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Last modified by makuadm on 2026-01-07 06:21
From version 43.1
edited by makuadm
on 2026-01-06 20:39
Change comment: Task [xwiki:FLASHUSER.Offline data analysis (DAQ).DEMO - Working with FLASH data.Tasks.Task_18.WebHome] has been updated!
To version 36.1
edited by sndueste
on 2023-09-29 11:07
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1 -FLASHUSER.Offline data analysis (DAQ).WebHome
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1 -XWiki.makuadm
1 +XWiki.sndueste
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1 -Experimental data is recorded as HDF files[[~[link~]>>doc:FS-FLASH USER tmp.Data Acquisition and controls 1.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.
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.
2 2  
3 -{{info title="How to login JupyterHub"}}
4 -=== ===
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]
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6 -{{view-file att--filename="tmp.mp4" height="150"/}}
7 -{{/info}}
5 +\\
8 8  
7 +{{expand title="How to login JupyterHub"}}
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9 +
10 +{{view-file att--filename="tmp.mp4" height="250"/}}
11 +{{/expand}}
12 +
13 +\\
14 +
15 +\\
16 +
9 9  {{info}}
10 -=== There are different options that help you to work with the FLASH HDF5 data in Python ===
18 +=== There are different options that help you to work with the FLASH HDF5 data in Python ===
11 11  
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"]]
20 +The currently developed option for large data sets: [[the FAB package>>url:https://hasfcpkg.desy.de/fab/fab.html||shape="rect"]] ... see below
14 14  
15 -(% class="Object" %)See also the collection of Demo data and sample scripts : [[doc:FS-FLASH USER tmp.Data Acquisition and controls 1.DAQ and controls overview.Offline data analysis (DAQ).Collection of HDF5 sample data from different beamlines.WebHome]]
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"]]
16 16  {{/info}}
17 17  
25 +\\
18 18  
19 19  [[~[~[image:attach:image2023-9-29_11-1-37.png~]~]>>url:https://hasfcpkg.desy.de/fab/fab.html||shape="rect"]]
20 20  
29 +\\
30 +
21 21  {{expand title="older ideas ..."}}
22 22  (% 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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27 27  
28 28  (% class="task-list" %)
29 29  (((
30 -{{task reference="/Tasks/Task_18" status="InProgress" completeDate="" createDate="2026-01-06" reporter=""}}
31 -Short descriptions including Links:   → as Text
32 -\\
40 +{{task reference="/Tasks/Task_18" status="InProgress"}}
41 +Short descriptions including Links:   → as Text\\
42 +
43 +(% class="task-list" %)
44 +(((
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46 +
47 +{{task reference="/Tasks/Task_19" status="InProgress"}}
48 +GPFS
33 33  {{/task}}
50 +
51 +{{task reference="/Tasks/Task_40" status="InProgress"}}
52 +Access rights
53 +{{/task}}
54 +
55 +{{task reference="/Tasks/Task_41" status="InProgress"}}
56 +Gamma Portal
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59 +{{task reference="/Tasks/Task_42" status="InProgress"}}
60 +Maxwell
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63 +{{task reference="/Tasks/Task_20" status="InProgress"}}
64 +JupyterHub
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66 +
67 +{{task reference="/Tasks/Task_21" status="InProgress"}}
68 +conda ?
69 +{{/task}}
70 +
71 +{{task reference="/Tasks/Task_36" status="InProgress"}}
72 +explain install from channel instead of fixed environment, but can use environment file from example repository
73 +{{/task}}
34 34  )))
75 +{{/task}}
76 +)))
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36 36  
37 37  (% class="task-list" %)
38 38  (((
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54 54  {{/task}}
55 55  )))
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58 58  (% class="task-list" %)
59 59  (((
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71 71  {{/task}}
72 72  )))
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75 75  (% class="task-list" %)
76 76  (((
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88 88  {{/task}}
89 89  )))
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121 121  {{/task}}
122 122  )))
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125 125  
126 126  ----
127 127  
128 128  ==== under review ====
129 129  
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130 130  
131 131  {{code language="bash"}}
132 132  conda create -n flashh5 python=3.10 # 3.10 not necessary, but would prefer 3.8 or higher
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143 143  ## delete from: /home/$USER/.local/share/jupyter/kernels/
144 144  {{/code}}
145 145  
146 -{{code language="py" title="
147 -moved to repository?"}}
195 +\\
196 +
197 +{{code language="py" title="moved to repository?"}}
148 148  class RunDirectory:
149 149  
150 150   def get_run_table(): # more or less information? RunComment | Number of Files | start & stop time ?
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189 189  # run.to_xarray(daq_map)
190 190  {{/code}}
191 191  
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194 194  {{/expand}}
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