update documenation

docs/html/_sources/pages/ecosystem.rst 2.txt

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+SPARCSpy Ecosystem
+==================
+
+This section will give you an overview of the SPARCSpy Ecosystem and make you familar with our datastructure.
+
+.. toctree::
+ :maxdepth: 2
+ :caption: Ecosystem:
+
+ ecosystem/installation
+ notebooks/example_sparcspy_project.ipynb

docs/html/_sources/pages/ecosystem/installation.rst 2.txt

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+.. _installation:
+
+*******************
+Installation
+*******************
+
+SPARCSpy has been tested with **Python 3.8 and 3.9**. We recommended installing the library within a conda environment. 
+
+To install the SPARCSpy library clone the Github repository and use pip to install the library in your current environment.
+Please make sure that the package is installed editable (with the `-e` flag). Otherwise pretrained models might not be available.
+
+We recommend installing the non-python dependencies with conda before installing SPARCSpy (especially if running on an M1 Silicon Mac):
+
+.. code::
+
+ git clone https://github.com/MannLabs/SPARCSpy
+ cd SPARCSpy
+
+ conda create -n "SPARCSpy"
+ conda activate SPARCSpy
+ conda install python=3.9 scipy 'scikit-image>=0.19' scikit-fmm cellpose opencv numba -c conda-forge
+
+
+In case you wish to utilize the ML capabilities of SPARCSpy (either for segmentation or classification) please follow the instructions `here <https://pytorch.org/get-started/locally/>`_ to install pytorch correctly for your operating system. Once this has been installed you can verify that pytorch is installed correctly by executing the following python code:
+
+.. code:: python
+
+ import torch
+ x = torch.rand(5, 3)
+ print(x)
+
+You can access the python console by typing `python` and exit it when you are finished by entering `exit()`.
+The output should look something like this:
+
+.. code:: python
+
+ tensor([[0.3380, 0.3845, 0.3217],
+ [0.8337, 0.9050, 0.2650],
+ [0.2979, 0.7141, 0.9069],
+ [0.1449, 0.1132, 0.1375],
+ [0.4675, 0.3947, 0.1426]])
+
+Once you have installed pytorch according to the instructions we still need to install pytorch lightning. To do this run:
+
+.. code:: 
+
+ conda install -c conda-forge pytorch-lightning
+
+Currently SPARCSpy depends on a developer version of alphabase so please install the package from source by doing the following:
+
+.. code::
+
+ pip install git+https://github.com/MannLabs/alphabase
+
+Once these steps are completed you can proceed to install the SPARCSpy package via pip:
+
+.. code:: 
+
+ pip install -e .
+
+In case you wish to export shapes for excision on a Leica LMD please also install the `py-lmd <https://github.com/MannLabs/py-lmd>`_ library into the same conda environment
+following the installation instructions `here <https://mannlabs.github.io/py-lmd/html/pages/quickstart.html#installation-from-github>`_.

docs/html/_sources/pages/guides/basic_workflow.rst 2.txt

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+*******************
+Basic Workflows
+*******************
+
+This will be the folder where we put tutorials

docs/html/_sources/pages/module.rst 2.txt

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+Module Documentation
+=====================
+
+Documentation for all functions included in the SPARCSpy module.
+
+.. toctree::
+ :maxdepth: 4
+ :caption: Module Documentation:
+
+ module/processing 
+ module/pipeline
+ module/ml

docs/html/_sources/pages/module/ml.rst 2.txt

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+*******************
+ml
+*******************
+
+.. toctree::
+ :maxdepth: 3
+
+datasets
+########
+
+.. automodule:: sparcscore.ml.datasets
+ :members:
+
+metrics
+########
+
+.. automodule:: sparcscore.ml.metrics
+ :members:
+
+models
+########
+
+.. autoclass:: sparcscore.ml.models.VGGBase
+ :members:
+ :show-inheritance: False
+
+.. autoclass:: sparcscore.ml.models.VGG1
+ :members:
+ :show-inheritance:
+
+.. autoclass:: sparcscore.ml.models.VGG2
+ :members:
+ :show-inheritance:
+
+
+plmodels
+########
+
+.. autoclass:: sparcscore.ml.plmodels.MultilabelSupervisedModel
+ :members:
+ :show-inheritance: False
+
+pretrained_models
+#################
+
+.. automodule:: sparcscore.ml.pretrained_models
+ :members:
+
+transforms
+###########
+
+.. automodule:: sparcscore.ml.transforms
+ :members:
+
+utils
+###########
+
+.. automodule:: sparcscore.ml.utils
+ :members:

docs/html/_sources/pages/module/pipeline.rst 2.txt

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+*******************
+pipeline 
+*******************
+
+.. toctree::
+ :maxdepth: 3
+
+base
+#######
+
+Logable
+==============
+.. autoclass:: sparcscore.pipeline.base.Logable
+ :members:
+
+ProcessingStep
+==============
+.. autoclass:: sparcscore.pipeline.base.ProcessingStep
+ :members:
+ :show-inheritance:
+
+project
+#######
+
+Project 
+=========
+.. autoclass:: sparcscore.pipeline.project.Project
+ :members:
+ :show-inheritance:
+
+
+TimecourseProject 
+=================
+.. autoclass:: sparcscore.pipeline.project.TimecourseProject
+ :members:
+ :show-inheritance:
+
+
+segmentation
+#############
+
+Segmentation
+==============
+.. autoclass:: sparcscore.pipeline.segmentation.Segmentation
+ :members:
+ :show-inheritance:
+
+ShardedSegmentation
+=====================
+.. autoclass:: sparcscore.pipeline.segmentation.ShardedSegmentation
+ :members:
+ :show-inheritance:
+
+TimecourseSegmentation
+======================
+.. autoclass:: sparcscore.pipeline.segmentation.TimecourseSegmentation
+ :members:
+ :show-inheritance:
+
+MultithreadedTimecourseSegmentation
+===================================
+.. autoclass:: sparcscore.pipeline.segmentation.MultithreadedSegmentation
+ :members:
+ :show-inheritance:
+
+
+workflows
+##########
+.. automodule:: sparcscore.pipeline.workflows
+ :members:
+
+extraction
+###########
+
+HDF5CellExtraction
+===================
+.. autoclass:: sparcscore.pipeline.extraction.HDF5CellExtraction
+ :members:
+ :show-inheritance:
+
+TimecourseHDF5CellExtraction
+============================
+.. autoclass:: sparcscore.pipeline.extraction.TimecourseHDF5CellExtraction
+ :members:
+ :show-inheritance:
+
+
+classification
+##############
+
+MLClusterClassifier
+===================
+.. autoclass:: sparcscore.pipeline.classification.MLClusterClassifier
+ :members:
+ :show-inheritance:
+
+ .. automethod:: __call__
+
+selection
+###########
+
+LMDSelection
+==============
+.. autoclass:: sparcscore.pipeline.selection.LMDSelection
+ :members:
+ :show-inheritance:
+

docs/html/_sources/pages/module/processing.rst 2.txt

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+*******************
+processing
+*******************
+
+utils
+######
+.. automodule:: sparcscore.processing.utils
+ :members:
+
+preprocessing
+#############
+.. automodule:: sparcscore.processing.preprocessing
+ :members:
+
+segmentation
+############
+.. automodule:: sparcscore.processing.segmentation
+ :members: