Title: | Helper functions for repgames and dyngames |
---|---|

Description: | Helper functions needed by my package repgames and dyngames |

Authors: | Sebastian Kranz |

Maintainer: | Sebastian Kranz <[email protected]> |

License: | GPL (>= 2) |

Version: | 0.1 |

Built: | 2024-09-15 04:15:30 UTC |

Source: | https://github.com/skranz/skUtils |

- Add a vector v to each row of m
- APPROXEQ Are a and b approximately equal (to within a specified tolerance)? p = approxeq(a, b, thresh) 'tol' defaults to 1e-3.
- Assigns all columns of df into variables with the same name in environment env
- Calculate numerically the expected value given a cdf
- Some functions that are useful for coding Looks through all loaded functions and searches for global variables that are used within the functions this is a common source for errors
- Clones an environment and its children
- Generates a matrix in which all cols are equal to col
- Computes quickly the maxima of each column of a matrix
- Computes quickly the minima of each column of a matrix
- Copies an environment
- Helper function to discretize a continous distribution. F.vec is a finite vector containing the value of the cdf at M different points. The function generates an M dimension vector of probabilities summing up to 1 that discretize the distribution
- Finds position where the function f becomes zero First tries find.root and if this fails tries optimize
- Gives the corresponding rows for a permutated grid.matrix given a permutation x.perm of the elements of the original list x
- Transforms a grid in long format into a matrix
- List all functions
- List all variables
- Some functions that are useful for manipulating or creating matrices and data.frames and working with lists of vectors, lists of lists or lists of matrices Transforms a matrix into grid in long format
- Some functions that are useful for lists and environments in particular generating, transforming, copying and assigning values Creates a list that is named by the names of its arguments
- Paste together columns of a matrix or data.frame
- Paste together rows of a matrix or data.frame
- Plot several lines
- rbinds a list of matrices, a list of lists, or a list of vectors into a data.frame (or matrix) each column is a list Assume that all columns in the sublists are in the same order
- Generates a matrix in which all rows are equal to row
- Computes quickly the minima of each row of a matrix
- Computes quickly the minima of each row of a matrix
- Need to check what it does
- My wrapper to the lattice function levelplot. Allows for some own color schemes The parameter focus specifies at which z range stronger color changes shall appear
- A wrapper for optimization. Allows to specify which variables shall be free Has the same syntax for one and multidimensional optmization Uses optim, omptimize or a grid search
- Calculates the 2dimensional paretofrontier of the points val1 and val2 The function returns the indices of the points that lie on the Pareto Frontier ordered by val1 and val2.
- Computes quickly the index of the largest element of each column of a matrix
- Computes quickly the index of the smallest element of each column of a matrix
- Computes quickly the index of the largest element of each row of a matrix
- Computes quickly the index of the smallest element of each row of a matrix

Add a vector v to each row of m

`add.rowvec(m, v)`

`add.rowvec(m, v)`

APPROXEQ Are a and b approximately equal (to within a specified tolerance)? p = approxeq(a, b, thresh) 'tol' defaults to 1e-3.

`approxeq(a, b, tol = 0.001)`

`approxeq(a, b, tol = 0.001)`

Assigns all columns of df into variables with the same name in environment env

`assign.cols(df, dest = sys.frame(sys.parent(1)))`

`assign.cols(df, dest = sys.frame(sys.parent(1)))`

Calculate numerically the expected value given a cdf

`calc.mean.from.F.fun(F.fun, x.min = 0, x.max = Inf, abs.tol = 10^(-10), x.seq = NULL, use.num.integrate = TRUE, ...)`

`calc.mean.from.F.fun(F.fun, x.min = 0, x.max = Inf, abs.tol = 10^(-10), x.seq = NULL, use.num.integrate = TRUE, ...)`

Some functions that are useful for coding Looks through all loaded functions and searches for global variables that are used within the functions this is a common source for errors

`check.global.vars()`

`check.global.vars()`

Clones an environment and its children

`clone.environment(env, made.clones = as.environment(list(org = list(), copy = list())), clone.parents = TRUE, clone.global = FALSE, exclude = NULL, clone.children = TRUE)`

`clone.environment(env, made.clones = as.environment(list(org = list(), copy = list())), clone.parents = TRUE, clone.global = FALSE, exclude = NULL, clone.children = TRUE)`

Generates a matrix in which all cols are equal to col

`col.matrix(row = NULL, col, ncol = length(row), dim = 2)`

`col.matrix(row = NULL, col, ncol = length(row), dim = 2)`

Computes quickly the maxima of each column of a matrix

`colMaxs(mat)`

`colMaxs(mat)`

Computes quickly the minima of each column of a matrix

`colMins(mat)`

`colMins(mat)`

Copies an environment

`copy.env(dest = sys.frame(sys.parent(1)), source = sys.frame(sys.parent(1)), names = NULL, name.change = NULL, exclude = NULL)`

`copy.env(dest = sys.frame(sys.parent(1)), source = sys.frame(sys.parent(1)), names = NULL, name.change = NULL, exclude = NULL)`

Helper function to discretize a continous distribution. F.vec is a finite vector containing the value of the cdf at M different points. The function generates an M dimension vector of probabilities summing up to 1 that discretize the distribution

`discretize.given.F.vec(F.vec)`

`discretize.given.F.vec(F.vec)`

Finds position where the function f becomes zero First tries find.root and if this fails tries optimize

`findzero(f, lower, upper, tol = .Machine$double.eps * 10, result.tol = tol, try.uniroot = TRUE, ...)`

`findzero(f, lower, upper, tol = .Machine$double.eps * 10, result.tol = tol, try.uniroot = TRUE, ...)`

