Description Usage Arguments Details Value Author(s) See Also Examples

Implements `which`

-like functionality for a `big.matrix`

,
with additional options for efficient comparisons (executed in C++);
also works for regular numeric matrices without the memory overhead.

1 | ```
mwhich(x, cols, vals, comps, op = 'AND')
``` |

`x` |
a |

`cols` |
a vector of column indices or names. |

`vals` |
a list (one component for each of |

`comps` |
a list of operators (one component for each of |

`op` |
the comparison operator for combining the results of the individual tests, either |

To improve performance and avoid the creation of massive temporary vectors in **R** when
doing comparisons, `mwhich()`

efficiently executes column-by-column comparisons
of values to the specified values or ranges, and then returns the row indices satisfying
the comparison specified by the `op`

operator. More advanced comparisons
are then possible (and memory-efficient) in **R** by doing set operations
(`union`

and `intersect`

, for example) on the
results of multiple `mwhich()`

calls.

Note that `NA`

is a valid argument in conjunction with `'eq'`

or
`'neq'`

, replacing traditional `is.na()`

calls.
And both `-Inf`

and `Inf`

can be used for one-sided inequalities.

If `mwhich()`

is used with a regular numeric **R** `matrix`

, we access the
data directly and thus incur no memory overhead. Interested developers might want
to look at our code for this case, which uses a handy pointer trick (accessor)
in C++.

a vector of row indices satisfying the criteria.

John W. Emerson <bigmemoryauthors@gmail.com>

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | ```
x <- as.big.matrix(matrix(1:30, 10, 3))
options(bigmemory.allow.dimnames=TRUE)
colnames(x) <- c("A", "B", "C")
x[,]
x[mwhich(x, 1:2, list(c(2,3), c(11,17)),
list(c('ge','le'), c('gt', 'lt')), 'OR'),]
x[mwhich(x, c("A","B"), list(c(2,3), c(11,17)),
list(c('ge','le'), c('gt', 'lt')), 'AND'),]
# These should produce the same answer with a regular matrix:
y <- matrix(1:30, 10, 3)
y[mwhich(y, 1:2, list(c(2,3), c(11,17)),
list(c('ge','le'), c('gt', 'lt')), 'OR'),]
y[mwhich(y, -3, list(c(2,3), c(11,17)),
list(c('ge','le'), c('gt', 'lt')), 'AND'),]
x[1,1] <- NA
mwhich(x, 1:2, NA, 'eq', 'OR')
mwhich(x, 1:2, NA, 'neq', 'AND')
# Column 1 equal to 4 and/or column 2 less than or equal to 16:
mwhich(x, 1:2, list(4, 16), list('eq', 'le'), 'OR')
mwhich(x, 1:2, list(4, 16), list('eq', 'le'), 'AND')
# Column 2 less than or equal to 15:
mwhich(x, 2, 15, 'le')
# No NAs in either column, and column 2 strictly less than 15:
mwhich(x, c(1:2,2), list(NA, NA, 15), list('neq', 'neq', 'lt'), 'AND')
x <- big.matrix(4, 2, init=1, type="double")
x[1,1] <- Inf
mwhich(x, 1, Inf, 'eq')
mwhich(x, 1, 1, 'gt')
mwhich(x, 1, 1, 'le')
``` |

bigmemory documentation built on May 21, 2017, 12:59 a.m.

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