add contribution section (#354)

docs/source/contributing.rst

@@ -0,0 +1,36 @@
+Contribution Guide
+==================
+
+Welcome to the contributing guide of py_neuromodulation! We are very happy that you are interested in our project.
+
+In general we recommend placing questions and issues in the `GitHub issue tracker <https://github.com/neuromodulation/py_neuromodulation/issues>`_.
+
+For code formatting we use `ruff <https://docs.astral.sh/ruff/formatter/>`_.
+
+For code development, we recommend using the package manager `rye <https://rye.astral.sh/>`_.
+
+To setup the python environment, type
+
+::
+
+    rye pin 3.12
+
+then sync the environment with
+
+::
+
+    rye sync
+
+Depending on your operating system, activate the rye virtual environment: 
+
+::
+
+    . .venv/bin/activate
+
+To install the documentation dependencies use pip:
+
+::
+
+    python -m pip install .[docs]
+
+

docs/source/index.rst

@@ -14,6 +14,7 @@ The *py_neuromodulation* toolbox allows for real time capable feature estimation
    usage
    auto_examples/index
    api_documentation
+   contributing
 
 Why py_neuromodulation?
 -----------------------

docs/source/nm_analysis.rst

@@ -1,5 +1,5 @@
 nm_analysis.py
 ==============
 
-.. automodule:: nm_analysis.Feature_Reader
+.. automodule:: nm_analysis
       :members:

docs/source/nm_stream_offline.rst → docs/source/nm_stream.rst

@@ -1,5 +1,5 @@
 nm_stream.py
-====================
+============
 
 .. automodule:: nm_stream
       :members:

docs/source/sg_execution_times.rst

@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**01:09.048** total execution time for 9 files **from all galleries**:
+**00:06.300** total execution time for 9 files **from all galleries**:
 
 .. container::
 
@@ -32,30 +32,30 @@ Computation times
    * - Example
      - Time
      - Mem (MB)
-   * - :ref:`sphx_glr_auto_examples_plot_1_example_BIDS.py` (``..\..\examples\plot_1_example_BIDS.py``)
-     - 00:25.194
+   * - :ref:`sphx_glr_auto_examples_plot_1_example_BIDS.py` (``../../examples/plot_1_example_BIDS.py``)
+     - 00:06.300
      - 0.0
-   * - :ref:`sphx_glr_auto_examples_plot_7_lsl_example.py` (``..\..\examples\plot_7_lsl_example.py``)
-     - 00:24.770
+   * - :ref:`sphx_glr_auto_examples_plot_0_first_demo.py` (``../../examples/plot_0_first_demo.py``)
+     - 00:00.000
      - 0.0
-   * - :ref:`sphx_glr_auto_examples_plot_0_first_demo.py` (``..\..\examples\plot_0_first_demo.py``)
-     - 00:12.259
+   * - :ref:`sphx_glr_auto_examples_plot_2_example_add_feature.py` (``../../examples/plot_2_example_add_feature.py``)
+     - 00:00.000
      - 0.0
-   * - :ref:`sphx_glr_auto_examples_plot_4_example_gridPointProjection.py` (``..\..\examples\plot_4_example_gridPointProjection.py``)
-     - 00:06.826
+   * - :ref:`sphx_glr_auto_examples_plot_3_example_sharpwave_analysis.py` (``../../examples/plot_3_example_sharpwave_analysis.py``)
+     - 00:00.000
      - 0.0
-   * - :ref:`sphx_glr_auto_examples_plot_2_example_add_feature.py` (``..\..\examples\plot_2_example_add_feature.py``)
+   * - :ref:`sphx_glr_auto_examples_plot_4_example_gridPointProjection.py` (``../../examples/plot_4_example_gridPointProjection.py``)
      - 00:00.000
      - 0.0
-   * - :ref:`sphx_glr_auto_examples_plot_3_example_sharpwave_analysis.py` (``..\..\examples\plot_3_example_sharpwave_analysis.py``)
+   * - :ref:`sphx_glr_auto_examples_plot_5_example_rmap_computing.py` (``../../examples/plot_5_example_rmap_computing.py``)
      - 00:00.000
      - 0.0
-   * - :ref:`sphx_glr_auto_examples_plot_5_example_rmap_computing.py` (``..\..\examples\plot_5_example_rmap_computing.py``)
+   * - :ref:`sphx_glr_auto_examples_plot_6_real_time_demo.py` (``../../examples/plot_6_real_time_demo.py``)
      - 00:00.000
      - 0.0
-   * - :ref:`sphx_glr_auto_examples_plot_6_real_time_demo.py` (``..\..\examples\plot_6_real_time_demo.py``)
+   * - :ref:`sphx_glr_auto_examples_plot_7_lsl_example.py` (``../../examples/plot_7_lsl_example.py``)
      - 00:00.000
      - 0.0
-   * - :ref:`sphx_glr_auto_examples_plot_8_cebra_example.py` (``..\..\examples\plot_8_cebra_example.py``)
+   * - :ref:`sphx_glr_auto_examples_plot_8_cebra_example.py` (``../../examples/plot_8_cebra_example.py``)
      - 00:00.000
      - 0.0

examples/plot_1_example_BIDS.py

@@ -184,7 +184,7 @@
 # Nevertheless, the user can also use the pipeline for machine learning decoding.
 # It can be used for regression and classification problems and also dimensionality reduction such as PCA and CCA.
 #
-# Here, we show an example using the XGBOOST classifier. The used labels came from a continuous grip force movement target, named "MOV_RIGHT".
+# Here, we show an example using a sklearn linear regression model. The used labels came from a continuous grip force movement target, named "MOV_RIGHT".
 #
 # First we initialize the :class:`~nm_decode.Decoder` class, which the specified *validation method*, here being a simple 3-fold cross validation,
 # the evaluation metric, used machine learning model, and the channels we want to evaluate performances for.

py_neuromodulation/nm_bursts.py

@@ -150,6 +150,7 @@ def calc_feature(self, data: np.ndarray) -> dict:
         batch_size = (
             filtered_data.shape[-1] if self.batch == 0 else self.samples_overlap
         )
+
         self.batch += 1
         self.data_buffer = np.concatenate(
             (

pyproject.toml

@@ -55,6 +55,8 @@ dependencies = [
     "pynput",
     "pyqt5",
     "pydantic>=2.7.3",
+    "pip>=24.2",
+    "nibabel>=5.2.1",
 ]
 
 [project.optional-dependencies]
@@ -75,8 +77,8 @@ docs = [
   "sphinx_togglebutton",
 ]
 
-[tool.rye]
-dev-dependencies = ["py-neuromodulation[dev]"]
+#[tool.rye]
+#dev-dependencies = ["py-neuromodulation[dev]"]
 
 [project.urls]
 bugtracker = "https://github.com/neuromodulation/py_neuromodulation/issues"