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Participer à sa traduction
10 avril 2011Vous pouvez nous aider à améliorer les locutions utilisées dans le logiciel ou à traduire celui-ci dans n’importe qu’elle nouvelle langue permettant sa diffusion à de nouvelles communautés linguistiques.
Pour ce faire, on utilise l’interface de traduction de SPIP où l’ensemble des modules de langue de MediaSPIP sont à disposition. ll vous suffit de vous inscrire sur la liste de discussion des traducteurs pour demander plus d’informations.
Actuellement MediaSPIP n’est disponible qu’en français et (...) -
MediaSPIP Player : problèmes potentiels
22 février 2011, parLe lecteur ne fonctionne pas sur Internet Explorer
Sur Internet Explorer (8 et 7 au moins), le plugin utilise le lecteur Flash flowplayer pour lire vidéos et son. Si le lecteur ne semble pas fonctionner, cela peut venir de la configuration du mod_deflate d’Apache.
Si dans la configuration de ce module Apache vous avez une ligne qui ressemble à la suivante, essayez de la supprimer ou de la commenter pour voir si le lecteur fonctionne correctement : /** * GeSHi (C) 2004 - 2007 Nigel McNie, (...) -
Encoding and processing into web-friendly formats
13 avril 2011, parMediaSPIP automatically converts uploaded files to internet-compatible formats.
Video files are encoded in MP4, Ogv and WebM (supported by HTML5) and MP4 (supported by Flash).
Audio files are encoded in MP3 and Ogg (supported by HTML5) and MP3 (supported by Flash).
Where possible, text is analyzed in order to retrieve the data needed for search engine detection, and then exported as a series of image files.
All uploaded files are stored online in their original format, so you can (...)
Sur d’autres sites (14702)
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Anomalie #3772 : Filtrage automatique par statut actif sur une boucle spip_articles depuis SPIP 3.x
8 mai 2016, par jluc -Comme écrit sur la page liée, un critère optionnel est actif "uniquement si l’environnement contient la balise demandée". Dans l’environnement des boucles imbriquées, la balise est bien définie, et ce serait donc normal que le critère soit activé.
Dans les exemples cités, le traitement ne semble pas malin car dans l’environnement de la boucle interne, cette balise est un champ de la table englobante, qui n’est pas l’une des tables sur lesquelles boucle la boucle interne, comme c’est souvent le cas pour les critères raccourcis.
Les critères optionnels et raccourcis ont été mis en place pour les arguments d’url ou les arguments des appels d’INCLURE ou de modèles, et rien n’est pas prévu de désambiguiser les homonymes : quand il y a statut dans une url, ce n’est ni spécialement un statut de rubrique, ni spécialement un statut d’article. Donc par conception,
statut, statut ?, id_rubrique
n’en tiennent pas compte.
On ne peut pas changer ça pour les critères raccourcis, sinon la transmission des #ID_RUBRIQUE ne pourrait pas se faire d’une boucle rubrique à une boucle article et les critères raccourcis n’auraient quasiment plus raison d’être.
A priori je trouve assez sain (car simple) que les critères optionnels fonctionnent pareil que les critères raccourcis. Donc il faudrait une raison sérieuse pour que ça soit différent. Quelle serait elle ?
