Merge pull request #669 from Verdant-Evolution/remove-numba-checks

Remove numba checks
HEXRD · Jul 5, 2024 · b7a88d8 · b7a88d8
2 parents b32cf68 + 2323a5f
commit b7a88d8
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Showing 22 changed files with 1,748 additions and 1,848 deletions.
diff --git a/hexrd/constants.py b/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

diff --git a/hexrd/distortion/dexela_2923.py b/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)

diff --git a/hexrd/findorientations.py b/hexrd/findorientations.py
@@ -352,8 +352,6 @@ 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 +372,7 @@ 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(
@@ -617,7 +612,7 @@ 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 +889,7 @@ 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,

diff --git a/hexrd/fitting/peakfunctions.py b/hexrd/fitting/peakfunctions.py
@@ -26,9 +26,9 @@
 # ============================================================
 
 import numpy as np
+from numba import njit
 import copy
 from hexrd import constants
-from hexrd.utils.decorators import numba_njit_if_available
 from hexrd.constants import \
     c_erf, cnum_exp1exp, cden_exp1exp, c_coeff_exp1exp
 
@@ -56,7 +56,7 @@
 """
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def erfc(x):
     # save the sign of x
     sign = np.sign(x)
@@ -80,7 +80,7 @@ def erfc(x):
 """
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def exp1exp_under1(x):
     f = np.zeros(x.shape).astype(np.complex128)
     for i in range(6):
@@ -99,7 +99,7 @@ def exp1exp_under1(x):
 """
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def exp1exp_over1(x):
     num = np.zeros(x.shape).astype(np.complex128)
     den = np.zeros(x.shape).astype(np.complex128)
@@ -117,7 +117,7 @@ def exp1exp_over1(x):
     return (num/den)*(1./x)
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def exp1exp(x):
     mask = np.sign(x.real)*np.abs(x) > 1.
 
@@ -457,19 +457,19 @@ def split_pvoigt1d(p, x):
 """
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def _calc_alpha(alpha, x0):
     a0, a1 = alpha
     return (a0 + a1*np.tan(np.radians(0.5*x0)))
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def _calc_beta(beta, x0):
     b0, b1 = beta
     return b0 + b1*np.tan(np.radians(0.5*x0))
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def _mixing_factor_pv(fwhm_g, fwhm_l):
     """
     @AUTHOR:  Saransh Singh, Lawrence Livermore National Lab,
@@ -499,7 +499,7 @@ def _mixing_factor_pv(fwhm_g, fwhm_l):
     return eta, fwhm
 
 
-@numba_njit_if_available(nogil=True)
+@njit(nogil=True)
 def _gaussian_pink_beam(p, x):
     """
     @author Saransh Singh, Lawrence Livermore National Lab
@@ -544,7 +544,7 @@ def _gaussian_pink_beam(p, x):
     return g
 
 
-@numba_njit_if_available(nogil=True)
+@njit(nogil=True)
 def _lorentzian_pink_beam(p, x):
     """
     @author Saransh Singh, Lawrence Livermore National Lab
@@ -579,7 +579,7 @@ def _lorentzian_pink_beam(p, x):
     return y
 
 
-@numba_njit_if_available(nogil=True)
+@njit(nogil=True)
 def _pink_beam_dcs_no_bg(p, x):
     """
     @author Saransh Singh, Lawrence Livermore National Lab

diff --git a/hexrd/fitting/utils.py b/hexrd/fitting/utils.py
@@ -1,12 +1,12 @@
 import fnmatch
 
 import numpy as np
+from numba import njit
 
 from hexrd.constants import (
     c_erf, cnum_exp1exp, cden_exp1exp, c_coeff_exp1exp
 )
 from hexrd.matrixutil import uniqueVectors
-from hexrd.utils.decorators import numba_njit_if_available
 
 
 # =============================================================================
@@ -138,7 +138,7 @@ def _set_peak_center_bounds(params, window_range, min_sep=0.01):
 """
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def erfc(x):
     # save the sign of x
     sign = np.sign(x)
@@ -162,7 +162,7 @@ def erfc(x):
 """
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def exp1exp_under1(x):
     f = np.zeros(x.shape).astype(np.complex128)
     for i in range(6):
@@ -181,7 +181,7 @@ def exp1exp_under1(x):
 """
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def exp1exp_over1(x):
     num = np.zeros(x.shape).astype(np.complex128)
     den = np.zeros(x.shape).astype(np.complex128)
@@ -199,7 +199,7 @@ def exp1exp_over1(x):
     return (num/den)*(1./x)
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def exp1exp(x):
     mask = np.sign(x.real)*np.abs(x) > 1.
 
@@ -210,19 +210,19 @@ def exp1exp(x):
     return f
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def _calc_alpha(alpha, x0):
     a0, a1 = alpha
     return (a0 + a1*np.tan(np.radians(0.5*x0)))
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def _calc_beta(beta, x0):
     b0, b1 = beta
     return b0 + b1*np.tan(np.radians(0.5*x0))
 
 
-@numba_njit_if_available(cache=True, nogil=True)
+@njit(cache=True, nogil=True)
 def _mixing_factor_pv(fwhm_g, fwhm_l):
     """
     @AUTHOR:  Saransh Singh, Lawrence Livermore National Lab,
@@ -252,7 +252,7 @@ def _mixing_factor_pv(fwhm_g, fwhm_l):
     return eta, fwhm
 
 
-@numba_njit_if_available(nogil=True)
+@njit(nogil=True)
 def _gaussian_pink_beam(p, x):
     """
     @author Saransh Singh, Lawrence Livermore National Lab
@@ -298,7 +298,7 @@ def _gaussian_pink_beam(p, x):
     return g
 
 
-@numba_njit_if_available(nogil=True)
+@njit(nogil=True)
 def _lorentzian_pink_beam(p, x):
     """
     @author Saransh Singh, Lawrence Livermore National Lab