Merge pull request #22 from EMSL-Computing/joss-edits

More Joss edits

Author: aramyxt

README.md

@@ -3,6 +3,8 @@
 ## What is 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.
 
+Documentation Quick Link: https://emsl-computing.github.io/Pore2Chip/
+
 ### A workflow for model-data-experiment (ModEx) design:
 
 Below is a conceptual figure, workflow, and vision for this all-in-one Python tool. The working principle starts with XCT imaging files, which will be characterized for soil structure-property relationships and then transformed into a 2D rendering applicable to pore-scale micromodel building. Micromodel experiments will then be used with PFLOTRAN/OpenFOAM/PINNs process models to simulate flow and reactive transport for calibration and V&V.

pyproject.toml

@@ -29,6 +29,11 @@ dynamic = ["dependencies"]
 [tool.setuptools.dynamic]
 dependencies = {file = ["requirements.txt"]}
 
+[project.optional-dependencies]
+extras = [
+  "pypardiso",
+]
+
 [project.urls]
 Homepage = "https://www.emsl.pnnl.gov/science/instruments-resources/terraforms-pore2chip"
 Source = "https://github.com/EMSL-Computing/Pore2Chip"

tests/test_coordination.py

@@ -4,14 +4,14 @@
 import openpnm as op
 import porespy as ps
 from pathlib import Path
+import pytest
+import numpy as np
 
 # Uncomment and modify these lines if the pore2chip package is not in the PYTHONPATH
 #mod_path = Path("__file__").resolve().parents[2]
 #sys.path.append(os.path.abspath(mod_path))
 
 from pore2chip.coordination import coordination_nums_2D, coordination_nums_3D
-#from pore2chip.src.pore2chip.export import coordination_nums_3D, coordination_nums_2D
-
 
 def generate_network():
     """
@@ -22,64 +22,75 @@ def generate_network():
     """
     network = op.network.Cubic([3, 3])  # Create a 3x3 cubic network
     network.add_model_collection(op.models.collections.geometry.
-                                 spheres_and_cylinders)  # Add geometry models
+                                spheres_and_cylinders)  # Add geometry models
     network.regenerate_models()  # Generate network properties
     print(network)  # For debugging purposes
     return network
 
+class TestCoordination():
 
-def test_coordination_nums_3D(network):
-    """
-    Test coordination_nums_2D function given an OpenPNM network.
+    def test_coordination_nums_3D(self):
+        """
+        Test coordination_nums_2D function given an OpenPNM network.
     
-    Args:
-        network (dict): The network structure and coordination numbers (e.g., op.network.Cubic).
-
-    Returns:
-        coordination_numbers (ndarray): An array of coordination numbers for each pore in the network..
-    """
-    coordination_numbers = coordination_nums_3D(pn=network)
-    print(coordination_numbers)  # For debugging purposes
-    print(coordination_numbers.mean())  # For debugging purposes
-    print(coordination_numbers.shape)  # For debugging purposes
-    return coordination_numbers
-
-
-def test_coordination_nums_2D(img_list):
-    """
-    Test coordination_nums_2D function given a list of images.
+        Args:
+            network (dict): The network structure and coordination numbers (e.g., op.network.Cubic).
+
+        Returns:
+            coordination_numbers (ndarray): An array of coordination numbers for each pore in the network..
+        """
+        network = generate_network()
+        coordination_numbers = coordination_nums_3D(pn=network)
+        assert coordination_numbers.any() == np.array([2,3,2,3,4,3,2,3,2],dtype=int).any()
+        #print(coordination_numbers)  # For debugging purposes
+        #print(coordination_numbers.mean())  # For debugging purposes
+        #print(coordination_numbers.shape)  # For debugging purposes
+        #return coordination_numbers
+
+
+    def test_coordination_nums_2D(self):
+        """
+        Test coordination_nums_2D function given a list of images.
     
-    Args:
-        img_list (ndarray): 3D image list
-
-    Returns:
-        coordination_numbers (ndarray): An array of coordination numbers for each pore in the network..
-    """
-    coordination_numbers = coordination_nums_2D(img_list)
-    print(coordination_numbers)
-    print(coordination_numbers.mean())
-    print(coordination_numbers.shape)
-    return coordination_numbers
-
-
-def main():
-    """
-    Main function to generate a network, test coordination number computations on 3D networks
-    and 2D image slices.
-    """
-
-    # Generate network
-    network = generate_network()
-
-    # Test coordination 3D on generated network
-    test_coordination_nums_3D(network)
-
-    # Generate a 3D image using PoreSpy with specified dimensions and random seed
-    blobs = ps.generators.blobs([5, 100, 100], seed=1)
-
-    # Test coordination 2D on image list
-    test_coordination_nums_2D(blobs)
-
-
-if __name__ == "__main__":
-    main()
+        Args:
+            img_list (ndarray): 3D image list
+
+        Returns:
+            coordination_numbers (ndarray): An array of coordination numbers for each pore in the network..
+        """
+        blobs = ps.generators.blobs([1, 100, 100], seed=1)
+        coordination_numbers = coordination_nums_2D(blobs)
+        assert coordination_numbers.any() == np.array(
+            [3, 3, 1, 0, 3, 1, 0, 1, 1, 3, 2, 2, 3, 3, 1, 2, 3, 2, 2, 1, 2, 1, 3, 1,      
+             2, 2, 5, 2, 0, 0, 1, 3, 1, 2, 1, 0, 1, 3, 4, 0, 3, 3, 0, 1, 2, 2, 3, 3,
+             2, 2, 2, 2, 3, 3, 0, 4, 1, 2, 4, 2, 1, 2, 3, 3, 2, 3, 5, 4, 1, 1, 2, 1,
+             2, 1, 2, 3, 3, 2, 2, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
+             1, 1, 1, 1, 1, 1, 1, 1, 1,]
+            ,dtype=float).any()
+        #print(coordination_numbers)
+        #print(coordination_numbers.mean())
+        #print(coordination_numbers.shape)
+        #return coordination_numbers
+
+
+#def main():
+    #"""
+    #Main function to generate a network, test coordination number computations on 3D networks
+    #and 2D image slices.
+    #"""
+
+    ## Generate network
+    #network = generate_network()
+
+    ## Test coordination 3D on generated network
+    #test_coordination_nums_3D(network)
+
+    ## Generate a 3D image using PoreSpy with specified dimensions and random seed
+    #blobs = ps.generators.blobs([5, 100, 100], seed=1)
+
+    ## Test coordination 2D on image list
+    #test_coordination_nums_2D(blobs)
+
+
+#if __name__ == "__main__":
+    #main()

tests/test_generate.py

@@ -25,14 +25,14 @@ def create_random_properties():
             - coordination_nums (np.ndarray): Array of random coordination numbers (converted to integers).
     """
     # Generating random pore diameters within specified range
-    pore_diameters = np.random.uniform(low=1.0, high=10.0, size=20)
+    pore_diameters = np.random.uniform(low=1.0, high=10.0, size=20, seed=1)
 
     # Generating random throat diameters within specified range
-    throat_diameters = np.random.uniform(low=0.5, high=6.0, size=20)
+    throat_diameters = np.random.uniform(low=0.5, high=6.0, size=20, seed=1)
 
     # Generating random coordination numbers within specified range and converting to integers
     coordination_nums = np.random.uniform(low=0, high=8,
-                                          size=20).astype(np.int64)
+                                          size=20, seed=1).astype(np.int64)
     return pore_diameters, throat_diameters, coordination_nums