Dear R helpers
I have some variables say ABC, DEF, PQR, LMN and XYZ. I am choosing any three
varaibles at random at a time for my analysis and name these files as
input1.csv, input2.csv and input3.csv. So if I choose variables say ABC, DEF and
PQR, I am passing the specifications of these variables to input1.csv,
input2.csv and input3.csv respectively.
This means in another case even if I choose say LMN, DEF and XYZ in this order,
then my input1.csv will have details of LMN, input2.csv will have detaisl of DEF
and input3.csv will have details of XYZ. Thus, I am keeping the (input) file
names constant but the contents of each of these input files may change from one
case to another case.
As an example, my input files are as given below.
input1.csv
name1 value1
DEF 10
input2.csv
name2 value2
LMN 8
input3.csv
name3 value3
PQR 7
## __________________________________________________________________
## The Problem
name1 = read.csv('input1.csv')$name1
value1 = read.csv('input1.csv')$value1
name2 = read.csv('input2.csv')$name2
value2 = read.csv('input2.csv')$value2
name3 = read.csv('input3.csv')$name3
value3 = read.csv('input3.csv')$value3
# (Thus if 1st variable chosen is DEF, then name1 = DEF, value1 = 10. Had I
chosen some otehr variable, then name1 and value1 will have different values).
Then I carry out my analysis and get the output as given below.
Scenario_and_range names values
Sc_1 (DEF LMN PQR) name1 10.04
Sc_1 (DEF LMN PQR) name2 8.21
Sc_1 (DEF LMN PQR) name3 7.23
Sc_2 (DEF LMN PQR) name1 9.96
Sc_2 (DEF LMN PQR) name2 8.47
Sc_2 (DEF LMN PQR) name3 7.40
.........................................................................
.........................................................................
My probelm is I know name1 pertains to DEF, name2 pertains to LMN and name3
pertains to PQR. But in the output I am not able to replace name1 with DEF,
name2 with LMN and so on i.e. I cannot hardcode the varaible names in data.frame
as name1 = DEF, name2 = LMN etc as these names are going to change frome case to
case. My objective is to get the names (in column 2 of above table) same as
respective names (appearing in 1st column) in its order i.e. instead of name1, I
should get DEF, in place of name2, I should get LMN and in place of name3, I
should get PQR. Hence, my output should be like -
Scenario_and_range names values
Sc_1 (DEF LMN PQR) DEF 10.04
Sc_1 (DEF LMN PQR) LMN 8.21
Sc_1 (DEF LMN PQR) PQR 7.23
Sc_2 (DEF LMN PQR) DEF 9.96
Sc_2 (DEF LMN PQR) LMN 8.47
Sc_2 (DEF LMN PQR) PQR 7.40
.........................................................................
.........................................................................
I have tried to expalin the problem but I am not sure how far I have been clear
in that. I am giving below the actual R code I have used to arrive at
the required output. Actually I have say 8-9 rates and I am choosing say any
three out of them. Each of these rates have three possible ranges with
respective probabilities. My objective is to generate random numbers for the
various possible range COMBINATIONS in proportion to the respective joint
probabilities. I have alraedy written the R code, I just need to refine my
output.
I also sincerely apologize for writing such a long mail.
Regards
Amelia
**** My R code
******************************************************************
## Actualy I am dealing with more than 3 variables i.e. rates and thus my names
are different in actual code.
## Beginning of a R code
## FUNCTION NO. 3
library(reshape)
no_rate = 3
combi_3 = function(n, N, rateA, rate_name1, rateA_rf1, rateA_rf2, rateA_rf3,
rateAprob1, rateAprob2, rateAprob3,
rateB, rate_name2, rateB_rf1, rateB_rf2, rateB_rf3,
rateBprob1, rateBprob2, rateBprob3,
rateC, rate_name3, rateC_rf1, rateC_rf2, rateC_rf3, rateCprob1,
rateCprob2, rateCprob3)
{
rateA_prob1 = rateAprob3/2
rateA_prob2 = rateAprob2/2
rateA_prob3 = rateAprob1
rateA_prob4 = rateA_prob2
rateA_prob5 = rateA_prob1
rateA_ran1_min = rateA-rateA_rf3
rateA_ran1_max = rateA-rateA_rf2
rateA_ran2_min = rateA-rateA_rf2
rateA_ran2_max = rateA-rateA_rf1
rateA_ran3_min = rateA-rateA_rf1
rateA_ran3_max = rateA+rateA_rf1
rateA_ran4_min = rateA+rateA_rf1
rateA_ran4_max = rateA+rateA_rf2
rateA_ran5_min = rateA+rateA_rf2
rateA_ran5_max = rateA+rateA_rf3
rateB_prob1 = rateBprob3/2
rateB_prob2 = rateBprob2/2
rateB_prob3 = rateBprob1
rateB_prob4 = rateB_prob2
rateB_prob5 = rateB_prob1
rateB_ran1_min = rateB-rateB_rf3
rateB_ran1_max = rateB-rateB_rf2
rateB_ran2_min = rateB-rateB_rf2
rateB_ran2_max = rateB-rateB_rf1
rateB_ran3_min = rateB-rateB_rf1
rateB_ran3_max = rateB+rateB_rf1
rateB_ran4_min = rateB+rateB_rf1
rateB_ran4_max = rateB+rateB_rf2
rateB_ran5_min = rateB+rateB_rf2
rateB_ran5_max = rateB+rateB_rf3
rateC_prob1 = rateCprob3/2
rateC_prob2 = rateCprob2/2
rateC_prob3 = rateCprob1
rateC_prob4 = rateC_prob2
rateC_prob5 = rateC_prob1
rateC_ran1_min = rateC-rateC_rf3
rateC_ran1_max = rateC-rateC_rf2
rateC_ran2_min = rateC-rateC_rf2
rateC_ran2_max = rateC-rateC_rf1
rateC_ran3_min = rateC-rateC_rf1
rateC_ran3_max = rateC+rateC_rf1
rateC_ran4_min = rateC+rateC_rf1
rateC_ran4_max = rateC+rateC_rf2
