Master of Neuroscience Wiki - User contributions [en]

Logi verwenden

2025-11-20T14:48:51Z

Davrot: /* ssh / scp */

Nicht vergessen: Viele kleine Dateien sind Gift für die Logi Performance!!!

Offizielle Anleitung hier: https://www.uni-bremen.de/fileadmin/user_upload/sites/zfn/Serverdienste/Netzlaufwerk.pdf

== ssh / scp ==
Unter Windows:

https://mobaxterm.mobatek.net/

Oder VS Code(-Insiders):

https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-ssh

oder eben die normalen ssh/scp Tools:<syntaxhighlight lang="bash">> ssh davrot@logi.zfn.uni-bremen.de
(davrot@logi.zfn.uni-bremen.de) Password:
Welcome to Ubuntu 24.04.3 LTS (GNU/Linux 6.8.0-63-generic x86_64)

[...]

3 additional security updates can be applied with ESM Apps.
Learn more about enabling ESM Apps service at https://ubuntu.com/esm

davrot@logi:~$ cd /logigrouphome/neuro_itp_logi_verwaltung</syntaxhighlight>Offensichtlich neuro_itp_logi_verwaltung durch den eigenen Gruppennamen austauschen.

=== Datei auf Logi hochladen ===
Lokal<syntaxhighlight lang="bash">
> scp megatestdatei.gross davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung
(davrot@logi.zfn.uni-bremen.de) Password:
megatestdatei.gross 100% 0 0.0KB/s 00:00
</syntaxhighlight>Auf logi<syntaxhighlight lang="bash">
davrot@logi:/logigrouphome/neuro_itp_logi_verwaltung$ ls -ltr
total 0
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:19 megatestdatei.gross

</syntaxhighlight>Parameter -r um rekursiv Verzeichnisse hochzuladen.

=== Datei von Logi herunterladen ===
Lokal<syntaxhighlight lang="bash">
> scp davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung/megatestdatei2.gross .
(davrot@logi.zfn.uni-bremen.de) Password:
davrot@tea: /home/davrot/
> ls -ltr
total 0
-rw-r--r-- 1 davrot users 0 Nov 20 15:22 megatestdatei2.gross

</syntaxhighlight>Parameter -r um rekursiv Verzeichnisse runterzuladen.

== rsync ==
Lokal<syntaxhighlight lang="bash">
> rsync -av * davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung/
(davrot@logi.zfn.uni-bremen.de) Password:
sending incremental file list
megatestdatei.gross
megatestdatei2.gross

sent 179 bytes received 54 bytes 42.36 bytes/sec
total size is 0 speedup is 0.00

</syntaxhighlight>Auf Logi<syntaxhighlight lang="bash">
davrot@logi:/logigrouphome/neuro_itp_logi_verwaltung$ ls -ltr
total 0
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:19 megatestdatei.gross
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:22 megatestdatei2.gross

</syntaxhighlight>

== Linux ==

== Windows ==

Logi verwenden

2025-11-20T14:45:12Z

Davrot:

Nicht vergessen: Viele kleine Dateien sind Gift für die Logi Performance!!!

Offizielle Anleitung hier: https://www.uni-bremen.de/fileadmin/user_upload/sites/zfn/Serverdienste/Netzlaufwerk.pdf

== ssh / scp ==
<syntaxhighlight lang="bash">> ssh davrot@logi.zfn.uni-bremen.de
(davrot@logi.zfn.uni-bremen.de) Password:
Welcome to Ubuntu 24.04.3 LTS (GNU/Linux 6.8.0-63-generic x86_64)

[...]

3 additional security updates can be applied with ESM Apps.
Learn more about enabling ESM Apps service at https://ubuntu.com/esm

davrot@logi:~$ cd /logigrouphome/neuro_itp_logi_verwaltung</syntaxhighlight>Offensichtlich neuro_itp_logi_verwaltung durch den eigenen Gruppennamen austauschen.

=== Datei auf Logi hochladen ===
Lokal<syntaxhighlight lang="bash">
> scp megatestdatei.gross davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung
(davrot@logi.zfn.uni-bremen.de) Password:
megatestdatei.gross 100% 0 0.0KB/s 00:00
</syntaxhighlight>Auf logi<syntaxhighlight lang="bash">
davrot@logi:/logigrouphome/neuro_itp_logi_verwaltung$ ls -ltr
total 0
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:19 megatestdatei.gross

</syntaxhighlight>Parameter -r um rekursiv Verzeichnisse hochzuladen.

=== Datei von Logi herunterladen ===
Lokal<syntaxhighlight lang="bash">
> scp davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung/megatestdatei2.gross .
(davrot@logi.zfn.uni-bremen.de) Password:
davrot@tea: /home/davrot/
> ls -ltr
total 0
-rw-r--r-- 1 davrot users 0 Nov 20 15:22 megatestdatei2.gross

</syntaxhighlight>Parameter -r um rekursiv Verzeichnisse runterzuladen.

== rsync ==
Lokal<syntaxhighlight lang="bash">
> rsync -av * davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung/
(davrot@logi.zfn.uni-bremen.de) Password:
sending incremental file list
megatestdatei.gross
megatestdatei2.gross

sent 179 bytes received 54 bytes 42.36 bytes/sec
total size is 0 speedup is 0.00

</syntaxhighlight>Auf Logi<syntaxhighlight lang="bash">
davrot@logi:/logigrouphome/neuro_itp_logi_verwaltung$ ls -ltr
total 0
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:19 megatestdatei.gross
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:22 megatestdatei2.gross

</syntaxhighlight>

== Linux ==

== Windows ==

Logi verwenden

2025-11-20T14:41:49Z

Davrot:

Nicht vergessen: Viele kleine Dateien sind Gift für die Logi Performance!!!

Offizielle Anleitung hier: https://www.uni-bremen.de/fileadmin/user_upload/sites/zfn/Serverdienste/Netzlaufwerk.pdf

== ssh / scp ==
<syntaxhighlight lang="bash">> ssh davrot@logi.zfn.uni-bremen.de
(davrot@logi.zfn.uni-bremen.de) Password:
Welcome to Ubuntu 24.04.3 LTS (GNU/Linux 6.8.0-63-generic x86_64)

[...]

3 additional security updates can be applied with ESM Apps.
Learn more about enabling ESM Apps service at https://ubuntu.com/esm

davrot@logi:~$ cd /logigrouphome/neuro_itp_logi_verwaltung</syntaxhighlight>Offensichtlich neuro_itp_logi_verwaltung durch den eigenen Gruppennamen austauschen.

=== Datei auf Logi hochladen ===
Lokal<syntaxhighlight lang="bash">
> scp megatestdatei.gross davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung
(davrot@logi.zfn.uni-bremen.de) Password:
megatestdatei.gross 100% 0 0.0KB/s 00:00
</syntaxhighlight>Auf logi<syntaxhighlight lang="bash">
davrot@logi:/logigrouphome/neuro_itp_logi_verwaltung$ ls -ltr
total 0
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:19 megatestdatei.gross

</syntaxhighlight>Parameter -r um rekursiv Verzeichnisse hochzuladen.

=== Datei von Logi herunterladen ===
Lokal<syntaxhighlight lang="bash">
> scp davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung/megatestdatei2.gross .
(davrot@logi.zfn.uni-bremen.de) Password:
davrot@tea: /home/davrot/
> ls -ltr
total 0
-rw-r--r-- 1 davrot users 0 Nov 20 15:22 megatestdatei2.gross

</syntaxhighlight>Parameter -r um rekursiv Verzeichnisse runterzuladen.

== rsync ==
Lokal<syntaxhighlight lang="bash">
> rsync -av * davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung/
(davrot@logi.zfn.uni-bremen.de) Password:
sending incremental file list
megatestdatei.gross
megatestdatei2.gross

sent 179 bytes received 54 bytes 42.36 bytes/sec
total size is 0 speedup is 0.00

</syntaxhighlight>Auf Logi<syntaxhighlight lang="bash">
davrot@logi:/logigrouphome/neuro_itp_logi_verwaltung$ ls -ltr
total 0
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:19 megatestdatei.gross
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:22 megatestdatei2.gross

</syntaxhighlight>

== Linux ==
Wir werden als User das Verzeichnis mounten.

Dafür brauchen wir:<syntaxhighlight lang="bash">
sudo apt install ceph-fuse # Debian/Ubuntu
dnf install ceph-fuse # Fedora
</syntaxhighlight>

Logi verwenden

2025-11-20T14:31:22Z

Davrot: /* rsync */

Nicht vergessen: Viele kleine Dateien sind Gift für die Logi Performance!!!

== ssh / scp ==
<syntaxhighlight lang="bash">> ssh davrot@logi.zfn.uni-bremen.de
(davrot@logi.zfn.uni-bremen.de) Password:
Welcome to Ubuntu 24.04.3 LTS (GNU/Linux 6.8.0-63-generic x86_64)

[...]

3 additional security updates can be applied with ESM Apps.
Learn more about enabling ESM Apps service at https://ubuntu.com/esm

davrot@logi:~$ cd /logigrouphome/neuro_itp_logi_verwaltung</syntaxhighlight>Offensichtlich neuro_itp_logi_verwaltung durch den eigenen Gruppennamen austauschen.

=== Datei auf Logi hochladen ===
Lokal<syntaxhighlight lang="bash">
> scp megatestdatei.gross davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung
(davrot@logi.zfn.uni-bremen.de) Password:
megatestdatei.gross 100% 0 0.0KB/s 00:00
</syntaxhighlight>Auf logi<syntaxhighlight lang="bash">
davrot@logi:/logigrouphome/neuro_itp_logi_verwaltung$ ls -ltr
total 0
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:19 megatestdatei.gross

</syntaxhighlight>Parameter -r um rekursiv Verzeichnisse hochzuladen.

=== Datei von Logi herunterladen ===
Lokal<syntaxhighlight lang="bash">
> scp davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung/megatestdatei2.gross .
(davrot@logi.zfn.uni-bremen.de) Password:
davrot@tea: /home/davrot/
> ls -ltr
total 0
-rw-r--r-- 1 davrot users 0 Nov 20 15:22 megatestdatei2.gross

</syntaxhighlight>Parameter -r um rekursiv Verzeichnisse runterzuladen.

== rsync ==
Lokal<syntaxhighlight lang="bash">
> rsync -av * davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung/
(davrot@logi.zfn.uni-bremen.de) Password:
sending incremental file list
megatestdatei.gross
megatestdatei2.gross

sent 179 bytes received 54 bytes 42.36 bytes/sec
total size is 0 speedup is 0.00

</syntaxhighlight>Auf Logi<syntaxhighlight lang="bash">
davrot@logi:/logigrouphome/neuro_itp_logi_verwaltung$ ls -ltr
total 0
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:19 megatestdatei.gross
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:22 megatestdatei2.gross

</syntaxhighlight>

== Linux ==
Wir werden als User das Verzeichnis mounten.

Dafür brauchen wir:<syntaxhighlight lang="bash">
sudo apt install ceph-fuse # Debian/Ubuntu
dnf install ceph-fuse # Fedora
</syntaxhighlight>

Logi verwenden

2025-11-20T14:27:16Z

Davrot:

Logi verwenden

2025-11-20T14:25:19Z

Davrot:

Logi verwenden

2025-11-20T14:23:48Z

Davrot: Created page with "== ssh / scp == <syntaxhighlight lang="bash">> ssh davrot@logi.zfn.uni-bremen.de (davrot@logi.zfn.uni-bremen.de) Password: Welcome to Ubuntu 24.04.3 LTS (GNU/Linux 6.8.0-63-generic x86_64) [...] 3 additional security updates can be applied with ESM Apps. Learn more about enabling ESM Apps service at https://ubuntu.com/esm davrot@logi:~$ cd /logigrouphome/neuro_itp_logi_verwaltung</syntaxhighlight>Offensichtlich neuro_itp_logi_verwaltung durch den eigenen Gruppennam..."

== ssh / scp ==
<syntaxhighlight lang="bash">> ssh davrot@logi.zfn.uni-bremen.de
(davrot@logi.zfn.uni-bremen.de) Password:
Welcome to Ubuntu 24.04.3 LTS (GNU/Linux 6.8.0-63-generic x86_64)

[...]

3 additional security updates can be applied with ESM Apps.
Learn more about enabling ESM Apps service at https://ubuntu.com/esm

davrot@logi:~$ cd /logigrouphome/neuro_itp_logi_verwaltung</syntaxhighlight>Offensichtlich neuro_itp_logi_verwaltung durch den eigenen Gruppennamen austauschen.

=== Datei auf Logi hochladen ===
Lokal<syntaxhighlight lang="bash">
> scp megatestdatei.gross davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung
(davrot@logi.zfn.uni-bremen.de) Password:
megatestdatei.gross 100% 0 0.0KB/s 00:00
</syntaxhighlight>Auf logi<syntaxhighlight lang="bash">
davrot@logi:/logigrouphome/neuro_itp_logi_verwaltung$ ls -ltr
total 0
-rw-r--r-- 1 davrot neuro_itp_logi_verwaltung 0 Nov 20 15:19 megatestdatei.gross

</syntaxhighlight>

=== Datei von Logi herunterladen ===
Lokal<syntaxhighlight lang="bash">
> scp davrot@logi.zfn.uni-bremen.de:/logigrouphome/neuro_itp_logi_verwaltung/megatestdatei2.gross .
(davrot@logi.zfn.uni-bremen.de) Password:
davrot@tea: /home/davrot/
> ls -ltr
total 0
-rw-r--r-- 1 davrot users 0 Nov 20 15:22 megatestdatei2.gross

</syntaxhighlight>

Main Page

2025-11-20T14:14:55Z

Davrot: /* Offtopic */

(Please ignore Create Account. Use '''Log in'''. The system will use autocreate to create your Wiki account if you have a University of Bremen, FB1 git or overleaf account.)

=== Python ===

* [[Python Tutorial]]
* [[Git jupyterlab]]

=== chat-ai.academiccloud.de and VS Code ===

* [[Get the API key]]
* [[Config VS Code (Insiders)]]

=== AI slop ===

* [[Using spec kit and copilot]]

=== Offtopic ===
* [[Computer admin tutorials]]
* [[Notizen zu Cloud-Instanzen und Services]]
* [[Thunderbird und der NextCloud Kalender]]
* [[Wie benutze ich Vaultwarden]]
* Linux: [[xpra]] connect to your application from "anywhere"
* [[Uni Datastorage Logi]] (Admin) & [[Logi verwenden]] (User)

Uni Datastorage Logi

2025-11-20T14:14:03Z

Davrot:

== Logi Storage beantragen ==
Die Online Tools sind der Dreh und Angelpunkt:

https://onlinetools.zfn.uni-bremen.de/

=== Funktionsaccount anlegen ===
[[File:2025-11-20 14-44.png|800x800px]]

Die Daten "müssen" durch einen Funktionsaccount verwaltet werden. Wenn der Funktionsaccount genehmigt wurde mit dem Funktionsaccount einloggen.

=== Gruppe anlegen ===
In die Gruppenverwaltung gehen und eine neue Gruppe beantragen:

[[File:2025-11-20 14-44.png|800x800px]]

[[File:2025-11-20 14-44 1.png]]

Mit der Bezeichnung und Beschreibung kreativ werden

[[File:2025-11-20 14-47.png|800x800px]]

Warten bis die Gruppe genehmigt wurde

[[File:2025-11-20 14-59.png|800x800px]]

=== Logi beantragen ===
Eine nette eMail an campusserver [@] uni-bremen.de schreiben.

Warten bis man freigeschaltet ist.

