Merge pull request #203 from ACCLAB/feat-final-changes

Bug fixes
Tutorials and readme updated
Added tests
Added additional arguments
Major forest plot code updates and added features
Trimmed various sections of code

Author: JAnns98

CHANGELOG.md

@@ -2,32 +2,30 @@
 
 <!-- do not remove -->
 
-## v2025.03.14
+## v2025.03.27
 
 ### New Features
 
-- **Horizontal Plots**: This new feature allows users to create horizontal plots instead of the regular vertical plots, providing a more compact visualization of data. This can be utilized by setting `horizontal=True` in the `plot()` method.
+- **Horizontal Plots**: Users can now create horizontal layout plots, providing compact data visualization. This can be achieved by setting `horizontal=True` in the `plot()` method.
 
-- **Forest Plots**: This new feature allows users to create forest plots! Forest plots provide a simple and intuitive way to visualize many delta-delta (or Deltas' g) or mini-meta effect sizes at once from multiple different dabest objects without presenting the raw data.
+- **Forest Plots**: Forest plots provide a simple and intuitive way to visualize many delta-delta (or Deltas’ g), mini-meta, or regular delta effect sizes at once from multiple different dabest objects without presenting the raw data.
 
-- **Gridkey**: This new feature allows users to create a gridkey to represent the labels of the groups in the plot. This can be utilized with the `gridkey_rows` argument in the `plot()` method.
+- **Gridkey**: Users can now represent their experimental labels in a gridkey format. This can be accessed with the `gridkey` argument in the `plot()` method. 
 
 - **Aesthetic Updates**: We have made several aesthetic improvements to the plots, including:
-   - **Swarm, Contrast, and Summary bars**: We have added bars to better highlight the various groups and their differences. These bars can be customized to suit the user's needs. The swarm and contrast bars are provided by default, while the summary bars can be added by the user.
+   - **Raw, Contrast, and Summary bars**: We added bars highlighting the various groups' differences. These bars can be customized to suit the user’s needs. Raw and contrast bars are provided by default, summary bars can be added by the user.
 
-   - **Delta-Delta Plots**: We have modified the delta-delta plot format to be more compact and easier to read. The new format brings the delta-delta (or Deltas' g) effect size closer to the regular effect sizes. In addition, a gap has been added to the zeroline to separate the delta-delta and regular effect sizes.
+   - **Delta-Delta and Mini-Meta Plots**: We have adjusted the spacing of delta-delta and mini-meta plots to reduce whitespace. The new format brings the added effect size closer to the regular effect sizes. In addition, delta-delta plots now have a gap in the zeroline to separate the delta-delta and regular effect sizes.
 
-   - **Delta-delta Effect Sizes for Proportion Plots**: Delta-delta effect sizes for proportion plots are now available.
-  
-   - **Mini-Meta Plots**: We have modified the mini-meta plot format to be more compact and easier to read. The new format brings the mini-meta effect size closer to the regular effect sizes.
+   - **Delta-delta Effect Sizes for Proportion Plots**: Delta-delta experimental plotting now supports binary data.
 
-   - **Proportion Plots Sample Sizes**: We have updated the proportion plots to show sample sizes for each group. These can be toggled on or off via the `prop_sample_counts` parameter.
+   - **Proportion Plots Sample Sizes**: The sample size of each binary option for each group can now be displayed. These can be toggled on or off via the `prop_sample_counts` parameter.
 
-   - **Effect Size Lines for Paired Plots**: Effect size lines for paired plots are now available. These can be toggled on or off via the `es_paired_lines` parameter.
+   - **Effect Size Lines for Paired Plots**: Paired plots now display lines linking the effect sizes within a group together in the contrast axes. These can be toggled on or off via the `contrast_paired_lines` parameter.
 
-   - **Baseline Error Curves**: Plots now include a baseline error dot and curve to show the error of the baseline/control group. By default, the dot is shown, while the curve can be added by the user (via the `show_baseline_ec` parameter).
+   - **Baseline Error Curves**: Baseline error dot and curve are now available to represent the baseline/control group in the contrast axes. The dot is shown by default, while the curve can be toggled on/off by the user (via the `show_baseline_ec` parameter).
 
-   - **Delta Text**: There is now an option to display delta text on the contrast axes. It displays the effect size of the contrast group relative to the reference group. This can be toggled on or off via the `delta_text` parameter. It is on by default.
+   - **Delta Text**: Effect size deltas are now displayed as text next to their respective effect size. This can be toggled on or off via the `delta_text` parameter.
 
