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Wiki source code of DEMO - Working with FLASH data

Version 23.1 by cpassow on 2022-04-05 16:14
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1 test
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5 === TODO ===
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10 Short descriptions including Links:   → as Text\\
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21 JupyterHub
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25 conda ?
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29 explain install from channel instead of fixed environment, but can use environment file from example repository
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51 environment file (repository with examples)
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62 Documentation
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87 examples with Stefan
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105 login in jupyter hub
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109 login maxwell display
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113 use slix
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117 use hdfview plugin in jupterLab
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121 create conda env with flashh5
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131 ----
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133 ==== under review ====
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137 {{code language="bash"}}
138 conda create -n flashh5 python=3.10 # 3.10 not necessary, but would prefer 3.8 or higher
139 source activate flashh5
140 conda install ipython numpy pandas #TODO: fix dependcies
141 conda install -c https://www.desy.de/~cpassow/condarepo/ flashh5
142
143 ## on jhub
144 conda install ipykernel
145 python -m ipykernel install --user --name flashh5 --display-name "flashh5"
146
147
148 ## to remove on jhub
149 ## delete from: /home/$USER/.local/share/jupyter/kernels/
150 {{/code}}
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154 {{code language="py" title="moved to repository?"}}
155 class RunDirectory:
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157 def get_run_table(): # more or less information? RunComment | Number of Files | start & stop time ?
158 ...
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160 def get_run(daq, run_number): # daq is not needed!
161
162 ...
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165 class Run:
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167 def get_files():
168 ...
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170 def get_channels(): # of file #1
171 ...
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173 def get_start_time(): # better as attribute?
174 ...
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176 def get_stop_time(): # which? | better as attribute?
177 ...
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179 def to_df(daq_map): # to_df(daq_map, slice) slice=[0:4] -> throw Exception
180 ...
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182 def to_series(channel):
183 ...
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185 def to_array(channel):
186 ...
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189 {{code language="py" title="ideas"}}
190 run.to_df(daq_map)
191 run.to_series(daq_adr or daq_map) # on channel only?
192 run.to_array(daq_adr) # on channel only?
193
194 ## interesting?
195 # run.to_dask(daq_map)
196 # run.to_xarray(daq_map)
197 {{/code}}
198
199 \\