================================================
# Wind speed
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='wind',figno=2)
plotfigure.show = True
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = "Wind"
plotaxes.scaled = True
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
plotaxes.afteraxes = pcolor_afteraxes
# Wind
add_wind(plotaxes)
add_land(plotaxes)
# ========================================================================
# Profile Plots
# ========================================================================
# Profile variables
def profile_afteraxes(current_data):
day_figure_title(current_data)
loc,label = plt.xticks()
label = loc/1.e3
plt.xticks(loc,label)
plt.xlabel('km')
if current_data.plotaxes.title == 'Wind':
plt.ylabel('m/s')
else:
plt.ylabel('m')
t = current_data.t
# Hurricane eye
x = t * hurricane_data.hurricane_velocity[0] + hurricane_data.R_eye_init[0]
plt.hold(True)
plt.plot(x,0.0,'r+')
plt.hold(False)
def remove_labels_profile(cd,direction='x'):
plt.hold(True)
if direction == 'x':
plt.xlabel('')
locs,labels = plt.xticks()
# labels = np.flipud(locs)/1.e3
labels = ['' for i in xrange(len(locs))]
plt.xticks(locs,labels)
plt.ylabel('m')
elif direction == 'y':
plt.ylabel('')
locs,labels = plt.yticks()
# labels = np.flipud(locs)/1.e3
labels = ['' for i in xrange(len(locs))]
plt.yticks(locs,labels)
plt.xlabel('m')
plt.hold(False)
def labels_profile(cd,direction='x'):
if direction == 'x':
loc,label = plt.xticks()
label = loc/1.e3
plt.xticks(loc,label)
plt.xlabel('km')
if cd.plotaxes.title == 'Wind':
plt.ylabel('m/s')
else:
plt.ylabel('m')
elif direction == 'y':
loc,label = plt.yticks()
label = loc/1.e3
plt.yticks(loc,label)
plt.ylabel('km')
if cd.plotaxes.title == 'Wind':
plt.xlabel('m/s')
else:
plt.xlabel('m')
def profile_afteraxes(current_data):
day_figure_title(current_data)
labels_profile(current_data)
# bathy_ref_lines_profile(current_data,surface_limits)
plotfigure = plotdata.new_plotfigure(name='profile', figno=4)
plotfigure.show = False
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Profiles'
plotaxes.xlimits = xlimits
# plotaxes.ylimits = surface_limits
plotaxes.afteraxes = profile_afteraxes
profile_plot = PlotProfile(0.0)
plotitem = plotaxes.new_plotitem(plot_type="1d_from_2d_data")
plotitem.map_2d_to_1d = profile_plot.surface_profile
plotitem.amr_plotstyle = ['-','-.','+','x','.']
plotitem.color = 'b'#(0.2,0.8,1.0)
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.map_2d_to_1d = profile_plot.bathy_profile
plotitem.amr_plotstyle = ['-','-.','+','x','.']
plotitem.color = 'k'
# ========================================================================
# Bathy Profile
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='bathy_profile',figno=20)
plotfigure.show = False
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [amrdata.xlower,amrdata.xupper]
plotaxes.title = "Bathymetry Profile"
plotaxes.scaled = 'equal'
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = b
plotitem.imshow_cmap = plt.get_cmap('earth')
plotitem.imshow_cmin = -3300
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = True
plotitem.amr_imshow_show = [1,1,1]
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
plotitem.show = True
# ========================================================================
# Figure for grids alone
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='grids', figno=11)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [amrdata.xlower,amrdata.xupper]
plotaxes.xlimits = [amrdata.ylower,amrdata.yupper]
plotaxes.title = 'grids'
plotaxes.afteraxes = pcolor_afteraxes
plotaxes.scaled = True
# Set up for item on these axes:
plotitem = plotaxes.new_plotitem(plot_type='2d_grid')
# plotitem.amr_grid_bgcolor = ['#ffeeee', '#eeeeff', '#eeffee']
plotitem.amr_grid_bgcolor = ['blue','red','green','cyan','yellow']
plotitem.amr_gridlines_show = [1,1,0,0,0,0]
plotitem.amr_gridedges_show = 1
# ========================================================================
# Figures for momentum
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='x-momentum', figno=13)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'X-Velocity'
plotaxes.scaled = True
plotaxes.xlimits = [amrdata.xlower,amrdata.xupper]
plotaxes.ylimits = [amrdata.ylower,amrdata.yupper]
plotaxes.afteraxes = pcolor_afteraxes
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
# plotitem.plot_var = geoplot.surface
plotitem.plot_var = water_u
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_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
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_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
plotfigure = plotdata.new_plotfigure(name='y-momentum', figno=14)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Y-Velocity'
plotaxes.scaled = True
plotaxes.xlimits = [amrdata.xlower,amrdata.xupper]
plotaxes.ylimits = [amrdata.ylower,amrdata.yupper]
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_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
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_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1,1,1]
# ========================================================================
# Contour plot for surface
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='contour_surface',figno=15)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Surface'
plotaxes.scaled = True
plotaxes.xlimits = [amrdata.xlower,amrdata.xupper]
plotaxes.ylimits = [amrdata.ylower,amrdata.yupper]
plotaxes.afteraxes = contour_afteraxes
# Surface
add_surface_elevation(plotaxes,plot_type='contour')
# Land
add_land(plotaxes,plot_type='contour')
# ========================================================================
# Contour plot for speed
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='contour_speed',figno=16)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Current'
plotaxes.scaled = True
plotaxes.xlimits = [amrdata.xlower,amrdata.xupper]
plotaxes.ylimits = [amrdata.ylower,amrdata.yupper]
plotaxes.afteraxes = contour_afteraxes
# Surface
add_surface_elevation(plotaxes,plot_type="contour")
# Land
add_land(plotaxes,plot_type='contour')
# ========================================================================
# 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 = [amrdata.xlower,amrdata.xupper]
plotaxes.ylimits = [amrdata.ylower,amrdata.yupper]
plotaxes.afteraxes = pcolor_afteraxes
# Vorticity
add_vorticity(plotaxes)
# Land
add_land(plotaxes)
# ========================================================================
# Figures for gauges
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=300, \
type='each_gauge')
plotfigure.show = False
plotfigure.clf_each_gauge = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [0.0,40.0*3600.0]
# plotaxes.ylimits = [0,150.0]
plotaxes.ylimits = [-3.0, 3.0]
plotaxes.title = 'Surface'
plotaxes.afteraxes = gauge_afteraxes
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'r-'
# # Plot topo as green curve:
# plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
# plotitem.plot_var = gaugetopo
# plotitem.plotstyle = 'g+'
#-----------------------------------------
# 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?
return plotdata
def plotfg(fgno, frameno, outdir='_output', save_png=False):
fname = "fort.fg%s_%s" % (str(fgno).zfill(2), str(frameno).zfill(4))
fname = os.path.join(outdir, fname)
if not os.path.exists(fname):
print "*** Did not find file ", fname, " in directory ", outdir
raise IOError("Missing fixed grid output file")
print "Plotting fixed grid output from ", fname
# Read parameters from header:
file = open(fname, 'r')
line = file.readline()
t = float(line.split()[0])
print 't = %s' % t
line = file.readline()
mx = int(line.split()[0])
line = file.readline()
my = int(line.split()[0])
line = file.readline()
xlow = float(line.split()[0])
line = file.readline()
ylow = float(line.split()[0])
line = file.readline()
xhi = float(line.split()[0])
line = file.readline()
yhi = float(line.split()[0])
if 0:
print 'mx = %s' % mx
print 'my = %s' % my
print 'xlow = %s' % xlow
print 'ylow = %s' % ylow
print 'xhi = %s' % xhi
print 'yhi = %s' % yhi
file.close()
x = linspace(xlow, xhi, mx + 1)
y = linspace(ylow, yhi, my + 1)
dx = x[1] - x[0]
dy = y[1] - y[0]
xcenter = x[:-1] + dx / 2.
ycenter = y[:-1] + dy / 2.
d = loadtxt(fname, skiprows=8)
h = reshape(d[:, 0], (my, mx))
B = reshape(d[:, 3], (my, mx))
eta = reshape(d[:, 4], (my, mx))
surface = ma.masked_where(isnan(eta), eta)
land = ma.masked_where(h > drytol, B)
# plot commands:
# ==============
# ===================================================
# Adjust these:
# Define function to plot topo contours for use in multiple places:
def add_contours():
clines = linspace(-20, 20, 21)
contour(xcenter, ycenter, B, clines, colors='k')
contour(xcenter, ycenter, B, [0.], colors='k', linewidths=2)
# Set colormaps:
water_cmap = geoplot.tsunami_colormap
land_cmap = geoplot.land_colors
seafloor_cmap = geoplot.seafloor_colormap
inundated_cmap = colormaps.make_colormap({0.: [1, .9, .9], 1.: [1, 0, 0]})
# ===================================================
figno = 150
figure(figno)
clf()
if ma.count(surface) != 0:
pcolormesh(x, y, surface, cmap=water_cmap)
clim((-5, 5))
colorbar()
if ma.count(land) != 0:
pcolormesh(x, y, land, cmap=land_cmap)
#clim((-0.02,0.02))
add_contours()
ncols = d.shape[1]
axis('scaled')
title('Surface on fixed grid %s at time = %8.5f' % (fgno, t))
xlim((xlow, xhi))
ylim((ylow, yhi))
if save_png:
fname = 'FixedGrid%sFrame%sFig%s.png' \
% (str(fgno).zfill(2), str(frameno).zfill(4), figno)
savefig(fname)
print "Saved figure as ", fname
return_fg = True # return all the fg arrays for other purposes?
if return_fg:
fg = empty((my, mx, ncols), dtype=float)
for col in range(ncols):
fg[:, :, col] = reshape(d[:, col], (my, mx))
if ncols > 5:
etamin = reshape(d[:, 5], (my, mx))
etamax = reshape(d[:, 6], (my, mx))
#etamax2 = where(B<0, 1., etamax)
etamax2 = where(B < 0, 1., etamax)
# Add red contour of maximum eta
#contour(xcenter,ycenter,etamax2,[drytol],colors='r',linewidths=2)
# Add brown contour of minimum eta
#contour(xcenter,ycenter,etamin-B,[exposed_tol],colors=([.9,.8,.2],),linewidths=2)
# Determine exposed and inundatated regions:
exposed = ma.masked_where(((B > 0) | (etamin > B + exposed_tol)),
etamin)
inundated = ma.masked_where(((B < 0) | (etamax < B + drytol)), etamax)
figno = 151
figure(figno)
clf()
if ma.count(inundated) != 0:
pcolormesh(x, y, inundated, cmap=inundated_cmap)
clim((0, 5))
colorbar()
add_contours()
# Add red contour of maximum eta
#contour(xcenter,ycenter,etamax2,[drytol],colors='r',linewidths=2)
title("Inundated region for t <= %8.5f" % t)
axis('scaled')
xlim((xlow, xhi))
ylim((ylow, yhi))
if save_png:
fname = 'FixedGrid%sFrame%sFig%s.png' \
% (str(fgno).zfill(2), str(frameno).zfill(4), figno)
savefig(fname)
print "Saved figure as ", fname
figno = 152
figure(figno)
clf()
if ma.count(exposed) != 0:
pcolormesh(x, y, exposed, cmap=seafloor_cmap)
#clim((-0.02,0.02))
colorbar()
add_contours()
# Add brown contour of minimum eta
#contour(xcenter,ycenter,etamin-B,[exposed_tol],colors=([.9,.8,.2],),linewidths=2)
title("Exposed seabed for t <= %8.5f" % t)
axis('scaled')
xlim((xlow, xhi))
ylim((ylow, yhi))
if save_png:
fname = 'FixedGrid%sFrame%sFig%s.png' \
% (str(fgno).zfill(2), str(frameno).zfill(4), figno)
savefig(fname)
print "Saved figure as ", fname
return fg
def setplot(plotdata):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
from numpy import linspace
plotdata.clearfigures() # clear any old figures,axes,items data
# To plot gauge locations on imshow or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=True)
# ========================================================================
# Water Velocity Helper Functions
# ========================================================================
def water_velocity(current_data,DRY_TOL=1e-6):
r"""Calculate velocity from the momentum and depth
Calculates the x and y velocities from the momenta. A mask is
constructed so that division by a small depth is avoided, controlled
by the optional keyword argument DRY_TOL (default = 1e-6). A check
for NaNs is also made. Any point not satisfying either of these
criteria is set to 0.0.
returns numpy.ndarray, nump.ndarray
"""
h = current_data.q[:,:,0]
hu = current_data.q[:,:,1]
hv = current_data.q[:,:,2]
u = np.zeros(hu.shape)
v = np.zeros(hv.shape)
index = np.nonzero((np.abs(h) > DRY_TOL) * (h != np.nan))
u[index[0],index[1]] = hu[index[0],index[1]] / h[index[0],index[1]]
v[index[0],index[1]] = hv[index[0],index[1]] / h[index[0],index[1]]
return u,v
def vorticity(current_data):
r"""Calculate vorticity of velocity field
Using matrix operations, calculate u_y + v_x, note that second order,
centered differences are used for interior points and forward and
backward differences for the boundary values.
returns numpy.ndarray of shape of u and v
"""
u,v = water_velocity(current_data)
dx = current_data.dx
dy = current_data.dy
u_y = np.zeros(u.shape)
u_y[:,0] = (-3.0*u[:,0] + 4.0 * u[:,1] - u[:,2]) / (2.0 * dy)
u_y[:,-1] = (u[:,-3] - 4.0 * u[:,-2] + 3.0 * u[:,-1]) / (2.0 * dy)
u_y[:,1:-1] = (u[:,2:] - u[:,0:-2]) / (2.0 * dy)
v_x = np.zeros(v.shape)
v_x[0,:] = (-3.0*v[0,:] + 4.0 * v[1,:] - v[2,:]) / (2.0 * dx)
v_x[-1,:] = (u[-3,:] - 4.0 * u[-2,:] + 3.0 * u[-1,:]) / (2.0 * dx)
v_x[1:-1,:] = (v[2:,:] - v[0:-2,:]) / (2.0 * dx)
return v_x - u_y
def water_speed(current_data):
u,v = water_velocity(current_data)
return np.sqrt(u**2+v**2)
def water_quiver(current_data):
u = water_u(current_data)
v = water_v(current_data)
plt.hold(True)
Q = plt.quiver(current_data.x[::2,::2],current_data.y[::2,::2],
u[::2,::2],v[::2,::2])
max_speed = np.max(np.sqrt(u**2+v**2))
label = r"%s m/s" % str(np.ceil(0.5*max_speed))
plt.quiverkey(Q,0.15,0.95,0.5*max_speed,label,labelpos='W')
plt.hold(False)
#-----------------------------------------
# Figure for imshow plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='full domain', figno=0)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('imshow')
plotaxes.title = 'Surface'
plotaxes.scaled = False
def fixup(current_data):
import pylab
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)
pylab.plot([139.7],[35.6],'wo',markersize=10)
pylab.text(138.2,35.9,'Tokyo',color='w',fontsize=25)
x_airport = 140.9317
y_airport = 38.1389
pylab.plot([x_airport],[y_airport],'wo',markersize=4)
pylab.text(x_airport-.15,y_airport+.04,'Airport',color='w',fontsize=15)
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = -1.0
plotitem.imshow_cmax = 1.0
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.gridedges_show = 1
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotitem.gridedges_show = 1
plotaxes.xlimits = [138,148]
plotaxes.ylimits = [34,42]
# 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.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figure for zoom plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Sendai Bay', figno=1)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('imshow')
plotaxes.title = 'Surface'
plotaxes.scaled = False
def fixup(current_data):
import pylab
#addgauges(current_data)
t = current_data.t
t = t / 3600. # hours
pylab.title('Surface at %4.2f hours' % t, fontsize=20)
x_airport = 140.9317
y_airport = 38.1389
pylab.plot([x_airport],[y_airport],'wo',markersize=10)
pylab.text(x_airport-.05,y_airport+.04,'Airport',color='w',fontsize=25)
#addgauges(current_data)
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = -1.0
plotitem.imshow_cmax = 1.0
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.gridedges_show = 1
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotitem.gridedges_show = 1
plotaxes.xlimits = [140.8,141.8]
plotaxes.ylimits = [37.3,38.6]
# 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.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figure for zoom plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Airport', figno=2)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('imshow')
plotaxes.title = 'Surface'
plotaxes.scaled = False
def fixup(current_data):
import pylab
#addgauges(current_data)
t = current_data.t
t = t / 3600. # hours
pylab.title('Surface at %4.2f hours' % t, fontsize=20)
x_airport = 140.9317
y_airport = 38.1389
pylab.plot([x_airport],[y_airport],'wo',markersize=10)
pylab.text(x_airport,y_airport+.01,'Airport',color='w',fontsize=25)
addgauges(current_data)
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = -1.0
plotitem.imshow_cmax = 1.0
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.gridedges_show = 1
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0,0,0]
plotitem.gridedges_show = 1
plotaxes.xlimits = [140.85,141.0]
plotaxes.ylimits = [38.08,38.20]
# 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.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=300, \
type='each_gauge')
plotfigure.clf_each_gauge = False
# 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
t = current_data.t
#legend(('surface','topography'),loc='lower left')
plot(t, 0*t, 'k')
n = floor(t.max()/3600.) + 2
xticks([3600*i for i in range(n)])
plotaxes.afteraxes = add_zeroline
# ========================================================================
# Water Current Plots
# ========================================================================
max_speed = 5.0
# Full figure
plotfigure = plotdata.new_plotfigure(name='full_currents', figno=400)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents Full Domain'
plotaxes.scaled = True
plotaxes.xlimits = [138,148]
plotaxes.ylimits = [34,42]
# Speed
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = water_speed
plotitem.imshow_cmap = plt.get_cmap('PuBu')
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = max_speed
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# plotitem.aftergrid = water_quiver
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.add_colorbar = False
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
# ========================================================================
# Zoomed Figure - Sendai Bay
plotfigure = plotdata.new_plotfigure(name='sendai_bay_currents', figno=401)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents Sendai Bay'
plotaxes.scaled = True
plotaxes.xlimits = [140.8,141.8]
plotaxes.ylimits = [37.3,38.6]
# Speed
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = water_speed
plotitem.imshow_cmap = plt.get_cmap('PuBu')
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = max_speed
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.add_colorbar = False
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
# ========================================================================
# Zoomed Figure - Airport
plotfigure = plotdata.new_plotfigure(name='airport_currents', figno=402)
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Currents Airport'
plotaxes.scaled = True
plotaxes.xlimits = [140.85,141.0]
plotaxes.ylimits = [38.08,38.20]
# Speed
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = water_speed
plotitem.imshow_cmap = plt.get_cmap('PuBu')
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = max_speed
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.add_colorbar = False
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
# ========================================================================
# Vorticity Plots
# ========================================================================
vorticity_limits = [-2,2]
# Full domain
plotfigure = plotdata.new_plotfigure(name='full_vorticity', figno=500)
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Vorticity'
plotaxes.scaled = True
plotaxes.xlimits = [138,148]
plotaxes.ylimits = [34,42]
# Speed
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = vorticity
plotitem.imshow_cmap = colormaps.make_colormap({1.0:'r',0.5:'w',0.0:'b'})
plotitem.imshow_cmin = vorticity_limits[0]
plotitem.imshow_cmax = vorticity_limits[1]
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.add_colorbar = False
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
#-----------------------------------------
# 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 = [400,401,402] # 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 setplot(plotdata):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
from numpy import linspace
plotdata.clearfigures() # clear any old figures,axes,items data
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=True, fontsize=8)
#-----------------------------------------
# Figure for pcolor plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='full domain', figno=0)
plotfigure.show = True # Turn the pcolor plot on or off (True or False)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.show = True ### Turn on or off the full domain plot
plotaxes.title = 'Surface'
plotaxes.scaled = True
def fixup(current_data):
import pylab
t = current_data.t
# pylab.title('Surface at %4.2f seconds' % t, fontsize=20)
t = t / 60. # minutes
pylab.title('Surface at %4.2f minutes' % t, fontsize=20)
pylab.xticks(fontsize=15)
pylab.yticks(fontsize=15)
#pylab.plot([205],[20],'wo',markersize=5)
#pylab.text(201,22,'Hawaii',color='w',fontsize=15)
# pylab.plot([139.7],[35.6],'wo',markersize=5)
# pylab.text(135.2,35.9,'Tokyo',color='w',fontsize=15)
# pylab.plot([235.81],[41.75],'wo',markersize=5)
# pylab.text(235.9,42,'Crescent City',color='w',fontsize=15)
addgauges(current_data)
plotaxes.afteraxes = fixup
# plotaxes.s = [137.57,141.41] # Full Domain
# plotaxes.ylimits = [39.67,44.15] # Full Domain
# plotaxes.xlimits = [139., 140.] ## Okushiri Island (Large area)
# plotaxes.ylimits = [41.5, 42.5] ## Okushiri Island (Large area)
# plotaxes.xlimits = [139.43, 139.48] ## Aonae peninsula
# plotaxes.ylimits = [42.03, 42.06] ## Aonae peninsula
# plotaxes.xlimits = [139.35, 139.6] ## Okushiri Island (Tight)
# plotaxes.ylimits = [42.0, 42.25] ## Okushiri Island (Tight)
# plotaxes.xlimits = [139.41, 139.43] ## Monai Long Coast
# plotaxes.ylimits = [42.08, 42.15] ## Monai Long Coast
# plotaxes.xlimits = [139.418, 139.426] ## Monai Short
# plotaxes.ylimits = [42.096, 42.106] ## Monai Short
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
# plotitem.pcolor_cmap = geoplot.tsunami_colormap
# plotitem.pcolor_cmap = colormaps.blue_white_red
# dictionary of [R,G,B] values at different levels:
my_cmap_surface = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.02: [0.75,0.75,1.0], \
0.0: [1.0,1.0,1.0], \
0.02: [1.0,0.75,0.75], \
1.0: [1.0,0.0,0.0]})
plotitem.pcolor_cmap = my_cmap_surface
plotitem.pcolor_cmin = -50.
