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Last modified by makuadm on 2026-01-07 06:21
From version 29.1
edited by cpassow
on 2022-04-06 16:47
Change comment: There is no comment for this version
To version 2.1
edited by cpassow
on 2022-04-04 08:06
Change comment: There is no comment for this version

Summary

Details

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Title
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1 -DEMO - Working with FLASH data
1 +DEMO - Documentation
Content
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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.
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2 +* Short descriptions including Links:
3 +(% style="list-style-type: square;" %)
4 +** GPFS
5 +** JupyterHub
6 +** conda ?
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]
8 +(% style="list-style-type: square;" %)
9 +* Links Repository
10 +(% style="list-style-type: square;" %)
11 +** including Method Description
4 4  
5 5  \\
6 6  
7 -{{expand title="TEST - How to login JupyterHub"}}
15 +(% style="list-style-type: square;" %)
16 +* Links to Binder
8 8  
9 -
10 -{{view-file att--filename="tmp.mp4" height="250"/}}
11 -{{/expand}}
12 -
13 13  \\
14 14  
15 15  \\
16 16  
17 -----
22 +Questions:
18 18  
19 -=== TODO ===
20 -
21 -(% class="task-list" %)
22 -(((
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
32 -{{/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}}
57 -)))
58 -{{/task}}
59 -)))
60 -
61 -\\
62 -
63 -(% class="task-list" %)
64 -(((
65 -{{task reference="/Tasks/Task_22" status="InProgress"}}
66 -distribution
67 -
68 -(% class="task-list" %)
69 -(((
70 -
71 -
72 -{{task reference="/Tasks/Task_23" status="InProgress"}}
73 -channel  (where to host?)
74 -{{/task}}
75 -
76 -{{task reference="/Tasks/Task_24" status="InProgress"}}
77 -environment file (repository with examples)
78 -{{/task}}
79 -)))
80 -{{/task}}
81 -)))
82 -
83 -\\
84 -
85 -(% class="task-list" %)
86 -(((
87 -{{task reference="/Tasks/Task_25" status="InProgress"}}
88 -Documentation
89 -
90 -(% class="task-list" %)
91 -(((
92 -
93 -
94 -{{task reference="/Tasks/Task_26" status="InProgress"}}
95 -here VS repository VS sphinx
96 -{{/task}}
97 -)))
98 -{{/task}}
99 -)))
100 -
101 -\\
102 -
103 -(% class="task-list" %)
104 -(((
105 -{{task reference="/Tasks/Task_27" status="InProgress"}}
106 -Binder
107 -
108 -(% class="task-list" %)
109 -(((
110 -
111 -
112 -{{task reference="/Tasks/Task_28" status="InProgress"}}
113 -examples with Stefan
114 -{{/task}}
115 -)))
116 -{{/task}}
117 -)))
118 -
119 -\\
120 -
121 -(% class="task-list" %)
122 -(((
123 -{{task reference="/Tasks/Task_29" status="InProgress"}}
124 -Screencast
125 -
126 -(% class="task-list" %)
127 -(((
128 -
129 -
130 -{{task reference="/Tasks/Task_30" status="InProgress"}}
131 -login in jupyter hub
132 -{{/task}}
133 -
134 -{{task reference="/Tasks/Task_31" status="InProgress"}}
135 -login maxwell display
136 -{{/task}}
137 -
138 -{{task reference="/Tasks/Task_32" status="InProgress"}}
139 -use slix
140 -{{/task}}
141 -
142 -{{task reference="/Tasks/Task_33" status="InProgress"}}
143 -use hdfview plugin in jupterLab
144 -{{/task}}
145 -
146 -{{task reference="/Tasks/Task_34" status="InProgress"}}
147 -create conda env with flashh5
148 -{{/task}}
149 -)))
150 -{{/task}}
151 -)))
152 -
153 -\\
154 -
155 -\\
156 -
157 -----
158 -
159 -==== under review ====
160 -
161 -\\
162 -
163 -{{code language="bash"}}
164 -conda create -n flashh5 python=3.10 # 3.10 not necessary, but would prefer 3.8 or higher
165 -source activate flashh5
166 -conda install ipython numpy pandas #TODO: fix dependcies
167 -conda install -c https://www.desy.de/~cpassow/condarepo/ flashh5
168 -
169 -## on jhub
170 -conda install ipykernel
171 -python -m ipykernel install --user --name flashh5 --display-name "flashh5"
172 -
173 -
174 -## to remove on jhub
175 -## delete from: /home/$USER/.local/share/jupyter/kernels/
176 -{{/code}}
177 -
178 -\\
179 -
180 -{{code language="py" title="moved to repository?"}}
181 -class RunDirectory:
182 -
183 - def get_run_table(): # more or less information? RunComment | Number of Files | start & stop time ?
184 - ...
185 -
186 - def get_run(daq, run_number): # daq is not needed!
187 -
188 - ...
189 -
190 -
191 -class Run: # constructor optional without RunDirectory or use there self.path
192 -
193 - def get_files():
194 - ...
195 -
196 - def get_channels(): # of file #1
197 - ...
198 -
199 - def get_start_time(): # better as attribute?
200 - ...
201 -
202 - def get_stop_time(): # which? | better as attribute?
203 - ...
204 -
205 - def to_df(daq_map): # to_df(daq_map, slice) slice=[0:4] -> throw Exception
206 - ...
207 -
208 - def to_series(channel):
209 - ...
210 -
211 - def to_array(channel):
212 - ...
213 -{{/code}}
214 -
215 -{{code language="py" title="ideas"}}
216 -run.to_df(daq_map)
217 -run.to_series(daq_adr or daq_map) # on channel only?
218 -run.to_array(daq_adr) # on channel only?
219 -
220 -## interesting?
221 -# run.to_dask(daq_map)
222 -# run.to_xarray(daq_map)
223 -{{/code}}
224 -
225 -\\
24 +(% style="list-style-type: square;" %)
25 +* for whom
26 +* where Maxwell / local / extern
27 +* distribution