rateC_ran5_min = rateC+rateC_rf2
rateC_ran5_max = rateC+rateC_rf3
##
________________________________________________________________________________________________
## COMPUTATIONS
R11 = paste(rate_name1, 1, sep = "")
R12 = paste(rate_name1, 2, sep = "")
R13 = paste(rate_name1, 3, sep = "")
R14 = paste(rate_name1, 4, sep = "")
R15 = paste(rate_name1, 5, sep = "")
R21 = paste(rate_name2, 1, sep = "")
R22 = paste(rate_name2, 2, sep = "")
R23 = paste(rate_name2, 3, sep = "")
R24 = paste(rate_name2, 4, sep = "")
R25 = paste(rate_name2, 5, sep = "")
R31 = paste(rate_name3, 1, sep = "")
R32 = paste(rate_name3, 2, sep = "")
R33 = paste(rate_name3, 3, sep = "")
R34 = paste(rate_name3, 4, sep = "")
R35 = paste(rate_name3, 5, sep = "")
data_lab <- expand.grid(c(R11, R12, R13, R14, R15), c(R21, R22, R23, R24,
R25), c(R31, R32, R33, R34, R35))
range_prob <- list()
range_prob[[1]] = c(rateA_prob1, rateA_prob2, rateA_prob3, rateA_prob4,
rateA_prob5 )
range_prob[[2]] = c(rateB_prob1, rateB_prob2, rateB_prob3, rateB_prob4,
rateB_prob5 )
range_prob[[3]] = c(rateC_prob1, rateC_prob2, rateC_prob3, rateC_prob4,
rateC_prob5 )
pdf = expand.grid(range_prob)
data_lab$probs = apply(pdf, 1, prod)
joint_probs = xtabs(probs ~ Var1 + Var2 + Var3, data = data_lab)
write.csv(data.frame(joint_probs), 'joint_probs3.csv', row.names =
FALSE)
#
_________________________________________________________________________________________________
ONS3 = read.csv('joint_probs3.csv')
names3 = apply(ONS3[, -4], 1, paste, collapse = ' ')
write.csv(data.frame(rate_combination = names3, Probability3 = ONS3[, 4]),
'prob_table3.csv', row.names = FALSE)
### ###### __________________________________________________
no_of_instances = N*(read.csv('prob_table3.csv')$Probability3)
write.csv(data.frame(rate1_range = ONS3[,1], rate2_range = ONS3[,2], rate3_range
= ONS3[,3], no_of_instances), 'Final Table3.csv', row.names = FALSE)
### ###### __________________________________________________
HM3 = read.csv('Final Table3.csv')
rateA_rates=rep(c(R11,R12,R13,R14,R15),25)
rateA_rates
number = HM3$no_of_instances
rateA_combination=rep(rateA_rates,number)
rateA_combination
interval.min=ifelse(rateA_combination==R11, rateA_ran1_min,
ifelse(rateA_combination==R12, rateA_ran2_min, ifelse(rateA_combination==R13,
rateA_ran3_min, ifelse(rateA_combination==R14, rateA_ran4_min,
rateA_ran5_min))))
interval.max=ifelse(rateA_combination==R11, rateA_ran1_max,
ifelse(rateA_combination==R12, rateA_ran2_max, ifelse(rateA_combination==R13,
rateA_ran3_max, ifelse(rateA_combination==R14, rateA_ran4_max,
rateA_ran5_max))))
rand.nums_rateA=runif(rateA_combination,min=interval.min,max=interval.max)
rateA_series = data.frame(rateA_combination,rand.nums_rateA)
write.csv(data.frame(rateA_series), 'rateA_series.csv', row.names =
FALSE)
##
________________________________________________________________________________________________________________________________________________________________________________________________________
## Random number generation for rateB
A2 = rep(c(R21), each = 5)
B2 = rep(c(R22), each = 5)
C2 = rep(c(R23), each = 5)
D2 = rep(c(R24), each = 5)
E2 = rep(c(R25), each = 5)
rateB_rates=rep(c(A2, B2, C2, D2, E2), 5)
rateB_rates
rateB_combination=rep(rateB_rates,number)
rateB_combination
interval.min=ifelse(rateB_combination==R21, rateB_ran1_min,
ifelse(rateB_combination==R22, rateB_ran2_min, ifelse(rateB_combination==R23,
rateB_ran3_min, ifelse(rateB_combination==R24, rateB_ran4_min,
rateB_ran5_min))))
interval.max=ifelse(rateB_combination==R21, rateB_ran1_max,
ifelse(rateB_combination==R22, rateB_ran2_max, ifelse(rateB_combination==R23,
rateB_ran3_max, ifelse(rateB_combination==R24, rateB_ran4_max,
rateB_ran5_max))))
rand.nums_rateB=runif(rateB_combination,min=interval.min,max=interval.max)
rateB_series = data.frame(rateB_combination,rand.nums_rateB)
write.csv(data.frame(rateB_series), 'rateB_series.csv', row.names =
FALSE)
##
________________________________________________________________________________________________________________________________________________________________________________________________________
## Random number generation for rateC
rateC_rates=rep(c(R31,R32,R33, R34, R35), each = 25)
rateC_rates
rateC_combination=rep(rateC_rates,number)
rateC_combination
interval.min=ifelse(rateC_combination==R31, rateC_ran1_min,
ifelse(rateC_combination==R32, rateC_ran2_min, ifelse(rateC_combination==R33,
rateC_ran3_min, ifelse(rateC_combination==R34, rateC_ran4_min,
rateC_ran5_min))))
interval.max=ifelse(rateC_combination==R31, rateC_ran1_max,
ifelse(rateC_combination==R32, rateC_ran2_max, ifelse(rateC_combination==R33,
rateC_ran3_max, ifelse(rateC_combination==R34, rateC_ran4_max,
rateC_ran5_max))))
rand.nums_rateC=runif(rateC_combination,min=interval.min,max=interval.max)
rateC_series = data.frame(rateC_combination,rand.nums_rateC)
write.csv(data.frame(rateC_series), 'rateC_series.csv', row.names =
FALSE)
####
________________________________________________________________________________________________________________________________________________
## Generation of combination names as per the no of random numbers generated
PP3 = read.csv('prob_table3.csv')$rate_combination
