Changeset 4151 for anuga_work

Timestamp:

Jan 9, 2007, 3:26:53 PM (18 years ago)

Author:

sexton

Message:

(1) updates to make_report script to handle multiple events for multiple return periods (2) take Onslow changes through to Port Hedland and Dampier

Location:

anuga_work/production

Files:

• dampier_2006/build_dampier.py (modified) (2 diffs)
• dampier_2006/make_report.py (modified) (7 diffs)
• dampier_2006/run_dampier.py (modified) (2 diffs)
• onslow_2006/make_report.py (modified) (7 diffs)
• onslow_2006/project.py (modified) (1 diff)
• onslow_2006/report/anuga_setup.tex (modified) (3 diffs)
• onslow_2006/report/metadata.tex (modified) (1 diff)
• onslow_2006/report/modelling_methodology.tex (modified) (1 diff)
• pt_hedland_2006/make_report.py (modified) (13 diffs)
• pt_hedland_2006/report/anuga.tex (deleted)
• pt_hedland_2006/report/anuga_setup.tex (added)
• pt_hedland_2006/report/computational_setup.tex (deleted)
• pt_hedland_2006/report/damage_inputs.tex (modified) (3 diffs)
• pt_hedland_2006/report/execsum.tex (modified) (2 diffs)
• pt_hedland_2006/report/interpretation.tex (modified) (2 diffs)
• pt_hedland_2006/report/introduction.tex (modified) (2 diffs)
• pt_hedland_2006/report/metadata.tex (modified) (1 diff)
• pt_hedland_2006/report/references.tex (modified) (2 diffs)
• pt_hedland_2006/report/timeseriesdiscussion.tex (added)
• pt_hedland_2006/report/tsunami_scenario.tex (modified) (1 diff)

anuga_work/production/dampier_2006/build_dampier.py

@@ -121 +121 @@
 
 print'clip combined geospatial object by bounding polygon'
-G_clipped = G.clip(project.bounding_polygon)
+G_clipped = G.clip(project.poly_all)
 #FIXME: add a clip function to pts
 #print'shape of clipped data', G_clipped.get_data_points().shape
@@ -128 +128 @@
 if access(project.topographies_dir,F_OK) == 0:
     mkdir (project.topographies_dir)
-G_clipped.export_points_file(project.combined_dir_name + '.pts')
-#G_clipped.export_points_file(project.combined_dir_name + '.xya')
-
-'''
-#-------------------------------------------------------------------------
-# Convert URS to SWW file for boundary conditions 
-#-------------------------------------------------------------------------
-print 'starting to create boundary conditions'
-boundaries_in_dir_name = project.boundaries_in_dir_name
-
-from anuga.shallow_water.data_manager import urs2sww
-
-print 'minlat=project.north_boundary, maxlat=project.south_boundary',project.north_boundary, project.south_boundary
-print 'minlon= project.west_boundary, maxlon=project.east_boundary',project.west_boundary, project.east_boundary
-
-#import sys; sys.exit()
-
-#if access(project.boundaries_dir,F_OK) == 0:
-#    mkdir (project.boundaries_dir)
-
-from caching import cache
-cache(urs2sww,
-      (boundaries_in_dir_name,
-       project.boundaries_dir_name1), 
-      {'verbose': True,
-       'minlat': project.south_boundary,
-       'maxlat': project.north_boundary,
-       'minlon': project.west_boundary,
-       'maxlon': project.east_boundary,
-#       'minlat': project.south,
-#       'maxlat': project.north,
-#       'minlon': project.west,
-#       'maxlon': project.east,
-       'mint': 0, 'maxt': 40000,
-#       'origin': domain.geo_reference.get_origin(),
-       'mean_stage': project.tide,
-#       'zscale': 1,                 #Enhance tsunami
-       'fail_on_NaN': False},
-       verbose = True,
-       )
-#       dependencies = source_dir + project.boundary_basename + '.sww')
+#G_clipped.export_points_file(project.combined_dir_name + '.pts')
+G_clipped.export_points_file(project.combined_dir_name + '.xya')

anuga_work/production/dampier_2006/make_report.py

@@ -73 +73 @@
 report_title = 'Tsunami impact modelling for %s' %scenario_name.title()
 
-# WA DLI data
-production_dirs = {#'20061101_053132_run': 'big event'} # parallel
-                    #'20061101_054432_run': 'big event'} # sequential
-                    #'20061107_070805_run': 'Mw 9.0',
-                    '20061116_055135_run': 'Mw 9.0'} # multiple interior regions
-                    #'20061116_062924_run': 'Mw 9.0'} # one interior region
-
 is_parallel = True
 if is_parallel == True:
     nodes = 8
-
-max_maps = {'Mw 9.0': 'mw9_map'}
-
+    
+return_periods = [1000, 100000]
+
+# output directories
+production_dirs_1000 = {'20061116_055135_run': 'Mw 9.0'} # RP 1000 years
+production_dirs_100000 = {'20061116_055135': 'Mw 8.0'} # RP 100000 years
+
+all_prod_dirs = [production_dirs_1000, production_dirs_100000]
+                          
+max_maps_1000 = {'Mw 6.0': 'mw6_map'}
+max_maps_100000 = {'Mw 9.0': 'mw9_map'}
+
+all_maps = [max_maps_1000, max_maps_100000]
+
+# gauge map names
 gauge_map1 = 'dampier_gauges_1.jpg'
 gauge_map2 = 'dampier_gauges_2.jpg'
@@ -91 +96 @@
 # Create sections and graphs for each designated production directory
 latex_output = []
-report_name = 'latexoutput_cipma'
+report_name = 'latexoutput'
 
