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/* Copyright 2020 The Chromium OS Authors. All rights reserved.
* Use of this source code is governed by a BSD-style license that can be
* found in the LICENSE file.
*/
#include "common.h"
#include "accel_cal.h"
#include "test_util.h"
#include "motion_sense.h"
#include <math.h>
struct motion_sensor_t motion_sensors[] = {};
const unsigned int motion_sensor_count = ARRAY_SIZE(motion_sensors);
struct accel_cal_algo algos[2] = {
{
.newton_fit = NEWTON_FIT(8, 1, 0.01f, 0.25f, 1.0e-8f, 100),
},
{
.newton_fit = NEWTON_FIT(8, 1, 0.01f, 0.25f, 1.0e-8f, 100),
}
};
struct accel_cal cal = {
.still_det = STILL_DET(0.00025f, 800 * MSEC, 1200 * MSEC, 5),
.algos = algos,
.num_temp_windows = ARRAY_SIZE(algos),
};
static bool accumulate(float x, float y, float z, float temperature)
{
return accel_cal_accumulate(&cal, 0, x, y, z, temperature)
| accel_cal_accumulate(&cal, 200 * MSEC, x, y, z, temperature)
| accel_cal_accumulate(&cal, 400 * MSEC, x, y, z, temperature)
| accel_cal_accumulate(&cal, 600 * MSEC, x, y, z, temperature)
| accel_cal_accumulate(&cal, 800 * MSEC, x, y, z, temperature)
| accel_cal_accumulate(&cal, 1000 * MSEC, x, y, z, temperature);
}
static int test_calibrated_correctly_with_kasa(void)
{
bool has_bias;
accumulate(1.01f, 0.01f, 0.01f, 21.0f);
accumulate(-0.99f, 0.01f, 0.01f, 21.0f);
accumulate(0.01f, 1.01f, 0.01f, 21.0f);
accumulate(0.01f, -0.99f, 0.01f, 21.0f);
accumulate(0.01f, 0.01f, 1.01f, 21.0f);
accumulate(0.01f, 0.01f, -0.99f, 21.0f);
accumulate(0.7171f, 0.7171f, 0.7171f, 21.0f);
has_bias = accumulate(-0.6971f, -0.6971f, -0.6971f, 21.0f);
TEST_EQ(has_bias, true, "%d");
TEST_NEAR(cal.bias[X], 0.01f, 0.0001f, "%f");
TEST_NEAR(cal.bias[Y], 0.01f, 0.0001f, "%f");
TEST_NEAR(cal.bias[Z], 0.01f, 0.0001f, "%f");
return EC_SUCCESS;
}
static int test_calibrated_correctly_with_newton(void)
{
bool has_bias = false;
struct kasa_fit kasa;
fpv3_t kasa_bias;
float kasa_radius;
int i;
float data[] = {
1.00290f, 0.09170f, 0.09649f,
0.95183f, 0.23626f, 0.25853f,
0.95023f, 0.15387f, 0.31865f,
0.97374f, 0.01639f, 0.27675f,
0.88521f, 0.30212f, 0.39558f,
0.92787f, 0.35157f, 0.21209f,
0.95162f, 0.33173f, 0.10924f,
0.98397f, 0.22644f, 0.07737f,
};
kasa_reset(&kasa);
for (i = 0; i < ARRAY_SIZE(data); i += 3) {
TEST_EQ(has_bias, false, "%d");
kasa_accumulate(&kasa, data[i], data[i + 1], data[i + 2]);
has_bias = accumulate(data[i], data[i + 1], data[i + 2], 21.0f);
}
kasa_compute(&kasa, kasa_bias, &kasa_radius);
TEST_EQ(has_bias, true, "%d");
/* Check that the bias is right */
TEST_NEAR(cal.bias[X], 0.01f, 0.001f, "%f");
TEST_NEAR(cal.bias[Y], 0.01f, 0.001f, "%f");
TEST_NEAR(cal.bias[Z], 0.01f, 0.001f, "%f");
/* Demonstrate that we got a better bias compared to kasa */
TEST_LT(sqrtf(powf(cal.bias[X] - 0.01f, 2.0f) +
powf(cal.bias[Y] - 0.01f, 2.0f) +
powf(cal.bias[Z] - 0.01f, 2.0f)),
sqrtf(powf(kasa_bias[X] - 0.01f, 2.0f) +
powf(kasa_bias[Y] - 0.01f, 2.0f) +
powf(kasa_bias[Z] - 0.01f, 2.0f)),
"%f");
return EC_SUCCESS;
}
static int test_temperature_gates(void)
{
bool has_bias;
accumulate(1.01f, 0.01f, 0.01f, 21.0f);
accumulate(-0.99f, 0.01f, 0.01f, 21.0f);
accumulate(0.01f, 1.01f, 0.01f, 21.0f);
accumulate(0.01f, -0.99f, 0.01f, 21.0f);
accumulate(0.01f, 0.01f, 1.01f, 21.0f);
accumulate(0.01f, 0.01f, -0.99f, 21.0f);
accumulate(0.7171f, 0.7171f, 0.7171f, 21.0f);
has_bias = accumulate(-0.6971f, -0.6971f, -0.6971f, 31.0f);
TEST_EQ(has_bias, false, "%d");
return EC_SUCCESS;
}
void before_test(void)
{
cal.still_det = STILL_DET(0.00025f, 800 * MSEC, 1200 * MSEC, 5);
accel_cal_reset(&cal);
}
void run_test(int argc, char **argv)
{
test_reset();
RUN_TEST(test_calibrated_correctly_with_kasa);
RUN_TEST(test_calibrated_correctly_with_newton);
RUN_TEST(test_temperature_gates);
test_print_result();
}
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