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Error installing package in anaconda : Attempted to make prefix record for unknown package type
25 janvier 2020, par ashwinidsI’m getting the error below for doing any operation install, update or uninstall
ERROR conda.core.link:_execute(700) : An error occurred while
uninstalling package ’::ffmpeg-3.2.4-2’. Rolling back
transaction : doneValueError(’Attempted to make prefix record for unknown package type :
ffmpeg-3.2.4-2’,)Details about the environment :
OS : ubuntu 18.04
python version : intelpython3Conda info
active environment : base
active env location : /home/p****/intelpython3
shell level : 1
user config file : /home/p****/.condarc
populated config files : /home/p****/.condarc
conda version : 4.7.12
conda-build version : not installed
python version : 3.6.8.final.0
virtual packages : __cuda=10.1
base environment : /home/p****/intelpython3 (writable)
channel URLs : https://conda.anaconda.org/intel/linux-64
https://conda.anaconda.org/intel/noarch
https://repo.anaconda.com/pkgs/main/linux-64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/r/linux-64
https://repo.anaconda.com/pkgs/r/noarch
package cache : /home/p****/intelpython3/pkgs
/home/p****/.conda/pkgs
envs directories : /home/p****/intelpython3/envs
/home/p****/.conda/envs
platform : linux-64
user-agent : conda/4.7.12 requests/2.20.1 CPython/3.6.8 Linux/5.0.0-36-generic ubuntu/18.04.3 glibc/2.27
UID:GID : 1000:1000
netrc file : None
offline mode : FalseConda list
# packages in environment at /home/p****/intelpython3:
#
# Name Version Build Channel
_tflow_select 2.1.0 gpu anaconda
absl-py 0.8.0 py36_0 anaconda
affine 2.3.0 pypi_0 pypi
asn1crypto 0.24.0 py36_3 intel
astor 0.8.0 py36_0 anaconda
atomicwrites 1.3.0 pypi_0 pypi
attrs 19.3.0 pypi_0 pypi
audioread 2.1.6 py36_0 <unknown>
awscli 1.16.292 pypi_0 pypi
backcall 0.1.0 py36_2 <unknown>
backports 1.0 py36_9 <unknown>
bayesian-optimization 1.0.1 pypi_0 pypi
bleach 2.1.3 py36_2 <unknown>
boto3 1.10.19 pypi_0 pypi
botocore 1.13.28 pypi_0 pypi
bzip2 1.0.6 17 intel
c-ares 1.15.0 h7b6447c_1001 anaconda
causalgraphicalmodels 0.0.4 pypi_0 pypi
certifi 2018.1.18 py36_2 intel
cffi 1.11.5 py36_3 intel
chardet 3.0.4 py36_3 intel
click 7.0 pypi_0 pypi
click-plugins 1.1.1 pypi_0 pypi
cligj 0.5.0 pypi_0 pypi
colorama 0.4.1 pypi_0 pypi
conda 4.7.12 py36_0
conda-env 2.6.0 1
conda-package-handling 1.6.0 py36h7b6447c_0 anaconda
cryptography 2.3 py36_1 intel
cudatoolkit 10.1.243 h6bb024c_0
cudnn 7.6.0 cuda10.1_0 anaconda
cupti 10.1.168 0 anaconda
cvxopt 1.2.3 pypi_0 pypi
cycler 0.10.0 py36_7 intel
cython 0.29.6 py36h7b7c402_0 intel
daal 2019.4 intel_243 <unknown>
daal4py 2019.4 py36h7b7c402_0 intel
dbus 1.13.12 h746ee38_0
decorator 4.3.0 py36_3 <unknown>
descartes 1.1.0 pypi_0 pypi
docutils 0.15.2 pypi_0 pypi
dowhy 0.1.1 pypi_0 pypi
entrypoints 0.2.3 py36_2 <unknown>
expat 2.2.6 he6710b0_0
ffmpeg 3.2.4 2 <unknown>
fiona 1.8.11 pypi_0 pypi
fontconfig 2.12.6 h49f89f6_0
freetype 2.8 hab7d2ae_1
funcsigs 1.0.2 py36_7 intel
gast 0.3.2 py_0 anaconda