 if is_parallel == True:
-
-    for i in range(nodes):
-        print 'Sending node %d of %d' %(i,nodes)
+    
+    for j, production_dirs in enumerate(all_prod_dirs):
+        
+        for i in range(nodes):
+            print 'Sending node %d of %d' %(i,nodes)
+            reportname = report_name + '%s' + 'rp%s' %(i,j)
+            swwfiles = {}
+            
+            for label_id in production_dirs.keys():
+                file_loc = project.output_dir + label_id + sep
+                sww_extra = '_P%s_%s' %(i,nodes)
+                swwfile = file_loc + project.scenario_name + sww_extra + '.sww'
+                swwfiles[swwfile] = label_id
+
+                texname, elev_output = sww2timeseries(swwfiles,
+                                                      project.gauge_filename,
+                                                      production_dirs,
+                                                      report = True,
+                                                      reportname = reportname,
+                                                      plot_quantity = ['stage', 'momentum'],
+                                                      surface = False,
+                                                      time_min = None,
+                                                      time_max = None,
+                                                      title_on = False,
+                                                      verbose = True)
+                
+                latex_output.append(texname)
+    
+else:
+
+    for i, production_dirs in enumerate(all_prod_dirs):
+
         swwfiles = {}
-        reportname = report_name + '_%s' %(i)
+        reportname = report_name + 'rp%s' %(i)
+        
         for label_id in production_dirs.keys():
+
             file_loc = project.output_dir + label_id + sep
-            sww_extra = '_P%s_%s' %(i,nodes)
-            swwfile = file_loc + project.scenario_name + sww_extra + '.sww'
+            swwfile = file_loc + project.scenario_name + '.sww'
             swwfiles[swwfile] = label_id
-
-            texname, elev_output = sww2timeseries(swwfiles,
-                                                  project.gauge_filename,
-                                                  production_dirs,
-                                                  report = True,
-                                                  reportname = reportname,
-                                                  plot_quantity = ['stage', 'momentum'],
-                                                  surface = False,
-                                                  time_min = None,
-                                                  time_max = None,
-                                                  title_on = False,
-                                                  verbose = True)
             
-            latex_output.append(texname)
-    
-else:
-    
-    for label_id in production_dirs.keys():
-
-        file_loc = project.output_dir + label_id + sep
-        swwfile = file_loc + project.scenario_name + '.sww'
-        swwfiles[swwfile] = label_id
-        
-    texname, elev_output = sww2timeseries(swwfiles,
-                                          project.gauge_filename,
-                                          production_dirs,
-                                          report = True,
-                                          reportname = report_name,
-                                          plot_quantity = ['stage', 'momentum'],
-                                          surface = False,
-                                          time_min = None,
-                                          time_max = None,
-                                          title_on = False,
-                                          verbose = True)
+        texname, elev_output = sww2timeseries(swwfiles,
+                                              project.gauge_filename,
+                                              production_dirs,
+                                              report = True,
+                                              reportname = reportname,
+                                              plot_quantity = ['stage', 'momentum'],
+                                              surface = False,
+                                              time_min = None,
+                                              time_max = None,
+                                              title_on = False,
+                                              verbose = True)
+        latex_output.append(texname)
 
 # Start report generation
 # Future: generate_report(reportdir, scenario, report_title, 
 # project.gauge_filename, max_maps, damage_maps, production_dirs, latex_output)
-report_name = reportdir + scenario + '_report_CIPMA.tex'
+report_name = reportdir + scenario + '_report.tex'
 fid = open(report_name, 'w')
 
@@ -200 +214 @@
 s = '%s} '%report_title
 fid.write(s)
+
 s = """
   \maketitle
@@ -207 +222 @@
   \input{execsum}
 
+\clearpage
+
   \\tableofcontents
   
+  \section{Introduction}
+    \label{sec:intro}
+  \input{introduction}
+
    \section{Modelling methodology}
     \label{sec:methodology}
     \input{modelling_methodology}
+    
+  \section{Tsunami scenarios}
+    \label{sec:tsunamiscenario}
+    \input{tsunami_scenario}
 
   \section{Data sources}
     \label{sec:data}
     \input{data}
-    
-   %\section{Inundation model}
-   % \label{sec:anuga}
-   % \input{anuga}
-   % \input{computational_setup}
         
   \section{Inundation modelling results}
@@ -227 +247 @@
 """
 fid.write(s)
-
-# Generate latex output for location points
-##s = '\\begin{table} \\begin{center} \n'
-##fid.write(s)
-##s = '\caption{Defined point locations for %s study area.}' %scenario_name
-##fid.write(s)
-##s = """
-##\label{table:locations}
-##\\begin{tabular}{|l|l|l|l|}\hline
-##\\bf{Point Name} & \\bf{Easting} & \\bf{Northing} & \\bf{Elevation (m)}\\\\ \hline
-##"""
-##fid.write(s)
-##
-##gauges, locations, elevation = get_gauges_from_file(project.gauge_filename)
-##
-##for name, gauges, elev in zip(locations, gauges, elevation):
-##    east = gauges[0]
-##    north = gauges[1]
-##    s = '%s & %.2f & %.2f & %.2f \\\\ \hline \n' %(name.replace('_',' '), east, north, elev)
-##    fid.write(s)
-##
-##s = '\\end{tabular} \n  \end{center} \n \end{table} \n \n'
-##fid.write(s)
-##
-
-s = '\\begin{figure}[hbt] \centerline{\includegraphics[scale = 0.5]{../report_figures/%s}}' %gauge_map2
-fid.write(s)
-s  = """
-\caption{Point locations used for Dampier study; surrounding the facility.
-See Appendix \\ref{sec:timeseries} for stage and momentum results.
-}  
-\label{fig:points2}
-\end{figure}
-"""
-fid.write(s)
-s = '\\begin{figure}[hbt] \centerline{\includegraphics[scale=0.5]{../report_figures/%s}}' %gauge_map3
-fid.write(s)
-s  = """
-\caption{Point locations used for Dampier study; section
-of the pipeline towards the boundary of the region and other boundary gauges.
-See Appendix \\ref{sec:timeseries} for stage and momentum results.}  
-\label{fig:points3}
-\end{figure}
-"""
-fid.write(s)
-    
-#s = '\input{interpretation} \n'
-#fid.write(s)
+    
+s = '\input{interpretation} \n'
+fid.write(s)
 
