predict-idlab · jonasvdd · Apr 24, 2023 · Dec 31, 2022 · Dec 31, 2022 · Dec 31, 2022
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -55,24 +55,8 @@ To install the requirements
 ```sh
 pip install poetry          # install poetry (if you do use the venv option)
 poetry install --all-extras # install all the dependencies
-poetry build                # build the underlying C code
 ```
 
-<details>
-   <summary>
-      <b>How to resolve the following error when running build.py:</b><br>
-      <code>Unable to build the "plotly_resampler.aggregation.algorithms.lttbc" C extension; will use the slower python fallback. <br>
-      command 'x86_64-linux-gnu-gcc' failed: No such file or directory
-      </code>
-   </summary>
-
-   To resolve this error we suggest to install some additional packages as no gcc (C compiler was found on your PC):
-   ```sh
-   sudo apt-get install build-essential libssl-dev libffi-dev python-dev
-   ```
-
-</details>
-
 ### Formatting the code
 
 We use [`black`](https://github.com/psf/black) and [`isort`](https://github.com/PyCQA/isort) to format the code.

diff --git a/LICENSE b/LICENSE
@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2022 Jonas Van Der Donckt, Jeroen Van Der Donckt, Emiel Deprost.
+Copyright (c) 2023 Jonas Van Der Donckt, Jeroen Van Der Donckt, Emiel Deprost.
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

diff --git a/README.md b/README.md
@@ -159,8 +159,7 @@ Paper (preprint): https://arxiv.org/abs/2206.08703
 
 - [x] Support `.add_traces()` (currently only `.add_trace` is supported)
 - [ ] Support `hf_color` and `hf_markersize`, see [#148](https://github.com/predict-idlab/plotly-resampler/pull/148)
-- [x] Create C bindings for our EfficientLTTB algorithm.
-- [ ] Integrate with [tsdownsample](https://github.com/predict-idlab/tsdownsample) :racehorse:
+- [x] Integrate with [tsdownsample](https://github.com/predict-idlab/tsdownsample) :racehorse:
 
 <br>
 

diff --git a/build.py b/build.py
diff --git a/docs/sphinx/FAQ.rst b/docs/sphinx/FAQ.rst
@@ -181,36 +181,6 @@ Some illustration:
    # ... (add more traces, etc.)
 
 
-.. raw:: html
-
-   </div>
-   </details>
-   <br>
-   <details>
-   <summary>
-      <a><b>I get errors such as:</b><br><ul><li>
-         <code>RuntimeError: module compiled against API version 0x10 but this version of numpy is 0xe</code></li>  
-         <li><code>ImportError: numpy.core.multiarray failed to import</code></li>
-         </ul>
-      </a>
-   </summary>
-   <div style="margin-left:1em">
-
-   Plotly-resampler uses compiled C code (which uses the NumPy C API) to speed up the LTTB data-aggregation algorithm. This C code gets compiled during the building stage of the package (which might be before you install the package).<br><br>
-   If this C extension was build against a more recent NumPy version than your local version, you obtain a 
-   <a href="https://numpy.org/devdocs/user/troubleshooting-importerror.html#c-api-incompatibility"><i>NumPy C-API incompatibility</i></a> 
-   and the above error will be raised.<br><br>
-
-   These above mentioned errors can thus be resolved by running<br>
-   &nbsp;&nbsp;&nbsp;&nbsp;<code>pip install --upgrade numpy</code><br>
-   and reinstalling plotly-resampler afterwards.<br><br>
-
-   For more information about compatibility and building upon NumPy, you can consult 
-   <a href="https://numpy.org/doc/stable/user/depending_on_numpy.html?highlight=compiled#for-downstream-package-authors">NumPy's docs for downstream package authors</a>.
-
-   We aim to limit this issue as much as possible (by for example using <a href="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/scipy/oldest-supported-numpy">oldest-supported-numpy</a> in our build.py), 
-   but if you still experience issues, please open an issue on <a href="https://github.com/predict-idlab/plotly-resampler/issues">GitHub</a>.
-
 .. raw:: html
 
    </div>

diff --git a/docs/sphinx/aggregation.rst b/docs/sphinx/aggregation.rst
@@ -21,3 +21,15 @@ Aggregator classes
     :members:
     :undoc-members:
     :show-inheritance:
+
+----------
+
+^^^^^^^^^^^^^^^^^^
+Aggregator parsing
+^^^^^^^^^^^^^^^^^^
+
+.. automodule:: plotly_resampler.aggregation.plotly_aggregator_parser
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
diff --git a/docs/sphinx/conf.py b/docs/sphinx/conf.py
@@ -65,8 +65,11 @@
 
 todo_include_todos = True
 
-autoclass_content = "both"
+# Commented out because it shows typehints in the signature.
+# autoclass_content = "both"
 autodoc_typehints = "description"
+# Don't show class signature with the class' name.
+autodoc_class_signature = "separated"
 autodoc_member_order = "bysource"
 autosummary_generate = True
 

diff --git a/plotly_resampler/__init__.py b/plotly_resampler/__init__.py
@@ -2,7 +2,7 @@
 
 import contextlib
 
-from .aggregation import LTTB, EfficientLTTB, EveryNthPoint
+from .aggregation import LTTB, EveryNthPoint, MinMaxLTTB
 from .figure_resampler import FigureResampler, FigureWidgetResampler
 from .registering import register_plotly_resampler, unregister_plotly_resampler
 
@@ -14,7 +14,7 @@
     "__version__",
     "FigureResampler",
     "FigureWidgetResampler",
-    "EfficientLTTB",
+    "MinMaxLTTB",
     "LTTB",
     "EveryNthPoint",
     "register_plotly_resampler",

diff --git a/plotly_resampler/aggregation/__init__.py b/plotly_resampler/aggregation/__init__.py
@@ -7,20 +7,22 @@
 __author__ = "Jonas Van Der Donckt"
 
 
-from .aggregation_interface import AbstractSeriesAggregator
+from .aggregation_interface import AbstractAggregator
 from .aggregators import (
     LTTB,
-    EfficientLTTB,
     EveryNthPoint,
     FuncAggregator,
     MinMaxAggregator,
+    MinMaxLTTB,
     MinMaxOverlapAggregator,
 )
+from .plotly_aggregator_parser import PlotlyAggregatorParser
 
 __all__ = [
-    "AbstractSeriesAggregator",
+    "AbstractAggregator",
+    "PlotlyAggregatorParser",
     "LTTB",
-    "EfficientLTTB",
+    "MinMaxLTTB",
     "EveryNthPoint",
     "FuncAggregator",
     "MinMaxAggregator",