Mirror/brk
1
0
Fork 0
mirror of https://github.com/bitcoinresearchkit/brk.git synced 2026-06-08 06:01:57 -07:00
Code Issues Packages Projects Releases Wiki Activity

global: snapshot

Browse Source
This commit is contained in:
nym21
2026-03-02 13:34:45 +01:00
parent 7cb1bfa667
commit 4d97cec869
57 changed files with 1724 additions and 2011 deletions
Download Patch File Download Diff File Expand all files Collapse all files
crates/brk_client/src/lib.rs
+122 -247
View File
@@ -2219,6 +2219,42 @@ impl _10y1m1w1y2y3m3y4y5y6m6y8yPattern3 {
}
}
/// Pattern struct for repeated tree structure.
pub struct _10y1m1w1y2y3m3y4y5y6m6y8yPattern2 {
pub _10y: MetricPattern1<StoredF32>,
pub _1m: MetricPattern1<StoredF32>,
pub _1w: MetricPattern1<StoredF32>,
pub _1y: MetricPattern1<StoredF32>,
pub _2y: MetricPattern1<StoredF32>,
pub _3m: MetricPattern1<StoredF32>,
pub _3y: MetricPattern1<StoredF32>,
pub _4y: MetricPattern1<StoredF32>,
pub _5y: MetricPattern1<StoredF32>,
pub _6m: MetricPattern1<StoredF32>,
pub _6y: MetricPattern1<StoredF32>,
pub _8y: MetricPattern1<StoredF32>,
}
impl _10y1m1w1y2y3m3y4y5y6m6y8yPattern2 {
/// Create a new pattern node with accumulated metric name.
pub fn new(client: Arc<BrkClientBase>, acc: String) -> Self {
Self {
_10y: MetricPattern1::new(client.clone(), _p("10y", &acc)),
_1m: MetricPattern1::new(client.clone(), _p("1m", &acc)),
_1w: MetricPattern1::new(client.clone(), _p("1w", &acc)),
_1y: MetricPattern1::new(client.clone(), _p("1y", &acc)),
_2y: MetricPattern1::new(client.clone(), _p("2y", &acc)),
_3m: MetricPattern1::new(client.clone(), _p("3m", &acc)),
_3y: MetricPattern1::new(client.clone(), _p("3y", &acc)),
_4y: MetricPattern1::new(client.clone(), _p("4y", &acc)),
_5y: MetricPattern1::new(client.clone(), _p("5y", &acc)),
_6m: MetricPattern1::new(client.clone(), _p("6m", &acc)),
_6y: MetricPattern1::new(client.clone(), _p("6y", &acc)),
_8y: MetricPattern1::new(client.clone(), _p("8y", &acc)),
}
}
}
/// Pattern struct for repeated tree structure.
pub struct InvestedNegNetNuplSupplyUnrealizedPattern {
pub invested_capital_in_loss_pct: MetricPattern1<StoredF32>,
@@ -2255,78 +2291,6 @@ impl InvestedNegNetNuplSupplyUnrealizedPattern {
}
}
/// Pattern struct for repeated tree structure.
pub struct _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<T> {
pub _10y: MetricPattern1<T>,
pub _1m: MetricPattern1<T>,
pub _1w: MetricPattern1<T>,
pub _1y: MetricPattern1<T>,
pub _2y: MetricPattern1<T>,
pub _3m: MetricPattern1<T>,
pub _3y: MetricPattern1<T>,
pub _4y: MetricPattern1<T>,
pub _5y: MetricPattern1<T>,
pub _6m: MetricPattern1<T>,
pub _6y: MetricPattern1<T>,
pub _8y: MetricPattern1<T>,
}
impl<T: DeserializeOwned> _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<T> {
/// Create a new pattern node with accumulated metric name.
pub fn new(client: Arc<BrkClientBase>, acc: String) -> Self {
Self {
_10y: MetricPattern1::new(client.clone(), _p("10y", &acc)),
_1m: MetricPattern1::new(client.clone(), _p("1m", &acc)),
_1w: MetricPattern1::new(client.clone(), _p("1w", &acc)),
_1y: MetricPattern1::new(client.clone(), _p("1y", &acc)),
_2y: MetricPattern1::new(client.clone(), _p("2y", &acc)),
_3m: MetricPattern1::new(client.clone(), _p("3m", &acc)),
_3y: MetricPattern1::new(client.clone(), _p("3y", &acc)),
_4y: MetricPattern1::new(client.clone(), _p("4y", &acc)),
_5y: MetricPattern1::new(client.clone(), _p("5y", &acc)),
_6m: MetricPattern1::new(client.clone(), _p("6m", &acc)),
_6y: MetricPattern1::new(client.clone(), _p("6y", &acc)),
_8y: MetricPattern1::new(client.clone(), _p("8y", &acc)),
}
}
}
/// Pattern struct for repeated tree structure.
pub struct _201520162017201820192020202120222023202420252026Pattern2<T> {
pub _2015: MetricPattern1<T>,
pub _2016: MetricPattern1<T>,
pub _2017: MetricPattern1<T>,
pub _2018: MetricPattern1<T>,
pub _2019: MetricPattern1<T>,
pub _2020: MetricPattern1<T>,
pub _2021: MetricPattern1<T>,
pub _2022: MetricPattern1<T>,
pub _2023: MetricPattern1<T>,
pub _2024: MetricPattern1<T>,
pub _2025: MetricPattern1<T>,
pub _2026: MetricPattern1<T>,
}
impl<T: DeserializeOwned> _201520162017201820192020202120222023202420252026Pattern2<T> {
/// Create a new pattern node with accumulated metric name.
pub fn new(client: Arc<BrkClientBase>, acc: String) -> Self {
Self {
_2015: MetricPattern1::new(client.clone(), _m(&acc, "2015_returns")),
_2016: MetricPattern1::new(client.clone(), _m(&acc, "2016_returns")),
_2017: MetricPattern1::new(client.clone(), _m(&acc, "2017_returns")),
_2018: MetricPattern1::new(client.clone(), _m(&acc, "2018_returns")),
_2019: MetricPattern1::new(client.clone(), _m(&acc, "2019_returns")),
_2020: MetricPattern1::new(client.clone(), _m(&acc, "2020_returns")),
_2021: MetricPattern1::new(client.clone(), _m(&acc, "2021_returns")),
_2022: MetricPattern1::new(client.clone(), _m(&acc, "2022_returns")),
_2023: MetricPattern1::new(client.clone(), _m(&acc, "2023_returns")),
_2024: MetricPattern1::new(client.clone(), _m(&acc, "2024_returns")),
_2025: MetricPattern1::new(client.clone(), _m(&acc, "2025_returns")),
_2026: MetricPattern1::new(client.clone(), _m(&acc, "2026_returns")),
}
}
}
/// Pattern struct for repeated tree structure.
pub struct AverageCumulativeMaxMedianMinPct10Pct25Pct75Pct90RollingSumPattern {
pub average: MetricPattern18<StoredU64>,
@@ -2859,6 +2823,28 @@ impl InvestedMaxMinPercentilesSpotPattern {
}
}
/// Pattern struct for repeated tree structure.
pub struct EmaHistogramLineSignalPattern {
pub ema_fast: MetricPattern1<StoredF32>,
pub ema_slow: MetricPattern1<StoredF32>,
pub histogram: MetricPattern1<StoredF32>,
pub line: MetricPattern1<StoredF32>,
pub signal: MetricPattern1<StoredF32>,
}
impl EmaHistogramLineSignalPattern {
/// Create a new pattern node with accumulated metric name.
pub fn new(client: Arc<BrkClientBase>, acc: String) -> Self {
Self {
ema_fast: MetricPattern1::new(client.clone(), _m(&acc, "ema_fast_1y")),
ema_slow: MetricPattern1::new(client.clone(), _m(&acc, "ema_slow_1y")),
histogram: MetricPattern1::new(client.clone(), _m(&acc, "histogram_1y")),
line: MetricPattern1::new(client.clone(), _m(&acc, "line_1y")),
signal: MetricPattern1::new(client.clone(), _m(&acc, "signal_1y")),
}
}
}
/// Pattern struct for repeated tree structure.
pub struct _1y24h30d7dPattern2 {
pub _1y: BtcCentsSatsUsdPattern,
@@ -2991,24 +2977,6 @@ impl CentsSatsUsdPattern {
}
}
/// Pattern struct for repeated tree structure.
pub struct HistogramLineSignalPattern {
pub histogram: MetricPattern1<StoredF32>,
pub line: MetricPattern1<StoredF32>,
pub signal: MetricPattern1<StoredF32>,
}
impl HistogramLineSignalPattern {
/// Create a new pattern node with accumulated metric name.
pub fn new(client: Arc<BrkClientBase>, acc: String) -> Self {
Self {
histogram: MetricPattern1::new(client.clone(), _m(&acc, "histogram_1y")),
line: MetricPattern1::new(client.clone(), _m(&acc, "line_1y")),
signal: MetricPattern1::new(client.clone(), _m(&acc, "signal_1y")),
}
}
}
/// Pattern struct for repeated tree structure.
pub struct _6bBlockTxindexPattern<T> {
pub _6b: AverageMaxMedianMinPct10Pct25Pct75Pct90Pattern<T>,
@@ -3252,7 +3220,7 @@ impl MetricsTree_Blocks {
/// Metrics tree node.
pub struct MetricsTree_Blocks_Difficulty {
pub raw: MetricPattern1<StoredF64>,
pub as_hash: MetricPattern1<StoredF32>,
pub as_hash: MetricPattern1<StoredF64>,
pub adjustment: MetricPattern1<StoredF32>,
pub epoch: MetricPattern1<DifficultyEpoch>,
pub blocks_before_next_adjustment: MetricPattern1<StoredU32>,
@@ -3342,22 +3310,34 @@ pub struct MetricsTree_Blocks_Count {
pub height_34d_ago: MetricPattern18<Height>,
pub height_55d_ago: MetricPattern18<Height>,
pub height_2m_ago: MetricPattern18<Height>,
pub height_9w_ago: MetricPattern18<Height>,
pub height_12w_ago: MetricPattern18<Height>,
pub height_89d_ago: MetricPattern18<Height>,
pub height_3m_ago: MetricPattern18<Height>,
pub height_14w_ago: MetricPattern18<Height>,
pub height_111d_ago: MetricPattern18<Height>,
pub height_144d_ago: MetricPattern18<Height>,
pub height_3m_ago: MetricPattern18<Height>,
pub height_6m_ago: MetricPattern18<Height>,
pub height_26w_ago: MetricPattern18<Height>,
pub height_200d_ago: MetricPattern18<Height>,
pub height_9m_ago: MetricPattern18<Height>,
pub height_350d_ago: MetricPattern18<Height>,
pub height_12m_ago: MetricPattern18<Height>,
pub height_1y_ago: MetricPattern18<Height>,
pub height_14m_ago: MetricPattern18<Height>,
pub height_2y_ago: MetricPattern18<Height>,
pub height_200w_ago: MetricPattern18<Height>,
pub height_26m_ago: MetricPattern18<Height>,
pub height_3y_ago: MetricPattern18<Height>,
pub height_200w_ago: MetricPattern18<Height>,
pub height_4y_ago: MetricPattern18<Height>,
pub height_5y_ago: MetricPattern18<Height>,
pub height_6y_ago: MetricPattern18<Height>,
pub height_8y_ago: MetricPattern18<Height>,
pub height_9y_ago: MetricPattern18<Height>,
pub height_10y_ago: MetricPattern18<Height>,
pub height_12y_ago: MetricPattern18<Height>,
pub height_14y_ago: MetricPattern18<Height>,
pub height_26y_ago: MetricPattern18<Height>,
}
impl MetricsTree_Blocks_Count {
@@ -3381,22 +3361,34 @@ impl MetricsTree_Blocks_Count {
height_34d_ago: MetricPattern18::new(client.clone(), "height_34d_ago".to_string()),
height_55d_ago: MetricPattern18::new(client.clone(), "height_55d_ago".to_string()),
height_2m_ago: MetricPattern18::new(client.clone(), "height_2m_ago".to_string()),
height_9w_ago: MetricPattern18::new(client.clone(), "height_9w_ago".to_string()),
height_12w_ago: MetricPattern18::new(client.clone(), "height_12w_ago".to_string()),
height_89d_ago: MetricPattern18::new(client.clone(), "height_89d_ago".to_string()),
height_3m_ago: MetricPattern18::new(client.clone(), "height_3m_ago".to_string()),
height_14w_ago: MetricPattern18::new(client.clone(), "height_14w_ago".to_string()),
height_111d_ago: MetricPattern18::new(client.clone(), "height_111d_ago".to_string()),
height_144d_ago: MetricPattern18::new(client.clone(), "height_144d_ago".to_string()),
height_3m_ago: MetricPattern18::new(client.clone(), "height_3m_ago".to_string()),
height_6m_ago: MetricPattern18::new(client.clone(), "height_6m_ago".to_string()),
height_26w_ago: MetricPattern18::new(client.clone(), "height_26w_ago".to_string()),
height_200d_ago: MetricPattern18::new(client.clone(), "height_200d_ago".to_string()),
height_9m_ago: MetricPattern18::new(client.clone(), "height_9m_ago".to_string()),
height_350d_ago: MetricPattern18::new(client.clone(), "height_350d_ago".to_string()),
height_12m_ago: MetricPattern18::new(client.clone(), "height_12m_ago".to_string()),
height_1y_ago: MetricPattern18::new(client.clone(), "height_1y_ago".to_string()),
height_14m_ago: MetricPattern18::new(client.clone(), "height_14m_ago".to_string()),
height_2y_ago: MetricPattern18::new(client.clone(), "height_2y_ago".to_string()),
height_200w_ago: MetricPattern18::new(client.clone(), "height_200w_ago".to_string()),
height_26m_ago: MetricPattern18::new(client.clone(), "height_26m_ago".to_string()),
height_3y_ago: MetricPattern18::new(client.clone(), "height_3y_ago".to_string()),
height_200w_ago: MetricPattern18::new(client.clone(), "height_200w_ago".to_string()),
height_4y_ago: MetricPattern18::new(client.clone(), "height_4y_ago".to_string()),
height_5y_ago: MetricPattern18::new(client.clone(), "height_5y_ago".to_string()),
height_6y_ago: MetricPattern18::new(client.clone(), "height_6y_ago".to_string()),
height_8y_ago: MetricPattern18::new(client.clone(), "height_8y_ago".to_string()),
height_9y_ago: MetricPattern18::new(client.clone(), "height_9y_ago".to_string()),
height_10y_ago: MetricPattern18::new(client.clone(), "height_10y_ago".to_string()),
height_12y_ago: MetricPattern18::new(client.clone(), "height_12y_ago".to_string()),
height_14y_ago: MetricPattern18::new(client.clone(), "height_14y_ago".to_string()),
height_26y_ago: MetricPattern18::new(client.clone(), "height_26y_ago".to_string()),
}
}
}
@@ -3873,9 +3865,9 @@ impl MetricsTree_Mining_Rewards {
pub struct MetricsTree_Mining_Hashrate {
pub hash_rate: MetricPattern1<StoredF64>,
pub hash_rate_1w_sma: MetricPattern1<StoredF64>,
pub hash_rate_1m_sma: MetricPattern1<StoredF32>,
pub hash_rate_2m_sma: MetricPattern1<StoredF32>,
pub hash_rate_1y_sma: MetricPattern1<StoredF32>,
pub hash_rate_1m_sma: MetricPattern1<StoredF64>,
pub hash_rate_2m_sma: MetricPattern1<StoredF64>,
pub hash_rate_1y_sma: MetricPattern1<StoredF64>,
pub hash_rate_ath: MetricPattern1<StoredF64>,
pub hash_rate_drawdown: MetricPattern1<StoredF32>,
pub hash_price_ths: MetricPattern1<StoredF32>,
@@ -5012,25 +5004,13 @@ pub struct MetricsTree_Market_Dca {
pub dca_sats_per_day: MetricPattern18<Sats>,
pub period_stack: _10y1m1w1y2y3m3y4y5y6m6y8yPattern3,
pub period_average_price: MetricsTree_Market_Dca_PeriodAveragePrice,
pub period_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>,
pub period_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2,
pub period_cagr: _10y2y3y4y5y6y8yPattern,
pub period_days_in_profit: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredU32>,
pub period_days_in_loss: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredU32>,
pub period_min_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>,
pub period_max_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>,
pub period_lump_sum_stack: _10y1m1w1y2y3m3y4y5y6m6y8yPattern3,
pub period_lump_sum_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>,
pub period_lump_sum_days_in_profit: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredU32>,
pub period_lump_sum_days_in_loss: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredU32>,
pub period_lump_sum_min_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>,
pub period_lump_sum_max_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>,
pub period_lump_sum_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2,
pub class_stack: MetricsTree_Market_Dca_ClassStack,
pub class_average_price: MetricsTree_Market_Dca_ClassAveragePrice,
pub class_returns: _201520162017201820192020202120222023202420252026Pattern2<StoredF32>,
pub class_days_in_profit: MetricsTree_Market_Dca_ClassDaysInProfit,
pub class_days_in_loss: MetricsTree_Market_Dca_ClassDaysInLoss,
pub class_min_return: MetricsTree_Market_Dca_ClassMinReturn,
pub class_max_return: MetricsTree_Market_Dca_ClassMaxReturn,
pub class_returns: MetricsTree_Market_Dca_ClassReturns,
}
impl MetricsTree_Market_Dca {
@@ -5041,23 +5021,11 @@ impl MetricsTree_Market_Dca {
period_average_price: MetricsTree_Market_Dca_PeriodAveragePrice::new(client.clone(), format!("{base_path}_period_average_price")),
period_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "dca_returns".to_string()),
period_cagr: _10y2y3y4y5y6y8yPattern::new(client.clone(), "dca_cagr".to_string()),
period_days_in_profit: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "dca_days_in_profit".to_string()),
period_days_in_loss: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "dca_days_in_loss".to_string()),
period_min_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "dca_min_return".to_string()),
period_max_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "dca_max_return".to_string()),
period_lump_sum_stack: _10y1m1w1y2y3m3y4y5y6m6y8yPattern3::new(client.clone(), "lump_sum_stack".to_string()),
period_lump_sum_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "lump_sum_returns".to_string()),
period_lump_sum_days_in_profit: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "lump_sum_days_in_profit".to_string()),
period_lump_sum_days_in_loss: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "lump_sum_days_in_loss".to_string()),
period_lump_sum_min_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "lump_sum_min_return".to_string()),
period_lump_sum_max_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2::new(client.clone(), "lump_sum_max_return".to_string()),
class_stack: MetricsTree_Market_Dca_ClassStack::new(client.clone(), format!("{base_path}_class_stack")),
class_average_price: MetricsTree_Market_Dca_ClassAveragePrice::new(client.clone(), format!("{base_path}_class_average_price")),
class_returns: _201520162017201820192020202120222023202420252026Pattern2::new(client.clone(), "dca_class".to_string()),
class_days_in_profit: MetricsTree_Market_Dca_ClassDaysInProfit::new(client.clone(), format!("{base_path}_class_days_in_profit")),
class_days_in_loss: MetricsTree_Market_Dca_ClassDaysInLoss::new(client.clone(), format!("{base_path}_class_days_in_loss")),
class_min_return: MetricsTree_Market_Dca_ClassMinReturn::new(client.clone(), format!("{base_path}_class_min_return")),
class_max_return: MetricsTree_Market_Dca_ClassMaxReturn::new(client.clone(), format!("{base_path}_class_max_return")),
class_returns: MetricsTree_Market_Dca_ClassReturns::new(client.clone(), format!("{base_path}_class_returns")),
}
}
}
@@ -5168,77 +5136,7 @@ impl MetricsTree_Market_Dca_ClassAveragePrice {
}
/// Metrics tree node.
pub struct MetricsTree_Market_Dca_ClassDaysInProfit {
pub _2015: MetricPattern1<StoredU32>,
pub _2016: MetricPattern1<StoredU32>,
pub _2017: MetricPattern1<StoredU32>,
pub _2018: MetricPattern1<StoredU32>,
pub _2019: MetricPattern1<StoredU32>,
pub _2020: MetricPattern1<StoredU32>,
pub _2021: MetricPattern1<StoredU32>,
pub _2022: MetricPattern1<StoredU32>,
pub _2023: MetricPattern1<StoredU32>,
pub _2024: MetricPattern1<StoredU32>,
pub _2025: MetricPattern1<StoredU32>,
pub _2026: MetricPattern1<StoredU32>,
}
impl MetricsTree_Market_Dca_ClassDaysInProfit {
pub fn new(client: Arc<BrkClientBase>, base_path: String) -> Self {
Self {
_2015: MetricPattern1::new(client.clone(), "dca_class_2015_days_in_profit".to_string()),
_2016: MetricPattern1::new(client.clone(), "dca_class_2016_days_in_profit".to_string()),
_2017: MetricPattern1::new(client.clone(), "dca_class_2017_days_in_profit".to_string()),
_2018: MetricPattern1::new(client.clone(), "dca_class_2018_days_in_profit".to_string()),
_2019: MetricPattern1::new(client.clone(), "dca_class_2019_days_in_profit".to_string()),
_2020: MetricPattern1::new(client.clone(), "dca_class_2020_days_in_profit".to_string()),
_2021: MetricPattern1::new(client.clone(), "dca_class_2021_days_in_profit".to_string()),
_2022: MetricPattern1::new(client.clone(), "dca_class_2022_days_in_profit".to_string()),
_2023: MetricPattern1::new(client.clone(), "dca_class_2023_days_in_profit".to_string()),
_2024: MetricPattern1::new(client.clone(), "dca_class_2024_days_in_profit".to_string()),
_2025: MetricPattern1::new(client.clone(), "dca_class_2025_days_in_profit".to_string()),
_2026: MetricPattern1::new(client.clone(), "dca_class_2026_days_in_profit".to_string()),
}
}
}
/// Metrics tree node.
pub struct MetricsTree_Market_Dca_ClassDaysInLoss {
pub _2015: MetricPattern1<StoredU32>,
pub _2016: MetricPattern1<StoredU32>,
pub _2017: MetricPattern1<StoredU32>,
pub _2018: MetricPattern1<StoredU32>,
pub _2019: MetricPattern1<StoredU32>,
pub _2020: MetricPattern1<StoredU32>,
pub _2021: MetricPattern1<StoredU32>,
pub _2022: MetricPattern1<StoredU32>,
pub _2023: MetricPattern1<StoredU32>,
pub _2024: MetricPattern1<StoredU32>,
pub _2025: MetricPattern1<StoredU32>,
pub _2026: MetricPattern1<StoredU32>,
}
impl MetricsTree_Market_Dca_ClassDaysInLoss {
pub fn new(client: Arc<BrkClientBase>, base_path: String) -> Self {
Self {
_2015: MetricPattern1::new(client.clone(), "dca_class_2015_days_in_loss".to_string()),
_2016: MetricPattern1::new(client.clone(), "dca_class_2016_days_in_loss".to_string()),
_2017: MetricPattern1::new(client.clone(), "dca_class_2017_days_in_loss".to_string()),
_2018: MetricPattern1::new(client.clone(), "dca_class_2018_days_in_loss".to_string()),
_2019: MetricPattern1::new(client.clone(), "dca_class_2019_days_in_loss".to_string()),
_2020: MetricPattern1::new(client.clone(), "dca_class_2020_days_in_loss".to_string()),
_2021: MetricPattern1::new(client.clone(), "dca_class_2021_days_in_loss".to_string()),
_2022: MetricPattern1::new(client.clone(), "dca_class_2022_days_in_loss".to_string()),
_2023: MetricPattern1::new(client.clone(), "dca_class_2023_days_in_loss".to_string()),
_2024: MetricPattern1::new(client.clone(), "dca_class_2024_days_in_loss".to_string()),
_2025: MetricPattern1::new(client.clone(), "dca_class_2025_days_in_loss".to_string()),
_2026: MetricPattern1::new(client.clone(), "dca_class_2026_days_in_loss".to_string()),
}
}
}
/// Metrics tree node.
