|
setplot_kml.py.html |
 |
|
Source file: setplot_kml.py
|
|
Directory: /Users/rjl/git/clawpack/geoclaw/examples/storm-surge/ike
|
|
Converted: Wed Dec 28 2016 at 23:12:20
using clawcode2html
|
|
This documentation file will
not reflect any later changes in the source file.
|
"""
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 __future__ import absolute_import
article = False
import os
import numpy
# Plot customization
import matplotlib
import matplotlib.pyplot as plt
import datetime
from clawpack.visclaw import colormaps, geoplot
import clawpack.clawutil.data as clawutil
import clawpack.amrclaw.data as amrclaw
import clawpack.geoclaw.data as geodata
import clawpack.geoclaw.surge.plot as surgeplot
import clawpack.geoclaw.surge.data as surgedata
try:
from setplotfg import setplotfg
except:
setplotfg = None
# Gauge support
days2seconds = lambda days: days * 60.0**2 * 24.0
date2seconds = lambda date: days2seconds(date.days) + date.seconds
seconds2days = lambda secs: secs / (24.0 * 60.0**2)
min2deg = lambda minutes: minutes / 60.0
ft2m = lambda x:0.3048 * x
# Gauge name translation
gauge_name_trans = {1:"W", 2:"X", 3:"Y", 4:"Z"}
gauge_surface_offset = [0.0, 0.0]
gauge_landfall = []
gauge_landfall.append(datetime.datetime(2008,9,13 + 1,7)
- datetime.datetime(2008,1,1,0))
gauge_landfall.append(datetime.datetime(2008,9,13 - 1,7)
- datetime.datetime(2008,1,1,0))
gauge_landfall.append(days2seconds(4.25))
def setplot(plotdata):
r"""Setplot function for surge plotting"""
plotdata.clearfigures() # clear any old figures,axes,items data
plotdata.format = 'binary'
fig_num_counter = surgeplot.figure_counter()
# Load data from output
clawdata = clawutil.ClawInputData(2)
clawdata.read(os.path.join(plotdata.outdir,'claw.data'))
amrdata = amrclaw.AmrclawInputData(clawdata)
amrdata.read(os.path.join(plotdata.outdir,'amr.data'))
physics = geodata.GeoClawData()
physics.read(os.path.join(plotdata.outdir,'geoclaw.data'))
surge_data = surgedata.SurgeData()
surge_data.read(os.path.join(plotdata.outdir,'surge.data'))
friction_data = surgedata.FrictionData()
friction_data.read(os.path.join(plotdata.outdir,'friction.data'))
# Load storm track
track = surgeplot.track_data(os.path.join(plotdata.outdir,'fort.track'))
# Calculate landfall time, off by a day, maybe leap year issue?
landfall_dt = datetime.datetime(2008,9,13,7) - datetime.datetime(2008,1,1,0)
landfall = (landfall_dt.days - 1.0) * 24.0 * 60**2 + landfall_dt.seconds
# Color limits
surface_range = 5.0
speed_range = 3.0
eta = physics.sea_level
if not isinstance(eta,list):
eta = [eta]
surface_limits = [eta[0]-surface_range,eta[0]+surface_range]
# surface_contours = numpy.linspace(-surface_range, surface_range,11)
surface_contours = [-5,-4.5,-4,-3.5,-3,-2.5,-2,-1.5,-1,-0.5,0.5,1,1.5,2,2.5,3,3.5,4,4.5,5]
speed_limits = [0.0,speed_range]
speed_contours = numpy.linspace(0.0,speed_range,13)
wind_limits = [0,64]
# wind_limits = [-0.002,0.002]
pressure_limits = [935,1013]
friction_bounds = [0.01,0.04]
# vorticity_limits = [-1.e-2,1.e-2]
# ==========================================================================
# ==========================================================================
# Plot specifications
# ==========================================================================
# ==========================================================================
#-----------------------------------------
# Some global kml flags
#-----------------------------------------
plotdata.kml_name = "Ike"
plotdata.kml_starttime = [2008,9,3,15,0,0] # Time of event in UTC [None]
plotdata.kml_tz_offset = 5 # Time zone offset (in hours) of event. [None]
plotdata.kml_index_fname = "Ike" # name for .kmz and .kml files ["_GoogleEarth"]
