[R] How to save output of multiple loops in a matrix
Jeff Newmiller
jdnewm|| @end|ng |rom dcn@d@v|@@c@@u@
Sun Mar 22 00:23:58 CET 2020
You really need to pick small problems and build solutions for them as
functions rather than copy-pasting code. Then you can build more
complicated solutions using those small solutions that can actually be
understood. I suspect that in a few days you would not understand your own
code because it is so complicated... but that is not inevitable... you
_can_ avoid creating write-only code.
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(tidyr)
damage_states <- c( 'Collapse', 'Extensive', 'Moderate', 'Slight')
# the following re-definition of d1 uses the stringsAsFactors parameter to
# prevent the character data from automatically being converted to
# factors, which is much better than having to use as.character later
# throughout your code.
d3 <- data.frame( Name = rep(c( 'Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)'
, 'Rojas(2010) - CR/LFM/DNO 2storey'
, 'Rojas(2010) - CR/LFM/DNO 3storey'
)
, each = 4
)
, Taxonomy = rep(c( 'CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//'
, 'CR/LFM/DNO/H:2/EDU2'
, 'CR/LFM/DNO/H:3'
)
, each = 4
)
, Damage_State = rep( damage_states, times = 3 )
, Y_vals = c( '0,6.49e-45,1.29e-29,3.35e-22,1.25e-17,1.8e-14,3.81e-12,2.35e-10,6.18e-09,8.78e-08,7.86e-07,4.92e-06,2.32e-05,8.76e-05,0.000274154,0.000736426,0.001740046,0.003688955,0.007130224,0.012730071,0.021221055,0.0333283,0.049687895,0.070771949,0.096832412,0.12787106'
, '5.02e-182,3.52e-10,8.81e-07,3.62e-05,0.000346166,0.001608096,0.004916965,0.01150426,0.022416772,0.038311015,0.059392175,0.085458446,0.115998702,0.150303282,0.187564259,0.226954808,0.267685669,0.309041053,0.35039806,0.391233913,0.431124831,0.469739614,0.506830242,0.542221151,0.575798268,0.607498531'
, '0,1.05e-10,4.75e-06,0.000479751,0.006156253,0.02983369,0.084284357,0.171401809,0.281721077,0.401071017,0.516782184,0.620508952,0.708327468,0.779597953,0.835636781,0.87866127,0.911104254,0.935237852,0.95300803,0.965993954,0.97543154,0.982263787,0.987197155,0.990753887,0.993316294,0.99516227'
, '4.61e-149,0.007234459,0.158482316,0.438164341,0.671470035,0.818341464,0.901312438,0.946339742,0.970531767,0.983584997,0.990707537,0.994650876,0.996869188,0.998137671,0.998874868,0.9993101,0.999570978,0.999729626,0.999827443,0.999888548,0.999927197,0.999951931,0.999967938,0.999978407,0.999985325,0.999989939'
, '0,4.91e-109,2.88e-47,3.32e-23,1.65e-11,1.78e-05,0.018162775,0.356628282,0.870224163,0.992779045,0.999855873,0.999998652,0.999999993,1,1,1,1,1,1,1,1,1,1,1,1,1'
, '0,1.21e-32,1.78e-05,0.645821244,0.999823159,0.999999999,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1'
, '0,0.077161367,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1'
, '0,0.996409276,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1'
, '0,1.29e-144,1.99e-71,1.16e-40,3.23e-24,1.59e-14,1.41e-08,6.42e-05,0.00971775,0.153727719,0.562404795,0.889217735,0.985915683,0.998997836,0.999955341,0.999998628,0.999999969,0.999999999,1,1,1,1,1,1,1,1'
, '0,2.12e-51,4.89e-14,0.001339285,0.559153268,0.995244295,0.999997786,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1'
, '0,3.22e-07,0.992496021,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1'
, '0,0.368907496,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1'
)
, stringsAsFactors = FALSE
)
# convert Damage_State to a factor using the desired sequence of levels
# This is useful when spread'ing the values to create columns in the
# desired order
d3$Damage_State = factor( d3$Damage_State, levels = damage_states )
d3long <- ( d3
%>% separate_rows( Y_vals, sep="," )
%>% mutate( Y_vals = as.numeric( Y_vals ) )
)
str( d3long )
#> 'data.frame': 312 obs. of 4 variables:
#> $ Name : chr "Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)" "Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)" "Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)" "Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)" ...