    - **Empty Circle Color Palette**: A new swarmplot color palette modification is available for unpaired plots via the `empty_circle` parameter in the `plot()` method. This option modifies the two-group swarmplots to have empty circles for the control group and filled circles for the experimental group.
 
@@ -38,9 +36,10 @@
 - **Numba for Speed Improvements**: We have included Numba to speed up the various calculations in DABEST. This should make the calculations faster and more efficient. Importing DABEST may take a little longer than before, and a progress bar will appear during the import process to show the calculations being performed. Once imported, loading and plotting data should now be faster.
 
 - **Terminology Updates**: We have made several updates to the documentation and terminology to improve clarity and consistency. For example:
-    - The method to utilise the Deltas' g effect size is now via the `.hedges_g.plot()` method now rather than creating a whole new `Delta_g` object as before. The functionality remains the same, it plots hedges_g effect sizes and then the Deltas' g effect size alongside these (if a delta-delta experiment was loaded correctly).
+    - Plot arguments have been adjusted to bring more clarity and consistency in naming. Arguments relating to the rawdata plot axis will now be typically referred to with ‘raw’ while arguments relating to the contrast axis will be referred to with ‘contrast’. For example, ‘raw_label’ replaces ‘swarm_label’ and ‘bar_label’. The various kwargs relating to each different type of plot (e.g., swarmplot_kwargs) remain unchanged. 
+    - The method to utilise the Deltas’ g effect size is now via the .hedges_g.plot() method rather than creating a whole new Delta_g object as before. The functionality remains the same, it plots hedges_g effect sizes and then the Deltas’ g effect size alongside these (if a delta-delta experiment was loaded correctly).
 
-- **Updated Tutorial Pages**: We have updated the tutorial pages to reflect the new features and changes. The tutorial pages are now more comprehensive and hopefully more intuitive!.
+- **Updated Tutorial Pages**: We have updated the tutorial pages to reflect the new features and changes. The tutorial pages are now more comprehensive and (hopefully!) more intuitive!
 
 - **Results Dataframe for Delta-delta and Mini-meta Plots**: A results dataframe can now be extracted for both the delta-delta and mini-meta effect size data (similar to the results dataframe for the regular effect sizes). These can be found via the `.results` attribute of the `.delta_delta` or `.mini_meta` object.
 

README.md

@@ -14,106 +14,132 @@ citation](https://zenodo.org/badge/DOI/10.1038/s41592-019-0470-3.svg)](https://r
 
 ## Recent Version Update
 
-We are proud to announce **DABEST Version TBC (v2025.03.14)** This new
-version of the DABEST Python library provides several new features and
-includes performance improvements. It’s a big one!
-
-1.  **Python 3.13 Support**: DABEST now supports Python 3.10-3.13.
-
-2.  **Horizontal Plots**: This new feature allows users to create
-    horizontal plots instead of the regular vertical plots, providing a
-    more compact visualization of data. This can be utilized by setting
-    `horizontal=True` in the `plot()` method. See the [Horizontal
-    Plots](../tutorials/08-horizontal_plot.html) tutorial for more
-    details.
-
-3.  **Forest Plots**: This new feature allows users to create forest
-    plots! Forest plots provide a simple and intuitive way to visualize
-    many delta-delta (or Deltas’ g) or mini-meta effect sizes at once
-    from multiple different dabest objects without presenting the raw
-    data. See the [Forest Plots](../tutorials/07-forest_plot.html)
-    tutorial for more details.
-
-4.  **Gridkey**: This new feature allows users to create a gridkey to
-    represent the labels of the groups in the plot. This can be utilized
-    with the `gridkey_rows` argument in the `plot()` method. See the
-    gridkey section in the [Plot
-    Aesthetics](../tutorials/09-plot_aesthetics.html) tutorial for more
+We are proud to announce **DABEST Version Dadar (v2025.03.27)** This new
+version of the DABEST Python library includes several new features and
+performance improvements. It’s a big one!
+
+1.  **Python 3.13 Support**: DABEST now supports Python 3.10—3.13.
+
+2.  **Horizontal Plots**: Users can now create horizontal layout plots,
+    providing compact data visualization. This can be achieved by
+    setting `horizontal=True` in the `.plot()` method. See the
+    [Horizontal Plots tutorial](../tutorials/08-horizontal_plot.html)
+    for more details.
+
+3.  **Forest Plots**: Forest plots provide a simple and intuitive way to
+    visualize many delta-delta (or delta *g*), mini-meta, or regular
+    delta effect sizes at once from multiple different dabest objects
+    without presenting the raw data. See the [Forest Plots
+    tutorial](../tutorials/07-forest_plot.html) for more details.
+
+4.  **Gridkey**: Users can now represent experimental labels in a
+    ‘gridkey’ table. This can be accessed with the `gridkey` parameter
+    in the `.plot()` method. See the gridkey section in the [Plot
+    Aesthetics tutorial](../tutorials/09-plot_aesthetics.html) for more
     details.
 