PPP3 = rep(PP3, number)
return(data.frame(PPP3, rateA = rateA_series$rand.nums_rateA, rateB =
rateB_series$rand.nums_rateB, rateC = rateC_series$rand.nums_rateC))
}
if
(no_rate ==3)
{
output = combi_3(n = read.csv('number.csv')$n, N =
read.csv('number.csv')$N, rateA = read.csv('rateA.csv')$rateA,
rate_name1 = read.csv('rateA.csv')$rate_name, rateA_rf1 =
read.csv('rateA_rf.csv')$rateA_rf1,
rateA_rf2 = read.csv('rateA_rf.csv')$rateA_rf2, rateA_rf3 =
read.csv('rateA_rf.csv')$rateA_rf3,
rateAprob1 = read.csv('rateA_probability.csv')$probability1, rateAprob2
= read.csv('rateA_probability.csv')$probability2, rateAprob3 =
read.csv('rateA_probability.csv')$probability3,
rateB = read.csv('rateB.csv')$rateB, rate_name2 =
read.csv('rateB.csv')$rate_name, rateB_rf1 =
read.csv('rateB_rf.csv')$rateB_rf1,
rateB_rf2 = read.csv('rateB_rf.csv')$rateB_rf2, rateB_rf3 =
read.csv('rateB_rf.csv')$rateB_rf3,
rateBprob1 = read.csv('rateB_probability.csv')$probability1, rateBprob2
= read.csv('rateB_probability.csv')$probability2, rateBprob3 =
read.csv('rateB_probability.csv')$probability3,
rateC = read.csv('rateC.csv')$rateC, rate_name3 =
read.csv('rateC.csv')$rate_name, rateC_rf1 =
read.csv('rateC_rf.csv')$rateC_rf1,
rateC_rf2 = read.csv('rateC_rf.csv')$rateC_rf2, rateC_rf3 =
read.csv('rateC_rf.csv')$rateC_rf3,
rateCprob1 = read.csv('rateC_probability.csv')$probability1, rateCprob2
= read.csv('rateC_probability.csv')$probability2, rateCprob3 =
read.csv('rateC_probability.csv')$probability3)
##
__________________________________________________________________________________________________________________________________________________
write.csv(data.frame(output), 'Rates Generated.csv', row.names = FALSE)
om3 = read.csv('Rates Generated.csv')
n = read.csv('number.csv')$n
N = read.csv('number.csv')$N
rateA = read.csv('rateA.csv')$rateA
rate_name1 = read.csv('rateA.csv')$rate_name
rateB = read.csv('rateB.csv')$rateB
rate_name2 = read.csv('rateB.csv')$rate_name
rateC = read.csv('rateC.csv')$rateC
rate_name3 = read.csv('rateC.csv')$rate_name
rateA_rf1 = read.csv('rateA_rf.csv')$rateA_rf1
rateB_rf1 = read.csv('rateB_rf.csv')$rateB_rf1
rateC_rf1 = read.csv('rateC_rf.csv')$rateC_rf1
rateA3 = rateA-rateA_rf1
rateA4 = rateA+rateA_rf1
rateB3 = rateB-rateB_rf1
rateB4 = rateB+rateB_rf1
rateC3 = rateC-rateC_rf1
rateC4 = rateC+rateC_rf1
rate_gen_num = length(om3$rateA) ### THIS rateA is from the scenario table.
add_A = runif(N-rate_gen_num, rateA3, rateA4)
add_B = runif(N-rate_gen_num, rateB3, rateB4)
add_C = runif(N-rate_gen_num, rateC3, rateC4)
if(rate_gen_num < N) rateA_adj = data.frame(namesA = paste(rate_name1, 3, sep
= ""), adj_rateA = add_A) else rateA_adj = 0
if(rate_gen_num < N) rateB_adj = data.frame(namesB = paste(rate_name2, 3, sep
= ""), adj_rateB = add_B) else rateB_adj = 0
if(rate_gen_num < N) rateC_adj = data.frame(namesC = paste(rate_name3, 3, sep
= ""), adj_rateC = add_C) else rateC_adj = 0
HM3 = read.csv('Final Table3.csv')
number = HM3$no_of_instances
PP3 = read.csv('prob_table3.csv')$rate_combination
PPP3 = rep(PP3, number)
combination_names = (c(as.character(PPP3), c(paste(rateA_adj$namesA,
rateB_adj$namesB, rateC_adj$namesC, sep = " "))))
adj_ratesA = c(read.csv('rateA_series.csv')$rand.nums_rateA,
rateA_adj$adj_rateA)
adj_ratesB = c(read.csv('rateB_series.csv')$rand.nums_rateB,
rateB_adj$adj_rateB)
adj_ratesC = c(read.csv('rateC_series.csv')$rand.nums_rateC,
rateC_adj$adj_rateC)
final_rates_3 = data.frame(rate_names = combination_names, ratesA = adj_ratesA,
ratesB = adj_ratesB, ratesC = adj_ratesC)
write.csv(data.frame(Scenario = paste("Sc_", 1:n, sep = ""),
sort_df(final_rates_3,(1))), 'final_rates3.csv', row.names = FALSE)
ONSPPA_3 = read.csv('final_rates3.csv')
NP = paste(ONSPPA_3$Scenario, "(",ONSPPA_3$rate_names,")",
sep = " ")
write.csv(data.frame(Scenario_and_rate_range = NP, sort_df(final_rates_3,(1))),
'final_rates3_3.csv', row.names = FALSE)
ONSPPA3 = read.csv('final_rates3_3.csv')
SK3 = data.frame(Scenario_and_rate_range = ONSPPA3$Scenario_and_rate_range,
rateA = ONSPPA3$ratesA, rateB = ONSPPA3$ratesB, rateC = ONSPPA3$ratesC )
f3 <- stack(SK3)
f3$Numbers <-rep(1:100,1)
f3$Scenario <- rep(NP,1)
f3
f3 <- f3[order(f3$Numbers), ]
write.csv(data.frame(f3), 'ksk3.csv', row.names = FALSE)
ksv3 = read.csv('ksk3.csv')
write.csv(data.frame(Scenarios_and_Rates_range = ksv3$Scenario, Rates =
ksv3$ind, Rate_values = ksv3$values), 'SHM3.csv', row.names = FALSE)
}
### Input data
'number.csv' # input file in csv form
n N
100 100
#_ rateA input _______________________________________________
'rateA.csv' # These rate names and values will change
from case to case.
rate_name rateA
ABC 8
'rateA_probability.csv'
probability1 probability2 probability3 # These are various range probabilities
here for ABC
0.6 0.3 0.1
'rateA_rf.csv'
rateA_rf1 rateA_rf2 rateA_rf3
0.5 0.75 1
# (These are possible range movements for rateA e.g. if rate A is ABC with base
value of say 8, it will move (+ - 0.5 i.e. 7.5 - 8.5 with probability 0.60, + -
0.75 i.e. 7.25 - 8.75 with probability 0.3 and + - 1 from the base rate of
8 i.e. 7 - 9 with probability 0.1.
