Merge pull request #921 from PMEAL/maint/pyproject.toml

- Migrated from setup.py to pyproject.toml #maint
- Migrated from flat layout to the PyPA recommended src layout #maint

.gitignore

@@ -154,10 +154,10 @@ cython_debug/
 *.pyc
 *.nblink
 
+# OpenPNM
+*.mphtxt
 docs/_build/
 docs/**/generated
 docs/examples
-
 examples/networks/*.vt*
-
 .vscode/

pyproject.toml

@@ -0,0 +1,84 @@
+[project]
+name = "porespy"
+dynamic = ["version"]
+description = "A set of tools for analyzing 3D images of porous materials"
+authors = [{ name = "PoreSpy Team", email = "jgostick@gmail.com" }]
+maintainers = [
+    { name = "Jeff Gostick", email = "jgostick@gmail.com" },
+    { name = "Amin Sadeghi", email = "amin.sadeghi@live.com" },
+]
+license = "MIT"
+keywords = [
+    "voxel images",
+    "porous materials",
+    "image analysis",
+    "direct numerical simulation",
+]
+classifiers = [
+    "Development Status :: 5 - Production/Stable",
+    "License :: OSI Approved :: MIT License",
+    "Operating System :: OS Independent",
+    "Programming Language :: Python",
+    "Programming Language :: Python :: 3",
+    "Topic :: Scientific/Engineering",
+    "Topic :: Scientific/Engineering :: Physics",
+]
+dependencies = [
+    "dask",
+    "deprecated",
+    "edt",
+    "matplotlib",
+    "numba",
+    "numpy",
+    "openpnm",
+    "pandas",
+    "psutil",
+    "rich",
+    "scikit-image",
+    "scipy",
+    "tqdm",
+    "pywavelets",
+    "nanomesh",
+    "setuptools",
+]
+readme = "README.md"
+requires-python = ">= 3.8"
+
+[project.urls]
+Homepage = "https://porespy.org"
+Repository = "https://github.com/PMEAL/porespy"
+"Bug Tracker" = "https://github.com/PMEAL/porespy/issues"
+Documentation = "https://porespy.org/"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.rye]
+managed = true
+dev-dependencies = [
+    "pytest",
+    "hatch",
+    "numpy-stl",
+    "pyevtk",
+    "trimesh",
+    "ipykernel",
+    "pypardiso",
+]
+
+[tool.hatch.metadata]
+allow-direct-references = true
+
+[tool.hatch.version]
+path = "src/porespy/__version__.py"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src/porespy"]
+
+[tool.pytest.ini_options]
+minversion = "6.0"
+addopts = "-ra -v"
+testpaths = ["test"]
+
+[tool.ruff]
+line-length = 92

porespy/beta/_dns_tools.py → src/porespy/beta/_dns_tools.py

@@ -28,7 +28,7 @@ def flux(c, axis, k=None):
     """
     k = np.ones_like(c) if k is None else np.array(k)
     # Compute the gradient of the concentration field using forward diff
-    dcdX = convolve1d(c, weights=np.array([-1, 1]), axis=axis)
+    dcdX = convolve1d(c, weights=np.array([-1.0, 1.0]), axis=axis)
     # dcdX @ outlet is incorrect due to forward diff -> use backward
     _fix_gradient_outlet(dcdX, axis)
     # Compute the conductivity at the faces using resistors in series
@@ -83,10 +83,11 @@ def _fix_gradient_outlet(J, axis):
     J_outlet[:] = J_penultimate_layer
 
 
-def _slice_view(a, i, axis):
+def _slice_view(a, idx, axis):
     """Returns a slice view of the array along the given axis."""
+    # Example: _slice_view(a, i=5, axis=1) -> a[:, 5, :]
     sl = [slice(None)] * a.ndim
-    sl[axis] = i
+    sl[axis] = idx
     return a[tuple(sl)]
 
