WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
Describe the bug

I'm trying to use an import map in my Deno project. I set up the import map like:

{
"imports": {
"interfaces/": "./interfaces/",
}
}

But when in another file I type:

import { IEnergyMeterValidator } from "interfaces/validators/mod.ts";

It shows the following error:

relative import path "interfaces/validators/mod.ts" not prefixed with / or ./ or ../ Imported from "file:///c%3A/Users/anton/Documents/inversor/validators/EnergyMeterValidator.ts"deno(invalid-specifier)

All those files exist and if I run the command deno run --import-map=import_map.json validators\EnergyMeterValidator.ts from the command line it works great.

Here is my vscode configuration:

{
"deno.enable": true,
"deno.lint": true,
"deno.unstable": true,
"deno.importMap": "./import_map.json"
}

To Reproduce

Recreate the file structure described above.

Copy my vscode configuration in vscode.

Copy my import_map.json.

Go to EnergyMeterValidator.ts and see the import line in red.

Expected behavior

The error should not be shown and the import map should be taken into account.

Versions

vscode: 1.54.3

deno: 1.8.2

extension: 3.2.0

Issue 2:
(EDIT: See comments below, this goes beyond import maps, there's a mismatch in how paths are encoded between the extension and the LSP on Windows)

I'm using an import map to remap .js imports to .ts in code I share between the browser and Deno.

It is working fine in Deno, but the extension reports the following errors:

Unable to load a local module: "file:///c%3A/vscode-deno-import-map/browser/secondary.js".
Please check the file path.

and

Property 'value' does not exist on type 'typeof import("file:///c%3A/vscode-deno-import-map/browser/shared")'.

To Reproduce

See screenshot below or minimal repro here: https://github.com/elisee/vscode-deno-import-map

Expected behavior

The import map should be properly applied by the extension and there should be no errors.

Screenshots

Versions

vscode: v1.53.2

deno: v1.8.0

extension: v3.1.0

os: windows (seems important, see comment below)
Issue 1:
VSCode Version: 0.10.11

OS Version: Windows 7, 10, Mac 10.11.4

Steps to Reproduce:

Start VS Code

Type a for loop without a spaced condition i.e j< 10

Issue 2:
VSCode Version: 1.1.1

OS Version: Windows 7

Hi, in my work environment only certain user agents are allowed to make http(s) requests, so I can't download any extension (getaddrinfo ENOTFOUND marketplace.visualstudio.com marketplace.visualstudio.com:443).

I had the same issue with package control for Sublime Text and there you can set a custom user agent string (https://packagecontrol.io/docs/settings) for the downloader.

Can you please implement that for VS Code?

Related: #262
Issue 1:
I'd like to let the user control whether or not to download the update. User may be using a mobile connection for all we know (tethered), so downloading automatically is not something that should happen without user consent. (same for installing automatically)

Issue 2:
Electron version: 0.36.8

Operating system: OSX

Atom has a setting core.automaticallyUpdate, when it's false, we don't check for updates. It would be nice to be able to periodically check if there is an update available, report the version to the user, but without auto-downloading the new update.

This would allow us to provide a mechanism to users to control when they spend that bandwidth, which is a problem for people on data plans. See the manual update section of atom/about#12 (comment) for what this would look like in atom.

Not sure on what the interface could be. Maybe a boolean in checkForUpdates()? Maybe also some data in the update-available event indicating whether or not the update is being downloaded? Just riffing here.
Issue 1:
Since my question is lost in stackoverflow, I decided to post it here as a bug, as I think it is.

http://stackoverflow.com/questions/38342266/shadowmap-cant-detect-all-instances-on-three-instancedbuffergeometry

Basically the idea is having one bufferGeometry duplicated and having an attribute array with the offsets of my objects (like they have in the above example).

If I try to add shadows, I only get shadows on 1 object, which I assume is because we only have 1 geometry.

Is there a way of adding shadows to all my objects?

Issue 2:
Description of the problem

It is possible for one object/group to have multiple materials, e.g. to have 12 faces of material A and next 12 faces of material B. Current implementation does not handle it properly.

