I try to use rCharts package to create interactive graphs. I used tutorials examples but I have not managed to use nPlot method. It did not return error but I did not receive the figure as they did in the tutorial.
require(devtools)
install_github('rCharts', 'ramnathv')
library(rCharts)
a<-as.data.frame(HairEyeColor)
hair_eye_male<-subset(a, Sex=="Male")
is.data.frame(hair_eye_male)
n1<-nPlot(Freq~Hair, group='Eye', data=hair_eye_male, type="multiBarChart")
n1
hair_eye = as.data.frame(HairEyeColor)
p2 <- nPlot(Freq ~ Hair, group = 'Eye',
data = subset(hair_eye, Sex == "Female"),
type = 'multiBarChart'
)
p2$chart(color = c('brown', 'blue', '#594c26', 'green'))
p2
in the Environment panel n1 and p2 appeared as Environment. I tried rChart and it works.
Best regards
Related
Hi I am having issues regarding a foreach loop where in every iteration I estimate a regression on a subset of the data with a different list of controls on several outcomes. The problem is that for some outcomes in some countries I only have missing values and therefore the regression function returns an error message. I would like to be able to run the loop, get the output with NAs or a string saying "Error" for example instead of the coefficient table. I tried several things but they don't quite work with the .combine = rbind option and if I use .combine = c I get a very messy output. Thanks in advance for any help.
reg <- function(y, d, c){
if (missing(c))
feols(as.formula(paste0(y, "~ 0 + treatment")), data = d)
else {
feols(as.formula(paste0(y, "~ 0 + treatment + ", c)), data = d)
}
}
# Here we set up the parallelization to run the code on the server
n.cores <- 9 #parallel::detectCores() - 1
#create the cluster
my.cluster <- parallel::makeCluster(
n.cores,
type = "PSOCK"
)
# print(my.cluster)
#register it to be used by %dopar%
doParallel::registerDoParallel(cl = my.cluster)
# #check if it is registered (optional)
# foreach::getDoParRegistered()
# #how many workers are available? (optional)
# foreach::getDoParWorkers()
# Here is the cycle to parallel regress each outcome on the global treatment
# variable for each RCT with strata control
tables <- foreach(
n = 1:9, .combine = rbind, .packages = c('data.table', 'fixest'),
.errorhandling = "pass"
) %dopar% {
dt_target <- dt[country == n]
c <- controls[n]
est <- lapply(outcomes, function(x) reg(y = x, d = dt_target, c))
table <- etable(est, drop = "!treatment", cluster = "uid", fitstat = "n")
table
}
i am new with f# , will be great if some 1 can help , nearly half a day gone solving this problem Thank you
module Certificate =
type T = {
Id: int
IsECert: bool
IsPrintCert: bool
CertifiedBy: string
Categories: Category.T list
}
let createPending now toZonedDateTime toBeCertifiedByName (job: Models.Job.T) (certificateType: Models.CertificateType.T) (pendingCertificate: Models.PendingCertificate.T) visualization (categories: Category.T list) =
let forCompletion = Models.PendingCertificate.getCertificateForCompletion pendingCertificate
{
Id = forCompletion.Id |> CertificateId.toInt
IsECert = Models.PendingCertificate.isECertificate pendingCertificate
IsPrintCert = Models.PendingCertificate.isPrintCertificate pendingCertificate
CertifiedBy = toBeCertifiedByName
Categories = categories}
i am getting an error in "Incomplete structured construct at or before this point"
Your formatting is all off. I will assume here that this is just a result of posting to StackOverflow, and your actual code is well indented.
The error comes from the definition of createPending: this function does not have a result. All its body consists of defining a forCompletion value, but there is nothing after it. Here's a simpler example that has the same problem:
let f x =
let y = 5
This function will produce the same error, because it also doesn't have a result. In F#, every function has to return something. The body cannot contain only definitions of helper functions or values. For example, I could fix my broken function above like this:
let f x =
let y = 5
x + y
This function first defines a helper value y, then adds it to its argument x, and returns the result.
> f 2
> 7
>
> f 0
> 5
How exactly you need to fix your function depends on what exactly you want it to mean. I can't help you here, because you haven't provided that information.
There is oriented graph:
We are adding node and edge to it:
and then removing some other (by the algorithm, it doesn't matter here):
I had tried to do this in F#, but I cannot choose properly architecture decisions because of my little experience.
open System.Collections.Generic
type Node = Node of int
type OGraph(nodes : Set<Node>,
edges : Dictionary<Node * int, Node>) =
member this.Nodes = nodes
member this.Edges = edges
let nodes = set [Node 1; Node 2; Node 3]
let edges = Dictionary<Node * int, Node>()
Array.iter edges.Add [|
(Node 1, 10), Node 2;
(Node 2, 20), Node 3;
|]
let myGraph = OGraph(nodes, edges)
myGraph.Nodes.Add (Node 4)
myGraph.Edges.Add ((Node 2, 50), Node 4)
myGraph.Edges.Remove (Node 2, 20)
myGraph.Nodes.Remove (Node 3)
How to add empty node? I mean, it may be 3 or 4 or even 100500. If we add node without number, then how we can use it to create edge? myGraph.Edges.Add ((Node 2, 50), ???) In imperative paradigm it would be simple because of using named references and Nulls, we can just create Node newNode = new Node() and then use this reference newNode, but seems that in F# this is a bad practice.
