This was supposed to be split into multiple commits to make it easier to understand
but I failed to do it properly. So this is the list of changes:
- New analytics_indicator_calc db table to store indicators calculations
- Reuse previous calculations during prediction/training; other models
previous calculations should also be reused as long as they belong to
the same sample (sampleid depends on sampleorigin), time range and indicator
- Allow bulk inserting of these calculations as this can hurt database performance
- Block the same analysable to be analysed for training and for prediction
- Use a new instance of the target and use it for is_valid_* functions
as using ::is_valid_sample can lead to problems if people
uses it to cache stuff
This was done for indicators, targets and time splitting methods so that we
can get the string identifier and component in order to display a help_icon.
The functions were also made abstract, removing the default implementation.
Indicators, targets and time splitting methods should define this function.
Now we only predict using the most recent range available, this means
that if someone upgrades to moodle 3.4 at three quarters of a course
we will only calculate the latest range, previous ranges were not
displayed anyway once more recent predictions were available.
This commit deletes all previous predictions :) this shouldn't be a
problem in master as we don't provide any guarantee, the alternative
(retrive sampleids from mdl_files) would have been slow and a waste of
time as well as require horrible code in an upgrade step (text fields
do not accept defaults nor we can use NOTNULL).
- Split model::predict in parts
- JS promises updated according to eslint-plugin-promise
- New API methods replacing direct DB queries
- Reduce insights nav link display cost
- Increase time limit as well as memory for big processes
- Move prediction action event to core
- Dataset write locking and others
- Refine last time range end time
- Removed dodgy splitting method id to int
- Replace admin_setting_predictor output_html overwrite for write_setting overwrite
- New APIs for access control
- Discard invalid samples also during prediction