#> $ Taxonomy : chr "CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//" "CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//" "CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//" "CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//" ...
#> $ Damage_State: Factor w/ 4 levels "Collapse","Extensive",..: 1 1 1 1 1 1 1 1 1 1 ...
#> $ Y_vals : num 0.00 6.49e-45 1.29e-29 3.35e-22 1.25e-17 ...
# By putting the vector of weights into a data frame you can make the
# meaning of the vector D1L self-documenting
weights <- data.frame( Damage_State = c( "Initial", rev( damage_states ) )
, D2L = c( 0, 2, 10, 50, 100 )
)
weights
#> Damage_State D2L
#> 1 Initial 0
#> 2 Slight 2
#> 3 Moderate 10
#> 4 Extensive 50
#> 5 Collapse 100
# Group-by to get one row per combination of Taxonomy, Damage_State,
# and Name, then create a position index value for each Y_vals value
# then split the dataframe by combinations of Taxonomy and Name. Each
# small data frame in the `data` column has its own columns Damage_State,
# Index, and Y_vals.
d3long1 <- ( d3long
%>% group_by( Taxonomy, Damage_State, Name )
%>% mutate( Index = seq.int( n() ) )
%>% ungroup()
%>% nest( data = -c( Taxonomy, Name ) )
)
d3long1
#> # A tibble: 3 x 3
#> Name Taxonomy data
#> <chr> <chr> <list>
#> 1 Hancilar et. al (2014) - CR/L~ CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990~ <tibble [1~
#> 2 Rojas(2010) - CR/LFM/DNO 2sto~ CR/LFM/DNO/H:2/EDU2 <tibble [1~
#> 3 Rojas(2010) - CR/LFM/DNO 3sto~ CR/LFM/DNO/H:3 <tibble [1~
# function to convert a sub-dataframe into a matrix,
# built with tidyverse tools
DFL_to_matrix <- function( DFL, labelCol, indexCol, valueCol ) {
stopifnot( 3 == length( DFL ) )
( DFL
%>% spread( !!labelCol, !!valueCol )
%>% select( -!!indexCol )
%>% as.matrix
)
}
# same function built with base R
DFL_to_matrix2 <- function( DFL, labelCol, indexCol, valueCol ) {
as.matrix( data.frame( split( DFL[[ valueCol ]]
, DFL[[ labelCol ]]
)
)
)
}
# you can test small functions and later re-use them
#DFL_to_matrix2( d3long1$data[[1]], "Damage_State", "Index", "Y_vals" )
# Now convert the long data frames into matrices
# then use matrix multiplication to weight the damage
d3long2 <- ( d3long1
%>% mutate( mat = lapply( data
, DFL_to_matrix2
, labelCol = "Damage_State"
, indexCol = "Index"
, valueCol = "Y_vals"
)
, vc = lapply( mat
, function( m ) {
mr <- m[ , rev( seq.int( ncol( m ) ) ) ]
m1 <- cbind( matrix( 1, nrow = nrow( m ) )
, mr
)
m0 <- cbind( mr
, matrix( 0, nrow = nrow( m ) )
)
c( ( m1 - m0 ) %*% weights$D2L )
}
)
)
)
str( d3long2[ 1,] )
#> Classes 'tbl_df', 'tbl' and 'data.frame': 1 obs. of 5 variables:
#> $ Name : chr "Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)"
#> $ Taxonomy: chr "CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//"
#> $ data :List of 1
#> ..$ :Classes 'tbl_df', 'tbl' and 'data.frame': 104 obs. of 3 variables:
#> .. ..$ Damage_State: Factor w/ 4 levels "Collapse","Extensive",..: 1 1 1 1 1 1 1 1 1 1 ...
#> .. ..$ Y_vals : num 0.00 6.49e-45 1.29e-29 3.35e-22 1.25e-17 ...
#> .. ..$ Index : int 1 2 3 4 5 6 7 8 9 10 ...
#> $ mat :List of 1
#> ..$ : num [1:26, 1:4] 0.00 6.49e-45 1.29e-29 3.35e-22 1.25e-17 ...