pub struct MetricsTree_Market_Dca_ClassMinReturn {
pub struct MetricsTree_Market_Dca_ClassReturns {
pub _2015: MetricPattern1<StoredF32>,
pub _2016: MetricPattern1<StoredF32>,
pub _2017: MetricPattern1<StoredF32>,
@@ -5253,56 +5151,21 @@ pub struct MetricsTree_Market_Dca_ClassMinReturn {
pub _2026: MetricPattern1<StoredF32>,
}
impl MetricsTree_Market_Dca_ClassMinReturn {
impl MetricsTree_Market_Dca_ClassReturns {
pub fn new(client: Arc<BrkClientBase>, base_path: String) -> Self {
Self {
_2015: MetricPattern1::new(client.clone(), "dca_class_2015_min_return".to_string()),
_2016: MetricPattern1::new(client.clone(), "dca_class_2016_min_return".to_string()),
_2017: MetricPattern1::new(client.clone(), "dca_class_2017_min_return".to_string()),
_2018: MetricPattern1::new(client.clone(), "dca_class_2018_min_return".to_string()),
_2019: MetricPattern1::new(client.clone(), "dca_class_2019_min_return".to_string()),
_2020: MetricPattern1::new(client.clone(), "dca_class_2020_min_return".to_string()),
_2021: MetricPattern1::new(client.clone(), "dca_class_2021_min_return".to_string()),
_2022: MetricPattern1::new(client.clone(), "dca_class_2022_min_return".to_string()),
_2023: MetricPattern1::new(client.clone(), "dca_class_2023_min_return".to_string()),
_2024: MetricPattern1::new(client.clone(), "dca_class_2024_min_return".to_string()),
_2025: MetricPattern1::new(client.clone(), "dca_class_2025_min_return".to_string()),
_2026: MetricPattern1::new(client.clone(), "dca_class_2026_min_return".to_string()),
}
}
}
/// Metrics tree node.
pub struct MetricsTree_Market_Dca_ClassMaxReturn {
pub _2015: MetricPattern1<StoredF32>,
pub _2016: MetricPattern1<StoredF32>,
pub _2017: MetricPattern1<StoredF32>,
pub _2018: MetricPattern1<StoredF32>,
pub _2019: MetricPattern1<StoredF32>,
pub _2020: MetricPattern1<StoredF32>,
pub _2021: MetricPattern1<StoredF32>,
pub _2022: MetricPattern1<StoredF32>,
pub _2023: MetricPattern1<StoredF32>,
pub _2024: MetricPattern1<StoredF32>,
pub _2025: MetricPattern1<StoredF32>,
pub _2026: MetricPattern1<StoredF32>,
}
impl MetricsTree_Market_Dca_ClassMaxReturn {
pub fn new(client: Arc<BrkClientBase>, base_path: String) -> Self {
Self {
_2015: MetricPattern1::new(client.clone(), "dca_class_2015_max_return".to_string()),
_2016: MetricPattern1::new(client.clone(), "dca_class_2016_max_return".to_string()),
_2017: MetricPattern1::new(client.clone(), "dca_class_2017_max_return".to_string()),
_2018: MetricPattern1::new(client.clone(), "dca_class_2018_max_return".to_string()),
_2019: MetricPattern1::new(client.clone(), "dca_class_2019_max_return".to_string()),
_2020: MetricPattern1::new(client.clone(), "dca_class_2020_max_return".to_string()),
_2021: MetricPattern1::new(client.clone(), "dca_class_2021_max_return".to_string()),
_2022: MetricPattern1::new(client.clone(), "dca_class_2022_max_return".to_string()),
_2023: MetricPattern1::new(client.clone(), "dca_class_2023_max_return".to_string()),
_2024: MetricPattern1::new(client.clone(), "dca_class_2024_max_return".to_string()),
_2025: MetricPattern1::new(client.clone(), "dca_class_2025_max_return".to_string()),
_2026: MetricPattern1::new(client.clone(), "dca_class_2026_max_return".to_string()),
_2015: MetricPattern1::new(client.clone(), "dca_class_2015_returns".to_string()),
_2016: MetricPattern1::new(client.clone(), "dca_class_2016_returns".to_string()),
_2017: MetricPattern1::new(client.clone(), "dca_class_2017_returns".to_string()),
_2018: MetricPattern1::new(client.clone(), "dca_class_2018_returns".to_string()),
_2019: MetricPattern1::new(client.clone(), "dca_class_2019_returns".to_string()),
_2020: MetricPattern1::new(client.clone(), "dca_class_2020_returns".to_string()),
_2021: MetricPattern1::new(client.clone(), "dca_class_2021_returns".to_string()),
_2022: MetricPattern1::new(client.clone(), "dca_class_2022_returns".to_string()),
_2023: MetricPattern1::new(client.clone(), "dca_class_2023_returns".to_string()),
_2024: MetricPattern1::new(client.clone(), "dca_class_2024_returns".to_string()),
_2025: MetricPattern1::new(client.clone(), "dca_class_2025_returns".to_string()),
_2026: MetricPattern1::new(client.clone(), "dca_class_2026_returns".to_string()),
}
}
}
@@ -5451,7 +5314,7 @@ pub struct MetricsTree_Market_Indicators_Macd {
pub _1d: MetricsTree_Market_Indicators_Macd_1d,
pub _1w: MetricsTree_Market_Indicators_Macd_1w,
pub _1m: MetricsTree_Market_Indicators_Macd_1m,
pub _1y: HistogramLineSignalPattern,
pub _1y: EmaHistogramLineSignalPattern,
}
impl MetricsTree_Market_Indicators_Macd {
@@ -5460,13 +5323,15 @@ impl MetricsTree_Market_Indicators_Macd {
_1d: MetricsTree_Market_Indicators_Macd_1d::new(client.clone(), format!("{base_path}_1d")),
_1w: MetricsTree_Market_Indicators_Macd_1w::new(client.clone(), format!("{base_path}_1w")),
_1m: MetricsTree_Market_Indicators_Macd_1m::new(client.clone(), format!("{base_path}_1m")),
_1y: HistogramLineSignalPattern::new(client.clone(), "macd".to_string()),
_1y: EmaHistogramLineSignalPattern::new(client.clone(), "macd".to_string()),
}
}
}
/// Metrics tree node.
pub struct MetricsTree_Market_Indicators_Macd_1d {
pub ema_fast: MetricPattern1<StoredF32>,
pub ema_slow: MetricPattern1<StoredF32>,
pub line: MetricPattern1<StoredF32>,
pub signal: MetricPattern1<StoredF32>,
pub histogram: MetricPattern1<StoredF32>,
@@ -5475,6 +5340,8 @@ pub struct MetricsTree_Market_Indicators_Macd_1d {
impl MetricsTree_Market_Indicators_Macd_1d {
pub fn new(client: Arc<BrkClientBase>, base_path: String) -> Self {
Self {
ema_fast: MetricPattern1::new(client.clone(), "macd_ema_fast_1d".to_string()),
ema_slow: MetricPattern1::new(client.clone(), "macd_ema_slow_1d".to_string()),
line: MetricPattern1::new(client.clone(), "macd_line_1d".to_string()),
signal: MetricPattern1::new(client.clone(), "macd_signal_1d".to_string()),
histogram: MetricPattern1::new(client.clone(), "macd_histogram_1d".to_string()),
@@ -5484,6 +5351,8 @@ impl MetricsTree_Market_Indicators_Macd_1d {
/// Metrics tree node.
pub struct MetricsTree_Market_Indicators_Macd_1w {
pub ema_fast: MetricPattern1<StoredF32>,
pub ema_slow: MetricPattern1<StoredF32>,
pub line: MetricPattern1<StoredF32>,
pub signal: MetricPattern1<StoredF32>,
pub histogram: MetricPattern1<StoredF32>,
@@ -5492,6 +5361,8 @@ pub struct MetricsTree_Market_Indicators_Macd_1w {
impl MetricsTree_Market_Indicators_Macd_1w {
pub fn new(client: Arc<BrkClientBase>, base_path: String) -> Self {
Self {
ema_fast: MetricPattern1::new(client.clone(), "macd_ema_fast_1w".to_string()),
ema_slow: MetricPattern1::new(client.clone(), "macd_ema_slow_1w".to_string()),
line: MetricPattern1::new(client.clone(), "macd_line_1w".to_string()),
signal: MetricPattern1::new(client.clone(), "macd_signal_1w".to_string()),
histogram: MetricPattern1::new(client.clone(), "macd_histogram_1w".to_string()),
@@ -5501,6 +5372,8 @@ impl MetricsTree_Market_Indicators_Macd_1w {
/// Metrics tree node.
pub struct MetricsTree_Market_Indicators_Macd_1m {
pub ema_fast: MetricPattern1<StoredF32>,
pub ema_slow: MetricPattern1<StoredF32>,
pub line: MetricPattern1<StoredF32>,
pub signal: MetricPattern1<StoredF32>,
pub histogram: MetricPattern1<StoredF32>,
@@ -5509,6 +5382,8 @@ pub struct MetricsTree_Market_Indicators_Macd_1m {
impl MetricsTree_Market_Indicators_Macd_1m {
pub fn new(client: Arc<BrkClientBase>, base_path: String) -> Self {
Self {
ema_fast: MetricPattern1::new(client.clone(), "macd_ema_fast_1m".to_string()),
ema_slow: MetricPattern1::new(client.clone(), "macd_ema_slow_1m".to_string()),
line: MetricPattern1::new(client.clone(), "macd_line_1m".to_string()),
signal: MetricPattern1::new(client.clone(), "macd_signal_1m".to_string()),
histogram: MetricPattern1::new(client.clone(), "macd_histogram_1m".to_string()),
crates/brk_computer/src/blocks/count/compute.rs
+63 -67
View File
@@ -72,97 +72,93 @@ impl Vecs {
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 55, |s| {
&mut s.height_55d_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 2 * 30, |s| {
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 60, |s| {
&mut s.height_2m_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 63, |s| {
&mut s.height_9w_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 84, |s| {
&mut s.height_12w_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 89, |s| {
&mut s.height_89d_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 3 * 30, |s| {
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 90, |s| {
&mut s.height_3m_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 98, |s| {
&mut s.height_14w_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 111, |s| {
&mut s.height_111d_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 144, |s| {
&mut s.height_144d_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 6 * 30, |s| {
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 180, |s| {
&mut s.height_6m_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 182, |s| {
&mut s.height_26w_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 200, |s| {
&mut s.height_200d_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 270, |s| {
&mut s.height_9m_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 350, |s| {
&mut s.height_350d_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 360, |s| {
&mut s.height_12m_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 365, |s| {
&mut s.height_1y_ago
})?;
self.compute_rolling_start(
&monotonic_data,
time,
starting_indexes,
exit,
2 * 365,
|s| &mut s.height_2y_ago,
)?;
self.compute_rolling_start(
&monotonic_data,
time,
starting_indexes,
exit,
200 * 7,
|s| &mut s.height_200w_ago,
)?;
self.compute_rolling_start(
&monotonic_data,
time,
starting_indexes,
exit,
3 * 365,
|s| &mut s.height_3y_ago,
)?;
self.compute_rolling_start(
&monotonic_data,
time,
starting_indexes,
exit,
4 * 365,
|s| &mut s.height_4y_ago,
)?;
self.compute_rolling_start(
&monotonic_data,
time,
starting_indexes,
exit,
5 * 365,
|s| &mut s.height_5y_ago,
)?;
self.compute_rolling_start(
&monotonic_data,
time,
starting_indexes,
exit,
6 * 365,
|s| &mut s.height_6y_ago,
)?;
self.compute_rolling_start(
&monotonic_data,
time,
starting_indexes,
exit,
8 * 365,
|s| &mut s.height_8y_ago,
)?;
self.compute_rolling_start(
&monotonic_data,
time,
starting_indexes,
exit,
10 * 365,
|s| &mut s.height_10y_ago,
)?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 420, |s| {
&mut s.height_14m_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 730, |s| {
&mut s.height_2y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 780, |s| {
&mut s.height_26m_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 1095, |s| {
&mut s.height_3y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 1400, |s| {
&mut s.height_200w_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 1460, |s| {
&mut s.height_4y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 1825, |s| {
&mut s.height_5y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 2190, |s| {
&mut s.height_6y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 2920, |s| {
&mut s.height_8y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 3285, |s| {
&mut s.height_9y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 3650, |s| {
&mut s.height_10y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 4380, |s| {
&mut s.height_12y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 5110, |s| {
&mut s.height_14y_ago
})?;
self.compute_rolling_start(&monotonic_data, time, starting_indexes, exit, 9490, |s| {
&mut s.height_26y_ago
})?;
// Compute rolling window block counts (both block_count's own rolling + separate block_count_sum)
let ws = crate::internal::WindowStarts {
crates/brk_computer/src/blocks/count/import.rs
+14 -2
View File
@@ -37,22 +37,34 @@ impl Vecs {
height_34d_ago: ImportableVec::forced_import(db, "height_34d_ago", version)?,
height_55d_ago: ImportableVec::forced_import(db, "height_55d_ago", version)?,
height_2m_ago: ImportableVec::forced_import(db, "height_2m_ago", version)?,
height_9w_ago: ImportableVec::forced_import(db, "height_9w_ago", version)?,
height_12w_ago: ImportableVec::forced_import(db, "height_12w_ago", version)?,
height_89d_ago: ImportableVec::forced_import(db, "height_89d_ago", version)?,
height_3m_ago: ImportableVec::forced_import(db, "height_3m_ago", version)?,
height_14w_ago: ImportableVec::forced_import(db, "height_14w_ago", version)?,
height_111d_ago: ImportableVec::forced_import(db, "height_111d_ago", version)?,
height_144d_ago: ImportableVec::forced_import(db, "height_144d_ago", version)?,
height_3m_ago: ImportableVec::forced_import(db, "height_3m_ago", version)?,
height_6m_ago: ImportableVec::forced_import(db, "height_6m_ago", version)?,
height_26w_ago: ImportableVec::forced_import(db, "height_26w_ago", version)?,
height_200d_ago: ImportableVec::forced_import(db, "height_200d_ago", version)?,
height_9m_ago: ImportableVec::forced_import(db, "height_9m_ago", version)?,
height_350d_ago: ImportableVec::forced_import(db, "height_350d_ago", version)?,
height_12m_ago: ImportableVec::forced_import(db, "height_12m_ago", version)?,
height_1y_ago: ImportableVec::forced_import(db, "height_1y_ago", version)?,
height_14m_ago: ImportableVec::forced_import(db, "height_14m_ago", version)?,
height_2y_ago: ImportableVec::forced_import(db, "height_2y_ago", version)?,
height_200w_ago: ImportableVec::forced_import(db, "height_200w_ago", version)?,
height_26m_ago: ImportableVec::forced_import(db, "height_26m_ago", version)?,
height_3y_ago: ImportableVec::forced_import(db, "height_3y_ago", version)?,
height_200w_ago: ImportableVec::forced_import(db, "height_200w_ago", version)?,
height_4y_ago: ImportableVec::forced_import(db, "height_4y_ago", version)?,
height_5y_ago: ImportableVec::forced_import(db, "height_5y_ago", version)?,
height_6y_ago: ImportableVec::forced_import(db, "height_6y_ago", version)?,
height_8y_ago: ImportableVec::forced_import(db, "height_8y_ago", version)?,
height_9y_ago: ImportableVec::forced_import(db, "height_9y_ago", version)?,
height_10y_ago: ImportableVec::forced_import(db, "height_10y_ago", version)?,
height_12y_ago: ImportableVec::forced_import(db, "height_12y_ago", version)?,
height_14y_ago: ImportableVec::forced_import(db, "height_14y_ago", version)?,
height_26y_ago: ImportableVec::forced_import(db, "height_26y_ago", version)?,
block_count_sum: RollingWindows::forced_import(
db,
"block_count_sum",
crates/brk_computer/src/blocks/count/vecs.rs
+41 -16
View File
@@ -12,37 +12,50 @@ pub struct Vecs<M: StorageMode = Rw> {
pub block_count: ComputedFromHeightCumulativeSum<StoredU32, M>,
pub block_count_sum: RollingWindows<StoredU32, M>,
// Window starts sorted by duration
pub height_1h_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_24h_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_24h_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 1d
pub height_3d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_1w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_1w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 7d
pub height_8d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_9d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_12d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_13d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_2w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_2w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 14d
pub height_21d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_26d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_1m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_1m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 30d
pub height_34d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_55d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_2m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_2m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 60d
pub height_9w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 63d
pub height_12w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 84d
pub height_89d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_3m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 90d
pub height_14w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 98d
pub height_111d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_144d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_3m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_6m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_6m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 180d
pub height_26w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 182d
pub height_200d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_9m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 270d
pub height_350d_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_1y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_2y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_200w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_3y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_4y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_5y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_6y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_8y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_10y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>,
pub height_12m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 360d
pub height_1y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 365d
pub height_14m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 420d
pub height_2y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 730d
pub height_26m_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 780d
pub height_3y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 1095d
pub height_200w_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 1400d
pub height_4y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 1460d
pub height_5y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 1825d
pub height_6y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 2190d
pub height_8y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 2920d
pub height_9y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 3285d
pub height_10y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 3650d
pub height_12y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 4380d
pub height_14y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 5110d
pub height_26y_ago: M::Stored<EagerVec<PcoVec<Height, Height>>>, // 9490d
}
impl Vecs {
@@ -72,22 +85,34 @@ impl Vecs {
34 => &self.height_34d_ago,
55 => &self.height_55d_ago,
60 => &self.height_2m_ago,
63 => &self.height_9w_ago,
84 => &self.height_12w_ago,
89 => &self.height_89d_ago,
90 => &self.height_3m_ago,
98 => &self.height_14w_ago,
111 => &self.height_111d_ago,
144 => &self.height_144d_ago,
180 => &self.height_6m_ago,
182 => &self.height_26w_ago,
200 => &self.height_200d_ago,
270 => &self.height_9m_ago,
350 => &self.height_350d_ago,
360 => &self.height_12m_ago,
365 => &self.height_1y_ago,
420 => &self.height_14m_ago,
730 => &self.height_2y_ago,
780 => &self.height_26m_ago,
1095 => &self.height_3y_ago,
1400 => &self.height_200w_ago,
1460 => &self.height_4y_ago,
1825 => &self.height_5y_ago,
2190 => &self.height_6y_ago,
2920 => &self.height_8y_ago,
3285 => &self.height_9y_ago,
3650 => &self.height_10y_ago,
4380 => &self.height_12y_ago,
5110 => &self.height_14y_ago,
9490 => &self.height_26y_ago,
_ => panic!("No start vec for {days} days"),
}
}
crates/brk_computer/src/blocks/difficulty/compute.rs
+2 -2
View File
@@ -1,6 +1,6 @@
use brk_error::Result;
use brk_indexer::Indexer;
use brk_types::{StoredF32, StoredU32};
use brk_types::{StoredF64, StoredU32};
use vecdb::Exit;
use super::super::TARGET_BLOCKS_PER_DAY_F32;
@@ -22,7 +22,7 @@ impl Vecs {
self.as_hash.height.compute_transform(
starting_indexes.height,
&indexer.vecs.blocks.difficulty,
|(i, v, ..)| (i, StoredF32::from(*v * multiplier)),
|(i, v, ..)| (i, StoredF64::from(*v * multiplier)),
exit,
)?;
crates/brk_computer/src/blocks/difficulty/vecs.rs
+1 -1
View File
@@ -8,7 +8,7 @@ use crate::internal::{ComputedFromHeight, ComputedHeightDerived};
#[derive(Traversable)]
pub struct Vecs<M: StorageMode = Rw> {
pub raw: ComputedHeightDerived<StoredF64>,
pub as_hash: ComputedFromHeight<StoredF32, M>,
pub as_hash: ComputedFromHeight<StoredF64, M>,
pub adjustment: ComputedFromHeight<StoredF32, M>,
pub epoch: ComputedFromHeight<DifficultyEpoch, M>,
pub blocks_before_next_adjustment: ComputedFromHeight<StoredU32, M>,
crates/brk_computer/src/distribution/compute/block_loop.rs
+16 -13
View File
@@ -48,6 +48,7 @@ pub(crate) fn process_blocks(
starting_height: Height,
last_height: Height,
chain_state: &mut Vec<BlockState>,
txindex_to_height: &mut RangeMap<TxIndex, Height>,
exit: &Exit,
) -> Result<()> {
// Create computation context with pre-computed vectors for thread-safe access
@@ -110,26 +111,28 @@ pub(crate) fn process_blocks(
let mut vr = VecsReaders::new(&vecs.any_address_indexes, &vecs.addresses_data);
debug!("VecsReaders created");
// Build txindex -> height lookup map for efficient prev_height computation
debug!("building txindex_to_height RangeMap");
let mut txindex_to_height: RangeMap<TxIndex, Height> = {
let first_txindex_len = indexer.vecs.transactions.first_txindex.len();
let all_first_txindexes: Vec<TxIndex> = indexer
// Extend txindex_to_height RangeMap with new entries (incremental, O(new_blocks))
let target_len = indexer.vecs.transactions.first_txindex.len();
let current_len = txindex_to_height.len();
if current_len < target_len {
debug!("extending txindex_to_height RangeMap from {} to {}", current_len, target_len);
let new_entries: Vec<TxIndex> = indexer
.vecs
.transactions
.first_txindex
.collect_range_at(0, first_txindex_len);
let mut map = RangeMap::with_capacity(first_txindex_len);
for first_txindex in all_first_txindexes {
map.push(first_txindex);
.collect_range_at(current_len, target_len);
for first_txindex in new_entries {
txindex_to_height.push(first_txindex);
}
map
};
debug!("txindex_to_height RangeMap built");
} else if current_len > target_len {
debug!("truncating txindex_to_height RangeMap from {} to {}", current_len, target_len);
txindex_to_height.truncate(target_len);
}
debug!("txindex_to_height RangeMap ready ({} entries)", txindex_to_height.len());
// Create reusable iterators and buffers for per-block reads
let mut txout_iters = TxOutReaders::new(indexer);
let mut txin_iters = TxInReaders::new(indexer, inputs, &mut txindex_to_height);
let mut txin_iters = TxInReaders::new(indexer, inputs, txindex_to_height);
let mut txout_to_txindex_buf = IndexToTxIndexBuf::new();
let mut txin_to_txindex_buf = IndexToTxIndexBuf::new();
crates/brk_computer/src/distribution/range_map.rs
+12 -1
View File
@@ -12,7 +12,7 @@ const CACHE_SIZE: usize = 8;
///
/// Includes an LRU cache of recently accessed ranges to avoid binary search
/// when there's locality in access patterns.
#[derive(Debug)]
#[derive(Debug, Clone)]
pub struct RangeMap<I, V> {
/// Sorted vec of first_index values. Position in vec = value.
first_indexes: Vec<I>,
@@ -44,6 +44,17 @@ impl<I: Ord + Copy + Default, V: From<usize> + Copy + Default> RangeMap<I, V> {
}
}
/// Number of ranges stored.
pub(crate) fn len(&self) -> usize {
self.first_indexes.len()
}
/// Truncate to `new_len` ranges and clear the cache.
pub(crate) fn truncate(&mut self, new_len: usize) {
self.first_indexes.truncate(new_len);
self.cache_len = 0;
}
/// Push a new first_index. Value is implicitly the current length.
/// Must be called in order (first_index must be >= all previous).
#[inline]
crates/brk_computer/src/distribution/vecs.rs
+40 -10
View File
@@ -5,7 +5,7 @@ use brk_indexer::Indexer;
use brk_traversable::Traversable;
use brk_types::{
Day1, EmptyAddressData, EmptyAddressIndex, FundedAddressData, FundedAddressIndex, Height,
SupplyState, Version,
SupplyState, TxIndex, Version,
};
use tracing::{debug, info};
use vecdb::{
@@ -23,7 +23,7 @@ use crate::{
};
use super::{
AddressCohorts, AddressesDataVecs, AnyAddressIndexesVecs, UTXOCohorts,
AddressCohorts, AddressesDataVecs, AnyAddressIndexesVecs, RangeMap, UTXOCohorts,
address::{
AddrCountsVecs, AddressActivityVecs, GrowthRateVecs, NewAddrCountVecs, TotalAddrCountVecs,
},
@@ -61,6 +61,14 @@ pub struct Vecs<M: StorageMode = Rw> {
LazyVecFrom1<FundedAddressIndex, FundedAddressIndex, FundedAddressIndex, FundedAddressData>,
pub emptyaddressindex:
LazyVecFrom1<EmptyAddressIndex, EmptyAddressIndex, EmptyAddressIndex, EmptyAddressData>,
/// In-memory block state for UTXO processing. Persisted via supply_state.
