utils.py

   1 # Copyright (C) 2013-2016 Martin Vejmelka, UC Denver
   2
   3 import json,sys
   4
   5 class Dict(dict):
   6     """
   7     A dictionary that allows member access to its keys.
   8     A convenience class.
   9     """
  10
  11     def __init__(self, d):
  12         """
  13         Updates itself with d.
  14         """
  15         self.update(d)
  16
  17     def __getattr__(self, item):
  18         try:
  19             return self[item]
  20         except KeyError:
  21             raise AttributeError(item)
  22
  23     def __setattr__(self, item, value):
  24         self[item] = value
  25
  26 def load_cfg():
  27     # load the system configuration
  28     cfg = Dict([])
  29     try:
  30         f_cfg = Dict(json.load(open('conf.json')))
  31     except IOError:
  32         print 'Warning: any conf.json file specified, creating defaults...'
  33         f_cfg = Dict([])
  34
  35     # Set default method settings
  36     try:
  37         # minimum confidence level for the satellite pixels to be considered
  38         cfg.minconf = f_cfg['method_settings'].get('minconf',70)
  39         # use 3D space-time points (or bounds)
  40         cfg.cloud = f_cfg['method_settings'].get('cloud',True)
  41         # dynamic penalization term?
  42         cfg.dyn_pen = f_cfg['method_settings'].get('dyn_pen',False)
  43         # if not so, 5-fold cross validation for C and gamma?
  44         if cfg.dyn_pen:
  45             cfg.search = False
  46         else:
  47             cfg.search = f_cfg['method_settings'].get('search',False)
  48         # interpolation of the results into fire mesh (if apply to spinup case)
  49         cfg.fire_interp = f_cfg['method_settings'].get('fire_interp',False)
  50     except:
  51         cfg.minconf = 70
  52         cfg.cloud = True
  53         cfg.dyn_pen = False
  54         cfg.search = False
  55         cfg.fire_interp = False
  56
  57     # Set default data paths
  58     try:
  59         # if ignitions are known: ([lons],[lats],[dates]) where lons and lats in degrees and dates in ESMF format
  60         # examples: "igns" : "([100],[45],['2015-05-15T20:09:00'])" or "igns" : "([100,105],[45,39],['2015-05-15T20:09:00','2015-05-15T23:09:00'])"
  61         cfg.igns = eval(f_cfg['data_paths'].get('igns','None'))
  62         # if infrared perimeters: path to KML files
  63         # examples: perim_path = './pioneer/perim'
  64         cfg.perim_path = f_cfg['data_paths'].get('perim_path','')
  65         # if forecast wrfout: path to netcdf wrfout forecast file
  66         # example: forecast_path = './patch/wrfout_patch'
  67         cfg.forecast_path = f_cfg['data_paths'].get('forecast_path','')
  68     except:
  69         cfg.igns = None
  70         cfg.perim_path = ''
  71         cfg.forecast_path = ''
  72
  73     # Set default plot settings
  74     try:
  75         # plot observed information (googlearth.kmz with png files)
  76         cfg.plot_observed = f_cfg['plot_settings'].get('plot_observed',False)
  77         # if so, only fire detections?
