def read_lab_data(d_param=None):
#import pdb; pdb.set_trace()
if d_param == None:
probdata = Data(os.path.join(datadir, 'setprob.data'))
d_param = probdata.d
print '+++ d_param = ', d_param
if d_param == 0.061: fname = 'd61g1234-new.txt'
if d_param == 0.080: fname = 'd80g1234-new.txt'
if d_param == 0.100: fname = 'd100g124-new.txt'
if d_param == 0.120: fname = 'd120g124-new.txt'
if d_param == 0.140: fname = 'd140g1234-new.txt'
if d_param == 0.149: fname = 'd149g124-new.txt'
if d_param == 0.189: fname = 'd189g1234-new.txt'
try:
print "Reading gauge data from ", fname
except:
print "*** No gauge data for d_param = ", d_param
try:
fname = os.path.join(datadir, fname)
gaugedata = loadtxt(fname)
except:
raise Exception("*** Cannot read file %s ", fname)
gauget = gaugedata[:, 0]
gauge_ave = {}
for gaugeno in [1, 2, 3, 4]:
try:
gauge_ave[gaugeno] = gaugedata[:, 3 * gaugeno] * 0.001
except:
# If fails for gaugeno==4 then it is gauge 3 that's missing:
gauge_ave[3] = None
#import pdb; pdb.set_trace()
try:
gauge_ave[4] = gaugedata[:, 9] * 0.001
except:
gauge_ave[2] = gaugedata[:, 4] * 0.001
gauge_ave[4] = gaugedata[:, 5] * 0.001
return d_param, gauget, gauge_ave
def read_setgauges(datadir):
"""
Read the info from setgauges.data.
"""
import os
import numpy as np
from pyclaw.data import Data
from matplotlib.mlab import find
setgauges = Data()
# default values if no gauges found:
setgauges.numgauges = 0
setgauges.gaugenos = []
setgauges.x = {}
setgauges.y = {}
setgauges.t1 = {}
setgauges.t2 = {}
fname = os.path.join(datadir, 'setgauges.data')
if not os.path.isfile(fname):
#print "*** Warning in read_setgauges: missing file ",fname
return setgauges
sgfile = open(fname, 'r')
lines = sgfile.readlines()
sgfile.close()
lineno = 0
ignore_line = True
while ignore_line:
line = lines[lineno] + "#"
#print "+++ lineno = %s, line = %s" % (lineno,line)
if line.split()[0][0] == "#":
lineno = lineno + 1
else:
ignore_line = False
try:
numgauges = int(line.split()[0])
except:
print "*** error setting numgauges"
return
if numgauges == 0:
return setgauges
#print '+++ ignoring %s lines, numgauges = %s' %(lineno, numgauges)
try:
sgno, x, y, t1, t2 = np.loadtxt(fname, unpack=True, skiprows=lineno+1, \
usecols=range(5))
if numgauges == 1:
# loadtxt returns numbers rather than arrays in this case:
sgno = [sgno]
x = [x]
y = [y]
t1 = [t1]
t2 = [t2]
except:
print "*** problem reading gauges from setgauges.data"
return setgauges
sgno = np.array(sgno, dtype=int) # convert to int
setgauges.gaugenos = sgno
setgauges.numgauges = numgauges
for n in sgno:
nn = find(sgno == n)
if len(nn) > 1:
print "*** Warning: found more than one gauge numbered ", n
if len(nn) == 0:
print "*** Error: didn't find gauge number %s in %s" % (n, fname)
else:
nn = nn[0]
setgauges.x[n] = x[nn]
setgauges.y[n] = y[nn]
setgauges.t1[n] = t1[nn]
setgauges.t2[n] = t2[nn]
return setgauges
def plotgauge(gaugeno, plotdata, verbose=False):
#==========================================
"""
Plot all requested plots for a single gauge from the computation.
The plots are requested by setting attributes of plotdata
to ClawPlotFigure objects with plot_type="each_gauge".
"""
if verbose:
gaugesoln = plotdata.getgauge(gaugeno)
print ' Plotting gauge %s at x = %g, y = %g ... ' \
% (gaugeno, gaugesoln.x, gaugesoln.y)
if plotdata.mode() == 'iplotclaw':
pylab.ion()
try:
plotfigure_dict = plotdata.plotfigure_dict
except:
print '*** Error in plotgauge: plotdata missing plotfigure_dict'
print '*** This should not happen'
return None
if len(plotfigure_dict) == 0:
print '*** Warning in plotgauge: plotdata has empty plotfigure_dict'
print '*** Apparently no figures to plot'
# initialize current_data containing data that will be passed
# to beforegauge, aftergauge, afteraxes commands
current_data = Data()
current_data.user = Data() # for user specified attributes
# to avoid potential conflicts
current_data.plotdata = plotdata
current_data.gaugeno = gaugeno
# call beforegauge if present, which might define additional
# attributes in current_data or otherwise set up plotting for this
# gauge.
beforegauge = getattr(plotdata, 'beforegauge', None)
if beforegauge:
if isinstance(beforegauge, str):
# a string to be executed
exec(beforegauge)
else:
# assume it's a function
try:
output = beforegauge(current_data)
if output: current_data = output
except:
print '*** Error in beforegauge ***'
raise
# iterate over each single plot that makes up this gauge:
# -------------------------------------------------------
if plotdata._mode == 'iplotclaw':
gaugesoln = plotdata.getgauge(gaugeno)
#import pdb; pdb.set_trace()
print ' Plotting Gauge %s at x = %g, y = %g ... ' \
% (gaugeno, gaugesoln.x, gaugesoln.y)
requested_fignos = plotdata.iplotclaw_fignos
else:
requested_fignos = plotdata.print_fignos
plotted_fignos = []
plotdata = set_show(plotdata) # set _show attributes for which figures
# and axes should be shown.
# loop over figures to appear for this gauge:
# -------------------------------------------
for figname in plotdata._fignames:
plotfigure = plotdata.plotfigure_dict[figname]
if (not plotfigure._show) or (plotfigure.type != 'each_gauge'):
continue # skip to next figure
figno = plotfigure.figno
if requested_fignos != 'all':
if figno not in requested_fignos:
continue # skip to next figure
plotted_fignos.append(figno)
if not plotfigure.kwargs.has_key('facecolor'):
# use Clawpack's default bg color (tan)
plotfigure.kwargs['facecolor'] = '#ffeebb'
# create figure and set handle:
plotfigure._handle = pylab.figure(num=figno, **plotfigure.kwargs)
pylab.ioff()
if plotfigure.clf_each_gauge:
pylab.clf()
try:
plotaxes_dict = plotfigure.plotaxes_dict
except:
print '*** Error in plotgauge: plotdata missing plotaxes_dict'
print '*** This should not happen'
return None
if (len(plotaxes_dict) == 0) or (len(plotfigure._axesnames) == 0):
print '*** Warning in plotgauge: plotdata has empty plotaxes_dict'
print '*** Apparently no axes to plot in figno ', figno
# loop over axes to appear on this figure:
# ----------------------------------------
for axesname in plotfigure._axesnames:
plotaxes = plotaxes_dict[axesname]
if not plotaxes._show:
continue # skip this axes if no items show
# create the axes:
axescmd = getattr(plotaxes, 'axescmd', 'subplot(1,1,1)')
axescmd = 'plotaxes._handle = pylab.%s' % axescmd
exec(axescmd)
pylab.hold(True)
# loop over items:
# ----------------
for itemname in plotaxes._itemnames:
plotitem = plotaxes.plotitem_dict[itemname]
try:
outdir = plotitem.outdir
if outdir is None:
outdir = plotdata.outdir
gaugesoln = plotdata.getgauge(gaugeno, outdir)
except:
print '*** Cannot find gauge number ', gaugeno
print '*** looking in directory ', outdir
print '*** cwd = ', os.getcwd()
return None
#import pdb; pdb.set_trace()
current_data.gaugesoln = gaugesoln
current_data.q = gaugesoln.q
current_data.t = gaugesoln.t
if plotitem._show:
try:
output = plotgauge1(gaugesoln,plotitem,\
current_data)
if output: current_data = output
if verbose:
print ' Plotted plotitem ', itemname
except:
print '*** Error in plotgauge: problem calling plotgauge1'
traceback.print_exc()
return None
# end of loop over plotitems
for itemname in plotaxes._itemnames:
plotitem = plotaxes.plotitem_dict[itemname]
if plotitem.afteritem:
print "*** ClawPlotItem.afteritem is deprecated"
print "*** use ClawPlotAxes.afteraxes "
print "*** or ClawPlotItem.aftergrid instead"
pylab.title("%s at gauge %s" % (plotaxes.title, gaugeno))
# call an afteraxes function if present:
afteraxes = getattr(plotaxes, 'afteraxes', None)
if afteraxes:
if isinstance(afteraxes, str):
# a string to be executed
exec(afteraxes)
else:
# assume it's a function
try:
current_data.plotaxes = plotaxes
current_data.plotfigure = plotaxes._plotfigure
output = afteraxes(current_data)
if output: current_data = output
except:
print '*** Error in afteraxes ***'
raise
if plotaxes.scaled:
pylab.axis('scaled')
# set axes limits:
if (plotaxes.xlimits is not None) & (type(plotaxes.xlimits)
is not str):
try:
pylab.xlim(plotaxes.xlimits[0], plotaxes.xlimits[1])
except:
pass # let axis be set automatically
if (plotaxes.ylimits is not None) & (type(plotaxes.ylimits)
is not str):
try:
pylab.ylim(plotaxes.ylimits[0], plotaxes.ylimits[1])
except:
pass # let axis be set automatically
# end of loop over plotaxes
# end of loop over plotfigures
# call an aftergauge function if present:
aftergauge = getattr(plotdata, 'aftergauge', None)
if aftergauge:
if isinstance(aftergauge, str):
# a string to be executed
exec(aftergauge)
else:
# assume it's a function
try:
output = aftergauge(current_data)
if output: current_data = output
except:
print '*** Error in aftergauge ***'
raise
