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In the same way that mth5 has a channel_summary method, that returns a dataframe with info about each channel, it would be nice to have a lighter-weight version that only returned one row per run.
This can be achieved by running a group_by on the channel_summary. grouper = df.groupby(["station", "run"])
A method that does this already is in aurora/aurora/tf_kernel/dataset.py, on the issue31 branch, which will soon be dev branch. The method is called channel_summary_to_dataset_definition
If run_summary is not appreciably faster than channel_summary, then it would probably be best to make run_summary depend explicitly on channel_summary as in my example.
grouper = df.groupby(["station", "run"])
The text was updated successfully, but these errors were encountered:
In the same way that mth5 has a channel_summary method, that returns a dataframe with info about each channel, it would be nice to have a lighter-weight version that only returned one row per run.
This can be achieved by running a group_by on the channel_summary.
grouper = df.groupby(["station", "run"])
A method that does this already is in aurora/aurora/tf_kernel/dataset.py, on the
issue31
branch, which will soon bedev
branch. The method is calledchannel_summary_to_dataset_definition
If run_summary is not appreciably faster than channel_summary, then it would probably be best to make run_summary depend explicitly on channel_summary as in my example.
grouper = df.groupby(["station", "run"])
The text was updated successfully, but these errors were encountered: