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Last modified by makuadm on 2026-01-07 06:21
From version 38.1
edited by sndueste
on 2023-09-29 11:15
Change comment: There is no comment for this version
To version 6.1
edited by cpassow
on 2022-04-04 08:58
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
Author
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1 -XWiki.sndueste
1 +XWiki.cpassow
Content
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1 -Experimental data is recorded as HDF files[[~[link~]>>doc:FLASHUSER.Data Acquisition and controls.Data Access at FLASH (DAQ, gpfs,\.\.\.).Offline data analysis (DAQ).The FLASH HDF5 structure.WebHome]] on the GPFS file system[[~[link~]>>doc:ASAP3.ASAP3 Data Storage for PETRA III]]. 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 +(% style="list-style-type: square;" %)
2 +* Short descriptions including Links:
3 +(% style="list-style-type: square;" %)
4 +** GPFS
5 +** JupyterHub
6 +** conda ?
2 2  
3 -{{info title="How to login JupyterHub"}}
4 -=== ===
8 +(% style="list-style-type: square;" %)
9 +* Links Repository
10 +(% style="list-style-type: square;" %)
11 +** including Method Description
5 5  
6 -{{view-file att--filename="tmp.mp4" height="150"/}}
7 -{{/info}}
8 -
9 9  \\
10 10  
11 -{{info}}
12 -=== There are different options that help you to work with the FLASH HDF5 data in Python ===
15 +(% style="list-style-type: square;" %)
16 +* Links to Binder
13 13  
14 -The currently developed option for large data sets: [[the FAB package>>url:https://hasfcpkg.desy.de/fab/fab.html||shape="rect"]] ... see below
15 -
16 -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"]]
17 -{{/info}}
18 -
19 19  \\
20 20  
21 -[[~[~[image:attach:image2023-9-29_11-1-37.png~]~]>>url:https://hasfcpkg.desy.de/fab/fab.html||shape="rect"]]
22 -
23 23  \\
24 24  
25 -{{expand title="older ideas ..."}}
26 -(% class="Object" %)(object oriented) [[https:~~/~~/gitlab.desy.de/christopher.passow/fdh-builder>>url:https://gitlab.desy.de/christopher.passow/fdh-builder.git||shape="rect"]]
22 +Questions:
27 27  
28 -----
24 +(% style="list-style-type: square;" %)
25 +* for whom
26 +* where Maxwell / local / extern
27 +* distribution\\
28 +(% style="list-style-type: square;" %)
29 +** channel?
30 +(% style="list-style-type: square;" %)
31 +*** where official hosted (DESY, privat, conda-forge)
32 +** enviroment?
33 +(% style="list-style-type: square;" %)
34 +*** via files / already created?
29 29  
30 -=== TODO ===
31 -
32 -(% class="task-list" %)
33 -(((
34 -{{task reference="/Tasks/Task_18" status="InProgress"}}
35 -Short descriptions including Links:   → as Text\\
36 -
37 -(% class="task-list" %)
38 -(((
39 -
40 -
41 -{{task reference="/Tasks/Task_19" status="InProgress"}}
42 -GPFS
43 -{{/task}}
44 -
45 -{{task reference="/Tasks/Task_40" status="InProgress"}}
46 -Access rights
47 -{{/task}}
48 -
49 -{{task reference="/Tasks/Task_41" status="InProgress"}}
50 -Gamma Portal
51 -{{/task}}
52 -
53 -{{task reference="/Tasks/Task_42" status="InProgress"}}
54 -Maxwell
55 -{{/task}}
56 -
57 -{{task reference="/Tasks/Task_20" status="InProgress"}}
58 -JupyterHub
59 -{{/task}}
60 -
61 -{{task reference="/Tasks/Task_21" status="InProgress"}}
62 -conda ?
63 -{{/task}}
64 -
65 -{{task reference="/Tasks/Task_36" status="InProgress"}}
66 -explain install from channel instead of fixed environment, but can use environment file from example repository
67 -{{/task}}
68 -)))
69 -{{/task}}
70 -)))
71 -
72 72  \\
73 73  
74 -(% class="task-list" %)
75 -(((
76 -{{task reference="/Tasks/Task_22" status="InProgress"}}
77 -distribution
78 -
79 -(% class="task-list" %)
80 -(((
81 -
82 -
83 -{{task reference="/Tasks/Task_23" status="InProgress"}}
84 -channel  (where to host?)
