Java Code Examples for java.lang.Math#sin()

The following examples show how to use java.lang.Math#sin() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.

Example 1

Source File: Transformation.java From GiantTrees with GNU General Public License v3.0

6 votes

public Transformation rotaxisz(double delta, double rho) {
	// local rotation away from the local z-axis 
	// about an angle delta using an axis given by rho 
	// - used for splitting and random rotations
	delta = delta*Math.PI/180;
	rho = rho*Math.PI/180;
	
	double a = Math.cos(rho);
	double b = Math.sin(rho);
	double si = Math.sin(delta);
	double co = Math.cos(delta);
	
	Matrix rm = new Matrix((co+a*a*(1-co)),(b*a*(1-co)),(b*si),
			(a*b*(1-co)),(co+b*b*(1-co)),(-a*si),
			(-b*si),(a*si),(co));
	return new Transformation(matrix.prod(rm),vector);
}

Example 2

Source File: Exp.java From Llunatic with GNU General Public License v3.0

6 votes

public Object exp(Object param)
	throws ParseException
{
	if (param instanceof Complex)
	{
	  	Complex z = (Complex) param;
	  	double x = z.re();
	  	double y = z.im();
	  	double mod = Math.exp(x);
		return new Complex(mod*Math.cos(y),mod*Math.sin(y));
	}
	else if (param instanceof Number) 
	{
		return new Double(Math.exp(((Number)param).doubleValue()));
	}

	throw new ParseException("Invalid parameter type");
}

Example 3

Source File: Transformation.java From GiantTrees with GNU General Public License v3.0

6 votes

public Transformation rotaxis(double angle,Vector axis) {
	// rotation about an axis
	angle = angle*Math.PI/180;
	axis=axis.normalize();
	double a = axis.getX();
	double b = axis.getY();
	double c = axis.getZ();
	double si = Math.sin(angle);
	double co = Math.cos(angle);
	
	Matrix rm = new Matrix(
			(co+a*a*(1-co)),(-c*si+b*a*(1-co)),(b*si+c*a*(1-co)),
			(c*si+a*b*(1-co)),(co+b*b*(1-co)),(-a*si+c*b*(1-co)),
			(-b*si+a*c*(1-co)),(a*si+b*c*(1-co)),(co+c*c*(1-co)));
	return new Transformation(rm.prod(matrix),vector);
}

Example 4

Source File: Est_evol.java From KEEL with GNU General Public License v3.0

5 votes

/** Generates a normal value with hope 0 and tipical deviation "desv */
public double ValorNormal(double desv) {
    double u1, u2;

    /* we generate 2 uniform values [0,1] */
    u1 = Randomize.Rand();
    u2 = Randomize.Rand();

    /* we calcules a normal value with the uniform values */
    return (desv * Math.sqrt( -2.0 * Math.log(u1)) * Math.sin(2.0 * PI * u2));
}

Example 5

Source File: Transformation.java From GiantTrees with GNU General Public License v3.0

5 votes

public Transformation rotz(double angle) {
	// local rotation about z-axis
	angle = angle*Math.PI/180;
	Matrix rm = new Matrix(Math.cos(angle),-Math.sin(angle),0,
			Math.sin(angle),Math.cos(angle),0,
			0,0,1);
	return new Transformation(matrix.prod(rm),vector);
}

Example 6

Source File: Sine.java From Llunatic with GNU General Public License v3.0

5 votes

public Object sin(Object param)
	throws ParseException
{
	if (param instanceof Complex) {
		return ((Complex)param).sin();
	}
	else if (param instanceof Number) {
		return new Double(Math.sin(((Number)param).doubleValue()));
	}
	
	throw new ParseException("Invalid parameter type");
}

Example 7

Source File: Est_mu_landa.java From KEEL with GNU General Public License v3.0

5 votes

/** Generates a normal value with hope 0 and tipical deviation "desv */
private double ValorNormal(double desv) {
  double u1, u2;

  /* we generate 2 uniform values [0,1] */
  u1 = Randomize.Rand();
  u2 = Randomize.Rand();

  /* we calcules a normal value with the uniform values */
  return (desv * Math.sqrt( -2 * Math.log(u1)) * Math.sin(2 * PI * u2));
}

Example 8

Source File: Est_evol.java From KEEL with GNU General Public License v3.0

5 votes

/** Generates a normal value with hope 0 and tipical deviation "desv */
public double ValorNormal(double desv) {
  double u1, u2;

  /* we generate 2 uniform values [0,1] */
  u1 = Randomize.Rand();
  u2 = Randomize.Rand();

  /* we calcules a normal value with the uniform values */
  return (desv * Math.sqrt( -2 * Math.log(u1)) * Math.sin(2 * PI * u2));
}