-5.  **Aesthetic Updates**: We have made several aesthetic improvements
-    to the plots, including:
-
-    - **Swarm, Contrast, and Summary bars**: We have added bars to
-      better highlight the various groups and their differences. These
-      bars can be customized to suit the user’s needs. The swarm and
-      contrast bars are provided by default, while the summary bars can
-      be added by the user. See the relevant sections in the [Plot
-      Aesthetics](../tutorials/09-plot_aesthetics.html) tutorial for
-      more details.
-
-    - **Delta-Delta Plots**: We have modified the delta-delta plot
-      format to be more compact and easier to read. The new format
-      brings the delta-delta (or Deltas’ g) effect size closer to the
-      regular effect sizes. In addition, a gap has been added to the
-      zeroline to separate the delta-delta and regular effect sizes.
-
-    - **Delta-delta Effect Sizes for Proportion Plots**: Delta-delta
-      effect sizes for proportion plots are now available.
-
-    - **Mini-Meta Plots**: We have modified the mini-meta plot format to
-      be more compact and easier to read. The new format brings the
-      mini-meta effect size closer to the regular effect sizes.
-
-    - **Proportion Plots Sample Sizes**: We have updated the proportion
-      plots to show sample sizes for each group. These can be toggled on
-      or off via the `prop_sample_counts` parameter.
-
-    - **Effect Size Lines for Paired Plots**: Effect size lines for
-      paired plots are now available. These can be toggled on or off via
-      the `es_paired_lines` parameter.
-
-    - **Baseline Error Curves**: Plots now include a baseline error dot
-      and curve to show the error of the baseline/control group. By
-      default, the dot is shown, while the curve can be added by the
-      user (via the `show_baseline_ec` parameter).
-
-    - **Delta Text**: There is now an option to display delta text on
-      the contrast axes. It displays the effect size of the contrast
-      group relative to the reference group. This can be toggled on or
-      off via the `delta_text` parameter. It is on by default.
-
-    - **Empty Circle Color Palette**: A new swarmplot color palette
+5.  **Other Visualization Improvements**:
+
+    - **Comparing means and effect sizes**: The estimation plots now
+      include three types of customizable visual features to enhance
+      contextualization and comparison of means and effect sizes:
+
+      - **Bars for the mean of the observed values (`raw_bars`)**:
+        Colored rectangles that extend from the zero line to the mean of
+        each group’s raw data. These bars visually highlight the central
+        tendency of the raw data.
+
+      - **Bars for effect size/s (`contrast_bars`)**: Similar to raw
+        bars, these highlight the effect-size difference between two
+        groups (typically test and control) in the contrast axis. They
+        provide a visual representation of the differences between
+        groups.
+
+      - **Summary bands (`reference_band`)**: An optional band or ribbon
+        that can be added to emphasize a specific effect size’s
+        confidence interval that is used as a reference range across the
+        entire contrast axis. Unlike raw and contrast bars, these span
+        horizontally (or vertically if `horizontal=True`) and are not
+        displayed by default.
+
+        Raw and contrast bars are shown by default. Users can customize
+        these bars and add summary bands as needed. For detailed
+        customization instructions, please refer to the [Plot Aesthetics
+        tutorial](../tutorials/09-plot_aesthetics.html).
+
+    - **Tighter spacing in delta-delta and mini-meta plots**: We have
+      adjusted the spacing of delta-delta and mini-meta plots to reduce
+      whitespace. The new format brings the overall effect size closer
+      to the two-groups effect sizes. In addition, delta-delta plots now
+      have a gap in the zero line to separate the delta-delta from the ∆
+      effect sizes.
+
+    - **Delta-delta effect sizes for proportion plots**: In addition to
+      continuous data, delta-delta plots now support binary data
+      (proportions). This means that 2-way designs for binary outcomes
+      can be analyzed with DABEST.
+
+    - **Proportion plots sample sizes**: The sample size of each binary
+      option for each group can now be displayed. These can be toggled
+      on/off via the `prop_sample_counts` parameter.
+
+    - **Effect size lines for paired plots**: Along with lines
+      connecting paired observed values, the paired plots now also
+      display lines linking the effect sizes within a group in the
+      contrast axes. These lines can be toggled on/off via the
+      `contrast_paired_lines` parameter.
+
+    - **Baseline error curves**: To represent the baseline/control group
+      in the contrast axes, it is now possible to plot the baseline dot
+      and the baseline error curve. The dot is shown by default, while
+      the curve can be toggled on/off via the `show_baseline_ec`
+      parameter. This dot helps make it clear where the baseline comes
+      from i.e. the control minus itself. The baseline error curve can
+      be used to show that the baseline itself is an estimate inferred
+      from the observed values of the control data.
+
+    - **Delta text**: Effect-size deltas (e.g. mean differences) are now
+      displayed as numerals next to their respective effect size. This
+      can be toggled on/off via the `delta_text` parameter.
+
+    - **Empty circle color palette**: A new swarmplot color palette
       modification is available for unpaired plots via the
-      `empty_circle` parameter in the `plot()` method. This option
+      `empty_circle` parameter in the `.plot()` method. This option
       modifies the two-group swarmplots to have empty circles for the
       control group and filled circles for the experimental group.
 