I changed OBJLoader.js, now it creates not one mesh per object, but one mesh per tuple (object name, group name, material name, material smoothness), named 'o:foo,g:bar,usemtl:baz,s:[01]'. This way there is still one material per mesh, but more than one mesh per object/group, albeit with somewhat convoluted names.

I don't know how to make an attachment in this issue tracker (I'm new to github), so I share that externally and provide links:

http://gnu.univ.gda.pl/~grzes/three.js/OBJLoader.js

http://gnu.univ.gda.pl/~grzes/three.js/OBJLoader.js.diff

Three.js version

Dev

r75

...

Browser

All of them

Chrome

Firefox

Internet Explorer

OS

All of them

Windows

Linux

Android

IOS

Hardware Requirements (graphics card, VR Device, ...)
Issue 1:
Running scipy.stats.kendalltau on attached data gives tau = 0.12017 and two-tailed p = 0.0666

Running same test (kenall tau-b) in R (cor.test), SPSS (NONPAR CORR) and the Excel Real-Statistics addin gives same value of tau but p = 0.099 in all 3 packages.

fmmnonzero.txt

Issue 2:
The null statistics for kendall's τ is very different in the case of ties. Presently, the code computes τ and then applies the null statistics for the tieless case to the general case, leaving people really puzzled.

I have created a pull request that improves performance and fixes a few problems, putting again the code in line with that we developed at the LAW (which was used in 2009). In doing so, I set up things so that a p-value of NaN is returned in case of ties, as the present situation is most dangerous.

I'm ready to help to modify the code so that it computes the pieces of information that the real null statistic needs, but I need a statistician to check the theoretical part. (IANS)
Issue 1:
Upgrading 1.7.1 to 1.7.2 with RPM causes postun script failed.

$ sudo rpm -Uvh elasticsearch-1.7.2.noarch.rpm
warning: elasticsearch-1.7.2.noarch.rpm: Header V4 RSA/SHA1 Signature, key ID d88e42b4: NOKEY
Preparing... ################################# [100%]
Updating / installing...
1:elasticsearch-1.7.2-1 ################################# [ 50%]
Cleaning up / removing...
2:elasticsearch-1.7.1-1 ################################# [100%]
post remove script called with unknown argument `1'
warning: %postun(elasticsearch-1.7.1-1.noarch) scriptlet failed, exit status 1

My environment is here.

$ lsb_release -a
LSB Version: :base-4.0-amd64:base-4.0-noarch:core-4.0-amd64:core-4.0-noarch:printing-4.0-amd64:printing-4.0-noarch
Distributor ID: AmazonAMI
Description: Amazon Linux AMI release 2015.03
Release: 2015.03
Codename: n/a
$ rpm --version
RPM version 4.11.2

Issue 2:
From https://discuss.elastic.co/t/1-7-1-rpm-warns-post-remove-script-called-with-unknown-argument/26693:

$ ESVERSION=1.7.1
$ package=elasticsearch-$ESVERSION.noarch.rpm && wget https://download.elasticsearch.org/elasticsearch/elasticsearch/$package -O /tmp/$package && sudo rpm -Uvh /tmp/$package
--2015-08-02 20:27:24-- https://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.7.1.noarch.rpm
Resolving download.elasticsearch.org... 174.129.211.252, 174.129.224.133, 23.21.179.119, ...
Connecting to download.elasticsearch.org|174.129.211.252|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 27323419 (26M) [application/x-redhat-package-manager]
Saving to: “/tmp/elasticsearch-1.7.1.noarch.rpm”

100%[===================================================>] 27,323,419 8.56M/s in 3.0s

2015-08-02 20:27:27 (8.56 MB/s) - “/tmp/elasticsearch-1.7.1.noarch.rpm” saved [27323419/27323419]

warning: /tmp/elasticsearch-1.7.1.noarch.rpm: Header V4 RSA/SHA1 Signature, key ID d88e42b4: NOKEY
Preparing... ########################################### [100%]
1:elasticsearch ########################################### [100%]
post remove script called with unknown argument `1'
warning: %postun(elasticsearch-1.7.0-1.noarch) scriptlet failed, exit status 1

Reported on Centos 6 and RHEL 6.6.
Issue 1:
Code Sample

url = """https://en.wikipedia.org/wiki/List_of_winners_of_the_Boston_Marathon"""

tables = pd.read_html(url, header=0)

print(tables[0].head())

Problem description

The above code ''should' just extract the displayed text in the HTML table; what's in the dataframe should be what's displayed on screen. This isn't what happens. If the HTML contains a hyperlink with a title attribute, this is picked up and added to the dataframe, duplicating the data.