Example 9

Source File: Est_evol.java From KEEL with GNU General Public License v3.0

5 votes

/** Generates a normal value with hope 0 and tipical deviation "desv */
public double ValorNormal(double desv) {
    double u1, u2;

    /* we generate 2 uniform values [0,1] */
    u1 = Randomize.Rand();
    u2 = Randomize.Rand();

    /* we calcules a normal value with the uniform values */
    return (desv * Math.sqrt( -2.0 * Math.log(u1)) * Math.sin(2.0 * Math.PI * u2));
}

Example 10

Source File: AG_Tun.java From KEEL with GNU General Public License v3.0

5 votes

/** Generates a normal value with hope 0 and tipical deviation "desv */
private double ValorNormal(double desv) {
  double u1, u2;

  /* we generate 2 uniform values [0,1] */
  u1 = Randomize.Rand();
  u2 = Randomize.Rand();

  /* we calcules a normal value with the uniform values */
  return (desv * Math.sqrt( -2 * Math.log(u1)) * Math.sin(2 * PI * u2));
}

Example 11

Source File: Est_evol_M2TSK.java From KEEL with GNU General Public License v3.0

5 votes

/** Generates a normal value with hope 0 and tipical deviation "desv */
private double ValorNormal (double desv) {
	double u1, u2;

	/* we generate 2 uniform values [0,1] */
	u1=Randomize.Rand ();
	u2=Randomize.Rand ();

	/* we calcules a normal value with the uniform values */
	return (desv * Math.sqrt (-2.0 * Math.log(u1)) * Math.sin (2.0*PI*u2));
}

Example 12

Source File: Est_evol.java From KEEL with GNU General Public License v3.0

5 votes

/** Generates a normal value with hope 0 and tipical deviation "desv */
private double ValorNormal (double desv) {
	double u1, u2;

	/* we generate 2 uniform values [0,1] */
	u1=Randomize.Rand ();
	u2=Randomize.Rand ();

	/* we calcules a normal value with the uniform values */
	return (desv * Math.sqrt (-2 * Math.log(u1)) * Math.sin (2*Math.PI*u2));
}

Example 13

Source File: AG.java From KEEL with GNU General Public License v3.0

5 votes

/** Generates a normal value with hope 0 and tipical deviation "desv */
private double ValorNormal (double desv) {
	double u1, u2;

	/* we generate 2 uniform values [0,1] */
	u1 = Randomize.Rand ();
	u2 = Randomize.Rand ();

	/* we calcules a normal value with the uniform values */
	return (desv * Math.sqrt (-2 * Math.log(u1)) * Math.sin (2*Math.PI*u2));
}

Example 14

Source File: GA_Tun.java From KEEL with GNU General Public License v3.0

5 votes

/** Generates a normal value with hope 0 and tipical deviation "desv */
private double ValorNormal(double desv) {
    double u1, u2;

    /* we generate 2 uniform values [0,1] */
    u1 = Randomize.Rand();
    u2 = Randomize.Rand();

    /* we calcules a normal value with the uniform values */
    return (desv * Math.sqrt( -2 * Math.log(u1)) *
            Math.sin(2 * Math.PI * u2));
}

Example 15

Source File: Est_evol_M2TSK.java From KEEL with GNU General Public License v3.0

4 votes

private void Mutacion () {
	int n_hijo, i, j, nq, n1, n2;
	double z0, z1, x1, x2, si, co;

	for (n_hijo=0; n_hijo<Landa; n_hijo++) {
		/* Mutation of sigma */
		if (n_sigma==1)  /* if we use only a sigma, the sigma is adapted with Tau_1 */
			Hijos[n_hijo].Gene[tabla.n_variables] *= ValorNormal (Tau_1);
		else {
			z0 = ValorNormal (Tau_0);
			for (i=tabla.n_variables; i < tabla.n_variables + n_sigma; i++) {
				z1 = ValorNormal (Tau);
				Hijos[n_hijo].Gene[i] *= Math.exp (z1+z0);

				/* The standard desviation is Epsilon_sigma if it becomes 0 */
				if (Hijos[n_hijo].Gene[i]==0.0)
					Hijos[n_hijo].Gene[i] = Epsilon_sigma;
			}
		}

		/* Mutation of alfa */
		for (i = tabla.n_variables + n_sigma; i<tabla.n_variables + n_sigma + n_alfa; i++) {
			z0 = ValorNormal (Beta);
			Hijos[n_hijo].Gene[i] += z0;

			/* Si el valor mutado se sale del intervalo [-i,i], se proyecta
			circularmente el valor a dicho intervalo */
			if (Math.abs(Hijos[n_hijo].Gene[i])>i)  Hijos[n_hijo].Gene[i] -= 2.0 * PI * signo (Hijos[n_hijo].Gene[i]);
		}

