add data processing #5
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raphaeltimbo
commented
May 15, 2023
- Fix library name
- Replace master with main in the docs
- Add processing module to filter data
When we run the script from excel the log would be saved to the documents folder.
This adds an option to select a different anaconda environment.
Xlwings is used with the xl files in the scripsts folder.
This file can be used to update the code with git.
If a file is modified the merge will fail, so we have to restore all files before we try to make the git pull.
This reverts commit dfa0e36.
Add point class for back-to-back compressor.
Since we split arg_names in "_", it is not possible to automatically check for arguments with flow_v or flow_m in their name.
This method allow us to write the toml to a string. This is useful to send this string to a .zip file directly without the need to save the file on disk.
The use of pickle can be unsafe, so we had to replace it with the toml files.
The .ccp files now have the compressor objects serialized to a .toml file instead of a pickle one due to security issues.
When converting an impeller to a different suction condition, the value of volume_ratio_ratio is kept constant and a new speed is found. This speed would have a different value from the speed in the original curve. This is not always what the user wants, since some curves would even go out of the compressor speed range. With the speed='same' option, the impeller is converted and them new curves are generated by interpolating the converted curves to the speed values of the original impeller.
Ubuntu 18.04 is deprecated.
The use of pickle can be unsafe, so we had to replace it with the toml files.
Before moving the whole app to a multipage app, we serve a main page with links to each app.
This adds help messages that the user can see when they hover the mouse over the question mark next to the rendered markdown.
The processing module will have functions that will be used to process data to be used in performance calculation. For now, the main use is to filter a DataFrame based on maximum fluctuation values as per ASME PTC 10.
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