Merge branch 'master' into lint-tomoutil

.github/workflows/container_build.sh

@@ -1,6 +1,11 @@
 #!/usr/bin/env bash
 cd /github/workspace/
 
+# Use archive mirror for CentOS 7 until we are ready to migrate to CentOS 8
+sed -i -e 's/mirrorlist/#mirrorlist/g' \
+	-e 's|#baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' \
+	/etc/yum.repos.d/CentOS-*
+
 # Install dependencies
 yum install -y wget git centos-release-scl ca-certificates
 

.github/workflows/test.yml

@@ -61,8 +61,9 @@ jobs:
       if: ${{ matrix.config.os == 'macos-latest'}}
 
     - name: Install HEXRD
+      # Install in editable mode for codecov
       run: |
-          pip install .
+          pip install -e .
       working-directory: hexrd
 
     - name: Install requirements-dev.txt
@@ -75,4 +76,22 @@ jobs:
         HEXRD_EXAMPLE_REPO_PATH: ${{ github.workspace }}/examples
       run: |
           pytest -s tests/
+      if: ${{ matrix.config.os != 'ubuntu-latest'}}
       working-directory: hexrd
+
+    - name: Run tests with codecov
+      env:
+        HEXRD_EXAMPLE_REPO_PATH: ${{ github.workspace }}/examples
+      run: |
+          pytest -s --cov hexrd --cov-report xml:coverage.xml tests/
+      if: ${{ matrix.config.os == 'ubuntu-latest'}}
+      working-directory: hexrd
+
+    - name: Upload coverage to Codecov
+      uses: codecov/codecov-action@v3
+      with:
+        token: ${{ secrets.CODECOV_TOKEN }}
+        file: coverage.xml
+        working-directory: hexrd
+      if: ${{ matrix.config.os == 'ubuntu-latest'}}
+

README.md

@@ -1,4 +1,5 @@
-[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8033939.svg)](https://doi.org/10.5281/zenodo.8033939) ![conda-package](https://github.com/HEXRD/hexrd/workflows/conda-package/badge.svg) ![test](https://github.com/HEXRD/hexrd/workflows/test/badge.svg) ![latest version](https://anaconda.org/hexrd/hexrd/badges/version.svg) ![last updated](https://anaconda.org/hexrd/hexrd/badges/latest_release_relative_date.svg) ![downloads](https://anaconda.org/hexrd/hexrd/badges/downloads.svg)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8033939.svg)](https://doi.org/10.5281/zenodo.8033939) ![conda-package](https://github.com/HEXRD/hexrd/workflows/conda-package/badge.svg) ![test](https://github.com/HEXRD/hexrd/workflows/test/badge.svg) [![codecov](https://codecov.io/gh/Hexrd/hexrd/graph/badge.svg)](https://codecov.io/gh/Hexrd/hexrd) ![latest version](https://anaconda.org/hexrd/hexrd/badges/version.svg) ![last updated](https://anaconda.org/hexrd/hexrd/badges/latest_release_relative_date.svg) ![downloads](https://anaconda.org/hexrd/hexrd/badges/downloads.svg)
+
 # HEXRD
 The HEXRD project is developing a cross-platform, open-source library for the general analysis of X-ray diffraction data.  This includes powder diffraction, Laue diffraction, and High Energy Diffraction Microscopy (_a.k.a._ 3DXRD, multi-grain rotation method) modalities.  At its core, HEXRD provides an abstraction of a generic diffraction instrument with support for multiple detectors.  This includes optimized transforms from the direct and reciprocal crystal lattices to the local detector coordinates, harnesses for interpolating image data into scattering angle coordinates, and sophisticated calibration routines.
 

hexrd/cli/fit_grains.py

@@ -335,7 +335,6 @@ def execute(args, parser):
         gid_list = None
         if args.grains is not None:
             gid_list = [int(i) for i in args.grains.split(',')]
-            pass
 
         fit_results = fit_grains(
             cfg,

hexrd/constants.py

@@ -251,24 +251,13 @@ def _readenv(name, ctor, default):
             del warnings
             return default
 
