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-rw-r--r--tests/unit_tests/test001_LinearRegression/scilabcode/mainfunction.sci112
1 files changed, 56 insertions, 56 deletions
diff --git a/tests/unit_tests/test001_LinearRegression/scilabcode/mainfunction.sci b/tests/unit_tests/test001_LinearRegression/scilabcode/mainfunction.sci
index c6e09a0c..e46f9c96 100644
--- a/tests/unit_tests/test001_LinearRegression/scilabcode/mainfunction.sci
+++ b/tests/unit_tests/test001_LinearRegression/scilabcode/mainfunction.sci
@@ -1,56 +1,56 @@
-//SCI2C: DEFAULT_PRECISION= FLOAT
-
-function mainfunction()
-
-// Knowing that
-// (1) P * (V^gamma) = C
-// Where
-// P = Pressure
-// V = Volume
-// gamma,C = constants depending on the particular gas used.
-// (2) log10(P) = log10(C) - gamma*log10(V)
-// (3) x = log10(V)
-// (4) y = log10(P)
-// than (2) becomes:
-// y = a + b*x;
-// Where
-// a = log10(C)
-// b = -gamma
-// Then thanks to this transformation it is possible to perform
-// a linear regression to estimate gamma and C!
-
-Volume = [54.3 61.8 72.4 88.7 118.6 194.0];
-Pressure = [61.2 49.5 37.6 28.4 19.2 10.1];
-x = log10(Volume);
-y = log10(Pressure);
-
-a = (sum(y)*sum(x.^2)-sum(x)*sum(x.*y))./(length(x)*sum(x.^2)-sum(x).*sum(x));
-b = (length(x)*sum(x.*y)-sum(x)*sum(y))./(length(x)*sum(x.^2)-sum(x).*sum(x));
-
-// Other way to compute a and b
-beq = sum((x-mean(x)).*(y-mean(y)))./sum((x-mean(x)).^2);
-aeq = mean(y)-mean(x)*beq;
-
-C = 10 .^a;
-gamma = -b;
-
-disp('C')
-disp(C)
-
-disp('gamma');
-disp(gamma);
-
-disp('a');
-disp(a)
-disp('aeq');
-disp(aeq)
-
-disp('b');
-disp(b)
-disp('beq');
-disp(beq)
-
- //plot(Volume,Pressure);
- //plot(Volume,(C ./(Volume.^gamma)),'r')
-endfunction
-
+//SCI2C: DEFAULT_PRECISION= FLOAT
+
+function mainfunction()
+
+// Knowing that
+// (1) P * (V^gamma) = C
+// Where
+// P = Pressure
+// V = Volume
+// gamma,C = constants depending on the particular gas used.
+// (2) log10(P) = log10(C) - gamma*log10(V)
+// (3) x = log10(V)
+// (4) y = log10(P)
+// than (2) becomes:
+// y = a + b*x;
+// Where
+// a = log10(C)
+// b = -gamma
+// Then thanks to this transformation it is possible to perform
+// a linear regression to estimate gamma and C!
+
+Volume = [54.3 61.8 72.4 88.7 118.6 194.0];
+Pressure = [61.2 49.5 37.6 28.4 19.2 10.1];
+x = log10(Volume);
+y = log10(Pressure);
+
+a = (sum(y)*sum(x.^2)-sum(x)*sum(x.*y))./(length(x)*sum(x.^2)-sum(x).*sum(x));
+b = (length(x)*sum(x.*y)-sum(x)*sum(y))./(length(x)*sum(x.^2)-sum(x).*sum(x));
+
+// Other way to compute a and b
+beq = sum((x-mean(x)).*(y-mean(y)))./sum((x-mean(x)).^2);
+aeq = mean(y)-mean(x)*beq;
+
+C = 10 .^a;
+gamma = -b;
+
+disp('C')
+disp(C)
+
+disp('gamma');
+disp(gamma);
+
+disp('a');
+disp(a)
+disp('aeq');
+disp(aeq)
+
+disp('b');
+disp(b)
+disp('beq');
+disp(beq)
+
+ //plot(Volume,Pressure);
+ //plot(Volume,(C ./(Volume.^gamma)),'r')
+endfunction
+