plotitem.pcolor_cmax = 50.
plotitem.add_colorbar = True
plotitem.amr_gridedges_show = [1]
# plotitem.amr_gridlines_show = [0,0,0,0,0] # Turn off/0n = 0/1 gridlines for levels [1,2,3, ...]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
plotitem.plot_var = geoplot.land
my_cmap_land = colormaps.make_colormap({ \
0.0: [0.0,1.0,0.0], \
1.0: [0.0,0.5,0.0] \
})
plotitem.pcolor_cmap = my_cmap_land
# plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = True
# plotitem.amr_gridlines_show = [0,0,0]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# 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(-20,20,11)
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 1}
plotitem.amr_contour_show = [0, 0, 0, 1]
# plotitem.gridlines_show = 0
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,0]
# Topo = Bathymetry and Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = False
plotitem.plot_var = geoplot.topo
# plotitem.pcolor_cmap = geoplot.bathy3_colormap #Try 1, 2 & 3
my_cmap_topo = colormaps.make_colormap({ \
-5000.0: [0,0,1], 0.0: [1,1,1], 100.0: [0.0,0.5,0.0] \
})
plotitem.pcolor_cmap = my_cmap_topo
plotitem.pcolor_cmin = -5000.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = False
# plotitem.amr_gridlines_show = [0,0,0]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# add contour lines of topo if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = linspace(-5000, -100, 6)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 1}
# plotitem.amr_contour_show = [0,0,0]
# plotitem.gridlines_show = 0
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,0]
#-----------------------------------------
# Figure for velocity plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='speed', figno=20)
plotfigure.show = False # Turn the pcolor plot on or off (True or False)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.show = True ### Turn on or off the full domain plot
plotaxes.title = 'Water speed'
plotaxes.scaled = True
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
def speed(current_data):
from numpy import where, sqrt
q = current_data.q
x = current_data.x
y = current_data.y
level = current_data.level
h = q[:, :, 0]
hu = q[:, :, 1]
hv = q[:, :, 2]
u = where(h > 0, hu / h, 0.)
v = where(h > 0, hv / h, 0.)
s = sqrt(u**2 + v**2)
print "level = %s, max speed = %s" % (level, s.max())
i = s.argmax()
print " at x = %s, y = %s" % (x.flat[i], y.flat[i])
return s
plotitem.plot_var = speed
my_cmap_surface = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.02: [0.75,0.75,1.0], \
0.0: [1.0,1.0,1.0], \
0.02: [1.0,0.75,0.75], \
1.0: [1.0,0.0,0.0]})
plotitem.pcolor_cmap = my_cmap_surface
plotitem.pcolor_cmin = -50.
plotitem.pcolor_cmax = 50.
plotitem.add_colorbar = True
plotitem.amr_gridedges_show = [1]
# plotitem.amr_gridlines_show = [0,0,0,0,0] # Turn off/0n = 0/1 gridlines for levels [1,2,3, ...]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
plotitem.plot_var = geoplot.land
my_cmap_land = colormaps.make_colormap({ \
0.0: [0.0,1.0,0.0], \
1.0: [0.0,0.5,0.0] \
})
plotitem.pcolor_cmap = my_cmap_land
# plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = True
# plotitem.amr_gridlines_show = [0,0,0]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# 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(-20,20,11)
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 1}
plotitem.amr_contour_show = [0, 0, 0, 1]
#-----------------------------------------
# Figure for zoom plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Zoom', figno=1)
plotfigure.show = False # Turn the zoom plot on or off (True or False)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.title = 'Surface'
plotaxes.scaled = True
##
# plotaxes.xlimits = [140.3, 140.5] ## Esashi Tide Gage
# plotaxes.ylimits = [41.75, 41.95] ## Esashi Tide Gage
# plotaxes.xlimits = [139.35, 139.6] ## Okushiri Island
# plotaxes.ylimits = [42.0, 42.25] ## Okushiri Island
# plotaxes.xlimits = [139.43, 139.48] ## Aonae peninsula
# plotaxes.ylimits = [42.03, 42.06] ## Aonae peninsula
# plotaxes.xlimits = [139.41, 139.43] ## Monai
# plotaxes.ylimits = [42.08, 42.15] ## Monai
# plotaxes.xlimits = [139.41385190, 139.42639510] ## MB05 Monai grid
# plotaxes.ylimits = [42.09458550, 42.10343920] ## MB05 Monai grid
plotaxes.xlimits = [139., 140.] ## Okushiri Island
plotaxes.ylimits = [41.5, 42.5] ## Okushiri Island
# dx = 0.00005
# dy = 0.00005
# plotaxes.xlimits = [139.423714744650-dx, 139.423714744650+dx] ## Station 8, Monai valley
# plotaxes.ylimits = [ 42.100414145210-dy, 42.100414145210+dy] ## Station 8, Monai valley
def fixup(current_data):
import pylab
addgauges(current_data)
t = current_data.t
pylab.title('Surface at %4.2f seconds' % t, fontsize=20)
# t = t / 60. # minutes
# pylab.title('Surface at %4.2f minutes' % t, fontsize=20)
# pylab.plot([139.7],[35.6],'wo',markersize=10)
# pylab.text(138.2,35.9,'Tokyo',color='w',fontsize=25)
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_cmap = colormaps.blue_white_red
plotitem.pcolor_cmin = -5.
plotitem.pcolor_cmax = 5.
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0] ##Levels of refinement
plotitem.gridedges_show = 1
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = True
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = linspace(-1000, 100, 11)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 2}
plotitem.amr_contour_show = [1, 0, 0]
plotitem.gridlines_show = 1
plotitem.gridedges_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 = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.gridedges_show = 1
# add contour lines of land if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = True
plotitem.plot_var = geoplot.land
plotitem.contour_levels = linspace(0, 100, 10)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 2}
plotitem.amr_contour_show = [0, 0, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=2, \
type='each_gauge')
plotfigure.clf_each_gauge = False # Switch gauge figures on or off
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
# plotaxes.ylimits = 'auto'
plotaxes.ylimits = [-20., 20.]
plotaxes.title = 'Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
plotitem.kwargs = {'linewidth': 2}
# Plot topo as green curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.show = True
def gaugetopo(current_data):
q = current_data.q
h = q[:, 0]
eta = q[:, 3]
topo = eta - h
return topo
plotitem.plot_var = gaugetopo
plotitem.plotstyle = 'g-'
def add_zeroline(current_data):
from pylab import plot, legend, xticks, floor, xlim
t = current_data.t
dtaxis = 60. # Set the axis time increment, in seconds
#t = t/dtaxis
tmax = t.max()
#print "tmax = ",tmax
legend(('surface', 'topography'), loc='lower left')
plot([0, tmax], [0, 0], 'k')
n = int(floor(tmax) + 2)
xticks([dtaxis * i for i in range(n)])
xlim(0., tmax)
plotaxes.afteraxes = add_zeroline
def plot_TG(current_data):
import pylab
gaugeno = current_data.gaugeno
if gaugeno == 5000:
try:
pylab.plot(Esashidata[:, 0], Esashidata[:, 1], 'k')
pylab.legend(['GeoClaw', 'Esashi data'])
except:
pylab.legend(['GeoClaw'])
if gaugeno == 6000:
try:
pylab.plot(Iwanaidata[:, 0], Iwanaidata[:, 1], 'k')
pylab.legend(['GeoClaw', 'Iwanai data'])
except:
pylab.legend(['GeoClaw'])
add_zeroline(current_data)
plotaxes.afteraxes = plot_TG
# Fixed grid plots:
# -----------------
if setplotfg is not None:
# Repeat as desired for other fixed grids...
otherfig = plotdata.new_otherfigure('Fixed Grid 1')
fgno = 1
sfgno = str(fgno).zfill(2) # e.g. '01'
otherfig.fname = '_PlotIndex_FixedGrid%s.html' % sfgno
def make_fgplots(plotdata):
fgdata = setplotfg(fgno, outdir=plotdata.outdir)
fgdata.fg2html('all')
otherfig.makefig = make_fgplots
#-----------------------------------------
# Parameters used only when creating html and/or latex hardcopy
# e.g., via pyclaw.plotters.frametools.printframes:
# Figure Printing
plotdata.printfigs = True # All figures printed
# plotdata.printfigs = False # No figures printed
plotdata.print_format = 'png' # file format
# Frame Printing
plotdata.print_framenos = 'all' # All frame figures printed
# plotdata.print_framenos = [] # No frame figures printed
# plotdata.print_framenos = range(0,21) # List of frame figures to print (n1:n2-1)
# Gauge Printing
# plotdata.print_gaugenos = 'all' # All gauge figures printed
plotdata.print_gaugenos = [] # No gauge figures printed
# plotdata.print_gaugenos = range(201,210) # List of gauge figures to print range(n1,n2-1)
# Print Figures (Both Frames and Gauges)
plotdata.print_fignos = 'all' # list of figures to print
# Create html or latex files
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?
