fix: add zref and density args to inversion (#24)

* fix: add zref and density args to inversion

* fix: removes references to density and zref

* fix: remove python 3.12 support, add test for 3.10

* chore: specify semantic release options

* chore: remove pypy from testing versions

.github/workflows/ci.yml

@@ -50,12 +50,9 @@ jobs:
       # run all of them to catch failures in different combinations.
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.11", "3.12"]
+        python-version: ["3.8", "3.10", "3.11"]
         runs-on: [ubuntu-latest, macos-latest, windows-latest]
 
-        include:
-          - python-version: pypy-3.9
-            runs-on: ubuntu-latest
     env:
       FORCE_COLOR: 3
       NUMBA_DISABLE_JIT: "1"

pyproject.toml

@@ -22,7 +22,6 @@ classifiers = [
   "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
-  "Programming Language :: Python :: 3.12",
   "Topic :: Scientific/Engineering",
   "Typing :: Typed",
 ]
@@ -214,3 +213,21 @@ build_command = """
     python -m pip install build
     python -m build .
 """
+commit_parser = "angular"
+
+[tool.semantic_release.commit_parser_options]
+allowed_tags = [
+    "build",    # Changes that affect the build system or external dependencies
+    "chore",    # Changes to the build process or auxiliary tools and libraries such as documentation generation
+    "ci",       # CI related changes
+    "docs",     # Documentation only changes
+    "feat",     # A new feature
+    "fix",      # A bug fix
+    "perf",     # A code change that improves performance
+    "style",    # Changes that do not affect the meaning of the code (white-space, formatting, missing semi-colons, etc)
+    "refactor", # A code change that neither fixes a bug nor adds a feature
+    "test",     # Adding missing or correcting existing tests
+]
+# including BREAKING CHANGE: in the commit message will trigger a major release
+minor_tags = ["feat"] # tags which result in minor releases
+patch_tags = ["fix", "perf"] # tags which result in patch releases

src/invert4geom/inversion.py

@@ -733,6 +733,8 @@ def run_inversion(
     input_grav: pd.DataFrame,
     input_grav_column: str,
     prism_layer: xr.Dataset,
+    density_contrast: float,
+    zref: float,
     max_iterations: int,
     l2_norm_tolerance: float = 0.2,
     delta_l2_norm_tolerance: float = 1.001,
@@ -765,6 +767,12 @@ def run_inversion(
         column name containing the gravity data *before* regional separation
     prism_layer : xr.Dataset
         starting prism layer
+    density_contrast : float
+        density contrast of the prisms layer, should be same value used to create the
+        starting model
+    zref : float
+        reference height of the prisms layer, should be same value used to create the
+        starting model
     max_iterations : int
         the maximum allowed iterations, inclusive and starting at 1
     l2_norm_tolerance : float, optional
@@ -812,15 +820,11 @@ def run_inversion(
     (
         prisms_df,
         prisms_ds,
-        density_contrast,
-        zref,
         prism_spacing,
         _,
     ) = utils.extract_prism_data(prism_layer)
 
-    logging.info("extracted zref is %s", zref)
     logging.info("extracted prism spacing is %s", prism_spacing)
-    logging.info("extracted density contrast is %s", density_contrast)
 
     # create empty jacobian matrix
     empty_jac: NDArray = np.empty(

src/invert4geom/utils.py

@@ -438,17 +438,13 @@ def extract_prism_data(
     pd.DataFrame,
     xr.Dataset,
     float,
-    float,
-    float,
     xr.DataArray,
 ]:
     """
     extract necessary info from starting prism layer, adds variables 'topo' and
     'starting_topo' to prism layer dataset (prisms_ds), converts it into dataframe
-    (prisms_df), gets the density contrast value (density) from the max density value in
-    prisms_df, gets the reference level (zref) from the min value of the prims tops,
-    gets the prism spacing (spacing) from prisms_ds, and creates a grid of the starting
-    topography (topo_grid) from the tops and bottoms of the prism layer.
+    (prisms_df), gets the prism spacing (spacing) from prisms_ds, and creates a grid of
+    the starting topography (topo_grid) from the tops and bottoms of the prism layer.
 
     Parameters
     ----------
@@ -457,32 +453,12 @@ def extract_prism_data(
 
     Returns
     -------
-    tuple
-        prisms_df, prisms_ds, density_contrast, zref, spacing, topo_grid)
+    tuple[pd.DataFrame, pd.Dataset, float, xr.DataArray]
+        prisms_df, prisms_ds, spacing, topo_grid
     """
 
     prisms_ds = copy.deepcopy(prism_layer.load())
 
-    # check that minimum elevation of prism tops is equal to max elevation of prism
-    # bottoms
-    # if not prisms_ds.top.to_numpy().min() == prisms_ds.bottom.to_numpy().max():
-    #     msg = "reference for prism layer is outside limits of tops and bottoms"
-    #     raise ValueError(msg)
-
-    # check prisms above reference have densities of opposite sign to prisms below
-    # try:
-    #     if not prisms_ds.density.to_numpy().max() == -prisms_ds.density.to_numpy().min(): # noqa: E501
-    #         msg = "densities should be represented as contrasts not absolutes."
-    #         raise ValueError(msg)
-    # # if not, they should at least be equal (if starting topo model is flat)
-    # except:
-    #     if not prisms_ds.density.to_numpy().max() == prisms_ds.density.to_numpy().min(): # noqa: E501
-    #         msg = "densities should be represented as contrasts not absolutes."
-    #         raise ValueError(msg)
-
-    density_contrast = prisms_ds.density.to_numpy().max()
-    zref = prisms_ds.top.to_numpy().min()
-
     # add starting topo to dataset
     topo_grid = xr.where(prisms_ds.density > 0, prisms_ds.top, prisms_ds.bottom)
     prisms_ds["topo"] = topo_grid
@@ -493,7 +469,7 @@ def extract_prism_data(
 
     spacing = get_spacing(prisms_df)
 
-    return prisms_df, prisms_ds, density_contrast, zref, spacing, topo_grid
+    return prisms_df, prisms_ds, spacing, topo_grid
 
 
 def get_spacing(prisms_df: pd.DataFrame) -> float:

tests/test_utils.py

@@ -507,9 +507,7 @@ def test_extract_prism_data():
     """
     prism_layer = dummy_prism_layer()
     results = utils.extract_prism_data(prism_layer)
-    prisms_df, prisms_ds, density_contrast, zref, spacing, topo_grid = results
-    assert density_contrast == 2670
-    assert zref == 0
+    prisms_df, prisms_ds, spacing, topo_grid = results
     assert spacing == 200
     expected = np.array([[0.0, 0.0, 0.0], [-30.0, -30.0, -30.0], [30.0, 30.0, 30.0]])
     npt.assert_array_equal(expected, topo_grid)