get rid of double leading underscore

Author: Vahid Tavanashad

mkl_fft/_float_utils.py

@@ -27,13 +27,13 @@
 import numpy as np
 
 __all__ = [
-    "__upcast_float16_array",
-    "__downcast_float128_array",
-    "__supported_array_or_not_implemented",
+    "_upcast_float16_array",
+    "_downcast_float128_array",
+    "_supported_array_or_not_implemented",
 ]
 
 
-def __upcast_float16_array(x):
+def _upcast_float16_array(x):
     """
     Used in _scipy_fft to upcast float16 to float32,
     instead of float64, as mkl_fft would do
@@ -46,18 +46,18 @@ def __upcast_float16_array(x):
         if xdt == np.longdouble and not xdt == np.float64:
             raise ValueError("type %s is not supported" % xdt)
     if not isinstance(x, np.ndarray):
-        __x = np.asarray(x)
-        xdt = __x.dtype
+        _x = np.asarray(x)
+        xdt = _x.dtype
         if xdt == np.half:
             # no half-precision routines, so convert to single precision
-            return np.asarray(__x, dtype=np.float32)
+            return np.asarray(_x, dtype=np.float32)
         if xdt == np.longdouble and not xdt == np.float64:
             raise ValueError("type %s is not supported" % xdt)
-        return __x
+        return _x
     return x
 
 
-def __downcast_float128_array(x):
+def _downcast_float128_array(x):
     """
     Used in _numpy_fft to unsafely downcast float128/complex256 to
     complex128, instead of raising an error
@@ -69,27 +69,27 @@ def __downcast_float128_array(x):
         elif xdt == np.clongdouble and not xdt == np.complex128:
             return np.asarray(x, dtype=np.complex128)
     if not isinstance(x, np.ndarray):
-        __x = np.asarray(x)
-        xdt = __x.dtype
+        _x = np.asarray(x)
+        xdt = _x.dtype
         if xdt == np.longdouble and not xdt == np.float64:
             return np.asarray(x, dtype=np.float64)
         elif xdt == np.clongdouble and not xdt == np.complex128:
             return np.asarray(x, dtype=np.complex128)
-        return __x
+        return _x
     return x
 
 
-def __supported_array_or_not_implemented(x):
+def _supported_array_or_not_implemented(x):
     """
     Used in _scipy_fft to convert array to float32,
     float64, complex64, or complex128 type or raise NotImplementedError
     """
-    __x = np.asarray(x)
+    _x = np.asarray(x)
     black_list = [np.half]
     if hasattr(np, "float128"):
         black_list.append(np.float128)
     if hasattr(np, "complex256"):
         black_list.append(np.complex256)
-    if __x.dtype in black_list:
+    if _x.dtype in black_list:
         raise NotImplementedError
-    return __x
+    return _x

mkl_fft/_numpy_fft.py

@@ -77,7 +77,7 @@
 
 from . import _pydfti as mkl_fft  # pylint: disable=no-name-in-module
 from ._fft_utils import _check_norm, _compute_fwd_scale
-from ._float_utils import __downcast_float128_array
+from ._float_utils import _downcast_float128_array
 
 
 # copied with modifications from:
@@ -240,7 +240,7 @@ def fft(a, n=None, axis=-1, norm=None):
 
     """
 
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     fsc = _compute_fwd_scale(norm, n, x.shape[axis])
 
     return trycall(mkl_fft.fft, (x,), {"n": n, "axis": axis, "fwd_scale": fsc})
@@ -333,7 +333,7 @@ def ifft(a, n=None, axis=-1, norm=None):
 
     """
 
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     fsc = _compute_fwd_scale(norm, n, x.shape[axis])
 
     return trycall(mkl_fft.ifft, (x,), {"n": n, "axis": axis, "fwd_scale": fsc})
@@ -424,7 +424,7 @@ def rfft(a, n=None, axis=-1, norm=None):
 
     """
 
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     fsc = _compute_fwd_scale(norm, n, x.shape[axis])
 
     return trycall(mkl_fft.rfft, (x,), {"n": n, "axis": axis, "fwd_scale": fsc})
@@ -517,7 +517,7 @@ def irfft(a, n=None, axis=-1, norm=None):
 
     """
 
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     fsc = _compute_fwd_scale(norm, n, 2 * (x.shape[axis] - 1))
 
     return trycall(
@@ -603,7 +603,7 @@ def hfft(a, n=None, axis=-1, norm=None):
     """
 
     norm = _swap_direction(norm)
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     x = np.array(x, copy=True, dtype=complex)
     np.conjugate(x, out=x)
     fsc = _compute_fwd_scale(norm, n, 2 * (x.shape[axis] - 1))
@@ -673,7 +673,7 @@ def ihfft(a, n=None, axis=-1, norm=None):
 