=== Gruppe verwalten ===
[[File:2025-11-20 14-48.png]]

==== Person einladen ====
[[File:2025-11-20 14-48 1.png|800x800px]]

Eine der beiden Varianten verwenden um die hinzuzufügende Person zu finden:

[[File:2025-11-20 14-49.png]]

Hier per Kontosuche
[[File:2025-11-20 14-49 1.png|800x800px]]
Die Person bekommt eine eMail und muss bestätigen

[[File:2025-11-20 14-50.png|800x800px]]

Die Person wird durch den Link auf so eine Seite weitergeleitet (nach User Authentifizierung)

[[File:2025-11-20 14-51.png|800x800px]]

==== Überprüfen ob die Person eingepflegt ist ====
[[File:2025-11-20 14-51 1.png|800x800px]]

== Speicher Quota kontrollieren ==
[[File:2025-11-20 15-11.png]]

[[File:2025-11-20 15-11 1.png|800x800px]]

File:2025-11-20 15-11 1.png

2025-11-20T14:13:45Z

Davrot:

2025-11-20 15-11 1

File:2025-11-20 15-11.png

2025-11-20T14:13:10Z

Davrot:

2025-11-20 15-11

Uni Datastorage Logi

2025-11-20T14:09:11Z

Davrot:

File:2025-11-20 14-51 1.png

2025-11-20T14:08:56Z

Davrot:

2025-11-20 14-51 1

File:2025-11-20 14-51.png

2025-11-20T14:07:45Z

Davrot:

2025-11-20 14-51

File:2025-11-20 14-50.png

2025-11-20T14:05:49Z

Davrot:

2025-11-20 14-50

File:2025-11-20 14-49 1.png

2025-11-20T14:05:14Z

Davrot:

2025-11-20 14-49 1

File:2025-11-20 14-49.png

2025-11-20T14:04:21Z

Davrot:

2025-11-20 14-49

File:2025-11-20 14-48 1.png

2025-11-20T14:03:40Z

Davrot:

2025-11-20 14-48 1

File:2025-11-20 14-48.png

2025-11-20T14:03:01Z

Davrot:

2025-11-20 14-48

Uni Datastorage Logi

2025-11-20T14:00:42Z

Davrot: Created page with "== Logi Storage beantragen == Die Online Tools sind der Dreh und Angelpunkt: https://onlinetools.zfn.uni-bremen.de/ === Funktionsaccount anlegen === 800x800px Die Daten "müssen" durch einen Funktionsaccount verwaltet werden. Wenn der Funktionsaccount genehmigt wurde mit dem Funktionsaccount einloggen. === Gruppe anlegen === In die Gruppenverwaltung gehen und eine neue Gruppe beantragen: 800x800px File:..."

File:2025-11-20 14-59.png

2025-11-20T14:00:20Z

Davrot:

2025-11-20 14-59

File:2025-11-20 14-47.png

2025-11-20T13:58:21Z

Davrot:

2025-11-20 14-47

File:2025-11-20 14-44 1.png

2025-11-20T13:57:13Z

Davrot:

2025-11-20 14-44 1

File:2025-11-20 14-44.png

2025-11-20T13:54:51Z

Davrot:

2025-11-20 14-44

Main Page

2025-11-20T13:52:57Z

Davrot:

Xpra

2025-11-14T13:03:15Z

Davrot: /* Install xpra (fedora) */

xpra is the tmux for X windows, they say...

=== Install xpra ===

* Install xpra (fedora)
<syntaxhighlight lang="bash">
sudo dnf -y install xpra
</syntaxhighlight>

=== The test setup ===

* The server is at 10.10.0.242, which can be reached by ssh (134.102.55.231 via ssh port 11081) or locally under 10.10.0.242.
* We want to run code-insiders on the server
* We want to access the code-insiders window from the home office as well as the office in the university.

=== The application ===
Start the application (here code-insiders): <syntaxhighlight lang="bash">
xpra start :100 --start="code-insiders" --bind-tcp=0.0.0.0:10000
</syntaxhighlight>

=== Without SSH Tunneling ===
Means that we are in the same network or are using a VPN<syntaxhighlight lang="bash">
xpra attach tcp://10.10.0.242:10000
</syntaxhighlight>

=== With SSH Tunneling ===
Making a tunnel from home via the ssh gate way (134.102.55.231 with ssh port on 11081) to (gate2 i.e. 10.10.0.242):<syntaxhighlight lang="bash">
ssh -p 11081 -L 10000:10.10.0.242:10000 davrot@134.102.55.231
</syntaxhighlight>Connect to the xpra session: <syntaxhighlight lang="bash">
xpra attach tcp://localhost:10000
</syntaxhighlight>

Xpra

2025-11-14T13:02:54Z

Davrot: Created page with "xpra is the tmux for X windows, they say... === Install xpra === ==== Install xpra (fedora) ==== <syntaxhighlight lang="bash"> sudo dnf -y install xpra </syntaxhighlight> === The test setup === * The server is at 10.10.0.242, which can be reached by ssh (134.102.55.231 via ssh port 11081) or locally under 10.10.0.242. * We want to run code-insiders on the server * We want to access the code-insiders window from the home office as well as the office in the university..."

xpra is the tmux for X windows, they say...

=== Install xpra ===

==== Install xpra (fedora) ====
<syntaxhighlight lang="bash">
sudo dnf -y install xpra
</syntaxhighlight>

=== The test setup ===

* The server is at 10.10.0.242, which can be reached by ssh (134.102.55.231 via ssh port 11081) or locally under 10.10.0.242.
* We want to run code-insiders on the server
* We want to access the code-insiders window from the home office as well as the office in the university.

=== The application ===
Start the application (here code-insiders): <syntaxhighlight lang="bash">
xpra start :100 --start="code-insiders" --bind-tcp=0.0.0.0:10000
</syntaxhighlight>

=== Without SSH Tunneling ===
Means that we are in the same network or are using a VPN<syntaxhighlight lang="bash">
xpra attach tcp://10.10.0.242:10000
</syntaxhighlight>

=== With SSH Tunneling ===
Making a tunnel from home via the ssh gate way (134.102.55.231 with ssh port on 11081) to (gate2 i.e. 10.10.0.242):<syntaxhighlight lang="bash">
ssh -p 11081 -L 10000:10.10.0.242:10000 davrot@134.102.55.231
</syntaxhighlight>Connect to the xpra session: <syntaxhighlight lang="bash">
xpra attach tcp://localhost:10000
</syntaxhighlight>

Main Page

2025-11-14T12:58:53Z

Davrot: /* Offtopic */

(Please ignore Create Account. Use '''Log in'''. The system will use autocreate to create your Wiki account if you have a University of Bremen, FB1 git or overleaf account.)

=== Python ===

* [[Python Tutorial]]
* [[Git jupyterlab]]

=== chat-ai.academiccloud.de and VS Code ===

* [[Get the API key]]
* [[Config VS Code (Insiders)]]

=== Offtopic ===
* [[Computer admin tutorials]]
* [[Notizen zu Cloud-Instanzen und Services]]
* [[Thunderbird und der NextCloud Kalender]]
* [[Wie benutze ich Vaultwarden]]
* Linux: [[xpra]] connect to your application from "anywhere"

Get the API key

2025-11-03T17:56:41Z

Davrot:

We start the voyage here: https://kisski.gwdg.de/en/leistungen/2-02-llm-service/

Click book:

[[File:2025-11-03 18-42.png|800x800px]]

Continue:

[[File:2025-11-03 18-43.png|800x800px]]

Select the SSO option:

[[File:2025-11-03 18-43 1.png|800x800px]]

Find University of Bremen and select it:

[[File:2025-11-03 18-44.png|800x800px]]

You are then redirected to the University of Bremen Identity Management:

[[File:2025-11-03 18-44 1.png|965x965px]]

Some fine-print to understand:

[[File:2025-11-03 18-45.png|985x985px]]

[[File:2025-11-03 18-45 1.png|718x718px]]

Back to the request form: You need to fill out everything!!!

[[File:2025-11-03 18-45 2.png|816x816px]]

More to click and fill out. For the why, I wrote that I need the API Key to connect VS Code with the LLM models.

[[File:2025-11-03 18-46.png|800x800px]]

First you get an automatic message. After a bit longer you will get the API key in a second email.