#> .. ..- attr(*, "dimnames")=List of 2
#> .. .. ..$ : NULL
#> .. .. ..$ : chr "Collapse" "Extensive" "Moderate" "Slight"
#> $ vc :List of 1
#> ..$ : num 9.22e-149 1.45e-02 3.17e-01 8.82e-01 1.41 ...
d3long3 <- ( d3long2
%>% select( Name, Taxonomy, vc )
%>% mutate( Y_vals = unlist( lapply( vc
, function(v){paste(v,collapse = ",") } )))
%>% select( -vc )
)
d3long3
#> # A tibble: 3 x 3
#> Name Taxonomy Y_vals
#> <chr> <chr> <chr>
#> 1 Hancilar et. al (201~ CR/LDUAL/HEX:4+HFEX:12.8/~ 9.22e-149,0.01446893292,0.31~
#> 2 Rojas(2010) - CR/LFM~ CR/LFM/DNO/H:2/EDU2 0,2.610109488,10.000712,35.8~
#> 3 Rojas(2010) - CR/LFM~ CR/LFM/DNO/H:3 0,0.737817568,9.939968168001~
On Sat, 21 Mar 2020, Ioanna Ioannou wrote:
> Hello again,
>
> Here is the reproducible example:
>
> rm(list = ls())
> library(plyr)
> library(dplyr)
> library( data.table)
> library(stringr)
>
>
> d1 <- data.frame( Name = rep(c('Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)',
> 'Rojas(2010) - CR/LFM/DNO 2storey',
> 'Rojas(2010) - CR/LFM/DNO 3storey'), each = 4),
> Taxonomy = rep(c('CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//',
> 'CR/LFM/DNO/H:2/EDU2',
> 'CR/LFM/DNO/H:3'), each = 4),
> Damage_State =rep(c('Collapse', 'Extensive', 'Moderate', 'Slight'), times =3),
> Y_vals = c('0,6.49e-45,1.29e-29,3.35e-22,1.25e-17,1.8e-14,3.81e-12,2.35e-10,6.18e-09,8.78e-08,7.86e-07,4.92e-06,2.32e-05,8.76e-05,0.000274154,0.000736426,0.001740046,0.003688955,0.007130224,0.012730071,0.021221055,0.0333283,0.049687895,0.070771949,0.096832412,0.12787106',
> '5.02e-182,3.52e-10,8.81e-07,3.62e-05,0.000346166,0.001608096,0.004916965,0.01150426,0.022416772,0.038311015,0.059392175,0.085458446,0.115998702,0.150303282,0.187564259,0.226954808,0.267685669,0.309041053,0.35039806,0.391233913,0.431124831,0.469739614,0.506830242,0.542221151,0.575798268,0.607498531',
> '0,1.05e-10,4.75e-06,0.000479751,0.006156253,0.02983369,0.084284357,0.171401809,0.281721077,0.401071017,0.516782184,0.620508952,0.708327468,0.779597953,0.835636781,0.87866127,0.911104254,0.935237852,0.95300803,0.965993954,0.97543154,0.982263787,0.987197155,0.990753887,0.993316294,0.99516227',
> '4.61e-149,0.007234459,0.158482316,0.438164341,0.671470035,0.818341464,0.901312438,0.946339742,0.970531767,0.983584997,0.990707537,0.994650876,0.996869188,0.998137671,0.998874868,0.9993101,0.999570978,0.999729626,0.999827443,0.999888548,0.999927197,0.999951931,0.999967938,0.999978407,0.999985325,0.999989939',
>
> '0,4.91e-109,2.88e-47,3.32e-23,1.65e-11,1.78e-05,0.018162775,0.356628282,0.870224163,0.992779045,0.999855873,0.999998652,0.999999993,1,1,1,1,1,1,1,1,1,1,1,1,1',
> '0,1.21e-32,1.78e-05,0.645821244,0.999823159,0.999999999,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1',
> '0,0.077161367,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1',
> '0,0.996409276,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1',
>
> '0,1.29e-144,1.99e-71,1.16e-40,3.23e-24,1.59e-14,1.41e-08,6.42e-05,0.00971775,0.153727719,0.562404795,0.889217735,0.985915683,0.998997836,0.999955341,0.999998628,0.999999969,0.999999999,1,1,1,1,1,1,1,1',
> '0,2.12e-51,4.89e-14,0.001339285,0.559153268,0.995244295,0.999997786,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1',
> '0,3.22e-07,0.992496021,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1',
