Last modified by robing on 2022/03/25 09:55
From version 50.1
edited by debonisg
on 2020/04/24 12:58
Change comment: There is no comment for this version
To version 52.1
edited by robing
on 2020/04/24 16:47
Change comment: There is no comment for this version

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1 -XWiki.debonisg
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42 42  This Collab is aimed at experimental and computational neuroscientists interested in the usage of the [[Neo>>https://neo.readthedocs.io/en/stable/]] and [[Elephant>>https://elephant.readthedocs.io/en/latest/]] tools in performing data analysis of spiking data.
43 43  Here, the collab illustrates the tool usage with regards to KR3.2, investigating sleep, anesthesia, and the transition to wakefulness.
44 44  
45 +[[image:https://github.githubassets.com/images/modules/logos_page/GitHub-Mark.png||height="35" width="35"]][[INM-6/wavescalephant>>https://github.com/INM-6/wavescalephant]]
46 +
45 45  == How the Pipeline works ==
46 46  
47 47  The design of the pipeline aims at interfacing a variety of general and specific analysis and processing steps in a flexible modular manner. Hence, it enables the pipeline to adapt to diverse types of data (e.g., electrical ECoG, or optical Calcium Imaging recordings) and to different analysis questions. This makes the analyses a) more reproducible and b) comparable amongst each other since they rely on the same stack of algorithms and any differences in the analysis are fully transparent.
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87 87  
88 88  * (((
89 89  **Build the Python environment**
90 -In the wavescalephant git repository, there is an environment file ([[pipeline/envs/wavescalephant_env.yaml>>https://drive.ebrains.eu/f/efe2ecf0874d4402bb11/]]) 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]]).
92 +In the wavescalephant git repository, there is an environment file ([[pipeline/envs/wavescalephant_env.yml>>https://drive.ebrains.eu/lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/envs/wavescalephant_env.yml]]) 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]]).
91 91  ##conda env create ~-~-file /envs/wavescalephant_env.yml##
92 92  
93 93  )))
94 94  * **Edit the settings**
95 -The settings file specifies the path to the output folder, where results are saved to. Open the template file //[[pipeline/settings_template.py>>https://drive.ebrains.eu/f/b6dbd9f15e4f4d97af17/]]//, set the ##output_path## to the desired path, and save it as //pipeline/settings.py//.
97 +The settings file specifies the path to the output folder, where results are saved to. Open the template file //[[pipeline/settings_template.py>>https://drive.ebrains.eu/lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/settings_template.py]]//, set the ##output_path## to the desired path, and save it as //pipeline/settings.py//.
96 96  
97 97  * **Edit the config files**
98 98  Each stage has a config file to specify which analysis/processing blocks to execute and which parameters to use. Edit the config template files //pipeline/stageXX_<stage_name>/config_template.yaml// according to your dataset and analysis goal, and save them as //pipeline/stageXX_<stage_name>/config.yaml//. A detailed description of the available parameter settings and their meaning is commented in the template files, and a more general description of the working mechanism of each stage can be found in the respective README file //pipeline/stageXX_<stage_name>/README.md//.
99 99  //Links are view-only//
100 -** full pipeline:[[ README.md>>https://drive.ebrains.eu/f/ec474df6919a4089832e/]], config.yaml
101 -** stage01_data_entry: [[README.md>>https://drive.ebrains.eu/f/b46ffe259b3a4a51a277/]], [[config.yaml>>https://drive.ebrains.eu/f/8de751f48d7d47edaec1/]]
102 -** stage02_processing: [[README.md>>https://drive.ebrains.eu/f/7f19d89913624425bf63/]], [[config.yaml>>https://drive.ebrains.eu/f/b1607671f6f2468aa43c/]]
103 -** stage03_trigger_detection: [[README.md>>https://drive.ebrains.eu/f/94d12860dde84bbab7b1/]], [[config.yaml>>https://drive.ebrains.eu/f/6dfb712d5fa24f4f9fcf/]]
104 -** stage04_wavefront_detection: [[README.md>>https://drive.ebrains.eu/d/9c53abd5eaf543b28615/]], [[config.yaml>>https://drive.ebrains.eu/f/9534e46c4fae41c78f17/]]
105 -** stage05_wave_characterization: [[README.md>>https://drive.ebrains.eu/f/4d79f3e314474c22a781/]], [[config.yaml>>https://drive.ebrains.eu/f/1689dda03be04251b85f/]]
102 +** full pipeline: [[README.md>>https://drive.ebrains.eu/smart-link/d2e93a2a-09f6-4dce-982d-0370953a4da8/]], [[config.yaml>>https://drive.ebrains.eu/smart-link/7948fbb3-bf8a-4785-9b28-d5c15a1aafa7/]]
103 +** stage01_data_entry: [[README.md>>https://drive.ebrains.eu/smart-link/896f8880-a7d1-4a30-adbf-98759860fed5/]], [[config.yaml>>https://drive.ebrains.eu/smart-link/d429639d-b76e-4093-8fad-a25463d41edc/]]
104 +** stage02_processing: [[README.md>>https://drive.ebrains.eu/smart-link/01f21fa5-94f7-4883-8388-cc50957f9c81/]], [[config.yaml>>https://drive.ebrains.eu/f/b1607671f6f2468ahttps://drive.ebrains.eu/smart-link/02a3f92c-dc7d-4b33-94f5-91b00db060d5/a43c/]]
105 +** stage03_trigger_detection: [[README.md>>https://drive.ebrains.eu/smart-link/18d276cd-a691-4ee1-81c6-7978cef9c1b4/]], [[config.yaml>>https://drive.ebrains.eu/smart-link/76adbb12-7cb4-42df-9fd5-735927ea3ba8/]]
106 +** stage04_wavefront_detection: [[README.md>>https://drive.ebrains.eu/smart-link/a8e80096-06a0-4ff4-b645-90e134e46ac5/]], [[config.yaml>>https://drive.ebrains.eu/smart-link/6b0b233f-30b7-4bbd-8564-1abebd27ea6d/]]
107 +** stage05_wave_characterization: [[README.md>>https://drive.ebrains.eu/smart-link/3009a214-a11f-424c-8a6e-13e7506545eb/]], [[config.yaml>>https://drive.ebrains.eu/smart-link/471001d5-33f5-488e-a9a4-f03b190e3da7/]]
106 106  
107 107  * **Enter a dataset**
108 108  There are two test datasets in the collab drive (IDIBAPS and LENS) for which there are also corresponding config files and scripts in the data_entry stage. So, these datasets are ready to be used and analyzed.
109 -For adding new datasets see //[[pipeline/stage01_data_entry/README.md>>https://drive.ebrains.eu/f/b46ffe259b3a4a51a277/]]//
111 +For adding new datasets see //[[pipeline/stage01_data_entry/README.md>>https://drive.ebrains.eu/smart-link/d2e93a2a-09f6-4dce-982d-0370953a4da8/]]//
110 110  
111 111  * **Run the pipeline (-stages)**
112 112  To run the pipeline with snakemake ([intro to snakemake]()) activate the Python environment ##conda activate wavescalephant_env,## make sure you are in the working directory `pipeline/`, and call ##snakemake## to run the entire pipeline.