if plotdata.mode() == 'iplotclaw':
pylab.ion()
for figno in plotted_fignos:
pylab.figure(figno)
pylab.draw()
if verbose:
print ' Done with plotgauge for gauge %i' % (gaugeno)
# print the figure(s) to file(s) if requested:
if (plotdata.mode() != 'iplotclaw') & plotdata.printfigs:
# iterate over all figures that are to be printed:
for figno in plotted_fignos:
printfig(gaugeno=gaugeno, figno=figno, \
format=plotdata.print_format, plotdir=plotdata.plotdir,\
verbose=verbose)
return current_data
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 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 = getattr(topoplotdata, 'topotype', 3)
cmap = getattr(topoplotdata, 'cmap', bathy3_colormap)
climits = getattr(topoplotdata, 'climits', [-50, 50])
figno = getattr(topoplotdata, 'figno', 200)
addcolorbar = getattr(topoplotdata, 'addcolorbar', True)
addcontour = getattr(topoplotdata, 'addcontour', False)
contour_levels = getattr(topoplotdata, 'contour_levels', [0, 0])
xlimits = getattr(topoplotdata, 'xlimits', None)
ylimits = getattr(topoplotdata, 'ylimits', None)
coarsen = getattr(topoplotdata, 'coarsen', 1)
if abs(topotype) != 3:
print "*** Only topotype = 3, -3 implemented so far."
return
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)
if topotype < 0:
topo = -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
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
#import pdb; pdb.set_trace()
if figno:
pylab.figure(figno)
pylab.pcolor(x, y, topo, cmap=cmap)
pylab.clim(climits)
pylab.axis('scaled')
if addcolorbar:
pylab.colorbar()
if addcontour:
pylab.contour(x, y, topo, levels=contour_levels, colors='k')
gridedges_show = True
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')
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
"""
Set up the plot figures, axes, and items to be done for each frame.
This module is imported by the plotting routines and then the
function setplot is called to set the plot parameters.
"""
from pyclaw.data import Data
userdata = Data(['claw.data','setprob.data'])
#--------------------------
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.
"""
plotdata.clearfigures() # clear any old figures,axes,items data
# Figure for q[0]
plotfigure = plotdata.new_plotfigure(name='q[0]', figno=0)
# Set up for axes in this figure:
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
Specifying a function plot_var for the plotting variable
========================================================
The pressure q[0] and q[1] are plotted on two sets of axes in a single
figure.
The Riemann invariants R1 = (-p+Z*u)/2*Z and R2 = (p-Z*u)/2*Z
are plotted in a second figure.
This illustrates how to specify plot_var as a function.
"""
from numpy import sqrt
from pyclaw.data import Data
probdata = Data('setprob.data') # read problem data values
Z = sqrt(probdata.rho * probdata.K) # impedance used in R1 and R2
#--------------------------
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.
"""
plotdata.clearfigures() # clear any old figures,axes,items data
def read_setgauges(datadir):
"""
Read the info from setgauges.data.
"""
import os
import numpy as np
from pyclaw.data import Data
from matplotlib.mlab import find
setgauges = Data()
# default values if no gauges found:
setgauges.numgauges = 0
setgauges.gaugenos = []
setgauges.x = {}
setgauges.y = {}
setgauges.t1 = {}
setgauges.t2 = {}
fname = os.path.join(datadir, 'setgauges.data')
if not os.path.isfile(fname):
#print "*** Warning in read_setgauges: missing file ",fname
return setgauges
sgfile = open(fname,'r')
lines = sgfile.readlines()
sgfile.close()
lineno = 0
ignore_line = True
while ignore_line:
line = lines[lineno] + "#"
#print "+++ lineno = %s, line = %s" % (lineno,line)
if line.split()[0][0]=="#":
lineno = lineno+1
else:
ignore_line = False
try:
numgauges = int(line.split()[0])
except:
print "*** error setting numgauges"
return
if numgauges==0:
return setgauges
#print '+++ ignoring %s lines, numgauges = %s' %(lineno, numgauges)
try:
sgno, x, y, t1, t2 = np.loadtxt(fname, unpack=True, skiprows=lineno+1, \
usecols=range(5))
if numgauges==1:
# loadtxt returns numbers rather than arrays in this case:
sgno = [sgno]; x = [x]; y = [y]; t1 = [t1]; t2 = [t2]
except:
print "*** problem reading gauges from setgauges.data"
return setgauges
sgno = np.array(sgno, dtype=int) # convert to int
setgauges.gaugenos = sgno
setgauges.numgauges = numgauges
for n in sgno:
nn = find(sgno==n)
if len(nn) > 1:
print "*** Warning: found more than one gauge numbered ",n
if len(nn) == 0:
print "*** Error: didn't find gauge number %s in %s" % (n,fname)
else:
nn = nn[0]
setgauges.x[n] = x[nn]
setgauges.y[n] = y[nn]
setgauges.t1[n] = t1[nn]
setgauges.t2[n] = t2[nn]
return setgauges
def plotgauge(gaugeno, plotdata, verbose=False):
#==========================================
"""
Plot all requested plots for a single gauge from the computation.
