docs: Minor polished to the documentation

Author: KennethEnevoldsen

docs/dependencydistance.rst

@@ -1,19 +1,29 @@
 Dependency Distance
 --------------------
 
-The *dependency_distance* component adds measures of depedency distance to both :code:`Doc`, :code:`Span`, and :code:`Token` objects under the ._.dependency_distance attribute.
-Dependency distance can be used a measure of syntactics complexity, the greater the distance, the more complex (`Liu 2008 <https://pdfs.semanticscholar.org/b6b9/cf00698a76d7a1e5ba58baa92d8799366813.pdf>`__, `Oya 2011 <http://www.paaljapan.org/conference2011/ProcNewest2011/pdf/poster/P-13.pdf>`__). 
+The *dependency_distance* component adds measures of depedency distance to both :code:`Doc`, :code:`Span`, and :code:`Token` objects 
+under the :code:`._.dependency_distance` attribute.
+Dependency distance can be used a measure of syntactics complexity, the greater the distance, the more complex 
+(`Liu 2008 <https://pdfs.semanticscholar.org/b6b9/cf00698a76d7a1e5ba58baa92d8799366813.pdf>`__, `Oya 2011 <http://www.paaljapan.org/conference2011/ProcNewest2011/pdf/poster/P-13.pdf>`__). 
 
-The implementation in textdescriptives follows Oya, 2011. We calculate the distances from each token to their dependent, and take the mean of this for calculating the mean dependency distance for spans. We then calculate the Doc level DD by averaging over the sentence-level mean DDs.
+The implementation in textdescriptives follows Oya, 2011. We calculate the distances 
+from each token to their dependent, and take the mean of this for calculating the mean 
+dependency distance for spans. We then calculate the Doc level dependency distance by
+averaging over the sentence-level mean dependency distances.
 
-Please see `this issue <https://github.com/HLasse/TextDescriptives/issues/77>`__ for how to calculate the DD metric proposed by Liu, 2008 with TextDescriptives.
+Please see `this issue <https://github.com/HLasse/TextDescriptives/issues/77>`__ for
+how to calculate the dependency distance metric proposed by Liu, 2008 with TextDescriptives.
 
 
-For :code:`Doc` objects, the mean and standard deviation of dependency distance on the sentence level is returned along with the mean and standard deviation of the proportion adjacent dependency relations on sentence level.
+For :code:`Doc` objects, the mean and standard deviation of dependency distance on the
+sentence level is returned along with the mean and standard deviation of the proportion
+adjacent dependency relations on sentence level.
 
-For :code:`Span` objects, the mean dependency distance and the mean proportion adjacent dependency relations in the span are returned.
+For :code:`Span` objects, the mean dependency distance and the mean proportion adjacent
+dependency relations in the span are returned.
 
-For :code:`Token` objects, the dependency distance and whether the dependency relation is an adjacent token is returned. 
+For :code:`Token` objects, the dependency distance and whether the dependency relation
+is an adjacent token is returned. 
 