# Thus we have five possible ranges in case of ABC as (7 - 7.25) with
probability 0.05 i.e. (half of extreme movement probability of 0.1 i.e. third
range), (7.25 - 7.5) with probability 0.15, (7.5 - 8.5) with probability 0.60,
(8.5 - 8.75) with probability 0.15 and (8.75 - 9) with probability 0.05.
#_______ rateB __________________________________________________________
'rateB.csv' # These rate names and values will change
from case to case.
rate_name rateA
DEF 9.5
'rateB_probability.csv'
probability1 probability2 probability3 # These are various range probabilities
here for DEF
0.7 0.3 0
'rateB_rf.csv'
rateB_rf1 rateB_rf2 rateB_rf3
1 1.5 0
#_______ rateC __________________________________________________________
'rateC.csv' # These rate names and values will change
from case to case.
rate_name rateC
PQR 5
'rateC_probability.csv'
probability1 probability2 probability3 # These are various range probabilities
here for PQR
0.5 0.3 0.2
'rateC_rf.csv'
rateC_rf1 rateC_rf2 rateC_rf3
0.5 1 1.5
### End of input files.
[[alternative HTML version deleted]]
Amelia wrote a few hundreds of lines .... This is too much reading. Please try to reduce you problem to 30 lines, and make the example self-contained (your data are not available). In 80% of the cases, the problem is self-resolved after it has been made self-contained. Dieter -- View this message in context: http://n4.nabble.com/Readjusting-the-OUTPUT-csv-file-tp1475448p1475478.html Sent from the R help mailing list archive at Nabble.com.
Dear Sir,
I really appreciate your suggestion. I was having the probelm of expressing my
problem precisely. In fact in my earlier mail, I have tried to write my probelm
in my initial few paras only. The rest content is my actual R code which I have
written and its working fine except for the final output which I want to have in
a particular form. I had produced the said R code as I thought it may be handy
for someone who may be interested.
For me another option was to attach the related R code but I understand we are
not supposed to send the attachments.
It was a difficult for me to express my problem effectively in few lines. Please
trust me that I had drafted it 2-3 times. I once again try to resend it without
the related R code. I thought it may be useful to have this R code handy. But
truely I sincerely apologize for the same and do appreciate the time contraints
all the R helpers have. Please Forgive me.
Here is my probelm restated.
### PROBLEM
I have some variables say ABC, DEF, PQR, LMN and XYZ. I am choosing any three
varaibles at random at a time for my analysis and name these files as
input1.csv, input2.csv and input3.csv. So if I choose variables say ABC, DEF and
PQR, I am passing the specifications of these variables to input1.csv,
input2.csv and input3.csv respectively.
This means in another case even if I choose say LMN, DEF and XYZ in this order,
then my input1.csv will have details of LMN, input2.csv will have detaisl of DEF
and input3.csv will have details of XYZ. Thus, I am keeping the (input) file
names constant but the contents of each of these input files may change from one
case to another case.
As an example, my input files are as given below.
input1.csv
name1 value1
DEF 10
input2.csv
name2 value2
LMN 8
input3.csv
name3 value3
PQR 7
## __________________________________________________________________
## The Problem
name1 = read.csv('input1.csv')$name1
value1 = read.csv('input1.csv')$value1
name2 = read.csv('input2.csv')$name2
value2 = read.csv('input2.csv')$value2
name3 = read.csv('input3.csv')$name3
value3 = read.csv('input3.csv')$value3
# (Thus if 1st variable chosen is DEF, then name1 = DEF, value1 = 10. Had I
chosen some otehr variable, then name1 and value1 will have different values).
Then I carry out my analysis and get the output as given below.
Scenario_and_range names values
Sc_1 (DEF LMN PQR) name1 10.04
Sc_1 (DEF LMN PQR) name2 8.21
Sc_1 (DEF LMN PQR) name3 7.23
Sc_2 (DEF LMN PQR) name1 9.96
Sc_2 (DEF LMN PQR) name2 8.47
Sc_2 (DEF LMN PQR) name3 7.40
.........................................................................
.........................................................................
The values appearing in the third column are the random nos. generated using the
base rate 10, 8 and 7 respectively.
My probelm is I know name1 pertains to DEF, name2 pertains to LMN and name3
pertains to PQR. But in the output I am not able to replace name1 with DEF,
name2 with LMN and so on i.e. I cannot hardcode the varaible names in data.frame
as name1 = DEF, name2 = LMN etc as these names are going to change frome case to
case. My objective is to get the names (in column 2 of above table) same as
respective names (appearing in 1st column) in its order i.e. instead of name1, I
should get DEF, in place of name2, I should get LMN and in place of name3, I
should get PQR.
Hence, my output should be like -
Scenario_and_range names values
Sc_1 (DEF LMN PQR) DEF 10.04
Sc_1 (DEF LMN PQR) LMN 8.21
Sc_1 (DEF LMN PQR) PQR 7.23
Sc_2 (DEF LMN PQR) DEF 9.96
Sc_2 (DEF LMN PQR) LMN 8.47
Sc_2 (DEF LMN PQR) PQR 7.40
.........................................................................
.........................................................................
Regards
Amelia
##_________________________________________________________________________
--- On Wed, 2/10/10, Dieter Menne <dieter.menne@menne-biomed.de> wrote:
From: Dieter Menne <dieter.menne@menne-biomed.de>
Subject: Re: [R] Readjusting the OUTPUT csv file
To: r-help@r-project.org
Date: Wednesday, February 10, 2010, 8:02 AM
Amelia wrote a few hundreds of lines ....