/// Kept across compute() calls to avoid O(n) rebuild on resume.
#[traversable(skip)]
chain_state: Vec<BlockState>,
/// In-memory txindex→height reverse lookup. Kept across compute() calls.
#[traversable(skip)]
txindex_to_height: RangeMap<TxIndex, Height>,
}
const SAVED_STAMPED_CHANGES: u16 = 10;
@@ -148,6 +156,9 @@ impl Vecs {
fundedaddressindex,
emptyaddressindex,
chain_state: Vec::new(),
txindex_to_height: RangeMap::default(),
db,
states_path,
};
@@ -230,8 +241,12 @@ impl Vecs {
debug!("recovered_height={}", recovered_height);
// Fresh start: reset all state
let (starting_height, mut chain_state) = if recovered_height.is_zero() {
// Take chain_state and txindex_to_height out of self to avoid borrow conflicts
let mut chain_state = std::mem::take(&mut self.chain_state);
let mut txindex_to_height = std::mem::take(&mut self.txindex_to_height);
// Recover or reuse chain_state
let starting_height = if recovered_height.is_zero() {
self.supply_state.reset()?;
self.addr_count.reset_height()?;
self.empty_addr_count.reset_height()?;
@@ -243,11 +258,18 @@ impl Vecs {
&mut self.address_cohorts,
)?;
chain_state.clear();
txindex_to_height.truncate(0);
info!("State recovery: fresh start");
(Height::ZERO, vec![])
Height::ZERO
} else if chain_state.len() == usize::from(recovered_height) {
// Normal resume: chain_state already matches, reuse as-is
debug!("reusing in-memory chain_state ({} entries)", chain_state.len());
recovered_height
} else {
// Recover chain_state from stored values
debug!("recovering chain_state from stored values");
// Rollback or first run after restart: rebuild from supply_state
debug!("rebuilding chain_state from stored values");
let height_to_timestamp = &blocks.time.timestamp_monotonic;
let height_to_price = &prices.price.cents.height;
@@ -257,7 +279,7 @@ impl Vecs {
debug!("building supply_state vec for {} heights", recovered_height);
let supply_state_data: Vec<_> = self.supply_state.collect_range_at(0, end);
let chain_state = supply_state_data
chain_state = supply_state_data
.into_iter()
.enumerate()
.map(|(h, supply)| BlockState {
@@ -266,9 +288,12 @@ impl Vecs {
timestamp: timestamp_data[h],
})
.collect();
debug!("chain_state vec built");
debug!("chain_state rebuilt");
(recovered_height, chain_state)
// Truncate RangeMap to match (entries are immutable, safe to keep)
txindex_to_height.truncate(end);
recovered_height
};
// Update starting_indexes if we need to recompute from an earlier point
@@ -316,10 +341,15 @@ impl Vecs {
starting_height,
last_height,
&mut chain_state,
&mut txindex_to_height,
exit,
)?;
}
// Put chain_state and txindex_to_height back
self.chain_state = chain_state;
self.txindex_to_height = txindex_to_height;
// 5. Compute aggregates (overlapping cohorts from separate cohorts)
aggregates::compute_overlapping(
&mut self.utxo_cohorts,
crates/brk_computer/src/internal/from_height/bps.rs
+46
View File
@@ -0,0 +1,46 @@
use brk_error::Result;
use brk_traversable::Traversable;
use brk_types::{StoredF32, Version};
use schemars::JsonSchema;
use vecdb::{Database, ReadableCloneableVec, Rw, StorageMode, UnaryTransform};
use crate::indexes;
use super::{ComputedFromHeight, LazyFromHeight};
use crate::internal::NumericValue;
/// Basis-point storage with lazy float view.
///
/// Stores integer basis points on disk (Pco-compressed),
/// exposes a lazy StoredF32 view (bps / 100).
#[derive(Traversable)]
pub struct BpsFromHeight<B, M: StorageMode = Rw>
where
B: NumericValue + JsonSchema,
{
pub bps: ComputedFromHeight<B, M>,
pub float: LazyFromHeight<StoredF32, B>,
}
impl<B> BpsFromHeight<B>
where
B: NumericValue + JsonSchema,
{
pub(crate) fn forced_import<F: UnaryTransform<B, StoredF32>>(
db: &Database,
name: &str,
version: Version,
indexes: &indexes::Vecs,
) -> Result<Self> {
let bps = ComputedFromHeight::forced_import(db, name, version, indexes)?;
let float = LazyFromHeight::from_computed::<F>(
&format!("{name}_float"),
version,
bps.height.read_only_boxed_clone(),
&bps,
);
Ok(Self { bps, float })
}
}
crates/brk_computer/src/internal/from_height/mod.rs
+2
View File
@@ -1,5 +1,6 @@
mod aggregated;
mod base;
mod bps;
mod by_unit;
mod constant;
mod cumulative;
@@ -16,6 +17,7 @@ mod value;
pub use aggregated::*;
pub use base::*;
pub use bps::*;
pub use by_unit::*;
pub use constant::*;
pub use cumulative::*;
crates/brk_computer/src/internal/from_height/ratio/extension.rs
+73 -56
View File
@@ -7,7 +7,6 @@ use crate::{
ComputeIndexes, blocks, indexes,
internal::{ComputedFromHeightStdDevExtended, Price},
};
use brk_types::get_percentile;
use super::super::ComputedFromHeight;
@@ -34,7 +33,7 @@ pub struct ComputedFromHeightRatioExtension<M: StorageMode = Rw> {
pub ratio_1y_sd: ComputedFromHeightStdDevExtended<M>,
}
const VERSION: Version = Version::TWO;
const VERSION: Version = Version::new(3);
impl ComputedFromHeightRatioExtension {
pub(crate) fn forced_import(
@@ -119,7 +118,8 @@ impl ComputedFromHeightRatioExtension {
exit,
)?;
// Percentiles: insert into sorted array on day boundaries
// Percentiles via order-statistic Fenwick tree with coordinate compression.
// O(n log n) total vs O(n²) for the naive sorted-insert approach.
let ratio_version = ratio_source.version();
self.mut_ratio_vecs()
.try_for_each(|v| -> Result<()> {
@@ -135,68 +135,85 @@ impl ComputedFromHeightRatioExtension {
.min(starting_indexes.height);
let start = starting_height.to_usize();
let day_start = &blocks.count.height_24h_ago;
let ratio_len = ratio_source.len();
// Collect sorted history up to starting point (one per day boundary)
let mut sorted = {
let ratio_data = ratio_source.collect_range_at(0, start);
let day_start_hist = day_start.collect_range_at(0, start);
let mut sorted: Vec<StoredF32> = Vec::new();
let mut last_day_start = Height::from(0_usize);
for (h, ratio) in ratio_data.into_iter().enumerate() {
let cur_day_start = day_start_hist[h];
if h == 0 || cur_day_start != last_day_start {
sorted.push(ratio);
last_day_start = cur_day_start;
if ratio_len > start {
let all_ratios = ratio_source.collect_range_at(0, ratio_len);
// Coordinate compression: unique sorted values → integer ranks
let coords = {
let mut c = all_ratios.clone();
c.sort_unstable();
c.dedup();
c
};
let m = coords.len();
// Build Fenwick tree (BIT) from elements [0, start) in O(m)
let mut bit = vec![0u32; m + 1]; // 1-indexed
for &v in &all_ratios[..start] {
bit[coords.binary_search(&v).unwrap() + 1] += 1;
}
for i in 1..=m {
let j = i + (i & i.wrapping_neg());
if j <= m {
bit[j] += bit[i];
}
}
sorted.sort_unstable();
sorted
};
let pct1_vec = &mut self.ratio_pct1.height;
let pct2_vec = &mut self.ratio_pct2.height;
let pct5_vec = &mut self.ratio_pct5.height;
let pct95_vec = &mut self.ratio_pct95.height;
let pct98_vec = &mut self.ratio_pct98.height;
let pct99_vec = &mut self.ratio_pct99.height;
// Highest power of 2 <= m (for binary-lifting kth query)
let log2 = {
let mut b = 1usize;
while b <= m {
b <<= 1;
}
b >> 1
};
let ratio_len = ratio_source.len();
let ratio_data = ratio_source.collect_range_at(start, ratio_len);
let mut last_day_start = if start > 0 {
day_start
.collect_one_at(start - 1)
.unwrap_or(Height::from(0_usize))
} else {
Height::from(0_usize)
};
// Find rank of k-th smallest element (k is 1-indexed) in O(log m)
let kth = |bit: &[u32], mut k: u32| -> usize {
let mut pos = 0;
let mut b = log2;
while b > 0 {
let next = pos + b;
if next <= m && bit[next] < k {
k -= bit[next];
pos = next;
}
b >>= 1;
}
pos
};
let day_start_data = day_start.collect_range_at(start, ratio_len);
let mut pct_vecs: [&mut EagerVec<PcoVec<Height, StoredF32>>; 6] = [
&mut self.ratio_pct1.height,
&mut self.ratio_pct2.height,
&mut self.ratio_pct5.height,
&mut self.ratio_pct95.height,
&mut self.ratio_pct98.height,
&mut self.ratio_pct99.height,
];
const PCTS: [f64; 6] = [0.01, 0.02, 0.05, 0.95, 0.98, 0.99];
for (offset, ratio) in ratio_data.into_iter().enumerate() {
let index = start + offset;
let mut count = start;
for (offset, &ratio) in all_ratios[start..].iter().enumerate() {
count += 1;
let cur_day_start = day_start_data[offset];
if index == 0 || cur_day_start != last_day_start {
let pos = sorted.binary_search(&ratio).unwrap_or_else(|p| p);
sorted.insert(pos, ratio);
last_day_start = cur_day_start;
}
// Insert into Fenwick tree: O(log m)
let mut i = coords.binary_search(&ratio).unwrap() + 1;
while i <= m {
bit[i] += 1;
i += i & i.wrapping_neg();
}
if sorted.is_empty() {
pct1_vec.truncate_push_at(index, StoredF32::NAN)?;
pct2_vec.truncate_push_at(index, StoredF32::NAN)?;
pct5_vec.truncate_push_at(index, StoredF32::NAN)?;
pct95_vec.truncate_push_at(index, StoredF32::NAN)?;
pct98_vec.truncate_push_at(index, StoredF32::NAN)?;
pct99_vec.truncate_push_at(index, StoredF32::NAN)?;
} else {
pct1_vec.truncate_push_at(index, get_percentile(&sorted, 0.01))?;
pct2_vec.truncate_push_at(index, get_percentile(&sorted, 0.02))?;
pct5_vec.truncate_push_at(index, get_percentile(&sorted, 0.05))?;
pct95_vec.truncate_push_at(index, get_percentile(&sorted, 0.95))?;
pct98_vec.truncate_push_at(index, get_percentile(&sorted, 0.98))?;
pct99_vec.truncate_push_at(index, get_percentile(&sorted, 0.99))?;
// Nearest-rank percentile: one kth query each
let idx = start + offset;
let cf = count as f64;
for (vec, &pct) in pct_vecs.iter_mut().zip(PCTS.iter()) {
let k = (cf * pct).ceil().max(1.0) as u32;
let val = coords[kth(&bit, k)];
vec.truncate_push_at(idx, val)?;
}
}
}
crates/brk_computer/src/internal/from_height/stddev/mod.rs
+17 -112
View File
@@ -5,7 +5,7 @@ pub use extended::*;
use brk_error::Result;
use brk_traversable::Traversable;
use brk_types::{Height, StoredF32, Version};
use vecdb::{AnyStoredVec, AnyVec, Database, Exit, ReadableVec, Rw, StorageMode, VecIndex, WritableVec};
use vecdb::{Database, Exit, ReadableVec, Rw, StorageMode};
use crate::{ComputeIndexes, blocks, indexes};
@@ -51,118 +51,23 @@ impl ComputedFromHeightStdDev {
exit: &Exit,
source: &impl ReadableVec<Height, StoredF32>,
) -> Result<()> {
// 1. Compute SMA using the appropriate lookback vec (or full-history SMA)
if self.days != usize::MAX {
let window_starts = blocks.count.start_vec(self.days);
self.sma.height.compute_rolling_average(
starting_indexes.height,
window_starts,
source,
exit,
)?;
} else {
// Full history SMA (days == usize::MAX)
self.sma.height.compute_sma_(
starting_indexes.height,
source,
self.days,
exit,
None,
)?;
}
let window_starts = blocks.count.start_vec(self.days);
// Split borrows: sd is mutated, sma is read
compute_sd(
&mut self.sd,
blocks,
starting_indexes,
exit,
&self.sma.height,
self.sma.height.compute_rolling_average(
starting_indexes.height,
window_starts,
source,
)
exit,
)?;
self.sd.height.compute_rolling_sd(
starting_indexes.height,
window_starts,
source,
&self.sma.height,
exit,
)?;
Ok(())
}
}
fn compute_sd(
sd: &mut ComputedFromHeight<StoredF32>,
blocks: &blocks::Vecs,
starting_indexes: &ComputeIndexes,
exit: &Exit,
sma: &impl ReadableVec<Height, StoredF32>,
source: &impl ReadableVec<Height, StoredF32>,
) -> Result<()> {
let source_version = source.version();
sd.height
.validate_computed_version_or_reset(source_version)?;
let starting_height = Height::from(sd.height.len()).min(starting_indexes.height);
let day_start = &blocks.count.height_24h_ago;
let start = starting_height.to_usize();
let mut n: usize = 0;
let mut welford_sum: f64 = 0.0;
let mut welford_sum_sq: f64 = 0.0;
if start > 0 {
let day_start_hist = day_start.collect_range_at(0, start);
let source_hist = source.collect_range_at(0, start);
let mut last_ds = Height::from(0_usize);
for h in 0..start {
let cur_ds = day_start_hist[h];
if h == 0 || cur_ds != last_ds {
let val = *source_hist[h] as f64;
n += 1;
welford_sum += val;
welford_sum_sq += val * val;
last_ds = cur_ds;
}
}
}
let source_len = source.len();
let source_data = source.collect_range_at(start, source_len);
let sma_data = sma.collect_range_at(start, sma.len());
let mut last_day_start = if start > 0 {
day_start
.collect_one_at(start - 1)
.unwrap_or(Height::from(0_usize))
} else {
Height::from(0_usize)
};
let day_start_data = day_start.collect_range_at(start, source_len);
for (offset, ratio) in source_data.into_iter().enumerate() {
let index = start + offset;
let cur_day_start = day_start_data[offset];
if index == 0 || cur_day_start != last_day_start {
let val = *ratio as f64;
n += 1;
welford_sum += val;
welford_sum_sq += val * val;
last_day_start = cur_day_start;
}
let average = sma_data[offset];
let avg_f64 = *average as f64;
let sd_val = if n > 0 {
let nf = n as f64;
let variance =
welford_sum_sq / nf - 2.0 * avg_f64 * welford_sum / nf + avg_f64 * avg_f64;
StoredF32::from(variance.max(0.0).sqrt() as f32)
} else {
StoredF32::from(0.0_f32)
};
sd.height.truncate_push_at(index, sd_val)?;
}
{
let _lock = exit.lock();
sd.height.flush()?;
}
Ok(())
}
crates/brk_computer/src/internal/transform/bp16_to_float.rs
+11
View File
@@ -0,0 +1,11 @@
use brk_types::{BasisPoints16, StoredF32};
use vecdb::UnaryTransform;
pub struct Bp16ToFloat;
impl UnaryTransform<BasisPoints16, StoredF32> for Bp16ToFloat {
#[inline(always)]
fn apply(bp: BasisPoints16) -> StoredF32 {
StoredF32::from(bp.to_f32())
}
}
crates/brk_computer/src/internal/transform/bp32_to_float.rs
+11
View File
@@ -0,0 +1,11 @@
use brk_types::{BasisPoints32, StoredF32};
use vecdb::UnaryTransform;
pub struct Bp32ToFloat;
impl UnaryTransform<BasisPoints32, StoredF32> for Bp32ToFloat {
#[inline(always)]
fn apply(bp: BasisPoints32) -> StoredF32 {
StoredF32::from(bp.to_f32())
}
}
crates/brk_computer/src/internal/transform/bps16_to_float.rs
+11
View File
@@ -0,0 +1,11 @@
use brk_types::{BasisPointsSigned16, StoredF32};
use vecdb::UnaryTransform;
pub struct Bps16ToFloat;
impl UnaryTransform<BasisPointsSigned16, StoredF32> for Bps16ToFloat {
#[inline(always)]
fn apply(bp: BasisPointsSigned16) -> StoredF32 {
StoredF32::from(bp.to_f32())
}
}
crates/brk_computer/src/internal/transform/bps32_to_float.rs
+11
View File
@@ -0,0 +1,11 @@
use brk_types::{BasisPointsSigned32, StoredF32};
use vecdb::UnaryTransform;
pub struct Bps32ToFloat;
impl UnaryTransform<BasisPointsSigned32, StoredF32> for Bps32ToFloat {
#[inline(always)]
fn apply(bp: BasisPointsSigned32) -> StoredF32 {
StoredF32::from(bp.to_f32())
}
}
crates/brk_computer/src/internal/transform/mod.rs
+8
View File
@@ -1,3 +1,7 @@
mod bp16_to_float;
mod bp32_to_float;
mod bps16_to_float;
mod bps32_to_float;
mod block_count_target;
mod cents_halve;
mod cents_identity;
@@ -42,6 +46,10 @@ mod volatility_sqrt30;
mod volatility_sqrt365;
mod volatility_sqrt7;
pub use bp16_to_float::*;
pub use bp32_to_float::*;
pub use bps16_to_float::*;
pub use bps32_to_float::*;
pub use block_count_target::*;
pub use cents_halve::*;
pub use cents_identity::*;
crates/brk_computer/src/market/ath/compute.rs
+19 -16
View File
@@ -1,14 +1,15 @@
use brk_error::Result;
use brk_types::StoredU16;
use brk_types::{Day1, StoredU16};
use vecdb::{Exit, ReadableVec, VecIndex};
use super::Vecs;
use crate::{ComputeIndexes, prices, traits::ComputeDrawdown};
use crate::{ComputeIndexes, indexes, prices, traits::ComputeDrawdown};
impl Vecs {
pub(crate) fn compute(
&mut self,
prices: &prices::Vecs,
indexes: &indexes::Vecs,
starting_indexes: &ComputeIndexes,
exit: &Exit,
) -> Result<()> {
@@ -18,27 +19,29 @@ impl Vecs {
exit,
)?;
let mut prev = None;
self.days_since_price_ath.height.compute_transform2(
let mut ath_day: Option<Day1> = None;
self.days_since_price_ath.height.compute_transform3(
starting_indexes.height,
&self.price_ath.cents.height,
&prices.price.cents.height,
|(i, ath, price, slf)| {
if prev.is_none() {
let i = i.to_usize();
prev.replace(if i > 0 {
slf.collect_one_at(i - 1).unwrap()
&indexes.height.day1,
|(i, ath, price, day, slf)| {
if ath_day.is_none() {
let idx = i.to_usize();
ath_day = Some(if idx > 0 {
let prev_days_since = slf.collect_one_at(idx - 1).unwrap();
Day1::from(day.to_usize().saturating_sub(usize::from(prev_days_since)))
} else {
StoredU16::default()
day
});
}
let days = if price == ath {
StoredU16::default()
if price == ath {
ath_day = Some(day);
(i, StoredU16::default())
} else {
prev.unwrap() + StoredU16::new(1)
};
prev.replace(days);
(i, days)
let days_since = (day.to_usize() - ath_day.unwrap().to_usize()) as u16;
(i, StoredU16::from(days_since))
}
},
exit,
)?;
crates/brk_computer/src/market/compute.rs
+3 -3
View File
@@ -19,7 +19,7 @@ impl Vecs {
exit: &Exit,
) -> Result<()> {
// ATH metrics (independent)
self.ath.compute(prices, starting_indexes, exit)?;
self.ath.compute(prices, indexes, starting_indexes, exit)?;
// Lookback metrics (independent)
self.lookback
@@ -27,7 +27,7 @@ impl Vecs {
// Returns metrics (depends on lookback)
self.returns
.compute(indexes, prices, blocks, &self.lookback, starting_indexes, exit)?;
.compute(prices, blocks, &self.lookback, starting_indexes, exit)?;
// Volatility (depends on returns)
self.volatility
@@ -39,7 +39,7 @@ impl Vecs {
// Moving average metrics (independent)
self.moving_average
.compute(blocks, prices, indexes, starting_indexes, exit)?;
.compute(blocks, prices, starting_indexes, exit)?;
// DCA metrics (depends on lookback for lump sum comparison)
self.dca
crates/brk_computer/src/market/dca/compute.rs
+7 -263
View File
@@ -1,8 +1,8 @@
use brk_error::Result;
use brk_types::{Bitcoin, Cents, Day1, Date, Dollars, Height, Sats, StoredF32, StoredU32};
use vecdb::{AnyVec, EagerVec, Exit, ReadableOptionVec, ReadableVec, PcoVec, PcoVecValue, VecIndex};
use brk_types::{Bitcoin, Cents, Date, Day1, Dollars, Sats, StoredF32};
use vecdb::{AnyVec, Exit, ReadableOptionVec, ReadableVec, VecIndex};
use super::{ByDcaClass, ByDcaPeriod, Vecs};
use super::Vecs;
use crate::{
ComputeIndexes, blocks, indexes,
internal::{ComputedFromHeight, PercentageDiffCents},
@@ -103,36 +103,20 @@ impl Vecs {
)?;
}
// DCA by period - CAGR (computed from returns)
// DCA by period - CAGR (computed from returns at height level)
for (cagr, returns, days) in self.period_cagr.zip_mut_with_period(&self.period_returns) {
let years = days as f32 / 365.0;
let returns_data: Vec<StoredF32> = returns.day1.collect_or_default();
cagr.height.compute_transform(
starting_indexes.height,
h2d,
|(h, di, _)| {
let v = returns_data.get(di.to_usize())
.map(|r| ((**r / 100.0 + 1.0).powf(1.0 / years) - 1.0) * 100.0)
.unwrap_or(0.0);
&returns.height,
|(h, r, ..)| {
let v = ((*r / 100.0 + 1.0).powf(1.0 / years) - 1.0) * 100.0;
(h, StoredF32::from(v))
},
exit,
)?;
}
// DCA by period - profitability
compute_period_rolling(
&mut self.period_days_in_profit,
&mut self.period_days_in_loss,
&mut self.period_min_return,
&mut self.period_max_return,
&self.period_returns,
blocks,
h2d,
starting_indexes,
exit,
)?;
// Lump sum by period - stack
let lookback_dca = lookback.price_ago.as_dca_period();
for (stack, lookback_price, days) in
@@ -171,19 +155,6 @@ impl Vecs {
)?;
}
// Lump sum by period - profitability
compute_period_rolling(
&mut self.period_lump_sum_days_in_profit,
&mut self.period_lump_sum_days_in_loss,
&mut self.period_lump_sum_min_return,
&mut self.period_lump_sum_max_return,
&self.period_lump_sum_returns,
blocks,
h2d,
starting_indexes,
exit,
)?;
// DCA by year class - stack (cumulative sum from class start date)
let start_days = super::ByDcaClass::<()>::start_days();
for (stack, day1) in self.class_stack.iter_mut().zip(start_days) {
@@ -265,7 +236,6 @@ impl Vecs {
.iter_mut()
.zip(self.class_average_price.iter())
{
returns.compute_binary::<Cents, Cents, PercentageDiffCents>(
starting_indexes.height,
&prices.price.cents.height,
@@ -274,18 +244,6 @@ impl Vecs {
)?;
}
// DCA by year class - profitability
compute_class_cumulative(
&mut self.class_days_in_profit,
&mut self.class_days_in_loss,
&mut self.class_min_return,
&mut self.class_max_return,
&self.class_returns,
h2d,
starting_indexes,
exit,
)?;
Ok(())
}
}
@@ -297,217 +255,3 @@ fn sats_from_dca(price: Dollars) -> Sats {
Sats::from(Bitcoin::from(DCA_AMOUNT / price))
}
}
#[allow(clippy::too_many_arguments)]
fn compute_period_rolling(
days_in_profit: &mut ByDcaPeriod<ComputedFromHeight<StoredU32>>,
days_in_loss: &mut ByDcaPeriod<ComputedFromHeight<StoredU32>>,
min_return: &mut ByDcaPeriod<ComputedFromHeight<StoredF32>>,
max_return: &mut ByDcaPeriod<ComputedFromHeight<StoredF32>>,
returns: &ByDcaPeriod<ComputedFromHeight<StoredF32>>,
blocks: &blocks::Vecs,
h2d: &EagerVec<PcoVec<Height, Day1>>,
starting_indexes: &ComputeIndexes,
exit: &Exit,
) -> Result<()> {
for ((((dip, dil), minr), maxr), (ret, days)) in days_in_profit
.iter_mut()
.zip(days_in_loss.iter_mut())
.zip(min_return.iter_mut())
.zip(max_return.iter_mut())
.zip(returns.iter_with_days())
{
let window_starts = blocks.count.start_vec(days as usize);
let returns_data: Vec<StoredF32> = ret.day1.collect_or_default();
compute_rolling(
&mut dip.height, h2d, &returns_data, window_starts, starting_indexes.height, exit,
|buf| StoredU32::from(buf.iter().copied().filter(|r| **r > 0.0).count()),
)?;
compute_rolling(
&mut dil.height, h2d, &returns_data, window_starts, starting_indexes.height, exit,
|buf| StoredU32::from(buf.iter().copied().filter(|r| **r < 0.0).count()),
)?;
compute_rolling(
&mut minr.height, h2d, &returns_data, window_starts, starting_indexes.height, exit,
|buf| {
buf.iter()
.copied()
.reduce(|a, b| if *b < *a { b } else { a })
.unwrap_or_default()
},
)?;
compute_rolling(
&mut maxr.height, h2d, &returns_data, window_starts, starting_indexes.height, exit,
|buf| {
buf.iter()
.copied()
.reduce(|a, b| if *b > *a { b } else { a })
.unwrap_or_default()
},
)?;
}
Ok(())
}
#[allow(clippy::too_many_arguments)]
fn compute_class_cumulative(
days_in_profit: &mut ByDcaClass<ComputedFromHeight<StoredU32>>,
days_in_loss: &mut ByDcaClass<ComputedFromHeight<StoredU32>>,
min_return: &mut ByDcaClass<ComputedFromHeight<StoredF32>>,
max_return: &mut ByDcaClass<ComputedFromHeight<StoredF32>>,
returns: &ByDcaClass<ComputedFromHeight<StoredF32>>,
h2d: &EagerVec<PcoVec<Height, Day1>>,
starting_indexes: &ComputeIndexes,
exit: &Exit,
) -> Result<()> {
let start_days = ByDcaClass::<()>::start_days();
for (((((dip, dil), minr), maxr), ret), from) in days_in_profit
.iter_mut()
.zip(days_in_loss.iter_mut())
.zip(min_return.iter_mut())
.zip(max_return.iter_mut())
.zip(returns.iter())
.zip(start_days)
{
compute_cumulative(
&mut dip.height, h2d, &ret.day1, from, starting_indexes.height, exit,
StoredU32::ZERO,
|prev, ret| if *ret > 0.0 { prev + StoredU32::ONE } else { prev },
)?;
compute_cumulative(
&mut dil.height, h2d, &ret.day1, from, starting_indexes.height, exit,
StoredU32::ZERO,
|prev, ret| if *ret < 0.0 { prev + StoredU32::ONE } else { prev },
)?;
compute_cumulative(
&mut minr.height, h2d, &ret.day1, from, starting_indexes.height, exit,
StoredF32::from(f32::MAX),
|prev, ret| if *ret < *prev { ret } else { prev },
)?;
compute_cumulative(
&mut maxr.height, h2d, &ret.day1, from, starting_indexes.height, exit,
StoredF32::from(f32::MIN),
|prev, ret| if *ret > *prev { ret } else { prev },
)?;
}
Ok(())
}
/// Compute a rolling day-window metric at height level using _start vecs.
