Description Usage Arguments Value Examples

View source: R/computeGradientField.R

Computes the multi-objective gradients for a matrix of `points`

.

1 2 3 | ```
computeGradientField(points, fn1, fn2, fn3 = NULL, scale.step = 0.5,
prec.grad = 1e-06, prec.norm = 1e-06, prec.angle = 1e-04,
parallelize = FALSE, lower, upper)
``` |

`points` |
[ |

`fn1` |
[ |

`fn2` |
[ |

`fn3` |
[ |

`scale.step` |
[ |

`prec.grad` |
[ |

`prec.norm` |
[ |

`prec.angle` |
[ |

`parallelize` |
[ |

`lower` |
[ |

`upper` |
[ |

[`matrix`

]

Returns `matrix`

of multi-objective gradients. The i-th row of the matrix
contains the multi-objective gradient vector of the i-th observation (= row)
of the input matrix `points`

.

1 2 3 4 5 6 7 | ```
# Define two single-objective test problems:
fn1 = function(x) sum((x - c(0.2, 1))^2)
fn2 = function(x) sum(x)
# Create a grid of points, for which the gradients should be computed:
points = expand.grid(x1 = seq(0, 1, 0.01), x2 = seq(0, 1, 0.05))
gradient.field = computeGradientField(points, fn1, fn2)
``` |

kerschke/mogsa documentation built on Oct. 27, 2018, 12:13 a.m.

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