 Usage
 ~~~~~~

docs/descriptivestats.rst

@@ -4,23 +4,26 @@ Descriptive Statistics
 The *descriptive_stats* component extracts a number of descriptive statistics. 
 The following attributes are added:
 
-* ._.counts (:code:`Doc` & :code:`Span`) 
-  
+* :code:`{Doc/Span}._.counts`
+
   *  Number of tokens.
   *  Number of unique tokens.
   *  Proportion unique tokens.
   *  Number of characters.
-* ._.sentence_length(:code:`Doc`)
+
+* :code:`{Doc/Span}._.sentence_length`
 
   * Mean sentence length.
   * Median sentence length.
   * Std of sentence length.
-* ._.syllables(:code:`Doc`)
+
+* :code:`{Doc/Span}._.syllables`
 
   * Mean number of syllables per token.
   * Median number of syllables per token.
   * Std of number of syllables per token.
-* ._.token_length(:code:`Doc` & :code:`Span`) 
+
+* :code:`{Doc/Span}._.token_length`
 
   * Mean token length.
   * Median token length.

docs/index.rst

@@ -50,7 +50,7 @@ please use the discussion Forums.
 
 .. toctree::
    :maxdepth: 2
-   :caption: Package References
+   :caption: Compoents
    :hidden:
 
    descriptivestats

docs/installation.rst

@@ -5,21 +5,15 @@ To get started using TextDescriptives you can install it using pip by running th
 .. code-block::
 
    pip install textdescriptives
-   pip install "textdescriptives[style,tests,docs,tutorials]"
 
-Installing from source
+Development Installation
 ^^^^^^^^^^^^^^^^^^^^^^^^^
 
-You can also install TextDescriptives directly from source using:
+To install TextDescriptives for development, clone the repository and install the
+package using the following commands:
 
 .. code-block::
 
-   git clone https://github.com/hlasse/textdescriptives.git
-   cd TextDescriptives
-   pip install .
+   git clone https://github.com/hlasse/TextDescriptives
 
-or
-
-.. code-block::
-
-   pip install git+https://github.com/hlasse/textdescriptives
+   pip install -e ".[style,tests,docs,tutorials]"

docs/news.rst

@@ -1,16 +1,19 @@
 News and Changelog
 ---------------------------------
 
-**v2.0.0 - X 2022**
-- All components have been renamed to have the :code:`textdescriptives/` prefix. I.e. components should now be loaded with e.g. :code:`nlp.add_pipe("textdescriptives/descriptive_stats)`.
-:code:`textdescriptives/all` can be used to load all components at once. 
+**v2.0.0 - 1st of January 2023**
+
+- All components have been renamed to have the :code:`textdescriptives/` prefix. I.e. components should now be loaded with e.g. :code:`nlp.add_pipe("textdescriptives/descriptive_stats)`. :code:`textdescriptives/all` can be used to load all components at once.
 - :code:`pos_stats` has been renamed to :code:`pos_proportions` for consistency.
 
 **v1.1.0 - 21st of September, 2022**
+
 - Added the new pipe; "quality". This pipe implements a series of metrics related to text quality, some of which were used by Rae et al. (2021) and Raffel et al. (2020) to filter large text corpora. See the documentation for examples.
 
 **v1.0.7 - 4th May, 2022**
+
 - Some minor fixes and bells and whistles.
 
 **v1.0.5 - 4th October, 2021**
-- POS proportions now use :code:`pos_` instead of :code:`tag_` by default. This behavior can be changed by setting `use_tag` to `False` when initialising the `pos_stats` module. 
+
+- POS proportions now use :code:`pos_` instead of :code:`tag_` by default. This behavior can be changed by setting `use_tag` to `False` when initialising the `pos_stats` module. 

docs/posstats.rst

@@ -3,10 +3,11 @@ Part-of-Speech Proportions
 
 The *pos_stats* component adds one attribute to a Doc or Span:
 
-* ._.proportions (:code:`Doc`) 
+* :code:`Doc._.pos_proportions` 
     * Dict of :code:`{pos_prop_POSTAG: proportion of all tokens tagged with POSTAG}`. Does not create a key if no tokens in the document fit the POSTAG.
 
-* ._.proportions (:code:`Span`) 
+* :code:`Span._.pos_proportions`
+* 
     * Dict of :code:`{pos_prop_POSTAG: proportion of all tokens tagged with POSTAG}`. Does not create a key if no tokens in the document fit the POSTAG.
 
 

docs/readability.rst

@@ -1,7 +1,7 @@
 Readability
 --------------------
 
-The *readability* component adds the following readabiltiy metrics under the ._.readability attribute to :code:`Doc` objects.
+The *readability* component adds the following readabiltiy metrics under the :code:`._.readability` attribute to :code:`Doc` objects.
 
 * Gunning-Fog
 * SMOG
@@ -12,7 +12,7 @@ The *readability* component adds the following readabiltiy metrics under the ._.
 * Lix
 * Rix
 
-For specifics of the implementation, refer to the source. The equations are largely derived from the `textstat <https://github.com/shivam5992/textstat>`_ library.
+For specifics of the implementation, refer to the source.±
 
 Usage
 ~~~~~~

src/textdescriptives/components/quality.py

@@ -673,12 +673,12 @@ def create_quality_component(
     out low quality text from large text corpora.
 
     References:
-    [1] Rae, J. W., Borgeaud, S., Cai, T., Millican, K., Hoffmann, J., Song, F., ... &
-        Irving, G. (2021). Scaling language models: Methods, analysis & insights from
-        training gopher. arXiv preprint arXiv:2112.11446.
-    [2] Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., ... &
-        Liu, P. J. (2020). Exploring the limits of transfer learning with a unified
-        text-to-text transformer. J. Mach. Learn. Res., 21(140), 1-67.
+    - [1] Rae, J. W., Borgeaud, S., Cai, T., Millican, K., Hoffmann, J., Song, F., ... &
+    Irving, G. (2021). Scaling language models: Methods, analysis & insights from
+    training gopher. arXiv preprint arXiv:2112.11446.
+    - [2] Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., ... &
+    Liu, P. J. (2020). Exploring the limits of transfer learning with a unified
+    text-to-text transformer. J. Mach. Learn. Res., 21(140), 1-67.
 
     Args:
         nlp (Language): spaCy language object, does not need to be specified in the