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-149,0.007234459,0.158482316,0.438164341,0.671470035,0.818341464,0.901312438,0.946339742,0.970531767,0.983584997,0.990707537,0.994650876,0.996869188,0.998137671,0.998874868,0.9993101,0.999570978,0.999729626,0.999827443,0.999888548,0.999927197,0.999951931,0.999967938,0.999978407,0.999985325,0.999989939
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]]
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 at 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-149,0.007234459,0.158482316,0.438164341,0.671470035,0.818341464,0.901312438,0.946339742,0.970531767,0.983584997,0.990707537,0.994650876,0.996869188,0.998137671,0.998874868,0.9993101,0.999570978,0.999729626,0.999827443,0.999888548,0.999927197,0.999951931,0.999967938,0.999978407,0.999985325,0.999989939 >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 at 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.
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 at dcn.davis.ca.us>
Sent: 21 March 2020 16:27
To: r-help at r-project.org <r-help at r-project.org>; Ioanna Ioannou
<ii54250 at msn.com>; r-help at r-project.org <r-help at
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 at 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 at 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.
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