renamed numba defaults class and moved it to top directory

src/pygama/math/functions/crystal_ball.py

@@ -9,8 +9,8 @@
 from math import erf
 
 from pygama.math.functions.pygama_continuous import pygama_continuous 
-from ..utils import numba_math_defaults_kwargs as nb_kwargs
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults_kwargs as nb_kwargs
+from pygama.utils import numba_math_defaults as nb_defaults
 
 
 

src/pygama/math/functions/exgauss.py

@@ -13,8 +13,8 @@
 from pygama.math.functions.error_function import nb_erf, nb_erfc
 from pygama.math.functions.gauss import nb_gauss_cdf, nb_gauss_pdf
 
-from ..utils import numba_math_defaults_kwargs as nb_kwargs
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults_kwargs as nb_kwargs
+from pygama.utils import numba_math_defaults as nb_defaults
 
 limit = np.log(sys.float_info.max)/10
 

src/pygama/math/functions/exponential.py

@@ -8,8 +8,8 @@
 import numpy as np
 
 from pygama.math.functions.pygama_continuous import pygama_continuous
-from ..utils import numba_math_defaults_kwargs as nb_kwargs
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults_kwargs as nb_kwargs
+from pygama.utils import numba_math_defaults as nb_defaults
 
 
 

src/pygama/math/functions/gauss.py

@@ -9,7 +9,7 @@
 
 from pygama.math.functions.error_function import nb_erf
 from pygama.math.functions.pygama_continuous import pygama_continuous 
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults as nb_defaults
 
 
 @nb.njit(**nb_defaults(parallel=False))

src/pygama/math/functions/linear.py

@@ -6,8 +6,8 @@
 from numba import prange
 
 from pygama.math.functions.pygama_continuous import pygama_continuous 
-from ..utils import numba_math_defaults_kwargs as nb_kwargs
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults_kwargs as nb_kwargs
+from pygama.utils import numba_math_defaults as nb_defaults
 
 
 @nb.njit(**nb_kwargs)

src/pygama/math/functions/moyal.py

@@ -10,8 +10,8 @@
 from math import erfc
 
 from pygama.math.functions.pygama_continuous import pygama_continuous
-from ..utils import numba_math_defaults_kwargs as nb_kwargs
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults_kwargs as nb_kwargs
+from pygama.utils import numba_math_defaults as nb_defaults
 
 
 

src/pygama/math/functions/poisson.py

@@ -8,8 +8,8 @@
 from numba import prange
 
 from scipy.stats import rv_discrete
-from ..utils import numba_math_defaults_kwargs as nb_kwargs
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults_kwargs as nb_kwargs
+from pygama.utils import numba_math_defaults as nb_defaults
 
 
 @nb.njit(**nb_defaults(parallel=False))

src/pygama/math/functions/polynomial.py

@@ -1,6 +1,6 @@
 import numba as nb
 import numpy as np
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults as nb_defaults
 
 
 @nb.njit(**nb_defaults(parallel=False))

src/pygama/math/functions/step.py

@@ -11,11 +11,9 @@
 
 from pygama.math.functions.gauss import nb_gauss
 from pygama.math.functions.pygama_continuous import pygama_continuous
-from ..utils import numba_math_defaults_kwargs as nb_kwargs
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults_kwargs as nb_kwargs
+from pygama.utils import numba_math_defaults as nb_defaults
 
-kwd = {"parallel": False, "fastmath": True}
-kwd_parallel = {"parallel": True, "fastmath": True}
 
 @nb.njit(**nb_defaults(parallel=False))
 def nb_step_int(x: float, mu: float, sigma: float, hstep: float) -> np.ndarray:

src/pygama/math/functions/uniform.py

@@ -10,8 +10,8 @@
 from numba import prange
 
 from pygama.math.functions.pygama_continuous import pygama_continuous
-from ..utils import numba_math_defaults_kwargs as nb_kwargs
-from ..utils import numba_math_defaults as nb_defaults
+from pygama.utils import numba_math_defaults_kwargs as nb_kwargs
+from pygama.utils import numba_math_defaults as nb_defaults
 
 
 @nb.njit(**nb_kwargs)

src/pygama/math/utils.py

@@ -3,9 +3,7 @@
 """
 import logging
 import sys
-import os
-from typing import Optional, Union, Callable, Any, Iterator
-from collections.abc import MutableMapping
+from typing import Optional, Union, Callable
 
