symnum {stats} | R Documentation |

Symbolically encode a given numeric or logical vector or array. Particularly useful for visualization of structured matrices, e.g., correlation, sparse, or logical ones.

```
symnum(x, cutpoints = c(0.3, 0.6, 0.8, 0.9, 0.95),
symbols = if(numeric.x) c(" ", ".", ",", "+", "*", "B")
else c(".", "|"),
legend = length(symbols) >= 3,
na = "?", eps = 1e-5, numeric.x = is.numeric(x),
corr = missing(cutpoints) && numeric.x,
show.max = if(corr) "1", show.min = NULL,
abbr.colnames = has.colnames,
lower.triangular = corr && is.numeric(x) && is.matrix(x),
diag.lower.tri = corr && !is.null(show.max))
```

`x` |
numeric or logical vector or array. |

`cutpoints` |
numeric vector whose values |

`symbols` |
character vector, one shorter than (the
When |

`legend` |
logical indicating if a |

`na` |
character or logical. How |

`eps` |
absolute precision to be used at left and right boundary. |

`numeric.x` |
logical indicating if |

`corr` |
logical. If |

`show.max` |
if |

`show.min` |
if |

`abbr.colnames` |
logical, integer or |

`lower.triangular` |
logical. If |

`diag.lower.tri` |
logical. If |

An atomic character object of class `noquote`

and the same
dimensions as `x`

.

If `legend`

is `TRUE`

(as by default when there are more
than two classes), the result has an attribute `"legend"`

containing a legend of the returned character codes, in the form

`c_1 s_1 c_2 s_2 \dots s_n c_{n+1}`

where `c_j`

` = cutpoints[j]`

and
`s_j`

` = symbols[j]`

.

The optional (mostly logical) arguments all try to use smart defaults. Specifying them explicitly may lead to considerably improved output in many cases.

Martin Maechler maechler@stat.math.ethz.ch

```
ii <- setNames(0:8, 0:8)
symnum(ii, cutpoints = 2*(0:4), symbols = c(".", "-", "+", "$"))
symnum(ii, cutpoints = 2*(0:4), symbols = c(".", "-", "+", "$"), show.max = TRUE)
symnum(1:12 %% 3 == 0) # --> "|" = TRUE, "." = FALSE for logical
## Pascal's Triangle modulo 2 -- odd and even numbers:
N <- 38
pascal <- t(sapply(0:N, function(n) round(choose(n, 0:N - (N-n)%/%2))))
rownames(pascal) <- rep("", 1+N) # <-- to improve "graphic"
symnum(pascal %% 2, symbols = c(" ", "A"), numeric.x = FALSE)
##-- Symbolic correlation matrices:
symnum(cor(attitude), diag.lower.tri = FALSE)
symnum(cor(attitude), abbr.colnames = NULL)
symnum(cor(attitude), abbr.colnames = FALSE)
symnum(cor(attitude), abbr.colnames = 2)
symnum(cor(rbind(1, rnorm(25), rnorm(25)^2)))
symnum(cor(matrix(rexp(30, 1), 5, 18))) # <<-- PATTERN ! --
symnum(cm1 <- cor(matrix(rnorm(90) , 5, 18))) # < White Noise SMALL n
symnum(cm1, diag.lower.tri = FALSE)
symnum(cm2 <- cor(matrix(rnorm(900), 50, 18))) # < White Noise "BIG" n
symnum(cm2, lower.triangular = FALSE)
## NA's:
Cm <- cor(matrix(rnorm(60), 10, 6)); Cm[c(3,6), 2] <- NA
symnum(Cm, show.max = NULL)
## Graphical P-values (aka "significance stars"):
pval <- rev(sort(c(outer(1:6, 10^-(1:3)))))
symp <- symnum(pval, corr = FALSE,
cutpoints = c(0, .001,.01,.05, .1, 1),
symbols = c("***","**","*","."," "))
noquote(cbind(P.val = format(pval), Signif = symp))
```

[Package *stats* version 4.3.0 Index]