Attention: Due to an upgrade beginning on Friday, the 22nd August 2025, any new collabs, groups and any changes to teams will not be kept beyond the weekend. User creation will also be disabled during this time. The actual upgrade will take place on Wednesday, 27th August. On that day, any service requiring a Keycloak login will be unavailable for the duration of the upgrade. Thank you for your understanding as we complete this important work.


Last modified by robing on 2022/03/25 09:55
From version 79.1
edited by robing
on 2020/05/25 22:10
Change comment: There is no comment for this version
To version 73.1
edited by denker
on 2020/05/08 15:19
Change comment: There is no comment for this version

Summary

Details

Page properties
Author
... ... @@ -1,1 +1,1 @@
1 -XWiki.robing
1 +XWiki.denker
Content
... ... @@ -78,8 +78,6 @@
78 78  
79 79  === ii) Local execution ===
80 80  
81 -//tested only with Linux!//
82 -
83 83  * **Get the code**
84 84  The source code of the pipeline is available via Github: [[INM-6/wavescalephant>>https://github.com/INM-6/wavescalephant]] and can be cloned to your machine ([[how to get started with Github>>https://guides.github.com/activities/hello-world/]]).
85 85  
... ... @@ -88,10 +88,6 @@
88 88  In the wavescalephant git repository, there is an environment file ([[pipeline/environment.yaml>>https://drive.ebrains.eu/smart-link/1a0b15bb-be87-46ee-b838-4734bc320d20/]]) specifying the required packages and versions. To build the environment, we recommend using conda ([[how to get started with conda>>https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html]]).
89 89  ##conda env create ~-~-file environment.yaml
90 90  conda activate wavescalephant_env##
91 -
92 -Make sure that neo and elephant were installed as their Github development version, and if necessary add them manually to the environment.
93 -##pip install git+https:~/~/github.com/NeuralEnsemble/elephant.git
94 -pip install git+https:~/~/github.com/NeuralEnsemble/python-neo.git##
95 95  
96 96  )))
97 97  * **Edit the settings**
... ... @@ -119,20 +119,8 @@
119 119  
120 120  All results are stored in the path specified in the //settings.py// file. The folder structure reflects the structuring of the pipeline into stages and blocks. All intermediate results are stored as //.nix// files using the [[Neo data format>>https://neo.readthedocs.io/en/stable/]] and can be loaded with ##neo.NixIO('/path/to/file.nix').read_block()##. Additionally, most blocks produce a figure, and each stage a report file, to give an overview of the execution log, parameters, intermediate results, and to help with debugging. The final stage (//stage05_wave_characterization//) stores the results as[[ //pandas.DataFrames//>>https://pandas.pydata.org/]] in //.csv// files, separately for each measure as well as in a combined dataframe for all measures.
121 121  
122 -**Examples of the output figures (for IDIBAPS dataset)**
116 +== Outlook ==
123 123  
124 -* Stage 01 - [[example signal traces and metadata>>https://drive.ebrains.eu/smart-link/cf2fa914-260d-4d61-a2da-03ea07b7f9be/]]
125 -* Stage 02 - [[background substraction>>https://drive.ebrains.eu/smart-link/586d2f3c-591b-4dfb-94ee-8c0e28050dc4/]]
126 -* Stage 02 - [[logMUA estimation>>https://drive.ebrains.eu/smart-link/c92e4b0c-0938-44e8-9f8d-00522796b2fd/]]
127 -* Stage 02 - [[processed signal trace>>https://drive.ebrains.eu/smart-link/26ed27c6-de56-4b48-a57b-f70aab629197/]]
128 -* Stage 03 - [[amplitude distribution>>https://drive.ebrains.eu/smart-link/8ba80293-ba75-4a37-8a8f-05d44cf6f65c/]]
129 -* Stage 03 - [[UP state detection>>https://drive.ebrains.eu/smart-link/ab172be0-178e-4153-a3e6-b4bace32dd50/]]
130 -* Stage 04 - [[trigger clustering>>https://drive.ebrains.eu/smart-link/4a1f0169-8b43-49ce-80c8-f2fa0f4d50d3/]]
131 -* Stage 05 - [[planar velocities>>https://drive.ebrains.eu/smart-link/f4de8073-cb40-47a7-bc82-f97d36dbae25/]]
132 -* Stage 05 - [[directionality>>https://drive.ebrains.eu/smart-link/5485032d-0121-4cde-9ea2-3e0af3f12178/]]
133 -
134 -=== Outlook ===
135 -
136 136  * Using the **KnowledgeGraph API **to insert data directly from the Knowledge Graph into the pipeline and also register and store the corresponding results as Analysis Objects. Such Analysis Objects are to incorporate **Provenance Tracking, **using [[fairgraph>>https://github.com/HumanBrainProject/fairgraph]],** **to record the details of the processing and analysis steps.
137 137  * Adding support for the pipeline to make use of **HPC** resources when running on the collab.
138 138  * Further extending the available **methods** to address a wider variety of analysis objectives and support the processing of other datatypes. Additional documentation and guides should also make it easier for non-developers to contribute new method blocks.
Collaboratory.Apps.Collab.Code.CollabClass[0]
Public
... ... @@ -1,1 +1,1 @@
1 -Yes
1 +No
XWiki.XWikiRights[3]
Allow/Deny
... ... @@ -1,1 +1,0 @@
1 -Allow
Levels
... ... @@ -1,1 +1,0 @@
1 -view
Users
... ... @@ -1,1 +1,0 @@
1 -XWiki.XWikiGuest
XWiki.XWikiRights[4]
Allow/Deny
... ... @@ -1,1 +1,0 @@
1 -Allow
Groups
... ... @@ -1,1 +1,0 @@
1 -XWiki.XWikiAllGroup
Levels
... ... @@ -1,1 +1,0 @@
1 -view