--- /dev/null
+/*
+ * This program is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 2 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program; if not, write to the Free Software
+ * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
+ *
+ * Copyright (C) 2008,2009 by Openmoko, Inc.
+ * Author: Nelson Castillo <arhuaco@freaks-unidos.net>
+ * All rights reserved.
+ *
+ *
+ * This filter is useful to reject samples that are not reliable. We consider
+ * that a sample is not reliable if it deviates form the Majority.
+ *
+ * 1) We collect S samples.
+ *
+ * 2) For each dimension:
+ *
+ * - We sort the points.
+ * - Points that are "close enough" are considered to be in the same set.
+ * - We choose the set with more elements. If more than "threshold"
+ * points are in this set we use the first and the last point of the set
+ * to define the valid range for this dimension [min, max], otherwise we
+ * discard all the points and go to step 1.
+ *
+ * 3) We consider the unsorted S samples and try to feed them to the next
+ * filter in the chain. If one of the points of each sample
+ * is not in the allowed range for its dimension, we discard the sample.
+ *
+ */
+
+#include <linux/kernel.h>
+#include <linux/slab.h>
+#include <linux/sort.h>
+#include <linux/touchscreen/ts_filter_group.h>
+
+struct ts_filter_group {
+ /* Private filter configuration. */
+ struct ts_filter_group_configuration *config;
+ /* Filter API. */
+ struct ts_filter tsf;
+
+ int N; /* How many samples we have. */
+ int *samples[MAX_TS_FILTER_COORDS]; /* The samples: our input. */
+
+ int *group_size; /* Used for temporal computations. */
+ int *sorted_samples; /* Used for temporal computations. */
+
+ int range_max[MAX_TS_FILTER_COORDS]; /* Max. computed ranges. */
+ int range_min[MAX_TS_FILTER_COORDS]; /* Min. computed ranges. */
+
+ int tries_left; /* We finish if we don't get enough samples. */
+ int ready; /* If we are ready to deliver samples. */
+ int result; /* Index of the point being returned. */
+};
+
+#define ts_filter_to_filter_group(f) \
+ container_of(f, struct ts_filter_group, tsf)
+
+
+static void ts_filter_group_clear_internal(struct ts_filter_group *tsfg,
+ int attempts)
+{
+ tsfg->N = 0;
+ tsfg->tries_left = attempts;
+ tsfg->ready = 0;
+ tsfg->result = 0;
+}
+
+static void ts_filter_group_clear(struct ts_filter *tsf)
+{
+ struct ts_filter_group *tsfg = ts_filter_to_filter_group(tsf);
+
+ ts_filter_group_clear_internal(tsfg, tsfg->config->attempts);
+}
+
+static struct ts_filter *ts_filter_group_create(
+ struct platform_device *pdev,
+ const struct ts_filter_configuration *conf,
+ int count_coords)
+{
+ struct ts_filter_group *tsfg;
+ int i;
+
+ tsfg = kzalloc(sizeof(struct ts_filter_group), GFP_KERNEL);
+ if (!tsfg)
+ return NULL;
+
+ tsfg->config = container_of(conf,
+ struct ts_filter_group_configuration,
+ config);
+ tsfg->tsf.count_coords = count_coords;
+
+ BUG_ON(tsfg->config->attempts <= 0);
+
+ tsfg->samples[0] = kmalloc((2 + count_coords) * sizeof(int) *
+ tsfg->config->length, GFP_KERNEL);
+ if (!tsfg->samples[0]) {
+ kfree(tsfg);
+ return NULL;
+ }
+ for (i = 1; i < count_coords; ++i)
+ tsfg->samples[i] = tsfg->samples[0] + i * tsfg->config->length;
+ tsfg->sorted_samples = tsfg->samples[0] + count_coords *
+ tsfg->config->length;
+ tsfg->group_size = tsfg->samples[0] + (1 + count_coords) *
+ tsfg->config->length;
+
+ ts_filter_group_clear_internal(tsfg, tsfg->config->attempts);
+
+ dev_info(&pdev->dev, "Created Group filter len:%d coords:%d close:%d "
+ "thresh:%d\n", tsfg->config->length, count_coords,
+ tsfg->config->close_enough, tsfg->config->threshold);
+
+ return &tsfg->tsf;
+}
+
+static void ts_filter_group_destroy(struct ts_filter *tsf)
+{
+ struct ts_filter_group *tsfg = ts_filter_to_filter_group(tsf);
+
+ kfree(tsfg->samples[0]); /* first guy has pointer from kmalloc */
+ kfree(tsf);
+}
+
+static int int_cmp(const void *_a, const void *_b)
+{
+ const int *a = _a;
+ const int *b = _b;
+
+ if (*a > *b)
+ return 1;
+ if (*a < *b)
+ return -1;
+ return 0;
+}
+
+static void ts_filter_group_prepare_next(struct ts_filter *tsf);
+
+static int ts_filter_group_process(struct ts_filter *tsf, int *coords)
+{
+ struct ts_filter_group *tsfg = ts_filter_to_filter_group(tsf);
+ int n;
+ int i;
+
+ BUG_ON(tsfg->N >= tsfg->config->length);
+ BUG_ON(tsfg->ready);
+
+ for (n = 0; n < tsf->count_coords; n++)
+ tsfg->samples[n][tsfg->N] = coords[n];
+
+ if (++tsfg->N < tsfg->config->length)
+ return 0; /* We need more samples. */
+
+ for (n = 0; n < tsfg->tsf.count_coords; n++) {
+ int *v = tsfg->sorted_samples;
+ int ngroups = 0;
+ int best_size;
+ int best_idx = 0;
+ int idx = 0;
+
+ memcpy(v, tsfg->samples[n], tsfg->N * sizeof(int));
+ /*
+ * FIXME: Remove this sort call. We already have the
+ * algorithm for this modification. The filter will
+ * need less points (about half) if there is not a
+ * lot of noise. Right now we are doing a constant
+ * amount of work no matter how much noise we are
+ * dealing with.