  78         if cfg.plot_observed:
  79             cfg.only_fire = f_cfg['plot_settings'].get('only_fire',False)
  80         else:
  81             cfg.only_fire = False
  82     except:
  83         cfg.plot_observed = False
  84         cfg.only_fire = False
  85
  86     # Set SVM default settings
  87     cfg.svm_settings = Dict([])
  88     # Plot settings
  89     try:
  90         # plot original data
  91         cfg.svm_settings.plot_data = f_cfg['plot_settings']['plot_svm'].get('plot_data',False)
  92         # plot scaled data with artificial data
  93         cfg.svm_settings.plot_scaled = f_cfg['plot_settings']['plot_svm'].get('plot_scaled',False)
  94         # plot decision volume
  95         cfg.svm_settings.plot_decision = f_cfg['plot_settings']['plot_svm'].get('plot_decision',False)
  96         # plot polynomial approximation
  97         cfg.svm_settings.plot_poly = f_cfg['plot_settings']['plot_svm'].get('plot_poly',False)
  98         # plot full hyperplane vs detections with support vectors
  99         cfg.svm_settings.plot_supports = f_cfg['plot_settings']['plot_svm'].get('plot_supports',False)
 100         # plot resulting fire arrival time vs detections
 101         cfg.svm_settings.plot_result = f_cfg['plot_settings']['plot_svm'].get('plot_result',False)
 102     except:
 103         cfg.svm_settings.plot_data = False
 104         cfg.svm_settings.plot_scaled = False
 105         cfg.svm_settings.plot_decision = False
 106         cfg.svm_settings.plot_poly = False
 107         cfg.svm_settings.plot_supports = False
 108         cfg.svm_settings.plot_result = False
 109     # Method settings
 110     try:
 111         # normalize the input data between 0 and 1
 112         cfg.svm_settings.norm = f_cfg['method_settings']['svm_settings'].get('norm',True)
 113         # if not Nans in the data are wanted (all Nans are going to be replaced by the maximum value)
 114         cfg.svm_settings.notnan = f_cfg['method_settings']['svm_settings'].get('notnan',True)
 115         # artificial creation of clear ground detections under real (preprocessing)
 116         cfg.svm_settings.artil = f_cfg['method_settings']['svm_settings'].get('artil',False)
 117         # if so, normalized vertical resolution (from 0 to 1) of the aggregation
 118         if cfg.svm_settings.artil:
 119             cfg.svm_settings.hartil = f_cfg['method_settings']['svm_settings'].get('hartil',.2)
 120         else:
 121             cfg.svm_settings.hartil = 0
 122         # artificial creation of fire detections above real (preprocessing)
 123         cfg.svm_settings.artiu = f_cfg['method_settings']['svm_settings'].get('artiu',True)
 124         # if so, normalized vertical resolution (from 0 to 1) of the aggregation
 125         if cfg.svm_settings.artiu:
 126             cfg.svm_settings.hartiu = f_cfg['method_settings']['svm_settings'].get('hartiu',.1)
 127         else:
 128             cfg.svm_settings.hartiu = 0
 129         # creation of an artificial mesh of clear ground detections at the bottom
 130         cfg.svm_settings.downarti = f_cfg['method_settings']['svm_settings'].get('downarti',True)
 131         # if so, how to the bottom normalized between 0 and 1 and confidence level of the artificial detections
 132         if cfg.svm_settings.downarti:
 133             cfg.svm_settings.dminz = f_cfg['method_settings']['svm_settings'].get('dminz',.1)
 134             cfg.svm_settings.confal = f_cfg['method_settings']['svm_settings'].get('confal',100)
 135         else:
 136             cfg.svm_settings.dminz = 0
 137             cfg.svm_settings.confal = 0
 138         # creation of an artificial mesh of fire detections at the top
 139         cfg.svm_settings.toparti = f_cfg['method_settings']['svm_settings'].get('toparti',False)
 140         # if so, how to the top normalized between 0 and 1 and confidence level of the artificial detections
 141         if cfg.svm_settings.toparti:
 142             cfg.svm_settings.dmaxz = f_cfg['method_settings']['svm_settings'].get('dmaxz',.1)
 143             cfg.svm_settings.confau = f_cfg['method_settings']['svm_settings'].get('confau',100)
 144         else:
 145             cfg.svm_settings.dmaxz = 0
 146             cfg.svm_settings.confau = 0
 147     except:
 148         cfg.svm_settings.notnan = True
 149         cfg.svm_settings.artil = False
 150         cfg.svm_settings.hartil = 0
 151         cfg.svm_settings.artiu = True
 152         cfg.svm_settings.hartiu = .1
 153         cfg.svm_settings.downarti = True
 154         cfg.svm_settings.dminz = .1
 155         cfg.svm_settings.confal = 100
 156         cfg.svm_settings.toparti = False
 157         cfg.svm_settings.dmaxz = 0
 158         cfg.svm_settings.confau = 0
 159     cfg.svm_settings.search = cfg.search
 160
 161     # Set AppKey for NRT downloads from https://nrt3.modaps.eosdis.nasa.gov/profile/app-keys
 162     try:
 163         cfg.appkey = f_cfg.get('appkey',None)
 164     except:
 165         cfg.appkey = None
 166
 167     return cfg