geopandas 0.6.2 pypi_0 pypi
get_terminal_size 1.0.0 py36_7 <unknown>
glib 2.63.1 h5a9c865_0
google-pasta 0.1.7 py_0 anaconda
grpcio 1.14.1 py36h9ba97e2_0 anaconda
gst-plugins-base 1.12.4 h33fb286_0
gstreamer 1.12.4 hb53b477_0
h5py 2.9.0 py36h7918eee_0 anaconda
hdf5 1.10.4 hb1b8bf9_0 anaconda
html5lib 1.0.1 py36_4 <unknown>
icc_rt 2019.4 intel_243 <unknown>
icu 58.2 h9c2bf20_1
idna 2.6 py36_3 intel
imageio 2.6.1 pypi_0 pypi
imgaug 0.2.6 pypi_0 pypi
impi_rt 2019.4 intel_243 <unknown>
importlib-metadata 0.23 pypi_0 pypi
intel-openmp 2019.4 intel_243 <unknown>
intelpython 2019.4 0 intel
ipp 2019.4 intel_243 <unknown>
ipykernel 4.6.1 py36_2 <unknown>
ipython 6.3.1 py36_3 <unknown>
ipython_genutils 0.2.0 py36_2 <unknown>
jedi 0.12.0 py36_2 <unknown>
jinja2 2.10.3 pypi_0 pypi
jmespath 0.9.4 pypi_0 pypi
joblib 0.13.2 pypi_0 pypi
jpeg 9b h024ee3a_2
json5 0.8.5 pypi_0 pypi
jsonschema 3.2.0 pypi_0 pypi
jupyter 1.0.0 py36_7 intel
jupyter_client 5.1.0 py36_5 <unknown>
jupyter_console 5.1.0 py36_2 <unknown>
jupyter_core 4.4.0 py36_6 <unknown>
jupyterlab 1.2.3 pypi_0 pypi
jupyterlab-server 1.0.6 pypi_0 pypi
keras 2.3.1 pypi_0 pypi
keras-applications 1.0.8 py_0 anaconda
keras-bert 0.80.0 pypi_0 pypi
keras-embed-sim 0.7.0 pypi_0 pypi
keras-layer-normalization 0.14.0 pypi_0 pypi
keras-multi-head 0.22.0 pypi_0 pypi
keras-pos-embd 0.11.0 pypi_0 pypi
keras-position-wise-feed-forward 0.6.0 pypi_0 pypi
keras-preprocessing 1.1.0 py_1 anaconda
keras-rectified-adam 0.17.0 pypi_0 pypi
keras-self-attention 0.41.0 pypi_0 pypi
keras-transformer 0.31.0 pypi_0 pypi
kiwisolver 1.0.1 py36_2 intel
libffi 3.2.1 11 intel
libgcc-ng 9.1.0 hdf63c60_0 anaconda
libgfortran-ng 7.3.0 hdf63c60_0 anaconda
libiconv 1.14 4 <unknown>
libpng 1.6.36 2 intel
libprotobuf 3.9.2 hd408876_0 anaconda
librosa 0.6.3 pypi_0 pypi
libsodium 1.0.16 3 <unknown>
libstdcxx-ng 9.1.0 hdf63c60_0 anaconda
libtiff 4.0.9 he85c1e1_1
libxcb 1.13 h1bed415_1
libxml2 2.9.8 hf84eae3_0
lightgbm 2.3.1 pypi_0 pypi
llvmlite 0.27.1 py36_0 intel
markdown 3.1.1 py36_0 anaconda
markupsafe 1.0 py36_3 <unknown>
matplotlib 2.1.0 py36hba5de38_0
mercantile 1.1.2 pypi_0 pypi
metaflow 2.0.0 pypi_0 pypi
mistune 0.8.3 py36_2 <unknown>
mkl 2019.4 intel_243 <unknown>
mkl-service 1.0.0 py36h7b7c402_11 intel
mkl_fft 1.0.11 py36h7b7c402_2 intel
mkl_random 1.0.2 py36h7b7c402_4 intel
more-itertools 7.2.0 pypi_0 pypi
mpi4py 3.0.0 py36_3 intel
mpmath 1.1.0 pypi_0 pypi
munch 2.5.0 pypi_0 pypi
nbconvert 5.2.1 py36_2 <unknown>
nbformat 4.4.0 py36_2 <unknown>
networkx 2.4 pypi_0 pypi
ninja 1.9.0 py36hfd86e86_0
noisyopt 0.2.2 pypi_0 pypi
notebook 5.2.2 py36_1 intel
numba 0.42.1 np116py36_2 intel
numexpr 2.6.8 py36_2 intel
numpy 1.16.2 py36h7b7c402_0 intel
numpy-base 1.16.2 py36_0 intel
oauthlib 3.1.0 pypi_0 pypi
olefile 0.46 py_0
openssl 1.0.2r 2 intel
packaging 19.2 pypi_0 pypi
pandas 0.24.1 py36_3 intel
pandocfilters 1.4.1 py36_2 <unknown>
parso 0.2.0 py36_2 <unknown>
path.py 11.0.1 py36_2 <unknown>
pcre 8.43 he6710b0_0
pexpect 4.2.1 py36_4 <unknown>
pickleshare 0.7.4 py36_3 <unknown>
