python.trfUtils.analytic Class Reference

Analytics service class. More...

Collaboration diagram for python.trfUtils.analytic:

Public Member Functions
def	__init__ (self, **kwargs)
def	fit (self, x, y, model='linear')
	Fitting function For a linear model: y(x) = slope * x + intersect. More...
def	slope (self)
def	getFittedData (self, filename, x_name='Time', y_name='pss', precision=2, tails=False, minPoints=5)
def	extractFromTable (self, table, x_name, y_name)
def	formatBytes (self, size)

Static Private Attributes
	_fit

Detailed Description

Analytics service class.

Definition at line 1252 of file trfUtils.py.

Constructor & Destructor Documentation

__init__()

def python.trfUtils.analytic.__init__	(		self,
		**	kwargs
	)

Definition at line 1256 of file trfUtils.py.

    def __init__(self, **kwargs):
        self._fit = None
 

Member Function Documentation

extractFromTable()

def python.trfUtils.analytic.extractFromTable	(		self,
			table,
			x_name,
			y_name
	)

Definition at line 1335 of file trfUtils.py.

    def extractFromTable(self, table, x_name, y_name):
        headerUpperVersion = {'pss':'PSS', 'swap':'Swap', 'rss':'RSS', 'vmem':'VMEM'}
        x = table.get(x_name, [])
        if '+' not in y_name:
            y = table.get(y_name, [])
            if len(y)==0:
                y = table.get(headerUpperVersion[y_name], [])
        else:
            try:
                y1_name = y_name.split('+')[0]
                y2_name = y_name.split('+')[1]
                y1_value = table.get(y1_name, [])
                y2_value = table.get(y2_name, [])
                if len(y1_value)==0 or len(y2_value)==0:
                    y1_value = table.get(headerUpperVersion[y1_name], [])
                    y2_value = table.get(headerUpperVersion[y2_name], [])
            except Exception as e:
                msg.warning('exception caught: {0}'.format(e))
                x = []
                y = []
            else:
                # create new list with added values (1,2,3) + (4,5,6) = (5,7,9)
                y = [x0 + y0 for x0, y0 in zip(y1_value, y2_value)]
 
        return x, y
 

fit()

def python.trfUtils.analytic.fit	(		self,
			x,
			y,
			model = 'linear'
	)

Fitting function For a linear model: y(x) = slope * x + intersect.

Parameters

x	list of input data (list of floats or ints).
y	list of input data (list of floats or ints).
model	model name (string).

Definition at line 1264 of file trfUtils.py.

    def fit(self, x, y, model='linear'):
        try:
            self._fit = Fit(x=x, y=y, model=model)
        except Exception as e:
            msg.warning('fit failed! {0}'.format(e))
 
        return self._fit
 

formatBytes()

def python.trfUtils.analytic.formatBytes	(		self,
			size
	)

Definition at line 1363 of file trfUtils.py.

    def formatBytes(self, size):
        # decimal system
        power = 1000
        n = 1
        power_labels = {1: 'K', 2: 'M', 3: 'G', 4: 'T'}
        while size > power:
            size /= power
            n += 1
        return round(size, 2), power_labels[n]+'B/s'
 
 

getFittedData()

def python.trfUtils.analytic.getFittedData	(		self,
			filename,
			x_name = 'Time',
			y_name = 'pss',
			precision = 2,
			tails = False,
			minPoints = 5
	)

Definition at line 1292 of file trfUtils.py.

    def getFittedData(self, filename, x_name='Time', y_name='pss', precision=2, tails=False, minPoints=5):
        _memFileToTable = memFileToTable()
        fitResult = {}
        table = _memFileToTable.getTable(filename, header=None, separator="\t")
        if table:
            # extract data to be fitted
            x, y = self.extractFromTable(table, x_name, y_name)
            # remove tails if desired
            # this is useful e.g. for memory monitor data where the first and last values
            # represent allocation and de-allocation, ie not interesting
            # here tail is defined to be first and last 20% of data
            if not tails:
                tail = int(len(x)/5)
                msg.info('removing tails from the memory monitor data; 20% from each side')
                x = x[tail:]
                x = x[:-tail]
                y = y[tail:]
                y = y[:-tail]
 
            if len(x)==len(y) and len(x) > minPoints:
                msg.info('fitting {0} vs {1}'.format(y_name, x_name))
                try:
                    fit = self.fit(x, y)
                    _slope = self.slope()
                except Exception as e:
                    msg.warning('failed to fit data, x={0}, y={1}: {2}'.format(x, y, e))
                else:
                    if _slope:
                        slope = round(fit.slope(), precision)
                        chi2 = round(fit.chi2(), precision)
                        fitResult = {"slope": slope, "chi2": chi2}
                        if slope:
                            HRslope, unit = self.formatBytes(slope)
                            msg.info('slope of the fitted line: {0} {1} (using {2} data points, chi2={3})'.format(HRslope, unit, len(x), chi2))
            else:
                msg.warning('wrong length of table data, x={0}, y={1} (must be same and length>={2})'.format(x, y, minPoints))
 
        return fitResult
 

slope()

def python.trfUtils.analytic.slope

(

self

)

Definition at line 1273 of file trfUtils.py.

    def slope(self):
        slope = None
 
        if self._fit:
            slope = self._fit.slope()
        else:
            msg.warning('Fit has not been defined')
 
        return slope
 

Member Data Documentation

_fit

python.trfUtils.analytic._fit

staticprivate

Definition at line 1254 of file trfUtils.py.

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The documentation for this class was generated from the following file:

• trfUtils.py