The plots are requested by setting attributes of plotdata
to ClawPlotFigure objects with plot_type="each_gauge".
"""
if verbose:
gaugesoln = plotdata.getgauge(gaugeno)
print ' Plotting gauge %s at x = %g, y = %g ... ' \
% (gaugeno, gaugesoln.x, gaugesoln.y)
if plotdata.mode() == 'iplotclaw':
pylab.ion()
try:
plotfigure_dict = plotdata.plotfigure_dict
except:
print '*** Error in plotgauge: plotdata missing plotfigure_dict'
print '*** This should not happen'
return None
if len(plotfigure_dict) == 0:
print '*** Warning in plotgauge: plotdata has empty plotfigure_dict'
print '*** Apparently no figures to plot'
# initialize current_data containing data that will be passed
# to beforegauge, aftergauge, afteraxes commands
current_data = Data()
current_data.user = Data() # for user specified attributes
# to avoid potential conflicts
current_data.plotdata = plotdata
current_data.gaugeno = gaugeno
# call beforegauge if present, which might define additional
# attributes in current_data or otherwise set up plotting for this
# gauge.
beforegauge = getattr(plotdata, 'beforegauge', None)
if beforegauge:
if isinstance(beforegauge, str):
# a string to be executed
exec(beforegauge)
else:
# assume it's a function
try:
output = beforegauge(current_data)
if output: current_data = output
except:
print '*** Error in beforegauge ***'
raise
# iterate over each single plot that makes up this gauge:
# -------------------------------------------------------
if plotdata._mode == 'iplotclaw':
gaugesoln = plotdata.getgauge(gaugeno)
#import pdb; pdb.set_trace()
print ' Plotting Gauge %s at x = %g, y = %g ... ' \
% (gaugeno, gaugesoln.x, gaugesoln.y)
requested_fignos = plotdata.iplotclaw_fignos
else:
requested_fignos = plotdata.print_fignos
plotted_fignos = []
plotdata = set_show(plotdata) # set _show attributes for which figures
# and axes should be shown.
# loop over figures to appear for this gauge:
# -------------------------------------------
for figname in plotdata._fignames:
plotfigure = plotdata.plotfigure_dict[figname]
if (not plotfigure._show) or (plotfigure.type != 'each_gauge'):
continue # skip to next figure
figno = plotfigure.figno
if requested_fignos != 'all':
if figno not in requested_fignos:
continue # skip to next figure
plotted_fignos.append(figno)
if not plotfigure.kwargs.has_key('facecolor'):
# use Clawpack's default bg color (tan)
plotfigure.kwargs['facecolor'] = '#ffeebb'
# create figure and set handle:
plotfigure._handle = pylab.figure(num=figno, **plotfigure.kwargs)
pylab.ioff()
if plotfigure.clf_each_gauge:
pylab.clf()
try:
plotaxes_dict = plotfigure.plotaxes_dict
except:
print '*** Error in plotgauge: plotdata missing plotaxes_dict'
print '*** This should not happen'
return None
if (len(plotaxes_dict) == 0) or (len(plotfigure._axesnames) == 0):
print '*** Warning in plotgauge: plotdata has empty plotaxes_dict'
print '*** Apparently no axes to plot in figno ',figno
# loop over axes to appear on this figure:
# ----------------------------------------
for axesname in plotfigure._axesnames:
plotaxes = plotaxes_dict[axesname]
if not plotaxes._show:
continue # skip this axes if no items show
# create the axes:
axescmd = getattr(plotaxes,'axescmd','subplot(1,1,1)')
axescmd = 'plotaxes._handle = pylab.%s' % axescmd
exec(axescmd)
pylab.hold(True)
# loop over items:
# ----------------
for itemname in plotaxes._itemnames:
plotitem = plotaxes.plotitem_dict[itemname]
try:
outdir = plotitem.outdir
if outdir is None:
outdir = plotdata.outdir
gaugesoln = plotdata.getgauge(gaugeno, outdir)
except:
print '*** Cannot find gauge number ',gaugeno
print '*** looking in directory ', outdir
print '*** cwd = ',os.getcwd()
return None
