Skip to content
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.

Sign up for GitHub

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

docs: Fix a few typos #15

Merged
merged 1 commit into from
Sep 18, 2022
Merged

docs: Fix a few typos #15

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/install.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@ You will need `Python <http://python.org>`_ version 2.6 or better to run
primarily under Python 2.7, so that version is recommended. It does *not*
run under Python 3.X.

.. warning:: To succesfully install :mod:`hypatia`, you will need an
.. warning:: To successfully install :mod:`hypatia`, you will need an
environment capable of compiling Python C code. See the
documentation about installing, e.g. ``gcc`` and ``python-devel``
for your system. You will also need :term:`setuptools` installed
Expand Down
2 changes: 1 addition & 1 deletion hypatia/text/baseindex.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -241,7 +241,7 @@ def _search_wids(self, wids):
# Subclass must override.
# It's not clear what it should do. It must return an upper bound on
# document scores for the query. It would be nice if a document score
# divided by the query's query_weight gave the proabability that a
# divided by the query's query_weight gave the probability that a
# document was relevant, but nobody knows how to do that. For
# CosineIndex, the ratio is the cosine of the angle between the document
# and query vectors. For OkapiIndex, the ratio is a (probably
Expand Down