Expected Output

Year Athlete \
0 1897 John J. McDermott
1 1898 Ronald J. MacDonald
2 1899 Lawrence Brignolia
3 1900 John "Jack" Caffery
4 1901 John "Jack" Caffery

Country/State Time Notes
0 United States (NY) 2:55:10 NaN
1 Canada Canada 2:42:00 NaN
2 United States (MA) 2:54:38 NaN
3 Canada 2:39:44 NaN
4 Canada 2:29:23 2nd victory

Output

Here's the actual output, the duplication is in the Athlete and Country/State columns.

Year Athlete
0 1897 McDermott, John J.John J. McDermott
1 1898 MacDonald, Ronald J.Ronald J. MacDonald
2 1899 Brignolia, LawrenceLawrence Brignolia
3 1900 Caffery, JohnJohn "Jack" Caffery
4 1901 Caffery, JohnJohn "Jack" Caffery

Country/State Time Notes
0 United States United States (NY) 2:55:10 NaN
1 Canada Canada 2:42:00 NaN
2 United States United States (MA) 2:54:38 NaN
3 Canada Canada 2:39:44 NaN
4 Canada Canada 2:29:23 2nd victory

Issue 2:
It seems that the apply method of a group invokes the function passed as parameter once for each group, as expectes. However, the function is invoked twice for the first group. Enclose is a short code reproducing this behavior. Is it a normal behavior or am I doing something wrong here.

I run the code with pandas 0.10.0 on. Windows 7, 32 bit version.

The code reproducing this behavior:

import pandas as pd

tdf = pd.DataFrame( { 'cat' : [1,1,1,2,2,1,1,2], 'B' : range(8)})

category = tdf['cat']

pGroups = tdf.groupby(by=category)

def getLen(df) :

print 'len ',len(df)

return len(df)

plen = pGroups.apply(getLen)
Issue 1:
This auto-formatted incorrectly

[
'two spaces indent',
{} //object placed two spaces to the left, expected to have the same indentation as text
]

Issue 2:
A gif probably explains it best:

Firstly, I'd contend that the ]) shouldn't be automatically indented, but I can live with that.

Main point: the {whatever} line automatically outdents as soon as I type the first { (presumably because it thinks it's opening a block rather than an object), and then continually tries to outdent whenever I type any more characters on the line (the re-indentation in the gif is me hitting ctrl+])

Been happening in atom --safe built off master for the last couple of days, presumably since the update to language-javascript@0.51 in relation to e38f1cd
Issue 1:
💻

Would you like to work on a fix?

How are you using Babel?

@babel/cli

Input code

Error occurring after installed latest @babel/core

Configuration file name

babel.config.js

Configuration

No response

Current and expected behavior

Getting error

Cannot find module '@babel/plugin-proposal-private-property-in-object'

Environment

Babel version: latest (7.22.0)

Node: 16

yarn v1.22.19

Mac OS Venutura / Ubuntu 22.0.4

Possible solution

It's working fine after I installed @babel/plugin-proposal-private-property-in-object .

yarn add @babel/plugin-proposal-private-property-in-object --dev

Additional context

Seems the latest release 7.22.0 has an issue.

It was working properly until few hours ago.

Issue 2:
Originally from babel/karma-babel-preprocessor#5

With to5Options.moduleIds: true module names are including the entire path. I tried setting the sourceRoot, but then the path was duplicated before the desired module portion.

The only way I was able to get just the module portion was to add filenameRelative to the per file options and assign it a function to strip the initial path. I feel like I'm missing something simple over this being a bug. Thoughts?

