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.buildinfo

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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 1d08db85a79bfccf7301ffbec52d7ebe
+tags: 645f666f9bcd5a90fca523b33c5a78b7

_sources/index.rst.txt

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+.. Pore2Chip documentation master file, created by
+   sphinx-quickstart on Thu Jan  2 09:45:53 2025.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+Pore2Chip Documentation
+=======================
+A python package that takes XCT images of porous materials and generates representative digital twin micromodels.
+
+.. figure:: _static/ModEx_Loop_SoilChip.jpg
+   :width: 636px
+   :height: 453px
+   :scale: 100 %
+   :alt: ModEx Loop for Pore2Chip and Chip2Flow
+
+ModEx Loop for Pore2Chip and Chip2Flow
+
+About Pore2Chip
+---------------
+**Pore2Chip** is a Python module designed to streamline the process of analyzing X-ray computed tomography (XCT) 
+images of soil and creating 2D micromodel designs based on that analysis. 
+It leverages the power of open-source libraries like OpenPNM, PoreSpy, and drawsvg to extract key information about the soil's 
+porous structure and translate it into a blueprint for microfluidic simulations or physical "lab-on-a-chip" devices developed using additive manufacturing.
+
+User Guide
+----------
+.. toctree::
+   :maxdepth: 1
+
+   install
+   quickstart
+
+Acknowledgements
+----------------
+This research was performed on a project award (Award DOIs: 10.46936/ltds.proj.2024.61069/60012423; 10.46936/intm.proj.2023.60674/60008777; 10.46936/intm.proj.2023.60904/60008965) 
+from the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility sponsored by the Biological and Environmental Research program under contract no. DE-AC05-76RL01830. 
+The authors acknowledge the contributions of Michael Perkins at PNNL’s Creative Services, who developed the conceptual graphics in this paper.
+
+PNNL-SA-197910
+
+Disclaimer
+----------
+This research work was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, 
+nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, 
+apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, 
+or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. 
+The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.
+
+.. note::
+
+   This project is under active development.
+
+

_sources/install.rst.txt

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+
+.. Installation
+.. =======================
+
+.. The OpenPNM and PoreSpy libraries are required to analyze XCT images. PoreSpy is used to generate a 
+.. pore network that is used to extract pore size distribution, pore throat size distribution, and pore coordination numbers. 
+.. OpenPNM is used to construct a new 2D pore network that will be used to create the micromodel design.
+
+.. Install using PiP:
+
+.. .. code-block:: console
+        .. $ pip install pore2chip
+
+Installation
+============
+
+The OpenPNM and PoreSpy libraries are required to analyze XCT images. PoreSpy is used to generate a 
+pore network that is used to extract pore size distribution, pore throat size distribution, and pore coordination numbers. 
+OpenPNM is used to construct a new 2D pore network that will be used to create the micromodel design.
+
+Pip Installation
+----------------
+Install using PiP:
+
+.. code-block:: bash
+
+   pip install pore2chip
+
+Install from source:
+
+.. code-block:: bash
+
+   git clone https://github.com/EMSL-Computing/Pore2Chip.git 
+   cd Pore2Chip
+   python3 -m build
+   python3 -m pip install pore2chip --no-index --find-links dist/
+
+Conda Environmental
+-------------------
+Creating a Conda environment:
+
+.. code-block:: bash
+
+   conda create -n pore2chip python=3.9
+   conda activate pore2chip
+   pip install pore2chip
+
+Docker Image
+------------
+Building a Docker Image with Jupyter Notebook:
+
+.. code-block:: bash
+
+   git clone https://github.com/EMSL-Computing/Pore2Chip.git 
+   cd Pore2Chip
+   docker build -t pore2chip
+   docker run -p 8888:8888 pore2chip
+
+
+.. note::
+
+   This project is under active development.