 # Assign titles to each production section 
 # Must specify one name per section
-for i, name in enumerate(production_dirs.keys()):
-
-    s = '\input{%s} \n \clearpage \n \n' %max_maps[production_dirs[name]]
+for i, max_maps in enumerate(all_maps):
+
+    s = '\subsection{Return Period: %s years} \n \n' %return_periods[i]      
     fid.write(s)
 
+    production_dirs = all_prod_dirs[i]
+    for name in enumerate(production_dirs.keys()):
+        s = '\input{%s} \n \clearpage \n \n' %max_maps[production_dirs[name]]
+        fid.write(s)
+
+# Generate latex output for location points
+s = '\\begin{table} \\begin{center} \n'
+fid.write(s)
+s = '\caption{Defined point locations for %s study area.}' %scenario_name.title()
+fid.write(s)
+s = """
+\label{table:locations}
+\\begin{tabular}{|l|l|l|l|}\hline
+\\bf{Point Name} & \\bf{Easting} & \\bf{Northing} & \\bf{Elevation (m)}\\\\ \hline
+"""
+fid.write(s)
+
+gauges, locations, elevation = get_gauges_from_file(project.gauge_filename)
+
+for name, gauges, elev in zip(locations, gauges, elevation):
+    east = gauges[0]
+    north = gauges[1]
+    s = '%s & %.2f & %.2f & %.2f \\\\ \hline \n' %(name.replace('_',' '), east, north, elev)
+    fid.write(s)
+
+s = '\\end{tabular} \n  \end{center} \n \end{table} \n \n'
+fid.write(s)
+
+#s = '\\begin{figure}[h] \n \centerline{ \includegraphics[width=\paperwidth]{../report_figures/%s}}' %gauge_map
+s = '\\begin{figure}[h] \n \centerline{ \includegraphics[scale=0.7]{../report_figures/%s}}' %gauge_map
+fid.write(s)
+
+s  = """
+\caption{Point locations used for Dampier study.}  
+\label{fig:points}
+\end{figure}
+
+\clearpage
+"""
+fid.write(s)
+
 # Closing
 
-
-s = """
-
+s = """
+   \section{Impact modelling}
+    \label{sec:impact}
+     \input{damage}
+"""
+fid.write(s)
+
+s = """
      \section{Summary}
      \label{sec:summary}
      \input{summary}
 
-     %\section{Acknowledgements}
-     %\input{acknowledgements}
+     \section{Acknowledgements}
+     \input{acknowledgements}
      
     \input{references}
 
+\clearpage
+
     \\appendix
 
-   \section{ANUGA modelling parameters}
-\label{sec:anugasetup}
-\input{anuga_setup}
+    \section{ANUGA modelling parameters}
+    \label{sec:anugasetup}
+    \input{anuga_setup}
+
+\clearpage
 
    \section{Metadata}
      \label{sec:metadata}
      \input{metadata}
-     
-\section{ANUGA modelling parameters}
-\label{sec:anugasetup}
-\input{anuga_setup}
 
 \clearpage
@@ -315 +336 @@
    \section{Time series}
      \label{sec:timeseries}
+     \input{timeseriesdiscussion}
+     \clearpage
 """
 fid.write(s)
@@ -320 +343 @@
 for i in range(len(latex_output)):
     if latex_output[i] <> '':
+        s = '\subsection{Return Period: %s years} \n' %return_periods[i]
+        fid.write(s)
         s = '\input{%s} \n \clearpage \n \n' %latex_output[i]   
         fid.write(s)
 
 s="""
+     \section{Damage modelling inputs}
+     \label{sec:damageinputs}
+     \input{damage_inputs}
+     
 \end{document}
 """

anuga_work/production/dampier_2006/run_dampier.py

@@ -45 +45 @@
 
 # filenames
-build_time = '20061107_063840_build'
-bound_time = '20061102_221245_build'
-
 boundaries_name = project.boundaries_name
 meshes_dir_name = project.meshes_dir_name+'.msh'
@@ -135 +132 @@
     domain.set_quantity('stage', tide)
     domain.set_quantity('friction', 0.01) 
-    #combined_time_dir_name = project.topographies_dir+build_time+project.combined_name
     print 'Start Set quantity'
 

anuga_work/production/onslow_2006/make_report.py

@@ -25 +25 @@
 * Tsunami scenario
 * Data sources
-
 * Inundation modelling results
 * Impact modelling
@@ -81 +80 @@
 
 # WA DLI data
-production_dirs = {'20060704_063234': 'MSL',
-                   '20060704_063005': 'HAT',
-                   '20060706_235246': 'LAT'}
-
-max_maps = {'MSL': 'MSL_map',
+production_dirs_test1 = {'20060704_063234': 'MSL',
+                         '20060704_063005': 'HAT',
+                         '20060706_235246': 'LAT'}
+
+production_dirs_test2 = production_dirs_test1
+
+return_periods = [1000, 1000000]
+
+all_prod_dirs = [production_dirs_test1, production_dirs_test2]
+#all_prod_dirs = [production_dirs_test1]
+
+is_parallel = False
+if is_parallel == True:
+    nodes = 8
+    
+max_maps1 = {'MSL': 'MSL_map',
             'HAT': 'HAT_map',
             'LAT': 'LAT_map'}
 
+max_maps2 = max_maps1
+
+all_maps = [max_maps1, max_maps2]
+
 gauge_map = 'onslow_dli_gauge.jpg'
 