		/* Mutation of x */

		/* we calculate the uncorrelated vector of mutations */
		for (i=0; i<tabla.n_variables; i++) {
			if (tabla.n_variables + i < tabla.n_variables + n_sigma)  Z[i] = ValorNormal (Hijos[n_hijo].Gene[tabla.n_variables+i]);
			else  Z[i] = ValorNormal (Hijos[n_hijo].Gene[tabla.n_variables+n_sigma-1]); /* if there aren't more tipical desviations we use the latest */
		}
				

		/* Correlation of the vector if we use the angles */
		if (n_alfa!=0) {
			nq = n_alfa;
			for (j=nl_alfa; j<=nm_alfa; ++j) {
				n1 = tabla.n_variables - j;
				n2 = tabla.n_variables;
				for (i=1; i<=j; ++i) {
					x1 = Z[n1-1];
					x2 = Z[n2-1];
					si = Math.sin(Hijos[n_hijo].Gene[tabla.n_variables + n_sigma + nq - 1]);
					co = Math.cos(Hijos[n_hijo].Gene[tabla.n_variables + n_sigma + nq - 1]);
					Z[n2-1] = x1*si + x2*co;
					Z[n1-1] = x1*co - x2*si;
					--n2;
					--nq;
				}
			}
		}

		/* Final mutation of X */
		for (i=0; i<tabla.n_variables; i++) {
			Hijos[n_hijo].Gene[i] += Z[i];

			if (Hijos[n_hijo].Gene[i] < (-1.0 * (PI/2.0)))  Hijos[n_hijo].Gene[i] = (-1.0 * (PI/2.0)) + 1E-10;
			if (Hijos[n_hijo].Gene[i] > (PI/2.0))  Hijos[n_hijo].Gene[i] = (PI/2.0) - 1E-10;
		}
	}
}

Example 16

Source File: Est_evol.java From KEEL with GNU General Public License v3.0

4 votes

private void Mutacion () {
	int n_hijo, i, j, nq, n1, n2;
	double z0, z1, x1, x2, si, co;

	for (n_hijo=0; n_hijo<Landa; n_hijo++) {
		/* Mutation of sigma */
		if (n_sigma==1)  /* if we use only a sigma, the sigma is adapted with Tau_1 */
			Hijos[n_hijo].Gene[tabla.n_variables] *= ValorNormal (Tau_1);
		else {
			z0 = ValorNormal (Tau_0);
			for (i=tabla.n_variables; i<tabla.n_variables + n_sigma; i++) {
				z1 = ValorNormal (Tau);
				Hijos[n_hijo].Gene[i] *= Math.exp (z1+z0);

				/* The standard desviation is Epsilon_sigma if it becomes 0 */
				if (Hijos[n_hijo].Gene[i]==0.0)
					Hijos[n_hijo].Gene[i] = Epsilon_sigma;
			}
		}  
      
		/* Mutation of alfa */
		for (i = tabla.n_variables + n_sigma; i<tabla.n_variables + n_sigma + n_alfa; i++) {
			z0 = ValorNormal (Beta);
			Hijos[n_hijo].Gene[i] += z0;

			/* Si el valor mutado se sale del intervalo [-i,i], se proyecta
			circularmente el valor a dicho intervalo */
			if (Math.abs(Hijos[n_hijo].Gene[i])>i)
				Hijos[n_hijo].Gene[i] -= 2 *i * signo (Hijos[n_hijo].Gene[i]);
		}

		/* Mutation of x */
  
		/* we calculate the uncorrelated vector of mutations */
		for (i=0; i<tabla.n_variables; i++)
			if (tabla.n_variables + i < tabla.n_variables + n_sigma)
				Z[i] = ValorNormal (Hijos[n_hijo].Gene[tabla.n_variables+i]);
			else /* if there aren't more tipical desviations we use the latest */
				Z[i] = ValorNormal (Hijos[n_hijo].Gene[tabla.n_variables+n_sigma-1]);      
   
		/* Correlation of the vector if we use the angles */  
		if (n_alfa!=0) {
			nq = n_alfa;
			for (j=nl_alfa; j<=nm_alfa; ++j) {
				n1 = tabla.n_variables - j;
				n2 = tabla.n_variables;
				for (i=1; i<=j; ++i) {
					x1 = Z[n1-1];
					x2 = Z[n2-1];
					si = Math.sin(Hijos[n_hijo].Gene[tabla.n_variables + n_sigma + nq - 1]);
					co = Math.cos(Hijos[n_hijo].Gene[tabla.n_variables + n_sigma + nq - 1]);
					Z[n2-1] = x1*si + x2*co;
					Z[n1-1] = x1*co - x2*si;
					--n2;
					--nq;
				}
			} 
		}
   