Should I specify separate types Node and Edge or use simple types instead? Or may be some other representation, more complicated?
It is better to use common .NET mutable collections (HashSet, Dictionary etc.), or special F# collections (Set, Map, etc.)? If collections are large, it is acceptable in terms of performance to copy entire collection every time it should be changed?
The graph itself is easy enough to model. You could define it like this:
type Graph = { Node : int option; Children : (int * Graph) list }
If you will, you can embellish it more, using either type aliases or custom types instead of primitive int values, but this is the basic idea.
You can model the three graphs pictured in the OP like the following. The formatting I've used looks quite verbose, but I deliberately formatted the values this way in order to make the structure clearer; you could write the values in a more compact form, if you'd like.
let x1 =
{
Node = Some 1;
Children =
[
(
10,
{
Node = Some 2;
Children =
[
(
20,
{
Node = Some 3;
Children = []
}
)
]
}
)
]
}
let x2 =
{
Node = Some 1;
Children =
[
(
10,
{
Node = Some 2;
Children =
[
(
20,
{
Node = Some 3;
Children = []
}
);
(
50,
{
Node = None;
Children = []
}
)
]
}
)
]
}
let x3 =
{
Node = Some 1;
Children =
[
(
10,
{
Node = Some 2;
Children =
[
(
50,
{
Node = Some 3;
Children = []
}
)
]
}
)
]
}
Notice the use of int option to capture whether or not a node has a value.
The Graph type is an F# record type, and uses the F# workhorse list for the children. This would be my default choice, and only if performance becomes a problem would I consider other data types. Lists are easy to work with.
Sine if these are easy:
Use Option - then an empty node is None
Maybe - depends on problem
This depends on your specific problem you are solving - the F# collections tend to be immutable and some operations are fast, but the .NET collections have other operations which are fast.
I am using the pc-stable from the package ‘pcalg’ version 2.0-10 to learn the structure . what I understand this algorithm does not effect the the order of the input data because it is order_independent. when I run it with different order ,I got different graph. can any one help me with this issue and this is my code.
library(pracma)
randindexMatriax <- matrix(0,10,ncol(TrainData))
numberUnique_val_col = vector()
pdf("Graph for Test PC Stable with random order.pdf")
par(mfrow=c(2,1))
for (i in 1:10)
{
randindex<-randperm(1:ncol(TrainData))
randindexMatriax[i,]<-randindex
TrainDataRandOrder<-data[,randindex]
V <- colnames( TrainDataRandOrder)
UD <-data.frame(TrainDataRandOrder)
numberUnique_val_col= sapply(UD,function(x)length(unique(x)))
suffStat <- list(dm = TrainDataRandOrder,nlev = c(numberUnique_val_col[1],numberUnique_val_col[2], numberUnique_val_col[3],numberUnique_val_col[4],
numberUnique_val_col[5],numberUnique_val_col[6], numberUnique_val_col[7],
numberUnique_val_col[8],numberUnique_val_col[9],
numberUnique_val_col[10],numberUnique_val_col[11],
numberUnique_val_col[12],numberUnique_val_col[13],
numberUnique_val_col[14],numberUnique_val_col[15],
numberUnique_val_col[16],numberUnique_val_col[17],
numberUnique_val_col[18],numberUnique_val_col[19], numberUnique_val_col[20]), adaptDF = FALSE)
pc.fit <- pc(suffStat, indepTest= disCItest, alpha=0.01, labels=V, fixedGaps = NULL, fixedEdges = NULL,NAdelete = TRUE, m.max = Inf,skel.method = "stable", conservative = TRUE,solve.confl = TRUE, verbose = TRUE)
The "Stable" part of PC-Stable only affects the Skeleton phase of the algorithm. The Orientation phase is still order-dependent. Do the two graphs have identical "skeletons"? That is, if you convert all directed edges into undirected edges, are the two graphs identical?
If not, you may have uncovered a bug in pcalg! Please post a sample dataset and two orderings of the columns that produce graphs with different skeletons.
does anyone know how i set 2i to object that created with riak_object
OBJ = riak_object:new()
i want to work with riak local client and i trying to do something similar to this:
Obj1 = riakc_obj:new(Bucket, UniqKey, Tablet),
MD1 = riakc_obj:get_update_metadata(Obj1),
MD2 = riakc_obj:set_secondary_index(MD1, {{integer_index, IdxTS}, [FirstTS, LastTS]}),
Obj2 = riakc_obj:update_metadata(Obj1, MD2)
but i can't found something similar in riak_object module, i only found examples on how to query 2i not how to set it.
Thanks
{ok, C} = riak:local_client(),
O = riak_object:new(<<"bucket">>, <<"key">>, <<"hello">>),
O2 = riak_object:update_metadata(
O,
dict:from_list([{<<"index">>, [{<<"my_index_bin">>, <<"index_key">>}]}])
),
C:put(O2).