> '0,0.368907496,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1')
> )
>
>
>
>
> D2L <- c(0, 2, 10, 50, 100)
>
> VC_final <- array(NA, length(distinct(d1[,c(1,2)])$Name) )
>
> # get the rows for the four damage states
> DS1_rows <- d1$Damage_State == unique(d1$Damage_State)[4]
> DS2_rows <- d1$Damage_State == unique(d1$Damage_State)[3]
> DS3_rows <- d1$Damage_State == unique(d1$Damage_State)[2]
> DS4_rows <- d1$Damage_State == unique(d1$Damage_State)[1]
>
> # step through all possible values of IM.type and Taxonomy and Name
> #### This is true for this subset not generalibale needs to be checked first ##
> VC <- matrix(NA, 3,26)
> for(Tax in unique(d1$Taxonomy)) {
> for(Name in unique(d1$Name)) {
> # get a logical vector of the rows to be use DS5 in this calculation
> calc_rows <- d1$Taxonomy == Tax & d1$Name == Name
>
>
> # check that there are any such rows in the DS5ata frame
> if(sum(calc_rows)) {
>
> cat(Tax,Name,"\n")
> # if so, fill in the four values for these rows
> VC[calc_rows] <- D2L[1] * (1- as.numeric(unlist(str_split(as.character(d1[calc_rows & DS1_rows,]$Y_vals), pattern = ","))) ) +
> D2L[2]* (as.numeric(unlist(str_split(as.character(d1[calc_rows & DS1_rows,]$Y_vals), pattern = ","))) -
> as.numeric(unlist(str_split(as.character(d1[calc_rows & DS2_rows,]$Y_vals), pattern = ",")))) +
> D2L[3]* (as.numeric(unlist(str_split(as.character(d1[calc_rows & DS2_rows,]$Y_vals), pattern = ","))) -
> as.numeric(unlist(str_split(as.character(d1[calc_rows & DS3_rows,]$Y_vals), pattern = ",")))) +
> D2L[4] * (as.numeric(unlist(str_split(as.character(d1[calc_rows & DS3_rows,]$Y_vals), pattern = ","))) -
> as.numeric(unlist(str_split(as.character(d1[calc_rows & DS4_rows,]$Y_vals), pattern = ",")))) +
> D2L[5]* as.numeric(unlist(str_split(as.character(d1[calc_rows & DS4_rows,]$Y_vals), pattern = ",")))
> print(VC[calc_rows] )
> }
> }
> }
>
>
>
> Vul <- distinct(d1[,c(1,2)])
>
> dim(VC) <- c(length(unlist(str_split(as.character(d1[2,]$Y_vals), pattern = ","))),length(distinct(d1[,c(1,2)])$Name)) ## (rows, cols)
> VC
> VC_t <- t(VC)
> Vulnerability <- matrix(apply(VC_t, 1, function(x) paste(x, collapse = ',')))
>
> Vul$Y_vals <- Vulnerability
>
>
>
>
> ________________________________
> From: Jeff Newmiller <jdnewmil using dcn.davis.ca.us>
> Sent: 21 March 2020 16:27
> To: r-help using r-project.org <r-help using r-project.org>; Ioanna Ioannou <ii54250 using msn.com>; r-help using r-project.org <r-help using r-project.org>
> Subject: Re: [R] How to save output of multiple loops in a matrix
>
> You have again posted using HTML and the result is unreadable. Please post a reproducible example using dput instead of assuming we can read your formatted code or table.
>
> On March 21, 2020 8:59:58 AM PDT, Ioanna Ioannou <ii54250 using msn.com> wrote:
>> Hello everyone,
>>
>> I am having this data.frame. For each row you have 26 values aggregated
>> in a cell and separated by a comma. I want to do some calculations for
>> all unique names and taxonomy which include the four different damage
>> states. I can estimate the results but i am struggling to save them in
>> a data.frame and assign next to them the unique combination of the
>> name, taxonomy. Any help much appreciated.
>>
>>
>> d1 <- read.csv('test.csv')
>>
>> D2L <- c(0, 2, 10, 50, 100)
>>
>> VC_final <- array(NA, length(distinct(d1[,c(65,4,3)])$Name) )
>> VC <- matrix(NA,
>> length(distinct(d1[,c(65,4,3)])$Name),length(unlist(str_split(as.character(d1[1,]$Y_vals),
>> pattern = ","))))
>>
>> # get the rows for the four damage states
>> DS1_rows <- d1$Damage_State == unique(d1$Damage_State)[4]
>> DS2_rows <- d1$Damage_State == unique(d1$Damage_State)[3]
>> DS3_rows <- d1$Damage_State == unique(d1$Damage_State)[2]
>> DS4_rows <- d1$Damage_State == unique(d1$Damage_State)[1]
>>
>> # step through all possible values of IM.type and Taxonomy and Name
>> #### This is true for this subset not generalibale needs to be checked
>> first ##
>>
>> for(IM in unique(d1$IM_type)) {
>> for(Tax in unique(d1$Taxonomy)) {
>> for(Name in unique(d1$Name)) {
>> # get a logical vector of the rows to be use DS5 in this calculation
>> calc_rows <- d1$IM_type == IM & d1$Taxonomy == Tax & d1$Name == Name
>>
>>
>> # check that there are any such rows in the DS5ata frame
>> if(sum(calc_rows)) {
>> cat(IM,Tax,Name,"\n")
>> # if so, fill in the four values for these rows
>> VC[calc_rows] <- D2L[1] * (1-
>> as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS1_rows,]$Y_vals), pattern = ","))) ) +
>> D2L[2]* (as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS1_rows,]$Y_vals), pattern = ","))) -
>> as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS2_rows,]$Y_vals), pattern = ",")))) +
>> D2L[3]* (as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS2_rows,]$Y_vals), pattern = ","))) -
>> as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS3_rows,]$Y_vals), pattern = ",")))) +
>> D2L[4] * (as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS3_rows,]$Y_vals), pattern = ","))) -
>> as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS4_rows,]$Y_vals), pattern = ",")))) +
>> D2L[5]* as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS4_rows,]$Y_vals), pattern = ",")))
>> print(VC[calc_rows] )
>> }
>> }
>> }
>> }
>>
>> for(Tax in unique(d1$Taxonomy)) {
>> for(Name in unique(d1$Name)) {
>> # get a logical vector of the rows to be use DS5 in this calculation
>> calc_rows <- d1$IM_type == IM & d1$Taxonomy == Tax & d1$Name == Name
>>
>>
>> # check that there are any such rows in the DS5ata frame
>> if(sum(calc_rows)) {
>> cat(IM,Tax,Name,"\n")
>> # if so, fill in the four values for these rows
>> VC[calc_rows] <- D2L[1] * (1-
>> as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS1_rows,]$Y_vals), pattern = ","))) ) +
>> D2L[2]* (as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS1_rows,]$Y_vals), pattern = ","))) -
>> as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS2_rows,]$Y_vals), pattern = ",")))) +
>> D2L[3]* (as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS2_rows,]$Y_vals), pattern = ","))) -
>> as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS3_rows,]$Y_vals), pattern = ",")))) +
>> D2L[4] * (as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS3_rows,]$Y_vals), pattern = ","))) -
>> as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS4_rows,]$Y_vals), pattern = ",")))) +
>> D2L[5]* as.numeric(unlist(str_split(as.character(d1[calc_rows &
>> DS4_rows,]$Y_vals), pattern = ",")))
>> print(unique(VC ))
>> }
>> }
>> }
>>
>> Vul <- distinct(d1[,c(65,4,3)])
>>
>> dim(VC) <- c(length(unlist(str_split(as.character(d1[1,]$Y_vals),
>> pattern = ","))),length(distinct(d1[,c(65,4,3)])$Name)) ## (rows,
>> cols)
>> VC
>> VC_t <- t(VC)
>> Vulnerability <- matrix(apply(VC_t, 1, function(x) paste(x, collapse =
>> ',')))
>>
>> Vul$Y_vals <- Vulnerability
>>
>>
>>
>>
>> Best,
>> ioanna
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>> Name Taxonomy Damage_State Y_vals
>> Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)
>> CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1// Slight
>> 4.61e-149,0.007234459,0.158482316,0.438164341,0.671470035,0.818341464,0.901312438,0.946339742,0.970531767,0.983584997,0.990707537,0.994650876,0.996869188,0.998137671,0.998874868,0.9993101,0.999570978,0.999729626,0.999827443,0.999888548,0.999927197,0.999951931,0.999967938,0.999978407,0.999985325,0.9
>> Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)
>> CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//
>> Collapse
>> 0,6.49e-45,1.29e-29,3.35e-22,1.25e-17,1.8e-14,3.81e-12,2.35e-10,6.18e-09,8.78e-08,7.86e-07,4.92e-06,2.32e-05,8.76e-05,0.000274154,0.000736426,0.001740046,0.003688955,0.007130224,0.012730071,0.021221055,0.0333283,0.049687895,0.070771949,0.096832412,0.12787106
>> Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)
>> CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//
>> Extensive
>> 5.02e-182,3.52e-10,8.81e-07,3.62e-05,0.000346166,0.001608096,0.004916965,0.01150426,0.022416772,0.038311015,0.059392175,0.085458446,0.115998702,0.150303282,0.187564259,0.226954808,0.267685669,0.309041053,0.35039806,0.391233913,0.431124831,0.469739614,0.506830242,0.542221151,0.575798268,0.607498531
>> Hancilar et. al (2014) - CR/LDUAL school - Case V (Sd)
>> CR/LDUAL/HEX:4+HFEX:12.8/YAPP:1990/EDU+EDU2//PLFSQ/IRRE//RSH1//
>> Moderate
>> 0,1.05e-10,4.75e-06,0.000479751,0.006156253,0.02983369,0.084284357,0.171401809,0.281721077,0.401071017,0.516782184,0.620508952,0.708327468,0.779597953,0.835636781,0.87866127,0.911104254,0.935237852,0.95300803,0.965993954,0.97543154,0.982263787,0.987197155,0.990753887,0.993316294,0.99516227
>> Rojas(2010) - CR/LFM/DNO 2storey CR/LFM/DNO/H:2/EDU2
>> Collapse
>> 0,4.91e-109,2.88e-47,3.32e-23,1.65e-11,1.78e-05,0.018162775,0.356628282,0.870224163,0.992779045,0.999855873,0.999998652,0.999999993,1,1,1,1,1,1,1,1,1,1,1,1,1
>> Rojas(2010) - CR/LFM/DNO 2storey CR/LFM/DNO/H:2/EDU2
>> Extensive
>> 0,1.21e-32,1.78e-05,0.645821244,0.999823159,0.999999999,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
>> Rojas(2010) - CR/LFM/DNO 2storey CR/LFM/DNO/H:2/EDU2
>> Moderate
>> 0,0.077161367,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
>> Rojas(2010) - CR/LFM/DNO 2storey CR/LFM/DNO/H:2/EDU2 Slight
>> 0,0.996409276,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
>> Rojas(2010) - CR/LFM/DNO 3storey CR/LFM/DNO/H:3 Collapse
>> 0,1.29e-144,1.99e-71,1.16e-40,3.23e-24,1.59e-14,1.41e-08,6.42e-05,0.00971775,0.153727719,0.562404795,0.889217735,0.985915683,0.998997836,0.999955341,0.999998628,0.999999969,0.999999999,1,1,1,1,1,1,1,1
>> Rojas(2010) - CR/LFM/DNO 3storey CR/LFM/DNO/H:3 Extensive
>> 0,2.12e-51,4.89e-14,0.001339285,0.559153268,0.995244295,0.999997786,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
>> Rojas(2010) - CR/LFM/DNO 3storey CR/LFM/DNO/H:3 Moderate
>> 0,3.22e-07,0.992496021,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
>> Rojas(2010) - CR/LFM/DNO 3storey CR/LFM/DNO/H:3 Slight
>> 0,0.368907496,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
>>
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> --
> Sent from my phone. Please excuse my brevity.
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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