Related
Let's say I have the following ParamSet object:
my_ps = paradox::ps(
minsplit = p_int(1, 64, logscale = TRUE),
cp = p_dbl(1e-04, 1, logscale = TRUE))
Is it possible to rename minsplit to survTree.minsplit without changing anything else?
The reason for this is that I use some learners as part of a GraphLearner and so their parameters names changed and I would like to have some code that adds the learner$id in front the parameters to use later for tuning (rather than rewriting them from scratch with the new names)
I think I have a partial solution here. It is only partial, because it does not support the transformation.
Where it works:
library(paradox)
my_ps = paradox::ps(
minsplit = p_int(1, 64),
cp = p_dbl(1e-04, 1)
)
my_ps$set_id = "john"
my_psc = ParamSetCollection$new(list(my_ps))
print(my_psc)
#> <ParamSetCollection>
#> id class lower upper nlevels default value
#> 1: john.minsplit ParamInt 1e+00 64 64 <NoDefault[3]>
#> 2: john.cp ParamDbl 1e-04 1 Inf <NoDefault[3]>
Created on 2022-12-07 by the reprex package (v2.0.1)
Where it does not:
library(paradox)
my_ps = paradox::ps(
minsplit = p_int(1, 64, logscale = TRUE),
cp = p_dbl(1e-04, 1)
)
my_ps$set_id = "john"
my_psc = ParamSetCollection$new(list(my_ps))
#> Error in .__ParamSetCollection__initialize(self = self, private = private, : Building a collection out sets, where a ParamSet has a trafo is currently unsupported!
Created on 2022-12-07 by the reprex package (v2.0.1)
The underlying problem is that we did not solve the problem of how to reconcile the parameter transformations of individual ParamSets and a possible parameter transformation of the ParamSetCollection
I fear that there is currently no neat solution for your problem.
Sorry I can not comment yet, this is not exactly the solution you are looking for but I hope this will fix the problem you are having.
You can set the param_space in the learner, before putting it in the graph, i.e. sticking with your search space. After you create the GraphLearner regularly it will have the desired search space.
A concrete example:
library(mlr3verse)
learner = lrn("regr.rpart", cp = to_tune(0.1, 0.2))
glrn = as_learner(po("pca") %>>% po("learner", learner))
at = auto_tuner(
"random_search",
glrn,
rsmp("holdout"),
term_evals = 10
)
task = tsk("mtcars")
at$train(task)
As far as I can find, there is only one tutorial about loading Seurat objects into WGCNA (https://ucdavis-bioinformatics-training.github.io/2019-single-cell-RNA-sequencing-Workshop-UCD_UCSF/scrnaseq_analysis/scRNA_Workshop-PART6.html). I am really new to programming so it's probably just my inexperience, but I am not sure how to load my Seurat object into a format that works with WGCNA's tutorials (https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/).
Here is what I have tried thus far:
This tries to replicate datExpr and datTraits from part I.1:
library(WGCNA)
library(Seurat)
#example Seurat object -----------------------------------------------
ERlist <- list(c("CPB1", "RP11-53O19.1", "TFF1", "MB", "ANKRD30B",
"LINC00173", "DSCAM-AS1", "IGHG1", "SERPINA5", "ESR1",
"ILRP2", "IGLC3", "CA12", "RP11-64B16.2", "SLC7A2",
"AFF3", "IGFBP4", "GSTM3", "ANKRD30A", "GSTT1", "GSTM1",
"AC026806.2", "C19ORF33", "STC2", "HSPB8", "RPL29P11",
"FBP1", "AGR3", "TCEAL1", "CYP4B1", "SYT1", "COX6C",
"MT1E", "SYTL2", "THSD4", "IFI6", "K1AA1467", "SLC39A6",
"ABCD3", "SERPINA3", "DEGS2", "ERLIN2", "HEBP1", "BCL2",
"TCEAL3", "PPT1", "SLC7A8", "RP11-96D1.10", "H4C8",
"PI15", "PLPP5", "PLAAT4", "GALNT6", "IL6ST", "MYC",
"BST2", "RP11-658F2.8", "MRPS30", "MAPT", "AMFR", "TCEAL4",
"MED13L", "ISG15", "NDUFC2", "TIMP3", "RP13-39P12.3", "PARD68"))
tnbclist <- list(c("FABP7", "TSPAN8", "CYP4Z1", "HOXA10", "CLDN1",
"TMSB15A", "C10ORF10", "TRPV6", "HOXA9", "ATP13A4",
"GLYATL2", "RP11-48O20.4", "DYRK3", "MUCL1", "ID4", "FGFR2",
"SHOX2", "Z83851.1", "CD82", "COL6A1", "KRT23", "GCHFR",