 6.  **Miscellaneous Improvements & Adjustments**
 
-    - **Numba for Speed Improvements**: We have included Numba to speed
-      up the various calculations in DABEST. This should make the
-      calculations faster and more efficient. Importing DABEST may take
-      a little longer than before, and a progress bar will appear during
-      the import process to show the calculations being performed. Once
-      imported, loading and plotting data should now be faster.
-
-    - **Terminology Updates**: We have made several updates to the
-      documentation and terminology to improve clarity and consistency.
-      For example:
-
-      - The method to utilise the Deltas’ g effect size is now via the
-        `.hedges_g.plot()` method now rather than creating a whole new
-        `Delta_g` object as before. The functionality remains the same,
-        it plots hedges_g effect sizes and then the Deltas’ g effect
-        size alongside these (if a delta-delta experiment was loaded
+    - **Numba for speed improvements**: We have added
+      [Numba](https://numba.pydata.org/) to speed up the various
+      calculations in DABEST. Precalculations will be performed during
+      import, which will help speed up the subsequent loading and
+      plotting of data.
+
+    - **Terminology/naming updates**: During the refactoring of the
+      code, we have made several updates to the documentation and
+      terminology to improve clarity and consistency. For example:
+
+      - Plot arguments have been adjusted to bring more clarity and
+        consistency in naming. Arguments relating to the rawdata plot
+        axis will now be typically referred to with `raw` while
+        arguments relating to the contrast axis will be referred to with
+        `contrast`. For example, `raw_label` replaces `swarm_label` and
+        `bar_label`. The various kwargs relating to each different type
+        of plot (e.g., `swarmplot_kwargs`) remain unchanged.
+
+      - The method to utilise the Delta *g* effect size is now via the
+        .hedges_g.plot() method rather than creating a whole new Delta_g
+        object as before. The functionality remains the same, it plots
+        hedges_g effect sizes and then the Delta *g* effect size
+        alongside these (if a delta-delta experiment was loaded
         correctly).
 
-    - **Updated Tutorial Pages**: We have updated the tutorial pages to
+    - **Updated tutorial pages**: We have updated the tutorial pages to
       reflect the new features and changes. The tutorial pages are now
-      more comprehensive and hopefully more intuitive!.
+      more comprehensive and (hopefully!) more intuitive!
 
-    - **Results Dataframe for Delta-delta and Mini-meta Plots**: A
+    - **Results dataframe for delta-delta and mini-meta plots**: A
       results dataframe can now be extracted for both the delta-delta
       and mini-meta effect size data (similar to the results dataframe
       for the regular effect sizes). These can be found via the
@@ -165,7 +191,7 @@ allowing everyone access to high-quality estimation plots.
 
 ## Installation
 
-This package is tested on Python 3.10 and onwards. It is highly
+This package is tested on Python 3.11 and onwards. It is highly
 recommended to download the [Anaconda
 distribution](https://www.continuum.io/downloads) of Python in order to
 obtain the dependencies easily.

dabest/__init__.py

@@ -3,6 +3,7 @@
 from ._stats_tools import confint_2group_diff as ci_2g
 from ._effsize_objects import TwoGroupsEffectSize, PermutationTest
 from ._dabest_object import Dabest
+from .forest_plot import forest_plot
 
 
 import os
@@ -11,4 +12,4 @@
     if not _NUMBA_COMPILED:
         precompile_all()
 
-__version__ = "2025.03.14"
+__version__ = "2025.03.27"