def ttest_table(ttest_table_name, tcrit, tables1, tables2, xcolname, ycolname):
assert (len(tables1) == len(tables2))
colnames = [xcolname, 'Mean', 'StdDev', 'Sig', 'tval', 'pval']
xcoltype = tables1[0].coltypes[tables1[0].colnames.index(xcolname)]
coltypes = [xcoltype, 'float', 'float', 'int', 'float', 'float']
xvalues = common_functions.get_timesteps(tables1 + tables2, xcolname)
result = datalib.Table(ttest_table_name, colnames, coltypes)
for x in xvalues:
data1 = [table[x][ycolname] for table in tables1]
data2 = [table[x][ycolname] for table in tables2]
diffMean, stdDev, tval, pval = ttest(data1, data2)
row = result.createRow()
row[xcolname] = x
row["Mean"] = diffMean
row["StdDev"] = stdDev
if tval >= tcrit:
row["Sig"] = 1
else:
row["Sig"] = 0
row["tval"] = tval
row["pval"] = pval
return result
def avr_table_from_tables( avr_table_name, tables, xcolname, ycolname ):
colnames = [xcolname, 'min', 'q1', 'median', 'q3', 'max', 'mean', 'mean_stderr', 'sampsize']
xcoltype = tables[0].coltypes[ tables[0].colnames.index(xcolname) ]
coltypes = [xcoltype, 'float', 'float', 'float', 'float', 'float', 'float', 'float', 'int']
result = datalib.Table(avr_table_name, colnames, coltypes)
xvalues = common_functions.get_timesteps( tables, xcolname )
for x in xvalues:
ydata = []
for table in tables:
ydata.append( table[x][ycolname] )
ydata.sort()
minimum, maximum, mean, mean_stderr, q1, q3, median = avr(ydata)
row = result.createRow()
row.set(xcolname, x)
row.set('min', minimum)
row.set('max', maximum)
row.set('mean', mean)
row.set('mean_stderr', mean_stderr)
row.set('median', median)
row.set('q1', q1)
row.set('q3', q3)
row.set('sampsize', len(ydata))
return result
def avr_table_from_tables(avr_table_name, tables, xcolname, ycolname):
colnames = [
xcolname, 'min', 'q1', 'median', 'q3', 'max', 'mean', 'mean_stderr',
'sampsize'
]
xcoltype = tables[0].coltypes[tables[0].colnames.index(xcolname)]
coltypes = [
xcoltype, 'float', 'float', 'float', 'float', 'float', 'float',
'float', 'int'
]
result = datalib.Table(avr_table_name, colnames, coltypes)
xvalues = common_functions.get_timesteps(tables, xcolname)
for x in xvalues:
ydata = []
for table in tables:
ydata.append(table[x][ycolname])
ydata.sort()
minimum, maximum, mean, mean_stderr, q1, q3, median = avr(ydata)
row = result.createRow()
row.set(xcolname, x)
row.set('min', minimum)
row.set('max', maximum)
row.set('mean', mean)
row.set('mean_stderr', mean_stderr)
row.set('median', median)
row.set('q1', q1)
row.set('q3', q3)
row.set('sampsize', len(ydata))
return result
def ttest_table( ttest_table_name,
tcrit,
tables1,
tables2,
xcolname,
ycolname ):
assert( len(tables1) == len(tables2) )
colnames = [xcolname, 'Mean', 'StdDev', 'Sig', 'tval', 'pval']
xcoltype = tables1[0].coltypes[ tables1[0].colnames.index(xcolname) ]
coltypes = [xcoltype, 'float', 'float', 'int', 'float', 'float']
xvalues = common_functions.get_timesteps( tables1 + tables2, xcolname )
result = datalib.Table( ttest_table_name, colnames, coltypes )
for x in xvalues:
data1 = [ table[x][ycolname] for table in tables1 ]
data2 = [ table[x][ycolname] for table in tables2 ]
diffMean, stdDev, tval, pval = ttest( data1, data2 )
row = result.createRow()
row[xcolname] = x
row["Mean"] = diffMean
row["StdDev"] = stdDev
if tval >= tcrit:
row["Sig"] = 1
else:
row["Sig"] = 0
row["tval"] = tval
row["pval"] = pval
return result