Not sure if this matters, but I am on windows.
Issue 1:
Symfony version(s) affected: 3.4.22

Description

A new entity was found through the relationship 'XXX#hcspData' that was not configured to cascade persist operations for entity: HCSPData@0000000023d966fc0000000028e438d7. To solve this issue: Either explicitly call EntityManager#persist() on this unknown entity or configure cascade persist this association in the mapping for example @manytoone(..,cascade={"persist"}). If you cannot find out which entity causes the problem implement 'HCSPData#__toString()' to get a clue.

How to reproduce

HCSPData is fetched in service, this service is used in Subscriber pinned with Doctrine prePersist.

It was like that since I remember.

Updating Symfony version resulted in above error. Lowering version to .21 and everything works again.

Doctrine package is the same, so I believe this is not Doctrine problem.

For 3.4.21

$entityManager->contains($documentEntity) // true

EntityManager { #540 // where HCSPData is fetched

EntityManager { #540 // where XXX is flushed

For 3.4.22

$entityManager->contains($documentEntity) // false

EntityManager { #540 // where HCSPData is fetched

EntityManager { #559 // where XXX is flushed

What i found - EntityManager fetching HCSPData and EntityManager creating new entity in 3.4.21 is the same object, but in 3.4.22 they are not. You had to made change that is breaking DI object injecting. Both service & subscriber are fetching EM same way: public function __construct(EntityManagerInterface $entityManager)

After some digging I found this:

b3e17d2

Reverting changes from this commit done by @mmarynich makes everything work again.

Issue 2:
Symfony version(s) affected: 4.2.3

Updating symfony/dependency-injection (v4.2.2 => v4.2.3)

Somehow there are now 2 entity manager instances in my application, causing all sort of WTFs :)

See https://github.com/ro0NL/symfony-issue-30091

Before:

DefaultController.php on line 13:
EntityAwareFactory {#278 ▼
...
-em: EntityManager {#233 …11}
}
DefaultController.php on line 13:
UserEmailRepository {#212 ▼
...
-em: EntityManager {#233 …11}
...
}

Both entity managers are instance 233

After

DefaultController.php on line 13:
EntityAwareFactory {#278 ▼
...
-em: EntityManager {#233 …11}
}
DefaultController.php on line 13:
UserEmailRepository {#298 ▼
...
-em: EntityManager {#283 …11}
...
}

Now the instances differ. The only differenence is sf/di 4.2.2 vs 4.2.3. Respectively the first and last commit.
Issue 1:
#12551 and comment: #12512 (comment)

usecols=['a',1] should raise

Issue 2:
Hi, guys! First of all, thanks for making this open source! =D Keep up the good work!

SCRIPT

import pandas as pd

dfs = pd.read_html('https://en.wikipedia.org/wiki/List_of_states_and_territories_of_the_United_States')

print(dfs[0])

The output we found where there is any colspan is considering only the first column, and the other values are pulled back in relation to the colspan amount, making the values on the tail's row as "NaN"

#### Expected Output

In this web page, there is a colspan in the "capital" and "largest city" columns when they are the same, I think that in a general way we would expect that the value would be duplicate on the following <colspan's amount> columns in the generated DataFrame

output of pd.show_versions()

INSTALLED VERSIONS

commit: None

python: 3.5.2.final.0

python-bits: 64

OS: Windows

OS-release: 10

machine: AMD64

processor: Intel64 Family 6 Model 15 Stepping 13, GenuineIntel

byteorder: little

LC_ALL: None

LANG: None

pandas: 0.18.1

nose: None

pip: 8.1.2

setuptools: 27.2.0

Cython: 0.24.1

numpy: 1.11.1

scipy: 0.18.0

statsmodels: None

xarray: None

IPython: 5.1.0

sphinx: None

patsy: None

dateutil: 2.5.3

pytz: 2016.6.1

blosc: None

bottleneck: None

tables: None

numexpr: None

matplotlib: 1.5.1

openpyxl: None

xlrd: None

xlwt: None

xlsxwriter: None

lxml: None

bs4: 4.5.1

html5lib: 0.999

httplib2: None

apiclient: None

sqlalchemy: None

pymysql: None

psycopg2: None

jinja2: 2.8

boto: None

pandas_datareader: 0.2.1
Issue 1:
I've just noticed that a specific type-unstable broadcast fails on master, while it works fine on julia 1.5