#[allow(clippy::too_many_arguments)]
fn compute_rolling<T: PcoVecValue + Default>(
output: &mut EagerVec<PcoVec<Height, T>>,
h2d: &EagerVec<PcoVec<Height, Day1>>,
returns_data: &[StoredF32],
window_starts: &EagerVec<PcoVec<Height, Height>>,
starting_height: Height,
exit: &Exit,
mut aggregate: impl FnMut(&[StoredF32]) -> T,
) -> Result<()> {
// Cursor + cache avoids per-height PcoVec page decompression for the
// h2d lookback read. Window-start heights are non-decreasing so the
// cursor only moves forward; the cache handles repeated values.
let mut h2d_cursor = h2d.cursor();
let mut last_ws = Height::ZERO;
let mut last_ws_di = Day1::default();
output.compute_transform2(
starting_height,
h2d,
window_starts,
|(h, di, window_start, ..)| {
let window_start_di = if window_start == last_ws {
last_ws_di
} else {
let target = window_start.to_usize();
let ws_di = if target >= h2d_cursor.position() {
h2d_cursor.advance(target - h2d_cursor.position());
h2d_cursor.next().unwrap_or_default()
} else {
// Cursor past target (batch boundary); rare fallback
h2d.collect_one(window_start).unwrap_or_default()
};
last_ws = window_start;
last_ws_di = ws_di;
ws_di
};
let start = window_start_di.to_usize();
let end = di.to_usize() + 1;
if start >= end {
return (h, T::default());
}
(h, aggregate(&returns_data[start..end]))
},
exit,
)?;
Ok(())
}
/// Compute a cumulative metric at height level starting from a fixed date.
#[allow(clippy::too_many_arguments)]
fn compute_cumulative<T: PcoVecValue + Default>(
output: &mut EagerVec<PcoVec<Height, T>>,
h2d: &EagerVec<PcoVec<Height, Day1>>,
returns: &impl ReadableOptionVec<Day1, StoredF32>,
from_day1: Day1,
starting_height: Height,
exit: &Exit,
initial: T,
mut accumulate: impl FnMut(T, StoredF32) -> T,
) -> Result<()> {
let mut last_di: Option<Day1> = None;
let sh = starting_height.to_usize();
let mut prev_value = if sh > 0 {
output.collect_one_at(sh - 1).unwrap_or_default()
} else {
T::default()
};
output.compute_transform(
starting_height,
h2d,
|(h, di, _)| {
let hi = h.to_usize();
if last_di.is_none() && hi > 0 {
last_di = Some(h2d.collect_one_at(hi - 1).unwrap());
}
if di < from_day1 {
last_di = Some(di);
prev_value = T::default();
return (h, T::default());
}
let prev_di = last_di;
last_di = Some(di);
let same_day = prev_di.is_some_and(|prev| prev == di);
let result = if same_day {
prev_value
} else {
let prev = if hi > 0 && prev_di.is_some_and(|pd| pd >= from_day1) {
prev_value
} else {
initial
};
let ret = returns.collect_one_flat(di).unwrap_or_default();
accumulate(prev, ret)
};
prev_value = result;
(h, result)
},
exit,
)?;
Ok(())
}
crates/brk_computer/src/market/dca/import.rs
+7 -160
View File
@@ -5,10 +5,7 @@ use vecdb::{Database, ImportableVec};
use super::{ByDcaCagr, ByDcaClass, ByDcaPeriod, Vecs};
use crate::{
indexes,
internal::{
ComputedFromHeight, Price,
ValueFromHeight,
},
internal::{ComputedFromHeight, Price, ValueFromHeight},
};
impl Vecs {
@@ -17,88 +14,26 @@ impl Vecs {
version: Version,
indexes: &indexes::Vecs,
) -> Result<Self> {
// DCA by period - stack (KISS)
let period_stack = ByDcaPeriod::try_new(|name, _days| {
ValueFromHeight::forced_import(
db,
&format!("{name}_dca_stack"),
version,
indexes,
)
ValueFromHeight::forced_import(db, &format!("{name}_dca_stack"), version, indexes)
})?;
// DCA by period - average price
let period_average_price = ByDcaPeriod::try_new(|name, _days| {
Price::forced_import(
db,
&format!("{name}_dca_average_price"),
version,
indexes,
)
Price::forced_import(db, &format!("{name}_dca_average_price"), version, indexes)
})?;
let period_returns = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_dca_returns"),
version,
indexes,
)
ComputedFromHeight::forced_import(db, &format!("{name}_dca_returns"), version, indexes)
})?;
// DCA by period - CAGR
let period_cagr = ByDcaCagr::try_new(|name, _days| {
ComputedFromHeight::forced_import(db, &format!("{name}_dca_cagr"), version, indexes)
})?;
// DCA by period - profitability
let period_days_in_profit = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_dca_days_in_profit"),
version + Version::ONE,
indexes,
)
})?;
let period_days_in_loss = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_dca_days_in_loss"),
version + Version::ONE,
indexes,
)
})?;
let period_min_return = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_dca_min_return"),
version,
indexes,
)
})?;
let period_max_return = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_dca_max_return"),
version,
indexes,
)
})?;
// Lump sum by period - stack (KISS)
let period_lump_sum_stack = ByDcaPeriod::try_new(|name, _days| {
ValueFromHeight::forced_import(
db,
&format!("{name}_lump_sum_stack"),
version,
indexes,
)
ValueFromHeight::forced_import(db, &format!("{name}_lump_sum_stack"), version, indexes)
})?;
// Lump sum by period - returns
let period_lump_sum_returns = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
@@ -108,92 +43,16 @@ impl Vecs {
)
})?;
// Lump sum by period - profitability
let period_lump_sum_days_in_profit = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_lump_sum_days_in_profit"),
version + Version::ONE,
indexes,
)
})?;
let period_lump_sum_days_in_loss = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_lump_sum_days_in_loss"),
version + Version::ONE,
indexes,
)
})?;
let period_lump_sum_min_return = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_lump_sum_min_return"),
version,
indexes,
)
})?;
let period_lump_sum_max_return = ByDcaPeriod::try_new(|name, _days| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_lump_sum_max_return"),
version,
indexes,
)
})?;
// DCA by year class - stack (KISS)
let class_stack = ByDcaClass::try_new(|name, _year, _day1| {
ValueFromHeight::forced_import(
db,
&format!("{name}_stack"),
version,
indexes,
)
ValueFromHeight::forced_import(db, &format!("{name}_stack"), version, indexes)
})?;
// DCA by year class - average price
let class_average_price = ByDcaClass::try_new(|name, _year, _day1| {
Price::forced_import(db, &format!("{name}_average_price"), version, indexes)
})?;
let class_returns = ByDcaClass::try_new(|name, _year, _day1| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_returns"),
version,
indexes,
)
})?;
// DCA by year class - profitability
let class_days_in_profit = ByDcaClass::try_new(|name, _year, _day1| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_days_in_profit"),
version,
indexes,
)
})?;
let class_days_in_loss = ByDcaClass::try_new(|name, _year, _day1| {
ComputedFromHeight::forced_import(
db,
&format!("{name}_days_in_loss"),
version,
indexes,
)
})?;
let class_min_return = ByDcaClass::try_new(|name, _year, _day1| {
ComputedFromHeight::forced_import(db, &format!("{name}_min_return"), version, indexes)
})?;
let class_max_return = ByDcaClass::try_new(|name, _year, _day1| {
ComputedFromHeight::forced_import(db, &format!("{name}_max_return"), version, indexes)
ComputedFromHeight::forced_import(db, &format!("{name}_returns"), version, indexes)
})?;
Ok(Self {
@@ -202,23 +61,11 @@ impl Vecs {
period_average_price,
period_returns,
period_cagr,
period_days_in_profit,
period_days_in_loss,
period_min_return,
period_max_return,
period_lump_sum_stack,
period_lump_sum_returns,
period_lump_sum_days_in_profit,
period_lump_sum_days_in_loss,
period_lump_sum_min_return,
period_lump_sum_max_return,
class_stack,
class_average_price,
class_returns,
class_days_in_profit,
class_days_in_loss,
class_min_return,
class_max_return,
})
}
}
crates/brk_computer/src/market/dca/vecs.rs
+5 -25
View File
@@ -1,11 +1,9 @@
use brk_traversable::Traversable;
use brk_types::{Cents, Height, Sats, StoredF32, StoredU32};
use brk_types::{Cents, Height, Sats, StoredF32};
use vecdb::{EagerVec, PcoVec, Rw, StorageMode};
use super::{ByDcaCagr, ByDcaClass, ByDcaPeriod};
use crate::internal::{
ComputedFromHeight, Price, ValueFromHeight,
};
use crate::internal::{ComputedFromHeight, Price, ValueFromHeight};
/// Dollar-cost averaging metrics by time period and year class
#[derive(Traversable)]
@@ -14,36 +12,18 @@ pub struct Vecs<M: StorageMode = Rw> {
/// Computed once, reused by all period rolling sums.
pub dca_sats_per_day: M::Stored<EagerVec<PcoVec<Height, Sats>>>,
// DCA by period - KISS types
// DCA by period
pub period_stack: ByDcaPeriod<ValueFromHeight<M>>,
pub period_average_price: ByDcaPeriod<Price<ComputedFromHeight<Cents, M>>>,
pub period_returns: ByDcaPeriod<ComputedFromHeight<StoredF32, M>>,
pub period_cagr: ByDcaCagr<ComputedFromHeight<StoredF32, M>>,
// DCA by period - profitability
pub period_days_in_profit: ByDcaPeriod<ComputedFromHeight<StoredU32, M>>,
pub period_days_in_loss: ByDcaPeriod<ComputedFromHeight<StoredU32, M>>,
pub period_min_return: ByDcaPeriod<ComputedFromHeight<StoredF32, M>>,
pub period_max_return: ByDcaPeriod<ComputedFromHeight<StoredF32, M>>,
// Lump sum by period (for comparison with DCA) - KISS types
// Lump sum by period (for comparison with DCA)
pub period_lump_sum_stack: ByDcaPeriod<ValueFromHeight<M>>,
pub period_lump_sum_returns: ByDcaPeriod<ComputedFromHeight<StoredF32, M>>,
// Lump sum by period - profitability
pub period_lump_sum_days_in_profit: ByDcaPeriod<ComputedFromHeight<StoredU32, M>>,
pub period_lump_sum_days_in_loss: ByDcaPeriod<ComputedFromHeight<StoredU32, M>>,
pub period_lump_sum_min_return: ByDcaPeriod<ComputedFromHeight<StoredF32, M>>,
pub period_lump_sum_max_return: ByDcaPeriod<ComputedFromHeight<StoredF32, M>>,
// DCA by year class - KISS types
// DCA by year class
pub class_stack: ByDcaClass<ValueFromHeight<M>>,
pub class_average_price: ByDcaClass<Price<ComputedFromHeight<Cents, M>>>,
pub class_returns: ByDcaClass<ComputedFromHeight<StoredF32, M>>,
// DCA by year class - profitability
pub class_days_in_profit: ByDcaClass<ComputedFromHeight<StoredU32, M>>,
pub class_days_in_loss: ByDcaClass<ComputedFromHeight<StoredU32, M>>,
pub class_min_return: ByDcaClass<ComputedFromHeight<StoredF32, M>>,
pub class_max_return: ByDcaClass<ComputedFromHeight<StoredF32, M>>,
}
crates/brk_computer/src/market/indicators/compute.rs
+30 -12
View File
@@ -9,6 +9,16 @@ use crate::{
mining, prices, transactions,
};
fn tf_multiplier(tf: &str) -> usize {
match tf {
"1d" => 1,
"1w" => 7,
"1m" => 30,
"1y" => 365,
_ => unreachable!(),
}
}
impl Vecs {
#[allow(clippy::too_many_arguments)]
pub(crate) fn compute(
@@ -60,18 +70,22 @@ impl Vecs {
)?;
}
// Pre-collect Height→Day1 mapping
let h2d: Vec<Day1> = indexes.height.day1.collect();
let total_heights = h2d.len();
// RSI per timeframe
for (tf, rsi_chain) in self.rsi.iter_mut() {
let m = tf_multiplier(tf);
let returns_source = match tf {
"1d" => &returns.price_returns._24h.height,
"1w" => &returns.price_returns._1w.height,
"1m" => &returns.price_returns._1m.height,
"1y" => &returns.price_returns._1y.height,
_ => unreachable!(),
};
super::rsi::compute(
rsi_chain,
tf,
returns,
&h2d,
total_heights,
blocks,
returns_source,
14 * m,
3 * m,
starting_indexes,
exit,
)?;
@@ -79,18 +93,22 @@ impl Vecs {
// MACD per timeframe
for (tf, macd_chain) in self.macd.iter_mut() {
let m = tf_multiplier(tf);
super::macd::compute(
macd_chain,
tf,
blocks,
prices,
&h2d,
total_heights,
12 * m,
26 * m,
9 * m,
starting_indexes,
exit,
)?;
}
// Gini (daily only, expanded to Height)
// Gini (daily, expanded to Height)
let h2d: Vec<Day1> = indexes.height.day1.collect();
let total_heights = h2d.len();
super::gini::compute(
&mut self.gini,
distribution,
crates/brk_computer/src/market/indicators/gini.rs
+27 -23
View File
@@ -1,5 +1,5 @@
use brk_error::Result;
use brk_types::{Day1, Sats, StoredF32, StoredU64, Version};
use brk_types::{Day1, StoredF32, Version};
use vecdb::{AnyStoredVec, AnyVec, Exit, ReadableOptionVec, VecIndex, WritableVec};
use crate::{ComputeIndexes, distribution, internal::ComputedFromHeight};
@@ -44,35 +44,39 @@ pub(super) fn compute(
return Ok(());
}
// Pre-collect all daily data
let supply_data: Vec<Vec<Sats>> = supply_vecs
let num_days = supply_vecs
.iter()
.map(|v| v.collect_or_default())
.collect();
let count_data: Vec<Vec<StoredU64>> = count_vecs
.iter()
.map(|v| v.collect_or_default())
.collect();
let num_days = supply_data.first().map_or(0, |v| v.len());
.map(|v| v.len())
.min()
.unwrap_or(0)
.min(count_vecs.iter().map(|v| v.len()).min().unwrap_or(0));
// Compute gini per day in-memory
let mut gini_daily = Vec::with_capacity(num_days);
let mut buckets: Vec<(u64, u64)> = Vec::with_capacity(supply_data.len());
for di in 0..num_days {
// Only compute gini for new days (each day is independent)
let start_day = if start_height > 0 {
h2d[start_height].to_usize()
} else {
0
};
let mut gini_new: Vec<f32> = Vec::with_capacity(num_days.saturating_sub(start_day));
let mut buckets: Vec<(u64, u64)> = Vec::with_capacity(supply_vecs.len());
for di in start_day..num_days {
buckets.clear();
buckets.extend(supply_data.iter().zip(count_data.iter()).map(|(s, c)| {
let count: u64 = c[di].into();
let supply: u64 = s[di].into();
(count, supply)
}));
gini_daily.push(gini_from_lorenz(&buckets));
let day = Day1::from(di);
for (sv, cv) in supply_vecs.iter().zip(count_vecs.iter()) {
let supply: u64 = sv.collect_one_flat(day).unwrap_or_default().into();
let count: u64 = cv.collect_one_flat(day).unwrap_or_default().into();
buckets.push((count, supply));
}
gini_new.push(gini_from_lorenz(&buckets));
}
// Expand to Height
(start_height..total_heights).for_each(|h| {
let di = h2d[h].to_usize();
let val = if di < gini_daily.len() {
StoredF32::from(gini_daily[di])
let offset = di.saturating_sub(start_day);
let val = if offset < gini_new.len() {
StoredF32::from(gini_new[offset])
} else {
StoredF32::NAN
};
@@ -92,7 +96,7 @@ fn gini_from_lorenz(buckets: &[(u64, u64)]) -> f32 {
let total_supply: u64 = buckets.iter().map(|(_, s)| s).sum();
if total_count == 0 || total_supply == 0 {
return 0.0;
return f32::NAN;
}
let (mut cumulative_count, mut cumulative_supply, mut area) = (0u64, 0u64, 0.0f64);
crates/brk_computer/src/market/indicators/import.rs
+12
View File
@@ -81,6 +81,18 @@ impl MacdChain {
)?;
Ok(Self {
ema_fast: ComputedFromHeight::forced_import(
db,
&format!("macd_ema_fast_{tf}"),
version,
indexes,
)?,
ema_slow: ComputedFromHeight::forced_import(
db,
&format!("macd_ema_slow_{tf}"),
version,
indexes,
)?,
line,
signal,
histogram,
crates/brk_computer/src/market/indicators/macd.rs
+42 -84
View File
@@ -1,103 +1,61 @@
use brk_error::Result;
use brk_types::{Day1, StoredF32};
use vecdb::{AnyStoredVec, AnyVec, Exit, VecIndex, WritableVec};
use vecdb::Exit;
use super::{MacdChain, smoothing::compute_ema, timeframe::{collect_closes, date_to_period}};
use crate::{ComputeIndexes, prices};
use super::MacdChain;
use crate::{ComputeIndexes, blocks, prices};
#[allow(clippy::too_many_arguments)]
pub(super) fn compute(
chain: &mut MacdChain,
tf: &str,
blocks: &blocks::Vecs,
prices: &prices::Vecs,
h2d: &[Day1],
total_heights: usize,
fast_days: usize,
slow_days: usize,
signal_days: usize,
starting_indexes: &ComputeIndexes,
exit: &Exit,
) -> Result<()> {
let source_version = prices.price.usd.height.version();
let close = &prices.price.usd.height;
let ws_fast = blocks.count.start_vec(fast_days);
let ws_slow = blocks.count.start_vec(slow_days);
let ws_signal = blocks.count.start_vec(signal_days);
chain
.line
.height
.validate_computed_version_or_reset(source_version)?;
chain
.signal
.height
.validate_computed_version_or_reset(source_version)?;
chain.line.height.truncate_if_needed_at(
chain
.line
.height
.len()
.min(starting_indexes.height.to_usize()),
)?;
chain.signal.height.truncate_if_needed_at(
chain
.signal
.height
.len()
.min(starting_indexes.height.to_usize()),
chain.ema_fast.height.compute_rolling_ema(
starting_indexes.height,
ws_fast,
close,
exit,
)?;
chain
.histogram
.height
.validate_computed_version_or_reset(source_version)?;
chain.histogram.height.truncate_if_needed_at(
chain
.histogram
.height
.len()
.min(starting_indexes.height.to_usize()),
chain.ema_slow.height.compute_rolling_ema(
starting_indexes.height,
ws_slow,
close,
exit,
)?;
let start_height = chain.line.height.len();
if start_height >= total_heights {
return Ok(());
}
// MACD line = ema_fast - ema_slow
chain.line.height.compute_subtract(
starting_indexes.height,
&chain.ema_fast.height,
&chain.ema_slow.height,
exit,
)?;
// Collect close prices at timeframe level
let closes = collect_closes(tf, prices);
let closes_f32: Vec<f32> = closes.iter().map(|d| **d as f32).collect();
// Signal = EMA of MACD line
chain.signal.height.compute_rolling_ema(
starting_indexes.height,
ws_signal,
&chain.line.height,
exit,
)?;
// Compute MACD in-memory
let ema12 = compute_ema(&closes_f32, 12);
let ema26 = compute_ema(&closes_f32, 26);
let macd_line: Vec<f32> = ema12.iter().zip(ema26.iter()).map(|(a, b)| a - b).collect();
let macd_signal = compute_ema(&macd_line, 9);
let macd_histogram: Vec<f32> = macd_line.iter().zip(macd_signal.iter()).map(|(a, b)| a - b).collect();
// Expand to Height
(start_height..total_heights).for_each(|h| {
let pi = date_to_period(tf, h2d[h]);
chain.line.height.push(if pi < macd_line.len() {
StoredF32::from(macd_line[pi])
} else {
StoredF32::NAN
});
chain.signal.height.push(if pi < macd_signal.len() {
StoredF32::from(macd_signal[pi])
} else {
StoredF32::NAN
});
chain.histogram.height.push(if pi < macd_histogram.len() {
StoredF32::from(macd_histogram[pi])
} else {
StoredF32::NAN
});
});
{
let _lock = exit.lock();
chain.line.height.write()?;
chain.signal.height.write()?;
chain.histogram.height.write()?;
}
// Histogram = line - signal
chain.histogram.height.compute_subtract(
starting_indexes.height,
&chain.line.height,
&chain.signal.height,
exit,
)?;
Ok(())
}
crates/brk_computer/src/market/indicators/mod.rs
-2
View File
@@ -3,8 +3,6 @@ mod gini;
mod import;
mod macd;
mod rsi;
mod smoothing;
mod timeframe;
mod vecs;
pub use vecs::{ByIndicatorTimeframe, MacdChain, RsiChain, Vecs};
crates/brk_computer/src/market/indicators/rsi.rs
+93 -104
View File
@@ -1,126 +1,115 @@
use brk_error::Result;
use brk_types::{Day1, StoredF32};
use vecdb::{AnyStoredVec, AnyVec, Exit, VecIndex, WritableVec};
use brk_types::{Height, StoredF32};
use vecdb::{Exit, ReadableVec};
use super::{
RsiChain,
smoothing::{compute_rma, compute_rolling_max, compute_rolling_min, compute_sma},
timeframe::{collect_returns, date_to_period},
};
use crate::{ComputeIndexes, market::returns::Vecs as ReturnsVecs};
use super::RsiChain;
use crate::{ComputeIndexes, blocks};
#[allow(clippy::too_many_arguments)]
pub(super) fn compute(
chain: &mut RsiChain,
tf: &str,
returns: &ReturnsVecs,
h2d: &[Day1],
total_heights: usize,
blocks: &blocks::Vecs,
returns_source: &impl ReadableVec<Height, StoredF32>,
rma_days: usize,
stoch_sma_days: usize,
starting_indexes: &ComputeIndexes,
exit: &Exit,
) -> Result<()> {
let source_version = returns.price_returns._24h.height.version();
let ws_rma = blocks.count.start_vec(rma_days);
let ws_sma = blocks.count.start_vec(stoch_sma_days);
let vecs = [
&mut chain.gains.height,
&mut chain.losses.height,
&mut chain.average_gain.height,
&mut chain.average_loss.height,
&mut chain.rsi.height,
&mut chain.rsi_min.height,
&mut chain.rsi_max.height,
&mut chain.stoch_rsi.height,
&mut chain.stoch_rsi_k.height,
&mut chain.stoch_rsi_d.height,
];
// Gains = max(return, 0)
chain.gains.height.compute_transform(
starting_indexes.height,
returns_source,
|(h, r, ..)| (h, StoredF32::from((*r).max(0.0))),
exit,
)?;
for v in vecs {
v.validate_computed_version_or_reset(source_version)?;
v.truncate_if_needed_at(v.len().min(starting_indexes.height.to_usize()))?;
}
// Losses = max(-return, 0)
chain.losses.height.compute_transform(
starting_indexes.height,
returns_source,
|(h, r, ..)| (h, StoredF32::from((-*r).max(0.0))),
exit,
)?;
let start_height = chain.gains.height.len();
if start_height >= total_heights {
return Ok(());
}
// Average gain = RMA of gains
chain.average_gain.height.compute_rolling_rma(
starting_indexes.height,
ws_rma,
&chain.gains.height,
exit,
)?;
// Collect returns at the appropriate timeframe level
let period_returns = collect_returns(tf, returns);
// Average loss = RMA of losses
chain.average_loss.height.compute_rolling_rma(
starting_indexes.height,
ws_rma,
&chain.losses.height,
exit,
)?;
// Compute in-memory
let gains: Vec<f32> = period_returns.iter().map(|r| r.max(0.0)).collect();
let losses: Vec<f32> = period_returns.iter().map(|r| (-r).max(0.0)).collect();
let avg_gain = compute_rma(&gains, 14);
let avg_loss = compute_rma(&losses, 14);
// RSI = 100 * avg_gain / (avg_gain + avg_loss)
chain.rsi.height.compute_transform2(
starting_indexes.height,
&chain.average_gain.height,
&chain.average_loss.height,
|(h, g, l, ..)| {
let sum = *g + *l;
let rsi = if sum == 0.0 { 50.0 } else { 100.0 * *g / sum };
(h, StoredF32::from(rsi))
},
exit,
)?;
let rsi: Vec<f32> = avg_gain
.iter()
.zip(avg_loss.iter())
.map(|(g, l)| {
let sum = g + l;
if sum == 0.0 { 50.0 } else { 100.0 * g / sum }
})
.collect();
// Rolling min/max of RSI over rma_days window
chain.rsi_min.height.compute_rolling_min_from_starts(
starting_indexes.height,
ws_rma,
&chain.rsi.height,
exit,
)?;
let rsi_min = compute_rolling_min(&rsi, 14);
let rsi_max = compute_rolling_max(&rsi, 14);
chain.rsi_max.height.compute_rolling_max_from_starts(
starting_indexes.height,
ws_rma,
&chain.rsi.height,
exit,
)?;
let stoch_rsi: Vec<f32> = rsi
.iter()
.zip(rsi_min.iter())
.zip(rsi_max.iter())
.map(|((r, mn), mx)| {
let range = mx - mn;
if range == 0.0 {
f32::NAN
// StochRSI = (rsi - rsi_min) / (rsi_max - rsi_min) * 100
chain.stoch_rsi.height.compute_transform3(
starting_indexes.height,
&chain.rsi.height,
&chain.rsi_min.height,
&chain.rsi_max.height,
|(h, r, mn, mx, ..)| {
let range = *mx - *mn;
let stoch = if range == 0.0 {
StoredF32::NAN
} else {
(r - mn) / range * 100.0
}
})
.collect();
StoredF32::from((*r - *mn) / range * 100.0)
};
(h, stoch)
},
exit,
)?;
let stoch_rsi_k = compute_sma(&stoch_rsi, 3);
let stoch_rsi_d = compute_sma(&stoch_rsi_k, 3);
// StochRSI K = SMA of StochRSI
chain.stoch_rsi_k.height.compute_rolling_average(
starting_indexes.height,
ws_sma,
&chain.stoch_rsi.height,
exit,
)?;
// Expand to Height
macro_rules! expand {
($target:expr, $buffer:expr) => {
for h in start_height..total_heights {
let pi = date_to_period(tf, h2d[h]);
let val = if pi < $buffer.len() {
StoredF32::from($buffer[pi])
} else {
StoredF32::NAN
};
$target.push(val);
}
};
}
expand!(chain.gains.height, gains);
expand!(chain.losses.height, losses);
expand!(chain.average_gain.height, avg_gain);
expand!(chain.average_loss.height, avg_loss);
expand!(chain.rsi.height, rsi);
expand!(chain.rsi_min.height, rsi_min);
expand!(chain.rsi_max.height, rsi_max);
expand!(chain.stoch_rsi.height, stoch_rsi);
expand!(chain.stoch_rsi_k.height, stoch_rsi_k);
expand!(chain.stoch_rsi_d.height, stoch_rsi_d);
{
let _lock = exit.lock();
chain.gains.height.write()?;
chain.losses.height.write()?;
chain.average_gain.height.write()?;
chain.average_loss.height.write()?;
chain.rsi.height.write()?;
chain.rsi_min.height.write()?;
chain.rsi_max.height.write()?;
chain.stoch_rsi.height.write()?;
chain.stoch_rsi_k.height.write()?;
chain.stoch_rsi_d.height.write()?;
}
// StochRSI D = SMA of K
chain.stoch_rsi_d.height.compute_rolling_average(
starting_indexes.height,
ws_sma,
&chain.stoch_rsi_k.height,
exit,
)?;
Ok(())
}
crates/brk_computer/src/market/indicators/smoothing.rs
-89
View File
@@ -1,89 +0,0 @@
use std::collections::VecDeque;
pub(super) fn compute_rma(source: &[f32], period: usize) -> Vec<f32> {
let mut result = Vec::with_capacity(source.len());
let k = 1.0 / period as f32;
let mut sum = 0.0f32;
for (i, &val) in source.iter().enumerate() {
if i < period {
sum += val;
result.push(sum / (i + 1) as f32);
} else {
let prev = result[i - 1];
result.push(val * k + prev * (1.0 - k));
}
}
result
}
pub(super) fn compute_ema(source: &[f32], period: usize) -> Vec<f32> {
let mut result = Vec::with_capacity(source.len());
let k = 2.0 / (period as f32 + 1.0);
let mut sum = 0.0f32;
for (i, &val) in source.iter().enumerate() {
if i < period {
sum += val;
result.push(sum / (i + 1) as f32);
} else {
let prev = result[i - 1];
result.push(val * k + prev * (1.0 - k));
}
}
result
}
pub(super) fn compute_sma(source: &[f32], window: usize) -> Vec<f32> {
let mut result = Vec::with_capacity(source.len());
let mut sum = 0.0f32;
for (i, &val) in source.iter().enumerate() {
sum += val;
if i >= window {
sum -= source[i - window];
}
let count = (i + 1).min(window);
result.push(sum / count as f32);
}
result
}
pub(super) fn compute_rolling_min(source: &[f32], window: usize) -> Vec<f32> {
let mut result = Vec::with_capacity(source.len());
let mut deque = VecDeque::new();
for (i, &val) in source.iter().enumerate() {
while deque.back().is_some_and(|&(_, v): &(usize, f32)| v >= val) {
deque.pop_back();
}
deque.push_back((i, val));
if deque.front().unwrap().0 + window <= i {
deque.pop_front();
}
result.push(deque.front().unwrap().1);
}
result
}
pub(super) fn compute_rolling_max(source: &[f32], window: usize) -> Vec<f32> {
let mut result = Vec::with_capacity(source.len());
let mut deque = VecDeque::new();
for (i, &val) in source.iter().enumerate() {
while deque.back().is_some_and(|&(_, v): &(usize, f32)| v <= val) {
deque.pop_back();
}
deque.push_back((i, val));
if deque.front().unwrap().0 + window <= i {
deque.pop_front();
}
result.push(deque.front().unwrap().1);
}
result
}
crates/brk_computer/src/market/indicators/timeframe.rs
-36
View File
@@ -1,36 +0,0 @@
use brk_types::{Day1, Dollars, Month1, StoredF32, Week1, Year1};
use vecdb::{ReadableOptionVec, VecIndex};
use crate::{market::returns::Vecs as ReturnsVecs, prices};
pub(super) fn collect_returns(tf: &str, returns: &ReturnsVecs) -> Vec<f32> {
let data: Vec<StoredF32> = match tf {
"1d" => returns.price_returns._24h.day1.collect_or_default(),
"1w" => returns.price_returns._1w.week1.collect_or_default(),
"1m" => returns.price_returns._1m.month1.collect_or_default(),
"1y" => returns.price_returns._1y.year1.collect_or_default(),
_ => unreachable!(),
};
data.into_iter().map(|v| *v).collect()
}
pub(super) fn collect_closes(tf: &str, prices: &prices::Vecs) -> Vec<Dollars> {
match tf {
"1d" => prices.split.close.usd.day1.collect_or_default(),
"1w" => prices.split.close.usd.week1.collect_or_default(),
"1m" => prices.split.close.usd.month1.collect_or_default(),
"1y" => prices.split.close.usd.year1.collect_or_default(),
_ => unreachable!(),
}
}
#[inline]
pub(super) fn date_to_period(tf: &str, di: Day1) -> usize {
match tf {
"1d" => di.to_usize(),
"1w" => Week1::from(di).to_usize(),
"1m" => Month1::from(di).to_usize(),
"1y" => Year1::from(Month1::from(di)).to_usize(),
_ => unreachable!(),
}
}
crates/brk_computer/src/market/indicators/vecs.rs
+2
View File
@@ -51,6 +51,8 @@ pub struct RsiChain<M: StorageMode = Rw> {
#[derive(Traversable)]
pub struct MacdChain<M: StorageMode = Rw> {
pub ema_fast: ComputedFromHeight<StoredF32, M>,
pub ema_slow: ComputedFromHeight<StoredF32, M>,
pub line: ComputedFromHeight<StoredF32, M>,
pub signal: ComputedFromHeight<StoredF32, M>,
pub histogram: ComputedFromHeight<StoredF32, M>,
crates/brk_computer/src/market/lookback/compute.rs
+4 -8
View File
@@ -1,6 +1,5 @@
use brk_error::Result;
use brk_types::Cents;
use vecdb::{Exit, ReadableVec, VecIndex};
use vecdb::Exit;
use super::Vecs;
use crate::{blocks, ComputeIndexes, prices};
@@ -13,17 +12,14 @@ impl Vecs {
starting_indexes: &ComputeIndexes,
exit: &Exit,
) -> Result<()> {
let close_data: Vec<Cents> = prices.price.cents.height.collect();
let price = &prices.price.cents.height;
for (price_ago, days) in self.price_ago.iter_mut_with_days() {
let window_starts = blocks.count.start_vec(days as usize);
price_ago.cents.height.compute_transform(
price_ago.cents.height.compute_lookback(
starting_indexes.height,
window_starts,
|(h, start_h, _)| {
let val = close_data[start_h.to_usize()];
(h, val)
},
price,
exit,
)?;
}
crates/brk_computer/src/market/moving_average/compute.rs
+4 -33
View File
@@ -1,16 +1,14 @@
use brk_error::Result;
use brk_types::Cents;
use vecdb::{Exit, ReadableOptionVec, VecIndex};
use vecdb::Exit;
use super::Vecs;
use crate::{ComputeIndexes, blocks, indexes, prices};
use crate::{ComputeIndexes, blocks, prices};
impl Vecs {
pub(crate) fn compute(
&mut self,
blocks: &blocks::Vecs,
prices: &prices::Vecs,
indexes: &indexes::Vecs,
starting_indexes: &ComputeIndexes,
exit: &Exit,
) -> Result<()> {
@@ -41,9 +39,6 @@ impl Vecs {
})?;
}
let h2d = &indexes.height.day1;
let closes: Vec<Cents> = prices.split.close.cents.day1.collect_or_default();
for (ema, period) in [
(&mut self.price_1w_ema, 7),
(&mut self.price_8d_ema, 8),
@@ -62,18 +57,9 @@ impl Vecs {
(&mut self.price_200w_ema, 200 * 7),
(&mut self.price_4y_ema, 4 * 365),
] {
let k = 2.0f64 / (period as f64 + 1.0);
// Compute date-level EMA, then expand to height level
let date_ema = compute_date_ema(&closes, k);
let window_starts = blocks.count.start_vec(period);
ema.compute_all(blocks, prices, starting_indexes, exit, |v| {
v.compute_transform(
starting_indexes.height,
h2d,
|(h, date, ..)| (h, Cents::from(date_ema[date.to_usize()])),
exit,
)?;
v.compute_rolling_ema(starting_indexes.height, window_starts, close, exit)?;
Ok(())
})?;
}
@@ -81,18 +67,3 @@ impl Vecs {
Ok(())
}
}
fn compute_date_ema(closes: &[Cents], k: f64) -> Vec<f64> {
let mut date_ema: Vec<f64> = Vec::with_capacity(closes.len());
let mut ema_val = 0.0f64;
for (d, close) in closes.iter().enumerate() {
let close = f64::from(*close);
if d == 0 {
ema_val = close;
} else {
ema_val = close * k + ema_val * (1.0 - k);
}
date_ema.push(ema_val);
}
date_ema
}
crates/brk_computer/src/market/range/compute.rs
+1 -4
View File
@@ -3,10 +3,7 @@ use brk_types::StoredF32;
use vecdb::{Exit, ReadableVec, VecIndex};
use super::Vecs;
use crate::{
blocks, ComputeIndexes, prices,
traits::{ComputeRollingMaxFromStarts, ComputeRollingMinFromStarts},
};
use crate::{blocks, ComputeIndexes, prices};
impl Vecs {
pub(crate) fn compute(
crates/brk_computer/src/market/returns/compute.rs
+7 -19
View File
@@ -1,14 +1,13 @@
use brk_error::Result;
use brk_types::{Dollars, StoredF32};
use vecdb::{Exit, ReadableOptionVec};
use vecdb::Exit;
use super::Vecs;
use crate::{ComputeIndexes, blocks, indexes, internal::PercentageDiffDollars, market::lookback, prices};
use crate::{ComputeIndexes, blocks, internal::PercentageDiffDollars, market::lookback, prices};
impl Vecs {
pub(crate) fn compute(
&mut self,
indexes: &indexes::Vecs,
prices: &prices::Vecs,
blocks: &blocks::Vecs,
lookback: &lookback::Vecs,
@@ -29,27 +28,16 @@ impl Vecs {
)?;
}
// CAGR computed from returns (2y+ periods only)
let h2d = &indexes.height.day1;
// CAGR computed from returns at height level (2y+ periods only)
let price_returns_dca = self.price_returns.as_dca_period();
for (cagr, returns, days) in self.cagr.zip_mut_with_period(&price_returns_dca) {
let years = days as f32 / 365.0;
let mut cached_di = None;
let mut cached_val = StoredF32::from(0.0);
cagr.height.compute_transform(
starting_indexes.height,
h2d,
|(h, di, _)| {
if cached_di != Some(di) {
cached_di = Some(di);
cached_val = StoredF32::from(
returns.day1
.collect_one_flat(di)
.map(|r| ((*r / 100.0 + 1.0).powf(1.0 / years) - 1.0) * 100.0)
.unwrap_or(0.0)
);
}
(h, cached_val)
&returns.height,
|(h, r, ..)| {
let v = ((*r / 100.0 + 1.0).powf(1.0 / years) - 1.0) * 100.0;
(h, StoredF32::from(v))
},
exit,
)?;
crates/brk_computer/src/market/volatility/compute.rs
+31 -65
View File
@@ -1,6 +1,6 @@
use brk_error::Result;
use brk_types::{Height, StoredF32};
use vecdb::Exit;
use vecdb::{EagerVec, Exit, PcoVec, ReadableVec};
use super::super::returns;
use super::Vecs;
@@ -13,73 +13,39 @@ impl Vecs {
exit: &Exit,
) -> Result<()> {
// Sharpe ratios: returns / volatility
self.sharpe_1w.height.compute_transform2(
starting_indexes_height,
&returns.price_returns._1w.height,
&self.price_1w_volatility.height,
|(h, ret, vol, ..)| {
let ratio = if *vol == 0.0 { 0.0 } else { *ret / *vol };
(h, StoredF32::from(ratio))
},
exit,
)?;
self.sharpe_1m.height.compute_transform2(
starting_indexes_height,
&returns.price_returns._1m.height,
&self.price_1m_volatility.height,
|(h, ret, vol, ..)| {
let ratio = if *vol == 0.0 { 0.0 } else { *ret / *vol };
(h, StoredF32::from(ratio))
},
exit,
)?;
self.sharpe_1y.height.compute_transform2(
starting_indexes_height,
&returns.price_returns._1y.height,
&self.price_1y_volatility.height,
|(h, ret, vol, ..)| {
let ratio = if *vol == 0.0 { 0.0 } else { *ret / *vol };
(h, StoredF32::from(ratio))
},
exit,
)?;
for (out, ret, vol) in [
(&mut self.sharpe_1w, &returns.price_returns._1w.height, &self.price_1w_volatility.height),
(&mut self.sharpe_1m, &returns.price_returns._1m.height, &self.price_1m_volatility.height),
(&mut self.sharpe_1y, &returns.price_returns._1y.height, &self.price_1y_volatility.height),
] {
compute_ratio(&mut out.height, starting_indexes_height, ret, vol, exit)?;
}
// Sortino ratios: returns / downside volatility
self.sortino_1w.height.compute_transform2(
starting_indexes_height,
&returns.price_returns._1w.height,
&returns.downside_1w_sd.sd.height,
|(h, ret, vol, ..)| {
let ratio = if *vol == 0.0 { 0.0 } else { *ret / *vol };
(h, StoredF32::from(ratio))
},
exit,
)?;
self.sortino_1m.height.compute_transform2(
starting_indexes_height,
&returns.price_returns._1m.height,
&returns.downside_1m_sd.sd.height,
|(h, ret, vol, ..)| {
let ratio = if *vol == 0.0 { 0.0 } else { *ret / *vol };
(h, StoredF32::from(ratio))
},
exit,
)?;
self.sortino_1y.height.compute_transform2(
starting_indexes_height,
&returns.price_returns._1y.height,
&returns.downside_1y_sd.sd.height,
|(h, ret, vol, ..)| {
let ratio = if *vol == 0.0 { 0.0 } else { *ret / *vol };
(h, StoredF32::from(ratio))
},
exit,
)?;
compute_ratio(&mut self.sortino_1w.height, starting_indexes_height, &returns.price_returns._1w.height, &returns.downside_1w_sd.sd.height, exit)?;
compute_ratio(&mut self.sortino_1m.height, starting_indexes_height, &returns.price_returns._1m.height, &returns.downside_1m_sd.sd.height, exit)?;
compute_ratio(&mut self.sortino_1y.height, starting_indexes_height, &returns.price_returns._1y.height, &returns.downside_1y_sd.sd.height, exit)?;
Ok(())
}
}
fn compute_ratio(
out: &mut EagerVec<PcoVec<Height, StoredF32>>,
starting_indexes_height: Height,
ret: &impl ReadableVec<Height, StoredF32>,
vol: &impl ReadableVec<Height, StoredF32>,
exit: &Exit,
) -> Result<()> {
out.compute_transform2(
starting_indexes_height,
ret,
vol,
|(h, ret, vol, ..)| {
let ratio = if *vol == 0.0 { 0.0 } else { *ret / *vol };
(h, StoredF32::from(ratio))
},
exit,
)?;
Ok(())
}
crates/brk_computer/src/mining/hashrate/vecs.rs
+3 -3
View File
@@ -9,9 +9,9 @@ use crate::internal::ComputedFromHeight;
pub struct Vecs<M: StorageMode = Rw> {
pub hash_rate: ComputedFromHeight<StoredF64, M>,
pub hash_rate_1w_sma: ComputedFromHeight<StoredF64, M>,
pub hash_rate_1m_sma: ComputedFromHeight<StoredF32, M>,
pub hash_rate_2m_sma: ComputedFromHeight<StoredF32, M>,
pub hash_rate_1y_sma: ComputedFromHeight<StoredF32, M>,
pub hash_rate_1m_sma: ComputedFromHeight<StoredF64, M>,
pub hash_rate_2m_sma: ComputedFromHeight<StoredF64, M>,
pub hash_rate_1y_sma: ComputedFromHeight<StoredF64, M>,
pub hash_rate_ath: ComputedFromHeight<StoredF64, M>,
pub hash_rate_drawdown: ComputedFromHeight<StoredF32, M>,
pub hash_price_ths: ComputedFromHeight<StoredF32, M>,
crates/brk_computer/src/traits/mod.rs
-149
View File
@@ -7,155 +7,6 @@ use vecdb::{
use crate::internal::sliding_window::SlidingWindowSorted;
/// Unified rolling extremum (min or max) from window starts.
