Linux Format - UK (2020-03)

(Antfer) #1
http://www.techradar.com/pro/linux March 2020 LXF260 83

HOTPICKS


AUDIO TAGGING SOFTWARE


PLOTTING APPLICATION


Nothing ever
published remains
‘unknown’ after
AcousticID analysis
has been carried
out by Picard.

he times of mass-scale CD ripping are gone,
and it seems most people prefer to keep their
music libraries on their hard drives. Maintaining
such a library can be tricky, especially if parts of your
collection were obtained from different sources,
encoded with various software, and some tracks still
look like Track X by Unknown Artist (my favourite!–Ed).
We have a cure, and it’s called Musicbrainz Picard. This
is a graphical application made using PyQt5. Essentially,
it is a front end to the Musicbrainz database, an open
music encyclopedia that anyone can contribute to. The
good thing about Picard is that you don’t have to rip
anything again but can fix your existing music files and
fetch missing metadata – not just album and track
names, but also cover art and lyrics.
Picard tries to recover missing metadata items using
the remaining ones. This often looks like a track having
all its details in the filename, but with blank metadata

eusz has been featured in Linux Format a
couple of times in the past, and we’re happy to
see this data visualisation software evolving
and getting better. Today’s Veusz is a powerful and finely
polished scientific application based on modern
versions of Qt 5 and Python 3. Veusz is a tool for
graphing – it was designed to turn piles of numbers into
visually appealing vector graphs that you might want to
use in a presentation or paper.
When you launch Veusz for the first time, a welcome
wizard pops up and guides you through the application’s
basics, specifically on building plots out of datasets. The
Veusz interface is similar to a vector editor, only that
objects are called widgets here. Functions, including the
basic ‘y=x’ plot are also widgets that can be placed on
the canvas using the Veusz toolbar, or via the Insert
menu. The wizard helps you to take baby steps in
putting several functions on the plot, customising their
settings, look and feel, importing numeric data from a
sample CSV file and using that data to build graphs, and

MusicBrainz


Picard


Veusz


fields inside. That is easy and just saves you from filling
the information manually. However, even if all the
metadata is missing, Picard is here to help. This
software can take acoustic fingerprints of your tracks
and find matches on Musicbrainz. As long as your
unknown tracks represent some officially released
content, there’s a good chance Picard will find the
correct names from the online database.
Using Picard makes it is easy to find out if your local
album copy is missing some tracks (B-sides, second
sides, etc.), or if some tracks were modified (someone
could have removed silence around a song) – the
application will indicate such things automatically. The
left side of the Picard window shows the ‘unclustered
tracks’. Drag them onto the right side to start
recovering. And don’t forget to click Save before exiting
the application.

finally multiplexing graphs in a grid. This excellent
tutorial is really useful, and we wish that more Linux
software included a wizard of that kind.
After some use it is easy to see that Veusz is a very
mature and sophisticated software. Its visualisation
tools are superior to those found in Dia or LibreOffice,
and the number of available features is astonishing.
Veusz sports a solid kit of scientific tools found under
the Data > Operations menu. You can compute dataset
extremes, multiply, divide, subtract datasets between
each other, filter and convert data and much more –
this is simply a heaven for those who work with maths,
statistics and the like.
Apart from 2D and 3D plotting capabilities, Veusz is
scriptable and extendible, and it can even be used as a
Python module in other projects. With all that in mind,
we doubt there are any decent Veusz rivals...

Version: 2.2.3 Web:https://github.
com/metabrainz/picard

Version: 3.1
Web: https://github.com/veusz/veusz

Plotting has never
been so exciting
thanks to the
power of Veusz!

T


V


8882March 0 h2rTinthTnyusBz March 2020 LXF260 83


HOTPICKS


AUDIOTAGGINGSOFTWARE


PLOTTINGAPPLICATION


Nothingever
publishedremains
‘unknown’after
AcousticIDanalysis
hasbeencarried
outbyPicard.

he times of mass-scale CD ripping are gone,
and it seems most people prefer to keep their
music libraries on their hard drives. Maintaining
suchalibrary can be tricky, especially if parts of your
collection were obtained from different sources,
encoded with various software, and some tracks still
look like Track X by Unknown Artist (my favourite!–Ed).
We have a cure, and it’s called Musicbrainz Picard. This
is a graphical application made using PyQt5. Essentially,
it is a front end to the Musicbrainz database, an open
music encyclopedia that anyone can contribute to. The
good thing about Picard is that you don’t have to rip
anything again but can fix your existing music files and
fetch missing metadata – not just album and track
names, but also cover art and lyrics.
Picard tries to recover missing metadata items using
the remaining ones. This often looks like a track having
all its details in the filename, but with blank metadata


eusz has been featured in Linux Format a
couple of times in the past, and we’re happy to
see this data visualisation software evolving
andgetting better. Today’s Veusz is a powerful and finely
polished scientific application based on modern
versions of Qt 5 and Python 3. Veusz is a tool for
graphing – it was designed to turn piles of numbers into
visually appealing vector graphs that you might want to
use in a presentation or paper.
When you launch Veusz for the first time, a welcome
wizard pops up and guides you through the application’s
basics, specifically on building plots out of datasets. The
Veusz interface is similar to a vector editor, only that
objects are called widgets here. Functions, including the
basic ‘y=x’ plot are also widgets that can be placed on
the canvas using the Veusz toolbar, or via the Insert
menu. The wizard helps you to take baby steps in
putting several functions on the plot, customising their
settings, look and feel, importing numeric data from a
sample CSV file and using that data to build graphs, and


MusicBrainz


Picard


Veusz


fields inside. That is easy and just saves you from filling
the information manually. However, even if all the
metadata is missing, Picard is here to help. This
software can take acoustic fingerprints of your tracks
and find matches on Musicbrainz. As long as your
unknown tracks represent some officially released
content, there’s a good chance Picard will find the
correct names from the online database.
Using Picard makes it is easy to find out if your local
album copy is missing some tracks (B-sides, second
sides, etc.), or if some tracks were modified (someone
could have removed silence around a song) – the
application will indicate such things automatically. The
left side of the Picard window shows the ‘unclustered
tracks’. Drag them onto the right side to start
recovering. And don’t forget to click Save before exiting
the application.

finally multiplexing graphs in a grid. This excellent
tutorial is really useful, and we wish that more Linux
software included a wizard of that kind.
After some use it is easy to see that Veusz is a very
mature and sophisticated software. Its visualisation
tools are superior to those found in Dia or LibreOffice,
and the number of available features is astonishing.
Veusz sports a solid kit of scientific tools found under
the Data > Operations menu. You can compute dataset
extremes, multiply, divide, subtract datasets between
each other, filter and convert data and much more –
this is simply a heaven for those who work with maths,
statistics and the like.
Apart from 2D and 3D plotting capabilities, Veusz is
scriptable and extendible, and it can even be used as a
Python module in other projects. With all that in mind,
we doubt there are any decent Veusz rivals...

Version: 2.2.3 Web:https://github.


com/metabrainz/picard


Version: 3.1


Web: https://github.com/veusz/veusz


Plotting has never
been so exciting
thanks to the
power of Veusz!

T


V

Free download pdf