def calculateStats(results, Fields, Filter):
""" Calculates S_ (Sum), A_ (Avg/mean), and D_ (std Deviation) for each field"""
try:
for field in Fields:
#print field,field,results[field]
parts = field.split('_')
if len(parts) > 1: prefix = parts[0] + '_'
else: prefix = ''
if len(results[field]) > 1:
results['S_' + field] = MLab.sum(results[field])
results['A_' + field] = MLab.mean(results[field])
results['D_' + field] = MLab.std(
results[field]) / (MLab.sqrt(len(results[field])) - 1)
else:
results['S_' + field] = results[field][0]
results['A_' + field] = results[field][0]
results['D_' + field] = 0.0
Filtered = MLab.nonzero(
results[prefix + 'TgtFound'][:len(results[field]) - 1])
if len(Filtered) > 1:
TgtFoundResults = MLab.choose(Filtered, results[field])
results['N_' + field] = MLab.mean(TgtFoundResults)
results['E_' + field] = MLab.std(TgtFoundResults) / (
MLab.sqrt(len(TgtFoundResults)) - 1)
else:
results['N_' + field] = MLab.choose(Filtered,
results[field])[0]
results['E_' + field] = 0.0
results['RtngConfCorr'] = calculateCorrelation(results['NavConf'],
results['DirRtng'])
results['RtngCorrCorr'] = calculateCorrelation(results['NavConf'],
results['TgtFound'])
results['ConfCorrCorr'] = calculateCorrelation(results['DirRtng'],
results['TgtFound'])
results['RtngEffcCorr'] = calculateCorrelation(results['NavConf'],
results['Efficiency'])
results['ConfEffcCorr'] = calculateCorrelation(results['DirRtng'],
results['Efficiency'])
results['A_CorrTgt'] = results['CorrTgt'] / float(results['IncrTgt'] +
results['CorrTgt'])
except IndexError:
pass #print 'ERROR: Missing keys when calculating stats for', field, Filter
except KeyError:
pass #print 'ERROR: Missing keys when calculating stats for', field, Filter
except ValueError:
print 'ERROR: Invalid entry in choice array', field, Filtered, len(
results[field]), '\n', results[field]