///
/// `should_replace` determines whether to evict the deque back:
/// - For min: `|back, new| *back >= *new`
/// - For max: `|back, new| *back <= *new`
pub fn compute_rolling_extremum_from_starts<I, T, A>(
out: &mut EagerVec<PcoVec<I, T>>,
max_from: I,
window_starts: &impl ReadableVec<I, I>,
values: &impl ReadableVec<I, A>,
should_replace: fn(&A, &A) -> bool,
exit: &Exit,
) -> Result<()>
where
I: VecIndex,
T: PcoVecValue + From<A>,
A: VecValue + Ord,
{
out.validate_and_truncate(window_starts.version() + values.version(), max_from)?;
out.repeat_until_complete(exit, |this| {
let skip = this.len();
let mut deque: std::collections::VecDeque<(usize, A)> =
std::collections::VecDeque::new();
let start_offset = if skip > 0 {
window_starts.collect_one_at(skip - 1).unwrap().to_usize()
} else {
0
};
let end = window_starts.len().min(values.len());
let starts_batch = window_starts.collect_range_at(start_offset, end);
let values_batch = values.collect_range_at(start_offset, end);
for (j, (start, value)) in starts_batch.into_iter().zip(values_batch).enumerate() {
let i = start_offset + j;
let start_usize = start.to_usize();
while let Some(&(idx, _)) = deque.front() {
if idx < start_usize {
deque.pop_front();
} else {
break;
}
}
while let Some((_, back)) = deque.back() {
if should_replace(back, &value) {
deque.pop_back();
} else {
break;
}
}
deque.push_back((i, value));
if i >= skip {
let extremum = deque.front().unwrap().1.clone();
this.checked_push_at(i, T::from(extremum))?;
if this.batch_limit_reached() {
break;
}
}
}
Ok(())
})?;
Ok(())
}
pub trait ComputeRollingMinFromStarts<I: VecIndex, T> {
fn compute_rolling_min_from_starts<A>(
&mut self,
max_from: I,
window_starts: &impl ReadableVec<I, I>,
values: &impl ReadableVec<I, A>,
exit: &Exit,
) -> Result<()>
where
A: VecValue + Ord,
T: From<A>;
}
impl<I, T> ComputeRollingMinFromStarts<I, T> for EagerVec<PcoVec<I, T>>
where
I: VecIndex,
T: PcoVecValue,
{
fn compute_rolling_min_from_starts<A>(
&mut self,
max_from: I,
window_starts: &impl ReadableVec<I, I>,
values: &impl ReadableVec<I, A>,
exit: &Exit,
) -> Result<()>
where
A: VecValue + Ord,
T: From<A>,
{
compute_rolling_extremum_from_starts(
self,
max_from,
window_starts,
values,
|back, new| *back >= *new,
exit,
)
}
}
pub trait ComputeRollingMaxFromStarts<I: VecIndex, T> {
fn compute_rolling_max_from_starts<A>(
&mut self,
max_from: I,
window_starts: &impl ReadableVec<I, I>,
values: &impl ReadableVec<I, A>,
exit: &Exit,
) -> Result<()>
where
A: VecValue + Ord,
T: From<A>;
}
impl<I, T> ComputeRollingMaxFromStarts<I, T> for EagerVec<PcoVec<I, T>>
where
I: VecIndex,
T: PcoVecValue,
{
fn compute_rolling_max_from_starts<A>(
&mut self,
max_from: I,
window_starts: &impl ReadableVec<I, I>,
values: &impl ReadableVec<I, A>,
exit: &Exit,
) -> Result<()>
where
A: VecValue + Ord,
T: From<A>,
{
compute_rolling_extremum_from_starts(
self,
max_from,
window_starts,
values,
|back, new| *back <= *new,
exit,
)
}
}
pub trait ComputeRollingMedianFromStarts<I: VecIndex, T> {
fn compute_rolling_median_from_starts<A>(
&mut self,
crates/brk_server/src/api/mod.rs
+4
View File
@@ -93,6 +93,10 @@ impl ApiRoutes for ApiRouter<AppState> {
include_bytes!("./scalar.js.br").as_slice(),
)
}))
.route(
"/.well-known/openapi.json",
get(|| async { Redirect::permanent("/openapi.json") }),
)
.route(
"/api/{*path}",
get(|| async { Redirect::permanent("/api") }),
crates/brk_server/src/api/openapi/compact.rs
+3 -3
View File
@@ -40,7 +40,7 @@ impl ApiJson {
/// 16. Remove required arrays from schemas
/// 17. Remove redundant "type": "object" when properties exist
/// 18. Flatten single-element type arrays
/// 19. Replace large enums (>20 values) with string type
/// 19. Replace large enums (>40 values) with string type
fn compact_json(json: &str) -> String {
let mut spec: Value = serde_json::from_str(json).expect("Invalid OpenAPI JSON");
@@ -175,9 +175,9 @@ fn compact_value(value: &mut Value) {
obj.remove("type");
}
// Step 19: Replace large enums (>20 values) with just string type
// Step 19: Replace large enums (>40 values) with just string type
if let Some(Value::Array(enum_values)) = obj.get("enum")
&& enum_values.len() > 20
&& enum_values.len() > 40
{
obj.remove("enum");
}
crates/brk_server/src/api/openapi/mod.rs
+1 -1
View File
@@ -29,7 +29,7 @@ pub fn create_openapi() -> OpenApi {
- **Metrics**: Thousands of time-series metrics across multiple indexes (date, block height, etc.)
- **[Mempool.space](https://mempool.space/docs/api/rest) compatible** (WIP): Most non-metrics endpoints follow the mempool.space API format
- **Multiple formats**: JSON and CSV output
- **LLM-optimized**: Compact OpenAPI spec at [`/api.json`](/api.json) for AI tools (full spec at [`/openapi.json`](/openapi.json))
- **LLM-optimized**: [`/llms.txt`](/llms.txt) for discovery, [`/api.json`](/api.json) compact OpenAPI spec for tool use (full spec at [`/openapi.json`](/openapi.json))
### Client Libraries
crates/brk_types/src/basis_points_16.rs
+139
View File
@@ -0,0 +1,139 @@
use std::ops::{Add, AddAssign, Div};
use derive_more::Deref;
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
use vecdb::{CheckedSub, Formattable, Pco};
use super::StoredF32;
/// Unsigned basis points stored as u16.
/// 1 bp = 0.01%. Range: 0–655.35%.
/// Use for bounded 0–100% values (dominance, adoption, RSI, etc.).
#[derive(
Debug,
Deref,
Clone,
Default,
Copy,
PartialEq,
Eq,
PartialOrd,
Ord,
Hash,
Serialize,
Deserialize,
Pco,
JsonSchema,
)]
pub struct BasisPoints16(u16);
impl BasisPoints16 {
pub const ZERO: Self = Self(0);
#[inline]
pub const fn new(value: u16) -> Self {
Self(value)
}
#[inline(always)]
pub const fn inner(self) -> u16 {
self.0
}
/// Convert to f32: divide by 100.
#[inline]
pub fn to_f32(self) -> f32 {
self.0 as f32 / 100.0
}
}
impl From<usize> for BasisPoints16 {
#[inline]
fn from(value: usize) -> Self {
Self(value as u16)
}
}
impl From<u16> for BasisPoints16 {
#[inline]
fn from(value: u16) -> Self {
Self(value)
}
}
impl From<BasisPoints16> for u16 {
#[inline]
fn from(value: BasisPoints16) -> Self {
value.0
}
}
/// Convert from float: multiply by 100 and round.
/// Input is in "display" form (e.g., 45.23 for 45.23%).
impl From<f64> for BasisPoints16 {
#[inline]
fn from(value: f64) -> Self {
debug_assert!(value >= 0.0 && value <= u16::MAX as f64 / 100.0, "f64 out of BasisPoints16 range: {value}");
Self((value * 100.0).round() as u16)
}
}
impl From<BasisPoints16> for f64 {
#[inline]
fn from(value: BasisPoints16) -> Self {
value.0 as f64 / 100.0
}
}
impl From<BasisPoints16> for StoredF32 {
#[inline]
fn from(value: BasisPoints16) -> Self {
StoredF32::from(value.to_f32())
}
}
impl Add for BasisPoints16 {
type Output = Self;
#[inline]
fn add(self, rhs: Self) -> Self::Output {
Self(self.0 + rhs.0)
}
}
impl AddAssign for BasisPoints16 {
#[inline]
fn add_assign(&mut self, rhs: Self) {
self.0 += rhs.0;
}
}
impl Div<usize> for BasisPoints16 {
type Output = Self;
#[inline]
fn div(self, rhs: usize) -> Self::Output {
Self(self.0 / rhs as u16)
}
}
impl CheckedSub for BasisPoints16 {
fn checked_sub(self, rhs: Self) -> Option<Self> {
self.0.checked_sub(rhs.0).map(Self)
}
}
impl std::fmt::Display for BasisPoints16 {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
let mut buf = itoa::Buffer::new();
let str = buf.format(self.0);
f.write_str(str)
}
}
impl Formattable for BasisPoints16 {
#[inline(always)]
fn fmt_csv(&self, f: &mut String) -> std::fmt::Result {
use std::fmt::Write;
write!(f, "{}", self)
}
}
crates/brk_types/src/basis_points_32.rs
+142
View File
@@ -0,0 +1,142 @@
use std::ops::{Add, AddAssign, Div};
use derive_more::Deref;
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
use vecdb::{CheckedSub, Formattable, Pco};
use super::StoredF32;
/// Unsigned basis points stored as u32.
/// 1 bp = 0.01%. Range: 0–42,949,672.95%.
/// Use for unbounded unsigned ratios (MVRV, NVT, SOPR, etc.).
#[derive(
Debug,
Deref,
Clone,
Default,
Copy,
PartialEq,
Eq,
PartialOrd,
Ord,
Hash,
Serialize,
Deserialize,
Pco,
JsonSchema,
)]
pub struct BasisPoints32(u32);
impl BasisPoints32 {
pub const ZERO: Self = Self(0);
#[inline]
pub const fn new(value: u32) -> Self {
Self(value)
}
#[inline(always)]
pub const fn inner(self) -> u32 {
self.0
}
/// Convert to f32: divide by 100.
#[inline]
pub fn to_f32(self) -> f32 {
self.0 as f32 / 100.0
}
}
impl From<usize> for BasisPoints32 {
#[inline]
fn from(value: usize) -> Self {
Self(value as u32)
}
}
impl From<u32> for BasisPoints32 {
#[inline]
fn from(value: u32) -> Self {
Self(value)
}
}
impl From<BasisPoints32> for u32 {
#[inline]
fn from(value: BasisPoints32) -> Self {
value.0
}
}
/// Convert from float: multiply by 100 and round.
/// Input is in "display" form (e.g., 450.23 for 450.23%).
impl From<f64> for BasisPoints32 {
#[inline]
fn from(value: f64) -> Self {
debug_assert!(
value >= 0.0 && value <= u32::MAX as f64 / 100.0,
"f64 out of BasisPoints32 range: {value}"
);
Self((value * 100.0).round() as u32)
}
}
impl From<BasisPoints32> for f64 {
#[inline]
fn from(value: BasisPoints32) -> Self {
value.0 as f64 / 100.0
}
}
impl From<BasisPoints32> for StoredF32 {
#[inline]
fn from(value: BasisPoints32) -> Self {
StoredF32::from(value.to_f32())
}
}
impl Add for BasisPoints32 {
type Output = Self;
#[inline]
fn add(self, rhs: Self) -> Self::Output {
Self(self.0 + rhs.0)
}
}
impl AddAssign for BasisPoints32 {
#[inline]
fn add_assign(&mut self, rhs: Self) {
self.0 += rhs.0;
}
}
impl Div<usize> for BasisPoints32 {
type Output = Self;
#[inline]
fn div(self, rhs: usize) -> Self::Output {
Self(self.0 / rhs as u32)
}
}
impl CheckedSub for BasisPoints32 {
fn checked_sub(self, rhs: Self) -> Option<Self> {
self.0.checked_sub(rhs.0).map(Self)
}
}
impl std::fmt::Display for BasisPoints32 {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
let mut buf = itoa::Buffer::new();
let str = buf.format(self.0);
f.write_str(str)
}
}
impl Formattable for BasisPoints32 {
#[inline(always)]
fn fmt_csv(&self, f: &mut String) -> std::fmt::Result {
use std::fmt::Write;
write!(f, "{}", self)
}
}
crates/brk_types/src/basis_points_signed_16.rs
+162
View File
@@ -0,0 +1,162 @@
use std::ops::{Add, AddAssign, Div, Sub, SubAssign};
use derive_more::Deref;
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
use vecdb::{CheckedSub, Formattable, Pco};
use super::StoredF32;
/// Signed basis points stored as i16.
/// 1 bp = 0.01%. Range: -327.67% to +327.67%.
/// Use for signed bounded values (NUPL, net PnL ratios, etc.).
#[derive(
Debug,
Deref,
Clone,
Default,
Copy,
PartialEq,
Eq,
PartialOrd,
Ord,
Hash,
Serialize,
Deserialize,
Pco,
JsonSchema,
)]
pub struct BasisPointsSigned16(i16);
impl BasisPointsSigned16 {
pub const ZERO: Self = Self(0);
#[inline]
pub const fn new(value: i16) -> Self {
Self(value)
}
#[inline(always)]
pub const fn inner(self) -> i16 {
self.0
}
#[inline]
pub fn is_negative(self) -> bool {
self.0 < 0
}
/// Convert to f32: divide by 100.
#[inline]
pub fn to_f32(self) -> f32 {
self.0 as f32 / 100.0
}
}
impl From<usize> for BasisPointsSigned16 {
#[inline]
fn from(value: usize) -> Self {
Self(value as i16)
}
}
impl From<i16> for BasisPointsSigned16 {
#[inline]
fn from(value: i16) -> Self {
Self(value)
}
}
impl From<BasisPointsSigned16> for i16 {
#[inline]
fn from(value: BasisPointsSigned16) -> Self {
value.0
}
}
/// Convert from float: multiply by 100 and round.
/// Input is in "display" form (e.g., -45.23 for -45.23%).
impl From<f64> for BasisPointsSigned16 {
#[inline]
fn from(value: f64) -> Self {
debug_assert!(
value >= i16::MIN as f64 / 100.0 && value <= i16::MAX as f64 / 100.0,
"f64 out of BasisPointsSigned16 range: {value}"
);
Self((value * 100.0).round() as i16)
}
}
impl From<BasisPointsSigned16> for f64 {
#[inline]
fn from(value: BasisPointsSigned16) -> Self {
value.0 as f64 / 100.0
}
}
impl From<BasisPointsSigned16> for StoredF32 {
#[inline]
fn from(value: BasisPointsSigned16) -> Self {
StoredF32::from(value.to_f32())
}
}
impl Add for BasisPointsSigned16 {
type Output = Self;
#[inline]
fn add(self, rhs: Self) -> Self::Output {
Self(self.0 + rhs.0)
}
}
impl AddAssign for BasisPointsSigned16 {
#[inline]
fn add_assign(&mut self, rhs: Self) {
self.0 += rhs.0;
}
}
impl Sub for BasisPointsSigned16 {
type Output = Self;
#[inline]
fn sub(self, rhs: Self) -> Self::Output {
Self(self.0 - rhs.0)
}
}
impl SubAssign for BasisPointsSigned16 {
#[inline]
fn sub_assign(&mut self, rhs: Self) {
self.0 -= rhs.0;
}
}
impl Div<usize> for BasisPointsSigned16 {
type Output = Self;
#[inline]
fn div(self, rhs: usize) -> Self::Output {
Self(self.0 / rhs as i16)
}
}
impl CheckedSub for BasisPointsSigned16 {
fn checked_sub(self, rhs: Self) -> Option<Self> {
self.0.checked_sub(rhs.0).map(Self)
}
}
impl std::fmt::Display for BasisPointsSigned16 {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
let mut buf = itoa::Buffer::new();
let str = buf.format(self.0);
f.write_str(str)
}
}
impl Formattable for BasisPointsSigned16 {
#[inline(always)]
fn fmt_csv(&self, f: &mut String) -> std::fmt::Result {
use std::fmt::Write;
write!(f, "{}", self)
}
}
crates/brk_types/src/basis_points_signed_32.rs
+162
View File
@@ -0,0 +1,162 @@
use std::ops::{Add, AddAssign, Div, Sub, SubAssign};
use derive_more::Deref;
use schemars::JsonSchema;
use serde::{Deserialize, Serialize};
use vecdb::{CheckedSub, Formattable, Pco};
use super::StoredF32;
/// Signed basis points stored as i32.
/// 1 bp = 0.01%. Range: -21,474,836.47% to +21,474,836.47%.
/// Use for unbounded signed values (returns, growth rates, volatility, z-scores, etc.).
#[derive(
Debug,
Deref,
Clone,
Default,
Copy,
PartialEq,
Eq,
PartialOrd,
Ord,
Hash,
Serialize,
Deserialize,
Pco,
JsonSchema,
)]
pub struct BasisPointsSigned32(i32);
impl BasisPointsSigned32 {
pub const ZERO: Self = Self(0);
#[inline]
pub const fn new(value: i32) -> Self {
Self(value)
}
#[inline(always)]
pub const fn inner(self) -> i32 {
self.0
}
#[inline]
pub fn is_negative(self) -> bool {
self.0 < 0
}
/// Convert to f32: divide by 100.
#[inline]
pub fn to_f32(self) -> f32 {
self.0 as f32 / 100.0
}
}
impl From<usize> for BasisPointsSigned32 {
#[inline]
fn from(value: usize) -> Self {
Self(value as i32)
}
}
impl From<i32> for BasisPointsSigned32 {
#[inline]
fn from(value: i32) -> Self {
Self(value)
}
}
impl From<BasisPointsSigned32> for i32 {
#[inline]
fn from(value: BasisPointsSigned32) -> Self {
value.0
}
}
/// Convert from float: multiply by 100 and round.
/// Input is in "display" form (e.g., -5000.23 for -5000.23%).
impl From<f64> for BasisPointsSigned32 {
#[inline]
fn from(value: f64) -> Self {
debug_assert!(
value >= i32::MIN as f64 / 100.0 && value <= i32::MAX as f64 / 100.0,
"f64 out of BasisPointsSigned32 range: {value}"
);
Self((value * 100.0).round() as i32)
}
}
impl From<BasisPointsSigned32> for f64 {
#[inline]
fn from(value: BasisPointsSigned32) -> Self {
value.0 as f64 / 100.0
}
}
impl From<BasisPointsSigned32> for StoredF32 {
#[inline]
fn from(value: BasisPointsSigned32) -> Self {
StoredF32::from(value.to_f32())
}
}
impl Add for BasisPointsSigned32 {
type Output = Self;
#[inline]
fn add(self, rhs: Self) -> Self::Output {
Self(self.0 + rhs.0)
}
}
impl AddAssign for BasisPointsSigned32 {
#[inline]
fn add_assign(&mut self, rhs: Self) {
self.0 += rhs.0;
}
}
impl Sub for BasisPointsSigned32 {
type Output = Self;
#[inline]
fn sub(self, rhs: Self) -> Self::Output {
Self(self.0 - rhs.0)
}
}
impl SubAssign for BasisPointsSigned32 {
#[inline]
fn sub_assign(&mut self, rhs: Self) {
self.0 -= rhs.0;
}
}
impl Div<usize> for BasisPointsSigned32 {
type Output = Self;
#[inline]
fn div(self, rhs: usize) -> Self::Output {
Self(self.0 / rhs as i32)
}
}
impl CheckedSub for BasisPointsSigned32 {
fn checked_sub(self, rhs: Self) -> Option<Self> {
self.0.checked_sub(rhs.0).map(Self)
}
}
impl std::fmt::Display for BasisPointsSigned32 {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
let mut buf = itoa::Buffer::new();
let str = buf.format(self.0);
f.write_str(str)
}
}
impl Formattable for BasisPointsSigned32 {
#[inline(always)]
fn fmt_csv(&self, f: &mut String) -> std::fmt::Result {
use std::fmt::Write;
write!(f, "{}", self)
}
}
crates/brk_types/src/datarange.rs
+3 -3
View File
@@ -6,17 +6,17 @@ use crate::{de_unquote_i64, de_unquote_limit, Limit};
/// Range parameters for slicing data
#[derive(Default, Debug, Deserialize, JsonSchema)]
pub struct DataRange {
/// Inclusive starting index, if negative counts from end
/// Inclusive starting index, if negative counts from end. Aliases: `from`, `f`, `s`
#[serde(default, alias = "s", alias = "from", alias = "f", deserialize_with = "de_unquote_i64")]
#[schemars(example = 0, example = -1, example = -10, example = -1000)]
start: Option<i64>,
/// Exclusive ending index, if negative counts from end
/// Exclusive ending index, if negative counts from end. Aliases: `to`, `t`, `e`
#[serde(default, alias = "e", alias = "to", alias = "t", deserialize_with = "de_unquote_i64")]
#[schemars(example = 1000)]
end: Option<i64>,
/// Maximum number of values to return (ignored if `end` is set)
/// Maximum number of values to return (ignored if `end` is set). Aliases: `count`, `c`, `l`
#[serde(default, alias = "l", alias = "count", alias = "c", deserialize_with = "de_unquote_limit")]
limit: Option<Limit>,
}
crates/brk_types/src/lib.rs
+8
View File
@@ -15,6 +15,10 @@ mod addresstxidsparam;
mod addressvalidation;
mod age;
mod anyaddressindex;
mod basis_points_16;
mod basis_points_32;
mod basis_points_signed_16;
mod basis_points_signed_32;
mod bitcoin;
mod blkmetadata;
mod blkposition;
@@ -202,6 +206,10 @@ pub use addresstxidsparam::*;
pub use addressvalidation::*;
pub use age::*;
pub use anyaddressindex::*;
pub use basis_points_16::*;
pub use basis_points_32::*;
pub use basis_points_signed_16::*;
pub use basis_points_signed_32::*;
pub use bitcoin::*;
pub use blkmetadata::*;
pub use blkposition::*;
crates/brk_types/src/percentile.rs
+1 -1
View File
@@ -30,7 +30,7 @@ where
if fract != 0.0 {
let left = sorted.get(index as usize).unwrap().clone();
let right = sorted.get(index.ceil() as usize).unwrap().clone();
left / 2 + right / 2
(left + right) / 2
} else {
sorted.get(index as usize).unwrap().clone()
}
docs/README.md
+1 -1
View File
@@ -43,7 +43,7 @@ curl https://bitview.space/api/mempool/price
Query metrics and blockchain data in JSON or CSV.
[Documentation](https://bitview.space/api) · [JavaScript](https://www.npmjs.com/package/brk-client) · [Python](https://pypi.org/project/brk-client) · [Rust](https://crates.io/crates/brk_client) · [LLM-friendly schema](https://bitview.space/api#tag/server/GET/api.json)
[Documentation](https://bitview.space/api) · [JavaScript](https://www.npmjs.com/package/brk-client) · [Python](https://pypi.org/project/brk-client) · [Rust](https://crates.io/crates/brk_client) · [llms.txt](https://bitview.space/llms.txt) · [LLM-friendly schema](https://bitview.space/api.json)
### Self-host
modules/brk-client/index.js
+127 -241
View File
@@ -2866,6 +2866,45 @@ function create_10y1m1w1y2y3m3y4y5y6m6y8yPattern3(client, acc) {
};
}
/**
* @typedef {Object} _10y1m1w1y2y3m3y4y5y6m6y8yPattern2
* @property {MetricPattern1<StoredF32>} _10y
* @property {MetricPattern1<StoredF32>} _1m
* @property {MetricPattern1<StoredF32>} _1w
* @property {MetricPattern1<StoredF32>} _1y
* @property {MetricPattern1<StoredF32>} _2y
* @property {MetricPattern1<StoredF32>} _3m
* @property {MetricPattern1<StoredF32>} _3y
* @property {MetricPattern1<StoredF32>} _4y
* @property {MetricPattern1<StoredF32>} _5y
* @property {MetricPattern1<StoredF32>} _6m
* @property {MetricPattern1<StoredF32>} _6y
* @property {MetricPattern1<StoredF32>} _8y
*/
/**
* Create a _10y1m1w1y2y3m3y4y5y6m6y8yPattern2 pattern node
* @param {BrkClientBase} client
* @param {string} acc - Accumulated metric name
* @returns {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2}
*/
function create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, acc) {
return {
_10y: createMetricPattern1(client, _p('10y', acc)),
_1m: createMetricPattern1(client, _p('1m', acc)),
_1w: createMetricPattern1(client, _p('1w', acc)),
_1y: createMetricPattern1(client, _p('1y', acc)),
_2y: createMetricPattern1(client, _p('2y', acc)),
_3m: createMetricPattern1(client, _p('3m', acc)),
_3y: createMetricPattern1(client, _p('3y', acc)),
_4y: createMetricPattern1(client, _p('4y', acc)),
_5y: createMetricPattern1(client, _p('5y', acc)),
_6m: createMetricPattern1(client, _p('6m', acc)),
_6y: createMetricPattern1(client, _p('6y', acc)),
_8y: createMetricPattern1(client, _p('8y', acc)),
};
}
/**
* @typedef {Object} InvestedNegNetNuplSupplyUnrealizedPattern
* @property {MetricPattern1<StoredF32>} investedCapitalInLossPct
@@ -2905,88 +2944,6 @@ function createInvestedNegNetNuplSupplyUnrealizedPattern(client, acc) {
};
}
/**
* @template T
* @typedef {Object} _10y1m1w1y2y3m3y4y5y6m6y8yPattern2
* @property {MetricPattern1<T>} _10y
* @property {MetricPattern1<T>} _1m
* @property {MetricPattern1<T>} _1w
* @property {MetricPattern1<T>} _1y
* @property {MetricPattern1<T>} _2y
* @property {MetricPattern1<T>} _3m
* @property {MetricPattern1<T>} _3y
* @property {MetricPattern1<T>} _4y
* @property {MetricPattern1<T>} _5y
* @property {MetricPattern1<T>} _6m
* @property {MetricPattern1<T>} _6y
* @property {MetricPattern1<T>} _8y
*/
/**
* Create a _10y1m1w1y2y3m3y4y5y6m6y8yPattern2 pattern node
* @template T
* @param {BrkClientBase} client
* @param {string} acc - Accumulated metric name
* @returns {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<T>}
*/
function create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, acc) {
return {
_10y: createMetricPattern1(client, _p('10y', acc)),
_1m: createMetricPattern1(client, _p('1m', acc)),
_1w: createMetricPattern1(client, _p('1w', acc)),
_1y: createMetricPattern1(client, _p('1y', acc)),
_2y: createMetricPattern1(client, _p('2y', acc)),
_3m: createMetricPattern1(client, _p('3m', acc)),
_3y: createMetricPattern1(client, _p('3y', acc)),
_4y: createMetricPattern1(client, _p('4y', acc)),
_5y: createMetricPattern1(client, _p('5y', acc)),
_6m: createMetricPattern1(client, _p('6m', acc)),
_6y: createMetricPattern1(client, _p('6y', acc)),
_8y: createMetricPattern1(client, _p('8y', acc)),
};
}
/**
* @template T
* @typedef {Object} _201520162017201820192020202120222023202420252026Pattern2
* @property {MetricPattern1<T>} _2015
* @property {MetricPattern1<T>} _2016
* @property {MetricPattern1<T>} _2017
* @property {MetricPattern1<T>} _2018
* @property {MetricPattern1<T>} _2019
* @property {MetricPattern1<T>} _2020
* @property {MetricPattern1<T>} _2021
* @property {MetricPattern1<T>} _2022
* @property {MetricPattern1<T>} _2023
* @property {MetricPattern1<T>} _2024
* @property {MetricPattern1<T>} _2025
* @property {MetricPattern1<T>} _2026
*/
/**
* Create a _201520162017201820192020202120222023202420252026Pattern2 pattern node
* @template T
* @param {BrkClientBase} client
* @param {string} acc - Accumulated metric name
* @returns {_201520162017201820192020202120222023202420252026Pattern2<T>}
*/
function create_201520162017201820192020202120222023202420252026Pattern2(client, acc) {
return {
_2015: createMetricPattern1(client, _m(acc, '2015_returns')),
_2016: createMetricPattern1(client, _m(acc, '2016_returns')),
_2017: createMetricPattern1(client, _m(acc, '2017_returns')),
_2018: createMetricPattern1(client, _m(acc, '2018_returns')),
_2019: createMetricPattern1(client, _m(acc, '2019_returns')),
_2020: createMetricPattern1(client, _m(acc, '2020_returns')),
_2021: createMetricPattern1(client, _m(acc, '2021_returns')),
_2022: createMetricPattern1(client, _m(acc, '2022_returns')),
_2023: createMetricPattern1(client, _m(acc, '2023_returns')),
_2024: createMetricPattern1(client, _m(acc, '2024_returns')),
_2025: createMetricPattern1(client, _m(acc, '2025_returns')),
_2026: createMetricPattern1(client, _m(acc, '2026_returns')),
};
}
/**
* @typedef {Object} AverageCumulativeMaxMedianMinPct10Pct25Pct75Pct90RollingSumPattern
* @property {MetricPattern18<StoredU64>} average
@@ -3580,6 +3537,31 @@ function createInvestedMaxMinPercentilesSpotPattern(client, acc) {
};
}
/**
* @typedef {Object} EmaHistogramLineSignalPattern
* @property {MetricPattern1<StoredF32>} emaFast
* @property {MetricPattern1<StoredF32>} emaSlow
* @property {MetricPattern1<StoredF32>} histogram
* @property {MetricPattern1<StoredF32>} line
* @property {MetricPattern1<StoredF32>} signal
*/
/**
* Create a EmaHistogramLineSignalPattern pattern node
* @param {BrkClientBase} client
* @param {string} acc - Accumulated metric name
* @returns {EmaHistogramLineSignalPattern}
*/
function createEmaHistogramLineSignalPattern(client, acc) {
return {
emaFast: createMetricPattern1(client, _m(acc, 'ema_fast_1y')),
emaSlow: createMetricPattern1(client, _m(acc, 'ema_slow_1y')),
histogram: createMetricPattern1(client, _m(acc, 'histogram_1y')),
line: createMetricPattern1(client, _m(acc, 'line_1y')),
signal: createMetricPattern1(client, _m(acc, 'signal_1y')),
};
}
/**
* @typedef {Object} _1y24h30d7dPattern2
* @property {BtcCentsSatsUsdPattern} _1y
@@ -3735,27 +3717,6 @@ function createCentsSatsUsdPattern(client, acc) {
};
}
/**
* @typedef {Object} HistogramLineSignalPattern
* @property {MetricPattern1<StoredF32>} histogram
* @property {MetricPattern1<StoredF32>} line
* @property {MetricPattern1<StoredF32>} signal
*/
/**
* Create a HistogramLineSignalPattern pattern node
* @param {BrkClientBase} client
* @param {string} acc - Accumulated metric name
* @returns {HistogramLineSignalPattern}
*/
function createHistogramLineSignalPattern(client, acc) {
return {
histogram: createMetricPattern1(client, _m(acc, 'histogram_1y')),
line: createMetricPattern1(client, _m(acc, 'line_1y')),
signal: createMetricPattern1(client, _m(acc, 'signal_1y')),
};
}
/**
* @template T
* @typedef {Object} _6bBlockTxindexPattern
@@ -3994,7 +3955,7 @@ function createRatioPattern2(client, acc) {
/**
* @typedef {Object} MetricsTree_Blocks_Difficulty
* @property {MetricPattern1<StoredF64>} raw
* @property {MetricPattern1<StoredF32>} asHash
* @property {MetricPattern1<StoredF64>} asHash
* @property {MetricPattern1<StoredF32>} adjustment
* @property {MetricPattern1<DifficultyEpoch>} epoch
* @property {MetricPattern1<StoredU32>} blocksBeforeNextAdjustment
@@ -4043,22 +4004,34 @@ function createRatioPattern2(client, acc) {
* @property {MetricPattern18<Height>} height34dAgo
* @property {MetricPattern18<Height>} height55dAgo
* @property {MetricPattern18<Height>} height2mAgo
* @property {MetricPattern18<Height>} height9wAgo
* @property {MetricPattern18<Height>} height12wAgo
* @property {MetricPattern18<Height>} height89dAgo
* @property {MetricPattern18<Height>} height3mAgo
* @property {MetricPattern18<Height>} height14wAgo
* @property {MetricPattern18<Height>} height111dAgo
* @property {MetricPattern18<Height>} height144dAgo
* @property {MetricPattern18<Height>} height3mAgo
* @property {MetricPattern18<Height>} height6mAgo
* @property {MetricPattern18<Height>} height26wAgo
* @property {MetricPattern18<Height>} height200dAgo
* @property {MetricPattern18<Height>} height9mAgo
* @property {MetricPattern18<Height>} height350dAgo
* @property {MetricPattern18<Height>} height12mAgo
* @property {MetricPattern18<Height>} height1yAgo
* @property {MetricPattern18<Height>} height14mAgo
* @property {MetricPattern18<Height>} height2yAgo
* @property {MetricPattern18<Height>} height200wAgo
* @property {MetricPattern18<Height>} height26mAgo
* @property {MetricPattern18<Height>} height3yAgo
* @property {MetricPattern18<Height>} height200wAgo
* @property {MetricPattern18<Height>} height4yAgo
* @property {MetricPattern18<Height>} height5yAgo
* @property {MetricPattern18<Height>} height6yAgo
* @property {MetricPattern18<Height>} height8yAgo
* @property {MetricPattern18<Height>} height9yAgo
* @property {MetricPattern18<Height>} height10yAgo
* @property {MetricPattern18<Height>} height12yAgo
* @property {MetricPattern18<Height>} height14yAgo
* @property {MetricPattern18<Height>} height26yAgo
*/
/**
@@ -4269,9 +4242,9 @@ function createRatioPattern2(client, acc) {
* @typedef {Object} MetricsTree_Mining_Hashrate
* @property {MetricPattern1<StoredF64>} hashRate
* @property {MetricPattern1<StoredF64>} hashRate1wSma
* @property {MetricPattern1<StoredF32>} hashRate1mSma
* @property {MetricPattern1<StoredF32>} hashRate2mSma
* @property {MetricPattern1<StoredF32>} hashRate1ySma
* @property {MetricPattern1<StoredF64>} hashRate1mSma
* @property {MetricPattern1<StoredF64>} hashRate2mSma
* @property {MetricPattern1<StoredF64>} hashRate1ySma
* @property {MetricPattern1<StoredF64>} hashRateAth
* @property {MetricPattern1<StoredF32>} hashRateDrawdown
* @property {MetricPattern1<StoredF32>} hashPriceThs
@@ -4761,25 +4734,13 @@ function createRatioPattern2(client, acc) {
* @property {MetricPattern18<Sats>} dcaSatsPerDay
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern3} periodStack
* @property {MetricsTree_Market_Dca_PeriodAveragePrice} periodAveragePrice
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>} periodReturns
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2} periodReturns
* @property {_10y2y3y4y5y6y8yPattern} periodCagr
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredU32>} periodDaysInProfit
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredU32>} periodDaysInLoss
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>} periodMinReturn
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>} periodMaxReturn
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern3} periodLumpSumStack
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>} periodLumpSumReturns
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredU32>} periodLumpSumDaysInProfit
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredU32>} periodLumpSumDaysInLoss
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>} periodLumpSumMinReturn
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2<StoredF32>} periodLumpSumMaxReturn
* @property {_10y1m1w1y2y3m3y4y5y6m6y8yPattern2} periodLumpSumReturns
* @property {MetricsTree_Market_Dca_ClassStack} classStack
* @property {MetricsTree_Market_Dca_ClassAveragePrice} classAveragePrice
* @property {_201520162017201820192020202120222023202420252026Pattern2<StoredF32>} classReturns
* @property {MetricsTree_Market_Dca_ClassDaysInProfit} classDaysInProfit
* @property {MetricsTree_Market_Dca_ClassDaysInLoss} classDaysInLoss
* @property {MetricsTree_Market_Dca_ClassMinReturn} classMinReturn
* @property {MetricsTree_Market_Dca_ClassMaxReturn} classMaxReturn
* @property {MetricsTree_Market_Dca_ClassReturns} classReturns
*/
/**
@@ -4831,55 +4792,7 @@ function createRatioPattern2(client, acc) {
*/
/**
* @typedef {Object} MetricsTree_Market_Dca_ClassDaysInProfit
* @property {MetricPattern1<StoredU32>} _2015
* @property {MetricPattern1<StoredU32>} _2016
* @property {MetricPattern1<StoredU32>} _2017
* @property {MetricPattern1<StoredU32>} _2018
* @property {MetricPattern1<StoredU32>} _2019
* @property {MetricPattern1<StoredU32>} _2020
* @property {MetricPattern1<StoredU32>} _2021
* @property {MetricPattern1<StoredU32>} _2022
* @property {MetricPattern1<StoredU32>} _2023
* @property {MetricPattern1<StoredU32>} _2024
* @property {MetricPattern1<StoredU32>} _2025
* @property {MetricPattern1<StoredU32>} _2026
*/
/**
* @typedef {Object} MetricsTree_Market_Dca_ClassDaysInLoss
* @property {MetricPattern1<StoredU32>} _2015
* @property {MetricPattern1<StoredU32>} _2016
* @property {MetricPattern1<StoredU32>} _2017
* @property {MetricPattern1<StoredU32>} _2018
* @property {MetricPattern1<StoredU32>} _2019
* @property {MetricPattern1<StoredU32>} _2020
* @property {MetricPattern1<StoredU32>} _2021
* @property {MetricPattern1<StoredU32>} _2022
* @property {MetricPattern1<StoredU32>} _2023
* @property {MetricPattern1<StoredU32>} _2024
* @property {MetricPattern1<StoredU32>} _2025
* @property {MetricPattern1<StoredU32>} _2026
*/
/**
* @typedef {Object} MetricsTree_Market_Dca_ClassMinReturn
* @property {MetricPattern1<StoredF32>} _2015
* @property {MetricPattern1<StoredF32>} _2016
* @property {MetricPattern1<StoredF32>} _2017
* @property {MetricPattern1<StoredF32>} _2018
* @property {MetricPattern1<StoredF32>} _2019
* @property {MetricPattern1<StoredF32>} _2020
* @property {MetricPattern1<StoredF32>} _2021
* @property {MetricPattern1<StoredF32>} _2022
* @property {MetricPattern1<StoredF32>} _2023
* @property {MetricPattern1<StoredF32>} _2024
* @property {MetricPattern1<StoredF32>} _2025
* @property {MetricPattern1<StoredF32>} _2026
*/
/**
* @typedef {Object} MetricsTree_Market_Dca_ClassMaxReturn
* @typedef {Object} MetricsTree_Market_Dca_ClassReturns
* @property {MetricPattern1<StoredF32>} _2015
* @property {MetricPattern1<StoredF32>} _2016
* @property {MetricPattern1<StoredF32>} _2017
@@ -4961,11 +4874,13 @@ function createRatioPattern2(client, acc) {
* @property {MetricsTree_Market_Indicators_Macd_1d} _1d
* @property {MetricsTree_Market_Indicators_Macd_1w} _1w
* @property {MetricsTree_Market_Indicators_Macd_1m} _1m
* @property {HistogramLineSignalPattern} _1y
* @property {EmaHistogramLineSignalPattern} _1y
*/
/**
* @typedef {Object} MetricsTree_Market_Indicators_Macd_1d
* @property {MetricPattern1<StoredF32>} emaFast
* @property {MetricPattern1<StoredF32>} emaSlow
* @property {MetricPattern1<StoredF32>} line
* @property {MetricPattern1<StoredF32>} signal
* @property {MetricPattern1<StoredF32>} histogram
@@ -4973,6 +4888,8 @@ function createRatioPattern2(client, acc) {
/**
* @typedef {Object} MetricsTree_Market_Indicators_Macd_1w
* @property {MetricPattern1<StoredF32>} emaFast
* @property {MetricPattern1<StoredF32>} emaSlow
* @property {MetricPattern1<StoredF32>} line
* @property {MetricPattern1<StoredF32>} signal
* @property {MetricPattern1<StoredF32>} histogram
@@ -4980,6 +4897,8 @@ function createRatioPattern2(client, acc) {
/**
* @typedef {Object} MetricsTree_Market_Indicators_Macd_1m
* @property {MetricPattern1<StoredF32>} emaFast
* @property {MetricPattern1<StoredF32>} emaSlow
* @property {MetricPattern1<StoredF32>} line
* @property {MetricPattern1<StoredF32>} signal
* @property {MetricPattern1<StoredF32>} histogram
@@ -6582,22 +6501,34 @@ class BrkClient extends BrkClientBase {
height34dAgo: createMetricPattern18(this, 'height_34d_ago'),
height55dAgo: createMetricPattern18(this, 'height_55d_ago'),
height2mAgo: createMetricPattern18(this, 'height_2m_ago'),
height9wAgo: createMetricPattern18(this, 'height_9w_ago'),
height12wAgo: createMetricPattern18(this, 'height_12w_ago'),
height89dAgo: createMetricPattern18(this, 'height_89d_ago'),
height3mAgo: createMetricPattern18(this, 'height_3m_ago'),
height14wAgo: createMetricPattern18(this, 'height_14w_ago'),
height111dAgo: createMetricPattern18(this, 'height_111d_ago'),
height144dAgo: createMetricPattern18(this, 'height_144d_ago'),
height3mAgo: createMetricPattern18(this, 'height_3m_ago'),
height6mAgo: createMetricPattern18(this, 'height_6m_ago'),
height26wAgo: createMetricPattern18(this, 'height_26w_ago'),
height200dAgo: createMetricPattern18(this, 'height_200d_ago'),
height9mAgo: createMetricPattern18(this, 'height_9m_ago'),
height350dAgo: createMetricPattern18(this, 'height_350d_ago'),
height12mAgo: createMetricPattern18(this, 'height_12m_ago'),
height1yAgo: createMetricPattern18(this, 'height_1y_ago'),
height14mAgo: createMetricPattern18(this, 'height_14m_ago'),
height2yAgo: createMetricPattern18(this, 'height_2y_ago'),
height200wAgo: createMetricPattern18(this, 'height_200w_ago'),
height26mAgo: createMetricPattern18(this, 'height_26m_ago'),
height3yAgo: createMetricPattern18(this, 'height_3y_ago'),
height200wAgo: createMetricPattern18(this, 'height_200w_ago'),
height4yAgo: createMetricPattern18(this, 'height_4y_ago'),
height5yAgo: createMetricPattern18(this, 'height_5y_ago'),
height6yAgo: createMetricPattern18(this, 'height_6y_ago'),
height8yAgo: createMetricPattern18(this, 'height_8y_ago'),
height9yAgo: createMetricPattern18(this, 'height_9y_ago'),
height10yAgo: createMetricPattern18(this, 'height_10y_ago'),
height12yAgo: createMetricPattern18(this, 'height_12y_ago'),
height14yAgo: createMetricPattern18(this, 'height_14y_ago'),
height26yAgo: createMetricPattern18(this, 'height_26y_ago'),
},
interval: createAverageHeightMaxMedianMinPct10Pct25Pct75Pct90Pattern(this, 'block_interval'),
halving: {
@@ -7111,16 +7042,8 @@ class BrkClient extends BrkClientBase {
},
periodReturns: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'dca_returns'),
periodCagr: create_10y2y3y4y5y6y8yPattern(this, 'dca_cagr'),
periodDaysInProfit: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'dca_days_in_profit'),
periodDaysInLoss: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'dca_days_in_loss'),
periodMinReturn: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'dca_min_return'),
periodMaxReturn: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'dca_max_return'),
periodLumpSumStack: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern3(this, 'lump_sum_stack'),
periodLumpSumReturns: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'lump_sum_returns'),
periodLumpSumDaysInProfit: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'lump_sum_days_in_profit'),
periodLumpSumDaysInLoss: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'lump_sum_days_in_loss'),
periodLumpSumMinReturn: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'lump_sum_min_return'),
periodLumpSumMaxReturn: create_10y1m1w1y2y3m3y4y5y6m6y8yPattern2(this, 'lump_sum_max_return'),
classStack: {
_2015: createBtcCentsSatsUsdPattern(this, 'dca_class_2015_stack'),
_2016: createBtcCentsSatsUsdPattern(this, 'dca_class_2016_stack'),
@@ -7149,62 +7072,19 @@ class BrkClient extends BrkClientBase {
_2025: createCentsSatsUsdPattern(this, 'dca_class_2025_average_price'),
_2026: createCentsSatsUsdPattern(this, 'dca_class_2026_average_price'),
},
classReturns: create_201520162017201820192020202120222023202420252026Pattern2(this, 'dca_class'),
classDaysInProfit: {
_2015: createMetricPattern1(this, 'dca_class_2015_days_in_profit'),
_2016: createMetricPattern1(this, 'dca_class_2016_days_in_profit'),
_2017: createMetricPattern1(this, 'dca_class_2017_days_in_profit'),
_2018: createMetricPattern1(this, 'dca_class_2018_days_in_profit'),
_2019: createMetricPattern1(this, 'dca_class_2019_days_in_profit'),
_2020: createMetricPattern1(this, 'dca_class_2020_days_in_profit'),
_2021: createMetricPattern1(this, 'dca_class_2021_days_in_profit'),
_2022: createMetricPattern1(this, 'dca_class_2022_days_in_profit'),
_2023: createMetricPattern1(this, 'dca_class_2023_days_in_profit'),
_2024: createMetricPattern1(this, 'dca_class_2024_days_in_profit'),
_2025: createMetricPattern1(this, 'dca_class_2025_days_in_profit'),
_2026: createMetricPattern1(this, 'dca_class_2026_days_in_profit'),
},
classDaysInLoss: {
_2015: createMetricPattern1(this, 'dca_class_2015_days_in_loss'),
_2016: createMetricPattern1(this, 'dca_class_2016_days_in_loss'),
_2017: createMetricPattern1(this, 'dca_class_2017_days_in_loss'),
_2018: createMetricPattern1(this, 'dca_class_2018_days_in_loss'),
_2019: createMetricPattern1(this, 'dca_class_2019_days_in_loss'),
_2020: createMetricPattern1(this, 'dca_class_2020_days_in_loss'),
_2021: createMetricPattern1(this, 'dca_class_2021_days_in_loss'),
_2022: createMetricPattern1(this, 'dca_class_2022_days_in_loss'),
_2023: createMetricPattern1(this, 'dca_class_2023_days_in_loss'),
_2024: createMetricPattern1(this, 'dca_class_2024_days_in_loss'),
_2025: createMetricPattern1(this, 'dca_class_2025_days_in_loss'),
_2026: createMetricPattern1(this, 'dca_class_2026_days_in_loss'),
},
classMinReturn: {
_2015: createMetricPattern1(this, 'dca_class_2015_min_return'),
_2016: createMetricPattern1(this, 'dca_class_2016_min_return'),
_2017: createMetricPattern1(this, 'dca_class_2017_min_return'),
_2018: createMetricPattern1(this, 'dca_class_2018_min_return'),
_2019: createMetricPattern1(this, 'dca_class_2019_min_return'),
_2020: createMetricPattern1(this, 'dca_class_2020_min_return'),
_2021: createMetricPattern1(this, 'dca_class_2021_min_return'),
_2022: createMetricPattern1(this, 'dca_class_2022_min_return'),
_2023: createMetricPattern1(this, 'dca_class_2023_min_return'),
_2024: createMetricPattern1(this, 'dca_class_2024_min_return'),
_2025: createMetricPattern1(this, 'dca_class_2025_min_return'),
_2026: createMetricPattern1(this, 'dca_class_2026_min_return'),
},
classMaxReturn: {
_2015: createMetricPattern1(this, 'dca_class_2015_max_return'),
_2016: createMetricPattern1(this, 'dca_class_2016_max_return'),
_2017: createMetricPattern1(this, 'dca_class_2017_max_return'),
_2018: createMetricPattern1(this, 'dca_class_2018_max_return'),
_2019: createMetricPattern1(this, 'dca_class_2019_max_return'),
_2020: createMetricPattern1(this, 'dca_class_2020_max_return'),
_2021: createMetricPattern1(this, 'dca_class_2021_max_return'),
_2022: createMetricPattern1(this, 'dca_class_2022_max_return'),
_2023: createMetricPattern1(this, 'dca_class_2023_max_return'),
_2024: createMetricPattern1(this, 'dca_class_2024_max_return'),
_2025: createMetricPattern1(this, 'dca_class_2025_max_return'),
_2026: createMetricPattern1(this, 'dca_class_2026_max_return'),
classReturns: {
_2015: createMetricPattern1(this, 'dca_class_2015_returns'),
_2016: createMetricPattern1(this, 'dca_class_2016_returns'),
_2017: createMetricPattern1(this, 'dca_class_2017_returns'),
_2018: createMetricPattern1(this, 'dca_class_2018_returns'),
_2019: createMetricPattern1(this, 'dca_class_2019_returns'),
_2020: createMetricPattern1(this, 'dca_class_2020_returns'),
_2021: createMetricPattern1(this, 'dca_class_2021_returns'),
_2022: createMetricPattern1(this, 'dca_class_2022_returns'),
_2023: createMetricPattern1(this, 'dca_class_2023_returns'),
_2024: createMetricPattern1(this, 'dca_class_2024_returns'),
_2025: createMetricPattern1(this, 'dca_class_2025_returns'),
_2026: createMetricPattern1(this, 'dca_class_2026_returns'),
},
},
indicators: {
@@ -7254,21 +7134,27 @@ class BrkClient extends BrkClientBase {
piCycle: createMetricPattern1(this, 'pi_cycle'),
macd: {
_1d: {
emaFast: createMetricPattern1(this, 'macd_ema_fast_1d'),
emaSlow: createMetricPattern1(this, 'macd_ema_slow_1d'),
line: createMetricPattern1(this, 'macd_line_1d'),
signal: createMetricPattern1(this, 'macd_signal_1d'),
histogram: createMetricPattern1(this, 'macd_histogram_1d'),
},
_1w: {
emaFast: createMetricPattern1(this, 'macd_ema_fast_1w'),
emaSlow: createMetricPattern1(this, 'macd_ema_slow_1w'),
line: createMetricPattern1(this, 'macd_line_1w'),
signal: createMetricPattern1(this, 'macd_signal_1w'),
histogram: createMetricPattern1(this, 'macd_histogram_1w'),
},
_1m: {
emaFast: createMetricPattern1(this, 'macd_ema_fast_1m'),
emaSlow: createMetricPattern1(this, 'macd_ema_slow_1m'),
line: createMetricPattern1(this, 'macd_line_1m'),
signal: createMetricPattern1(this, 'macd_signal_1m'),
histogram: createMetricPattern1(this, 'macd_histogram_1m'),
},
_1y: createHistogramLineSignalPattern(this, 'macd'),
_1y: createEmaHistogramLineSignalPattern(this, 'macd'),
},
gini: createMetricPattern1(this, 'gini'),
},
modules/brk-client/package.json
+8 -2
View File
@@ -7,7 +7,7 @@
"test:basic": "node tests/basic.js",
"test:tree": "node tests/tree.js"
},
"description": "BRK JavaScript client",
"description": "Bitcoin on-chain analytics client — thousands of metrics, block explorer, and address index",
"engines": {
"node": ">=18"
},
@@ -23,7 +23,13 @@
"brk",
"bitcoin",
"blockchain",
"research"
"research",
"on-chain",
"analytics",
"metrics",
"api",
"data",
"cryptocurrency"
],
"license": "MIT",
"main": "index.js",
packages/brk_client/brk_client/__init__.py
+70 -131
View File
@@ -2688,6 +2688,24 @@ class _10y1m1w1y2y3m3y4y5y6m6y8yPattern3:
self._6y: BtcCentsSatsUsdPattern = BtcCentsSatsUsdPattern(client, _p('6y', acc))
self._8y: BtcCentsSatsUsdPattern = BtcCentsSatsUsdPattern(client, _p('8y', acc))
class _10y1m1w1y2y3m3y4y5y6m6y8yPattern2:
"""Pattern struct for repeated tree structure."""
