fabian-s / biosensors.usc Goto Github PK
View Code? Open in Web Editor NEWThis project forked from glucodensities/biosensors.usc
License: GNU General Public License v3.0
This project forked from glucodensities/biosensors.usc
License: GNU General Public License v3.0
W checking whether package ‘biosensors.usc’ can be installed (59.2s)
Found the following significant warnings:
alglib/ap.cpp:9060:16: warning: ‘__builtin___sprintf_chk’ may write a terminating nul past the end of the destination [-Wformat-overflow=]
See ‘/home/fabians/fda/biosensors.usc.Rcheck/00install.out’ for details.
N checking installed package size
installed size is 22.8Mb
sub-directories of 1Mb or more:
extdata 4.8Mb
include 1.3Mb
libs 16.5Mb
N checking top-level files ...
File
LICENSE
is not mentioned in the DESCRIPTION file.
W checking R files for non-ASCII characters ...
Found the following file with non-ASCII characters:
regmod.R
Portable packages must use only ASCII characters in their R code,
except perhaps in comments.
Use \uxxxx escapes for other characters.
N checking R code for possible problems (6.6s)
clustering: no visible global function definition for ‘is’
clustering_prediction: no visible global function definition for ‘is’
clustering_prediction: no visible global function definition for ‘dist’
generate_data: no visible global function definition for ‘runif’
hypothesis_testing: no visible global function definition for ‘is’
load_density_data: no visible global function definition for
‘approxfun’
nadayara_prediction: no visible global function definition for ‘is’
nadayara_regression: no visible global function definition for ‘is’
regmod_regression: no visible global function definition for ‘is’
regmod_regression: no visible global function definition for
‘as.formula’
regmod_regression: no visible global function definition for ‘lm’
ridge_regression: no visible global function definition for ‘median’
wasserstein_regression: no visible global function definition for ‘is’
Undefined global functions or variables:
approxfun as.formula dist is lm median runif
Consider adding
importFrom("methods", "is")
importFrom("stats", "approxfun", "as.formula", "dist", "lm", "median",
"runif")
to your NAMESPACE file (and ensure that your DESCRIPTION Imports field
contains 'methods').
✓ checking for missing documentation entries (1.1s)
W checking for code/documentation mismatches (1.1s)
Functions or methods with usage in documentation object 'clustering_prediction' but not in code:
‘energy_prediction’
Codoc mismatches from documentation object 'nadayara_prediction':
nadayara_prediction
Code: function(nadaraya, Qpred, hs = NULL)
Docs: function(data, response)
Argument names in code not in docs:
nadaraya Qpred hs
Argument names in docs not in code:
data response
Mismatches in argument names:
Position: 1 Code: nadaraya Docs: data
Position: 2 Code: Qpred Docs: response
Codoc mismatches from documentation object 'regmod_regression':
regmod_regression
Code: function(data, predictor)
Docs: function(data, response)
Argument names in code not in docs:
predictor
Argument names in docs not in code:
response
Mismatches in argument names:
Position: 2 Code: predictor Docs: response
Codoc mismatches from documentation object 'ridge_regression':
regmod_regression
Code: function(data, predictor)
Docs: function(data, response)
Argument names in code not in docs:
predictor
Argument names in docs not in code:
response
Mismatches in argument names:
Position: 2 Code: predictor Docs: response
Codoc mismatches from documentation object 'wasserstein_prediction':
wasserstein_prediction
Code: function(reg, xpred)
Docs: function(regression, xpred)
Argument names in code not in docs:
reg
Argument names in docs not in code:
regression
Mismatches in argument names:
Position: 1 Code: reg Docs: regression
W checking Rd \usage sections (2.4s)
Objects in \usage without \alias in documentation object 'clustering_prediction':
‘energy_prediction’
Undocumented arguments in documentation object 'nadayara_prediction'
‘response’
Documented arguments not in \usage in documentation object 'nadayara_prediction':
‘Qpred’ ‘hs’
Documented arguments not in \usage in documentation object 'ridge_regression':
‘w’ ‘method’ ‘type’
Objects in \usage without \alias in documentation object 'ridge_regression':
‘regmod_regression’
Undocumented arguments in documentation object 'wasserstein_prediction'
‘regression’
Documented arguments not in \usage in documentation object 'wasserstein_prediction':
‘reg’
Functions with \usage entries need to have the appropriate \alias
entries, and all their arguments documented.
The \usage entries must correspond to syntactically valid R code.
See chapter ‘Writing R documentation files’ in the ‘Writing R
W checking compilation flags in Makevars ...
Non-portable flags in variable 'PKG_CXXFLAGS':
-Wstrict-aliasing=0 -Wno-unused-but-set-variable -Wno-unused-function -Wno-maybe-uninitialized
W checking for GNU extensions in Makefiles
Found the following file(s) containing GNU extensions:
src/Makevars
Portable Makefiles do not use GNU extensions such as +=, :=, $(shell),
$(wildcard), ifeq ... endif, .NOTPARALLEL See section ‘Writing portable
packages’ in the ‘Writing R Extensions’ manual.
W checking compilation flags used
Compilation used the following non-portable flag(s):
‘-Wno-maybe-uninitialized’ ‘-Wno-unused-but-set-variable’
‘-Wno-unused-function’ ‘-Wstrict-aliasing=0’
including flag(s) suppressing warnings
W checking compiled code ...
File ‘biosensors.usc/libs/biosensors.usc.so’:
Found ‘_ZSt4cout’, possibly from ‘std::cout’ (C++)
Object: ‘biosensors.usc.o’
Found ‘abort’, possibly from ‘abort’ (C)
Object: ‘alglib/ap.o’
Found ‘rand’, possibly from ‘rand’ (C)
Object: ‘alglib/ap.o’
Compiled code should not call entry points which might terminate R nor
write to stdout/stderr instead of to the console, nor use Fortran I/O
nor system RNGs.
E checking examples (2s)
Running examples in ‘biosensors.usc-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: generate_data
> ### Title: generate_data
> ### Aliases: generate_data
>
> ### ** Examples
>
> data = generate_data(n=100, Qp=100, Xp=5)
> names(data)
[1] "data" "densities" "quantiles" "variables"
> header(data$quantiles)
Error in header(data$quantiles) : could not find function "header"
Execution halted
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 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.