1 files changed, 0 insertions, 53 deletions
diff --git a/silx/image/utils.py b/silx/image/utils.py
deleted file mode 100644
index 996d010..0000000
--- a/silx/image/utils.py
+++ /dev/null
@@ -1,53 +0,0 @@
-# -*- coding: utf-8 -*-
-# /*##########################################################################
-# Copyright (C) 2019 European Synchrotron Radiation Facility
-#
-# Permission is hereby granted, free of charge, to any person obtaining a copy
-# of this software and associated documentation files (the "Software"), to deal
-# in the Software without restriction, including without limitation the rights
-# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-# copies of the Software, and to permit persons to whom the Software is
-# furnished to do so, subject to the following conditions:
-#
-# The above copyright notice and this permission notice shall be included in
-# all copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
-# THE SOFTWARE.
-#
-# ############################################################################*/
-
-import numpy as np
-from math import ceil
-
-def gaussian_kernel(sigma, cutoff=4, force_odd_size=False):
-    """
-    Generates a Gaussian convolution kernel.
-
-    :param sigma: Standard Deviation of the Gaussian curve.
-    :param cutoff: Parameter tuning the truncation of the Gaussian.
-        The higher cutoff, the biggest the array will be (and the closest to
-        a "true" Gaussian function).
-    :param force_odd_size: when set to True, the resulting array will always
-        have an odd size, regardless of the values of "sigma" and "cutoff".
-    :return: a numpy.ndarray containing the truncated Gaussian function.
-        The array size is 2*c*s+1 where c=cutoff, s=sigma.
-
-    Nota: due to the quick decay of the Gaussian function, small values of the
-        "cutoff" parameter are usually fine. The energy difference between a
-        Gaussian truncated to [-c, c] and a "true" one is
-            erfc(c/(sqrt(2)*s))
-        so choosing cutoff=4*sigma keeps the truncation error below 1e-4.
-    """
-    size = int(ceil(2 * cutoff * sigma + 1))
-    if force_odd_size and size % 2 == 0:
-        size += 1
-    x = np.arange(size) - (size - 1.0) / 2.0
-    g = np.exp(-(x / sigma) ** 2 / 2.0)
-    g /= g.sum()
-    return g