_sources/quickstart.rst.txt

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+
+Quickstart Guide
+=======================
+
+This guide is meant to showcase the basics of micromodel design and file exporting.
+
+Step 1: Importing Libraries
+---------------------------
+Before starting, we will import Pore2Chip as well as some support libraries for data visualization and modification.
+
+.. literalinclude:: ./examples/quickstart_example.py
+   :language: python
+   :start-after: # Step 1 Start
+   :end-before: # Step 1 End
+
+Step 2: Loading Desired Data
+----------------------------
+In order to extract data from XCT images, we need to load it into memory as a 3D array of pixel values. This can be done 
+all in one step using Pore2Chip's built-in function ``read_and_filter_list``. Other parameters such as cropping the image, 
+custom threshold values, and gray value masking can also be set in the function parameters.
+
+.. literalinclude:: ./examples/quickstart_example.py
+   :language: python
+   :start-after: # Step 2 Start
+   :end-before: # Step 2 End
+
+
+.. figure:: example_figures/quickstart_figure_1.png
+   :width: 416px
+   :height: 416px
+   :scale: 100 %
+   :alt: Filtered Image in 3D Image Stack
+
+Step 3: Pore Data Extraction
+----------------------------
+Now that the segmented data is loaded into memory, we will use the ``metrics`` module to extract the necessary information needed to 
+cunstruct the micromodel design. This extraction is based on pore network extraction via watershed segmentation and the SNOW 
+algorithm provided by `Porespy`.
+
+First, we will extract the pore and pore throat diameters:
+
+.. literalinclude:: ./examples/quickstart_example.py
+   :language: python
+   :start-after: # Step 3.1 Start
+   :end-before: # Step 3.1 End
+
+Next, we will extract the pore coordination numbers:
+
+.. literalinclude:: ./examples/quickstart_example.py
+   :language: python
+   :start-after: # Step 3.2 Start
+   :end-before: # Step 3.2 End
+
+The variables we extracted are arrays that contain all of the pore diameters, throat diameters, and coordination numbers for all the 
+extracted pores in the pore network. We can visualize the distribution of the data using `matplotlib`:
+
+.. literalinclude:: ./examples/quickstart_example.py
+   :language: python
+   :start-after: # Step 3.3 Start
+   :end-before: # Step 3.3 End
+
+.. figure:: example_figures/quickstart_figure_2.png
+   :width: 1165px
+   :height: 400px
+   :scale: 100 %
+   :alt: Histogram of Pore Data Values
+
+.. note::
+
+   Keep in mind that the data that is extracted is measured in the number of pixels in the segmented image. If you know the resolution 
+   size of the original XCT scan, you can scale the pixel values by the voxel size from the XCT metadata. Alternatively, you can keep note 
+   of the voxel/volume scale and adjust scaling on the final micromodel design.
+
+Step 4: Micromodel Network Generation
+-------------------------------------
+Once all the necessary data is extracted (pore diameters, throat diameters, and coordination numbers), we can move on to designing the micromodel. 
+Pore2Chip creates micromodels by constructing a 2D pore network (backed by `OpenPNM`) that has the overall pore properties that we extracted 
+in step 2. Then, the network is converted from a digital representation to a shape representation using `drawsvg`.
+
+To construct the 2D `OpenPNM` network, we will use the ``generate_network()`` function in the ``generate`` module:
+
+.. literalinclude:: ./examples/quickstart_example.py
+   :language: python
+   :start-after: # Step 4 Start
+   :end-before: # Step 4 End
+
+.. figure:: example_figures/quickstart_figure_3.png
+   :width: 630px
+   :height: 470px
+   :scale: 100 %
+   :alt: Visualization of OpenPNM network generated by Pore2Chip
+
+The code above generates a network that is a diamond lattice of 6 x 18 pores. The ``generate_network()`` function has parameters for the number of 
+pores on the X and Y axis, diameters, coordination numbers, and other optional arguments such as ``center_channel``, which was used above. The 
+argument or 3 designates a column of pores (3-wide) than the micromodel must connect from top to bottom, ensuring connectivity throughout the 
+entire network (more info on the generation algorithm in the modules page WIP).
+
+Step 5: Micromodel Exporting
+-------------------------------------
+Once we have our desired network, we will export it as a micromodel that can be used in simulations or fabrication for microfluidic experiments. This 
+is done with the ``export`` module. We will use ``network2svg()`` to export our micromodel as a scalable vector graphic:
+
+.. literalinclude:: ./examples/quickstart_example.py
+   :language: python
+   :start-after: # Step 5 Start
+   :end-before: # Step 5 End
+
+This is what the exported SVG based on the `OpenPNM` network looks like:
+
+.. figure:: example_figures/micromodel.svg
+   :scale: 100 %
+   :alt: Micromodel Exported by Pore2Chip
+
+This vector image can be used as is for fabrication, or imported into other software such as InkScape for further modification and exported as a 
+DWG file compatible with most CAD software. There is also a function in ``export`` called ``network2dxf()``, which can export a network to a DXF 
+file that most CAD software understands, but is currently still being refined (WIP).
+
+.. note::
+
+   This project is under active development.

_static/_sphinx_javascript_frameworks_compat.js

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+ * ~~~~~~~~~~
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+ *
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+ * xref RemovedInSphinx60Warning
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