Improve test coverage

.coveragerc

@@ -0,0 +1,4 @@
+[run]
+branch = True
+source = pymuonsuite
+omit = pymuonsuite/test/*

.github/workflows/python-package-tests.yml

@@ -54,6 +54,9 @@ jobs:
         if [ -f requirements-dev.txt ]; then pip install -r requirements-dev.txt; fi
       shell: bash # Windows runners have Git Bash installed so this should work on all runners
     - name: Install package
-      run: pip install .
+      run: pip install -e .
     - name: Test with pytest
-      run: pytest
+      run: pytest --cov pymuonsuite --cov-report xml
+    - name: Upload to Codecov
+      if: matrix.python-version == '3.10' && matrix.os == 'ubuntu-latest'
+      uses: codecov/codecov-action@v3

.gitignore

@@ -43,6 +43,7 @@ htmlcov/
 .cache
 nosetests.xml
 coverage.xml
+coverage
 *.cover
 .hypothesis/
 .pytest_cache/

README.md

@@ -1,3 +1,6 @@
+[![Build Status](https://github.com/muon-spectroscopy-computational-project/pymuon-suite/actions/workflows/python-package-tests.yml/badge.svg?branch=main)](https://github.com/muon-spectroscopy-computational-project/pymuon-suite/actions/workflows/python-package-tests.yml)
+[![Codecov](https://codecov.io/gh/muon-spectroscopy-computational-project/pymuon-suite/branch/main/graph/badge.svg)](https://codecov.io/gh/muon-spectroscopy-computational-project/pymuon-suite)
+
 # pymuon-suite
 Collection of scripts and utilities for muon spectroscopy.
 

pymuonsuite/calculate/hfine.py

@@ -59,13 +59,13 @@ def compute_hfine_tensor(
     N = len(points)
 
     magmoms = np.array(spins).astype(float)
-    species = np.array(species).astype("S2")
+    species = np.array(species)
     if species.shape == ():
         species = np.repeat(species[None], N)
     for i, s in enumerate(species):
-        if s == b"e":
+        if s == "e":
             mm = 2 * _bohrmag
-        elif s == b"mu":
+        elif s == "mu":
             mm = mu_cnst.m_gamma * cnst.hbar
         else:
             mm = _get_isotope_data(s, "gamma")[0] * cnst.hbar
@@ -140,7 +140,7 @@ def compute_hfine_mullpop(
     |                        magnetization). Default is True
     |   fermi (bool):        if True, include a Fermi contact term
     |                        (magnetization at site i). Default is True
-    |   fermi_neigh (bool):  if True, include an empyrical neighbour
+    |   fermi_neigh (bool):  if True, include an empirical neighbour
     |                        correction for the Fermi contact term.
     |                        Default is False
 

pymuonsuite/calculate/uep/charged.py

@@ -241,6 +241,18 @@ def has_spin(self):
     def thomasFermiE(self):
         return self._thomasFermiE
 
+    def _validate_points(self, points: object) -> np.ndarray:
+        """Ensure that points has at least two dimensions.
+
+        Arguments:
+            points {object} -- List of points to be validated.
+
+        Returns:
+            np.ndarray -- Array of points with at least two dimensions
+        """
+        points = np.array(points)
+        return points[None, :] if len(points.shape) == 1 else points
+
     def rho(self, p, max_process_p=20):
         """Charge density
 
@@ -262,9 +274,7 @@ def rho(self, p, max_process_p=20):
         """
 
         # Return charge density at a point or list of points
-        p = np.array(p)
-        if len(p.shape) == 1:
-            p = p[None, :]  # Make it into a list of points
+        p = self._validate_points(p)
 
         # The point list is sliced for convenience, to avoid taking too much
         # memory
@@ -308,9 +318,7 @@ def V(self, p, max_process_p=20):
         """
 
         # Return potential at a point or list of points
-        p = np.array(p)
-        if len(p.shape) == 1:
-            p = p[None, :]  # Make it into a list of points
+        p = self._validate_points(p)
 
         # The point list is sliced for convenience, to avoid taking too much
         # memory
@@ -356,9 +364,7 @@ def dV(self, p, max_process_p=20):
         """
 
         # Return potential gradient at a point or list of points
-        p = np.array(p)
-        if len(p.shape) == 1:
-            p = p[None, :]  # Make it into a list of points
+        p = self._validate_points(p)
 
         # The point list is sliced for convenience, to avoid taking too much
         # memory
@@ -409,10 +415,7 @@ def d2V(self, p, max_process_p=20):
         """
 
         # Return potential Hessian  at a point or a list of points
-
-        p = np.array(p)
-        if len(p.shape) == 1:
-            p = p[None, :]  # Make it into a list of points
+        p = self._validate_points(p)
 
         # The point list is sliced for convenience, to avoid taking too much
         # memory
@@ -481,9 +484,7 @@ def Hfine(self, p, contact=False, max_process_p=20):
             )
 
         # Return hyperfine tensors at a point or a list of points
-        p = np.array(p)
-        if len(p.shape) == 1:
-            p = p[None, :]  # Make it into a list of points
+        p = self._validate_points(p)
 
         # The point list is sliced for convenience, to avoid taking too much
         # memory

pymuonsuite/io/output.py

@@ -16,27 +16,6 @@
 from soprano.utils import silence_stdio
 
 
-def write_tensors(tensors, filename, symbols):
-    """
-    Write out a set of 2 dimensional tensors for every atom in a system.
-
-    | Args:
-    |   tensors(Numpy float array, shape: (Atoms, :, :): A list of tensors
-    |       for each atom.
-    |   filename(str): Filename for file.
-    |   symbols(str array): List containing chemical symbol of each atom in
-    |       system.
-    |
-    | Returns: Nothing
-    """
-    tensfile = open(filename, "w")
-    for i in range(np.size(tensors, 0)):
-        tensfile.write("{0} {1}\n".format(symbols[i], i))
-        tensfile.write(
-            "\n".join(["\t".join([str(x) for x in ln]) for ln in tensors[i]]) + "\n"
-        )
-
-
 def write_cluster_report(args, params, clusters):
 
     if params["clustering_method"] == "hier":

pymuonsuite/muairss.py

@@ -230,14 +230,12 @@ def muairss_batch_io(args, global_params, save=False):
 
     for path in structure_files:
         name = parse_structure_name(path)
-        parameter_file = os.path.join(structures_path, "{}.yaml".format(name))
-        if not os.path.isfile(parameter_file):
-            parameter_file = None
         with silence_stdio():
             struct = io.read(path)
         params = dict(global_params)  # Copy
         params["name"] = name
-        if parameter_file is not None:
+        parameter_file = os.path.join(structures_path, "{}.yaml".format(name))
+        if os.path.isfile(parameter_file):
             params = load_input_file(parameter_file, MuAirssSchema, merge=params)
         params["out_folder"] = params["name"]