"PRICKLE1", "GCNT2", "KHDRBS3", "SIPA1L2", "LMO4", "TFAP2B",
"SLC43A3", "FURIN", "ELF5", "C1ORF116", "ADD3", "EFNA3",
"EFCAB4A", "LTF", "LRRC31", "ARL4C", "GPNMB", "VIM",
"SDR16C5", "RHOV", "PXDC1", "MALL", "YAP1", "A2ML1",
"RP1-257A7.5", "RP11-353N4.6", "ZBTB18", "CTD-2314B22.3", "GALNT3",
"BCL11A", "CXADR", "SSFA2", "ADM", "GUCY1A3", "GSTP1",
"ADCK3", "SLC25A37", "SFRP1", "PRNP", "DEGS1", "RP11-110G21.2",
"AL589743.1", "ATF3", "SIVA1", "TACSTD2", "HEBP2"))
genes = c(unlist(c(ERlist,tnbclist)))
mat = matrix(rnbinom(500*length(genes),mu=500,size=1),ncol=500)
rownames(mat) = genes
colnames(mat) = paste0("cell",1:500)
sobj = CreateSeuratObject(mat)
sobj = NormalizeData(sobj)
sobj$ClusterName = factor(sample(0:1,ncol(sobj),replace=TRUE))
sobj$Patient = paste0("Patient", 1:500)
sobj = AddModuleScore(object = sobj, features = tnbclist,
name = "TNBC_List",ctrl=5)
sobj = AddModuleScore(object = sobj, features = ERlist,
name = "ER_List",ctrl=5)
#WGCNA -----------------------------------------------------------------
sobjwgcna <- sobj
sobjwgcna <- FindVariableFeatures(sobjwgcna, selection.method = "vst", nfeatures = 2000,
verbose = FALSE, assay = "RNA")
options(stringsAsFactors = F)
sobjwgcnamat <- GetAssayData(sobjwgcna)
datExpr <- t(sobjwgcnamat)[,VariableFeatures(sobjwgcna)]
datTraits <- sobjwgcna#meta.data
datTraits = subset(datTraits, select = -c(nCount_RNA, nFeature_RNA))
I then copy-paste the code as written in the WGCNA I.2a tutorial (https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/FemaleLiver-02-networkConstr-auto.pdf), and that all works until I get to this line in the I.3 tutorial (https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/FemaleLiver-03-relateModsToExt.pdf):
MEList = moduleEigengenes(datExpr, colors = moduleColors)
Error in t.default(expr[, restrict1]) : argument is not a matrix
I tried converting both moduleColors and datExpr into a matrix with as.matrix(), but the error still persists.
Hopefully this makes sense, and thanks for reading!
So doing as.matrix(datExpr) right after datExpr <- t(sobjwgcnamat)[,VariableFeatures(sobjwgcna)] worked. I had been trying it right before MEList = moduleEigengenes(datExpr, colors = moduleColors)
and that didn't work. Seems simple but order matters I guess.
I am attempting to create a table which has citations built into the table. Here is a visual of what I am trying to achieve.
As far as I know you can only add footnotes in rowvars or colvars in kableExtra (love that package).
# Create a dataframe called df
Component <- c('N2','P3')
Latency <- c('150 to 200ms', '625 to 800ms')
Location <- c('FCz, Fz, Cz', 'Pz, Oz')
df <- data.frame(Component, Latency, Location)
Below is my attempt after reading through kableExtra's Git page
# Trying some code taken from the kableExtra guide
row.names(df) <- df$Component
df[1] <- NULL
dt_footnote <- df
names(dt_footnote)[1] <- paste0(names(dt_footnote)[2],
footnote_marker_symbol(1))
row.names(dt_footnote)[2] <- paste0(row.names(dt_footnote)[2],
footnote_marker_alphabet(1))
kable(dt_footnote, align = "c",
# Remember this escape = F
escape = F, "latex", longtable = T, booktabs = T, caption = "My Table Name") %>%
kable_styling(full_width = F) %>%
footnote(alphabet = "Jones, 2013",
symbol = "Footnote Symbol 1; ",
footnote_as_chunk = T)
But this code only works on the headers. The ultimate goal would be if I could use a BibTex reference such as #JonesFunctionalMixedEffectModels2013 such that the final part of the code would look like
footnote(alphabet = #davidsonFunctionalMixedEffectModels2009,
symbol = "Footnote Symbol 1; ", footnote_as_chunk = T)
Anyone have any ideas?
Thanks
What I did at the end was to generate a temporary table with pander, then copy the references' number manually to my kable
pander(
df,
caption = "Temporal",
style = "simple",
justify = "left")
I want to display a decomposition wavelet in 3 level.
so can any help me in give a Matlab function to display it?