MWE:

on julia 1.5

julia> broadcast((args...) -> NamedTuple{(:a, :b)}(args), [sin, cos], [1, 2])
2-element Array{NamedTuple{(:a, :b),T} where T<:Tuple,1}:
(a = sin, b = 1)
(a = cos, b = 2)

on nightly build

julia> broadcast((args...) -> NamedTuple{(:a, :b)}(args), [sin, cos], [1, 2])
ERROR: TypeError: in typeassert, expected AbstractVector{var"#s825"} where var"#s825"<:(NamedTuple{(:a, :b), _A} where _A<:Tuple{Function, Int64}), got a value of type Vector{NamedTuple{(:a, :b), T} where T<:Tuple}
Stacktrace:
[1] copy
@ ./broadcast.jl:928 [inlined]
[2] materialize
@ ./broadcast.jl:881 [inlined]
[3] broadcast(::var"#1#2", ::Vector{Function}, ::Vector{Int64})
@ Base.Broadcast ./broadcast.jl:819
[4] top-level scope
@ REPL[1]:1

Here's my versioninfo

julia> versioninfo()
Julia Version 1.6.0-DEV.1493
Commit f3252bf505 (2020-11-14 16:56 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-11.0.0 (ORCJIT, skylake)

(I've just redownloaded the nightly build, banner says 2 days old master.)

Issue 2:
Running the tests for AutomotiveSimulator errors on nightly (https://s3.amazonaws.com/julialang-reports/nanosoldier/pkgeval/by_hash/c3bb6df_vs_788b2c7/AutomotiveSimulator.1.6.0-DEV-a896693d33.log) due to a type assert error in broadcasting.

feature extraction: Error During Test at /home/kc/PkgEval16/dev/AutomotiveSimulator/test/test_features.jl:119
Got exception outside of a @test
TypeError: in typeassert, expected AbstractVector{var"#s825"} where var"#s825"<:(AbstractVector{var"#s825"} where var"#s825"<:Union{Missing, Float64}), got a value of type Vector{Vector{T} where T}
Stacktrace:
[1] copy(bc::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{1}, Tuple{Base.OneTo{Int64}}, AutomotiveSimulator.var"#25#26"{typeof(dist_to_front_neighbor), Roadway{Float64}, Vector{EntityScene{VehicleState, VehicleDef, Int64}}}, Tuple{Vector{Int64}}})
@ Base.Broadcast ./broadcast.jl:928
[2] materialize
@ ./broadcast.jl:881 [inlined]
[3] broadcast(f::AutomotiveSimulator.var"#25#26"{typeof(dist_to_front_neighbor), Roadway{Float64}, Vector{EntityScene{VehicleState, VehicleDef, Int64}}}, As::Vector{Int64})
@ Base.Broadcast ./broadcast.jl:819
[4] extract_feature(ft::SceneFeature, feature::Function, roadway::Roadway{Float64}, scenes::Vector{EntityScene{VehicleState, VehicleDef, Int64}}, ids::Vector{Int64})
@ AutomotiveSimulator ~/PkgEval16/dev/AutomotiveSimulator/src/feature-extraction/features.jl:96
....

This type assert comes from:

julia/base/broadcast.jl

Lines 924 to 928
in
3dc54a2

# The typeassert gives inference a helping hand on the element type and dimensionality

# (work-around for #28382)

ElType′ = ElType <: Type ? Type : ElType

RT = dest isa AbstractArray ? AbstractArray{<:ElType′, ndims(dest)} : Any

return copyto_nonleaf!(dest, bc′, iter, state, 1)::RT

and was introduced in #30485.

Is the package doing something wrong or is this type assert a bit too strict?

cc @nalimilan
Issue 1:
Screenshot

[drag & drop image(s) here!]

Description

When tried creating charts, the scroll option for Query section is missing. Due to which users are not able to access some of the functionality.