85 -{{/task}}
86 -
87 -{{task reference="/Tasks/Task_24" status="InProgress"}}
88 -environment file (repository with examples)
89 -{{/task}}
90 -)))
91 -{{/task}}
92 -)))
93 -
94 -\\
95 -
96 -(% class="task-list" %)
97 -(((
98 -{{task reference="/Tasks/Task_25" status="InProgress"}}
99 -Documentation
100 -
101 -(% class="task-list" %)
102 -(((
103 -
104 -
105 -{{task reference="/Tasks/Task_26" status="InProgress"}}
106 -here VS repository VS sphinx
107 -{{/task}}
108 -)))
109 -{{/task}}
110 -)))
111 -
112 -\\
113 -
114 -(% class="task-list" %)
115 -(((
116 -{{task reference="/Tasks/Task_27" status="InProgress"}}
117 -Binder
118 -
119 -(% class="task-list" %)
120 -(((
121 -
122 -
123 -{{task reference="/Tasks/Task_28" status="InProgress"}}
124 -examples with Stefan
125 -{{/task}}
126 -)))
127 -{{/task}}
128 -)))
129 -
130 -\\
131 -
132 -(% class="task-list" %)
133 -(((
134 -{{task reference="/Tasks/Task_29" status="InProgress"}}
135 -Screencast
136 -
137 -(% class="task-list" %)
138 -(((
139 -
140 -
141 -{{task reference="/Tasks/Task_30" status="InProgress"}}
142 -login in jupyter hub
143 -{{/task}}
144 -
145 -{{task reference="/Tasks/Task_31" status="InProgress"}}
146 -login maxwell display
147 -{{/task}}
148 -
149 -{{task reference="/Tasks/Task_32" status="InProgress"}}
150 -use slix
151 -{{/task}}
152 -
153 -{{task reference="/Tasks/Task_33" status="InProgress"}}
154 -use hdfview plugin in jupterLab
155 -{{/task}}
156 -
157 -{{task reference="/Tasks/Task_34" status="InProgress"}}
158 -create conda env with flashh5
159 -{{/task}}
160 -)))
161 -{{/task}}
162 -)))
163 -
164 -\\
165 -
166 -\\
167 -
168 -----
169 -
170 -==== under review ====
171 -
172 -\\
173 -
174 -{{code language="bash"}}
175 -conda create -n flashh5 python=3.10 # 3.10 not necessary, but would prefer 3.8 or higher
176 -source activate flashh5
177 -conda install ipython numpy pandas #TODO: fix dependcies
178 -conda install -c https://www.desy.de/~cpassow/condarepo/ flashh5
179 -
180 -## on jhub
181 -conda install ipykernel
182 -python -m ipykernel install --user --name flashh5 --display-name "flashh5"
183 -
184 -
185 -## to remove on jhub
186 -## delete from: /home/$USER/.local/share/jupyter/kernels/
187 -{{/code}}
188 -
189 -\\
190 -
191 191  {{code language="py" title="moved to repository?"}}
192 192  class RunDirectory:
193 193  
194 - def get_run_table(): # more or less information? RunComment | Number of Files | start & stop time ?
41 + def get_run_table(self):
195 195   ...
196 196  
197 - def get_run(daq, run_number): # daq is not needed!
198 -
44 + def get_run(self, daq, run_number):
199 199   ...
200 200  
201 201  
202 -class Run: # constructor optional without RunDirectory or use there self.path
48 +class Run:
203 203  
204 - def get_files():
50 + def get_files(self):
205 205   ...
206 206  
207 - def get_channels(): # of file #1
53 + def get_channels(self): # of file #1?
208 208   ...
209 209  
210 - def get_start_time(): # better as attribute?
56 + def get_start_time(self):
211 211   ...
212 212  
213 - def get_stop_time(): # which? | better as attribute?
59 + def get_stop_time(self): # which?
214 214   ...
215 -
216 - def to_df(daq_map): # to_df(daq_map, slice) slice=[0:4] -> throw Exception
61 +
62 + def to_df(self, channel_dict):
217 217   ...
218 218  
219 - def to_series(channel):
65 + def to_series(self, channel):
220 220   ...
221 221  
222 - def to_array(channel):
68 + def to_array(self, channel):
223 223   ...
224 224  {{/code}}
225 225  
226 226  {{code language="py" title="ideas"}}
227 -run.to_df(daq_map)
228 -run.to_series(daq_adr or daq_map) # on channel only?
229 -run.to_array(daq_adr) # on channel only?
73 +run.to_df(channel_dict)
74 +run.to_series(channel_string or channel_dict) # on channel only?
75 +run.to_array(channel_string) # on channel only?
230 230  
231 -## interesting?
232 -# run.to_dask(daq_map)
233 -# run.to_xarray(daq_map)
77 +# run.to_dask(dict)
78 +# run.to_xarray(dict)
234 234  {{/code}}
235 235  
236 236  \\
237 -
238 -\\
239 -{{/expand}}