Test your API key:<syntaxhighlight lang="python3">
from openai import OpenAI

# API configuration
api_key = "XXXXXXXXXXXXXXXXX" # Replace with your API key
base_url = "https://chat-ai.academiccloud.de/v1"

# Start OpenAI client
client = OpenAI(api_key=api_key, base_url=base_url)

# List all available models
models = client.models.list()

# Print all models
for model in models:
print(model.id)
print()
</syntaxhighlight>The result is:<syntaxhighlight lang="python-console">
qwen3-coder-30b-a3b-instruct
meta-llama-3.1-8b-instruct
openai-gpt-oss-120b
gemma-3-27b-it
qwen3-30b-a3b-thinking-2507
qwen3-30b-a3b-instruct-2507
qwen3-32b
qwen3-235b-a22b
llama-3.3-70b-instruct
qwen2.5-vl-72b-instruct
medgemma-27b-it
qwq-32b
deepseek-r1
deepseek-r1-distill-llama-70b
mistral-large-instruct
qwen2.5-coder-32b-instruct
internvl2.5-8b
teuken-7b-instruct-research
codestral-22b
llama-3.1-sauerkrautlm-70b-instruct
meta-llama-3.1-8b-rag
qwen2.5-omni-7b
</syntaxhighlight>

File:2025-11-03 18-46.png

2025-11-03T17:54:59Z

Davrot:

2025-11-03 18-46

File:2025-11-03 18-45 2.png

2025-11-03T17:54:01Z

Davrot:

2025-11-03 18-45 2

File:2025-11-03 18-45 1.png

2025-11-03T17:53:29Z

Davrot:

2025-11-03 18-45 1

File:2025-11-03 18-45.png

2025-11-03T17:52:13Z

Davrot:

2025-11-03 18-45

File:2025-11-03 18-44 1.png

2025-11-03T17:51:16Z

Davrot:

2025-11-03 18-44 1

Get the API key

2025-11-03T17:50:44Z

Davrot:

File:2025-11-03 18-44.png

2025-11-03T17:50:06Z

Davrot:

2025-11-03 18-44

File:2025-11-03 18-43 1.png

2025-11-03T17:49:23Z

Davrot:

2025-11-03 18-43 1

File:2025-11-03 18-43.png

2025-11-03T17:48:45Z

Davrot:

2025-11-03 18-43

File:2025-11-03 18-42.png

2025-11-03T17:47:13Z

Davrot:

2025-11-03 18-42

Config VS Code (Insiders)

2025-11-03T17:41:44Z

Davrot:

For the foreseeable future you need to install the VS Code '''''Insiders''''' version!!! See [https://code.visualstudio.com/insiders/ here]

Ctrl+Shift+P: Preferences: Open User Settings (JSON)

This is an example. Please note the "qwen3-32" selects the model not "name": "qwen3-32"<syntaxhighlight lang="json">
{
"github.copilot.chat.customOAIModels": {
"qwen3-32b": {
"name": "qwen3-32b",
"url": "https://chat-ai.academiccloud.de/v1",
"toolCalling": false,
"vision": false,
"thinking": true,
"maxInputTokens": 128000,
"maxOutputTokens": 8192,
"requiresAPIKey": true
}
},
"workbench.startupEditor": "none"
}
</syntaxhighlight>Next

Ctrl + Shift + P: Chat: Manage Language Models
[[File:2025-11-03 18-18.png|800x800px]]

If "OpenAI Compatible" is not listed, you need to click "+ Add Models..." and select the option. The setting icon of "OpenAI Compatible" allows you to set the API key. It will not be present, if a model of this type is running.

I had to press the non hide button in the front of the model name.

I closed and opened VS Code. Now I can use that model under Plan, Ask and Edit but not Agent. I don't know why...

[[File:2025-11-03 18-25.png]]
Example interaction:

Example interaction:

[[File:2025-11-03 18-40.png]]

Config VS Code (Insiders)

2025-11-03T17:41:11Z

Davrot:

For the foreseeable future you need to install the VS Code '''''Insiders''''' version!!! See [https://code.visualstudio.com/insiders/ here]

Ctrl+Shift+P: Preferences: Open User Settings (JSON)

This is an example. Please note the "qwen3-32" selects the model not "name": "qwen3-32"<syntaxhighlight lang="json">
{
"github.copilot.chat.customOAIModels": {
"qwen3-32b": {
"name": "qwen3-32b",
"url": "https://chat-ai.academiccloud.de/v1",
"toolCalling": false,
"vision": false,
"thinking": true,
"maxInputTokens": 128000,
"maxOutputTokens": 8192,
"requiresAPIKey": true
}
},
"workbench.startupEditor": "none"
}
</syntaxhighlight>Next

Ctrl + Shift + P: Chat: Manage Language Models
[[File:2025-11-03 18-18.png|800x800px]]
If "OpenAI Compatible" is not listed, you need to click "+ Add Models..." and select the option. The setting icon of "OpenAI Compatible" allows you to set the API key. It will not be present, if a model of this type is running.

I had to press the non hide button in the front of the model name.

I closed and opened VS Code. Now I can use that model under Plan, Ask and Edit but not Agent. I don't know why...

[[File:2025-11-03 18-25.png]]

Example interaction:

[[File:2025-11-03 18-40.png]]

File:2025-11-03 18-40.png

2025-11-03T17:40:45Z

Davrot:

2025-11-03 18-40

File:2025-11-03 18-25.png

2025-11-03T17:39:13Z

Davrot:

2025-11-03 18-25

File:2025-11-03 18-18.png

2025-11-03T17:34:23Z

Davrot:

2025-11-03 18-18

Config VS Code (Insiders)

2025-11-03T17:32:17Z

Davrot: Created page with "For the foreseeable future you need to install the VS Code '''''Insiders''''' version!!! See [https://code.visualstudio.com/insiders/ here] Ctrl+Shift+P : Preferences: Open User Settings (JSON) This is an example. Please note the "qwen3-32" selects the model not "name": "qwen3-32"<syntaxhighlight lang="json"> { "github.copilot.chat.customOAIModels": { "qwen3-32b": { "name": "qwen3-32b", "url": "https://chat-ai.academiccloud.d..."

Get the API key

2025-11-03T17:28:02Z

Davrot: Created page with "Test your API key:<syntaxhighlight lang="python3"> from openai import OpenAI # API configuration api_key = "XXXXXXXXXXXXXXXXX" # Replace with your API key base_url = "https://chat-ai.academiccloud.de/v1" # Start OpenAI client client = OpenAI(api_key=api_key, base_url=base_url) # List all available models models = client.models.list() # Print all models for model in models: print(model.id) print() </syntaxhighlight>The result is:<syntaxhighlight lang="python-cons..."

Test your API key:<syntaxhighlight lang="python3">
from openai import OpenAI

# API configuration
api_key = "XXXXXXXXXXXXXXXXX" # Replace with your API key
base_url = "https://chat-ai.academiccloud.de/v1"

# Start OpenAI client
client = OpenAI(api_key=api_key, base_url=base_url)

# List all available models
models = client.models.list()

# Print all models
for model in models:
print(model.id)
print()
</syntaxhighlight>The result is:<syntaxhighlight lang="python-console">
qwen3-coder-30b-a3b-instruct
meta-llama-3.1-8b-instruct
openai-gpt-oss-120b
gemma-3-27b-it
qwen3-30b-a3b-thinking-2507
qwen3-30b-a3b-instruct-2507
qwen3-32b
qwen3-235b-a22b
llama-3.3-70b-instruct
qwen2.5-vl-72b-instruct
medgemma-27b-it
qwq-32b
deepseek-r1
deepseek-r1-distill-llama-70b
mistral-large-instruct
qwen2.5-coder-32b-instruct
internvl2.5-8b
teuken-7b-instruct-research
codestral-22b
llama-3.1-sauerkrautlm-70b-instruct
meta-llama-3.1-8b-rag
qwen2.5-omni-7b
</syntaxhighlight>

Main Page

2025-11-03T17:26:26Z

Davrot:

[[Python Tutorial]]

[[Git jupyterlab]]

=== chat-ai.academiccloud.de and VS Code ===

* [[Get the API key]]
* [[Config VS Code (Insiders)]]

=== Offtopic ===
* [[Computer admin tutorials]]
* [[Notizen zu Cloud-Instanzen und Services]]
* [[Thunderbird und der NextCloud Kalender]]
* [[Wie benutze ich Vaultwarden]]

Python Tutorial

2025-10-23T17:21:35Z

Davrot: /* PyTorch */

== How to Python in computational neuroscience, data mining, and more ==
All the tutorials are tested with Python 3.11.x. Older version might have a problem with the new versions of type anotations.