# Specify Layout 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 setplot(plotdata):
# --------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
plotdata.clearfigures() # clear any old figures,axes,items dat
# plotdata.format = "netcdf"
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=True)
def title_hours(current_data):
from pylab import title
t = current_data.t
h = t / 3600.
title('%5.2f Hours after Quake' % h)
def plotcc(current_data):
from pylab import plot, text
plot([235.8162], [41.745616], 'wo')
text(235.8, 41.9, 'Cr.City', color='w', fontsize=10)
#-----------------------------------------
# Figure for big area
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Pacific', figno=0)
plotfigure.kwargs = {'figsize': (16, 4)}
plotfigure.show = True
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Pacific'
plotaxes.scaled = True
def aa(current_data):
title_hours(current_data)
if 0:
from pylab import savefig
fname = 'pacific%s.png' % str(current_data.frameno).zfill(4)
savefig(fname)
print 'Saved ', fname
plotaxes.afteraxes = aa
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.1: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.1: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = -0.3
plotitem.imshow_cmax = 0.3
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
plotaxes.xlimits = [132, 238]
plotaxes.ylimits = [30, 50]
#plotaxes.afteraxes = addgauges
# Add contour lines of bathymetry:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
#plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = linspace(-6000, 0, 7)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [0, 0, 1,
0] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(0., 11., 1.)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [0, 0, 0,
1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figure for zoom
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='California', figno=10)
#plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'California'
plotaxes.scaled = True
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.1: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.1: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = -0.3
plotitem.imshow_cmax = 0.3
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
plotaxes.xlimits = [227, 237]
plotaxes.ylimits = [35, 45]
def af(current_data):
from pylab import savefig, figure
figure(10)
plotcc(current_data)
title_hours(current_data)
addgauges(current_data)
if 0:
fname = '/Users/rjl/OUTPUT/Users/rjl/Dropbox/mygeo/CC/_plots/' +\
'california%s.png' % str(current_data.frameno).zfill(4)
savefig(fname)
print 'Saved ', fname
#plotdata.afterframe = af
plotaxes.afteraxes = af
# Add contour lines of eta:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.surface
from numpy import arange, linspace
plotitem.contour_levels = linspace(-0.3, 0.3, 13)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [0, 0, 1, 0] # AMR levels to show contours
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = False
# 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(-4500, 0, 10)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [0, 0, 1, 0] # AMR levels to show contours
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = True
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(0., 11., 1.)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [0, 0, 0,
1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
plotitem.show = False
#-----------------------------------------
# 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.print_gaugenos = 'all' # list of gauges 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 setplot(plotdata):
#--------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
from pyclaw.plotters.plottools import fix_long_tick_labels
from numpy import linspace
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.rundir = plotdata.outdir # where to find data files, e.g.
# gauge locations
def set_drytol(current_data):
current_data.user.drytol = 1.e-2
plotdata.beforeframe = set_drytol
def saveframe(current_data):
import pylab
fname = 'ok_%smin.png' % current_data.frameno
pylab.savefig(fname)
print 'Saved ',fname
#plotdata.afterframe = saveframe
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=True, fontsize=8)
#-----------------------------------------
# Figure for pcolor plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='full domain', figno=0)
plotfigure.show = True # Turn the pcolor plot on or off (True or False)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.show = True ### Turn on or off the full domain plot
plotaxes.title = 'Surface'
plotaxes.scaled = True
# xlimits = [137.57,141.41] # Full Domain
# ylimits = [39.67,44.15] # Full Domain
# xlimits = [139., 140.] ## Okushiri Island (Large area)
# ylimits = [41.5, 42.5] ## Okushiri Island (Large area)
# xlimits = [139.43, 139.48] ## Aonae peninsula
# ylimits = [42.03, 42.06] ## Aonae peninsula
# xlimits = [139.41, 139.43] ## Monai Long Coast
# ylimits = [42.08, 42.15] ## Monai Long Coast
# xlimits = [139.418, 139.426] ## Monai Short
# ylimits = [42.096, 42.106] ## Monai Short
#xlimits = 'auto' ## full domain
#ylimits = 'auto' ## full domain
xlimits = [139.35, 139.6] ## Okushiri Island (Tight)
ylimits = [42.0, 42.25] ## Okushiri Island (Tight)
# xlimits and ylimits need to be set for fixup to work!
plotaxes.xlimits = xlimits
plotaxes.ylimits = ylimits
def fixup(current_data):
import pylab
t = current_data.t
# pylab.title('Surface at %4.2f seconds' % t, fontsize=20)
t = t / 60. # minutes
pylab.title('Surface at %4.2f minutes' % t, fontsize=20)
fix_long_tick_labels(xlimits,ylimits)
addgauges(current_data)
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
# plotitem.pcolor_cmap = geoplot.tsunami_colormap
# plotitem.pcolor_cmap = colormaps.blue_white_red
# dictionary of [R,G,B] values at different levels:
my_cmap_surface = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.02: [0.75,0.75,1.0], \
0.0: [1.0,1.0,1.0], \
0.02: [1.0,0.75,0.75], \
1.0: [1.0,0.0,0.0]})
plotitem.pcolor_cmap = my_cmap_surface
plotitem.pcolor_cmin = -5.
plotitem.pcolor_cmax = 5.
plotitem.add_colorbar = False
plotitem.amr_gridedges_show = [1]
# plotitem.amr_gridlines_show = [0,0,0,0,0] # Turn off/0n = 0/1 gridlines for levels [1,2,3, ...]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
plotitem.plot_var = geoplot.land
my_cmap_land = colormaps.make_colormap({ \
0.0: [0.0,1.0,0.0], \
1.0: [0.0,0.5,0.0] \
})
plotitem.pcolor_cmap = my_cmap_land
# plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = False
# plotitem.amr_gridlines_show = [0,0,0]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# 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(-20,20,11)
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid','linewidths':1}
plotitem.amr_contour_show = [0,0,0,1]
# plotitem.gridlines_show = 0
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,0]
# Topo = Bathymetry and Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = False
plotitem.plot_var = geoplot.topo
# plotitem.pcolor_cmap = geoplot.bathy3_colormap #Try 1, 2 & 3
my_cmap_topo = colormaps.make_colormap({ \
-5000.0: [0,0,1], 0.0: [1,1,1], 100.0: [0.0,0.5,0.0] \
})
plotitem.pcolor_cmap = my_cmap_topo
plotitem.pcolor_cmin = -5000.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = False
# plotitem.amr_gridlines_show = [0,0,0]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# add contour lines of topo if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = linspace(-5000,-100,6)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles':'solid','linewidths':1}
# plotitem.amr_contour_show = [0,0,0]
# plotitem.gridlines_show = 0
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,0]
#-----------------------------------------
# Figure for velocity plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='speed', figno=20)
plotfigure.show = False # Turn the pcolor plot on or off (True or False)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.show = True ### Turn on or off the full domain plot
plotaxes.title = 'Water speed'
plotaxes.scaled = True
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
def speed(current_data):
from numpy import where,sqrt
q = current_data.q
x = current_data.x
y = current_data.y
level = current_data.level
h = q[:,:,0]
hu = q[:,:,1]
hv = q[:,:,2]
u = where(h>0, hu/h, 0.)
v = where(h>0, hv/h, 0.)
s = sqrt(u**2 + v**2)
print "level = %s, max speed = %s" %(level,s.max())
i = s.argmax()
print " at x = %s, y = %s" % (x.flat[i],y.flat[i])
return s
plotitem.plot_var = speed
my_cmap_surface = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.02: [0.75,0.75,1.0], \
0.0: [1.0,1.0,1.0], \
0.02: [1.0,0.75,0.75], \
1.0: [1.0,0.0,0.0]})
plotitem.pcolor_cmap = my_cmap_surface
plotitem.pcolor_cmin = -50.
plotitem.pcolor_cmax = 50.