     # The copy may be required for multithreading.
     norm = _swap_direction(norm)
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     x = np.array(x, copy=True, dtype=float)
     fsc = _compute_fwd_scale(norm, n, x.shape[axis])
 
@@ -785,7 +785,7 @@ def fftn(a, s=None, axes=None, norm=None):
 
     """
 
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     s, axes = _cook_nd_args(x, s, axes)
     fsc = _compute_fwd_scale(norm, s, x.shape)
 
@@ -892,7 +892,7 @@ def ifftn(a, s=None, axes=None, norm=None):
 
     """
 
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     s, axes = _cook_nd_args(x, s, axes)
     fsc = _compute_fwd_scale(norm, s, x.shape)
 
@@ -1180,7 +1180,7 @@ def rfftn(a, s=None, axes=None, norm=None):
 
     """
 
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     s, axes = _cook_nd_args(x, s, axes)
     fsc = _compute_fwd_scale(norm, s, x.shape)
 
@@ -1324,7 +1324,7 @@ def irfftn(a, s=None, axes=None, norm=None):
 
     """
 
-    x = __downcast_float128_array(a)
+    x = _downcast_float128_array(a)
     s, axes = _cook_nd_args(x, s, axes, invreal=True)
     fsc = _compute_fwd_scale(norm, s, x.shape)
 

mkl_fft/_scipy_fft.py

@@ -34,7 +34,7 @@
 
 from . import _pydfti as mkl_fft  # pylint: disable=no-name-in-module
 from ._fft_utils import _compute_fwd_scale
-from ._float_utils import __supported_array_or_not_implemented
+from ._float_utils import _supported_array_or_not_implemented
 
 __doc__ = """
 This module implements interfaces mimicing `scipy.fft` module.
@@ -223,7 +223,7 @@ def _cook_nd_args(a, s=None, axes=None, invreal=False):
 
 def _validate_input(a):
     try:
-        x = __supported_array_or_not_implemented(a)
+        x = _supported_array_or_not_implemented(a)
     except ValueError:
         raise NotImplementedError
 

mkl_fft/_scipy_fftpack.py

@@ -25,46 +25,46 @@
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
 from . import _pydfti as mkl_fft  # pylint: disable=no-name-in-module
-from ._float_utils import __upcast_float16_array
+from ._float_utils import _upcast_float16_array
 
 __all__ = ["fft", "ifft", "fftn", "ifftn", "fft2", "ifft2", "rfft", "irfft"]
 
 
 def fft(a, n=None, axis=-1, overwrite_x=False):
-    x = __upcast_float16_array(a)
+    x = _upcast_float16_array(a)
     return mkl_fft.fft(x, n=n, axis=axis, overwrite_x=overwrite_x)
 
 
 def ifft(a, n=None, axis=-1, overwrite_x=False):
-    x = __upcast_float16_array(a)
+    x = _upcast_float16_array(a)
     return mkl_fft.ifft(x, n=n, axis=axis, overwrite_x=overwrite_x)
 
 
 def fftn(a, shape=None, axes=None, overwrite_x=False):
-    x = __upcast_float16_array(a)
+    x = _upcast_float16_array(a)
     return mkl_fft.fftn(x, s=shape, axes=axes, overwrite_x=overwrite_x)
 
 
 def ifftn(a, shape=None, axes=None, overwrite_x=False):
-    x = __upcast_float16_array(a)
+    x = _upcast_float16_array(a)
     return mkl_fft.ifftn(x, s=shape, axes=axes, overwrite_x=overwrite_x)
 
 
 def fft2(a, shape=None, axes=(-2, -1), overwrite_x=False):
-    x = __upcast_float16_array(a)
+    x = _upcast_float16_array(a)
     return mkl_fft.fftn(x, s=shape, axes=axes, overwrite_x=overwrite_x)
 
 
 def ifft2(a, shape=None, axes=(-2, -1), overwrite_x=False):
-    x = __upcast_float16_array(a)
+    x = _upcast_float16_array(a)
     return mkl_fft.ifftn(x, s=shape, axes=axes, overwrite_x=overwrite_x)
 
 
 def rfft(a, n=None, axis=-1, overwrite_x=False):
-    x = __upcast_float16_array(a)
+    x = _upcast_float16_array(a)
     return mkl_fft.rfftpack(x, n=n, axis=axis, overwrite_x=overwrite_x)
 
 
 def irfft(a, n=None, axis=-1, overwrite_x=False):
-    x = __upcast_float16_array(a)
+    x = _upcast_float16_array(a)
     return mkl_fft.irfftpack(x, n=n, axis=axis, overwrite_x=overwrite_x)