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clang-tidy performance-type-promotion-in-math-fn (#236)
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+2
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@@ -768,7 +768,7 @@ void Ekf::get_innovation_test_status(uint16_t *status, float *mag, float *vel, f
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// return the airspeed fusion innovation test ratio
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*tas = sqrtf(_tas_test_ratio);
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// return the terrain height innovation test ratio
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*hagl = sqrt(_terr_test_ratio);
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*hagl = sqrtf(_terr_test_ratio);
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}
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// return a bitmask integer that describes which state estimates are valid
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@@ -912,7 +912,7 @@ Vector3f Ekf::calcRotVecVariances()
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q3 = -_state.quat_nominal(3);
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}
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float t2 = q0*q0;
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float t3 = acos(q0);
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float t3 = acosf(q0);
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float t4 = -t2+1.0f;
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float t5 = t2-1.0f;
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if ((t4 > 1e-9f) && (t5 < -1e-9f)) {
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@@ -365,7 +365,7 @@ bool EstimatorInterface::initialise_interface(uint64_t timestamp)
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// set the observaton buffer length to handle the minimum time of arrival between observations in combination
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// with the worst case delay from current time to ekf fusion time
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// allow for worst case 50% extension of the ekf fusion time horizon delay due to timing jitter
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uint16_t ekf_delay_ms = max_time_delay_ms + (int)(ceil((float)max_time_delay_ms * 0.5f));
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uint16_t ekf_delay_ms = max_time_delay_ms + (int)(ceilf((float)max_time_delay_ms * 0.5f));
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_obs_buffer_length = (ekf_delay_ms / _params.sensor_interval_min_ms) + 1;
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// limit to be no longer than the IMU buffer (we can't process data faster than the EKF prediction rate)
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