#import pdb; pdb.set_trace()
current_data.gaugesoln = gaugesoln
current_data.q = gaugesoln.q
current_data.t = gaugesoln.t
if plotitem._show:
try:
output = plotgauge1(gaugesoln,plotitem,\
current_data)
if output: current_data = output
if verbose:
print ' Plotted plotitem ', itemname
except:
print '*** Error in plotgauge: problem calling plotgauge1'
traceback.print_exc()
return None
# end of loop over plotitems
for itemname in plotaxes._itemnames:
plotitem = plotaxes.plotitem_dict[itemname]
if plotitem.afteritem:
print "*** ClawPlotItem.afteritem is deprecated"
print "*** use ClawPlotAxes.afteraxes "
print "*** or ClawPlotItem.aftergrid instead"
pylab.title("%s at gauge %s" % (plotaxes.title,gaugeno))
# call an afteraxes function if present:
afteraxes = getattr(plotaxes, 'afteraxes', None)
if afteraxes:
if isinstance(afteraxes, str):
# a string to be executed
exec(afteraxes)
else:
# assume it's a function
try:
current_data.plotaxes = plotaxes
current_data.plotfigure = plotaxes._plotfigure
output = afteraxes(current_data)
if output: current_data = output
except:
print '*** Error in afteraxes ***'
raise
if plotaxes.scaled:
pylab.axis('scaled')
# set axes limits:
if (plotaxes.xlimits is not None) & (type(plotaxes.xlimits) is not str):
try:
pylab.xlim(plotaxes.xlimits[0], plotaxes.xlimits[1])
except:
pass # let axis be set automatically
if (plotaxes.ylimits is not None) & (type(plotaxes.ylimits) is not str):
try:
pylab.ylim(plotaxes.ylimits[0], plotaxes.ylimits[1])
except:
pass # let axis be set automatically
# end of loop over plotaxes
# end of loop over plotfigures
# call an aftergauge function if present:
aftergauge = getattr(plotdata, 'aftergauge', None)
if aftergauge:
if isinstance(aftergauge, str):
# a string to be executed
exec(aftergauge)
else:
# assume it's a function
try:
output = aftergauge(current_data)
if output: current_data = output
except:
print '*** Error in aftergauge ***'
raise
if plotdata.mode() == 'iplotclaw':
pylab.ion()
for figno in plotted_fignos:
pylab.figure(figno)
pylab.draw()
if verbose:
print ' Done with plotgauge for gauge %i' % (gaugeno)
# print the figure(s) to file(s) if requested:
if (plotdata.mode() != 'iplotclaw') & plotdata.printfigs:
# iterate over all figures that are to be printed:
for figno in plotted_fignos:
printfig(gaugeno=gaugeno, figno=figno, \
format=plotdata.print_format, plotdir=plotdata.plotdir,\
verbose=verbose)
return current_data
def get_frame(self, frameno):
if self.solutions.has_key(frameno):
# don't read if already in dictionary:
return self.grid, self.solutions[frameno]
fname = "fort.fg%s_%s" % (str(
self.fgno).zfill(2), str(frameno).zfill(4))
fname = os.path.join(self.outdir, fname)
if not os.path.exists(fname):
print "*** Did not find file ", fname, " in directory ", self.outdir
raise IOError("Missing fixed grid output file")
self.grid = Data()
grid = self.grid
# Read parameters from header:
file = open(fname, 'r')
line = file.readline()
t = float(line.split()[0])
print "Reading fixed grid output from ", fname
print ' Frame %s at t = %s' % (frameno, t)
line = file.readline()
grid.mx = int(line.split()[0])
line = file.readline()
grid.my = int(line.split()[0])
line = file.readline()
grid.xlow = float(line.split()[0])
line = file.readline()
grid.ylow = float(line.split()[0])
line = file.readline()
grid.xhi = float(line.split()[0])
line = file.readline()
grid.yhi = float(line.split()[0])
file.close()
grid.x = linspace(grid.xlow, grid.xhi, grid.mx + 1)
grid.y = linspace(grid.ylow, grid.yhi, grid.my + 1)
grid.dx = grid.x[1] - grid.x[0]
grid.dy = grid.y[1] - grid.y[0]
grid.xcenter = grid.x[:-1] + grid.dx / 2.
grid.ycenter = grid.y[:-1] + grid.dy / 2.