def __init__(self, client: BrkClientBase, acc: str):
"""Create pattern node with accumulated metric name."""
self._10y: MetricPattern1[StoredF32] = MetricPattern1(client, _p('10y', acc))
self._1m: MetricPattern1[StoredF32] = MetricPattern1(client, _p('1m', acc))
self._1w: MetricPattern1[StoredF32] = MetricPattern1(client, _p('1w', acc))
self._1y: MetricPattern1[StoredF32] = MetricPattern1(client, _p('1y', acc))
self._2y: MetricPattern1[StoredF32] = MetricPattern1(client, _p('2y', acc))
self._3m: MetricPattern1[StoredF32] = MetricPattern1(client, _p('3m', acc))
self._3y: MetricPattern1[StoredF32] = MetricPattern1(client, _p('3y', acc))
self._4y: MetricPattern1[StoredF32] = MetricPattern1(client, _p('4y', acc))
self._5y: MetricPattern1[StoredF32] = MetricPattern1(client, _p('5y', acc))
self._6m: MetricPattern1[StoredF32] = MetricPattern1(client, _p('6m', acc))
self._6y: MetricPattern1[StoredF32] = MetricPattern1(client, _p('6y', acc))
self._8y: MetricPattern1[StoredF32] = MetricPattern1(client, _p('8y', acc))
class InvestedNegNetNuplSupplyUnrealizedPattern:
"""Pattern struct for repeated tree structure."""
@@ -2706,42 +2724,6 @@ class InvestedNegNetNuplSupplyUnrealizedPattern:
self.unrealized_loss_rel_to_market_cap: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'unrealized_loss_rel_to_market_cap'))
self.unrealized_profit_rel_to_market_cap: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'unrealized_profit_rel_to_market_cap'))
class _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(Generic[T]):
"""Pattern struct for repeated tree structure."""
def __init__(self, client: BrkClientBase, acc: str):
"""Create pattern node with accumulated metric name."""
self._10y: MetricPattern1[T] = MetricPattern1(client, _p('10y', acc))
self._1m: MetricPattern1[T] = MetricPattern1(client, _p('1m', acc))
self._1w: MetricPattern1[T] = MetricPattern1(client, _p('1w', acc))
self._1y: MetricPattern1[T] = MetricPattern1(client, _p('1y', acc))
self._2y: MetricPattern1[T] = MetricPattern1(client, _p('2y', acc))
self._3m: MetricPattern1[T] = MetricPattern1(client, _p('3m', acc))
self._3y: MetricPattern1[T] = MetricPattern1(client, _p('3y', acc))
self._4y: MetricPattern1[T] = MetricPattern1(client, _p('4y', acc))
self._5y: MetricPattern1[T] = MetricPattern1(client, _p('5y', acc))
self._6m: MetricPattern1[T] = MetricPattern1(client, _p('6m', acc))
self._6y: MetricPattern1[T] = MetricPattern1(client, _p('6y', acc))
self._8y: MetricPattern1[T] = MetricPattern1(client, _p('8y', acc))
class _201520162017201820192020202120222023202420252026Pattern2(Generic[T]):
"""Pattern struct for repeated tree structure."""
def __init__(self, client: BrkClientBase, acc: str):
"""Create pattern node with accumulated metric name."""
self._2015: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2015_returns'))
self._2016: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2016_returns'))
self._2017: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2017_returns'))
self._2018: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2018_returns'))
self._2019: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2019_returns'))
self._2020: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2020_returns'))
self._2021: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2021_returns'))
self._2022: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2022_returns'))
self._2023: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2023_returns'))
self._2024: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2024_returns'))
self._2025: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2025_returns'))
self._2026: MetricPattern1[T] = MetricPattern1(client, _m(acc, '2026_returns'))
class AverageCumulativeMaxMedianMinPct10Pct25Pct75Pct90RollingSumPattern:
"""Pattern struct for repeated tree structure."""
@@ -3008,6 +2990,17 @@ class InvestedMaxMinPercentilesSpotPattern:
self.spot_cost_basis_percentile: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'spot_cost_basis_percentile'))
self.spot_invested_capital_percentile: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'spot_invested_capital_percentile'))
class EmaHistogramLineSignalPattern:
"""Pattern struct for repeated tree structure."""
def __init__(self, client: BrkClientBase, acc: str):
"""Create pattern node with accumulated metric name."""
self.ema_fast: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'ema_fast_1y'))
self.ema_slow: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'ema_slow_1y'))
self.histogram: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'histogram_1y'))
self.line: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'line_1y'))
self.signal: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'signal_1y'))
class _1y24h30d7dPattern2:
"""Pattern struct for repeated tree structure."""
@@ -3074,15 +3067,6 @@ class CentsSatsUsdPattern:
self.sats: MetricPattern1[SatsFract] = MetricPattern1(client, _m(acc, 'sats'))
self.usd: MetricPattern1[Dollars] = MetricPattern1(client, _m(acc, 'usd'))
class HistogramLineSignalPattern:
"""Pattern struct for repeated tree structure."""
def __init__(self, client: BrkClientBase, acc: str):
"""Create pattern node with accumulated metric name."""
self.histogram: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'histogram_1y'))
self.line: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'line_1y'))
self.signal: MetricPattern1[StoredF32] = MetricPattern1(client, _m(acc, 'signal_1y'))
class _6bBlockTxindexPattern(Generic[T]):
"""Pattern struct for repeated tree structure."""
@@ -3171,7 +3155,7 @@ class MetricsTree_Blocks_Difficulty:
def __init__(self, client: BrkClientBase, base_path: str = ''):
self.raw: MetricPattern1[StoredF64] = MetricPattern1(client, 'difficulty')
self.as_hash: MetricPattern1[StoredF32] = MetricPattern1(client, 'difficulty_as_hash')
self.as_hash: MetricPattern1[StoredF64] = MetricPattern1(client, 'difficulty_as_hash')
self.adjustment: MetricPattern1[StoredF32] = MetricPattern1(client, 'difficulty_adjustment')
self.epoch: MetricPattern1[DifficultyEpoch] = MetricPattern1(client, 'difficulty_epoch')
self.blocks_before_next_adjustment: MetricPattern1[StoredU32] = MetricPattern1(client, 'blocks_before_next_difficulty_adjustment')
@@ -3223,22 +3207,34 @@ class MetricsTree_Blocks_Count:
self.height_34d_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_34d_ago')
self.height_55d_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_55d_ago')
self.height_2m_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_2m_ago')
self.height_9w_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_9w_ago')
self.height_12w_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_12w_ago')
self.height_89d_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_89d_ago')
self.height_3m_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_3m_ago')
self.height_14w_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_14w_ago')
self.height_111d_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_111d_ago')
self.height_144d_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_144d_ago')
self.height_3m_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_3m_ago')
self.height_6m_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_6m_ago')
self.height_26w_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_26w_ago')
self.height_200d_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_200d_ago')
self.height_9m_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_9m_ago')
self.height_350d_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_350d_ago')
self.height_12m_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_12m_ago')
self.height_1y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_1y_ago')
self.height_14m_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_14m_ago')
self.height_2y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_2y_ago')
self.height_200w_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_200w_ago')
self.height_26m_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_26m_ago')
self.height_3y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_3y_ago')
self.height_200w_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_200w_ago')
self.height_4y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_4y_ago')
self.height_5y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_5y_ago')
self.height_6y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_6y_ago')
self.height_8y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_8y_ago')
self.height_9y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_9y_ago')
self.height_10y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_10y_ago')
self.height_12y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_12y_ago')
self.height_14y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_14y_ago')
self.height_26y_ago: MetricPattern18[Height] = MetricPattern18(client, 'height_26y_ago')
class MetricsTree_Blocks_Halving:
"""Metrics tree node."""
@@ -3479,9 +3475,9 @@ class MetricsTree_Mining_Hashrate:
def __init__(self, client: BrkClientBase, base_path: str = ''):
self.hash_rate: MetricPattern1[StoredF64] = MetricPattern1(client, 'hash_rate')
self.hash_rate_1w_sma: MetricPattern1[StoredF64] = MetricPattern1(client, 'hash_rate_1w_sma')
self.hash_rate_1m_sma: MetricPattern1[StoredF32] = MetricPattern1(client, 'hash_rate_1m_sma')
self.hash_rate_2m_sma: MetricPattern1[StoredF32] = MetricPattern1(client, 'hash_rate_2m_sma')
self.hash_rate_1y_sma: MetricPattern1[StoredF32] = MetricPattern1(client, 'hash_rate_1y_sma')
self.hash_rate_1m_sma: MetricPattern1[StoredF64] = MetricPattern1(client, 'hash_rate_1m_sma')
self.hash_rate_2m_sma: MetricPattern1[StoredF64] = MetricPattern1(client, 'hash_rate_2m_sma')
self.hash_rate_1y_sma: MetricPattern1[StoredF64] = MetricPattern1(client, 'hash_rate_1y_sma')
self.hash_rate_ath: MetricPattern1[StoredF64] = MetricPattern1(client, 'hash_rate_ath')
self.hash_rate_drawdown: MetricPattern1[StoredF32] = MetricPattern1(client, 'hash_rate_drawdown')
self.hash_price_ths: MetricPattern1[StoredF32] = MetricPattern1(client, 'hash_price_ths')
@@ -4061,73 +4057,22 @@ class MetricsTree_Market_Dca_ClassAveragePrice:
self._2025: CentsSatsUsdPattern = CentsSatsUsdPattern(client, 'dca_class_2025_average_price')
self._2026: CentsSatsUsdPattern = CentsSatsUsdPattern(client, 'dca_class_2026_average_price')
class MetricsTree_Market_Dca_ClassDaysInProfit:
class MetricsTree_Market_Dca_ClassReturns:
"""Metrics tree node."""
def __init__(self, client: BrkClientBase, base_path: str = ''):
self._2015: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2015_days_in_profit')
self._2016: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2016_days_in_profit')
self._2017: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2017_days_in_profit')
self._2018: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2018_days_in_profit')
self._2019: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2019_days_in_profit')
self._2020: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2020_days_in_profit')
self._2021: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2021_days_in_profit')
self._2022: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2022_days_in_profit')
self._2023: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2023_days_in_profit')
self._2024: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2024_days_in_profit')
self._2025: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2025_days_in_profit')
self._2026: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2026_days_in_profit')
class MetricsTree_Market_Dca_ClassDaysInLoss:
"""Metrics tree node."""
def __init__(self, client: BrkClientBase, base_path: str = ''):
self._2015: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2015_days_in_loss')
self._2016: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2016_days_in_loss')
self._2017: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2017_days_in_loss')
self._2018: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2018_days_in_loss')
self._2019: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2019_days_in_loss')
self._2020: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2020_days_in_loss')
self._2021: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2021_days_in_loss')
self._2022: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2022_days_in_loss')
self._2023: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2023_days_in_loss')
self._2024: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2024_days_in_loss')
self._2025: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2025_days_in_loss')
self._2026: MetricPattern1[StoredU32] = MetricPattern1(client, 'dca_class_2026_days_in_loss')
class MetricsTree_Market_Dca_ClassMinReturn:
"""Metrics tree node."""
def __init__(self, client: BrkClientBase, base_path: str = ''):
self._2015: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2015_min_return')
self._2016: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2016_min_return')
self._2017: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2017_min_return')
self._2018: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2018_min_return')
self._2019: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2019_min_return')
self._2020: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2020_min_return')
self._2021: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2021_min_return')
self._2022: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2022_min_return')
self._2023: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2023_min_return')
self._2024: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2024_min_return')
self._2025: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2025_min_return')
self._2026: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2026_min_return')
class MetricsTree_Market_Dca_ClassMaxReturn:
"""Metrics tree node."""
def __init__(self, client: BrkClientBase, base_path: str = ''):
self._2015: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2015_max_return')
self._2016: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2016_max_return')
self._2017: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2017_max_return')
self._2018: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2018_max_return')
self._2019: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2019_max_return')
self._2020: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2020_max_return')
self._2021: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2021_max_return')
self._2022: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2022_max_return')
self._2023: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2023_max_return')
self._2024: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2024_max_return')
self._2025: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2025_max_return')
self._2026: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2026_max_return')
self._2015: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2015_returns')
self._2016: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2016_returns')
self._2017: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2017_returns')
self._2018: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2018_returns')
self._2019: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2019_returns')
self._2020: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2020_returns')
self._2021: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2021_returns')
self._2022: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2022_returns')
self._2023: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2023_returns')
self._2024: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2024_returns')
self._2025: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2025_returns')
self._2026: MetricPattern1[StoredF32] = MetricPattern1(client, 'dca_class_2026_returns')
class MetricsTree_Market_Dca:
"""Metrics tree node."""
@@ -4136,25 +4081,13 @@ class MetricsTree_Market_Dca:
self.dca_sats_per_day: MetricPattern18[Sats] = MetricPattern18(client, 'dca_sats_per_day')
self.period_stack: _10y1m1w1y2y3m3y4y5y6m6y8yPattern3 = _10y1m1w1y2y3m3y4y5y6m6y8yPattern3(client, 'dca_stack')
self.period_average_price: MetricsTree_Market_Dca_PeriodAveragePrice = MetricsTree_Market_Dca_PeriodAveragePrice(client)
self.period_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredF32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'dca_returns')
self.period_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2 = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'dca_returns')
self.period_cagr: _10y2y3y4y5y6y8yPattern = _10y2y3y4y5y6y8yPattern(client, 'dca_cagr')
self.period_days_in_profit: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredU32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'dca_days_in_profit')
self.period_days_in_loss: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredU32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'dca_days_in_loss')
self.period_min_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredF32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'dca_min_return')
self.period_max_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredF32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'dca_max_return')
self.period_lump_sum_stack: _10y1m1w1y2y3m3y4y5y6m6y8yPattern3 = _10y1m1w1y2y3m3y4y5y6m6y8yPattern3(client, 'lump_sum_stack')
self.period_lump_sum_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredF32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'lump_sum_returns')
self.period_lump_sum_days_in_profit: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredU32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'lump_sum_days_in_profit')
self.period_lump_sum_days_in_loss: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredU32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'lump_sum_days_in_loss')
self.period_lump_sum_min_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredF32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'lump_sum_min_return')
self.period_lump_sum_max_return: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2[StoredF32] = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'lump_sum_max_return')
self.period_lump_sum_returns: _10y1m1w1y2y3m3y4y5y6m6y8yPattern2 = _10y1m1w1y2y3m3y4y5y6m6y8yPattern2(client, 'lump_sum_returns')
self.class_stack: MetricsTree_Market_Dca_ClassStack = MetricsTree_Market_Dca_ClassStack(client)
self.class_average_price: MetricsTree_Market_Dca_ClassAveragePrice = MetricsTree_Market_Dca_ClassAveragePrice(client)
self.class_returns: _201520162017201820192020202120222023202420252026Pattern2[StoredF32] = _201520162017201820192020202120222023202420252026Pattern2(client, 'dca_class')
self.class_days_in_profit: MetricsTree_Market_Dca_ClassDaysInProfit = MetricsTree_Market_Dca_ClassDaysInProfit(client)
self.class_days_in_loss: MetricsTree_Market_Dca_ClassDaysInLoss = MetricsTree_Market_Dca_ClassDaysInLoss(client)
self.class_min_return: MetricsTree_Market_Dca_ClassMinReturn = MetricsTree_Market_Dca_ClassMinReturn(client)
self.class_max_return: MetricsTree_Market_Dca_ClassMaxReturn = MetricsTree_Market_Dca_ClassMaxReturn(client)
self.class_returns: MetricsTree_Market_Dca_ClassReturns = MetricsTree_Market_Dca_ClassReturns(client)
class MetricsTree_Market_Indicators_Rsi_1d:
"""Metrics tree node."""
@@ -4214,6 +4147,8 @@ class MetricsTree_Market_Indicators_Macd_1d:
"""Metrics tree node."""
def __init__(self, client: BrkClientBase, base_path: str = ''):
self.ema_fast: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_ema_fast_1d')
self.ema_slow: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_ema_slow_1d')
self.line: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_line_1d')
self.signal: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_signal_1d')
self.histogram: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_histogram_1d')
@@ -4222,6 +4157,8 @@ class MetricsTree_Market_Indicators_Macd_1w:
"""Metrics tree node."""
def __init__(self, client: BrkClientBase, base_path: str = ''):
self.ema_fast: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_ema_fast_1w')
self.ema_slow: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_ema_slow_1w')
self.line: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_line_1w')
self.signal: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_signal_1w')
self.histogram: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_histogram_1w')
@@ -4230,6 +4167,8 @@ class MetricsTree_Market_Indicators_Macd_1m:
"""Metrics tree node."""
def __init__(self, client: BrkClientBase, base_path: str = ''):
self.ema_fast: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_ema_fast_1m')
self.ema_slow: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_ema_slow_1m')
self.line: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_line_1m')
self.signal: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_signal_1m')
self.histogram: MetricPattern1[StoredF32] = MetricPattern1(client, 'macd_histogram_1m')
@@ -4241,7 +4180,7 @@ class MetricsTree_Market_Indicators_Macd:
self._1d: MetricsTree_Market_Indicators_Macd_1d = MetricsTree_Market_Indicators_Macd_1d(client)
self._1w: MetricsTree_Market_Indicators_Macd_1w = MetricsTree_Market_Indicators_Macd_1w(client)
self._1m: MetricsTree_Market_Indicators_Macd_1m = MetricsTree_Market_Indicators_Macd_1m(client)
self._1y: HistogramLineSignalPattern = HistogramLineSignalPattern(client, 'macd')
self._1y: EmaHistogramLineSignalPattern = EmaHistogramLineSignalPattern(client, 'macd')
class MetricsTree_Market_Indicators:
"""Metrics tree node."""
packages/brk_client/pyproject.toml
+2 -2
View File
@@ -1,11 +1,11 @@
[project]
name = "brk-client"
version = "0.1.9"
description = "Python client for the Bitcoin Research Kit"
description = "Bitcoin on-chain analytics client — thousands of metrics, block explorer, and address index"
readme = "README.md"
requires-python = ">=3.9"
license = "MIT"
keywords = ["bitcoin", "blockchain", "analytics", "on-chain"]
keywords = ["bitcoin", "blockchain", "analytics", "on-chain", "metrics", "api", "data", "cryptocurrency", "brk"]
classifiers = [
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
website/.well-known/ai-plugin.json
+15
View File
@@ -0,0 +1,15 @@
{
"schema_version": "v1",
"name_for_human": "Bitcoin Research Kit",
"name_for_model": "bitcoin_research_kit",
"description_for_human": "Query Bitcoin on-chain analytics: thousands of metrics, block explorer, address index.",
"description_for_model": "Bitcoin on-chain analytics API. Search metrics via /api/metrics/search/{query}, fetch data via /api/metric/{metric}/{index}. No auth required.",
"auth": { "type": "none" },
"api": {
"type": "openapi",
"url": "https://bitview.space/openapi.json"
},
"logo_url": "https://bitview.space/assets/favicon-196.png",
"contact_email": "hello@bitcoinresearchkit.org",
"legal_info_url": "https://github.com/bitcoinresearchkit/brk/blob/main/docs/LICENSE.md"
}
website/llms.txt
+72
View File
@@ -0,0 +1,72 @@
# Bitcoin Research Kit (BRK)
> Open-source Bitcoin on-chain analytics API. Thousands of metrics, block explorer, address index — all computed from a Bitcoin Core node, including the price.
Base URL: https://bitview.space
## API
Free, no auth required. JSON and CSV output. Mempool.space compatible for block/tx/address endpoints.
- [Interactive docs](https://bitview.space/api)
- [OpenAPI spec (compact, LLM-optimized)](https://bitview.space/api.json)
- [OpenAPI spec (full)](https://bitview.space/openapi.json)
## Discover
Search for metrics by keyword:
GET /api/metrics/search/{query}
Browse all available metrics:
GET /api/metrics/list
List available indexes (date, height, etc.):
GET /api/metrics/indexes
Browse the full metric catalog as a tree:
GET /api/metrics
## Query
Get a metric by name and index:
GET /api/metric/{metric}/{index}
GET /api/metric/{metric}/{index}?start=-30
Fetch multiple metrics at once:
GET /api/metrics/bulk?index={index}&metrics={metric1},{metric2}
See the `MetricData` schema and query parameters (`start`, `end`, `limit`) in the [OpenAPI spec](https://bitview.space/api.json).
## Block Explorer
GET /api/block-height/{height}
GET /api/block/{hash}
GET /api/tx/{txid}
GET /api/address/{address}
## Mempool
GET /api/mempool/price
GET /api/mempool/info
GET /api/v1/fees/recommended
## Client Libraries
- JavaScript: https://www.npmjs.com/package/brk-client
- Python: https://pypi.org/project/brk-client/
- Rust: https://crates.io/crates/brk_client
## Metric Categories
Market, supply, mining, network activity, UTXO age bands, cointime economics, holder cohorts, cost basis distributions, and more. Use the discovery endpoints above to explore.
## Source
- GitHub: https://github.com/bitcoinresearchkit/brk
- License: MIT
website/robots.txt
+6 -1
View File
@@ -1,2 +1,7 @@
User-agent: *
Allow: /
Allow: /
# LLM-friendly resources
# llms.txt: https://llmstxt.org/
# api.json: Compact OpenAPI spec optimized for LLM consumption
Sitemap: https://bitview.space/llms.txt