 import numpy as np
 
@@ -105,75 +103,3 @@ def print_fit_results(pars: np.ndarray, cov: np.ndarray, func: Optional[Callable
         log.info(f"{par_names[i]} = {mean} +/- {sigma}")
     if pad:
         log.info("")
-
-
-def getenv_bool(name: str, default: bool = False) -> bool:
-    """Get environment value as a boolean, returning True for 1, t and true
-    (caps-insensitive), and False for any other value and default if undefined.
-    """
-    val = os.getenv(name)
-    if not val:
-        return default
-    elif val.lower() in ("1", "t", "true"):
-        return True
-    else:
-        return False
-
-class NumbaMathDefaults(MutableMapping):
-    """Bare-bones class to store some Numba default options. Defaults values
-    are set from environment variables
-
-    Examples
-    --------
-    Set all default option values for a processor at once by expanding the
-    provided dictionary:
-
-    >>> from numba import guvectorize
-    >>> from pygama.math.utils import numba_defaults_kwargs as nb_kwargs
-    >>> @guvectorize([], "", **nb_kwargs, nopython=True) # def proc(...): ...
-
-    Customize one argument but still set defaults for the others:
-
-    >>> from pygama.math.utils import numba_defaults as nb_defaults
-    >>> @guvectorize([], "", **nb_defaults(cache=False) # def proc(...): ...
-
-    Override global options at runtime:
-
-    >>> from pygama.math.utils import numba_defaults
-    >>> # must set options before explicitly importing pygama.math.distributions!
-    >>> numba_defaults.cache = False
-    """
-
-    def __init__(self) -> None:
-        self.parallel: bool = getenv_bool("MATH_PARALLEL", default=True)
-        self.fastmath: bool = getenv_bool("MATH_FAST", default=True)
-
-    def __getitem__(self, item: str) -> Any:
-        return self.__dict__[item]
-
-    def __setitem__(self, item: str, val: Any) -> None:
-        self.__dict__[item] = val
-
-    def __delitem__(self, item: str) -> None:
-        del self.__dict__[item]
-
-    def __iter__(self) -> Iterator:
-        return self.__dict__.__iter__()
-
-    def __len__(self) -> int:
-        return len(self.__dict__)
-
-    def __call__(self, **kwargs) -> dict:
-        mapping = self.__dict__.copy()
-        mapping.update(**kwargs)
-        return mapping
-
-    def __str__(self) -> str:
-        return str(self.__dict__)
-
-    def __repr__(self) -> str:
-        return str(self.__dict__)
-
-
-numba_math_defaults = NumbaMathDefaults()
-numba_math_defaults_kwargs = numba_math_defaults

src/pygama/utils.py

@@ -0,0 +1,76 @@
+import os
+from collections.abc import MutableMapping
+from typing import Any, Iterator
+
+
+def getenv_bool(name: str, default: bool = False) -> bool:
+    """Get environment value as a boolean, returning True for 1, t and true
+    (caps-insensitive), and False for any other value and default if undefined.
+    """
+    val = os.getenv(name)
+    if not val:
+        return default
+    elif val.lower() in ("1", "t", "true"):
+        return True
+    else:
+        return False
+
+
+class NumbaPygamaDefaults(MutableMapping):
+    """Bare-bones class to store some Numba default options. Defaults values
+    are set from environment variables. Useful for the pygama.math distributions
+
+    Examples
+    --------
+    Set all default option values for a numba wrapped function at once by expanding the
+    provided dictionary:
+
+    >>> from numba import njit
+    >>> from pygama.utils import numba_math_defaults_kwargs as nb_kwargs
+    >>> @njit([], "", **nb_kwargs, nopython=True) # def dist(...): ...
+
+    Customize one argument but still set defaults for the others:
+
+    >>> from pygama.utils import numba_math_defaults as nb_defaults
+    >>> @njit([], "", **nb_defaults(cache=False) # def dist(...): ...
+
+    Override global options at runtime:
+
+    >>> from pygama.utils import numba_math_defaults
+    >>> # must set options before explicitly importing pygama.math.distributions!
+    >>> numba_math_defaults.cache = False
+    """
+
+    def __init__(self) -> None:
+        self.parallel: bool = getenv_bool("PYGAMA_PARALLEL", default=True)
+        self.fastmath: bool = getenv_bool("PYGAMA_FAST", default=True)
+
+    def __getitem__(self, item: str) -> Any:
+        return self.__dict__[item]
+
+    def __setitem__(self, item: str, val: Any) -> None:
+        self.__dict__[item] = val
+
+    def __delitem__(self, item: str) -> None:
+        del self.__dict__[item]
+
+    def __iter__(self) -> Iterator:
+        return self.__dict__.__iter__()
+
+    def __len__(self) -> int:
+        return len(self.__dict__)
+
+    def __call__(self, **kwargs) -> dict:
+        mapping = self.__dict__.copy()
+        mapping.update(**kwargs)
+        return mapping
+
+    def __str__(self) -> str:
+        return str(self.__dict__)
+
+    def __repr__(self) -> str:
+        return str(self.__dict__)
+
+
+numba_math_defaults = NumbaPygamaDefaults()
+numba_math_defaults_kwargs = numba_math_defaults

tests/math/test_math_utils.py

@@ -31,11 +31,3 @@ def test_print_fit_results(caplog):
         "p2 = 1.0 +/- 1.0",
         "",
     ] == [rec.message for rec in caplog.records]
-
-
-def test_math_numba_defaults():
-    assert pgu.numba_math_defaults_kwargs.fastmath
-    assert pgu.numba_math_defaults_kwargs.parallel
-
-    pgu.numba_math_defaults.fastmath = False
-    assert ~pgu.numba_math_defaults.fastmath

tests/test_utils.py

@@ -0,0 +1,9 @@
+import pygama.utils as pgu
+
+
+def test_math_numba_defaults():
+    assert pgu.numba_math_defaults_kwargs.fastmath
+    assert pgu.numba_math_defaults_kwargs.parallel
+
+    pgu.numba_math_defaults.fastmath = False
+    assert ~pgu.numba_math_defaults.fastmath