[cA cH cV cD]=dwt2(a,waveletname);
out=[cA cH;cV cD];
figure;imshow(out,[]);
That only works for the first level.
actually, I want to representation square mode such wavemenu in Matlab.
example of the view decomposition
I am fairly new to it.
thanx.
You should use the function wavedec2(Image,numberOfLevels,'wname') with the amount of levels that you need.
For more information look at
http://www.mathworks.com/help/wavelet/ref/wavedec2.html
Code for example with db1
clear all
im = imread('cameraman.tif');
[c,s] = wavedec2(im,3,'db1');
A1 = appcoef2(c,s,'db1',1);
[H1,V1,D1] = detcoef2('all',c,s,1);
A2 = appcoef2(c,s,'db1',2);
[H2,V2,D2] = detcoef2('all',c,s,2);
A3 = appcoef2(c,s,'db1',3);
[H3,V3,D3] = detcoef2('all',c,s,3);
V1img = wcodemat(V1,255,'mat',1);
H1img = wcodemat(H1,255,'mat',1);
D1img = wcodemat(D1,255,'mat',1);
A1img = wcodemat(A1,255,'mat',1);
V2img = wcodemat(V2,255,'mat',1);
H2img = wcodemat(H2,255,'mat',1);
D2img = wcodemat(D2,255,'mat',1);
A2img = wcodemat(A2,255,'mat',1);
V3img = wcodemat(V3,255,'mat',1);
H3img = wcodemat(H3,255,'mat',1);
D3img = wcodemat(D3,255,'mat',1);
A3img = wcodemat(A3,255,'mat',1);
mat3 = [A3img,V3img;H3img,D3img];
mat2 = [mat3,V2img;H2img,D2img];
mat1 = [mat2,V1img;H1img,D1img];
imshow(uint8(mat1))
The final result
Hi I want to solve three equation, please find the details in picture. I want to find the value of alpha, h and Q in terms of alpha and h how do i do this using Maxima?
[B1=\frac{{{h}^{2}}}{\mathit{Qs}}]
[B2={{h}^{2}}+\alpha+1]
[B3=\frac{1}{\mathit{Qs}}]
[B0={{h}^{2}}]
[C2=\frac{{{h}^{4}}}{{{\mathit{Qs}}^{2}}}-2{{h}^{2}}\,\left( {{h}^{2}}+\alpha+1\right) =0]
[C4={{\left( {{h}^{2}}+\alpha+1\right) }^{2}}-\frac{2{{h}^{2}}}{{{\mathit{Qs}}^{2}}}-2{{h}^{2}}=0]
[C6=\frac{1}{{{\mathit{Qs}}^{2}}}-2\left( {{h}^{2}}+\alpha+1\right) =0]
algsys([C2,C4,C6],[h,alpha,Qs]);?????
I see that by just adding QS to the list of variables to solve for, I get some solutions. I didn't check them. Some of them may be redundant, I didn't check that either.
(%i20) algsys ([C2, C4, C6], [h, alpha, QS]);
(%o20) [[h = -1,alpha = -(2^(3/2)-2)/(sqrt(2)-2),QS = sqrt(2-sqrt(2))/2],
[h = 1,alpha = -(2^(3/2)-2)/(sqrt(2)-2),QS = sqrt(2-sqrt(2))/2],
[h = -1,alpha = -(2^(3/2)-2)/(sqrt(2)-2),QS = -sqrt(2-sqrt(2))/2],
[h = 1,alpha = -(2^(3/2)-2)/(sqrt(2)-2),QS = -sqrt(2-sqrt(2))/2],
[h = -1,alpha = -(2^(3/2)+2)/(sqrt(2)+2),QS = sqrt(sqrt(2)+2)/2],
[h = 1,alpha = -(2^(3/2)+2)/(sqrt(2)+2),QS = sqrt(sqrt(2)+2)/2],
[h = -1,alpha = -(2^(3/2)+2)/(sqrt(2)+2),QS = -sqrt(sqrt(2)+2)/2],
[h = 1,alpha = -(2^(3/2)+2)/(sqrt(2)+2),QS = -sqrt(sqrt(2)+2)/2]]
Try replacing h^2 with a single variable, say h2 (and replace h^4 with h2^2).
Try simplifying the equations with expand and/or ratsimp.
In solve(eqns, vars), the variables vars are the ones you are trying to solve for. So I think you want alpha, h, Q (well, actually alpha, h2, Q if you follow my previous advice).
Finally, PLEASE paste your input and output into the question instead of linking to an image, which makes it much more difficult for someone else to try working with your equations.