source: anuga_work/production/new_south_wales/batemans_bay/plot_area_energy2.py @ 7577

"""
This file plots offshore wave energy against inundation area
Created: 3 December 2009
Cretor: Jonathan Griffin
"""
import matplotlib
matplotlib.use('Agg')
import pylab
from pylab import *
import csv
from os.path import join

boundary_path = "/nas/gemd/georisk_models/inundation/data/new_south_wales/batemans_bay_tsunami_scenario_2009/anuga/boundaries/"
in_file_name = 'area_comparisons_anuga_sum.csv'
energy_file_name = 'wave_energy_summary.csv'
energy_figure_name = 'area_wave_energy_sum_areas2.png'
wave_height_figure_name = 'area_wave_wave_height_sum_areas2.png'
madsen_figure_name = 'area_wave_madsen_sum_areas2.png'
energy_run_up_figure_name = 'area_wave_energy_run_up_sum_areas2.png'

in_file = join(boundary_path, in_file_name)

energy_file = join(boundary_path, energy_file_name)
energy_figure_path = join(boundary_path, 'figures',energy_figure_name)
wave_height_figure_path = join(boundary_path, 'figures',wave_height_figure_name)
madsen_figure_path = join(boundary_path, 'figures',madsen_figure_name)
energy_run_up_figure_path = join(boundary_path, 'figures',energy_run_up_figure_name)

csv_in = csv.reader(open(in_file,'r'))
csv_energy = csv.reader(open(energy_file,'r'))
##header = csv_in.next()
header_energy = csv_energy.next()

event_dict = {'Event1_MSL':58346,
              'Event2_MSL':51204,
              'Event3_MSL':58284,
              'Puysegur_200yr':58129,
              'Puysegur_500yr':58115,
              'Puysegur_1000yr':58226,
              'Puysegur_5000yr':58286,
              'Puysegur_15000yr':58272,
              'New_Hebrides_200yr':51077,
              'New_Hebrides_500yr':51378,
              'New_Hebrides_1000yr':51347,
              'New_Hebrides_2000yr':51292,
              'New_Hebrides_5000yr':51424}

anuga_areas_dict = {}
for row in csv_in:
    anuga_areas_dict[row[0]]=float(row[1])
print anuga_areas_dict
##area_id_list = []
area_anuga_list = []
##energy_id_list = []
##energy = []
energy_list = []
wave_height_list = []
madsen_list = []
energy_run_up_list = []
##area_sum_list = []

for row in csv_energy:
    event_id = row[0].split('/')[10]
    print 'event id', event_id
    for key, value in event_dict.iteritems():
        if value == int(event_id):
            print 'anuga_areas_dict[value]',anuga_areas_dict[str(value)]
            area_anuga_list.append(anuga_areas_dict[str(value)])
            energy_list.append(float(row[1]))
            wave_height_list.append(float(row[5]))
            madsen_list.append(float(row[3]))
            energy_run_up_list.append(float(row[4]))
##    if event_name == False:
##        continue
    
pylab.cla()

pylab.title('Inundation area and maximum offshore energy')
pylab.xlabel('Maximum crest integrated energy at 100 m contour (J)')
#pylab.xlabel('Maximum offshore wave height (m)')
pylab.ylabel('Area inundated (m^2)')
##for key, value in area_percent:
##    key_list = []
##    for val in value:
##        key_list.append(key)
pylab.scatter(energy_list,area_anuga_list)
#pylab.scatter(energy,area_sum_list)
#pylab.axis([0,2e7,0,500000])
pylab.savefig(energy_figure_path)

pylab.cla()

pylab.title('Inundation area and maximum offshore wave height')
#pylab.xlabel('Maximum crest integrated energy at 100 m contour (J)')
pylab.xlabel('Maximum offshore wave height (m)')
pylab.ylabel('Area inundated (m^2)')
##for key, value in area_percent:
##    key_list = []
##    for val in value:
##        key_list.append(key)
pylab.scatter(wave_height_list,area_anuga_list)
#pylab.scatter(energy,area_sum_list)
#pylab.axis([0,2e7,0,500000])
pylab.savefig(wave_height_figure_path)

pylab.cla()

pylab.title('Inundation area and Madsen run-up solution')
#pylab.xlabel('Maximum crest integrated energy at 100 m contour (J)')
pylab.xlabel('Madsen run-up solution (m)')
pylab.ylabel('Area inundated (m^2)')
##for key, value in area_percent:
##    key_list = []
##    for val in value:
##        key_list.append(key)
pylab.scatter(madsen_list,area_anuga_list)
#pylab.scatter(energy,area_sum_list)
#pylab.axis([0,2e7,0,500000])
pylab.savefig(madsen_figure_path)

pylab.cla()

pylab.title('Inundation area and energy balance run-up solution')
#pylab.xlabel('Maximum crest integrated energy at 100 m contour (J)')
pylab.xlabel('Energy balance run-up solution (m)')
pylab.ylabel('Area inundated (m^2)')
##for key, value in area_percent:
##    key_list = []
##    for val in value:
##        key_list.append(key)
pylab.scatter(energy_run_up_list,area_anuga_list)
#pylab.scatter(energy,area_sum_list)
#pylab.axis([0,2e7,0,500000])
pylab.savefig(energy_run_up_figure_path)