# Set to path where KMZ files will be stored; KML file will then
# link to this path.
# plotdata.kml_publish = 'http://www.domain.edu/path/to/kmz/files'
# ========================================================================
# Entire Gulf
# ========================================================================
gulf_xlimits = [clawdata.lower[0],clawdata.upper[0]]
gulf_ylimits = [clawdata.lower[1],clawdata.upper[1]]
gulf_shrink = 1.0
# --------------------------
# Surface - entire gulf
# --------------------------
plotfigure = plotdata.new_plotfigure(name='Surface - Entire Domain',
figno=0)
plotfigure.show = True
plotfigure.use_for_kml = True
plotfigure.kml_use_for_initial_view = True
# These override axes limits set below in plotitems
plotfigure.kml_xlimits = gulf_xlimits
plotfigure.kml_ylimits = gulf_ylimits
# Resolution - needs to be set carefully for the transparent colormap
rcl = 40
plotfigure.kml_dpi = rcl*2
plotfigure.kml_figsize = [11.6, 9.6]
plotfigure.kml_tile_images = False # Tile images for faster loading. Requires GDAL [False]
plotaxes = plotfigure.new_plotaxes()
plotitem = plotaxes.new_plotitem(name='surface',plot_type='2d_pcolor')
plotitem.plot_var = geoplot.surface_or_depth
plotitem.pcolor_cmap = geoplot.googleearth_transparent
plotitem.pcolor_cmin = -surface_range
plotitem.pcolor_cmax = surface_range
def kml_colorbar(filename):
cmin = -surface_range
cmax = surface_range
geoplot.kml_build_colorbar(filename,
geoplot.googleearth_transparent,
cmin,cmax)
plotfigure.kml_colorbar = kml_colorbar
# --------------------------
# Water Speed - entire gulf
# --------------------------
plotfigure = plotdata.new_plotfigure(name='Currents - Entire Domain',
figno=1)
plotfigure.show = True
plotfigure.use_for_kml = True
plotfigure.kml_use_for_initial_view = False
# These override axes limits set below in plotitems
plotfigure.kml_xlimits = gulf_xlimits
plotfigure.kml_ylimits = gulf_ylimits
plotfigure.kml_figsize = [11.6,9.6]
plotfigure.kml_dpi = 80 # size not so important with contourf
plotfigure.kml_tile_images = False # Tile images for faster loading. Requires GDAL [False]
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotitem = plotaxes.new_plotitem(name='surface', plot_type='2d_contourf')
plotitem.plot_var = geoplot.surface_or_depth
plotitem.contour_levels = speed_contours
plotitem.fill_cmin = min(speed_contours)
plotitem.fill_cmax = max(speed_contours)
cmap= plt.get_cmap('OrRd')
cmap._rgba_under = (0.0,0.0,0.0,0.0)
plotitem.fill_cmap = cmap
def cbar_speeds(filename):
cmin = min(speed_contours)
cmax = max(speed_contours)
geoplot.kml_build_colorbar(filename,cmap,cmin,cmax)
plotfigure.kml_colorbar = cbar_speeds
# ========================================================================
# Houston/Galveston
# ========================================================================
houston_xlimits = [-(95.0 + 26.0 / 60.0), -(94.0 + 25.0 / 60.0)]
houston_ylimits = [29.1, 29.0 + 55.0 / 60.0]
houston_shrink = 0.9
#No need to worry about fitting the plot exactly if we are not using
# the transparent colormap with pcolor.
#num_cells = [116, 96]
#dx = (gulf_xlimits[1] - float(gulf_xlimits[0]))/num_cells[0] # = 0.25
#dy = (gulf_ylimits[1] - float(gulf_ylimits[0]))/num_cells[1] # = 0.25
#houston_xlimits = [gulf_xlimits[0] + 14*dx, gulf_xlimits[0] + 21*dx] # [-95.25, -94.5]
#houston_ylimits = [gulf_ylimits[0] + 82*dy, gulf_ylimits[0] + 88*dy] # [-95.25, -94.5]
#figsize = [(21-14)*dx,(88-82)*dy] # relative to [11.6, 9.6] occupied by larger grid
figsize = [houston_xlimits[1]-houston_xlimits[0],houston_ylimits[1]-houston_ylimits[0]]
dpi = 400
# --------------------------------------
# Surface Elevations - Houston/Galveston
# --------------------------------------
plotfigure = plotdata.new_plotfigure(name='Surface - Houston/Galveston',
figno=2)
plotfigure.show = True
plotfigure.use_for_kml = True
plotfigure.kml_xlimits = houston_xlimits
plotfigure.kml_ylimits = houston_ylimits
plotfigure.kml_dpi = dpi # data is not more resolve than this
plotfigure.kml_figsize = figsize
plotfigure.kml_tile_images = False
# pcolor for water.
plotaxes = plotfigure.new_plotaxes()
plotitem = plotaxes.new_plotitem(name='surface',plot_type='2d_contourf')
plotitem.contour_levels = surface_contours
plotitem.fill_cmin = min(surface_contours)
plotitem.fill_cmax = max(surface_contours)