@@ -95 +109 @@
 # Create sections and graphs for each designated production directory
 latex_output = []
+report_name = 'latexoutput'
 swwfiles = {}
-for label_id in production_dirs.keys():
-    
-    file_loc = project.outputdir + label_id + sep
-    swwfile = file_loc + project.basename + '.sww'
-    swwfiles[swwfile] = label_id
-
-texname, elev_output = sww2timeseries(swwfiles,
-                                      project.gauge_filename,
-                                      #project.gauge_filename_bindi,
-                                      production_dirs,
-                                      report = True,
-                                      reportname = 'latexoutput',
-                                      plot_quantity = ['stage', 'speed'],
-                                      surface = False,
-                                      time_min = None,
-                                      time_max = None,
-                                      title_on = False,
-                                      verbose = True)
-
-latex_output.append(texname)
-
+if is_parallel == True:
+
+    for j, production_dirs in enumerate(all_prod_dirs):
+        
+        for i in range(nodes):
+            print 'Sending node %d of %d' %(i,nodes)
+            swwfiles = {}
+            reportname = report_name + '%s' + 'rp%s' %(i,j)
+            
+            for label_id in production_dirs.keys():
+                file_loc = project.output_dir + label_id + sep
+                sww_extra = '_P%s_%s' %(i,nodes)
+                swwfile = file_loc + project.basename + sww_extra + '.sww'
+                #swwfile = file_loc + project.scenario_name + sww_extra + '.sww'
+                swwfiles[swwfile] = label_id
+
+                texname, elev_output = sww2timeseries(swwfiles,
+                                                      project.gauge_filename,
+                                                      production_dirs,
+                                                      report = True,
+                                                      reportname = reportname,
+                                                      plot_quantity = ['stage', 'momentum'],
+                                                      surface = False,
+                                                      time_min = None,
+                                                      time_max = None,
+                                                      title_on = False,
+                                                      verbose = True)
+                
+                latex_output.append(texname)
+    
+else:
+
+    for i, production_dirs in enumerate(all_prod_dirs):
+
+        swwfiles = {}
+        reportname = report_name + 'rp%s' %(i)
+        
+        for label_id in production_dirs.keys():
+
+            file_loc = project.outputdir + label_id + sep
+            swwfile = file_loc + project.basename + '.sww'
+            #swwfile = file_loc + project.scenario_name + sww_extra + '.sww'
+            swwfiles[swwfile] = label_id
+            
+        texname, elev_output = sww2timeseries(swwfiles,
+                                              project.gauge_filename,
+                                              production_dirs,
+                                              report = True,
+                                              reportname = reportname,
+                                              plot_quantity = ['stage', 'speed'],
+                                              surface = False,
+                                              time_min = None,
+                                              time_max = None,
+                                              title_on = False,
+                                              verbose = True)
+        
+        latex_output.append(texname)
+    
 # Start report generation
 # Future: generate_report(reportdir, scenario, report_title, 
@@ -152 +204 @@
 \usepackage{setspace}
 \usepackage{rotating}
+\usepackage{pdfpages}
 \include{appendix}
 \setstretch{1.25}
@@ -164 +217 @@
 fid.write(s)
 
-#s = '\\title{%s} \n' %report_title
-#fid.write(s)
-
 s = """
 \date{\\today}
@@ -218 +268 @@
 # Assign titles to each production section 
 # Must specify one name per section
-for i, name in enumerate(production_dirs.keys()):
-#
-#    s = '\subsection{%s} \n \n' %production_dirs[name]      
-#    fid.write(s)
-
-    s = '\input{%s} \n \clearpage \n \n' %max_maps[production_dirs[name]]
+for i, max_maps in enumerate(all_maps):
+
+    s = '\subsection{Return Period: %s years} \n \n' %return_periods[i]      
     fid.write(s)
+
+    production_dirs = all_prod_dirs[i]
+    for i, name in enumerate(production_dirs.keys()):
+
+        s = '\input{%s} \n \clearpage \n \n' %max_maps[production_dirs[name]]
+        fid.write(s)
 
 # Generate latex output for location points
@@ -308 +361 @@
 fid.write(s)
 
-s = '\input{%s} \n \clearpage \n \n' %latex_output[0]
-fid.write(s)
+for i in range(len(latex_output)):
+    if latex_output[i] <> '':
+        s = '\subsection{Return Period: %s years} \n' %return_periods[i]
+        fid.write(s)
+        s = '\input{%s} \n \clearpage \n \n' %latex_output[i]   
+        fid.write(s)
 
 s="""

anuga_work/production/onslow_2006/project.py

@@ -17 +17 @@
 state = 'western_australia'
 scenario_dir_name = 'onslow_tsunami_scenario_2006'
+scenario_name = 'onslow'
 
 # 250m data to be provided

anuga_work/production/onslow_2006/report/anuga_setup.tex

@@ -12 +12 @@
  
 The initial conditions used for this scenario are MSL, HAT and LAT which were
-defined in Section \ref{sec:data}.
+defined in Section \ref{sec:data}. Figure \ref{fig:IC} shows the MSL, HAT and 
+LAT contours to illustrate the water level for each of these inial conditions.
 The dynamics of
 tidal effects (that is, the changes in water height over time for
@@ -23 +24 @@
 in the scenario. The 
 results are therefore likely to be over estimates.
+
+\begin{figure}[h]
+
+  \centerline{\includegraphics[width=\paperwidth]{../report_figures/onslow_dli_contour.jpg}}
+
+  \caption{Onslow region showing the initial conditions used for the study; 
+  -1.5m AHD (LAT), 0m AHD (MSL) and 1.5m AHD (HAT) contour lines.}
+  \label{fig:IC}
+\end{figure}
+
 
 To set up a model for the tsunami scenario, a study area is first 
@@ -69 +80 @@
 The final item to be addressed to complete the model setup is the 
 definition of the boundary condition. As 
-discussed in Section \ref{sec:methodology}, a range of events with
-different return periods will modelled. It must be 
-remembered that tsunamis are typically made up of a series
+discussed in Section \ref{sec:methodology}, a series of events corresponding
+to a range of return periods are selected as the tsunami sources.
+The resultant tsunami wave is made up of a series
 of waves with different amplitudes which is affected by the energy
 and style of the event as well as the bathymetry whilst it travels
-from its source to Onslow. The amplitude and velocity of each of these
+from its source to Dampier. The amplitude and velocity of each of these
 waves are then provided to ANUGA as boundary conditions and propagated
 inshore.

