Mercurial > hg > nsaunier > traffic-intelligence

comparison python/pavement.py @ 475:819eef979d3f

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clarified argument name and made it available in a calling function
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Sun, 23 Mar 2014 23:49:37 -0400
parents 16fe64136506
children 6ebdd90ce3ee
comparison
equal deleted inserted replaced
474:59903d14d244 475:819eef979d3f
131 else: 131 else:
132 somme_eau, somme_neige, somme_abrasif, somme_sel, somme_lc, somme_lrg, somme_lrd, premiere_neige, autres_abrasifs, neigeMTQ_sup_seuil = '','','','','','','','','','' 132 somme_eau, somme_neige, somme_abrasif, somme_sel, somme_lc, somme_lrg, somme_lrd, premiere_neige, autres_abrasifs, neigeMTQ_sup_seuil = '','','','','','','','','',''
133 133
134 return (somme_eau, somme_neige, neigeMTQ_sup_seuil, somme_abrasif, somme_sel, somme_lc, somme_lrg, somme_lrd, premiere_neige, autres_abrasifs) 134 return (somme_eau, somme_neige, neigeMTQ_sup_seuil, somme_abrasif, somme_sel, somme_lc, somme_lrg, somme_lrd, premiere_neige, autres_abrasifs)
135 135
136 def ecWeatherIndicators(data, startDate, endDate, snowThreshold, datatype, minProportionMeasures = 0.): 136 def ecWeatherIndicators(data, startDate, endDate, snowThreshold, weatherDatatype, minProportionMeasures = 0.):
137 '''Computes the indicators from Environment Canada files 137 '''Computes the indicators from Environment Canada files
138 (loaded as a recarray using csv2rec in data), 138 (loaded as a recarray using csv2rec in data),
139 between start and end dates (datetime.datetime objects) 139 between start and end dates (datetime.datetime objects)
140 140
141 dataType is to indicate Environnement Canada data ('ec') or else MTQ 141 weatherDataType is to indicate Environnement Canada data ('ec') or else MTQ
142 minProportionMeasures is proportion of measures necessary to consider the indicators''' 142 minProportionMeasures is proportion of measures necessary to consider the indicators'''
143 from matplotlib.mlab import find 143 from matplotlib.mlab import find
144 nbre_jours_T_negatif,nbre_jours_gel_degel,pluie_tot,neige_tot,ecart_type_T = 0,0,0,0,0 144 nbre_jours_T_negatif,nbre_jours_gel_degel,pluie_tot,neige_tot,ecart_type_T = 0,0,0,0,0
145 compteur,nbre_jours_gel_consecutifs=0,0 145 compteur,nbre_jours_gel_consecutifs=0,0
146 tmoys = [] 146 tmoys = []
156 tmax = None 156 tmax = None
157 if not np.isnan(data['tmin'][i]): 157 if not np.isnan(data['tmin'][i]):
158 tmin = data['tmin'][i] 158 tmin = data['tmin'][i]
159 else: 159 else:
160 tmin = None 160 tmin = None
161 if datatype == 'ec': 161 if weatherDatatype == 'ec':
162 if data['pluie_tot'][i] != None and not np.isnan(data['pluie_tot'][i]): 162 if data['pluie_tot'][i] != None and not np.isnan(data['pluie_tot'][i]):
163 pluie_tot += data['pluie_tot'][i] 163 pluie_tot += data['pluie_tot'][i]
164 if data['neige_tot'][i] != None and not np.isnan(data['neige_tot'][i]): 164 if data['neige_tot'][i] != None and not np.isnan(data['neige_tot'][i]):
165 neige_tot += data['neige_tot'][i] 165 neige_tot += data['neige_tot'][i]
166 if tmax != None: 166 if tmax != None:
277 277
278 def plotMarkingMeasures(self, measure, options = 'o', dayRatio = 1., **kwargs): 278 def plotMarkingMeasures(self, measure, options = 'o', dayRatio = 1., **kwargs):
279 for i in range(1,7): 279 for i in range(1,7):
280 self.plot('{}_{}'.format(measure, i), options, dayRatio, **kwargs) 280 self.plot('{}_{}'.format(measure, i), options, dayRatio, **kwargs)
281 281
282 def computeMarkingMeasureVariations(self, dataLabel, lanePositions, weatherData, snowThreshold, minProportionMeasures = 0.): 282 def computeMarkingMeasureVariations(self, dataLabel, lanePositions, weatherData, snowThreshold, weatherDataType = 'ec', minProportionMeasures = 0.):
283 '''Computes for each successive measurement 283 '''Computes for each successive measurement
284 lanePositions = None 284 lanePositions = None
285 measure variation, initial measure, time duration, weather indicators 285 measure variation, initial measure, time duration, weather indicators
286 286
287 TODO if measurements per lane, add a variable for lane position (position1 to 6) 287 TODO if measurements per lane, add a variable for lane position (position1 to 6)
294 nonZeroIndices = ~np.isnan(self.data[dataLabel]) 294 nonZeroIndices = ~np.isnan(self.data[dataLabel])
295 days = self.data[nonZeroIndices]['jours'] 295 days = self.data[nonZeroIndices]['jours']
296 dates = self.data[nonZeroIndices]['date_mesure'] 296 dates = self.data[nonZeroIndices]['date_mesure']
297 measures = self.data[nonZeroIndices][dataLabel] 297 measures = self.data[nonZeroIndices][dataLabel]
298 for i in range(1, len(dates)): 298 for i in range(1, len(dates)):
299 nDaysTNegative, nDaysThawFreeze, deltaTemp, nConsecutiveFrozenDays, totalRain, totalSnow, snowAboveThreshold, stdevTemp = ecWeatherIndicators(weatherData, dates[i-1], dates[i], snowThreshold, minProportionMeasures) 299 nDaysTNegative, nDaysThawFreeze, deltaTemp, nConsecutiveFrozenDays, totalRain, totalSnow, snowAboveThreshold, stdevTemp = ecWeatherIndicators(weatherData, dates[i-1], dates[i], snowThreshold, weatherDataType, minProportionMeasures)
300 if dates[i-1].year+1 == dates[i].year: 300 if dates[i-1].year+1 == dates[i].year:
301 winter = 1 301 winter = 1
302 if days[i-1]<365: 302 if days[i-1]<365:
303 firstWinter = 1 303 firstWinter = 1
304 else: 304 else: