1 files changed, 0 insertions, 118 deletions
diff --git a/silx/math/fit/filters/src/strip.c b/silx/math/fit/filters/src/strip.c
deleted file mode 100644
index dec0742..0000000
--- a/silx/math/fit/filters/src/strip.c
+++ /dev/null
@@ -1,118 +0,0 @@
-#/*##########################################################################
-# Copyright (c) 2004-2016 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.
-#
-#############################################################################*/
-/*
-    This file provides a background strip function, to isolate low frequency
-    background signal from a spectrum (and later substact it from the signal
-    to be left only with the peaks to be fitted).
-
-    It is adapted from PyMca source file "SpecFitFuns.c". The main difference
-    with the original code is that this code does not handle the python
-    wrapping, which is done elsewhere using cython.
-
-    Authors: V.A. Sole, P. Knobel
-    License: MIT
-    Last modified: 17/06/2016
-*/
-
-#include <string.h>
-
-#include <stdio.h>
-
-/*  strip(double* input, double c, long niter, double* output)
-
-    The strip background is probably PyMca's  most popular background model.
-
-    In its simplest implementation it is just as an iterative procedure depending
-    on two parameters. These parameters are the strip background width w, and the
-    strip background number of iterations. At each iteration, if the contents of
-    channel i, y(i), is above the average of the contents of the channels at w
-    channels of distance, y(i-w) and y(i+w),  y(i) is replaced by the average.
-    At the end of the process we are left with something that resembles a spectrum
-    in which the peaks have been "stripped".
-
-    Parameters:
-
-        - input: Input data array
-        - c: scaling factor applied to the average of y(i-w) and y(i+w) before
-          comparing to y(i)
-        - niter: number of iterations
-        - deltai: operator width (in number of channels)
-        - anchors: Array of anchors, indices of points that will not be
-          modified during the stripping procedure.
-        - output: output array
-
-*/
-int strip(double* input, long len_input,
-          double c, long niter, int deltai,
-          long* anchors, long len_anchors,
-          double* output)
-{
-    long iter_index, array_index, anchor_index, anchor;
-    int anchor_nearby_flag;
-    double  t_mean;
-
-    memcpy(output, input, len_input * sizeof(double));
-
-    if (deltai <=0) deltai = 1;
-
-    if (len_input < (2*deltai+1)) return(-1);
-
-    if (len_anchors > 0) {
-        for (iter_index = 0; iter_index < niter; iter_index++) {
-            for (array_index = deltai; array_index < len_input - deltai; array_index++) {
-                /* if index is within +- deltai of an anchor, don't do anything */
-                anchor_nearby_flag = 0;
-                for (anchor_index=0; anchor_index<len_anchors; anchor_index++)
-                {
-                    anchor = anchors[anchor_index];
-                    if (array_index > (anchor - deltai) && array_index < (anchor + deltai))
-                    {
-                        anchor_nearby_flag = 1;
-                        break;
-                    }
-                }
-                /* skip this array_index index */
-                if (anchor_nearby_flag) {
-                    continue;
-                }
-
-                t_mean = 0.5 * (input[array_index-deltai] + input[array_index+deltai]);
-                if (input[array_index] > (t_mean * c))
-                    output[array_index] = t_mean;
-            }
-            memcpy(input, output, len_input * sizeof(double));
-        }
-    }
-    else {
-        for (iter_index = 0; iter_index < niter; iter_index++) {
-            for (array_index=deltai; array_index < len_input - deltai; array_index++) {
-                t_mean = 0.5 * (input[array_index-deltai] + input[array_index+deltai]);
-
-                if (input[array_index] > (t_mean * c))
-                    output[array_index] = t_mean;
-            }
-            memcpy(input, output, len_input * sizeof(double));
-        }
-    }
-    return(0);
-}