plotitem.add_colorbar = True
plotitem.amr_gridedges_show = [1]
# plotitem.amr_gridlines_show = [0,0,0,0,0] # Turn off/0n = 0/1 gridlines for levels [1,2,3, ...]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_pcolor')
plotitem.show = True
plotitem.plot_var = geoplot.land
my_cmap_land = colormaps.make_colormap({ \
0.0: [0.0,1.0,0.0], \
1.0: [0.0,0.5,0.0] \
})
plotitem.pcolor_cmap = my_cmap_land
# plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = True
# plotitem.amr_gridlines_show = [0,0,0]
# plotitem.gridedges_show = 0
#plotitem.amr_data_show = [1,1,1,1,0]
# 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(-20,20,11)
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles':'solid','linewidths':1}
plotitem.amr_contour_show = [0,0,0,1]
#-----------------------------------------
# Figure for zoom plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Zoom', figno=1)
plotfigure.show = False # Turn the zoom plot on or off (True or False)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('pcolor')
plotaxes.title = 'Surface'
plotaxes.scaled = True
##
# plotaxes.xlimits = [140.3, 140.5] ## Esashi Tide Gage
# plotaxes.ylimits = [41.75, 41.95] ## Esashi Tide Gage
# plotaxes.xlimits = [139.35, 139.6] ## Okushiri Island
# plotaxes.ylimits = [42.0, 42.25] ## Okushiri Island
# plotaxes.xlimits = [139.43, 139.48] ## Aonae peninsula
# plotaxes.ylimits = [42.03, 42.06] ## Aonae peninsula
# plotaxes.xlimits = [139.41, 139.43] ## Monai
# plotaxes.ylimits = [42.08, 42.15] ## Monai
# plotaxes.xlimits = [139.41385190, 139.42639510] ## MB05 Monai grid
# plotaxes.ylimits = [42.09458550, 42.10343920] ## MB05 Monai grid
plotaxes.xlimits = [139., 140.] ## Okushiri Island
plotaxes.ylimits = [41.5, 42.5] ## Okushiri Island
# dx = 0.00005
# dy = 0.00005
# plotaxes.xlimits = [139.423714744650-dx, 139.423714744650+dx] ## Station 8, Monai valley
# plotaxes.ylimits = [ 42.100414145210-dy, 42.100414145210+dy] ## Station 8, Monai valley
def fixup(current_data):
import pylab
addgauges(current_data)
t = current_data.t
pylab.title('Surface at %4.2f seconds' % t, fontsize=20)
# t = t / 60. # minutes
# pylab.title('Surface at %4.2f minutes' % t, fontsize=20)
# pylab.plot([139.7],[35.6],'wo',markersize=10)
# pylab.text(138.2,35.9,'Tokyo',color='w',fontsize=25)
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_cmap = colormaps.blue_white_red
plotitem.pcolor_cmin = -5.
plotitem.pcolor_cmax = 5.
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0,0,0] ##Levels of refinement
plotitem.gridedges_show = 1
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = True
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = linspace(-1000,100,11)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles':'solid','linewidths':2}
plotitem.amr_contour_show = [1,0,0]
plotitem.gridlines_show = 1
plotitem.gridedges_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 = True
plotitem.amr_gridlines_show = [0,0,0]
plotitem.gridedges_show = 1
# add contour lines of land if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = True
plotitem.plot_var = geoplot.land
plotitem.contour_levels = linspace(0,100,10)
plotitem.amr_contour_colors = ['y'] # color on each level
plotitem.kwargs = {'linestyles':'solid','linewidths':2}
plotitem.amr_contour_show = [0,0,0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=2, \
type='each_gauge')
plotfigure.clf_each_gauge = False # Switch gauge figures on or off
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = 'auto'
# plotaxes.ylimits = 'auto'
plotaxes.ylimits = [-20.,20.]
plotaxes.title = 'Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
plotitem.kwargs = {'linewidth':2}
# Plot topo as green curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.show = True
def gaugetopo(current_data):
q = current_data.q
h = q[:,0]
eta = q[:,3]
topo = eta - h
return topo
plotitem.plot_var = gaugetopo
plotitem.plotstyle = 'g-'
def add_zeroline(current_data):
from pylab import plot, legend, xticks, floor, xlim
t = current_data.t
dtaxis=60. # Set the axis time increment, in seconds
#t = t/dtaxis
tmax = t.max()
#print "tmax = ",tmax
legend(('surface','topography'),loc='lower left')
plot([0,tmax],[0,0],'k')
n = int(floor(tmax) + 2)
xticks([dtaxis*i for i in range(n)])
xlim(0.,tmax)
plotaxes.afteraxes = add_zeroline
def plot_TG(current_data):
import pylab
gaugeno = current_data.gaugeno
if gaugeno == 5000:
try:
pylab.plot(Esashidata[:,0],Esashidata[:,1],'k')
pylab.legend(['GeoClaw','Esashi data'])
except:
pylab.legend(['GeoClaw'])
if gaugeno == 6000:
try:
pylab.plot(Iwanaidata[:,0],Iwanaidata[:,1],'k')
pylab.legend(['GeoClaw','Iwanai data'])
except:
pylab.legend(['GeoClaw'])
add_zeroline(current_data)
plotaxes.afteraxes = plot_TG
# Fixed grid plots:
# -----------------
if setplotfg is not None:
fgnos = [1,2,3,4] ## list of fixed grid numbers to plot
framenos = 'all' ## or list of frames to plot for each fgno
def make_fgplot_generator(fgno):
def make_fgplot(plotdata):
fgdata = setplotfg(fgno, outdir=plotdata.outdir)
fgdata.fg2html(framenos)
return make_fgplot
for fgno in fgnos:
otherfig = plotdata.new_otherfigure('Fixed Grid %s' % fgno)
sfgno = str(fgno).zfill(2) # e.g. '01'
otherfig.fname = '_PlotIndex_FixedGrid%s.html' % sfgno
otherfig.makefig = make_fgplot_generator(fgno)
#-----------------------------------------
# Parameters used only when creating html and/or latex hardcopy
# e.g., via pyclaw.plotters.frametools.printframes:
# Figure Printing
plotdata.printfigs = True # All figures printed
# plotdata.printfigs = False # No figures printed
plotdata.print_format = 'png' # file format
# Frame Printing
plotdata.print_framenos = 'all' # All frame figures printed
# plotdata.print_framenos = [] # No frame figures printed
# plotdata.print_framenos = range(0,21) # List of frame figures to print (n1:n2-1)
# Gauge Printing
# plotdata.print_gaugenos = 'all' # All gauge figures printed
plotdata.print_gaugenos = [] # No gauge figures printed
# plotdata.print_gaugenos = range(201,210) # List of gauge figures to print range(n1,n2-1)
# Print Figures (Both Frames and Gauges)
plotdata.print_fignos = 'all' # list of figures to print
# Create html or latex files
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?
# Specify Layout 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
plt.hold(False)
plt.savefig(topo_file)
plt.show()
# Domain plot
domain_file = '/Users/mandli/Documents/research/Papers/awr10/figures/ss_domain.png'
# domain_file = './ss_domain.png'
if not os.path.exists(domain_file):
plt.figure(2)
plt.hold(True)
# Water and land
water = np.ma.masked_where(bath>0.0,np.zeros(bath.shape))
plt.pcolor(X,Y,bath.T,cmap=geoplot.land_colors)
# light blue = [0,0.5,1]
plt.pcolor(X,Y,water.T,cmap=colormaps.make_colormap({1.0:'w',0.0:'w'}))
# Hurricane Track
plt.plot([-200e3,500e3],[0.0,0.0],'r-',lw=2)
for n in [0,5]:
plt.plot(n*3600*5,0.0,'rD',markersize=10)
plt.text(n*3600*5-4e3,15e3,"%s hr" % n)
for n in [-6,13,20]:
plt.plot(n*3600*5,0.0,'rD',markersize=10)
plt.text(n*3600*5-10e3,15e3,"%s hr" % n)
# plt.annotate('Position of Storm (h)',(0.0,-5e3),(-100e3,-100e3),arrowprops={'width':1,'color':'k','shrink':0.10})
# Gauges
setgauges = gt.read_setgauges('./_output')
offset = 30e3
n = 9
def plotfg(fgno, frameno, outdir='_output', save_png=False):
fname = "fort.fg%s_%s" % (str(fgno).zfill(2), str(frameno).zfill(4))
fname = os.path.join(outdir,fname)
if not os.path.exists(fname):
print "*** Did not find file ",fname," in directory ",outdir
raise IOError("Missing fixed grid output file")
print "Plotting fixed grid output from ",fname
# Read parameters from header:
file = open(fname,'r')
line = file.readline()
t = float(line.split()[0])
print 't = %s' % t
line = file.readline()
mx = int(line.split()[0])
line = file.readline()
my = int(line.split()[0])
line = file.readline()
xlow = float(line.split()[0])
line = file.readline()
ylow = float(line.split()[0])
line = file.readline()
xhi = float(line.split()[0])
line = file.readline()
yhi = float(line.split()[0])
if 0:
print 'mx = %s' % mx
print 'my = %s' % my
print 'xlow = %s' % xlow
print 'ylow = %s' % ylow
print 'xhi = %s' % xhi
print 'yhi = %s' % yhi
file.close()
x = linspace(xlow,xhi,mx+1)
y = linspace(ylow,yhi,my+1)
dx = x[1]-x[0]
dy = y[1]-y[0]
xcenter = x[:-1] + dx/2.
ycenter = y[:-1] + dy/2.
d = loadtxt(fname, skiprows=8)
h = reshape(d[:,0], (my,mx))
B = reshape(d[:,3], (my,mx))
eta = reshape(d[:,4], (my,mx))
surface = ma.masked_where(isnan(eta),eta)
land = ma.masked_where(h>drytol,B)
# plot commands:
# ==============
# ===================================================
# Adjust these:
# Define function to plot topo contours for use in multiple places:
def add_contours():
clines = linspace(-20,20,21)
contour(xcenter,ycenter,B,clines,colors='k')
contour(xcenter,ycenter,B,[0.],colors='k',linewidths=2)
# Set colormaps:
water_cmap = geoplot.tsunami_colormap
land_cmap = geoplot.land_colors
seafloor_cmap = geoplot.seafloor_colormap
inundated_cmap = colormaps.make_colormap({0.:[1,.9,.9], 1.:[1,0,0]})
# ===================================================
figno = 150
figure(figno)
clf()
if ma.count(surface) != 0:
pcolormesh(x,y,surface,cmap=water_cmap)
clim((-5,5))
colorbar()
if ma.count(land) != 0:
pcolormesh(x,y,land,cmap=land_cmap)
#clim((-0.02,0.02))
add_contours()
ncols = d.shape[1]
axis('scaled')
title('Surface on fixed grid %s at time = %8.5f' % (fgno,t))
xlim((xlow,xhi))
ylim((ylow,yhi))
if save_png:
fname = 'FixedGrid%sFrame%sFig%s.png' \
% (str(fgno).zfill(2), str(frameno).zfill(4), figno)
savefig(fname)
print "Saved figure as ",fname
return_fg = True # return all the fg arrays for other purposes?
