Description Usage Arguments Value Examples
Generate distance measures to ascertain a mean distance measure between codes.
1 2 3 4 | cm_distance(dataframe, time.var = NULL, parallel = FALSE,
code.var = "code", causal = FALSE, start.var = "start",
end.var = "end", mean.digits = 2, sd.digits = 2,
stan.digits = 2)
|
dataframe |
A data frame from the cm_x2long family
( |
time.var |
An optional variable to split the dataframe by (if you have data that is by various times this must be supplied). |
parallel |
logical. If TRUE runs the cm_distance on multiple cores. This is effective with larger data sets but may actually be slower with smaller data sets. |
code.var |
The name of the code variable column. Defaults to "codes" as out putted by x2long family. |
causal |
logical. If TRUE measures the distance between x and y given that x must proceed y. |
start.var |
The name of the start variable column. Defaults to "start" as out putted by x2long family. |
end.var |
The name of the end variable column. Defaults to "end" as out putted by x2long family. |
mean.digits |
The number of digits to be displayed in the mean matrix. |
sd.digits |
The number of digits to be displayed in the sd (standard deviation) matrix. |
stan.digits |
The number of digits to use in the standardized mean difference matrix. |
An object of the class cm.dist. This is a list of n lists with the following components per each list (time.var):
mean |
A distance matrix of average distances between codes |
sd |
A matrix of standard deviations of distances between codes |
n |
A matrix of counts of distances between codes |
combined |
A matrix of combined mean, sd and n of distances between codes |
standardized |
A matrix of standardized values of distances between codes. The closer a value is to zero the closer two codes relate. |
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 | foo <- list(
AA = qcv(terms="02:03, 05"),
BB = qcv(terms="1:2, 3:10"),
CC = qcv(terms="1:9, 100:150")
)
foo2 <- list(
AA = qcv(terms="40"),
BB = qcv(terms="50:90"),
CC = qcv(terms="60:90, 100:120, 150"),
DD = qcv(terms="")
)
(dat <- cm_range2long(foo, foo2, v.name = "time"))
(out <- cm_distance(dat, time.var = "time", causal=TRUE))
names(out)
names(out$foo2)
out$foo2
#========================================
x <- list(
transcript_time_span = qcv(00:00 - 1:12:00),
A = qcv(terms = "2.40:3.00, 6.32:7.00, 9.00,
10.00:11.00, 59.56"),
B = qcv(terms = "3.01:3.02, 5.01, 19.00, 1.12.00:1.19.01"),
C = qcv(terms = "2.40:3.00, 5.01, 6.32:7.00, 9.00, 17.01")
)
(dat <- cm_time2long(x))
gantt_wrap(dat, "code", border.color = "black", border.size = 5,
sig.dig.line.freq = -2)
(a <- cm_distance(dat))
names(a)
names(a$dat)
a$dat
|
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