anuga_work/production/onslow_2006/report/metadata.tex

@@ -1 @@
-
-See Enclosure.
+%\includepdf[pages={1-6}]{MetadataforATWSOnslowScenario}

anuga_work/production/onslow_2006/report/modelling_methodology.tex

@@ -1 @@
-
 Geoscience Australia aims to define the economic and social threat posed to urban communities 
 by a range of rapid onset natural hazards. Through the integration of natural hazard research, defining national exposure and 

anuga_work/production/pt_hedland_2006/make_report.py

@@ -52 +52 @@
 from os import getcwd, sep, altsep, mkdir, access, F_OK
 import project
-from anuga.pyvolution.util import sww2timeseries, get_gauges_from_file
+from anuga.abstract_2d_finite_volumes.util import sww2timeseries, get_gauges_from_file
 
 # Derive scenario name
@@ -70 +70 @@
 report_title = 'Tsunami impact modelling for the North West shelf: %s' %scenario_name.title()
 
+is_parallel = False
+if is_parallel == True:
+    nodes = 8
+    
 # WA DLI data
 production_dirs = {'20060707_001859': 'MSL',
@@ -75 +79 @@
                    '20060707_003424': 'LAT'}
 
+all_prod_dirs = [production_dirs]
+
 max_maps = {'MSL': 'MSL_map',
             'HAT': 'HAT_map',
@@ -83 +89 @@
 # Create sections and graphs for each designated production directory
 latex_output = []
+report_name = 'latexoutput'
 swwfiles = {}
-for label_id in production_dirs.keys():
-    
-    file_loc = project.outputdir + label_id + sep
-    swwfile = file_loc + project.basename + '.sww'
-    swwfiles[swwfile] = label_id
-
-texname, elev_output = sww2timeseries(swwfiles,
-                                      project.gauge_filename,
-                                      production_dirs,
-                                      report = True,
-                                      reportname = 'latexoutput',
-                                      plot_quantity = ['stage', 'speed'],
-                                      surface = False,
-                                      time_min = None,
-                                      time_max = None,
-                                      title_on = False,
-                                      verbose = True)
-
-latex_output.append(texname)
-
+if is_parallel == True:
+
+    for j, production_dirs in enumerate(all_prod_dirs):
+        
+        for i in range(nodes):
+            print 'Sending node %d of %d' %(i,nodes)
+            swwfiles = {}
+            reportname = report_name + '%s' + 'rp%s' %(i,j)
+            
+            for label_id in production_dirs.keys():
+                file_loc = project.output_dir + label_id + sep
+                sww_extra = '_P%s_%s' %(i,nodes)
+                swwfile = file_loc + project.basename + sww_extra + '.sww'
+                #swwfile = file_loc + project.scenario_name + sww_extra + '.sww'
+                swwfiles[swwfile] = label_id
+
+                texname, elev_output = sww2timeseries(swwfiles,
+                                                      project.gauge_filename,
+                                                      production_dirs,
+                                                      report = True,
+                                                      reportname = reportname,
+                                                      plot_quantity = ['stage', 'momentum'],
+                                                      surface = False,
+                                                      time_min = None,
+                                                      time_max = None,
+                                                      title_on = False,
+                                                      verbose = True)
+                
+                latex_output.append(texname)
+    
+else:
+
+    for i, production_dirs in enumerate(all_prod_dirs):
+
+        swwfiles = {}
+        reportname = report_name + 'rp%s' %(i)
+        
+        for label_id in production_dirs.keys():
+
+            file_loc = project.outputdir + label_id + sep
+            swwfile = file_loc + project.basename + '.sww'
+            #swwfile = file_loc + project.scenario_name + sww_extra + '.sww'
+            swwfiles[swwfile] = label_id
+            
+        texname, elev_output = sww2timeseries(swwfiles,
+                                              project.gauge_filename,
+                                              production_dirs,
+                                              report = True,
+                                              reportname = reportname,
+                                              plot_quantity = ['stage', 'speed'],
+                                              surface = False,
+                                              time_min = None,
+                                              time_max = None,
+                                              title_on = False,
+                                              verbose = True)
+        
+        latex_output.append(texname)
+    
 # Start report generation
 # Future: generate_report(reportdir, scenario, report_title, 
@@ -139 +184 @@
 \usepackage{setspace}
 \usepackage{rotating}
+\usepackage{pdfpages}
 \include{appendix}
 \setstretch{1.25}
@@ -151 +197 @@
 fid.write(s)
 
-#s = '\\title{%s} \n' %report_title
-#fid.write(s)
-
 s = """
 \date{\\today}
@@ -174 +217 @@
   \input{execsum}
 
+\clearpage
+
   \\tableofcontents
   
@@ -191 +236 @@
     \label{sec:data}
     \input{data}
-    
-   \section{Inundation model}
-    \label{sec:anuga}
-    \input{anuga}
-    \input{computational_setup}
         
   \section{Inundation modelling results}
@@ -202 +242 @@
 """
 fid.write(s)
+    
+s = '\input{interpretation} \n'
+fid.write(s)
+
+# Assign titles to each production section 
+# Must specify one name per section
+for i, max_maps in enumerate(all_maps):
+
+    s = '\subsection{Return Period: %s years} \n \n' %return_periods[i]      
+    fid.write(s)
+
+    production_dirs = all_prod_dirs[i]
+    for i, name in enumerate(production_dirs.keys()):
+
+        s = '\input{%s} \n \clearpage \n \n' %max_maps[production_dirs[name]]
+        fid.write(s)
 
 # Generate latex output for location points
 s = '\\begin{table} \\begin{center} \n'
 fid.write(s)
-s = '\caption{Defined point locations for %s study area.}' %scenario_name
+s = '\caption{Defined point locations for %s study area.}' %scenario_name.title()
 fid.write(s)
 s = """
@@ -226 +282 @@
 fid.write(s)
 
