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Wiki source code of DEMO - Working with FLASH data

Version 35.1 by sndueste on 2023-09-28 16:54
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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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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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7 {{expand title="How to login JupyterHub"}}
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10 {{view-file att--filename="tmp.mp4" height="250"/}}
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15 {{info}}
16 === Reference implementation (Python) ===
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18 (imperative)  (% 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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20 (% 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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23 {{/info}}
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25 link to Repos and Fab
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33 {{expand title="older ideas ..."}}
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36 ----
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38 === TODO ===
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40 (% class="task-list" %)
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43 Short descriptions including Links:   → as Text\\
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49 {{task reference="/Tasks/Task_19" status="InProgress"}}
50 GPFS
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54 Access rights
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58 Gamma Portal
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62 Maxwell
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66 JupyterHub
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70 conda ?
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74 explain install from channel instead of fixed environment, but can use environment file from example repository
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76 )))
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85 distribution
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92 channel  (where to host?)
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96 environment file (repository with examples)
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98 )))
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107 Documentation
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114 here VS repository VS sphinx
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125 Binder
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132 examples with Stefan
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143 Screencast
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150 login in jupyter hub
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154 login maxwell display
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158 use slix
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162 use hdfview plugin in jupterLab
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166 create conda env with flashh5
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176 ----
177
178 ==== under review ====
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182 {{code language="bash"}}
183 conda create -n flashh5 python=3.10 # 3.10 not necessary, but would prefer 3.8 or higher
184 source activate flashh5
185 conda install ipython numpy pandas #TODO: fix dependcies
186 conda install -c https://www.desy.de/~cpassow/condarepo/ flashh5
187
188 ## on jhub
189 conda install ipykernel
190 python -m ipykernel install --user --name flashh5 --display-name "flashh5"
191
192
193 ## to remove on jhub
194 ## delete from: /home/$USER/.local/share/jupyter/kernels/
195 {{/code}}
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199 {{code language="py" title="moved to repository?"}}
200 class RunDirectory:
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202 def get_run_table(): # more or less information? RunComment | Number of Files | start & stop time ?
203 ...
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205 def get_run(daq, run_number): # daq is not needed!
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207 ...
208
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210 class Run: # constructor optional without RunDirectory or use there self.path
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212 def get_files():
213 ...
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215 def get_channels(): # of file #1
216 ...
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218 def get_start_time(): # better as attribute?
219 ...
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221 def get_stop_time(): # which? | better as attribute?
222 ...
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224 def to_df(daq_map): # to_df(daq_map, slice) slice=[0:4] -> throw Exception
225 ...
226
227 def to_series(channel):
228 ...
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230 def to_array(channel):
231 ...
232 {{/code}}
233
234 {{code language="py" title="ideas"}}
235 run.to_df(daq_map)
236 run.to_series(daq_adr or daq_map) # on channel only?
237 run.to_array(daq_adr) # on channel only?
238
239 ## interesting?
240 # run.to_dask(daq_map)
241 # run.to_xarray(daq_map)
242 {{/code}}
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247 {{/expand}}