-
Notifications
You must be signed in to change notification settings - Fork 80
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Add data_type_id column to preprocessed and processed data tables #194
Add data_type_id column to preprocessed and processed data tables #194
Conversation
…origin' into add-data-type-to-preproc-proc-data
Returns | ||
------- | ||
str or int | ||
string value of data_type or data_type_id |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
can you indicate here when would it be a string and when would it be an int?
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
@squirrelo, I think you missed this comment.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Ah, it is in two places. Got the other one you missed and missed this one.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Ok, that's weird. It's changed if you look at the file diff but this comment is still here.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Ah gotcha, thanks!
Just a few changes, all of which are very minor. |
This should be good to merge. |
…data Add data_type_id column to preprocessed and processed data tables
Needed because we want finer grain control over what datatype we are working with. Before this, we got it from raw data, which could potentially have multiple types (e.g. 16S and 18S in same run). Now we keep track of the datatype through the entire process.
This also has the required edits to the data objects to allow for addition of data_type upon creation and for getting both the text data_type and the data_type_id using, for example,
RawData.data_type(ret_id=True)