-s = '\\begin{sidewaysfigure} \n \centerline{ \includegraphics[width=\paperwidth]{../report_figures/%s}}' %gauge_map
+#s = '\\begin{figure}[h] \n \centerline{ \includegraphics[width=\paperwidth]{../report_figures/%s}}' %gauge_map
+s = '\\begin{figure}[h] \n \centerline{ \includegraphics[scale=0.7]{../report_figures/%s}}' %gauge_map
 fid.write(s)
 
@@ -232 +289 @@
 \caption{Point locations used for Port Hedland study.}  
 \label{fig:points}
-\end{sidewaysfigure}
-"""
-fid.write(s)
-    
-s = '\input{interpretation} \n'
-fid.write(s)
-
-# Assign titles to each production section 
-# Must specify one name per section
-for i, name in enumerate(production_dirs.keys()):
-#
-#    s = '\subsection{%s} \n \n' %production_dirs[name]      
-#    fid.write(s)
-
-    s = '\input{%s} \n \clearpage \n \n' %max_maps[production_dirs[name]]
-    fid.write(s)
+\end{figure}
+
+\clearpage
+"""
+fid.write(s)
 
 # Closing
@@ -258 +304 @@
 fid.write(s)
 
-#for i, name in enumerate(production_dirs.keys()):
-
-#    s = '\input{%s} \n \clearpage \n \n' %damage_maps[production_dirs[name]]
-#    fid.write(s)
-
-s = """
+s = """
+  % \section{Impact due to data accuracy}
+  %   \input{discussion}
+  %   \label{sec:issues}
+
      \section{Summary}
      \label{sec:summary}
      \input{summary}
+
+     \section{Acknowledgements}
+     \input{acknowledgements}
      
     \input{references}
+
+\clearpage
 
     \\appendix
@@ -286 +336 @@
    \section{Time series}
      \label{sec:timeseries}
-"""
-fid.write(s)
-
-s = '\input{%s} \n \clearpage \n \n' %latex_output[0]
-fid.write(s)
+     \input{timeseriesdiscussion}
+     \clearpage
+"""
+fid.write(s)
+
+for i in range(len(latex_output)):
+    if latex_output[i] <> '':
+        s = '\subsection{Return Period: %s years} \n' %return_periods[i]
+        fid.write(s)
+        s = '\input{%s} \n \clearpage \n \n' %latex_output[i]   
+        fid.write(s)
 
 s="""
-
-\pagebreak
 
    \section{Damage modelling inputs}

anuga_work/production/pt_hedland_2006/report/damage_inputs.tex

@@ -1 @@
-\begin{table}[p]
+\begin{table}[h]
 \begin{center}
 \caption{Framed residential building collapse probability. $h$ is the
@@ -16 +16 @@
 \end{table}
 
-\begin{table}
+\begin{table}[h]
 \begin{center}
 \caption{Mortality and injury state probability}
@@ -34 +34 @@
 \end{table}
 
-\begin{table}
+\begin{table}[h]
 \begin{center}
 \caption{Injury level classificationse. Floor height is assumed to be 30cm}

anuga_work/production/pt_hedland_2006/report/execsum.tex

@@ -1 +1 @@
 This report is being provided to the Fire and Emergency Services Authority
 (FESA) as part of the Collaborative Research Agreement (CRA) 
-with Geoscience Australia (GA).
-FESA recognises the potential vulnerability of the Western Australia
-coastline to tsunamigenic earthquakes originating from 
-the Sunda Arc subduction zone that caused the December 2004 event. 
-There is historic evidence of tsunami events affecting the 
+with Geoscience Australia (GA), Tsunami Impact Modelling for WA.
+FESA has recognised the potential vulnerability of the Western Australia
+coastline to tsunami originating from earthquakes on
+the Sunda Arc subduction zone. 
+There is historic evidence of tsunami affecting the 
 Western Australia coastline, \cite{CB:ausgeo}, 
 and FESA has sought to assess
@@ -11 +11 @@
 threat and develop detailed response plans for a range of plausible events.
 
-This report describes the modelling methodology and initial results
-for a specific tsunami-genic event as it impacts the Port Hedland township
-and its surrounds. In particular, maximum inundation maps are shown
-and discussed for the event occurring at mean sea level as well as highest and lowest astronomical tide. 
-The inundation results allow estimation of the number of houses inundated and collapsed, as well as
+This report describes the modelling methodology and results
+for a number of tsunami-genic events with varied return periods
+as they impact the Port Hedland region.
+In particular, maximum inundation maps are shown
+and discussed 
+for the event occurring at mean sea level as well as 
+highest and lowest astronomical tide. The inundation results allow
+estimation of the number of houses inundated and collapsed, as well as
 the numbers of persons affected. 
-For this specific event at high tide, one house is inundated and there are no injuries. 
 
-Future studies
-will present a series of scenarios for a range of return periods to 
-assist FESA in developing appropriate plans for a range of event impacts.
-This will also allow an assessment of the relative tsunami risk 
+The results of this study will allow an assessment of the relative tsunami risk 
 to communities along the NW Shelf of WA. 
 This report and the decision support tool are the 
-June 2006 deliverables of the Collaborative Research Agreement,
-Tsunami Impact Modelling for WA, between FESA and GA.
+June 2007 deliverables of the Collaborative Research Agreement
+between FESA and GA.
 
 
+

anuga_work/production/pt_hedland_2006/report/interpretation.tex

@@ -1 @@
-The main features of the
-tsunami wave and resultant inundation ashore is described in this section. 
-We have
-chosen a number of locations to illustrate the features
-of the tsunami as it approaches and impacts Port Hedland.
-These locations have been chosen as we believe they would 
-either be critical
-in an emergency situation, (e.g. the hospital) or
-effect recovery efforts, (e.g. the airport and wharfs). These locations
-are described in Table \ref{table:locations} and shown in 
-Figure \ref{fig:points}. The water's stage and speed 
-at each of these locations are shown
-as a function of time in the series of graphs shown in
-Appendix \ref{sec:timeseries}. It is assumed that the earthquake is
-generated at the beginning of the simulation, i.e. time = 0 minutes.
-Stage is defined as the absolute
-water level (in metres) relative to AHD 
-\footnote{For an offshore location such as Middle Channel,
-the initial water level will be that of the tidal scenario. In the 
-case of MSL, this water level will be 0. As the tsunami wave moves
-through this point, the water height may grow and thus the stage will 
-represent the amplitude of the wave. For an onshore location such as the 
-Hospital, the actual water depth will be the difference between
-the stage and the elevation at that point. Therefore, at the beginning
-of the simulation, there will be no water onshore and therefore
-the stage and the elevation will be identical.}. Both stage and speed 
-(in metres/second) for
-each scenario (HAT, MSL and LAT) are shown
-on consistent scales to allow comparison between point locations.
-As a useful benchmark, Table \ref{table:speedexamples}
-describes typical examples for a range of speeds found in the 
-simulations. 
-
-\begin{table}[h]
-\label{table:speedexamples}
-\caption{Examples of a range of velocities.}
-\begin{center}
-\begin{tabular}{|l|l|}\hline
-{\bf Velocity (m/s)} & {\bf Example} \\ \hline
-1 & leisurely stroll pace\\ \hline
-1.5 & average walking pace \\ \hline
-%2 & 100m Olympic male freestyle \\ \hline
-%3 & mackeral \\ \hline
-4 & average person can maintain running for 1000m \\ \hline
-%5 & blue whale \\ \hline
-10 & 100m Olympic male sprinter \\ \hline
-16 & car travelling in urban zones (60 km/hr) \\ \hline
-\end{tabular}
-\end{center}
-\end{table}
-
-A tsunami wave typically has a small amplitude and typically travels at 
-100's of kilometres per hour. 
-The low amplitude complicates the ability to detect
-the wave. As the water depth decreases, 
-the speed of the wave 
-decreases and the amplitude grows. Another important feature of tsunamis 
-is drawdown. This means that the water is seen to retreat from the beaches
-before a tsunami wave 
-impacts that location. Other features 
-include reflections (where the wave is redirected due to the 
-influence 
-of the coast) and shoaling (where the wave's amplitude is amplified
-close to the coast due to wave interactions).
-These features are seen in the MSL scenario; 
-there is a small wave, followed
-by a large drawdown and then a large secondary wave.
-There are variations in the behaviour for the
-HAT and LAT scenarios, and these will be explained below.
- 
-The features described above will be 
-illustrated for the MSL case by the Middel Channel location,
-Figure \ref{fig:gaugeMiddleChannel}.
-The first, small wave can be seen at around 230 mins (shown in red),
-with an amplitude of around 0.3 m\footnote{In this
-scenario, the initial water level is 0 m, which means that
-the actual amplitude is the difference between the stage value
-and the initial water level; 0.3 - 0}.
-The drawdown of around 2.6 m (i.e. 0.27 - -2.37) then occurs at around 270 mins
-(i.e. 4.5 hours after the event has been generated), before
-the second wave arrives at around 280 mins
-with an amplitude of around 1.8 m (i.e. 1.8 - 0). Subsequent waves
-are evident with decreased amplitudes.
-These features are replicated at each of the offshore points (those
-points with negative elevation as shown in Table \ref{table:locations}).
-The speed of the tsunami wave is greatest for those locations
-in shallowest water. Middle Channel is in shallower water
-than Mt Goldworthy Wharf - Berth
-and the maximum speeds measured are 1.93 m/s and 2.9 m/s respectively.
-
-There are variations in these behaviours for the HAT and LAT scenarios.
-Referring again to the Middle Channel location (Figure 
-\ref{fig:gaugeMiddleChannel}),
-
-{\bf stuff to write in here about the HAT, LAT scenarios }
+The inundation extent calculated at Port Hedland will be described in this section with
+impact assessments following in Section \ref{sec:impact}.
+% there will need to be something in here for when doing a range of events for each return period.
+Figures \ref{fig:HAT_max_inundation}, \ref{fig:MSL_max_inundation} and 
+\ref{fig:LAT_max_inundation} illustrate the maximum inundation extent
+for the Mw 9 event occurring at HAT, MSL and LAT respectively. 
+As expected, there is greater inundation for the HAT scenario with increased
+extent. The major road from the south, 
+the Great Northern Highway, remains free of inundation for all tidal
+scenarios. At HAT, the road feeding off the highway, Anderson Street,
+suffers inundation in the tidal flat region. The inundation would
+be enough to halt usage of the road.
+The road servicing Finucane Station remains
+free of inundation, however there is a small section of the railway which
+receives under 0.2 m of water. Likewise, there
+is inundation on a section of the railway which services Port Hedland Station.
+There is not enough information regarding 
+the railway structure to determine whether it would halt its usage (i.e. how
+high has it been built). The airport remains
+free of inundation for each tidal scenario. 
 
 The geography of the Port Hedland area has played a role in offering
@@ -110 +35 @@
 the region past the east of the headland.
 
