@@ -54,7 +54,7 @@ def __init__(self, prnt):
5454 self .plotTitle = None
5555 self .numBins = 25
5656 self .binWidth = 1.5
57- self .boxWhiskerMethod = "Month "
57+ self .boxWhiskerMethod = "month "
5858
5959 self .yrange = 0
6060 self .color = ""
@@ -226,8 +226,10 @@ def getSelectedSeries(self, seriesID):
226226 return self .createSeriesInfo (seriesID , seriesInfo , series )
227227
228228 def createSeriesInfo (self , seriesID , seriesInfo , series ):
229- startDate = series .begin_date_time
230- endDate = series .end_date_time
229+
230+ dates = self .memDB .series_service .get_result_dates (series .ResultID )
231+ startDate = dates [1 ]
232+ endDate = dates [0 ]
231233
232234 if endDate > self .endDate :
233235 self .endDate = endDate
@@ -237,14 +239,15 @@ def createSeriesInfo(self, seriesID, seriesInfo, series):
237239 if not self .isSubsetted :
238240 self .currentStart = self .startDate
239241 self .currentEnd = self .endDate
240-
241- variableName = series .variable_name
242- unitsName = series .variable_units_name
243- siteName = series .site_name
244- dataType = series .data_type
245- variable = self .memDB .series_service .get_variable_by_id (series .variable_id )
246-
247- noDataValue = variable .no_data_value
242+ #TODO odm2
243+
244+ unitsName = series .UnitsObj .UnitsName
245+ siteName = series .FeatureActionObj .SamplingFeatureObj .SamplingFeatureName
246+ dataType = "datatype" #series.data_type
247+ #variable = self.memDB.series_service.get_variable_by_id(series.variable_id)
248+ variable = series .VariableObj
249+ variableName = variable .VariableNameCV
250+ noDataValue = variable .NoDataValue
248251 if self .editID == seriesID :
249252 #d= DataFrame(pandas.read_sql())
250253 logger .debug ("editing -- getting datavalues for graph" )
@@ -256,6 +259,7 @@ def createSeriesInfo(self, seriesID, seriesInfo, series):
256259 data = self .memDB .getDataValuesforGraph (seriesID , noDataValue , self .currentStart , self .currentEnd )
257260 logger .debug ("Finished plotting -- getting datavalues for graph" )
258261
262+
259263 logger .debug ("assigning variables..." )
260264 seriesInfo .seriesID = seriesID
261265 seriesInfo .series = series
@@ -266,13 +270,13 @@ def createSeriesInfo(self, seriesID, seriesInfo, series):
266270 seriesInfo .siteName = siteName
267271 seriesInfo .variableName = variableName
268272 seriesInfo .variableUnits = unitsName
269- seriesInfo .plotTitle = "Site: " + siteName + " \n VarName: " + variableName + " \n QCL: " + series .quality_control_level_code
270- seriesInfo .axisTitle = variableName + " (" + unitsName + ")"
273+ seriesInfo .plotTitle = "Site: %s \n VarName: %s \n QCL: %s" % ( siteName , variableName , series .ProcessingLevelID )
274+ seriesInfo .axisTitle = "%s (%s)" % ( variableName , unitsName )
271275 seriesInfo .noDataValue = noDataValue
272276 seriesInfo .dataTable = data
273277
274278 if len (data ) > 0 :
275- seriesInfo .yrange = np .max (data ['DataValue ' ]) - np .min (data ['DataValue ' ])
279+ seriesInfo .yrange = np .max (data ['datavalue ' ]) - np .min (data ['datavalue ' ])
276280 else :
277281 seriesInfo .yrange = 0
278282
@@ -298,9 +302,9 @@ def getSeriesInfo(self, seriesID):
298302
299303 def buildPlotInfo (self , seriesInfo ):
300304 #remove all of the nodatavalues from the pandas table
301- filteredData = seriesInfo .dataTable [seriesInfo .dataTable ["DataValue " ] != seriesInfo .noDataValue ]
302- val = filteredData ["Month " ].map (calcSeason )
303- filteredData ["Season " ] = val
305+ filteredData = seriesInfo .dataTable [seriesInfo .dataTable ["datavalue " ] != seriesInfo .noDataValue ]
306+ val = filteredData ["month " ].map (calcSeason )
307+ filteredData ["season " ] = val
304308
305309 # construct tasks for the task server
306310 tasks = [("Probability" , filteredData ),
@@ -353,12 +357,12 @@ class Statistics(object):
353357 def __init__ (self , data ):
354358 start_time = timeit .default_timer ()
355359
356- dvs = data ["DataValue " ]
360+ dvs = data ["datavalue " ]
357361 count = len (dvs )
358362 if count > 0 :
359363
360364 time = timeit .default_timer ()
361- self .NumberofCensoredObservations = len (data [data ["CensorCode " ] != "nc" ])
365+ self .NumberofCensoredObservations = len (data [data ["censorcodecv " ] != "nc" ])
362366 elapsed = timeit .default_timer () - time
363367 logger .debug ("censored observations using len: %s" % elapsed )
364368
@@ -396,13 +400,13 @@ def __init__(self, data, method):
396400 self .intervals = {}
397401 self .method = method
398402
399- interval_types = ["Overall " , "Year " , "Month " , "Season " ]
400- intervals = ["Overall " , "Year " , "Month " , "Season " ]
403+ interval_types = ["overall " , "year " , "month " , "season " ]
404+ intervals = ["overall " , "year " , "month " , "season " ]
401405
402406 interval_options = zip (interval_types , intervals )
403407 for interval_type , interval in interval_options :
404408 start_time = timeit .default_timer ()
405- if interval_type == "Overall " :
409+ if interval_type == "overall " :
406410 interval = data
407411 else :
408412 interval = data .groupby (interval_type )
@@ -421,18 +425,18 @@ def calculateBoxWhiskerData(self, interval, interval_type):
421425
422426 results = self .calculateIntervalsOnGroups (interval )
423427
424- if interval_type == "Season " or interval_type == "Month " :
428+ if interval_type == "season " or interval_type == "month " :
425429 func = None
426- if interval_type == "Season " :
430+ if interval_type == "season " :
427431 func = numToSeason
428- elif interval_type == "Month " :
432+ elif interval_type == "month " :
429433 func = numToMonth
430434
431435 self .intervals [interval_type ] = BoxWhiskerPlotInfo (
432436 interval_type , interval_type , [func (x ) for x in results ["names" ]],
433437 [results ["median" ], results ["conflimit" ], results ["mean" ], results ["confint" ]])
434438
435- elif interval_type == "Overall " :
439+ elif interval_type == "overall " :
436440 self .intervals [interval_type ] = BoxWhiskerPlotInfo (
437441 interval_type , None , [],
438442 [results ["median" ], results ["conflimit" ], results ["mean" ], results ["confint" ]])
@@ -452,7 +456,7 @@ def calculateIntervalsOnGroups(self, interval):
452456
453457 if isinstance (interval , pd .core .groupby .DataFrameGroupBy ):
454458 for name , group in interval :
455- datavalue = group ['DataValue ' ]
459+ datavalue = group ['datavalue ' ]
456460 group_mean = np .mean (datavalue )
457461 group_median = np .median (datavalue )
458462 group_std = math .sqrt (np .var (datavalue ))
@@ -467,8 +471,8 @@ def calculateIntervalsOnGroups(self, interval):
467471 median .append (group_median )
468472 mean .append (group_mean )
469473 else :
470- name = "Overall "
471- datavalue = interval ['DataValue ' ]
474+ name = "overall "
475+ datavalue = interval ['datavalue ' ]
472476 data_mean = np .mean (datavalue )
473477 data_median = np .median (datavalue )
474478 data_std = math .sqrt (np .var (datavalue ))
@@ -539,7 +543,7 @@ def __init__(self, data):
539543 :param data:
540544 :return:
541545 """
542- self .yAxis = data ['DataValue ' ]
546+ self .yAxis = data ['datavalue ' ]
543547 # Determine rank, sorting values doesn't change outcome while using pandas.
544548 ranks = self .yAxis .rank ()
545549 PrbExc = ranks / (len (ranks ) + 1 ) * 100
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