This is too much reading. Please try to reduce you problem to 30 lines, and
make the example self-contained (your data are not available). In 80% of the
cases, the problem is self-resolved after it has been made self-contained.
Dieter
--
View this message in context:
http://n4.nabble.com/Readjusting-the-OUTPUT-csv-file-tp1475448p1475478.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
R-help@r-project.org mailing list
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.
[[alternative HTML version deleted]]
On 02/10/2010 06:02 PM, Amelia Livington wrote:> Dear R helpers > > I have some variables say ABC, DEF, PQR, LMN and XYZ. I am choosing any three varaibles at random at a time for my analysis and name these files as input1.csv, input2.csv and input3.csv. So if I choose variables say ABC, DEF and PQR, I am passing the specifications of these variables to input1.csv, input2.csv and input3.csv respectively. > > This means in another case even if I choose say LMN, DEF and XYZ in this order, then my input1.csv will have details of LMN, input2.csv will have detaisl of DEF and input3.csv will have details of XYZ. Thus, I am keeping the (input) file names constant but the contents of each of these input files may change from one case to another case. > > As an example, my input files are as given below.Hi Amelia, I think you have just won the Posting Guide Medal of Honor for a message containing such a detailed description of the problem. I also think that what you need is: names(name1)[1] where you want the name of the variable in the file "input1.csv" that is read into the object named "name1". If this sounds confusing, read in the file as in your excellent example and then execute the above command. Jim
Amelia,
I think your problem (or at least part of it) comes from the fact that in your
learning of R syntax you learned about the magical shortcut index tool
"$" without gaining an adequate appreciation and understanding of what
that is a shortcut for (common misunderstanding). The great thing about the
magical shortcuts, is that when used as intended, they make life easier (thus
being magical shortcuts), the drawback of magical shortcuts is that when used in
ways never intended, the result is often the programming equivalent of
accidentally turning yourself into a toad.
Don't worry though, the solution is simple, don't use the magical
shortcut, but go back to the unmagical tool that it is a shortcut for
"[[".
Try:
name1 <- read.csv('input1.csv')[[name1]]
value1 <- read.csv('input1.csv')[[value1]]
and see if that does what you intend.
Also note that in the above you are reading input1.csv twice, it is probably
more efficient to read it once and store the data frame, then extract the
information that you want and delete the data frame (I/O can be slow compared to
in memory processes).
Hope this helps,
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Amelia Livington
> Sent: Wednesday, February 10, 2010 12:03 AM
> To: r-help at r-project.org
> Subject: [R] Readjusting the OUTPUT csv file
>
> Dear R helpers
>
> I have some variables say ABC, DEF, PQR, LMN and XYZ. I am choosing any
> three varaibles at random at a time for my analysis and name these
> files as input1.csv, input2.csv and input3.csv. So if I choose
> variables say ABC, DEF and PQR, I am passing the specifications of
> these variables to input1.csv, input2.csv and input3.csv respectively.
>
> This means in another case even if I choose say LMN, DEF and XYZ in
> this order, then my input1.csv will have details of LMN, input2.csv
> will have detaisl of DEF and input3.csv will have details of XYZ. Thus,
> I am keeping the (input) file names constant but the contents of each
> of these input files may change from one case to another case.
>
> As an example, my input files are as given below.
>
> input1.csv
> name1 value1
> DEF 10
>
> input2.csv
> name2 value2
> LMN 8
>
> input3.csv
> name3 value3
> PQR 7
>
> ## __________________________________________________________________
>
> ## The Problem
>
> name1 = read.csv('input1.csv')$name1
> value1 = read.csv('input1.csv')$value1
>
>
> name2 = read.csv('input2.csv')$name2
> value2 = read.csv('input2.csv')$value2
>
>
> name3 = read.csv('input3.csv')$name3
> value3 = read.csv('input3.csv')$value3
>
> # (Thus if 1st variable chosen is DEF, then name1 = DEF, value1 = 10.
> Had I chosen some otehr variable, then name1 and value1 will have
> different values).
>
> Then I carry out my analysis and get the output as given below.
>
> Scenario_and_range names values
> Sc_1 (DEF LMN PQR) name1 10.04
> Sc_1 (DEF LMN PQR) name2 8.21
> Sc_1 (DEF LMN PQR) name3 7.23
>
> Sc_2 (DEF LMN PQR) name1 9.96
> Sc_2 (DEF LMN PQR) name2 8.47
> Sc_2 (DEF LMN PQR) name3 7.40
> .......................................................................
> ..
> .......................................................................
> ..
>
> My probelm is I know name1 pertains to DEF, name2 pertains to LMN and
> name3 pertains to PQR. But in the output I am not able to replace name1
> with DEF, name2 with LMN and so on i.e. I cannot hardcode the varaible
> names in data.frame as name1 = DEF, name2 = LMN etc as these names are
> going to change frome case to case. My objective is to get the names
> (in column 2 of above table) same as respective names (appearing in 1st
> column) in its order i.e. instead of name1, I should get DEF, in place
> of name2, I should get LMN and in place of name3, I should get PQR.
> Hence, my output should be like -
>
>
> Scenario_and_range names values
> Sc_1 (DEF LMN PQR) DEF 10.04
> Sc_1 (DEF LMN PQR) LMN 8.21
> Sc_1 (DEF LMN PQR) PQR 7.23
>
> Sc_2 (DEF LMN PQR) DEF 9.96
> Sc_2 (DEF LMN PQR) LMN 8.47
> Sc_2 (DEF LMN PQR) PQR 7.40
> .......................................................................
> ..
> .......................................................................
> ..
>
>
> I have tried to expalin the problem but I am not sure how far I have
> been clear in that. I am giving below the actual R code I have used to
> arrive at the required output. Actually I have say 8-9 rates and I am
> choosing say any three out of them. Each of these rates have three
> possible ranges with respective probabilities. My objective is
> to generate random numbers for the various possible range COMBINATIONS
> in proportion to the respective joint probabilities. I have alraedy
> written the R code, I just need to refine my output.
>
> I also sincerely apologize for writing such a long mail.
>
> Regards
>
> Amelia
>
> **** My R code
> ******************************************************************
>
> ## Actualy I am dealing with more than 3 variables i.e. rates and thus
> my names are different in actual code.