pillow 6.2.1 pypi_0 pypi
pip 19.3.1 pypi_0 pypi
pluggy 0.13.1 pypi_0 pypi
prompt_toolkit 1.0.15 py36_2 <unknown>
protobuf 3.9.2 py36he6710b0_0 anaconda
ptyprocess 0.5.2 py36_2 <unknown>
pulp 2.0 pypi_0 pypi
py 1.8.0 pypi_0 pypi
pyasn1 0.4.8 pypi_0 pypi
pycosat 0.6.3 py36_3 intel
pycparser 2.18 py36_2 intel
pydot 1.4.1 pypi_0 pypi
pyeditline 2.0.0 py36_0 intel
pygments 2.2.0 py36_5 <unknown>
pygmy 0.2.0 pypi_0 pypi
pyopenssl 17.5.0 py36_2 intel
pyparsing 2.2.0 py36_2 intel
pyportfolioopt 0.4.3 pypi_0 pypi
pyproj 2.4.2.post1 pypi_0 pypi
pyqt 5.6.0 py36h22d08a2_6
pyrsistent 0.15.6 pypi_0 pypi
pysocks 1.6.7 py36_1 intel
pytesseract 0.3.0 pypi_0 pypi
pytest 4.6.6 pypi_0 pypi
python 3.6.8 7 intel
python-dateutil 2.6.0 py36_12 intel
python-graphviz 0.13 pypi_0 pypi
pytorch 1.3.1 py3.6_cuda10.1.243_cudnn7.6.3_0 pytorch
pytz 2018.4 py36_3 intel
pywavelets 1.1.1 pypi_0 pypi
pyyaml 4.1 py36_3 intel
pyzmq 16.0.2 py36_6 <unknown>
qt 5.6.2 hd25b39d_14
rasterio 1.1.1 pypi_0 pypi
regex 2019.11.1 pypi_0 pypi
requests 2.20.1 py36_1 intel
requests-oauthlib 1.3.0 pypi_0 pypi
resampy 0.2.1 pypi_0 pypi
rio-cogeo 1.1.6 pypi_0 pypi
rsa 3.4.2 pypi_0 pypi
ruamel_yaml 0.11.14 py36_4 intel
s3transfer 0.2.1 pypi_0 pypi
sacremoses 0.0.35 pypi_0 pypi
scikit-image 0.16.2 pypi_0 pypi
scikit-learn 0.20.3 py36h7b7c402_5 intel
scipy 1.3.3 pypi_0 pypi
seaborn 0.9.0 pypi_0 pypi
sentencepiece 0.1.83 pypi_0 pypi
setuptools 39.0.1 py36_0 intel
shapely 1.6.4.post2 pypi_0 pypi
simplegeneric 0.8.1 py36_7 <unknown>
sip 4.18.1 py36hf484d3e_2
six 1.11.0 py36_3 intel
smp 0.1.4 py36_0 intel
snuggs 1.4.7 pypi_0 pypi
sqlite 3.27.2 4 intel
supermercado 0.0.5 pypi_0 pypi
sympy 1.4 pypi_0 pypi
tbb 2019.6 intel_243 <unknown>
tbb4py 2019.6 py36_intel_0 <unknown>
tcl 8.6.4 24 intel
tensorboard 1.14.0 py36hf484d3e_0 anaconda
tensorflow 1.14.0 gpu_py36h3fb9ad6_0 anaconda
tensorflow-base 1.14.0 gpu_py36he45bfe2_0 anaconda
tensorflow-estimator 1.14.0 py_0 anaconda
tensorflow-gpu 1.14.0 h0d30ee6_0 anaconda
termcolor 1.1.0 py36_1 anaconda
terminado 0.8.1 py36_2 <unknown>
testpath 0.3.1 py36_2 <unknown>
tk 8.6.4 29 intel
torchvision 0.4.2 py36_cu101 pytorch
tornado 4.5.2 py36_5 <unknown>
tqdm 4.36.1 py_0 anaconda
traitlets 4.3.2 py36_3 <unknown>
transformers 2.1.1 pypi_0 pypi
tweepy 3.8.0 pypi_0 pypi
urllib3 1.22 pypi_0 pypi
wcwidth 0.1.7 py36_6 <unknown>
webencodings 0.5.1 py36_0 <unknown>
werkzeug 0.16.0 py_0 anaconda
wheel 0.31.0 py36_3 intel
widgetsnbextension 3.2.0 py36_1 <unknown>
wrapt 1.11.2 py36h7b6447c_0 anaconda
x264 20131218 0 <unknown>
xgboost 0.81 py36_0 intel
xz 5.2.3 2 intel
yaml 0.1.7 2 intel
zipp 0.6.0 pypi_0 pypi
zlib 1.2.11 5 intel
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Date and segment comparison feature
31 octobre 2019, par Matomo Core Team — Analytics Tips, DevelopmentGet a clearer picture with the date and segment comparison feature
What can you do with it ? What are the benefits ?
Make informed decisions faster by easily comparing different segments and dates with each other.
Compare report data for multiple segments next to each other
Directly compare the behaviour of visitors from different segments e.g. customers with accounts vs. customers without accounts. Segment comparisons are a powerful way to compare different audience ; learn which ones perform better ; and in what way their actions differ.
Compare report data for two time periods next to each other
See how your website performs compared to the previous month/week/year. Including seeing trends over those periods. Say, your business always picks up at the same times within a year, or there’s a sag in business for every user segment over this year and the last except one.
By being able to compare date ranges you are able to get a quick overview of trends and period to period performance. Has a campaign worked better in September than in October ? Get an instant look by having the side-by-side comparison in Matomo.
What is it capable of ?
It lets you ask the question, “What is different ?”
If you look at reports you’ll only see how people behave overall and if you look at specific segments you’ll see how they behave at face value, however, if you compare data together you’ll be quickly informed on what makes them unique. This data is still there when you don’t use the comparison feature, it’s just buried. Comparing data highlights discrepancies and leads to important questions and answers.
For example, perhaps some class of users have very low engagement on a specific day compared to the rest of your visitors, and perhaps those users are responsible for an outsized proportion of churn.
Who could benefit from it, and why ?
Everyone can benefit from using it (and probably should use it). It’s yours to experiment with ! You shouldn’t feel restricted to only comparing between the current and last period, or having questions before you start comparing. Follow your instincts and see what pops out when data from different segments is laid out next to each other.
Where can you find it in Matomo ?
- Segment comparison is activated by the new icon in the segment selector
- Date comparison can be found in the calendar section of Matomo
- The list of active comparisons is visible at the top of the page for all pages that support comparison
- Comparisons are visible in every report that supports comparing data, and reports that do not support it will display a message saying so
How do you use it ?
- To compare segments, click the icon in the segment selector
- To compare periods, click the ‘compare’ checkbox in the period selector, then select what period you want to compare it against in the dropdown (previous period, previous year, or a custom range)
- When comparisons are active, view your reports as normal
Take it away !
The comparison feature is a new tool from Matomo 3.12.0 that highlights discrepancies and differences in data that can lead to more clarity and understanding, so we’d encourage everyone to use it.
Try it out today in your Matomo and see the power behind this new data comparison mode !
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