if return_fg:
fg = empty((my,mx,ncols), dtype=float)
for col in range(ncols):
fg[:,:,col] = reshape(d[:,col],(my,mx))
if ncols > 5:
etamin = reshape(d[:,5], (my,mx))
etamax = reshape(d[:,6], (my,mx))
#etamax2 = where(B<0, 1., etamax)
etamax2 = where(B<0, 1., etamax)
# Add red contour of maximum eta
#contour(xcenter,ycenter,etamax2,[drytol],colors='r',linewidths=2)
# Add brown contour of minimum eta
#contour(xcenter,ycenter,etamin-B,[exposed_tol],colors=([.9,.8,.2],),linewidths=2)
# Determine exposed and inundatated regions:
exposed = ma.masked_where(((B>0) | (etamin > B+exposed_tol)), etamin)
inundated = ma.masked_where(((B<0) | (etamax < B+drytol)), etamax)
figno = 151
figure(figno)
clf()
if ma.count(inundated) != 0:
pcolormesh(x,y,inundated,cmap=inundated_cmap)
clim((0,5))
colorbar()
add_contours()
# Add red contour of maximum eta
#contour(xcenter,ycenter,etamax2,[drytol],colors='r',linewidths=2)
title("Inundated region for t <= %8.5f" % t)
axis('scaled')
xlim((xlow,xhi))
ylim((ylow,yhi))
if save_png:
fname = 'FixedGrid%sFrame%sFig%s.png' \
% (str(fgno).zfill(2), str(frameno).zfill(4), figno)
savefig(fname)
print "Saved figure as ",fname
figno = 152
figure(figno)
clf()
if ma.count(exposed) != 0:
pcolormesh(x,y,exposed,cmap=seafloor_cmap)
#clim((-0.02,0.02))
colorbar()
add_contours()
# Add brown contour of minimum eta
#contour(xcenter,ycenter,etamin-B,[exposed_tol],colors=([.9,.8,.2],),linewidths=2)
title("Exposed seabed for t <= %8.5f" % t)
axis('scaled')
xlim((xlow,xhi))
ylim((ylow,yhi))
if save_png:
fname = 'FixedGrid%sFrame%sFig%s.png' \
% (str(fgno).zfill(2), str(frameno).zfill(4), figno)
savefig(fname)
print "Saved figure as ",fname
return fg
def setplot(plotdata):
# --------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
from numpy import linspace
plotdata.clearfigures() # clear any old figures,axes,items data
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(
current_data.plotdata, gaugenos="all", format_string="ko", add_labels=True, fontsize=8
)
# -----------------------------------------
# Figure for pcolor plot
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="full domain", figno=0)
plotfigure.show = True # Turn the pcolor plot on or off (True or False)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes("pcolor")
plotaxes.show = True ### Turn on or off the full domain plot
plotaxes.title = "Surface"
plotaxes.scaled = True
def fixup(current_data):
import pylab
t = current_data.t
# pylab.title('Surface at %4.2f seconds' % t, fontsize=20)
t = t / 60.0 # minutes
pylab.title("Surface at %4.2f minutes" % t, fontsize=20)
pylab.xticks(fontsize=15)
pylab.yticks(fontsize=15)
# pylab.plot([205],[20],'wo',markersize=5)
# pylab.text(201,22,'Hawaii',color='w',fontsize=15)
# pylab.plot([139.7],[35.6],'wo',markersize=5)
# pylab.text(135.2,35.9,'Tokyo',color='w',fontsize=15)
# pylab.plot([235.81],[41.75],'wo',markersize=5)
# pylab.text(235.9,42,'Crescent City',color='w',fontsize=15)
addgauges(current_data)
plotaxes.afteraxes = fixup
# plotaxes.s = [137.57,141.41] # Full Domain
# plotaxes.ylimits = [39.67,44.15] # Full Domain
# plotaxes.xlimits = [139., 140.] ## Okushiri Island (Large area)
# plotaxes.ylimits = [41.5, 42.5] ## Okushiri Island (Large area)
# plotaxes.xlimits = [139.43, 139.48] ## Aonae peninsula
# plotaxes.ylimits = [42.03, 42.06] ## Aonae peninsula
# plotaxes.xlimits = [139.35, 139.6] ## Okushiri Island (Tight)
# plotaxes.ylimits = [42.0, 42.25] ## Okushiri Island (Tight)
# plotaxes.xlimits = [139.41, 139.43] ## Monai Long Coast
# plotaxes.ylimits = [42.08, 42.15] ## Monai Long Coast
# plotaxes.xlimits = [139.418, 139.426] ## Monai Short
# plotaxes.ylimits = [42.096, 42.106] ## Monai Short
# Water
plotitem = plotaxes.new_plotitem(plot_type="2d_pcolor")
plotitem.show = True
# plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
# plotitem.pcolor_cmap = geoplot.tsunami_colormap
# plotitem.pcolor_cmap = colormaps.blue_white_red
# dictionary of [R,G,B] values at different levels:
my_cmap_surface = colormaps.make_colormap(
{
-1.0: [0.0, 0.0, 1.0],
-0.02: [0.75, 0.75, 1.0],
0.0: [1.0, 1.0, 1.0],
0.02: [1.0, 0.75, 0.75],
1.0: [1.0, 0.0, 0.0],
}
)
plotitem.pcolor_cmap = my_cmap_surface
plotitem.pcolor_cmin = -50.0
plotitem.pcolor_cmax = 50.0
plotitem.add_colorbar = True
plotitem.amr_gridedges_show = [1]
# plotitem.amr_gridlines_show = [0,0,0,0,0] # Turn off/0n = 0/1 gridlines for levels [1,2,3, ...]
# plotitem.gridedges_show = 0
# plotitem.amr_data_show = [1,1,1,1,0]
# Land
plotitem = plotaxes.new_plotitem(plot_type="2d_pcolor")
plotitem.show = True
plotitem.plot_var = geoplot.land
my_cmap_land = colormaps.make_colormap({0.0: [0.0, 1.0, 0.0], 1.0: [0.0, 0.5, 0.0]})
plotitem.pcolor_cmap = my_cmap_land
# plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = True
# plotitem.amr_gridlines_show = [0,0,0]
# plotitem.gridedges_show = 0
# plotitem.amr_data_show = [1,1,1,1,0]
# 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(-20,20,11)
plotitem.contour_levels = [0.0]
plotitem.amr_contour_colors = ["k"] # color on each level
plotitem.kwargs = {"linestyles": "solid", "linewidths": 1}
plotitem.amr_contour_show = [0, 0, 0, 1]
# plotitem.gridlines_show = 0
# plotitem.gridedges_show = 0
# plotitem.amr_data_show = [1,1,1,0]
# Topo = Bathymetry and Land
plotitem = plotaxes.new_plotitem(plot_type="2d_pcolor")
plotitem.show = False
plotitem.plot_var = geoplot.topo
# plotitem.pcolor_cmap = geoplot.bathy3_colormap #Try 1, 2 & 3
my_cmap_topo = colormaps.make_colormap({-5000.0: [0, 0, 1], 0.0: [1, 1, 1], 100.0: [0.0, 0.5, 0.0]})
plotitem.pcolor_cmap = my_cmap_topo
plotitem.pcolor_cmin = -5000.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = False
# plotitem.amr_gridlines_show = [0,0,0]
# plotitem.gridedges_show = 0
# plotitem.amr_data_show = [1,1,1,1,0]
# add contour lines of topo if desired:
plotitem = plotaxes.new_plotitem(plot_type="2d_contour")
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = linspace(-5000, -100, 6)
plotitem.amr_contour_colors = ["y"] # color on each level
plotitem.kwargs = {"linestyles": "solid", "linewidths": 1}
# plotitem.amr_contour_show = [0,0,0]
# plotitem.gridlines_show = 0
# plotitem.gridedges_show = 0
# plotitem.amr_data_show = [1,1,1,0]
# -----------------------------------------
# Figure for velocity plot
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="speed", figno=20)
plotfigure.show = True # Turn the pcolor plot on or off (True or False)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes("pcolor")
plotaxes.show = True ### Turn on or off the full domain plot
plotaxes.title = "Water speed"
plotaxes.scaled = True
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type="2d_pcolor")
plotitem.show = True
def speed(current_data):
from numpy import where, sqrt
q = current_data.q
x = current_data.x
y = current_data.y
level = current_data.level
h = q[:, :, 0]
hu = q[:, :, 1]
hv = q[:, :, 2]
u = where(h > 0, hu / h, 0.0)
v = where(h > 0, hv / h, 0.0)
s = sqrt(u ** 2 + v ** 2)
print "level = %s, max speed = %s" % (level, s.max())
i = s.argmax()
print " at x = %s, y = %s" % (x.flat[i], y.flat[i])
return s
plotitem.plot_var = speed
my_cmap_surface = colormaps.make_colormap(
{
-1.0: [0.0, 0.0, 1.0],
-0.02: [0.75, 0.75, 1.0],
0.0: [1.0, 1.0, 1.0],
0.02: [1.0, 0.75, 0.75],
1.0: [1.0, 0.0, 0.0],
}
)
plotitem.pcolor_cmap = my_cmap_surface
plotitem.pcolor_cmin = -50.0
plotitem.pcolor_cmax = 50.0
plotitem.add_colorbar = True
plotitem.amr_gridedges_show = [1]