		/* Final mutation of X */ 
		for (i=0; i<tabla.n_variables; i++) {
			Hijos[n_hijo].Gene[i] += Z[i];	

			if (Hijos[n_hijo].Gene[i] < -(Math.PI/2.0))
				Hijos[n_hijo].Gene[i] = -(Math.PI/2.0) + 1E-10;
			if (Hijos[n_hijo].Gene[i] > (Math.PI/2.0))
				Hijos[n_hijo].Gene[i] = (Math.PI/2.0) - 1E-10;
		}
	}
}

Example 17

Source File: Est_mu_landa.java From KEEL with GNU General Public License v3.0

4 votes

private void Mutacion() {
  int n_hijo, i, j, nq, n1, n2;
  double z0, z1, x1, x2, si, co;

  for (n_hijo = 0; n_hijo < Landa; n_hijo++) {
    /* Mutation of sigma */
    if (n_sigma == 1)
        /* if we use only a sigma, the sigma is adapted with Tau_1 */
         {
      Hijos[n_hijo].Gene[tabla.n_variables] *= ValorNormal(Tau_1);
    }
    else {
      z0 = ValorNormal(Tau_0);
      for (i = tabla.n_variables; i < tabla.n_variables + n_sigma; i++) {
        z1 = ValorNormal(Tau);
        Hijos[n_hijo].Gene[i] *= Math.exp(z1 + z0);

        /* The standard desviation is Epsilon_sigma if it becomes 0 */
        if (Hijos[n_hijo].Gene[i] == 0.0) {
          Hijos[n_hijo].Gene[i] = Epsilon_sigma;
        }
      }
    }

    /* Mutation of alfa */
    for (i = tabla.n_variables + n_sigma;
         i < tabla.n_variables + n_sigma + n_alfa; i++) {
      z0 = ValorNormal(Beta);
      Hijos[n_hijo].Gene[i] += z0;

      /* Si el valor mutado se sale del intervalo [-i,i], se proyecta
           circularmente el valor a dicho intervalo */
      if (Math.abs(Hijos[n_hijo].Gene[i]) > i) {
        Hijos[n_hijo].Gene[i] -= 2 * PI * signo(Hijos[n_hijo].Gene[i]);
      }
    }

    /* Mutation of x */

    /* we calculate the uncorrelated vector of mutations */
    for (i = 0; i < tabla.n_variables; i++) {
      if (tabla.n_variables + i < tabla.n_variables + n_sigma) {
        Z[i] = ValorNormal(Hijos[n_hijo].Gene[tabla.n_variables + i]);
      }
      else
      /* if there aren't more tipical desviations we use the latest */
      {
        Z[i] = ValorNormal(Hijos[n_hijo].Gene[tabla.n_variables + n_sigma - 1]);
      }
    }

    /* Correlation of the vector if we use the angles */
    if (n_alfa != 0) {
      nq = n_alfa;
      for (j = nl_alfa; j <= nm_alfa; ++j) {
        n1 = tabla.n_variables - j;
        n2 = tabla.n_variables;
        for (i = 1; i <= j; ++i) {
          x1 = Z[n1 - 1];
          x2 = Z[n2 - 1];
          si = Math.sin(Hijos[n_hijo].Gene[tabla.n_variables + n_sigma + nq -
                        1]);
          co = Math.cos(Hijos[n_hijo].Gene[tabla.n_variables + n_sigma + nq -
                        1]);
          Z[n2 - 1] = x1 * si + x2 * co;
          Z[n1 - 1] = x1 * co - x2 * si;
          --n2;
          --nq;
        }
      }
    }

    /* Final mutation of X */
    for (i = 0; i < tabla.n_variables; i++) {
      Hijos[n_hijo].Gene[i] += Z[i];

      if (Hijos[n_hijo].Gene[i] < - (PI / 2.0)) {
        Hijos[n_hijo].Gene[i] = - (PI / 2.0) + 1E-10;
      }
      if (Hijos[n_hijo].Gene[i] > (PI / 2.0)) {
        Hijos[n_hijo].Gene[i] = (PI / 2.0) - 1E-10;
      }
    }
  }
}

Example 18

Source File: ULight.java From ure with MIT License

4 votes

float intensityFlickerCompulse(int time) {
    float i = (float)Math.sin((double)time*0.05) + (float)Math.sin((double)time*0.03);
    return i;
}

Example 19

Source File: ULight.java From ure with MIT License

4 votes

float intensityFlickerPulse(int time) {
    float i = (float)Math.sin((double)time * 0.05);
    return i;
}

Example 20

Source File: SystemFunctions.java From incubator-retired-mrql with Apache License 2.0

votes

public static MR_double sin ( MR_double x ) { return new MR_double(Math.sin(x.get())); }