[https://www.youtube.com/playlist?list=PLK_Ujz7qXyqMhAlJcTke-qq5hytk7djCc Anna Förster: German Python Videos from the FB1 ComCast Team]

[https://atticlectures.net/scipro/python-2024/ Bálint Aradi (FB1): Attic Lectures (English python course)]

=== Flow chart ===

* [[Basic Structure of a Computer]]
* [[Representation of Numbers in the Computer]]
*[[Systematic Programming]]
*[[Flow chart symbols]]
*[[Examples]]
*[[Flow chart for baking bread]]

=== Workflow ===

* [[Python installation]]
* [[VS Code installation]]
* [[VS Code configuration]]
* [[VS Code Microsoft Tutorials]]
* [[VS Code Python Interactive window]]
* [[VS Code Markdown]]
* [[VS Code Debugging]]
* [[VS Code Working remotely via ssh]]
Important VS Code notes:

* You can mark segments of source node with your mouse (or keyboard) and use the TAB key to increase the level of the indentation or use SHIFT + TAB do decrease the indentation level.
* Linux: CTRL + SHIFT + 7 toggles between comment and normal source code.
* The function key F2 allows you to change variable and function names. VS Code goes through all the node in your Project directory and changes all occurrences of the function or variable name accordingly. The same is true if you change a file name in a project directory.

=== Python: The Basics of the basics ===

* [[Overview]]
* [[Hello, Python]]
** [[input, print, string, int, float]]
* [[Style Rulez]]
* [[Programming Recommendations]]
** [[Assert]]
* [[Basic Math Operations]]
* [[Truth Value Testing]]
* [[Formatted String Literals]]
* [[Flow Control Overview]]
** [[Flow Control: if, elif, else]]
** [[Flow Control: for-loop]]
** [[Flow Control: while, pass, break, continue]]
** [[Flow Control: match case]]
* Sequence Types
** [[Lists]]
*** [[List Comprehensions|List Comprehensions]]
**[[Tuple]]
***[[zip]]
*Mapping Types
**[[Dict|Dict]]
*[[Functions]]
*[[Type annotations]]
*[[Files]]
*[[JSON and dict for parameter files]]
*[[Creating order via sub-directories: os.makedirs]]
*[[Finding files in a directory: glob]]
*[[Class]]
*[[Exceptions (try / except)]]
*[[Importing Modules]]
*[[Built-in Functions]]
*[[Built-in Keywords]]

=== Python: Special topics ===

* [[pickle: save and load Python objects]]
* [[The Python Standard Library|The Python Standard Library]]
* [[Dataclass]]
* [[Organizing parameters: dataclasses and dataconf]]
* [[ProcessPoolExecutor: A fast way to implement multiprocessing]]
* [[Logging]]
* [[Python Scopes and Namespaces]]
* [[Collection of distinct hashable objects -- set and frozenset]]

=== Numpy: The Basics of the basics ===

* [[The N-dimensional array (ndarray)]]
** [[set_printoptions]]
* [[Dimensions and shape]]
** [[Broadcasting: Automatic adaption of dimensions|Broadcasting: Automatic adaption of dimensions]]
*[[Making a new matrix]]
**[[Making a matrix from numerical ranges]]
* [[Convert other data into numpy arrays e.g. asarray]]
* [[New matrix]]
* [[Save and load]]
* [[Reshape and flatten]]
* [[Slices and Views]]
* [[Concatenate Matrices and arrays]]
* [[Merging matrices]]
* [[Unique]]
* [[Where]]
** [[Piecewise]]
* [[Extending an existing matrix: tile, repeat, pad]]
* [[Boolean matricies and logic functions]]
* [[Advanced Indexing]]
** [[Ravel and UnRavel]]
* [[Available dtypes]]
* [[Constants]]
* [[Math functions]]
* [[Linear algebra]]
* [[Random numbers the non-legacy way]]
* [[Statistics]]
* [[FFT]]
** [[rfft and spectral power]]
** [[Spectral power and averaging over trials]]
* [[Meshgrid]]
* [[Flip, rot90, and roll a matrix]]
* Iterate
** [[ndenumerate]]
** [[ndindex]]
** [[flat]]

=== Numpy: Special topics ===

* [[Einstein summation]]
* [[Numba: Numpy just in time compiler -- speeding Numpy up]]
* [[Memory layout of Numpy matrices]]
* [[Stack and Split, Compress]]
* [[Beyond normal np.save]]
* [[Trim Zeros of a 1d array]]
* Iterating over an array / matrix
** [[nditer provides many ways to visit all the elements of one or more arrays]]
** [[Replacing an inner for loop with apply_along_axis]]
** [[nested_iters]]
* [[Manipulation of integers and their bits]]
* [[Numpy and JSON over Pandas]]
* [[Resize: Compensation for bad planning? Don't!]]
* [[Dealing with the main diagonal / triangles of a matrix]]

=== Numpy: Matlab topics ===

* [[Dealing with Matlab files]]
* [[Matlab is also just a Python package]]
* [[Running Python remotely from Matlab]]

In the case you know Matlab check here: [[NumPy for MATLAB users]]

=== Matplotlib.pyplot ===

* [[Simple plot and imshow examples]]
* [[Subplot]]
* [[subplots and gridspec: A more flexible placement]]
* [[Overview of the available functions]]
* [[Animation and Slider]]

=== Pandas ===

* [[Basics]]

=== Machine learning: Sci-kit Learn ===

* [[Sci-kit Overview]]
* [[KMeans]]
* [[PCA]]
* [[FastICA]]
* [[Support Vector Machine]]
* [[K Nearest Neighbours (pure numpy)]]

=== Machine learning: Pure numpy ===
* [[ROC (pure numpy)|ROC]]
* [[K Nearest Neighbours (pure numpy)|K Nearest Neighbours]]

=== SciPy ===

* [[Remove a common signal from your data with SVD]]
* [[scipy.signal: Butterworth low, high and band-pass]]

=== Python: Questions of spectral nature ===

* [[PyWavelets: Wavelet Transforms in Python]]
* [[Instantanious Spectral Coherence]]
** [[Linearize the spectral coherence]]

=== Python: Daily little helper ===

* [[TQDM: Make your progress visible]]
* [[Argh: Organize your command line arguments]]
* [[psutil vs os.cpu_count: How many "CPUs" do I have?]]
* [[ZeroMQ: Microservices as well as connecting computers via message queue]]
* [[Austin: Time and memory profiling]]

=== OpenCV2 and Python ===

* [[OpenCV2: Play, write, read a video]]
* [[How to read a webcam with CV2]]

=== PyTorch ===

* PyTorch lecture
** [https://mscneuro.neuro.uni-bremen.de/images/e/e3/PyTorch-Part0_and_4-Training_a_network.pdf Part 0 and 4]
** [https://mscneuro.neuro.uni-bremen.de/images/5/5f/PyTorch-Part1-a_stroll_through_the_zoo.pdf Part 1]
** [https://mscneuro.neuro.uni-bremen.de/images/8/83/PyTorch-Part2-Tensors_et_al.pdf Part 2]
** [https://mscneuro.neuro.uni-bremen.de/index.php/File:PyTorch-Part3-Training_a_network.pdf Part 3]

* [[Get CUDA ready!]]
* [[Converting the original MNIST files into numpy]]
* [[Interfacing Data]]
* [[Data augmentation]]
* [[Layers]]
* [[Creating networks]]
* [[Train the network]]
* [[Fisher Exact Test: Test if your performance difference is significant]]
* [[Write your own layer]]
** [[Replace the automatic autograd with your own torch.autograd.Function]]
*[[How to take advantage of an optimizer for your non-Pytorch project]]
*[[How to take advantage of a learning rate scheduler for your non-Pytorch project]]
*[[Unfold: How to manually calculate the indices for a sliding 2d window]]

=== PyBind11 ===

* [[Expanding Python with C++ modules]]
* [[The fast and furious way (CPU and GPU CUDA)]]
* [[PyBind11 Stub-Generation]]

=== Tensorflow / Keras ===

* [[A fast non-introduction]]

=== Sympy ===

* [[Symbolic Computation]]

=== Numerical Integration, Differentiation, and Differential Equations ===

* [[Integration and Differentiation]]
* [[Differential Equations]]

=== Arduino ===

* [[Basics with Python / Matlab]]

=== Matlab: Basics ===

* [[Basic Commands and Variables]]
* [[Matlab Graphics]]
* [[Vectorization and Vector Calculus in Matlab]]
* [[Matlab Data Analysis]]

=== Other topics ===

* [[Open Source Tools]]
* [[Machine Learning Resources]]
* [[Datasets]]

=== S1: Advanced Programming (last update 16.02.2024) ===
* [[S1 Advanced programming and data analysis]]
* [[Preperations]]
* [[Task 1 -- Classycal neurons: Simulation and Mathematical Anaylsis]]
* [[Task 2 -- Collective coherent cortices: Data analysis]]
* Neuron Models Equations
** For detailed descriptions, please see:
*** [https://neuronaldynamics.epfl.ch/online 'Neuronal Dynamics' textbook]
*** [https://boulderschool.yale.edu/sites/default/files/files/DayanAbbott.pdf 'Theoretical Neuroscience' textbook]

* Neuron Models Equations -- Rate-based neurons
** [[DivInE-model for MT neurons]]

* Neuron Models Equations -- Spiking neurons without explicit spike generation mechanism
** [[Leaky Integrate-and-Fire]]
** [[Exponential Integrate-and-Fire]]
** [[Quadratic Integrate-and-Fire]]
** [[Connor Stevens]]

* [[References]]
* Task 1 -- Pictures for comparision
** [[Task 1 --Mandatory Tasks]]

* Task 2 -- Pictures for comparision
** [[Task 2 -- Mandatory Tasks]]
** [[Task 2 -- Voluntary Tasks: Preprocessing]]
** [[Task 2 -- Voluntary Tasks: More Information!]]
=== Advanced Studies ===
* Material from ages past
** [[2022: Preparation -- Python class with and without classes]]
** [[2022: Deep Networks and Pytorch]]
** [[2022: Divisive inhibition: a dynamical circuit for change detection]]
** [[2022: Synchronization and dynamic oscillations in the visual system]]
** [[2020: Deep Networks and Tensor Flow]]
** [[2020: Divisive Normalization -- a Universal Concept for Adaptive Dynamics and Function of Cortical Circuits]]
** [[2020: Recurrent networks: Temporal dynamics and synchronization]]
** [[2017: Oscillations and information routing: CTC model]]
** [[2017: Change detection: The DivInE-Model]]
** [[2017: Contour Integration]]
** [[2017: Computation Spike by Spike]]
** [[2017: Natural scenes and sparse coding in visual cortex]]

Python Tutorial

2025-10-23T17:20:25Z

Davrot: /* PyTorch */

== How to Python in computational neuroscience, data mining, and more ==
All the tutorials are tested with Python 3.11.x. Older version might have a problem with the new versions of type anotations.

[https://www.youtube.com/playlist?list=PLK_Ujz7qXyqMhAlJcTke-qq5hytk7djCc Anna Förster: German Python Videos from the FB1 ComCast Team]

[https://atticlectures.net/scipro/python-2024/ Bálint Aradi (FB1): Attic Lectures (English python course)]

=== Flow chart ===

* [[Basic Structure of a Computer]]
* [[Representation of Numbers in the Computer]]
*[[Systematic Programming]]
*[[Flow chart symbols]]
*[[Examples]]
*[[Flow chart for baking bread]]

=== Workflow ===

* [[Python installation]]
* [[VS Code installation]]
* [[VS Code configuration]]
* [[VS Code Microsoft Tutorials]]
* [[VS Code Python Interactive window]]
* [[VS Code Markdown]]
* [[VS Code Debugging]]
* [[VS Code Working remotely via ssh]]
Important VS Code notes:

* You can mark segments of source node with your mouse (or keyboard) and use the TAB key to increase the level of the indentation or use SHIFT + TAB do decrease the indentation level.
* Linux: CTRL + SHIFT + 7 toggles between comment and normal source code.
* The function key F2 allows you to change variable and function names. VS Code goes through all the node in your Project directory and changes all occurrences of the function or variable name accordingly. The same is true if you change a file name in a project directory.

=== Python: The Basics of the basics ===

* [[Overview]]
* [[Hello, Python]]
** [[input, print, string, int, float]]
* [[Style Rulez]]
* [[Programming Recommendations]]
** [[Assert]]
* [[Basic Math Operations]]
* [[Truth Value Testing]]
* [[Formatted String Literals]]
* [[Flow Control Overview]]
** [[Flow Control: if, elif, else]]
** [[Flow Control: for-loop]]
** [[Flow Control: while, pass, break, continue]]
** [[Flow Control: match case]]
* Sequence Types
** [[Lists]]
*** [[List Comprehensions|List Comprehensions]]
**[[Tuple]]
***[[zip]]
*Mapping Types
**[[Dict|Dict]]
*[[Functions]]
*[[Type annotations]]
*[[Files]]
*[[JSON and dict for parameter files]]
*[[Creating order via sub-directories: os.makedirs]]
*[[Finding files in a directory: glob]]
*[[Class]]
*[[Exceptions (try / except)]]
*[[Importing Modules]]
*[[Built-in Functions]]
*[[Built-in Keywords]]

=== Python: Special topics ===

* [[pickle: save and load Python objects]]
* [[The Python Standard Library|The Python Standard Library]]
* [[Dataclass]]
* [[Organizing parameters: dataclasses and dataconf]]
* [[ProcessPoolExecutor: A fast way to implement multiprocessing]]
* [[Logging]]
* [[Python Scopes and Namespaces]]
* [[Collection of distinct hashable objects -- set and frozenset]]

=== Numpy: The Basics of the basics ===

* [[The N-dimensional array (ndarray)]]
** [[set_printoptions]]
* [[Dimensions and shape]]
** [[Broadcasting: Automatic adaption of dimensions|Broadcasting: Automatic adaption of dimensions]]
*[[Making a new matrix]]
**[[Making a matrix from numerical ranges]]
* [[Convert other data into numpy arrays e.g. asarray]]
* [[New matrix]]
* [[Save and load]]
* [[Reshape and flatten]]
* [[Slices and Views]]
* [[Concatenate Matrices and arrays]]
* [[Merging matrices]]
* [[Unique]]
* [[Where]]
** [[Piecewise]]
* [[Extending an existing matrix: tile, repeat, pad]]
* [[Boolean matricies and logic functions]]
* [[Advanced Indexing]]
** [[Ravel and UnRavel]]
* [[Available dtypes]]
* [[Constants]]
* [[Math functions]]
* [[Linear algebra]]
* [[Random numbers the non-legacy way]]
* [[Statistics]]
* [[FFT]]
** [[rfft and spectral power]]
** [[Spectral power and averaging over trials]]
* [[Meshgrid]]
* [[Flip, rot90, and roll a matrix]]
* Iterate
** [[ndenumerate]]
** [[ndindex]]
** [[flat]]

=== Numpy: Special topics ===

* [[Einstein summation]]
* [[Numba: Numpy just in time compiler -- speeding Numpy up]]
* [[Memory layout of Numpy matrices]]
* [[Stack and Split, Compress]]
* [[Beyond normal np.save]]
* [[Trim Zeros of a 1d array]]
* Iterating over an array / matrix
** [[nditer provides many ways to visit all the elements of one or more arrays]]
** [[Replacing an inner for loop with apply_along_axis]]
** [[nested_iters]]
* [[Manipulation of integers and their bits]]
* [[Numpy and JSON over Pandas]]
* [[Resize: Compensation for bad planning? Don't!]]
* [[Dealing with the main diagonal / triangles of a matrix]]

=== Numpy: Matlab topics ===

* [[Dealing with Matlab files]]
* [[Matlab is also just a Python package]]
* [[Running Python remotely from Matlab]]

In the case you know Matlab check here: [[NumPy for MATLAB users]]

=== Matplotlib.pyplot ===

* [[Simple plot and imshow examples]]
* [[Subplot]]
* [[subplots and gridspec: A more flexible placement]]
* [[Overview of the available functions]]
* [[Animation and Slider]]