>
> ## Beginning of a R code
>
> ## FUNCTION NO. 3
>
> library(reshape)
> no_rate = 3
>
> combi_3 = function(n, N, rateA, rate_name1, rateA_rf1, rateA_rf2,
> rateA_rf3, rateAprob1, rateAprob2, rateAprob3,
> rateB, rate_name2, rateB_rf1, rateB_rf2,
> rateB_rf3, rateBprob1, rateBprob2, rateBprob3,
> rateC, rate_name3, rateC_rf1, rateC_rf2, rateC_rf3,
> rateCprob1, rateCprob2, rateCprob3)
>
> {
>
> rateA_prob1 = rateAprob3/2
> rateA_prob2 = rateAprob2/2
> rateA_prob3 = rateAprob1
> rateA_prob4 = rateA_prob2
> rateA_prob5 = rateA_prob1
>
> rateA_ran1_min = rateA-rateA_rf3
> rateA_ran1_max = rateA-rateA_rf2
> rateA_ran2_min = rateA-rateA_rf2
> rateA_ran2_max = rateA-rateA_rf1
> rateA_ran3_min = rateA-rateA_rf1
> rateA_ran3_max = rateA+rateA_rf1
> rateA_ran4_min = rateA+rateA_rf1
> rateA_ran4_max = rateA+rateA_rf2
> rateA_ran5_min = rateA+rateA_rf2
> rateA_ran5_max = rateA+rateA_rf3
>
> rateB_prob1 = rateBprob3/2
> rateB_prob2 = rateBprob2/2
> rateB_prob3 = rateBprob1
> rateB_prob4 = rateB_prob2
> rateB_prob5 = rateB_prob1
>
> rateB_ran1_min = rateB-rateB_rf3
> rateB_ran1_max = rateB-rateB_rf2
> rateB_ran2_min = rateB-rateB_rf2
> rateB_ran2_max = rateB-rateB_rf1
> rateB_ran3_min = rateB-rateB_rf1
> rateB_ran3_max = rateB+rateB_rf1
> rateB_ran4_min = rateB+rateB_rf1
> rateB_ran4_max = rateB+rateB_rf2
> rateB_ran5_min = rateB+rateB_rf2
> rateB_ran5_max = rateB+rateB_rf3
>
> rateC_prob1 = rateCprob3/2
> rateC_prob2 = rateCprob2/2
> rateC_prob3 = rateCprob1
> rateC_prob4 = rateC_prob2
> rateC_prob5 = rateC_prob1
>
> rateC_ran1_min = rateC-rateC_rf3
> rateC_ran1_max = rateC-rateC_rf2
> rateC_ran2_min = rateC-rateC_rf2
> rateC_ran2_max = rateC-rateC_rf1
> rateC_ran3_min = rateC-rateC_rf1
> rateC_ran3_max = rateC+rateC_rf1
> rateC_ran4_min = rateC+rateC_rf1
> rateC_ran4_max = rateC+rateC_rf2
> rateC_ran5_min = rateC+rateC_rf2
> rateC_ran5_max = rateC+rateC_rf3
>
> ##
> _______________________________________________________________________
> _________________________
>
> ## COMPUTATIONS
>
> R11 = paste(rate_name1, 1, sep = "")
> R12 = paste(rate_name1, 2, sep = "")
> R13 = paste(rate_name1, 3, sep = "")
> R14 = paste(rate_name1, 4, sep = "")
> R15 = paste(rate_name1, 5, sep = "")
>
> R21 = paste(rate_name2, 1, sep = "")
> R22 = paste(rate_name2, 2, sep = "")
> R23 = paste(rate_name2, 3, sep = "")
> R24 = paste(rate_name2, 4, sep = "")
> R25 = paste(rate_name2, 5, sep = "")
>
> R31 = paste(rate_name3, 1, sep = "")
> R32 = paste(rate_name3, 2, sep = "")
> R33 = paste(rate_name3, 3, sep = "")
> R34 = paste(rate_name3, 4, sep = "")
> R35 = paste(rate_name3, 5, sep = "")
>
> data_lab <- expand.grid(c(R11, R12, R13, R14, R15), c(R21, R22, R23,
> R24, R25), c(R31, R32, R33, R34, R35))
> range_prob <- list()
>
> range_prob[[1]] = c(rateA_prob1, rateA_prob2, rateA_prob3,
> rateA_prob4, rateA_prob5 )
> range_prob[[2]] = c(rateB_prob1, rateB_prob2, rateB_prob3,
> rateB_prob4, rateB_prob5 )
> range_prob[[3]] = c(rateC_prob1, rateC_prob2, rateC_prob3,
> rateC_prob4, rateC_prob5 )
>
> pdf = expand.grid(range_prob)
> data_lab$probs = apply(pdf, 1, prod)
> joint_probs = xtabs(probs ~ Var1 + Var2 + Var3, data = data_lab)
>
> write.csv(data.frame(joint_probs), 'joint_probs3.csv', row.names
> FALSE)
>
> #
> _______________________________________________________________________
> __________________________
>
> ONS3 = read.csv('joint_probs3.csv')
> names3 = apply(ONS3[, -4], 1, paste, collapse = ' ')
>
> write.csv(data.frame(rate_combination = names3, Probability3 = ONS3[,
> 4]), 'prob_table3.csv', row.names = FALSE)
>
> ### ###### __________________________________________________
>
> no_of_instances = N*(read.csv('prob_table3.csv')$Probability3)
>
> write.csv(data.frame(rate1_range = ONS3[,1], rate2_range = ONS3[,2],
> rate3_range = ONS3[,3], no_of_instances), 'Final Table3.csv',
row.names
> = FALSE)
>
> ### ###### __________________________________________________
>
> HM3 = read.csv('Final Table3.csv')
>
> rateA_rates=rep(c(R11,R12,R13,R14,R15),25)
> rateA_rates
>
> number = HM3$no_of_instances
>
> rateA_combination=rep(rateA_rates,number)
> rateA_combination
>
> interval.min=ifelse(rateA_combination==R11, rateA_ran1_min,
> ifelse(rateA_combination==R12, rateA_ran2_min,
> ifelse(rateA_combination==R13, rateA_ran3_min,
> ifelse(rateA_combination==R14, rateA_ran4_min, rateA_ran5_min))))
> interval.max=ifelse(rateA_combination==R11, rateA_ran1_max,
> ifelse(rateA_combination==R12, rateA_ran2_max,
> ifelse(rateA_combination==R13, rateA_ran3_max,
> ifelse(rateA_combination==R14, rateA_ran4_max, rateA_ran5_max))))
>
> rand.nums_rateA=runif(rateA_combination,min=interval.min,max=interval.m
> ax)
>
> rateA_series = data.frame(rateA_combination,rand.nums_rateA)
>
> write.csv(data.frame(rateA_series), 'rateA_series.csv', row.names
> FALSE)
>
> ##
> _______________________________________________________________________
> _______________________________________________________________________