# plotitem.amr_gridlines_show = [0,0,0,0,0] # Turn off/0n = 0/1 gridlines for levels [1,2,3, ...]
# plotitem.gridedges_show = 0
# plotitem.amr_data_show = [1,1,1,1,0]
# Land
plotitem = plotaxes.new_plotitem(plot_type="2d_pcolor")
plotitem.show = True
plotitem.plot_var = geoplot.land
my_cmap_land = colormaps.make_colormap({0.0: [0.0, 1.0, 0.0], 1.0: [0.0, 0.5, 0.0]})
plotitem.pcolor_cmap = my_cmap_land
# plotitem.pcolor_cmap = geoplot.land_colors
plotitem.pcolor_cmin = 0.0
plotitem.pcolor_cmax = 100.0
plotitem.add_colorbar = True
# plotitem.amr_gridlines_show = [0,0,0]
# plotitem.gridedges_show = 0
# plotitem.amr_data_show = [1,1,1,1,0]
# 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(-20,20,11)
plotitem.contour_levels = [0.0]
plotitem.amr_contour_colors = ["k"] # color on each level
plotitem.kwargs = {"linestyles": "solid", "linewidths": 1}
plotitem.amr_contour_show = [0, 0, 0, 1]
# -----------------------------------------
# Figure for zoom plot
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Zoom", figno=1)
plotfigure.show = False # Turn the zoom plot on or off (True or False)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes("pcolor")
plotaxes.title = "Surface"
plotaxes.scaled = True
##
# plotaxes.xlimits = [140.3, 140.5] ## Esashi Tide Gage
# plotaxes.ylimits = [41.75, 41.95] ## Esashi Tide Gage
# plotaxes.xlimits = [139.35, 139.6] ## Okushiri Island
# plotaxes.ylimits = [42.0, 42.25] ## Okushiri Island
# plotaxes.xlimits = [139.43, 139.48] ## Aonae peninsula
# plotaxes.ylimits = [42.03, 42.06] ## Aonae peninsula
# plotaxes.xlimits = [139.41, 139.43] ## Monai
# plotaxes.ylimits = [42.08, 42.15] ## Monai
# plotaxes.xlimits = [139.41385190, 139.42639510] ## MB05 Monai grid
# plotaxes.ylimits = [42.09458550, 42.10343920] ## MB05 Monai grid
plotaxes.xlimits = [139.0, 140.0] ## Okushiri Island
plotaxes.ylimits = [41.5, 42.5] ## Okushiri Island
# dx = 0.00005
# dy = 0.00005
# plotaxes.xlimits = [139.423714744650-dx, 139.423714744650+dx] ## Station 8, Monai valley
# plotaxes.ylimits = [ 42.100414145210-dy, 42.100414145210+dy] ## Station 8, Monai valley
def fixup(current_data):
import pylab
addgauges(current_data)
t = current_data.t
pylab.title("Surface at %4.2f seconds" % t, fontsize=20)
# t = t / 60. # minutes
# pylab.title('Surface at %4.2f minutes' % t, fontsize=20)
# pylab.plot([139.7],[35.6],'wo',markersize=10)
# pylab.text(138.2,35.9,'Tokyo',color='w',fontsize=25)
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_cmap = colormaps.blue_white_red
plotitem.pcolor_cmin = -5.0
plotitem.pcolor_cmax = 5.0
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0] ##Levels of refinement
plotitem.gridedges_show = 1
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type="2d_contour")
plotitem.show = True
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = linspace(-1000, 100, 11)
plotitem.amr_contour_colors = ["y"] # color on each level
plotitem.kwargs = {"linestyles": "solid", "linewidths": 2}
plotitem.amr_contour_show = [1, 0, 0]
plotitem.gridlines_show = 1
plotitem.gridedges_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 = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.gridedges_show = 1
# add contour lines of land if desired:
plotitem = plotaxes.new_plotitem(plot_type="2d_contour")
plotitem.show = True
plotitem.plot_var = geoplot.land
plotitem.contour_levels = linspace(0, 100, 10)
plotitem.amr_contour_colors = ["y"] # color on each level
plotitem.kwargs = {"linestyles": "solid", "linewidths": 2}
plotitem.amr_contour_show = [0, 0, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# -----------------------------------------
# Figures for gauges
# -----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Surface & topo", figno=2, type="each_gauge")
plotfigure.clf_each_gauge = False # Switch gauge figures on or off
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = "auto"
# plotaxes.ylimits = 'auto'
plotaxes.ylimits = [-20.0, 20.0]
plotaxes.title = "Surface"
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type="1d_plot")
plotitem.plot_var = 3
plotitem.plotstyle = "b-"
plotitem.kwargs = {"linewidth": 2}
# Plot topo as green curve:
plotitem = plotaxes.new_plotitem(plot_type="1d_plot")
plotitem.show = True
def gaugetopo(current_data):
q = current_data.q
h = q[:, 0]
eta = q[:, 3]
topo = eta - h
return topo
plotitem.plot_var = gaugetopo
plotitem.plotstyle = "g-"
def add_zeroline(current_data):
from pylab import plot, legend, xticks, floor, xlim
t = current_data.t
dtaxis = 60.0 # Set the axis time increment, in seconds
# t = t/dtaxis
tmax = t.max()
# print "tmax = ",tmax
legend(("surface", "topography"), loc="lower left")
plot([0, tmax], [0, 0], "k")
n = int(floor(tmax) + 2)
xticks([dtaxis * i for i in range(n)])
xlim(0.0, tmax)
plotaxes.afteraxes = add_zeroline
def plot_TG(current_data):
import pylab
gaugeno = current_data.gaugeno
if gaugeno == 5000:
try:
pylab.plot(Esashidata[:, 0], Esashidata[:, 1], "k")
pylab.legend(["GeoClaw", "Esashi data"])
except:
pylab.legend(["GeoClaw"])
if gaugeno == 6000:
try:
pylab.plot(Iwanaidata[:, 0], Iwanaidata[:, 1], "k")
pylab.legend(["GeoClaw", "Iwanai data"])
except:
pylab.legend(["GeoClaw"])
add_zeroline(current_data)
plotaxes.afteraxes = plot_TG
# Fixed grid plots:
# -----------------
if setplotfg is not None:
# Repeat as desired for other fixed grids...
otherfig = plotdata.new_otherfigure("Fixed Grid 1")
fgno = 1
sfgno = str(fgno).zfill(2) # e.g. '01'
otherfig.fname = "_PlotIndex_FixedGrid%s.html" % sfgno
def make_fgplots(plotdata):
fgdata = setplotfg(fgno, outdir=plotdata.outdir)
fgdata.fg2html("all")
otherfig.makefig = make_fgplots
# -----------------------------------------
# Parameters used only when creating html and/or latex hardcopy
# e.g., via pyclaw.plotters.frametools.printframes:
# Figure Printing
plotdata.printfigs = True # All figures printed
# plotdata.printfigs = False # No figures printed
plotdata.print_format = "png" # file format
# Frame Printing
plotdata.print_framenos = "all" # All frame figures printed
# plotdata.print_framenos = [] # No frame figures printed
# plotdata.print_framenos = range(0,21) # List of frame figures to print (n1:n2-1)
# Gauge Printing
# plotdata.print_gaugenos = 'all' # All gauge figures printed
plotdata.print_gaugenos = [] # No gauge figures printed
# plotdata.print_gaugenos = range(201,210) # List of gauge figures to print range(n1,n2-1)
# Print Figures (Both Frames and Gauges)
plotdata.print_fignos = "all" # list of figures to print
# Create html or latex files
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?
# Specify Layout 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 setplot(plotdata):
# --------------------------
"""
Specify what is to be plotted at each frame.
Input: plotdata, an instance of pyclaw.plotters.data.ClawPlotData.
Output: a modified version of plotdata.
"""
from pyclaw.plotters import colormaps, geoplot
plotdata.clearfigures() # clear any old figures,axes,items dat
# plotdata.format = "netcdf"
try:
tsudata = open(plotdata.outdir + '/settsunami.data').readlines()
for line in tsudata:
if 'sealevel' in line:
sealevel = float(line.split()[0])
print "sealevel = ", sealevel
except:
print "Could not read sealevel, setting to 0."
sealevel = 0.
#clim_ocean = 2.0
#clim_CC = 2.0
clim_ocean = 5.0
clim_CC = 5.0
cmax_ocean = clim_ocean + sealevel
cmin_ocean = -clim_ocean + sealevel
cmax_CC = clim_CC + sealevel
cmin_CC = -clim_CC + sealevel
# To plot gauge locations on pcolor or contour plot, use this as
# an afteraxis function:
def addgauges(current_data):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos=[0], format_string='ko', add_labels=True)
def timeformat(t):
from numpy import mod
hours = int(t / 3600.)
tmin = mod(t, 3600.)
min = int(tmin / 60.)
sec = int(mod(tmin, 60.))
timestr = '%s:%s:%s' % (hours, str(min).zfill(2), str(sec).zfill(2))
return timestr
def title_hours(current_data):
from pylab import title
t = current_data.t
timestr = timeformat(t)
title('%s after earthquake' % timestr)
def aframe(current_data):
from pylab import figure, savefig
if 0:
tminutes = int(current_data.t / 60.)
figure(0)
fname = 'Pacific%s.png' % tminutes
savefig(fname)
print "Saved ", fname
figure(11)
fname = 'GraysHarbor%s.png' % tminutes
savefig(fname)
print "Saved ", fname
figure(12)
fname = 'Westport%s.png' % tminutes
savefig(fname)
print "Saved ", fname
figure(13)
fname = 'Ocosta%s.png' % tminutes
savefig(fname)
print "Saved ", fname
plotdata.afterframe = aframe
#-----------------------------------------
# Figure for big area
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Pacific', figno=0)
plotfigure.kwargs = {'figsize': (10, 6)}
#plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
#plotaxes.cmd = 'subplot(121)'
plotaxes.title = 'Pacific'
plotaxes.scaled = False
# modified for debug:
#plotaxes.xlimits = [231.5,236.5]
#plotaxes.ylimits = [45,49]
#plotaxes.xlimits = [235.8,236.2]
#plotaxes.ylimits = [46.1,46.9]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, savefig
title_hours(current_data)
ticklabel_format(format='plain', useOffset=False)
xticks(rotation=20)
a = gca()
a.set_aspect(1. / cos(46.349 * pi / 180.))