-The tsunami wave has an amplitude of around 0.3 m for the MSL
-scenario as it enters the 
-channel (Figure \ref{fig:gaugeMiddleChannel}. There seems to be
-limited or no amplification of the tsunami wave as it moves into
-the channel. The amplitude of the first tsunami wave is around 0.3 m at
-the Mt Goldworthy Wharf - Berth location (shown in red in Figure 
-\ref{fig:gaugeMtGoldworthyWharf-Berth} and the maximum amplitude
-is around 1.7 m. At MSL and LAT, there is limited inundation in the
-areas surrounding the channel. At HAT, significantly increased
-inundation is evident surrounding the channel, however, this inundation
-is essentially caught in the tidal flat regions.
-
-As expected, there is greater inundation for the HAT scenario with increased
-extent, with minimal inundation found at the locations chosen. 
-The major road from the south, 
-the Great Northern Highway, remains free of inundation for all tidal
-scenarios. At HAT, the road feeding off the highway, Anderson Street,
-suffers inundation in the tidal flat region. The inundation would
-be enough to halt usage of the road.
-The road servicing Finucane Station remains
-free of inundation, however there is a small section of the railway which
-receives under 0.2 m of water. Likewise, there
-is inundation on a section of the railway which services Port Hedland Station.
-There is not enough information regarding 
-the railway structure to determine whether it would halt its usage (i.e. how
-high has it been built). The airport remains
-free of inundation for each tidal scenario. Section \ref{sec:impact}
-details the impact estimates to the residential infrastructure.
+In addition to describing the maximum inundation extent,
+we have
+chosen a number of locations to illustrate the features
+of the tsunami as it approaches and impacts Port Hedland.
+These locations have been chosen as we believe they would 
+either be critical
+in an emergency situation, (e.g. the hospital) or
+effect recovery efforts, (e.g. the airport and wharfs). These locations
+are described in Table \ref{table:locations} and shown in 
+Figure \ref{fig:points}. The water's stage and speed 
+at each of these locations are shown
+as a function of time in the series of graphs shown in
+Appendix \ref{sec:timeseries}. Discussion of the main features of the
+tsunami wave is also described in Appendix \ref{sec:timeseries}.

anuga_work/production/pt_hedland_2006/report/introduction.tex

@@ -23 +23 @@
 detailing critical infrastructure as well as damage modelling estimates. 
 
-This report is the first in a series of tsunami assessments 
-of the North West Shelf. The scenario used for this study has
-an unknown return period, but considered a plausible event (see
-Section \ref{sec:tsunamiscenario}). 
-Subsequent assessments will use refined hazard models with
-associate return rates for other localities, as advised by FESA.
+This report details the impact assessments for a range of tsunami events.
+These events are based on the probabilistic hazard assessment conducted
+for the Western Australian coastline. A number of events are selected for
+return periods of 500, 1000 and 2000 years, see Section \ref{sec:tsunamiscenario}.
+
 Port Hedland has a population of around 42000 (including South Hedland) and
 is part of the Pilbara region of Western Autralia
@@ -37 +36 @@
 
 The modelling technique to simulate the 
-impact ashore will be discussed in Section \ref{sec:anuga} and data inputs
-discussed in Section \ref{sec:data}. 
+impact ashore will be discussed in Section \ref{sec:methodology} and 
+event and data inputs
+discussed in Sections \ref{sec:tsunamiscenario} and \ref{sec:data} respectively. 
 The inundation results are presented and discussed in Section \ref{sec:results} 
 and the impact modelling results outlined in Section \ref{sec:impact}.

anuga_work/production/pt_hedland_2006/report/metadata.tex

@@ -1 @@
-
-to be provided by Hamish and Kathryn
+%\includepdf[pages={1-6}]{MetadataforATWSPortHedlandScenario}

anuga_work/production/pt_hedland_2006/report/references.tex

@@ -12 +12 @@
 Tsunami (MOST) model, NOAA Technical Memorandum ERL PMEL-112.
 
-%\bibitem{somerville:urs} Somerville, P., Thio, H.K. and Ichinose, G. (2005)
-%Probabilistic Tsunami Hazard Analysis. Report delivered to Geoscience
-%Australia 2005.
+\bibitem{prob:fesa} Burbidge, D. and Cummins, P. (2006) Probabilistic
+Tsunami Hazard Assessment of Western Australia. Report to the 
+Fire and Emergency Services Authority of Western Australia.
+
+\bibitem{somerville:urs} Somerville, P., Thio, H.K. and Ichinose, G. (2005)
+Probabilistic Tsunami Hazard Analysis. Report delivered to Geoscience
+Australia 2005.
 
 \bibitem{matsuyama:1999}
@@ -46 +50 @@
 HAZUS-MH User Manual, Washington DC, USA.
 
+\bibitem{uq:friction} Duncan - do you have a reference for this?
+
 \end{thebibliography}

anuga_work/production/pt_hedland_2006/report/tsunami_scenario.tex

@@ -1 @@
-The tsunamigenic event used in this report was developed for a 
-preliminary tsunami hazard assessment study delivered by GA
-to FESA in September 2005
-\cite{BC:FESA}. In the assessment, a suite of Mw 9 earthquakes
-were evenly spaced along the Sunda Arc subduction zone and there
-was no consideration of the likelihood of each event. 
-Other less likely sources were not considered, such
-as intra-plate earthquakes near the WA coast, volcanoes, landslides
-or asteroids. 
-In the preliminary assessment,
-the maximum magnitude of earthquakes off Java was considered to be
-at least 8.5 and could potentially be as high as 9.
 
-FESA is interested in the ``most frequent worst case scenario''. Whilst
-we currently cannot determine exactly what that event may be, the Mw 9 event 
-provides a plausible worst case scenario. To understand the 
-frequency of these tsunami-genic events,
-GA is building probabilistic
-models to develop a more complete tsunami hazard assessment
-for the Sunda Arc subduction zone,
-due for completion in late 2006. In the preliminary assessment for
-example, it was suggested that while Mw 7 and 8 earthquakes are expected
-to occur with a greater frequency than Mw 9 events, 
-they are likely to pose a comparatively low and more localised hazard to WA. 
-
-Figure \ref{fig:mw9} shows the maximum wave height of a tsunami initiated 
-by a Mw 9 event off
-the coast of Java. This event provides the source and
-boundary condition to the
-inundation model presented in Section \ref{sec:anuga}. 
-
-
-\begin{figure}[hbt]
-
-  \centerline{ \includegraphics[width=100mm, height=75mm]
-{../report_figures/mw9.jpg}}
-
-  \caption{Maximum wave height (in cms) for a Mw 9 event off the 
-coast of Java}
-  \label{fig:mw9}
-\end{figure}