.. _fwflag_interpolate_aggregated_feats:
================================
--interpolate_aggregated_feats
================================
Switch
======

--interpolate_aggregated_feats DAYS

Description
===========

Aggregates message-level features up to a new group-by field, interpolating across the given number of days for groups with sparse/missing dates. Aliased as ``--interpolate_feats``.

Argument and Default Value
==========================

A float — the number of days to interpolate across. Default: ``None``.

Details
=======

**Verified requirement:** the feature table given by :doc:`fwflag_f` must be at the **message level** (grouped by your :doc:`fwflag_messageid_field`, not e.g. ``user_id``) — ``FeatureRefiner.createInterpolatedFeatTable()`` asserts this explicitly and fails with ``AssertionError: Interpolate currently only works if interpolating message-level features`` otherwise.

**Known issue — broken in SQLite mode.** Once past that check, it calls ``mm.getTableColumnNameTypes(...)``, which queries ``information_schema.columns`` — not supported by SQLite. Verified: fails with ``sqlite3.OperationalError: no such table: information_schema.columns``. Works against MySQL.

Other Switches
==============

Required Switches:

* :doc:`fwflag_d`, :doc:`fwflag_c`, :doc:`fwflag_t`
* :doc:`fwflag_f` (a message-level feature table)
* :doc:`fwflag_date_field`

Example Commands
================

Requires MySQL — broken against SQLite, see Known issue above:

.. code-block:: bash

	dlatkInterface.py -d dla_tutorial -t msgs -c user_id -f 'feat$1gram$msgs$message_id' \
	--date_field date --interpolate_aggregated_feats 3