=== Pandas ===

* [[Basics]]

=== Machine learning: Sci-kit Learn ===

* [[Sci-kit Overview]]
* [[KMeans]]
* [[PCA]]
* [[FastICA]]
* [[Support Vector Machine]]
* [[K Nearest Neighbours (pure numpy)]]

=== Machine learning: Pure numpy ===
* [[ROC (pure numpy)|ROC]]
* [[K Nearest Neighbours (pure numpy)|K Nearest Neighbours]]

=== SciPy ===

* [[Remove a common signal from your data with SVD]]
* [[scipy.signal: Butterworth low, high and band-pass]]

=== Python: Questions of spectral nature ===

* [[PyWavelets: Wavelet Transforms in Python]]
* [[Instantanious Spectral Coherence]]
** [[Linearize the spectral coherence]]

=== Python: Daily little helper ===

* [[TQDM: Make your progress visible]]
* [[Argh: Organize your command line arguments]]
* [[psutil vs os.cpu_count: How many "CPUs" do I have?]]
* [[ZeroMQ: Microservices as well as connecting computers via message queue]]
* [[Austin: Time and memory profiling]]

=== OpenCV2 and Python ===

* [[OpenCV2: Play, write, read a video]]
* [[How to read a webcam with CV2]]

=== PyTorch ===

* PyTorch lecture
** [https://mscneuro.neuro.uni-bremen.de/images/e/e3/PyTorch-Part0_and_4-Training_a_network.pdf Part 0 and 4]
** [https://mscneuro.neuro.uni-bremen.de/images/5/5f/PyTorch-Part1-a_stroll_through_the_zoo.pdf Part 1]
** Part 2
** [https://mscneuro.neuro.uni-bremen.de/index.php/File:PyTorch-Part3-Training_a_network.pdf Part 3]

* [[Get CUDA ready!]]
* [[Converting the original MNIST files into numpy]]
* [[Interfacing Data]]
* [[Data augmentation]]
* [[Layers]]
* [[Creating networks]]
* [[Train the network]]
* [[Fisher Exact Test: Test if your performance difference is significant]]
* [[Write your own layer]]
** [[Replace the automatic autograd with your own torch.autograd.Function]]
*[[How to take advantage of an optimizer for your non-Pytorch project]]
*[[How to take advantage of a learning rate scheduler for your non-Pytorch project]]
*[[Unfold: How to manually calculate the indices for a sliding 2d window]]

=== PyBind11 ===

* [[Expanding Python with C++ modules]]
* [[The fast and furious way (CPU and GPU CUDA)]]
* [[PyBind11 Stub-Generation]]

=== Tensorflow / Keras ===

* [[A fast non-introduction]]

=== Sympy ===

* [[Symbolic Computation]]

=== Numerical Integration, Differentiation, and Differential Equations ===

* [[Integration and Differentiation]]
* [[Differential Equations]]

=== Arduino ===

* [[Basics with Python / Matlab]]

=== Matlab: Basics ===

* [[Basic Commands and Variables]]
* [[Matlab Graphics]]
* [[Vectorization and Vector Calculus in Matlab]]
* [[Matlab Data Analysis]]

=== Other topics ===

* [[Open Source Tools]]
* [[Machine Learning Resources]]
* [[Datasets]]

=== S1: Advanced Programming (last update 16.02.2024) ===
* [[S1 Advanced programming and data analysis]]
* [[Preperations]]
* [[Task 1 -- Classycal neurons: Simulation and Mathematical Anaylsis]]
* [[Task 2 -- Collective coherent cortices: Data analysis]]
* Neuron Models Equations
** For detailed descriptions, please see:
*** [https://neuronaldynamics.epfl.ch/online 'Neuronal Dynamics' textbook]
*** [https://boulderschool.yale.edu/sites/default/files/files/DayanAbbott.pdf 'Theoretical Neuroscience' textbook]

* Neuron Models Equations -- Rate-based neurons
** [[DivInE-model for MT neurons]]

* Neuron Models Equations -- Spiking neurons without explicit spike generation mechanism
** [[Leaky Integrate-and-Fire]]
** [[Exponential Integrate-and-Fire]]
** [[Quadratic Integrate-and-Fire]]
** [[Connor Stevens]]

* [[References]]
* Task 1 -- Pictures for comparision
** [[Task 1 --Mandatory Tasks]]

* Task 2 -- Pictures for comparision
** [[Task 2 -- Mandatory Tasks]]
** [[Task 2 -- Voluntary Tasks: Preprocessing]]
** [[Task 2 -- Voluntary Tasks: More Information!]]
=== Advanced Studies ===
* Material from ages past
** [[2022: Preparation -- Python class with and without classes]]
** [[2022: Deep Networks and Pytorch]]
** [[2022: Divisive inhibition: a dynamical circuit for change detection]]
** [[2022: Synchronization and dynamic oscillations in the visual system]]
** [[2020: Deep Networks and Tensor Flow]]
** [[2020: Divisive Normalization -- a Universal Concept for Adaptive Dynamics and Function of Cortical Circuits]]
** [[2020: Recurrent networks: Temporal dynamics and synchronization]]
** [[2017: Oscillations and information routing: CTC model]]
** [[2017: Change detection: The DivInE-Model]]
** [[2017: Contour Integration]]
** [[2017: Computation Spike by Spike]]
** [[2017: Natural scenes and sparse coding in visual cortex]]

Python Tutorial

2025-10-23T17:20:12Z

Davrot: /* PyTorch */

== How to Python in computational neuroscience, data mining, and more ==
All the tutorials are tested with Python 3.11.x. Older version might have a problem with the new versions of type anotations.

[https://www.youtube.com/playlist?list=PLK_Ujz7qXyqMhAlJcTke-qq5hytk7djCc Anna Förster: German Python Videos from the FB1 ComCast Team]

[https://atticlectures.net/scipro/python-2024/ Bálint Aradi (FB1): Attic Lectures (English python course)]

=== Flow chart ===

* [[Basic Structure of a Computer]]
* [[Representation of Numbers in the Computer]]
*[[Systematic Programming]]
*[[Flow chart symbols]]
*[[Examples]]
*[[Flow chart for baking bread]]

=== Workflow ===

* [[Python installation]]
* [[VS Code installation]]
* [[VS Code configuration]]
* [[VS Code Microsoft Tutorials]]
* [[VS Code Python Interactive window]]
* [[VS Code Markdown]]
* [[VS Code Debugging]]
* [[VS Code Working remotely via ssh]]
Important VS Code notes:

* You can mark segments of source node with your mouse (or keyboard) and use the TAB key to increase the level of the indentation or use SHIFT + TAB do decrease the indentation level.
* Linux: CTRL + SHIFT + 7 toggles between comment and normal source code.
* The function key F2 allows you to change variable and function names. VS Code goes through all the node in your Project directory and changes all occurrences of the function or variable name accordingly. The same is true if you change a file name in a project directory.

