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Tropical Fisheries Analysis with R
Hi, @tokami. I am recently having an error in completing the catchCurve and I am confused. I tried the code
selar_res_cc <- catchCurve(selar_lfq_catch_vec,
catch_columns = c(1, 2),
reg_int = c(10.5, 14.5),
calc_ogive = TRUE)
Here is the error message:
Error in catchCurve(selar_lfq_catch_vec, catch_columns = c(1, 2), reg_int = c(10.5, :
You need to assign values to Linf and K for the catch curve based on length-frequency data!
What should I do?
why removing LBB?
Dear Tobias Mildenberger,
Thank you for creating TropFishR! I am new to the package and am having a few issues figuring it out.
I am trying to run the example set out in help(Bhattcharya) with the synLFQ1 data, but every time I select points 19 - 23 I am faced with the error code below:
Error in plot.window(xlim, ylim, "", ...) : need finite 'ylim' values
In addition: Warning messages:
1: In sqrt(-interval/b.co1) : NaNs produced
2: In rnorm(n = n_rnorm, mean = l.mean.co1, sd = s.co1) : NAs produced
Could you explain what I am doing wrong?
Current runtime is with 11min above max of 10min
Hi
Thanks for TropFishR package
I have problem with lfqModify
each time running the code lfq_sum <- lfqModify(synLFQ4, vectorise_catch = TRUE)
this errors will display:
Error in lfqModify(synLFQ4, vectorise_catch = TRUE) :
unused argument (vectorise_catch = TRUE)
How I can fix this issue?
Thanks in advance
Mohammad
`
noted by Hadi:
Dear Sir,
I'm trying to use the "A manual for the length-based Bayesian biomass estimator within TropFishR"
I follow the steps in the vignettes, but when I reach the "plotLBB.data(lfq)" I get error mesage:
> remotes::install_github("tokami/TropFishR")
Downloading GitHub repo tokami/TropFishR@HEAD
Running `R CMD build`...
* checking for file 'C:\Users\asamw\AppData\Local\Temp\RtmpuoSXW2\remotes1a208bc25be\tokami-TropFishR-4f0a13f/DESCRIPTION' ... OK
* preparing 'TropFishR':
* checking DESCRIPTION meta-information ... OK
* checking for LF line-endings in source and make files and shell scripts
* checking for empty or unneeded directories
* building 'TropFishR_1.6.3.tar.gz'
Installing package into ‘C:/Users/asamw/AppData/Local/R/win-library/4.2’
(as ‘lib’ is unspecified)
* installing *source* package 'TropFishR' ...
** using staged installation
** R
** data
*** moving datasets to lazyload DB
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (TropFishR)
> library(TropFishR)
> ## load data set into R environment
> data("synLFQ8")
> ## plot length-frequency data
> plot(synLFQ8, Fname = "catch")
> ## aggregate lfq data per year
> lfq <- lfqModify(synLFQ8, aggregate = "year")
> ## plot lfq data in standard TropFishR manner
> plot(lfq, Fname = "catch")
> ## plot data in LBB manner
> plotLBB.data(lfq)
Error in plotLBB.data(lfq) : could not find function "plotLBB.data"
Please help me with this issue as I'm intending to use this method in my data analysis.
Thanks
Issam
add terminal F and M values on the plot?
lastLengthClass <- max(which(!is.na(catch_cor)),na.rm=TRUE)
diag()
and thus the start of real cohort choosable? or fix it as the first age class in the first column?plus.group = 6
or plus.group = 54
for age and length, respectivelyI am following your tutorial here. The data I used can be found here.
Here's what I did:
library(TropFishR)
lfq1 <- read.csv("lfq-data.csv")
dates <- colnames(lfq1)[-1]
dates <- strsplit(dates, "X")
dates <- unlist(lapply(dates, function(x) x[2]))
dates <- as.Date(dates, "%Y.%m.%d") # I changed this part to follow the format of dates in my data
lfq1new <- list(dates = dates,
midLengths = lfq1$midlength,
catch = as.matrix(lfq1[,-1]))
class(lfq1new) <- "lfq"
plot(lfq1new, Fname = "catch")
set.seed(1)
lfq1a <- lfqModify(lfq1new, bin_size = 4)
lfqbin <- lfqRestructure(lfq1a, MA = 5, addl.sqrt = FALSE)
But the last code throws an error:
Error in seq.default(val_first, val_last) :
'from' must be a finite number
In addition: Warning messages:
1: In min(which(lfq$catch[, i] != 0)) :
no non-missing arguments to min; returning Inf
2: In max(which(lfq$catch[, i] != 0)) :
no non-missing arguments to max; returning -Inf
What should I do? At first I thought that maybe the data arrangement is wrong, but I am pretty sure that it is correct, since I followed the tutorial given in the link above (the data follows the "Data arrangement 3").
this should be done in a separate function to allow for use in other functions and interchangeability with new approaches
install.packages(devtools)
Error in install.packages : object 'devtools' not found
devtools::install_github(“tokami/TropFishR”)
Error: unexpected input in "devtools::install_github(“"
Hi,
I am trying to run the tutorial "Single-species fish stock assessment with TropFishR" with version 1.6.2. ELEFAN function is not returning score_mat. This is how it looks like
res_RSA <- ELEFAN(synLFQ7a, Linf_range = seq(119,139,1), MA = 5,
K_range = seq(0.01,2,0.1), addl.sqrt = TRUE,
hide.progressbar = TRUE, contour=5)
# find 3 highest score values
n <- length(res_RSA$score_mat)
n
I get:
[1] 0
Later ,I installed version 1.2 from CRAN archive and got everything to work fine. Do you know why this may be?
Thanks!
Dear Tobias,
Do you think it would be possible to add a na.rm parameter to VBGF, defaulting to FALSE like max() does (for example)? This would avoid having to code VBGF calls in an if/else wrapper to deal with NAs when running VBGF on a vector with NAs.
Thanks!
I am running the ELEFAN_SA()
function. Here's the code:
sp_SA <- ELEFAN_SA(
lfq = sp_rlfd,
seasonalised = TRUE,
init_par = list(
Linf = Linf03,
K = 1,
t_anchor = 0.5,
ts = 0.5,
C = 0.5
),
low_par = list(
Linf = Linf03 - 2,
K = 0.5,
t_anchor = 0, ts = 0, C = 0
),
up_par = list(
Linf = Linf03 + 2,
K = 1.5,
t_anchor = 1, ts = 1, C = 1
),
SA_temp = 2e5,
SA_time = 60 * 5,
maxit = 500,
MA = 5,
plot.score = TRUE,
verbose = FALSE
)
However, I got this error:
Simulated annealing is running.
This will take approximately 1 minutes.
value: 39
Error in aggregate.data.frame(as.data.frame(x), ...) :
no rows to aggregate
P.S. The code above works fine while I am on Arch Linux. Currently, I migrated to Debian 12.
Currently using TropFishR
version 1.6.2 (I tried using 1.6.3 but I encountered similar error).
Edit 1: I also tried the 1.6.0 version ("nojags"), but same error.
Edit 2: Same issue when I tried to run it in a virtual machine running Linux Mint and Manjaro.
Edit 3: By the way, here's the data I used: data
Here's the sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 12 (bookworm)
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.21.so; LAPACK version 3.11.0
locale:
[1] LC_CTYPE=en_PH.UTF-8 LC_NUMERIC=C LC_TIME=en_PH.UTF-8 LC_COLLATE=en_PH.UTF-8
[5] LC_MONETARY=en_PH.UTF-8 LC_MESSAGES=en_PH.UTF-8 LC_PAPER=en_PH.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_PH.UTF-8 LC_IDENTIFICATION=C
time zone: Asia/Manila
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] TropFishR_1.6.2 RColorBrewer_1.1-3 data.table_1.14.10 here_1.0.1
loaded via a namespace (and not attached):
[1] crayon_1.5.2 doParallel_1.0.17 cli_3.6.2 zoo_1.8-12 bit_4.0.5 msm_1.7.1 tmvtnorm_1.6
[8] gmm_1.8 rprojroot_2.0.4 ff_4.0.9 stats4_4.3.2 grid_4.3.2 expm_0.999-8 MASS_7.3-60
[15] foreach_1.5.2 mvtnorm_1.2-4 propagate_1.0-6 compiler_4.3.2 codetools_0.2-19 sandwich_3.1-0 Rcpp_1.0.11
[22] GenSA_1.1.12 lattice_0.22-5 parallel_4.3.2 splines_4.3.2 minpack.lm_1.2-4 Matrix_1.6-1.1 tools_4.3.2
[29] iterators_1.0.14 GA_3.2.3 survival_3.5-7
Dear Tobias Mildenberger,
I am having some trobles running "catchCurve" function.
synLFQ7b <- lfqModify(Mydata, vectorise_catch = TRUE, plus_group = 118)
res_cc <- catchCurve(Mydatab, reg_int = c(6,18), calc_ogive = TRUE)###出错了
Error in catchCurve(Mydatab, reg_int = c(6, 18), calc_ogive = TRUE) :
The catch curve with constant time interval is not applicable to length-frequency data. Please provide a catch vector.
warning regarding memory.limit()
might be connected to use of propagate which uses package ff
propagate::predictNLS
currently omitted.
find solution
Good afternoon, it's me again.
I followed your tutorial here, and you presented the code:
# find 3 highest score values
n <- length(res_RSA$score_mat)
best_scores <- sort(res_RSA$score_mat,partial=n-0:2)[n-0:2]
ind <- arrayInd(which(res_RSA$score_mat %in% best_scores),
dim(res_RSA$score_mat))
Ks <- as.numeric(rownames(res_RSA$score_mat)[ind[,1]])
Linfs <- as.numeric(colnames(res_RSA$score_mat)[ind[,2]])
...
But when I entered the first line, and I looked in my environment, n
is 0L
.
I inspected res_RSA
and score_mat
is not present.
I am currently using TropFishR 1.6.0
under Linux Mint 18.3
with R version 3.4.4 (2018-03-15)
.
Dear Tobias Mildenberger,
Thanks a lot for the TropFishR package!!!
I am new with TropFishR.
I appreciate if you could indicate which function I should use to run the "linking of means (to represent the same cohort ) after Bhattacharya's method using lenght frequency data".
revise the lognormal option. Which parameters are required? mu and sigma correspond to mode length and standard deviation? run examples with same dataset "tilapia" using parameters resulting from select() or select_Millar().
Hello! I can't run the example because after clicking in the 2 points of the curve I have an error message.
output <-catchCurve(synLFQ3, calc_ogive = TRUE)
Please choose the minimum and maximum point in the graph
to include for the regression line!
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
In addition: Warning messages:
1: In if (I == which(ind)) { :
the condition has length > 1 and only the first element will be used
2: In min(x) : no non-missing arguments to min; returning Inf
3: In max(x) : no non-missing arguments to max; returning -Inf
Thank you in advance for your response!
Hi @tokami ,
I have been playing around with TropFishR
using some dummy data. Thank you for this package. At this point, I'm getting an error with the following.
> TB1 <- predict_mod(lfq_catch_vec, type = "ThompBell",
+ FM_change = seq(0,1.5,0.05),
+ stock_size_1 = 1,
+ curr.E = lfq_catch_vec$par$E,
+ s_list = selectivity_list,
+ plot = FALSE, hide.progressbar = TRUE)
Error is:
Error in if (!is.na(curr.E)) { : argument is of length zero
In addition: Warning message:
In max(FM, na.rm = TRUE) : no non-missing arguments to max; returning -Inf
My lfq_catch_vec
is below.
> lfq_catch_vec
$dates
[1] "2005-01-01" "2006-01-01" "2007-01-01"
$midLengths
[1] 11 13 15 17 19 21 23 25 27
$catch
X2005 X2006 X2007
V1 5 11 2
V2 22 49 15
V3 66 139 22
V4 106 337 69
V5 166 477 133
V6 243 421 115
V7 209 308 68
V8 112 168 49
V9 105 145 19
$par
$par$Linf
[1] 27.18388
$par$K
[1] 0.7627744
$par$t_anchor
[1] 0.6635739
$par$C
[1] 0.5911645
$par$ts
[1] 0.6136335
$par$phiL
[1] 2.751019
$par$M
[1] 1.136
$par$FM
numeric(0)
$par$E
numeric(0)
$par$a
[1] 0.015
$par$b
[1] 3
$par$Lmat
[1] 35
$par$wmat
[1] 5
attr(,"class")
[1] "lfq"
My data has three years. So this now has three columns. Definitely above I can see that lfq_catch_vec$par$E
is 0
. But why is that? Have I done something suboptimal while generating this object? This is how I generated the lfq_catch_vec
.
## define plus group as largest length class smaller than Linf
plus_group <- lfq_bin2$midLengths[max(which(lfq_bin2$midLengths < lfq_bin2$par$Linf))]
## summarise catch matrix into vector and add plus group
lfq_catch_vec <- lfqModify(lfq_bin2, vectorise_catch = TRUE, plus_group = plus_group)
And this is my lfq_bin2
object.
> lfq_bin2
$dates
[1] "2005-04-15" "2005-05-15" "2005-07-15" "2005-08-15" "2005-09-15"
[6] "2005-10-15" "2005-11-15" "2005-12-15" "2006-01-15" "2006-02-15"
[11] "2006-03-15" "2006-04-15" "2006-05-15" "2006-06-15" "2006-07-15"
[16] "2006-09-15" "2006-10-15" "2006-11-15" "2006-12-15" "2007-01-15"
[21] "2007-02-15" "2007-03-15"
$midLengths
[1] 11 13 15 17 19 21 23 25 27 29 31
$catch
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 3 0 1 0 0 0 0 1 0 3 2 4 0
[2,] 8 1 3 0 3 1 3 3 1 3 7 17 3
[3,] 17 6 6 3 4 4 17 9 7 6 11 31 7
[4,] 16 20 11 6 12 11 16 14 38 15 15 32 20
[5,] 31 27 11 11 20 21 22 23 48 34 35 55 25
[6,] 22 60 45 42 22 21 11 20 41 35 45 49 58
[7,] 22 38 29 30 28 27 21 14 24 28 38 48 38
[8,] 17 18 13 6 23 23 5 7 13 14 20 35 14
[9,] 9 15 11 5 11 11 4 4 2 10 14 19 12
[10,] 6 7 4 2 3 3 1 1 0 5 11 10 12
[11,] 1 2 2 0 1 0 2 0 0 2 4 6 3
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] 0 0 2 0 0 0 1 1 0
[2,] 1 4 5 6 1 1 2 9 4
[3,] 4 15 32 12 11 3 4 5 13
[4,] 7 47 50 30 64 19 31 33 5
[5,] 8 78 44 50 71 29 52 57 24
[6,] 16 67 26 25 41 18 46 41 28
[7,] 10 41 17 26 24 14 28 31 9
[8,] 4 16 6 15 17 14 19 25 5
[9,] 5 7 3 1 6 2 5 5 4
[10,] 3 2 1 0 2 0 2 1 1
[11,] 1 2 0 0 0 0 1 0 0
$par
$par$Linf
[1] 27.18388
$par$K
[1] 0.7627744
$par$t_anchor
[1] 0.6635739
$par$C
[1] 0.5911645
$par$ts
[1] 0.6136335
$par$phiL
[1] 2.751019
$par$M
[1] 1.136
attr(,"class")
[1] "lfq"
You feedback is very much appreciated.
Thanks,
Shani.
Standardize use of Rn_max and fESP throughout ELEFAN, ELEFAN_GA, and ELEFAN_SA. Documentation states that the scores between methods are not comparable, but they should be.
Dear Tobias Mildenberger,
I am having some trobles running "catchCurve" function. I modified my length-frequency data with the "lfqModify" function and, after run catchCurve the programm returns the following message:"Error: "x" must be numeric.". In fact the same message return when I run the examples contained in the help of the catchCurve function. It is maybe possible that the function is not working properly? I thank you in advance.
If you make rtypes_Millar an exported object, then it is useful for others to make a predictive selectivity function for published gillnet selectivity parameters. Alternatively you could make a predict function that works for all models included in select_Millar()
option required for GillnetSelect.R to manually exclude data points with low number of observations from analysis.
idea: identify() from plot with data points + info about number of observations
alternative: threshold number, everything below is excluded
score_mat is not an output of ELEFAN anymore
An example of powell_wetherall() should be included to show how lfq data like synLFQ5 can be translated into the function (i.e. convert to catches for the year)
Good afternoon, I am trying to install the dev2.0
version of TropFishR
, but the installed version is 1.6.0
.
> devtools::install_github('tokami/TropFishR', ref= "dev2.0")
Downloading GitHub repo tokami/[email protected]
✔ checking for file ‘/tmp/RtmpyUxKuq/remotes2d092447bcbe/tokami-TropFishR-50fdbae/DESCRIPTION’ ...
─ preparing ‘TropFishR’:
✔ checking DESCRIPTION meta-information ...
─ checking for LF line-endings in source and make files and shell scripts
─ checking for empty or unneeded directories
─ looking to see if a ‘data/datalist’ file should be added
─ building ‘TropFishR_1.6.0.tar.gz’
I removed the previous version before trying to install the dev2.0
: remove.packages("TropFishR", lib="~/R/x86_64-pc-linux-gnu-library/3.5")
> sessionInfo()
R version 3.5.3 (2019-03-11)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Manjaro Linux
get rid of quartz() and windows(), but this is the best option for identity() function, because after enlarging small GUI window, identify function has problems, hard to hit the points, same problem when using dev.new(), because only new window is created when graph was produced before
Dear developer,
I have problem in run the command ypr. I am using the following code:
devtools::install_github("tokami/TropFishR")
require(TropFishR)
Winf=(0.000006*30)^3.085
m=mean(as.vector(c(0.755, 0.567, 0.483)))
param=list(Linf=30,Winf=Winf,K=0.24,t0=-0.61,M=m,tr=0.25,tc=0.5)
#param a list consisting of following parameters (not all are required):
#• Linf: infinite length in cm,
#• Winf: infinite weight,
#• K: growth coefficent for investigated species per year [1/year],
#• t0: theoretical time zero, at which individuals of this species hatch,
#• M: natural mortality,
#• tr: age of recruitment,
#• tc: age of first capture;
#FM_change vector with ascending fishing mortalities,
#t default NA
ypr(param, FM_change=seq(0,2,0.1))
Thank you in advance for your help,
Isabella
Please share the demo file in excel for each in data
Quang
function to be used for the biomass per recruit calculation with selection ogive other than knife edge. Implemented approach returns negative values...
I am currently conducting research on shrimp stock assessment using the ‘TropFishR’ package to analyze a monthly carapace length frequency dataset. The package allows for the analysis of one year of data, specifically data collected from January to December of a particular year. Sample code for opening the library, working with an Excel file, and opening the dataset from the working directory is provided below:
library(TropFishR)
library(openxlsx)
setwd
data <- read.xlsx("frequency.xlsx")
set.seed(1)
dates <- as.Date(paste0("15-",01:12,"-2022"),format="%d-%m-%Y")
However, if we have more than one year of data, how can we feed it into the ‘TropFishR’ package?
Hi. Firstly thanks for the package!
