butools.fitting.SquaredDifference¶
-
butools.fitting.
SquaredDifference
()¶ Matlab: sd = SquaredDifference(p1, p2)
Mathematica: sd = SquaredDifference[p1, p2]
Python/Numpy: sd = SquaredDifference(p1, p2)
Returns the squared difference between two vectors.
Parameters: p1 : vector, length M
The first vector
p2 : vector, length M
The second vector
Returns: sd : double
The squared difference calculated as \(sq=\sum_{i=1}^M (p1_i-p2_i)^2\)
Examples
For Matlab:
>>> tr = dlmread('/home/gabor/github/butools/test/data/bctrace.iat'); >>> trAcf = LagCorrelationsFromTrace(tr, 10); >>> disp(trAcf); Columns 1 through 6 0.20005 0.18927 0.13895 0.14213 0.11713 0.12368 Columns 7 through 10 0.11212 0.10051 0.10019 0.098797 >>> [D0, D1] = MAPFromFewMomentsAndCorrelations(MarginalMomentsFromTrace(tr, 3), trAcf(1)); >>> mapAcf = LagCorrelationsFromMAP(D0, D1, 10); >>> disp(mapAcf); Columns 1 through 6 0.20005 0.12003 0.072023 0.043216 0.025931 0.015559 Columns 7 through 10 0.0093357 0.0056017 0.0033611 0.0020168 >>> sqAcf = SquaredDifference(mapAcf, trAcf); >>> disp(sqAcf); 0.07738
For Mathematica:
>>> tr = Flatten[Import["/home/gabor/github/butools/test/data/bctrace.iat","CSV"]]; >>> trAcf = LagCorrelationsFromTrace[tr, 10]; >>> Print[trAcf]; {0.2000486547928462, 0.18927461196895048, 0.1389510350355339, 0.14213385937998096, 0.11712708793961699, 0.12367812078281121, 0.11212100297743381, 0.10051058879698098, 0.10019060948165948, 0.0987971115012499} >>> {D0, D1} = MAPFromFewMomentsAndCorrelations[MarginalMomentsFromTrace[tr, 3], trAcf[[1]]]; >>> mapAcf = LagCorrelationsFromMAP[D0, D1, 10]; >>> Print[mapAcf]; {0.20004865479284564, 0.12003405953863643, 0.07202335583933256, 0.04321576564432875, 0.025930510713659746, 0.015558937250009402, 0.009335740858440003, 0.005601671629332731, 0.0033611392516858904, 0.0020167653187785875} >>> sqAcf = SquaredDifference[mapAcf, trAcf]; >>> Print[sqAcf]; 0.07737982553629176
For Python/Numpy:
>>> tr = np.loadtxt("/home/gabor/github/butools/test/data/bctrace.iat") >>> trAcf = LagCorrelationsFromTrace(tr, 10) >>> print(trAcf) [0.20004885484210852, 0.18927480124417365, 0.13895117398714094, 0.14213400151438738, 0.11712720506721902, 0.12367824446146115, 0.1121211150989561, 0.10051068930807179, 0.10019070967277495, 0.098797210298893726] >>> D0, D1 = MAPFromFewMomentsAndCorrelations(MarginalMomentsFromTrace(tr, 3), trAcf[0]) >>> mapAcf = LagCorrelationsFromMAP(D0, D1, 10) >>> print(mapAcf) [ 0.20005 0.12003 0.07202 0.04322 0.02593 0.01556 0.00934 0.0056 0.00336 0.00202] >>> sqAcf = SquaredDifference(mapAcf, trAcf) >>> print(sqAcf) 0.0773799594638