# what is the colormap used here?
#plotfigure.kml_colorbar = cbar_houston
# --------------------------------
# Water Speed - Houston/Galveston
# --------------------------------
plotfigure = plotdata.new_plotfigure(name='Currents - Houston/Galveston',
figno=3)
plotfigure.show = True
plotfigure.use_for_kml = True
# These override axes limits set below in plotitems
plotfigure.kml_xlimits = houston_xlimits
plotfigure.kml_ylimits = houston_ylimits
plotfigure.kml_figsize = figsize
plotfigure.kml_dpi = dpi # data is not more resolve than this
plotfigure.kml_tile_images = False # Tile images for faster loading. Requires GDAL [False]
# Water
plotaxes = plotfigure.new_plotaxes()
plotitem = plotaxes.new_plotitem(name='surface', plot_type='2d_contourf')
plotitem.plot_var = geoplot.surface_or_depth
plotitem.contour_levels = speed_contours
plotitem.fill_cmin = min(speed_contours)
plotitem.fill_cmax = max(speed_contours)
cmap= plt.get_cmap('OrRd')
cmap._rgba_under = (0.0,0.0,0.0,0.0)
plotitem.fill_cmap = cmap
# ========================================================================
# Figures for gauges
# ========================================================================
plotfigure = plotdata.new_plotfigure(name='Surface & topo', figno=300, \
type='each_gauge')
plotfigure.show = True
plotfigure.clf_each_gauge = True
# plotfigure.kwargs['figsize'] = (16,10)
def gauge_after_axes(cd):
if cd.gaugeno in [1,2,3,4]:
axes = plt.gca()
# # Add Kennedy gauge data
# kennedy_gauge = kennedy_gauges[gauge_name_trans[cd.gaugeno]]
# axes.plot(kennedy_gauge['t'] - seconds2days(date2seconds(gauge_landfall[0])),
# kennedy_gauge['mean_water'] + kennedy_gauge['depth'], 'k-',
# label='Gauge Data')
# Add GeoClaw gauge data
geoclaw_gauge = cd.gaugesoln
axes.plot(seconds2days(geoclaw_gauge.t - date2seconds(gauge_landfall[1])),
geoclaw_gauge.q[3,:] + gauge_surface_offset[0], 'b--',
label="GeoClaw")
# Add ADCIRC gauge data
# ADCIRC_gauge = ADCIRC_gauges[kennedy_gauge['gauge_no']]
# axes.plot(seconds2days(ADCIRC_gauge[:,0] - gauge_landfall[2]),
# ADCIRC_gauge[:,1] + gauge_surface_offset[1], 'r-.', label="ADCIRC")
# Fix up plot
axes.set_title('Station %s' % cd.gaugeno)
axes.set_xlabel('Days relative to landfall')
axes.set_ylabel('Surface (m)')
axes.set_xlim([-2,1])
axes.set_ylim([-1,5])
axes.set_xticks([-2,-1,0,1])
axes.set_xticklabels([r"$-2$",r"$-1$",r"$0$",r"$1$"])
axes.grid(True)
axes.legend()
plt.hold(False)
surgeplot.gauge_afteraxes(cd)
# Set up for axes in this figure:
plotaxes = plotfigure.new_plotaxes()
plotaxes.xlimits = [-2,1]
#plotaxes.xlabel = "Days from landfall"
#plotaxes.ylabel = "Surface (m)"
plotaxes.ylimits = [-1,5]
plotaxes.title = 'Surface'
plotaxes.afteraxes = gauge_after_axes
# Plot surface as blue curve:
plotitem = plotaxes.new_plotitem(plot_type='1d_plot')
plotitem.plot_var = 3
plotitem.plotstyle = 'b-'
#-----------------------------------------
# Parameters used only when creating html and/or latex hardcopy
# e.g., via pyclaw.plotters.frametools.printframes:
plotdata.printfigs = True # print figures
plotdata.print_format = 'png' # file format
plotdata.print_framenos = 'all' # list of frames to print
plotdata.print_gaugenos = 'all' # list of gauges to print
plotdata.print_fignos = [0,1,2,3] # list of figures to print
plotdata.html_homelink = '../README.html' # pointer for top of index
plotdata.latex_figsperline = 2 # layout of plots
plotdata.latex_framesperline = 1 # layout of plots
plotdata.latex_makepdf = False # also run pdflatex?
plotdata.html = False # create html files of plots?
plotdata.latex = False # create latex file of plots?
plotdata.kml = True
return plotdata