I am new on R and also TropFishR. I am trying to arrange my data to plot raw catch frequencies. Here is the code I wrote. When run it I get the error message below. What am I missing?
library(TropFishR)
sample.no <- seq(1,9)
dates <- as.Date(c("2017-06-21","2017-07-25","2017-08-22","2017-09-26"))
midLengths <- seq(3.5,11.5,1)
catch <- c(
## 2017-06-21
0,12,15,0,0,0,0,0,0,
## 2017-07-25
0,0,11,13,4,0,0,0,1,
## 2017-08-22
0,0,0,0,14,12,6,0,0,
## 2017-09-26
0,0,3,3,6,15,9,0,0)
catch <- matrix(catch,9,4)
colnames(catch) <- c(17.4166667,17.5,17.5833333,17.6666667)
sc <- list(sample.no,midLengths,dates,catch)
names(sc)<- c("sample.no","midLengths","dates","catch")
attr(sc,"catch")="lfq"
plot(sc, Fname = "catch")
Error in xy.coords(x, y, xlabel, ylabel, log) :
'x' is a list, but does not have components 'x' and 'y'
check + include
QAICc <- function(mod){
ll <- as.numeric(mod$value)
K <- length(mod$estimates[,1])
n <- nnzero(CatchPerNet_mat)
c_hat = as.numeric(mod$out[4]/mod$out[6])
qaicc = -2*ll/c_hat + 2*K + 2*K*(K + 1)/(n - K - 1)
qaicc
}
Hi all,
I have been trying to use TropfishR package In fact, I got the same message below.
Error: package or namespace load failed for ‘TropFishR’ in dyn.load(file, DLLpath = DLLpath, ...):
unable to load shared object '/Library/Frameworks/R.framework/Versions/4.0/Resources/library/gmm/libs/gmm.so':
dlopen(/Library/Frameworks/R.framework/Versions/4.0/Resources/library/gmm/libs/gmm.so, 6): Library not loaded: /usr/local/gfortran/lib/libgomp.1.dylib
Referenced from: /Library/Frameworks/R.framework/Versions/4.0/Resources/library/gmm/libs/gmm.so
Reason: image not found
If you have an idea to fix it and use package, I would be great
Best regards,
Tevfik
edit: Ps : R version 4.0.0 Patched (2020-05-03 r78349) -- "Arbor Day"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (64-bit)
Rn_max scores and seeds are switched when seasonalised ELEFAN is run
how to calculate the parameter------meanvalue
Hi, I'm using Mac device and I was unable to install 'TropFishR' from GitHub and some errors appeared as below:
Installing 23 packages: rlang, digest, backports, diffobj, waldo, ps, callr, brio, cli, R6, labeling, testthat, tibble, xfun, htmlwidgets, sandwich, iterators, data.table, Formula, foreach, ff, RcppArmadillo, doParallel
trying URL 'https://cran.rstudio.com/bin/macosx/contrib/4.0/rlang_0.4.8.tgz'
Error in download.file(url, destfile, method, mode = "wb", ...) :
(converted from warning) URL 'https://cran.rstudio.com/bin/macosx/contrib/4.0/rlang_0.4.8.tgz': status was 'SSL connect error'
Error: Failed to install 'TropFishR' from GitHub:
(converted from warning) download of package ‘rlang’ failed
library(TropFishR)
Error: package or namespace load failed for ‘TropFishR’ in dyn.load(file, DLLpath = DLLpath, ...):
unable to load shared object '/Library/Frameworks/R.framework/Versions/4.0/Resources/library/gmm/libs/gmm.so':
dlopen(/Library/Frameworks/R.framework/Versions/4.0/Resources/library/gmm/libs/gmm.so, 6): Library not loaded: /usr/local/gfortran/lib/libgomp.1.dylib
Referenced from: /Library/Frameworks/R.framework/Versions/4.0/Resources/library/gmm/libs/gmm.so
Reason: image not found
In addition: Warning message:
package ‘TropFishR’ was built under R version 4.0.2
Note that I'm using ''R'' version 4.0.1 (2020-06-06) --
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (64-bit).
would you please help to solve the issues with Mac device.
Thank you.
I am trying to apply the ELEFAN routine to jellyfish, their lifespan oscilates typically from 1 to 4 months making it hard to differenciate between cohorts as some of them might be spaced just for 15 days instead of a whole year. However, for one of the species I am completely sure that for the whole lifespan I only have 1 cohort but when I throw the analysis I receive a ncohort of 4, being it extremely high given the loleny recruitment peak registered for the data. Is it possible to fix the ncohort before running ELEFAN so I can get a K value more consistent with the input data?
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🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.