Gives the corresponding rows for a permutated grid.matrix given a permutation x.perm of the elements of the original list x

`grid.matrix.permutation(x, perm.col)`

`grid.matrix.permutation(x, perm.col)`

Transforms a grid in long format into a matrix

`grid.to.matrix(grid, nrow = length(unique(grid[, 1])), ncol = length(unique(grid[, 2])), val.col = 3)`

`grid.to.matrix(grid, nrow = length(unique(grid[, 1])), ncol = length(unique(grid[, 2])), val.col = 3)`

List all functions

`ls.funs(env = sys.frame(-1))`

`ls.funs(env = sys.frame(-1))`

List all variables

`ls.vars(env = sys.frame(-1))`

`ls.vars(env = sys.frame(-1))`

Some functions that are useful for manipulating or creating matrices and data.frames and working with lists of vectors, lists of lists or lists of matrices Transforms a matrix into grid in long format

`matrix.to.grid(mat, x = 1:NROW(mat), y = 1:NCOL(mat), x.name = "x", y.name = "y")`

`matrix.to.grid(mat, x = 1:NROW(mat), y = 1:NCOL(mat), x.name = "x", y.name = "y")`

Some functions that are useful for lists and environments in particular generating, transforming, copying and assigning values Creates a list that is named by the names of its arguments

`named.list(...)`

`named.list(...)`

Paste together columns of a matrix or data.frame

`paste.matrix.cols(mat, cols = 1:NCOL(mat), ...)`

`paste.matrix.cols(mat, cols = 1:NCOL(mat), ...)`

Paste together rows of a matrix or data.frame

`paste.matrix.rows(mat, rows = 1:NROW(mat), ...)`

`paste.matrix.rows(mat, rows = 1:NROW(mat), ...)`

Plot several lines

`## S3 method for class 'multi.lines' plot(mat = NULL, xvar, yvar, ynames = yvar, col = NULL, ylim = NULL, xlab = xvar, ylab = "", legend.pos = NULL, legend.title = NULL, add = FALSE, lwd = 1, ...)`

`## S3 method for class 'multi.lines' plot(mat = NULL, xvar, yvar, ynames = yvar, col = NULL, ylim = NULL, xlab = xvar, ylab = "", legend.pos = NULL, legend.title = NULL, add = FALSE, lwd = 1, ...)`

rbinds a list of matrices, a list of lists, or a list of vectors into a data.frame (or matrix) each column is a list Assume that all columns in the sublists are in the same order

`rbind.list(li, cols = NULL, check.common.cols = FALSE)`

`rbind.list(li, cols = NULL, check.common.cols = FALSE)`

Generates a matrix in which all rows are equal to row

`row.matrix(row, col, nrow = length(col), dim = 1)`

`row.matrix(row, col, nrow = length(col), dim = 1)`

Computes quickly the minima of each row of a matrix

`rowMaxs(mat)`

`rowMaxs(mat)`

Computes quickly the minima of each row of a matrix

`rowMins(mat)`

`rowMins(mat)`

Need to check what it does

`set.default(env, name, x, overwrite.null = TRUE, inherits = TRUE)`

`set.default(env, name, x, overwrite.null = TRUE, inherits = TRUE)`

My wrapper to the lattice function levelplot. Allows for some own color schemes The parameter focus specifies at which z range stronger color changes shall appear

`sk.levelplot(x = NULL, y = NULL, z = NULL, xnames = NULL, ynames = NULL, grid.xyz = NULL, col.scheme = "darkredgreen", na.col = NULL, at = NULL, at.scheme = "interval", focus = 0, cuts = 15, col.regions = NULL, xlab = NULL, ylab = NULL, panel = panel.levelplot, zlim = NULL, reverse.colors = FALSE, ...)`

`sk.levelplot(x = NULL, y = NULL, z = NULL, xnames = NULL, ynames = NULL, grid.xyz = NULL, col.scheme = "darkredgreen", na.col = NULL, at = NULL, at.scheme = "interval", focus = 0, cuts = 15, col.regions = NULL, xlab = NULL, ylab = NULL, panel = panel.levelplot, zlim = NULL, reverse.colors = FALSE, ...)`

A wrapper for optimization. Allows to specify which variables shall be free Has the same syntax for one and multidimensional optmization Uses optim, omptimize or a grid search

`sk.optim(par, f, lower = NULL, upper = NULL, free.par = 1:NROW(par), method = "default", num.grid.steps = NULL, maximize = TRUE, f.can.take.matrix = FALSE, tol = .Machine$double.eps^0.25, ...)`

`sk.optim(par, f, lower = NULL, upper = NULL, free.par = 1:NROW(par), method = "default", num.grid.steps = NULL, maximize = TRUE, f.can.take.matrix = FALSE, tol = .Machine$double.eps^0.25, ...)`

Calculates the 2dimensional paretofrontier of the points val1 and val2 The function returns the indices of the points that lie on the Pareto Frontier ordered by val1 and val2.

`sk.pareto.frontier(val1, val2, tol = 0, ord = NULL)`

`sk.pareto.frontier(val1, val2, tol = 0, ord = NULL)`

Computes quickly the index of the largest element of each column of a matrix

`which.colMaxs(mat)`

`which.colMaxs(mat)`

Computes quickly the index of the smallest element of each column of a matrix

`which.colMins(mat)`

`which.colMins(mat)`

Computes quickly the index of the largest element of each row of a matrix

`which.rowMaxs(mat)`

`which.rowMaxs(mat)`

Computes quickly the index of the smallest element of each row of a matrix

`which.rowMins(mat)`

`which.rowMins(mat)`