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Wiki source code of DEMO - Working with FLASH data

Last modified by sndueste on 2025-04-23 14:53
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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.
2
3 {{info title="How to login JupyterHub"}}
4 === ===
5
6 {{view-file att--filename="tmp.mp4" height="150"/}}
7 {{/info}}
8
9 {{info}}
10 === There are different options that help you to work with the FLASH HDF5 data in Python ===
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"]]
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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}}
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19 [[~[~[image:attach:image2023-9-29_11-1-37.png~]~]>>url:https://hasfcpkg.desy.de/fab/fab.html||shape="rect"]]
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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"]]
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24 ----
25
26 === TODO ===
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28 (% class="task-list" %)
29 (((
30 {{task reference="/Tasks/Task_18" status="InProgress"}}
31 Short descriptions including Links:   → as Text
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34 (((
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37 {{task reference="/Tasks/Task_19" status="InProgress"}}
38 GPFS
39 {{/task}}
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42 Access rights
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45 {{task reference="/Tasks/Task_41" status="InProgress"}}
46 Gamma Portal
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50 Maxwell
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54 JupyterHub
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57 {{task reference="/Tasks/Task_21" status="InProgress"}}
58 conda ?
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61 {{task reference="/Tasks/Task_36" status="InProgress"}}
62 explain install from channel instead of fixed environment, but can use environment file from example repository
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64 )))
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72 distribution
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79 channel  (where to host?)
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83 environment file (repository with examples)
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85 )))
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93 Documentation
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100 here VS repository VS sphinx
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110 Binder
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117 examples with Stefan
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127 Screencast
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134 login in jupyter hub
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138 login maxwell display
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141 {{task reference="/Tasks/Task_32" status="InProgress"}}
142 use slix
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145 {{task reference="/Tasks/Task_33" status="InProgress"}}
146 use hdfview plugin in jupterLab
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149 {{task reference="/Tasks/Task_34" status="InProgress"}}
150 create conda env with flashh5
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152 )))
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158 ----
159
160 ==== under review ====
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 {{code language="py" title="
179 moved to repository?"}}
180 class RunDirectory:
181
182 def get_run_table(): # more or less information? RunComment | Number of Files | start & stop time ?
183 ...
184
185 def get_run(daq, run_number): # daq is not needed!
186
187 ...
188
189
190 class Run: # constructor optional without RunDirectory or use there self.path
191
192 def get_files():
193 ...
194
195 def get_channels(): # of file #1
196 ...
197
198 def get_start_time(): # better as attribute?
199 ...
200
201 def get_stop_time(): # which? | better as attribute?
202 ...
203
204 def to_df(daq_map): # to_df(daq_map, slice) slice=[0:4] -> throw Exception
205 ...
206
207 def to_series(channel):
208 ...
209
210 def to_array(channel):
211 ...
212 {{/code}}
213
214 {{code language="py" title="ideas"}}
215 run.to_df(daq_map)
216 run.to_series(daq_adr or daq_map) # on channel only?
217 run.to_array(daq_adr) # on channel only?
218
219 ## interesting?
220 # run.to_dask(daq_map)
221 # run.to_xarray(daq_map)
222 {{/code}}
223
224
225
226 {{/expand}}