plotaxes.afteraxes = aa
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.5: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.5: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = cmin_ocean
plotitem.imshow_cmax = cmax_ocean
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
#plotaxes.afteraxes = addgauges
# Add contour lines of bathymetry:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = linspace(-6000, 0, 7)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [0, 0, 1,
0] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# Add contour lines of topography:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
from numpy import arange, linspace
plotitem.contour_levels = arange(0., 11., 1.)
plotitem.amr_contour_colors = ['g'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [0, 0, 0,
1] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figure for line plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='line', figno=2)
#plotfigure.show = False
def eta_slice(current_data):
from pylab import find, nan, array
x = current_data.x
y = current_data.y
q = current_data.q
j1 = find(y[0, :] > 47.5)
if len(j1) == 0:
x = eta = array([nan])
else:
j = min(j1)
x = x[:, j]
eta = q[:, j, 3]
return x, eta
def B_slice(current_data):
from pylab import find, nan, array
x = current_data.x
y = current_data.y
q = current_data.q
j1 = find(y[0, :] > 47.5)
if len(j1) == 0:
x = B = array([nan])
else:
j = min(j1)
x = x[:, j]
eta = q[:, j, 3]
h = q[:, j, 0]
B = eta - h
return x, B
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('line')
plotaxes.axescmd = 'subplot(212)'
plotaxes.title = 'Bathymetry'
# Water
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.show = False
plotitem.map_2d_to_1d = eta_slice
plotitem.color = 'b'
plotitem.kwargs = {'linewidth': 2}
# Topography
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
#plotitem.show = False
plotitem.map_2d_to_1d = B_slice
plotitem.color = 'k'
plotitem.plotstyle = 'o-'
def aa(current_data):
from pylab import ticklabel_format
ticklabel_format(format='plain', useOffset=False)
plotaxes.afteraxes = aa
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('linezoom')
#plotaxes.show = False
plotaxes.axescmd = 'subplot(211)'
plotaxes.title = 'Surface'
#plotaxes.xlimits = [-0.1,0.1]
plotaxes.ylimits = [-4, 6]
# Water
plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
plotitem.map_2d_to_1d = eta_slice
plotitem.color = 'b'
plotitem.plotstyle = 'o-'
plotitem.kwargs = {'linewidth': 2}
#-----------------------------------------
# Figure for zoom2
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name="Gray's Harbor", figno=11)
plotfigure.show = False
plotfigure.kwargs = {'figsize': (10, 9)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
#plotaxes.cmd = 'subplot(122)'
plotaxes.title = "Gray's Harbor"
plotaxes.scaled = False
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.5: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.5: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = cmin_CC
plotitem.imshow_cmax = cmax_CC
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [0]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [0]
plotaxes.xlimits = [235.8, 236.2]
plotaxes.ylimits = [46.75, 47.1]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, savefig
#addgauges(current_data)
title_hours(current_data)
ticklabel_format(format='plain', useOffset=False)
xticks(rotation=20)
a = gca()
a.set_aspect(1. / cos(46.86 * pi / 180.))
plotaxes.afteraxes = aa
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 2}
plotitem.amr_contour_show = [0, 0, 0, 0, 1, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figure for zoom
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Washington', figno=10)
plotfigure.show = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Washington'
plotaxes.scaled = False
plotaxes.afteraxes = aa
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.1: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.1: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = cmin_ocean
plotitem.imshow_cmax = cmax_ocean
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 100.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
plotaxes.xlimits = [235, 236.5]
plotaxes.ylimits = [46, 49]
plotaxes.afteraxes = aa
#-----------------------------------------
# Figure for zoom3
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Long Beach', figno=12)
plotfigure.show = False
plotfigure.kwargs = {'figsize': (8, 7)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Long Beach'
plotaxes.scaled = False
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.show = False
plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({-1.0: [0.0,0.0,1.0], \
-0.5: [0.5,0.5,1.0], \
0.0: [1.0,1.0,1.0], \
0.5: [1.0,0.5,0.5], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = cmin_ocean
plotitem.imshow_cmax = cmax_ocean
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [0]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.plot_var = geoplot.land
#plotitem.plot_var = 3
land_cmap = colormaps.make_colormap({0.0: [0.0,0.0,1.0], \
0.5: [1.0,0.0,0.0], \
1.0: [0.0,1.0,0.0]})
plotitem.imshow_cmap = geoplot.land_colors
#plotitem.imshow_cmap = land_cmap
plotitem.imshow_cmin = 0.
plotitem.imshow_cmax = 10.
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [0]
plotaxes.xlimits = [235.90, 235.98]
plotaxes.ylimits = [46.30, 46.39]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, imshow, \
savefig, plot
from pyclaw.plotters.plottools import plotbox
#addgauges(current_data)
title_hours(current_data)
ticklabel_format(format='plain', useOffset=False)
xticks(rotation=20)
a = gca()
#a.set_aspect(1./cos(46.86*pi/180.))
a.set_aspect(1. / cos(46.349 * pi / 180.))
plot([235.9499], [46.3490], 'wo')
#extent = (235.8756, 235.9116, 46.854, 46.8756)
#plotbox(extent)
#imshow(OcostaGE,extent=extent, alpha=0.5)
#extent = (235.81, 235.95, 46.85, 46.95)
#imshow(WestportGE,extent=extent, alpha=0.8)
plotaxes.afteraxes = aa
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
#plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.0]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 2}
plotitem.amr_contour_show = [0, 0, 0, 0, 1, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figure for zoom4
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Berm', figno=13)
plotfigure.show = False
plotfigure.kwargs = {'figsize': (12, 8)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Berm location'
plotaxes.scaled = False
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.show=False
plotitem.plot_var = geoplot.depth
#plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({0.0: [1.0,1.0,1.0], \
0.5: [1.0,0.8,0.0], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = 0.
plotitem.imshow_cmax = 3.
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.show=False
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 20.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
#plotaxes.xlimits = [235.88, 235.905]
#plotaxes.ylimits = [46.855, 46.87]
plotaxes.xlimits = [235.947, 235.951]
plotaxes.ylimits = [46.347, 46.35]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, imshow, \
savefig, plot
addgauges(current_data)
title_hours(current_data)
ticklabel_format(format='plain', useOffset=False)
xticks(rotation=20)
plot([235.9499], [46.3490], 'wo')
#extent = (235.8756, 235.9116, 46.854, 46.8756)
#imshow(OcostaGE,extent=extent, alpha=0.5)
a = gca()
a.set_aspect(1. / cos(46.349 * pi / 180.))
#extent = (235.81, 235.95, 46.85, 46.95)
#imshow(WestportGE,extent=extent, alpha=0.8)
plotaxes.afteraxes = aa
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
#plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 2}
plotitem.amr_contour_show = [0, 0, 0, 0, 1, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figure for zoom4 speed
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='Ocosta speed', figno=14)
plotfigure.show = False
plotfigure.kwargs = {'figsize': (12, 8)}
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.title = 'Ocosta'
plotaxes.scaled = False
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.show=False
def speed(current_data):
from numpy import sqrt, where
q = current_data.q
h = q[:, :, 0]
hu = q[:, :, 1]
hv = q[:, :, 2]
u = where(h > 0.01, hu / h, 0.)
v = where(h > 0.01, hv / h, 0.)
speed = sqrt(u**2 + v**2)
return v
plotitem.plot_var = speed
#plotitem.plot_var = geoplot.surface_or_depth
my_cmap = colormaps.make_colormap({0.0: [0.0,0.0,1.0], \
0.5: [1.0,1.0,1.0], \
1.0: [1.0,0.0,0.0]})
plotitem.imshow_cmap = my_cmap
plotitem.imshow_cmin = -3.
plotitem.imshow_cmax = 3.
plotitem.add_colorbar = True
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
#plotitem.show=False
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land_colors
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 20.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.amr_gridedges_show = [1]
#plotaxes.xlimits = [235.88, 235.905]
#plotaxes.ylimits = [46.855, 46.87]
plotaxes.xlimits = [235.88, 235.935]
plotaxes.ylimits = [46.845, 46.875]
def aa(current_data):
from pylab import ticklabel_format, xticks, gca, cos, pi, imshow, savefig
addgauges(current_data)
title_hours(current_data)
ticklabel_format(format='plain', useOffset=False)
xticks(rotation=20)
#extent = (235.8756, 235.9116, 46.854, 46.8756)
#imshow(OcostaGE,extent=extent, alpha=0.5)
a = gca()
a.set_aspect(1. / cos(46.86 * pi / 180.))
#extent = (235.81, 235.95, 46.85, 46.95)
#imshow(WestportGE,extent=extent, alpha=0.8)
plotaxes.afteraxes = aa
# add contour lines of bathy if desired:
plotitem = plotaxes.new_plotitem(plot_type='2d_contour')
#plotitem.show = False
plotitem.plot_var = geoplot.topo
plotitem.contour_levels = [0.]
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid', 'linewidths': 2}
plotitem.amr_contour_show = [0, 0, 0, 0, 1, 0]
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
#-----------------------------------------
# Figures for gauges
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='gauge plot', figno=300, \
type='each_gauge')
#plotfigure.clf_each_gauge = False
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.ylimits = [-1, 10]
plotaxes.xlimits = [-1, 10]
plotaxes.title = 'Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 4
plotitem.plotstyle = 'b-'
def axes_gauge(current_data):
from pylab import plot, legend, xticks, floor,\
yticks,xlabel,savefig,xlim,ylim,xlabel,ylabel
t = current_data.t
gaugeno = current_data.gaugeno
xticks(linspace(0, 1, 7), [str(i) for i in range(0, 7, 10)])
xlabel('time (minutes) after quake', fontsize=15)
ylabel('meters', fontsize=15)
ylim(-1, 10)
plotaxes.afteraxes = axes_gauge
#-----------------------------------------
# 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.print_gaugenos = 'all' # list of gauges 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