> __________________________________________________________
>
> ## Random number generation for rateB
>
> A2 = rep(c(R21), each = 5)
> B2 = rep(c(R22), each = 5)
> C2 = rep(c(R23), each = 5)
> D2 = rep(c(R24), each = 5)
> E2 = rep(c(R25), each = 5)
>
> rateB_rates=rep(c(A2, B2, C2, D2, E2), 5)
> rateB_rates
>
> rateB_combination=rep(rateB_rates,number)
> rateB_combination
>
> interval.min=ifelse(rateB_combination==R21, rateB_ran1_min,
> ifelse(rateB_combination==R22, rateB_ran2_min,
> ifelse(rateB_combination==R23, rateB_ran3_min,
> ifelse(rateB_combination==R24, rateB_ran4_min, rateB_ran5_min))))
> interval.max=ifelse(rateB_combination==R21, rateB_ran1_max,
> ifelse(rateB_combination==R22, rateB_ran2_max,
> ifelse(rateB_combination==R23, rateB_ran3_max,
> ifelse(rateB_combination==R24, rateB_ran4_max, rateB_ran5_max))))
>
> rand.nums_rateB=runif(rateB_combination,min=interval.min,max=interval.m
> ax)
>
> rateB_series = data.frame(rateB_combination,rand.nums_rateB)
>
> write.csv(data.frame(rateB_series), 'rateB_series.csv', row.names
> FALSE)
>
> ##
> _______________________________________________________________________
> _______________________________________________________________________
> __________________________________________________________
>
> ## Random number generation for rateC
>
> rateC_rates=rep(c(R31,R32,R33, R34, R35), each = 25)
> rateC_rates
>
> rateC_combination=rep(rateC_rates,number)
> rateC_combination
>
> interval.min=ifelse(rateC_combination==R31, rateC_ran1_min,
> ifelse(rateC_combination==R32, rateC_ran2_min,
> ifelse(rateC_combination==R33, rateC_ran3_min,
> ifelse(rateC_combination==R34, rateC_ran4_min, rateC_ran5_min))))
> interval.max=ifelse(rateC_combination==R31, rateC_ran1_max,
> ifelse(rateC_combination==R32, rateC_ran2_max,
> ifelse(rateC_combination==R33, rateC_ran3_max,
> ifelse(rateC_combination==R34, rateC_ran4_max, rateC_ran5_max))))
>
> rand.nums_rateC=runif(rateC_combination,min=interval.min,max=interval.m
> ax)
>
> rateC_series = data.frame(rateC_combination,rand.nums_rateC)
>
> write.csv(data.frame(rateC_series), 'rateC_series.csv', row.names
> FALSE)
>
> ####
> _______________________________________________________________________
> _______________________________________________________________________
> __
>
> ## Generation of combination names as per the no of random numbers
> generated
>
> PP3 = read.csv('prob_table3.csv')$rate_combination
> PPP3 = rep(PP3, number)
> return(data.frame(PPP3, rateA = rateA_series$rand.nums_rateA, rateB >
rateB_series$rand.nums_rateB, rateC = rateC_series$rand.nums_rateC))
> }
>
>
>
> if
> (no_rate ==3)
> {
>
> output = combi_3(n = read.csv('number.csv')$n, N >
read.csv('number.csv')$N, rateA = read.csv('rateA.csv')$rateA,
> rate_name1 = read.csv('rateA.csv')$rate_name, rateA_rf1 >
read.csv('rateA_rf.csv')$rateA_rf1,
> rateA_rf2 = read.csv('rateA_rf.csv')$rateA_rf2, rateA_rf3 >
read.csv('rateA_rf.csv')$rateA_rf3,
> rateAprob1 = read.csv('rateA_probability.csv')$probability1,
rateAprob2
> = read.csv('rateA_probability.csv')$probability2, rateAprob3 >
read.csv('rateA_probability.csv')$probability3,
> rateB = read.csv('rateB.csv')$rateB, rate_name2 >
read.csv('rateB.csv')$rate_name, rateB_rf1 >
read.csv('rateB_rf.csv')$rateB_rf1,
> rateB_rf2 = read.csv('rateB_rf.csv')$rateB_rf2, rateB_rf3 >
read.csv('rateB_rf.csv')$rateB_rf3,
> rateBprob1 = read.csv('rateB_probability.csv')$probability1,
rateBprob2
> = read.csv('rateB_probability.csv')$probability2, rateBprob3 >
read.csv('rateB_probability.csv')$probability3,
> rateC = read.csv('rateC.csv')$rateC, rate_name3 >
read.csv('rateC.csv')$rate_name, rateC_rf1 >
read.csv('rateC_rf.csv')$rateC_rf1,
> rateC_rf2 = read.csv('rateC_rf.csv')$rateC_rf2, rateC_rf3 >
read.csv('rateC_rf.csv')$rateC_rf3,
> rateCprob1 = read.csv('rateC_probability.csv')$probability1,
rateCprob2
> = read.csv('rateC_probability.csv')$probability2, rateCprob3 >
read.csv('rateC_probability.csv')$probability3)
>
> ##
> _______________________________________________________________________
> _______________________________________________________________________
> ____
>
> write.csv(data.frame(output), 'Rates Generated.csv', row.names >
FALSE)
>
> om3 = read.csv('Rates Generated.csv')
> n = read.csv('number.csv')$n
> N = read.csv('number.csv')$N
> rateA = read.csv('rateA.csv')$rateA
> rate_name1 = read.csv('rateA.csv')$rate_name
> rateB = read.csv('rateB.csv')$rateB
> rate_name2 = read.csv('rateB.csv')$rate_name
> rateC = read.csv('rateC.csv')$rateC
> rate_name3 = read.csv('rateC.csv')$rate_name
>
> rateA_rf1 = read.csv('rateA_rf.csv')$rateA_rf1
> rateB_rf1 = read.csv('rateB_rf.csv')$rateB_rf1
> rateC_rf1 = read.csv('rateC_rf.csv')$rateC_rf1
>
> rateA3 = rateA-rateA_rf1
> rateA4 = rateA+rateA_rf1
>
> rateB3 = rateB-rateB_rf1
> rateB4 = rateB+rateB_rf1
>
> rateC3 = rateC-rateC_rf1
> rateC4 = rateC+rateC_rf1
>
> rate_gen_num = length(om3$rateA) ### THIS rateA is from the scenario
> table.
>
> add_A = runif(N-rate_gen_num, rateA3, rateA4)
> add_B = runif(N-rate_gen_num, rateB3, rateB4)
> add_C = runif(N-rate_gen_num, rateC3, rateC4)
>
> if(rate_gen_num < N) rateA_adj = data.frame(namesA = paste(rate_name1,
> 3, sep = ""), adj_rateA = add_A) else rateA_adj = 0
> if(rate_gen_num < N) rateB_adj = data.frame(namesB = paste(rate_name2,
> 3, sep = ""), adj_rateB = add_B) else rateB_adj = 0
> if(rate_gen_num < N) rateC_adj = data.frame(namesC = paste(rate_name3,
> 3, sep = ""), adj_rateC = add_C) else rateC_adj = 0
>
> HM3 = read.csv('Final Table3.csv')
> number = HM3$no_of_instances
> PP3 = read.csv('prob_table3.csv')$rate_combination
> PPP3 = rep(PP3, number)
>
> combination_names = (c(as.character(PPP3), c(paste(rateA_adj$namesA,
> rateB_adj$namesB, rateC_adj$namesC, sep = " "))))
> adj_ratesA = c(read.csv('rateA_series.csv')$rand.nums_rateA,
> rateA_adj$adj_rateA)
> adj_ratesB = c(read.csv('rateB_series.csv')$rand.nums_rateB,
> rateB_adj$adj_rateB)
> adj_ratesC = c(read.csv('rateC_series.csv')$rand.nums_rateC,
> rateC_adj$adj_rateC)
>
> final_rates_3 = data.frame(rate_names = combination_names, ratesA >
adj_ratesA, ratesB = adj_ratesB, ratesC = adj_ratesC)
>
> write.csv(data.frame(Scenario = paste("Sc_", 1:n, sep =
""),
> sort_df(final_rates_3,(1))), 'final_rates3.csv', row.names = FALSE)
>
> ONSPPA_3 = read.csv('final_rates3.csv')
>
> NP = paste(ONSPPA_3$Scenario,
"(",ONSPPA_3$rate_names,")", sep = " ")
>
> write.csv(data.frame(Scenario_and_rate_range = NP,
> sort_df(final_rates_3,(1))), 'final_rates3_3.csv', row.names =
FALSE)
>
> ONSPPA3 = read.csv('final_rates3_3.csv')
>
> SK3 = data.frame(Scenario_and_rate_range >
ONSPPA3$Scenario_and_rate_range, rateA = ONSPPA3$ratesA, rateB >
ONSPPA3$ratesB, rateC = ONSPPA3$ratesC )
>
> f3 <- stack(SK3)
>
> f3$Numbers <-rep(1:100,1)
>
> f3$Scenario <- rep(NP,1)
>
> f3
>
> f3 <- f3[order(f3$Numbers), ]
>
> write.csv(data.frame(f3), 'ksk3.csv', row.names = FALSE)
>
> ksv3 = read.csv('ksk3.csv')
>
> write.csv(data.frame(Scenarios_and_Rates_range = ksv3$Scenario, Rates >
ksv3$ind, Rate_values = ksv3$values), 'SHM3.csv', row.names = FALSE)
>
> }
>
> ### Input data
>
> 'number.csv' # input file in csv form
> n N
> 100 100
>
> #_ rateA input _______________________________________________
>
> 'rateA.csv' # These rate names and values will
change
> from case to case.
> rate_name rateA
> ABC 8
>
> 'rateA_probability.csv'
> probability1 probability2 probability3 # These are various range
> probabilities here for ABC
> 0.6 0.3 0.1
>
> 'rateA_rf.csv'
> rateA_rf1 rateA_rf2 rateA_rf3
> 0.5 0.75 1
>
>
> # (These are possible range movements for rateA e.g. if rate A is ABC
> with base value of say 8, it will move (+ - 0.5 i.e. 7.5 - 8.5 with
> probability 0.60, + - 0.75 i.e. 7.25 - 8.75 with probability 0.3 and +
> - 1 from the base rate of 8 i.e. 7 - 9 with probability 0.1.
>
> # Thus we have five possible ranges in case of ABC as (7 - 7.25) with
> probability 0.05 i.e. (half of extreme movement probability of 0.1 i.e.
> third range), (7.25 - 7.5) with probability 0.15, (7.5 - 8.5) with
> probability 0.60, (8.5 - 8.75) with probability 0.15 and (8.75 - 9)
> with probability 0.05.
>
> #_______ rateB
> __________________________________________________________
>
>
> 'rateB.csv' # These rate names and values will
change
> from case to case.
> rate_name rateA
> DEF 9.5
>
>
> 'rateB_probability.csv'
> probability1 probability2 probability3 # These are various range
> probabilities here for DEF
> 0.7 0.3 0
>
>
>
> 'rateB_rf.csv'
> rateB_rf1 rateB_rf2 rateB_rf3
> 1 1.5 0
>
>
> #_______ rateC
> __________________________________________________________
>
> 'rateC.csv' # These rate names and values will
change
> from case to case.
> rate_name rateC
> PQR 5
>
>
> 'rateC_probability.csv'
> probability1 probability2 probability3 # These are various range
> probabilities here for PQR
> 0.5 0.3 0.2
>
>
> 'rateC_rf.csv'
> rateC_rf1 rateC_rf2 rateC_rf3
> 0.5 1 1.5
>
> ### End of input files.
>
>
>
> [[alternative HTML version deleted]]