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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 32.1
edited by sndueste
on 2022-10-27 11:19
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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]
5 5  
6 -{{view-file att--filename="tmp.mp4" height="150"/}}
7 -{{/info}}
5 +\\
8 8  
9 -{{info}}
10 -=== There are different options that help you to work with the FLASH HDF5 data in Python ===
7 +{{expand title="TEST - How to login JupyterHub"}}
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"]]
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]]
16 -{{/info}}
10 +{{view-file att--filename="tmp.mp4" height="250"/}}
11 +{{/expand}}
17 17  
13 +\\
18 18  
19 -[[~[~[image:attach:image2023-9-29_11-1-37.png~]~]>>url:https://hasfcpkg.desy.de/fab/fab.html||shape="rect"]]
15 +\\
20 20  
21 -{{expand title="older ideas ..."}}
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"]]
23 -
24 24  ----
25 25  
26 26  === TODO ===
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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 -\\
23 +{{task reference="/Tasks/Task_18" status="InProgress"}}
24 +Short descriptions including Links:   → as Text\\
25 +
26 +(% class="task-list" %)
27 +(((
28 +
29 +
30 +{{task reference="/Tasks/Task_19" status="InProgress"}}
31 +GPFS
33 33  {{/task}}
33 +
34 +{{task reference="/Tasks/Task_40" status="InProgress"}}
35 +Access rights
36 +{{/task}}
37 +
38 +{{task reference="/Tasks/Task_41" status="InProgress"}}
39 +Gamma Portal
40 +{{/task}}
41 +
42 +{{task reference="/Tasks/Task_42" status="InProgress"}}
43 +Maxwell
44 +{{/task}}
45 +
46 +{{task reference="/Tasks/Task_20" status="InProgress"}}
47 +JupyterHub
48 +{{/task}}
49 +
50 +{{task reference="/Tasks/Task_21" status="InProgress"}}
51 +conda ?
52 +{{/task}}
53 +
54 +{{task reference="/Tasks/Task_36" status="InProgress"}}
55 +explain install from channel instead of fixed environment, but can use environment file from example repository
56 +{{/task}}
34 34  )))
58 +{{/task}}
59 +)))
35 35  
61 +\\
36 36  
37 37  (% class="task-list" %)
38 38  (((
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54 54  {{/task}}
55 55  )))
56 56  
83 +\\
57 57  
58 58  (% class="task-list" %)
59 59  (((
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71 71  {{/task}}
72 72  )))
73 73  
101 +\\
74 74  
75 75  (% class="task-list" %)
76 76  (((
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88 88  {{/task}}
89 89  )))
90 90  
119 +\\
91 91  
92 92  (% class="task-list" %)
93 93  (((
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121 121  {{/task}}
122 122  )))
123 123  
153 +\\
124 124  
155 +\\
125 125  
126 126  ----
127 127  
128 128  ==== under review ====
129 129  
161 +\\
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?"}}
178 +\\
179 +
180 +{{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  
225 +\\
192 192  
193 -
194 -{{/expand}}
227 +\\
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