=== Python: The Basics of the basics ===

* [[Overview]]
* [[Hello, Python]]
** [[input, print, string, int, float]]
* [[Style Rulez]]
* [[Programming Recommendations]]
** [[Assert]]
* [[Basic Math Operations]]
* [[Truth Value Testing]]
* [[Formatted String Literals]]
* [[Flow Control Overview]]
** [[Flow Control: if, elif, else]]
** [[Flow Control: for-loop]]
** [[Flow Control: while, pass, break, continue]]
** [[Flow Control: match case]]
* Sequence Types
** [[Lists]]
*** [[List Comprehensions|List Comprehensions]]
**[[Tuple]]
***[[zip]]
*Mapping Types
**[[Dict|Dict]]
*[[Functions]]
*[[Type annotations]]
*[[Files]]
*[[JSON and dict for parameter files]]
*[[Creating order via sub-directories: os.makedirs]]
*[[Finding files in a directory: glob]]
*[[Class]]
*[[Exceptions (try / except)]]
*[[Importing Modules]]
*[[Built-in Functions]]
*[[Built-in Keywords]]

=== Python: Special topics ===

* [[pickle: save and load Python objects]]
* [[The Python Standard Library|The Python Standard Library]]
* [[Dataclass]]
* [[Organizing parameters: dataclasses and dataconf]]
* [[ProcessPoolExecutor: A fast way to implement multiprocessing]]
* [[Logging]]
* [[Python Scopes and Namespaces]]
* [[Collection of distinct hashable objects -- set and frozenset]]

=== Numpy: The Basics of the basics ===

* [[The N-dimensional array (ndarray)]]
** [[set_printoptions]]
* [[Dimensions and shape]]
** [[Broadcasting: Automatic adaption of dimensions|Broadcasting: Automatic adaption of dimensions]]
*[[Making a new matrix]]
**[[Making a matrix from numerical ranges]]
* [[Convert other data into numpy arrays e.g. asarray]]
* [[New matrix]]
* [[Save and load]]
* [[Reshape and flatten]]
* [[Slices and Views]]
* [[Concatenate Matrices and arrays]]
* [[Merging matrices]]
* [[Unique]]
* [[Where]]
** [[Piecewise]]
* [[Extending an existing matrix: tile, repeat, pad]]
* [[Boolean matricies and logic functions]]
* [[Advanced Indexing]]
** [[Ravel and UnRavel]]
* [[Available dtypes]]
* [[Constants]]
* [[Math functions]]
* [[Linear algebra]]
* [[Random numbers the non-legacy way]]
* [[Statistics]]
* [[FFT]]
** [[rfft and spectral power]]
** [[Spectral power and averaging over trials]]
* [[Meshgrid]]
* [[Flip, rot90, and roll a matrix]]
* Iterate
** [[ndenumerate]]
** [[ndindex]]
** [[flat]]

=== Numpy: Special topics ===

* [[Einstein summation]]
* [[Numba: Numpy just in time compiler -- speeding Numpy up]]
* [[Memory layout of Numpy matrices]]
* [[Stack and Split, Compress]]
* [[Beyond normal np.save]]
* [[Trim Zeros of a 1d array]]
* Iterating over an array / matrix
** [[nditer provides many ways to visit all the elements of one or more arrays]]
** [[Replacing an inner for loop with apply_along_axis]]
** [[nested_iters]]
* [[Manipulation of integers and their bits]]
* [[Numpy and JSON over Pandas]]
* [[Resize: Compensation for bad planning? Don't!]]
* [[Dealing with the main diagonal / triangles of a matrix]]

=== Numpy: Matlab topics ===

* [[Dealing with Matlab files]]
* [[Matlab is also just a Python package]]
* [[Running Python remotely from Matlab]]

In the case you know Matlab check here: [[NumPy for MATLAB users]]

=== Matplotlib.pyplot ===

* [[Simple plot and imshow examples]]
* [[Subplot]]
* [[subplots and gridspec: A more flexible placement]]
* [[Overview of the available functions]]
* [[Animation and Slider]]

=== Pandas ===

* [[Basics]]

=== Machine learning: Sci-kit Learn ===

* [[Sci-kit Overview]]
* [[KMeans]]
* [[PCA]]
* [[FastICA]]
* [[Support Vector Machine]]
* [[K Nearest Neighbours (pure numpy)]]

=== Machine learning: Pure numpy ===
* [[ROC (pure numpy)|ROC]]
* [[K Nearest Neighbours (pure numpy)|K Nearest Neighbours]]

=== SciPy ===

* [[Remove a common signal from your data with SVD]]
* [[scipy.signal: Butterworth low, high and band-pass]]

=== Python: Questions of spectral nature ===

* [[PyWavelets: Wavelet Transforms in Python]]
* [[Instantanious Spectral Coherence]]
** [[Linearize the spectral coherence]]

=== Python: Daily little helper ===

* [[TQDM: Make your progress visible]]
* [[Argh: Organize your command line arguments]]
* [[psutil vs os.cpu_count: How many "CPUs" do I have?]]
* [[ZeroMQ: Microservices as well as connecting computers via message queue]]
* [[Austin: Time and memory profiling]]

=== OpenCV2 and Python ===

* [[OpenCV2: Play, write, read a video]]
* [[How to read a webcam with CV2]]

=== PyTorch ===

* PyTorch lecture
** [https://mscneuro.neuro.uni-bremen.de/images/e/e3/PyTorch-Part0_and_4-Training_a_network.pdf Part 0 and 4]
** [https://mscneuro.neuro.uni-bremen.de/images/5/5f/PyTorch-Part1-a_stroll_through_the_zoo.pdf Part 1]
** Part 2
** [[File:PyTorch-Part3-Training a network.pdf|thumb]][https://mscneuro.neuro.uni-bremen.de/index.php/File:PyTorch-Part3-Training_a_network.pdf Part 3]

* [[Get CUDA ready!]]
* [[Converting the original MNIST files into numpy]]
* [[Interfacing Data]]
* [[Data augmentation]]
* [[Layers]]
* [[Creating networks]]
* [[Train the network]]
* [[Fisher Exact Test: Test if your performance difference is significant]]
* [[Write your own layer]]
** [[Replace the automatic autograd with your own torch.autograd.Function]]
*[[How to take advantage of an optimizer for your non-Pytorch project]]
*[[How to take advantage of a learning rate scheduler for your non-Pytorch project]]
*[[Unfold: How to manually calculate the indices for a sliding 2d window]]

=== PyBind11 ===

* [[Expanding Python with C++ modules]]
* [[The fast and furious way (CPU and GPU CUDA)]]
* [[PyBind11 Stub-Generation]]

=== Tensorflow / Keras ===

* [[A fast non-introduction]]

=== Sympy ===

* [[Symbolic Computation]]

=== Numerical Integration, Differentiation, and Differential Equations ===

* [[Integration and Differentiation]]
* [[Differential Equations]]

=== Arduino ===

* [[Basics with Python / Matlab]]

=== Matlab: Basics ===

* [[Basic Commands and Variables]]
* [[Matlab Graphics]]
* [[Vectorization and Vector Calculus in Matlab]]
* [[Matlab Data Analysis]]

=== Other topics ===

* [[Open Source Tools]]
* [[Machine Learning Resources]]
* [[Datasets]]

=== S1: Advanced Programming (last update 16.02.2024) ===
* [[S1 Advanced programming and data analysis]]
* [[Preperations]]
* [[Task 1 -- Classycal neurons: Simulation and Mathematical Anaylsis]]
* [[Task 2 -- Collective coherent cortices: Data analysis]]
* Neuron Models Equations
** For detailed descriptions, please see:
*** [https://neuronaldynamics.epfl.ch/online 'Neuronal Dynamics' textbook]
*** [https://boulderschool.yale.edu/sites/default/files/files/DayanAbbott.pdf 'Theoretical Neuroscience' textbook]

* Neuron Models Equations -- Rate-based neurons
** [[DivInE-model for MT neurons]]

* Neuron Models Equations -- Spiking neurons without explicit spike generation mechanism
** [[Leaky Integrate-and-Fire]]
** [[Exponential Integrate-and-Fire]]
** [[Quadratic Integrate-and-Fire]]
** [[Connor Stevens]]

* [[References]]
* Task 1 -- Pictures for comparision
** [[Task 1 --Mandatory Tasks]]

* Task 2 -- Pictures for comparision
** [[Task 2 -- Mandatory Tasks]]
** [[Task 2 -- Voluntary Tasks: Preprocessing]]
** [[Task 2 -- Voluntary Tasks: More Information!]]
=== Advanced Studies ===
* Material from ages past
** [[2022: Preparation -- Python class with and without classes]]
** [[2022: Deep Networks and Pytorch]]
** [[2022: Divisive inhibition: a dynamical circuit for change detection]]
** [[2022: Synchronization and dynamic oscillations in the visual system]]
** [[2020: Deep Networks and Tensor Flow]]
** [[2020: Divisive Normalization -- a Universal Concept for Adaptive Dynamics and Function of Cortical Circuits]]
** [[2020: Recurrent networks: Temporal dynamics and synchronization]]
** [[2017: Oscillations and information routing: CTC model]]
** [[2017: Change detection: The DivInE-Model]]
** [[2017: Contour Integration]]
** [[2017: Computation Spike by Spike]]
** [[2017: Natural scenes and sparse coding in visual cortex]]