d = loadtxt(fname, skiprows=8)
solution = Data()
solution.t = t
solution.ncols = d.shape[1]
solution.h = reshape(d[:, 0], (grid.my, grid.mx))
solution.B = reshape(d[:, 3], (grid.my, grid.mx))
solution.eta = reshape(d[:, 4], (grid.my, grid.mx))
solution.surface = ma.masked_where(isnan(solution.eta), solution.eta)
solution.land = ma.masked_where(solution.h > self.drytol, solution.B)
solution.fg = empty((grid.my, grid.mx, solution.ncols), dtype=float)
for col in range(solution.ncols):
solution.fg[:, :, col] = reshape(d[:, col], (grid.my, grid.mx))
self.solutions[frameno] = solution
return grid, solution
def get_frame(self, frameno):
if self.solutions.has_key(frameno):
# don't read if already in dictionary:
return self.grid, self.solutions[frameno]
fname = "fort.fg%s_%s" % (str(self.fgno).zfill(2), str(frameno).zfill(4))
fname = os.path.join(self.outdir,fname)
if not os.path.exists(fname):
print "*** Did not find file ",fname," in directory ",self.outdir
raise IOError("Missing fixed grid output file")
self.grid = Data()
grid = self.grid
# Read parameters from header:
file = open(fname,'r')
line = file.readline()
t = float(line.split()[0])
print "Reading fixed grid output from ",fname
print ' Frame %s at t = %s' % (frameno,t)
line = file.readline()
grid.mx = int(line.split()[0])
line = file.readline()
grid.my = int(line.split()[0])
line = file.readline()
grid.xlow = float(line.split()[0])
line = file.readline()
grid.ylow = float(line.split()[0])
line = file.readline()
grid.xhi = float(line.split()[0])
line = file.readline()
grid.yhi = float(line.split()[0])
file.close()
grid.x = linspace(grid.xlow, grid.xhi, grid.mx+1)
grid.y = linspace(grid.ylow, grid.yhi, grid.my+1)
grid.dx = grid.x[1]-grid.x[0]
grid.dy = grid.y[1]-grid.y[0]
grid.xcenter = grid.x[:-1] + grid.dx/2.
grid.ycenter = grid.y[:-1] + grid.dy/2.
d = loadtxt(fname, skiprows=8)
solution = Data()
solution.t = t
solution.ncols = d.shape[1]
solution.h = reshape(d[:,0], (grid.my,grid.mx))
solution.B = reshape(d[:,3], (grid.my,grid.mx))
solution.eta = reshape(d[:,4], (grid.my,grid.mx))
solution.surface = ma.masked_where(isnan(solution.eta),solution.eta)
solution.land = ma.masked_where(solution.h>self.drytol,solution.B)
solution.fg = empty((grid.my,grid.mx,solution.ncols), dtype=float)
for col in range(solution.ncols):
solution.fg[:,:,col] = reshape(d[:,col],(grid.my,grid.mx))
self.solutions[frameno] = solution
return grid, solution
def read_dtopo(fname, topotype=1):
header = read_header(fname)
if (len(header["header_lines"]) == 0) and (abs(topotype) > 1):
raise ValueError("*** topotype = %s but no header found" % topotype)
if (len(header["header_lines"]) > 0) and (abs(topotype) == 1):
raise ValueError("*** topotype = %s but header found" % topotype)
header_length = header["header_lines"].count("\n")
if topotype == 1:
d = np.loadtxt(fname, skiprows=header_length)
ncol = d.shape[1]
if ncol == 3:
tcol = None
xcol = d[:, 0]
ycol = d[:, 1]
dzcol = d[:, 2]
else:
tcol = d[:, 0]
xcol = d[:, 1]
ycol = d[:, 2]
dzcol = d[:, 3]
xdiff = np.diff(xcol)
inddiff = pylab.find(xdiff < 0)
mx = inddiff[0] + 1
mt = 1
if tcol is not None:
# check if there is more than one time in this file:
tdiff = np.diff(tcol)
inddiff = pylab.find(tdiff > 0)
if len(inddiff) > 0:
mt = len(inddiff) + 1
my = len(xcol) / (mx * mt)
if my != int(len(xcol) / float(mx * mt)):
print("*** found mx = %s, mt = %s" % (mx, mt))
raise ValueError("*** mx*mt does not divide length of data")
print("Found mt = %s times with mx = %s, my = %s" % (mt, mx, my))
if tcol is None:
t = []
else:
t = tcol[0 :: mx * my]
X = np.reshape(xcol[: mx * my], (my, mx))
Y = np.reshape(ycol[: mx * my], (my, mx))
dZ = np.reshape(dzcol, (mt, my, mx))
elif topotype == 3:
try:
my = header["nrows"]
mx = header["ncols"]
mt = header["mtimes"]
xll = header["xll"]
yll = header["yll"]
t0 = header["t0"]
dx = header["dx"]
dy = header["dy"]
dt = header["dt"]
except:
raise ValueError("*** Missing information from header")
if (dt == 0) or (mt == 1):
t = np.array([t0])
else:
t = np.arange(t0, t0 + mt * dt, dt)
x = np.linspace(xll, xll + mx * dx, mx)
y = np.linspace(yll, yll + my * dy, my)
X, Y = np.meshgrid(x, y)
X = X.T
Y = Y.T
fdata = np.loadtxt(fname, skiprows=header_length)
dzcol = np.reshape(fdata, (mx * my * mt, 1))
dZ = np.empty((mt, mx, my))
for i in range(mt):
dzi = np.reshape(dzcol[i * mx * my : (i + 1) * mx * my], (my, mx))
dzi = np.flipud(dzi)
dZ[i, :, :] = dzi.T
else:
raise ValueError("*** Cannot read topotype = " % topotype)
dtopo = Data()
dtopo.t = t
dtopo.X = X
dtopo.Y = Y
dtopo.dZ = dZ
return dtopo
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
probdata = Data(os.path.join(datadir, 'setprob.data'))
d = probdata.d
clawdata = Data(os.path.join(datadir, 'amr2ez.data'))
my = clawdata.my
print "+++ in setplot d = ", d
print "+++ in setplot my = ", my
def set_drytol(current_data):
