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feat(passes/radar): port pass history + compass calibration, cumulative what's new
- Pass history (Iu-yang1 fork): PassesSettings.hoursBefore look-back window; second 'Time before' slider in the pass filter; completed passes stay listed (progress clamped to [0,1]) in the history window. - Compass calibration (Iu-yang1 fork): OtherSettings.compassOffsetDegrees, CompassAccuracy from the magnetic sensor, calibration dialog with figure-eight accuracy meter, corrected heading and manual offset field; RadarViewModel applies the offset. - What's New dialog now shows the cumulative 4.4.6->4.4.7 changelog and follows the system language (values/ + values-zh/). - pass_filter_history_hours localized in es/ru/si/tr/uk.
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@@ -30,7 +30,9 @@ data class PassesSettings(
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val aosStartMinute: Int = 0,
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val aosEndMinute: Int = 23 * 60 + 59,
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val invertAosTimeWindow: Boolean = false,
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val selectedModes: List<String>
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val selectedModes: List<String>,
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/** 历史过境回看窗口(小时): 过境列表从 now-hoursBefore 开始计算. */
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val hoursBefore: Int = 0
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)
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data class RCSettings(
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@@ -71,7 +73,9 @@ data class OtherSettings(
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val highElevation: Double = 45.0,
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/** Independent auto-sync toggle for LoTW confirmed grids (separate from the
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* ephemeris auto-update; only effective after at least one manual sync). */
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val stateOfAutoLotwSync: Boolean = true
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val stateOfAutoLotwSync: Boolean = true,
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/** 指南针手动航向偏置(度, -180..180): 雷达方位 = 传感器方位 + 磁偏角 + 该偏置. */
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val compassOffsetDegrees: Float = 0f
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)
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data class DataSourcesSettings(
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+11
@@ -20,8 +20,19 @@ package com.rtbishop.look4sat.core.domain.repository
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import com.rtbishop.look4sat.core.domain.predict.GeoPos
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import kotlinx.coroutines.flow.StateFlow
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/** 指南针校准精度等级, 由磁场传感器 accuracy 事件映射而来. */
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enum class CompassAccuracy {
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UNAVAILABLE,
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UNRELIABLE,
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LOW,
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MEDIUM,
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HIGH
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}
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interface ISensorsRepo {
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val sensorData: StateFlow<Pair<Float, Float>>
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/** 指南针当前校准精度 (磁场传感器 accuracy), 用于校准对话框进度. */
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val compassAccuracy: StateFlow<CompassAccuracy>
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fun getMagDeclination(geoPos: GeoPos, time: Long = System.currentTimeMillis()): Float
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fun enableSensor()
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fun disableSensor()
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