 

porespy/io/_funcs.py → src/porespy/io/_funcs.py

@@ -1,13 +1,15 @@
 import os
 import subprocess
+
 import numpy as np
 import scipy.ndimage as nd
 import skimage.measure as ms
-from porespy.tools import sanitize_filename
-from porespy.networks import generate_voxel_image
-from porespy.filters import reduce_peaks
-from skimage.morphology import ball
 from edt import edt
+from skimage.morphology import ball
+
+from porespy.filters import reduce_peaks
+from porespy.networks import generate_voxel_image
+from porespy.tools import sanitize_filename
 
 
 def dict_to_vtk(data, filename, voxel_size=1, origin=(0, 0, 0)):
@@ -289,7 +291,7 @@ def _save_stl(im, vs, filename):
         from stl import mesh
     except ModuleNotFoundError:
         msg = 'numpy-stl can be installed with pip install numpy-stl'
-        ModuleNotFoundError(msg)
+        raise ModuleNotFoundError(msg)
     im = np.pad(im, pad_width=10, mode="constant", constant_values=True)
     vertices, faces, norms, values = ms.marching_cubes(im)
     vertices *= vs

porespy/simulations/_dns.py → src/porespy/simulations/_dns.py

@@ -1,16 +1,17 @@
 import logging
+
 import numpy as np
 import openpnm as op
+
 from porespy.filters import trim_nonpercolating_paths
-from porespy.tools import Results
 from porespy.generators import faces
-
+from porespy.tools import Results
 
 logger = logging.getLogger(__name__)
 ws = op.Workspace()
 
 
-__all__ = ['tortuosity_fd']
+__all__ = ["tortuosity_fd"]
 
 
 def tortuosity_fd(im, axis, solver=None):
@@ -56,7 +57,7 @@ def tortuosity_fd(im, axis, solver=None):
     """
     if axis > (im.ndim - 1):
         raise Exception(f"'axis' must be <= {im.ndim}")
-    openpnm_v3 = op.__version__.startswith('3')
+    openpnm_v3 = op.__version__.startswith("3")
 
     # Obtain original porosity
     eps0 = im.sum(dtype=np.int64) / im.size
@@ -68,17 +69,17 @@ def tortuosity_fd(im, axis, solver=None):
     # Check if porosity is changed after trimmimg floating pores
     eps = im.sum(dtype=np.int64) / im.size
     if not eps:
-        raise Exception('No pores remain after trimming floating pores')
+        raise Exception("No pores remain after trimming floating pores")
     if eps < eps0:  # pragma: no cover
-        logger.warning('Found non-percolating regions, were filled to percolate')
+        logger.warning("Found non-percolating regions, were filled to percolate")
 
     # Generate a Cubic network to be used as an orthogonal grid
     net = op.network.CubicTemplate(template=im, spacing=1.0)
     if openpnm_v3:
         phase = op.phase.Phase(network=net)
     else:
         phase = op.phases.GenericPhase(network=net)
-    phase['throat.diffusive_conductance'] = 1.0
+    phase["throat.diffusive_conductance"] = 1.0
     # Run Fickian Diffusion on the image
     fd = op.algorithms.FickianDiffusion(network=net, phase=phase)
     # Choose axis of concentration gradient
@@ -94,9 +95,9 @@ def tortuosity_fd(im, axis, solver=None):
         fd._update_A_and_b()
         fd.x, info = solver.solve(fd.A.tocsr(), fd.b)
         if info:
-            raise Exception(f'Solver failed to converge, exit code: {info}')
+            raise Exception(f"Solver failed to converge, exit code: {info}")
     else:
-        fd.settings.update({'solver_family': 'scipy', 'solver_type': 'cg'})
+        fd.settings.update({"solver_family": "scipy", "solver_type": "cg"})
         fd.run()
 
     # Calculate molar flow rate, effective diffusivity and tortuosity
@@ -108,7 +109,7 @@ def tortuosity_fd(im, axis, solver=None):
     L = im.shape[axis]
     A = np.prod(im.shape) / L
     # L-1 because BCs are put inside the domain, see issue #495
-    Deff = r_in * (L-1)/A / dC
+    Deff = r_in * (L - 1) / A / dC
     tau = eps / Deff
 
     # Attach useful parameters to Results object
@@ -119,8 +120,9 @@ def tortuosity_fd(im, axis, solver=None):
     result.original_porosity = eps0
     result.effective_porosity = eps
     conc = np.zeros(im.size, dtype=float)
-    conc[net['pore.template_indices']] = fd['pore.concentration']
+    conc[net["pore.template_indices"]] = fd["pore.concentration"]
     result.concentration = conc.reshape(im.shape)
+    result.sys = fd.A, fd.b
 
     # Free memory
     ws.close_project(net.project)