source: anuga_work/production/australia_ph2/plot_comparisons/plot_250m_comparisons.py @ 7542

"""
Program to plot the results from the Phase 2 comparisions.


Creator: Jonathan Griffin
Created: 29 September 2009
"""
import os
import sys
from os.path import join
import csv

import matplotlib
matplotlib.use('Agg')
import pylab
from pylab import *
import numpy

path = r'/nas/gemd/georisk_models/inundation/data/australia_ph2/documents/250m comparisons'
path_list = []
model_list = ['BatemansBay', 'Busselton', 'Carnarvon', 'Geraldton', 'GoldCoast', 'Gosford', 'Pt_hedland']

# Choose figure name here! This controls what is plotted
#figure_name = 'Phase2comparions_percent.png' # Plots the mean percentage difference in stage
figure_name = 'Phase2comparions.png'   # Plots the absolute difference in stage
figure_folder = join(path, 'figures')
figure_path = join(figure_folder, figure_name)

for model in model_list:
    model_path = join(path, model, 'comparisons.csv')
    path_list.append(model_path)

plot_dict = {'BatemansBay':'x', 'Busselton':'^', 'Carnarvon':'x', 'Geraldton':'h', 'GoldCoast': 'v', 'Gosford':'+', 'Pt_hedland':'+'}
colour_dict = {'BatemansBay':'r', 'Busselton':'b', 'Carnarvon': 2.03, 'Geraldton':'b', 'GoldCoast': 'r', 'Gosford':'r', 'Pt_hedland':'b'}

mean_100m_stage = {'BatemansBay': 1.10, 'Busselton': 0.98, 'Carnarvon': 2.03, 'Geraldton':0.95,
                   'GoldCoast': 2.22, 'Gosford': 1.86, 'Hobart': 2.05,'Pt_hedland': 0.77}
event_dict = {'BatemansBay': 58284, 'Busselton': 27283, 'Carnarvon': 27283, 'Geraldton':27283,
              'GoldCoast': 51469, 'Gosford': 51436, 'Hobart': 58260, 'Pt_hedland': 27283}
#
pylab.cla()
counter = 0
for file_path in path_list:
    reader = csv.reader(open(file_path))
    header = reader.next()
    depth_index = header.index('VALUE_')
    stage_diff_index = header.index('STAGE_DIFF')
    orig_stage_index = header.index('stage_high_res_model')
    print depth_index, stage_diff_index, orig_stage_index
    depth = []
    stage_diff = []
    orig_stage = []
    for row in reader:
        depth.append(float(row[depth_index]))
        stage_diff.append(abs((float(row[stage_diff_index]))))
        orig_stage.append(float(row[orig_stage_index]))
    depth_dict = dict.fromkeys(depth).keys()

    stage_diff_dict = {}
    orig_stage_dict = {}
    percent_diff_dict = {}
    stage_diff_mean_dict = {}
    orig_stage_mean_dict = {}
    percent_diff_mean_dict = {}
    key_list = []
    
    diff_mean_list = []
    percent_mean_list = []
    
    for key in depth_dict:
   
        stage_diff_list = []        
        orig_stage_list = []
        percent_diff_list = []
        for i in range(len(depth)):
            if depth[i] == key:
                stage_diff_list.append(stage_diff[i])
                orig_stage_list.append(orig_stage[i])
                percent_diff_list.append((stage_diff[i]/orig_stage[i])*100)
        stage_diff_dict[key] = stage_diff_list
        orig_stage_dict[key] = orig_stage_list
        percent_diff_dict[key] = percent_diff_list

        stage_diff_mean_dict[key] = numpy.mean(stage_diff_dict[key])
        orig_stage_mean_dict[key] = numpy.mean(orig_stage_dict[key])
        percent_diff_mean_dict[key] = numpy.mean( percent_diff_dict[key])
        key_list.append(key)
        diff_mean_list.append(stage_diff_mean_dict[key])
        percent_mean_list.append(percent_diff_mean_dict[key])

    pylab.semilogy()
    pylab.xlabel('Depth (m)') 
    
    if figure_name == 'Phase2comparions.png':
        pylab.title('Mean difference in stage height (m)')
        pylab.ylabel('Difference (m)')
        pylab.scatter(key_list,diff_mean_list, marker = plot_dict[model_list[counter]],color = colour_dict[model_list[counter]])
    if figure_name == 'Phase2comparions_percent.png':
        pylab.title('Mean percentage difference in stage height')
        pylab.ylabel('Difference %')
        pylab.scatter(key_list,percent_mean_list, marker = plot_dict[model_list[counter]],color = colour_dict[model_list[counter]])
            
    counter+=1

if figure_name == 'Phase2comparions.png':
   pylab.text(-58, 50, 'East Coast', color = 'r')
   pylab.text(-58, 30, 'West Coast', color = 'b')
 
if figure_name == 'Phase2comparions_percent.png':
    pylab.text(-58, 600, 'East Coast', color = 'r')
    pylab.text(-58, 400, 'West Coast', color = 'b')
    

pylab.savefig(figure_path)