# The drytol parameter is used in masking land and water and
# affects what color map is used for cells with small water depth h.
# The cell will be plotted as dry if h < drytol.
# The best value to use often depends on the application and can
# be set here (measured in meters):
current_data.user.drytol = 1.e-3
plotdata.beforeframe = set_drytol
# To plot gauge locations on imshow or contour plot, use this as
# an afteraxis function:
figkwargs = dict(figsize=(18, 9), dpi=800)
#-----------------------------------------
# Figure for imshow plot
#-----------------------------------------
plotfigure = plotdata.new_plotfigure(name='imshow', figno=0)
plotfigure.show = True
#plotfigure.kwargs = figkwargs
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes('imshow')
plotaxes.title = 'Case 1'
plotaxes.scaled = True
def addgauges(current_data, fnt=14):
from pyclaw.plotters import gaugetools
gaugetools.plot_gauge_locations(current_data.plotdata, \
gaugenos='all', format_string='ko', add_labels=True,markersize=8,fontsize=fnt)
def fixup(current_data):
import pylab
t = current_data.t
pylab.title('Case 1: surface at %4.2f seconds' % t, fontsize=14)
#pylab.xticks([141.0325-.03,141.0325,141.0325+.03],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_fukushima = 141.0325
#y_fukushima = 37.421389
#pylab.plot([x_fukushima],[y_fukushima],'wo',markersize=8)
#pylab.text(x_fukushima-.015,y_fukushima+.004,'Fukushima',color='w',fontsize=15)
addgauges(current_data)
plotaxes.afteraxes = fixup
# Water
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.show = True
#plotitem.plot_var = geoplot.surface
plotitem.plot_var = geoplot.surface_or_depth
plotitem.imshow_cmap = geoplot.tsunami_colormap
plotitem.imshow_cmin = -.02
plotitem.imshow_cmax = .02
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.gridedges_show = 1
# 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 = arange(-2.5, 1, .01)
plotitem.amr_contour_colors = ['k'] # color on each level
plotitem.kwargs = {'linestyles': 'solid'}
plotitem.amr_contour_show = [2] # show contours only on finest level
plotitem.gridlines_show = 0
plotitem.gridedges_show = 0
# Land
plotitem = plotaxes.new_plotitem(plot_type='2d_imshow')
plotitem.show = True
plotitem.plot_var = geoplot.land
plotitem.imshow_cmap = geoplot.land1_colormap
plotitem.imshow_cmin = 0.0
plotitem.imshow_cmax = 1.0
plotitem.add_colorbar = False
plotitem.amr_gridlines_show = [0, 0, 0]
plotitem.gridedges_show = 1
#dx2 = .04
#dy2 = .08
plotaxes.xlimits = [-1.0, 3.0]
# plotaxes.xlimits = [-1.0,2.0]
plotaxes.ylimits = [0, 1.]
