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Last modified by makuadm on 2026-01-07 06:21
From version 36.1
edited by sndueste
on 2023-09-29 11:07
Change comment: There is no comment for this version
To version 42.2
edited by rangeadm
on 2025-02-13 08:01
Change comment: Update document after refactoring.

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1 +FS-FLASH USER tmp.Data Acquisition and controls.DAQ and controls overview.Offline data analysis (DAQ).WebHome
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1 -XWiki.sndueste
1 +XWiki.rangeadm
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1 -Experimental data is recorded as HDF files[link] on the GPFS file system[link]. The access rights[link to ACLs] are linked to the user's DESY account and can be managed by the PI via the GAMMA portal[link]. The experimental data can be downloaded via the GAMMA portal, but it is advised to use the DESY computing infrastructure. Access point are via ssh[link], Maxwell-Display Server[link] or JuyterHub[link]. We recommmend using the JupyterHub for data exploration and the SLURM resources[link] for high performances computing.
1 +Experimental data is recorded as HDF files[[~[link~]>>doc:FLASHUSER.Data Acquisition and controls.DAQ and controls overview.Offline data analysis (DAQ).The FLASH HDF5 structure.WebHome]] on the GPFS file system[[~[link~]>>https://docs.desy.de/asap3/]]. The access rights are linked to the user's DESY account and can be managed by the PI via the GAMMA portal[[~[link~]>>url:https://gamma-portal.desy.de/||shape="rect"]]. The experimental data can be downloaded via the GAMMA portal, but it is advised to use the DESY computing infrastructure. Access point are via ssh, Maxwell-Display Server[[~[link~]>>url:https://confluence.desy.de/display/MXW/Maxwell+Cluster||shape="rect"]] or JuyterHub[[~[link~]>>url:https://confluence.desy.de/display/MXW/JupyterHub+on+Maxwell||shape="rect"]]. We recommend using the JupyterHub for data exploration and the SLURM resources for high performances computing - see FAB for easy usage of the infrastructure.
2 2  
3 -For simplified acccess we provide a conda module flashh5[link] which can be installed in a personal conda environment[link] on the Maxwell Cluster. Example on the usage can be found here [link - repo + binder]
3 +{{info title="How to login JupyterHub"}}
4 +=== ===
4 4  
5 -\\
6 +{{view-file att--filename="tmp.mp4" height="150"/}}
7 +{{/info}}
6 6  
7 -{{expand title="How to login JupyterHub"}}
8 -
9 -
10 -{{view-file att--filename="tmp.mp4" height="250"/}}
11 -{{/expand}}
12 -
13 -\\
14 -
15 -\\
16 -
17 17  {{info}}
18 -=== There are different options that help you to work with the FLASH HDF5 data in Python ===
10 +=== There are different options that help you to work with the FLASH HDF5 data in Python ===
19 19  
20 -The currently developed option for large data sets: [[the FAB package>>url:https://hasfcpkg.desy.de/fab/fab.html||shape="rect"]] ... see below
12 +* The currently developed option for large data sets: [[the FAB package>>url:https://hasfcpkg.desy.de/fab/fab.html||shape="rect"]] ... see below
13 +* and for smaller projects:  (% class="Object" %)[[https:~~/~~/gitlab.desy.de/christopher.passow/flash-daq-hdf>>url:https://gitlab.desy.de/christopher.passow/flash-daq-hdf||shape="rect"]]
21 21  
22 -and for smaller projects:  (% class="Object" %)[[https:~~/~~/gitlab.desy.de/christopher.passow/flash-daq-hdf>>url:https://gitlab.desy.de/christopher.passow/flash-daq-hdf||shape="rect"]]
15 +(% class="Object" %)See also the collection of Demo data and sample scripts : [[doc:FLASHUSER.Data Acquisition and controls.DAQ and controls overview.Offline data analysis (DAQ).Collection of HDF5 sample data from different beamlines.WebHome]]
23 23  {{/info}}
24 24  
25 -\\
26 26  
27 27  [[~[~[image:attach:image2023-9-29_11-1-37.png~]~]>>url:https://hasfcpkg.desy.de/fab/fab.html||shape="rect"]]
28 28  
29 -\\
30 -
31 31  {{expand title="older ideas ..."}}
32 32  (% class="Object" %)(object oriented) [[https:~~/~~/gitlab.desy.de/christopher.passow/fdh-builder>>url:https://gitlab.desy.de/christopher.passow/fdh-builder.git||shape="rect"]]
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38 38  (% class="task-list" %)
39 39  (((
40 40  {{task reference="/Tasks/Task_18" status="InProgress"}}
41 -Short descriptions including Links:   → as Text\\
31 +Short descriptions including Links:   → as Text
42 42  
43 43  (% class="task-list" %)
44 44  (((
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75 75  {{/task}}
76 76  )))
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80 80  (% class="task-list" %)
81 81  (((
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97 97  {{/task}}
98 98  )))
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102 102  (% class="task-list" %)
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115 115  {{/task}}
116 116  )))
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133 133  {{/task}}
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138 138  (% class="task-list" %)
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167 167  {{/task}}
168 168  )))
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170 -\\
171 171  
172 -\\
173 173  
174 174  ----
175 175  
176 176  ==== under review ====
177 177  
178 -\\
179 179  
180 180  {{code language="bash"}}
181 181  conda create -n flashh5 python=3.10 # 3.10 not necessary, but would prefer 3.8 or higher
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192 192  ## delete from: /home/$USER/.local/share/jupyter/kernels/
193 193  {{/code}}
194 194  
195 -\\
196 -
197 -{{code language="py" title="moved to repository?"}}
178 +{{code language="py" title="
179 +moved to repository?"}}
198 198  class RunDirectory:
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200 200   def get_run_table(): # more or less information? RunComment | Number of Files | start & stop time ?
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239 239  # run.to_xarray(daq_map)
240 240  {{/code}}
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225 +
245 245  {{/expand}}
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