-
-# 0 = do NOT use numba
-# 1 = use numba (default)
-USE_NUMBA = _readenv("HEXRD_USE_NUMBA", int, 1)
-if USE_NUMBA:
-    try:
-        import numba
-    except ImportError:
-        print("*** Numba not available, processing may run slower ***")
-        USE_NUMBA = False
-
 del _readenv
 
 
 def set_numba_cache():
     """Set the numba cache only if the following are true:
 
-    1. We are using numba
+    1. We are using numba - assumed true now
     2. We are on Windows
     3. We don't have write access to this file
     4. The NUMBA_CACHE_DIR environment variable is not defined
@@ -277,8 +266,6 @@ def set_numba_cache():
     directory where it doesn't have permission, and cause the application to
     freeze. Avoid that by setting the cache dir ourselves.
     """
-    if not USE_NUMBA:
-        return
 
     if os.name != 'nt':
         return

hexrd/deprecation.py

@@ -0,0 +1,35 @@
+import os
+import functools
+
+
+class DeprecatedFunctionError(Exception):
+    """Custom exception for deprecated functions."""
+    pass
+
+
+def deprecated(new_func: str = None, removal_date: str = None):
+    """
+    Decorator to mark functions as deprecated. Raises an error if
+    the 'ACK_DEPRECATED' environment variable is not set. Alerts the
+    user to the replacement function if provided.
+    """
+
+    def decorator(func):
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            if new_func is not None:
+                print(
+                    f"Warning: {func.__name__} is deprecated and is marked for"
+                    f" removal. Please use {new_func} instead."
+                    f" Removal date: {removal_date}"
+                )
+            if os.getenv('ACK_DEPRECATED') != 'true':
+                raise DeprecatedFunctionError(
+                    f"Function {func.__name__} is deprecated. Set environment "
+                    "variable 'ACK_DEPRECATED' to 'true' to acknowledge."
+                )
+            return func(*args, **kwargs)
+
+        return wrapper
+
+    return decorator

hexrd/distortion/dexela_2923.py

@@ -5,11 +5,9 @@
 @author: Joel V. Bernier
 """
 import numpy as np
+import numba
 
 from hexrd import constants
-from hexrd.constants import USE_NUMBA
-if USE_NUMBA:
-    import numba
 
 from .distortionabc import DistortionABC
 from .registry import _RegisterDistortionClass
@@ -69,71 +67,44 @@ def _find_quadrant(xy_in):
     return quad_label
 
 
-if USE_NUMBA:
-    @numba.njit(nogil=True, cache=True)
-    def _dexela_2923_distortion(out_, in_, params):
-        for el in range(len(in_)):
-            xi, yi = in_[el, :]
-            if xi < 0.:
-                if yi < 0.:
-                    # 3rd quadrant
-                    out_[el, :] = in_[el, :] + params[4:6]
-                else:
-                    # 2nd quadrant
-                    out_[el, :] = in_[el, :] + params[2:4]
+@numba.njit(nogil=True, cache=True)
+def _dexela_2923_distortion(out_, in_, params):
+    for el in range(len(in_)):
+        xi, yi = in_[el, :]
+        if xi < 0.:
+            if yi < 0.:
+                # 3rd quadrant
+                out_[el, :] = in_[el, :] + params[4:6]
             else:
-                if yi < 0.:
-                    # 4th quadrant
-                    out_[el, :] = in_[el, :] + params[6:8]
-                else:
-                    # 1st quadrant
-                    out_[el, :] = in_[el, :] + params[0:2]
-
-    @numba.njit(nogil=True, cache=True)
-    def _dexela_2923_inverse_distortion(out_, in_, params):
-        for el in range(len(in_)):
-            xi, yi = in_[el, :]
-            if xi < 0.:
-                if yi < 0.:
-                    # 3rd quadrant
-                    out_[el, :] = in_[el, :] - params[4:6]
-                else:
-                    # 2nd quadrant
-                    out_[el, :] = in_[el, :] - params[2:4]
+                # 2nd quadrant
+                out_[el, :] = in_[el, :] + params[2:4]
+        else:
+            if yi < 0.:
+                # 4th quadrant
+                out_[el, :] = in_[el, :] + params[6:8]
             else:
-                if yi < 0.:
-                    # 4th quadrant
-                    out_[el, :] = in_[el, :] - params[6:8]
-                else:
-                    # 1st quadrant
-                    out_[el, :] = in_[el, :] - params[0:2]
-else:
-    def _dexela_2923_distortion(out_, in_, params):
-        # find quadrant
-        ql = _find_quadrant(in_)
-        ql1 = ql == 1
-        ql2 = ql == 2
-        ql3 = ql == 3
-        ql4 = ql == 4
-        out_[ql1, :] = in_[ql1] + np.tile(params[0:2], (sum(ql1), 1))
-        out_[ql2, :] = in_[ql2] + np.tile(params[2:4], (sum(ql2), 1))
-        out_[ql3, :] = in_[ql3] + np.tile(params[4:6], (sum(ql3), 1))
-        out_[ql4, :] = in_[ql4] + np.tile(params[6:8], (sum(ql4), 1))
-        return
-
-    def _dexela_2923_inverse_distortion(out_, in_, params):
-        ql = _find_quadrant(in_)
-        ql1 = ql == 1
-        ql2 = ql == 2
-        ql3 = ql == 3
-        ql4 = ql == 4
-        out_[ql1, :] = in_[ql1] - np.tile(params[0:2], (sum(ql1), 1))
-        out_[ql2, :] = in_[ql2] - np.tile(params[2:4], (sum(ql2), 1))
-        out_[ql3, :] = in_[ql3] - np.tile(params[4:6], (sum(ql3), 1))
-        out_[ql4, :] = in_[ql4] - np.tile(params[6:8], (sum(ql4), 1))
-        return
-
-
+                # 1st quadrant
+                out_[el, :] = in_[el, :] + params[0:2]
+
+
+@numba.njit(nogil=True, cache=True)
+def _dexela_2923_inverse_distortion(out_, in_, params):
+    for el in range(len(in_)):
+        xi, yi = in_[el, :]
+        if xi < 0.:
+            if yi < 0.:
+                # 3rd quadrant
+                out_[el, :] = in_[el, :] - params[4:6]
+            else:
+                # 2nd quadrant
+                out_[el, :] = in_[el, :] - params[2:4]
+        else:
+            if yi < 0.:
+                # 4th quadrant
+                out_[el, :] = in_[el, :] - params[6:8]
+            else:
+                # 1st quadrant
+                out_[el, :] = in_[el, :] - params[0:2]
 
 def test_disortion():
     pts = np.random.randn(16, 2)

hexrd/distortion/distortionabc.py

@@ -8,9 +8,9 @@ class DistortionABC(metaclass=abc.ABCMeta):
     @abc.abstractmethod
     def apply(self, xy_in):
         """Apply distortion mapping"""
-        pass
+        raise NotImplementedError
 
     @abc.abstractmethod
     def apply_inverse(self, xy_in):
         """Apply inverse distortion mapping"""
-        pass
+        raise NotImplementedError

hexrd/distortion/registry.py

@@ -20,5 +20,3 @@ def register(cls, acls):
         """Register adapter class"""
         if acls.__name__ != 'DistortionBase':
             cls.distortion_registry[acls.maptype] = acls
-
-    pass  # end class

hexrd/findorientations.py

@@ -131,9 +131,6 @@ def generate_orientation_fibers(cfg, eta_ome):
                 ome_c = eta_ome.omeEdges[0] + (0.5 + coms[i][ispot][0])*del_ome
                 eta_c = eta_ome.etaEdges[0] + (0.5 + coms[i][ispot][1])*del_eta
                 input_p.append(np.hstack([this_hkl, this_tth, eta_c, ome_c]))
-                pass
-            pass
-        pass
 
     # do the mapping
     start = timeit.default_timer()
@@ -155,7 +152,6 @@ def generate_orientation_fibers(cfg, eta_ome):
                     discretefiber_reduced, input_p, chunksize=chunksize
                 ), total=ntotal
             ):
-            pass
         print(_.shape)
         '''
         pool.close()
@@ -352,8 +348,6 @@ def quat_distance(x, y):
             qbar[:, i] = rot.quatAverageCluster(
                 qfib_r[:, cl == i + 1], qsym
             ).flatten()
-            pass
-        pass
 
     if algorithm in ('dbscan', 'ort-dbscan') and qbar.size/4 > 1:
         logger.info("\tchecking for duplicate orientations...")
@@ -374,10 +368,7 @@ def quat_distance(x, y):
                 tmp[:, i] = rot.quatAverageCluster(
                     qbar[:, cl == i + 1].reshape(4, npts), qsym
                 ).flatten()
-                pass
             qbar = tmp
-            pass
-        pass
 
     logger.info("clustering took %f seconds", timeit.default_timer() - start)
     logger.info(
@@ -592,7 +583,7 @@ def generate_eta_ome_maps(cfg, hkls=None, save=True):
             map_fname
         )
 
-        eta_ome.save(fn)
+        eta_ome.save_eta_ome_maps(fn)
 
         logger.info('saved eta/ome orientation maps to "%s"', fn)
 
@@ -617,7 +608,7 @@ def _filter_eta_ome_maps(eta_ome, filter_stdev=False):
 
     """
     gl_filter = ndimage.filters.gaussian_laplace
-    for i, pf in enumerate(eta_ome.dataStore):
+    for pf in eta_ome.dataStore:
         # first compoute row-wise median over omega channel
         ome_median = np.tile(np.nanmedian(pf, axis=0), (len(pf), 1))
 
@@ -894,7 +885,7 @@ def find_orientations(cfg,
     logger.info("\tmean reflections per grain: %d", mean_rpg)
     logger.info("\tneighborhood size: %d", min_samples)
 
-    qbar, cl = run_cluster(
+    qbar, _ = run_cluster(
         completeness, qfib, plane_data.getQSym(), cfg,
         min_samples=min_samples,
         compl_thresh=compl_thresh,

hexrd/fitgrains.py

@@ -184,8 +184,7 @@ def fit_grain_FF_reduced(grain_id):
             culled_results[det_key] = [presults[i] for i in np.where(idx)[0]]
             num_refl_tot += len(valid_refl_ids)
             num_refl_valid += sum(valid_refl_ids)
-
-            pass  # now we have culled data
+            # now we have culled data
 
         # CAVEAT: completeness from pullspots only; incl saturated and overlaps
         # <JVB 2015-12-15>
@@ -220,8 +219,6 @@ def fit_grain_FF_reduced(grain_id):
                     plane_data.latVecOps['B'], plane_data.wavelength,
                     ome_period,
                     simOnly=False, return_value_flag=2)
-            pass  # end conditional on fit
-        pass  # end tolerance looping
 
     if refit is not None:
         # first get calculated x, y, ome from previous solution
@@ -279,7 +276,6 @@ def fit_grain_FF_reduced(grain_id):
             ]
 
             num_refl_valid += sum(idx_new)
-            pass
 
         # only execute fit if left with enough reflections
         if num_refl_valid > 12:
@@ -297,8 +293,6 @@ def fit_grain_FF_reduced(grain_id):
                     plane_data.latVecOps['B'], plane_data.wavelength,
                     ome_period,
                     simOnly=False, return_value_flag=2)
-            pass
-        pass  # close refit conditional
     return grain_id, completeness, chisq, grain_params