+ */
+ sort(v, tsfg->N, sizeof(int), int_cmp, NULL);
+
+ tsfg->group_size[0] = 1;
+ for (i = 1; i < tsfg->N; ++i) {
+ if (v[i] - v[i - 1] <= tsfg->config->close_enough)
+ tsfg->group_size[ngroups]++;
+ else
+ tsfg->group_size[++ngroups] = 1;
+ }
+ ngroups++;
+
+ best_size = tsfg->group_size[0];
+ for (i = 1; i < ngroups; i++) {
+ idx += tsfg->group_size[i - 1];
+ if (best_size < tsfg->group_size[i]) {
+ best_size = tsfg->group_size[i];
+ best_idx = idx;
+ }
+ }
+
+ if (best_size < tsfg->config->threshold) {
+ /* This set is not good enough for us. */
+ if (--tsfg->tries_left) {
+ ts_filter_group_clear_internal
+ (tsfg, tsfg->tries_left);
+ /* No errors but we need more samples. */
+ return 0;
+ }
+ return 1; /* We give up: error. */
+ }
+
+ tsfg->range_min[n] = v[best_idx];
+ tsfg->range_max[n] = v[best_idx + best_size - 1];
+ }
+
+ ts_filter_group_prepare_next(tsf);
+
+ return 0;
+}
+
+/*
+ * This private function prepares a point that will be returned
+ * in ts_filter_group_getpoint if it is available. It updates
+ * the priv->ready state also.
+ */
+static void ts_filter_group_prepare_next(struct ts_filter *tsf)
+{
+ struct ts_filter_group *priv = ts_filter_to_filter_group(tsf);
+ int n;
+
+ while (priv->result < priv->N) {
+ for (n = 0; n < priv->tsf.count_coords; ++n) {
+ if (priv->samples[n][priv->result] <
+ priv->range_min[n] ||
+ priv->samples[n][priv->result] > priv->range_max[n])
+ break;
+ }
+
+ if (n == priv->tsf.count_coords) /* Sample is OK. */
+ break;
+
+ priv->result++;
+ }
+
+ if (unlikely(priv->result >= priv->N)) { /* No sample to deliver. */
+ ts_filter_group_clear_internal(priv, priv->config->attempts);
+ priv->ready = 0;
+ } else {
+ priv->ready = 1;
+ }
+}
+
+static int ts_filter_group_haspoint(struct ts_filter *tsf)
+{
+ struct ts_filter_group *priv = ts_filter_to_filter_group(tsf);
+
+ return priv->ready;
+}
+
+static void ts_filter_group_getpoint(struct ts_filter *tsf, int *point)
+{
+ struct ts_filter_group *priv = ts_filter_to_filter_group(tsf);
+ int n;
+
+ BUG_ON(!priv->ready);
+
+ for (n = 0; n < priv->tsf.count_coords; n++)
+ point[n] = priv->samples[n][priv->result];
+
+ priv->result++;
+
+ /* This call will update priv->ready. */
+ ts_filter_group_prepare_next(tsf);
+}
+
+/*
+ * Get ready to process the next batch of points, forget
+ * points we could have delivered.
+ */
+static void ts_filter_group_scale(struct ts_filter *tsf, int *coords)
+{
+ struct ts_filter_group *priv = ts_filter_to_filter_group(tsf);
+
+ ts_filter_group_clear_internal(priv, priv->config->attempts);
+}
+
+const struct ts_filter_api ts_filter_group_api = {
+ .create = ts_filter_group_create,
+ .destroy = ts_filter_group_destroy,
+ .clear = ts_filter_group_clear,
+ .process = ts_filter_group_process,
+ .haspoint = ts_filter_group_haspoint,
+ .getpoint = ts_filter_group_getpoint,
+ .scale = ts_filter_group_scale,
+};
+EXPORT_SYMBOL_GPL(ts_filter_group_api);
+
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