Design input

Scrolling CSS is missing for

Issue 2:
auto ldap registration enabled, below error is first time a new user tried to login to superset. 2nd login worked

Error adding new user to database. (raised as a result of Query-invoked autoflush; consider using a session.no_autoflush block if this flush is occurring prematurely)

(MySQLdb._exceptions.IntegrityError) (1062, "Duplicate entry 'secretusername' for key 'username'")

[SQL: INSERT INTO ab_user (first_name, last_name, username, password, active, email, last_login, login_count, fail_login_count, created_on, changed_on, created_by_fk, changed_by_fk) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)]

[parameters: ('f', 'l', 'secretusername', None, 1, 'secretusername@domain.com', None, None, None, datetime.datetime(2020, 5, 27, 9, 4, 7, 357169), datetime.datetime(2020, 5, 27, 9, 4, 7, 357177), None, None)]

(Background on this error at: http://sqlalche.me/e/gkpj)

Exception on /login/ [POST]

Traceback (most recent call last):

File "/usr/local/lib64/python3.6/site-packages/flask/app.py", line 2447, in wsgi_app

response = self.full_dispatch_request()

File "/usr/local/lib64/python3.6/site-packages/flask/app.py", line 1952, in full_dispatch_request

rv = self.handle_user_exception(e)

File "/usr/local/lib64/python3.6/site-packages/flask/app.py", line 1821, in handle_user_exception

reraise(exc_type, exc_value, tb)

File "/usr/local/lib64/python3.6/site-packages/flask/_compat.py", line 39, in reraise

raise value

File "/usr/local/lib64/python3.6/site-packages/flask/app.py", line 1950, in full_dispatch_request

rv = self.dispatch_request()

File "/usr/local/lib64/python3.6/site-packages/flask/app.py", line 1936, in dispatch_request

return self.view_functionsrule.endpoint

File "/usr/local/lib/python3.6/site-packages/flask_appbuilder/security/views.py", line 515, in login

form.username.data, form.password.data

File "/usr/local/lib/python3.6/site-packages/flask_appbuilder/security/manager.py", line 941, in auth_user_ldap

self.update_user_auth_stat(user)

File "/usr/local/lib/python3.6/site-packages/flask_appbuilder/security/manager.py", line 735, in update_user_auth_stat

if not user.login_count:

AttributeError: 'bool' object has no attribute 'login_count'
Issue 1:
Description

I think scoring of cross_val_score (also GridSearchCV and so on) is not good especially with cv={# of samples} (i.e. LeaveOneOut). In evaluating R2 or MAE values, mean of y is calculated with respect to each CV model in cross_val_score, but calculation of mean should be performed on all y. The difference become conspicuous when we use Leave One Out. Then mean of y with respect to each model equals to just y since number of test sample is one. Consequently, R2 value become zero.

Example code to Reproduce

PLS regression with Boston data set

from sklearn import datasets,cross_decomposition
from sklearn.model_selection import cross_val_score,cross_val_predict
from sklearn.metrics import r2_score

# Boston data set
boston = datasets.load_boston()
X,y = boston.data,boston.target

pls = cross_decomposition.PLSRegression(10)
r2cv_1 = cross_val_score(pls,X,y,scoring='r2',cv=X.shape[0]).mean()
r2cv_2 = r2_score(y,cross_val_predict(pls,X,y,cv=X.shape[0]))
print('r2cv(cross_val_score + mean) : {0:8.4f}\nr2cv(cross_val_predict + r2_score):{1:8.4f}'.format(r2cv_1,r2cv_2))

Results

r2cv(cross_val_score + mean) : 0.0000
r2cv(cross_val_predict + r2_score): 0.7190

R2cv value is expected to be 0.7190 but returned value is zero with cross_val_score.

Versions

Python 3.5.2 (default, Nov 23 2017, 16:37:01)

[GCC 5.4.0 20160609]

NumPy 1.14.5

SciPy 1.1.0

Scikit-Learn 0.19.1

Issue 2:
from sklearn.datasets import make_regression
from sklearn.cross_validation import cross_val_score, LeaveOneOut
from sklearn.linear_model import Ridge

X, y, coef_ = make_regression(random_state=42, noise=1, n_samples=200, coef=True)
cross_val_score(Ridge(), X, y, cv=LeaveOneOut(len(X)))

array([ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,

0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,

0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,

0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,

0., 0., 0., 0., 0., 0., 0., 0.])

Maybe the single sample in the LOO is not interpreted correctly? :-/