# plotaxes.ylimits = [-1.,1.]
#-----------------------------------------
# Figure for line plot
#-----------------------------------------
# plotfigure = plotdata.new_plotfigure(name='line', figno=500)
# Set up for axes in this figure:
# plotaxes = plotfigure.new_plotaxes()
# plotaxes.xlimits = [-12,12]
# plotaxes.ylimits = [-12, 12]
# plotaxes.title = 'Surface'
# Plot surface as blue curve:
# plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
# plotitem.plotstyle = 'b-'
# Plot Runup
# t,x1,x2 = loadtxt('_output/fort.runup',unpack=True)
# plot(t,x1)
# plot(t,x2)
#-----------------------------------------
# Figure for cross section of surface
#-----------------------------------------
# plotfigure = plotdata.new_plotfigure(name='surface', figno=200)
# plotaxes = plotfigure.new_plotaxes('surface')
# plotitem = plotaxes.new_plotitem(plot_type='1d_from_2d_data')
# def crosssec(current_data):
# q = current_data.q
# x = current_data.x
# return x[:,50], q[:,50,3]
# plotitem.map_2d_to_1d = crosssec
# def plot_beach(current_data):
# import pylab
# x = current_data.x[:,50]
# pylab.plot(x, -0.5*x,'k')
# plotaxes.ylimits = [-0.5,0.5]
# plotaxes.afteraxes = plot_beach
#-----------------------------------------
# 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, 5.0]
#plotaxes.ylimits = [-0.03,0.03]
plotaxes.title = 'Surface'
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
# Plot fine grid as red curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.show = False
#plotitem.outdir = '_output_fine'
plotitem.plot_var = 3
plotitem.plotstyle = '-'
plotitem.color = 'r'
# 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 eta
plotitem.plot_var = gaugetopo
plotitem.clf_each_gauge = False
plotitem.plotstyle = 'b-'
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([range(10)])
#plotaxes.afteraxes = add_zeroline
def plot_labData(current_data):
import pylab
gaugeno = current_data.gaugeno
try:
d_param = d
print "+++ d_param = ", d_param
except:
print "+++ d not set"
d_param = None
d, gauget, gauge_ave = read_lab_data(d_param)
try:
pylab.plot(gauget, gauge_ave[gaugeno], 'k')
pylab.legend(('GeoClaw', 'Lab Data'), loc='lower right')
#pylab.legend(('GeoClaw coarse', 'GeoClaw fine', 'Lab Data'), loc='lower right')
except:
print "No data for gauge ", gaugeno
#gaugeTime
print "+++ for gauges, my = ", my
if my:
pylab.title("Gauge %s for d = %4.3f with my = %s" %
(gaugeno, d, my))
else:
pylab.title("Gauge %s for d = %4.3f" % (gaugeno, d))
plotaxes.afteraxes = plot_labData
def add_tankdata(datafile):
from pylab import plot
import numpy as np
ts = np.loadtxt(datafile)
plot(ts[:, 0], ts[:, 1], 'k-')
#-----------------------------------------
# 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 = [0] # list of frames to print
plotdata.print_gaugenos = 'all' # list of gauges to print
plotdata.print_fignos = [300] # list of figures to print
plotdata.html = True # create html files of plots?
plotdata.html_homelink = '../README.html' # pointer for top of index
plotdata.latex = False # create latex file of plots?
plotdata.latex_figsperline = 2 # layout of plots
plotdata.latex_framesperline = 1 # layout of plots
plotdata.latex_makepdf = False # also run pdflatex?
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 read_dtopo(fname, topotype=1):
header = read_header(fname)
if (len(header['header_lines']) == 0) and (abs(topotype)>1):
raise ValueError("*** topotype = %s but no header found" % topotype)
if (len(header['header_lines']) > 0) and (abs(topotype)==1):
raise ValueError("*** topotype = %s but header found" % topotype)
header_length = header['header_lines'].count('\n')
if topotype==1:
d = np.loadtxt(fname, skiprows=header_length)
ncol = d.shape[1]
if ncol == 3:
tcol = None
xcol = d[:,0]
ycol = d[:,1]
dzcol = d[:,2]
else:
tcol = d[:,0]
xcol = d[:,1]
ycol = d[:,2]
dzcol = d[:,3]
xdiff = np.diff(xcol)
inddiff = pylab.find(xdiff<0)
mx = inddiff[0]+1
mt = 1
if tcol is not None:
# check if there is more than one time in this file:
tdiff = np.diff(tcol)
inddiff = pylab.find(tdiff>0)
if len(inddiff) > 0:
mt = len(inddiff)+1
my = len(xcol)/(mx*mt)
if my != int(len(xcol)/float(mx*mt)):
print "*** found mx = %s, mt = %s" % (mx,mt)
raise ValueError("*** mx*mt does not divide length of data")
print "Found mt = %s times with mx = %s, my = %s" % (mt,mx,my)
if tcol is None:
t = []
else:
t = tcol[0::mx*my]
X = np.reshape(xcol[:mx*my],(my,mx))
Y = np.reshape(ycol[:mx*my],(my,mx))
dZ = np.reshape(dzcol,(mt,my,mx))
elif topotype==3:
try:
my = header['nrows']
mx = header['ncols']
mt = header['mtimes']
xll = header['xll']
yll = header['yll']
t0 = header['t0']
dx = header['dx']
dy = header['dy']
dt = header['dt']
except:
raise ValueError("*** Missing information from header")
if (dt==0) or (mt==1):
t = np.array([t0])
else:
t = np.arange(t0,t0+mt*dt,dt)
x = np.linspace(xll,xll + mx*dx, mx)
y = np.linspace(yll,yll + my*dy, my)
X,Y = np.meshgrid(x,y)
X = X.T
Y = Y.T
fdata = np.loadtxt(fname, skiprows=header_length)
dzcol = np.reshape(fdata,(mx*my*mt, 1))
dZ = np.empty((mt,mx,my))
for i in range(mt):
dzi = np.reshape(dzcol[i*mx*my:(i+1)*mx*my], (my,mx))
dzi = np.flipud(dzi)
dZ[i,:,:] = dzi.T
else:
raise ValueError("*** Cannot read topotype = " % topotype)
dtopo = Data()
dtopo.t = t
dtopo.X = X
dtopo.Y = Y
dtopo.dZ = dZ
return dtopo
