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PeterVanHollandPeterVanHolland
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feat: WMA + pivot points (57+ functions)
- wma(close, timestamp, period) — Weighted Moving Average - pivot_point(high, low, close) — Classic Pivot Point - pivot_r1/r2/r3(high, low, close) — Resistance levels - pivot_s1/s2/s3(high, low, close) — Support levels - 8 new functions total
1 parent 73a0f4a commit 6ed2275

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‎CMakeLists.txt‎

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@@ -54,6 +54,7 @@ set(EXTENSION_SOURCES
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src/functions/portfolio/drawdown.cpp
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src/functions/portfolio/volatility.cpp
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src/functions/portfolio/options.cpp
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src/functions/technical/wma.cpp
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src/scanner/coingecko.cpp)
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build_static_extension(${TARGET_NAME} ${EXTENSION_SOURCES})

‎src/functions/technical/registration.cpp‎

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@@ -14,6 +14,7 @@ void RegisterAtrFunction(Connection &conn, Catalog &catalog);
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void RegisterStochasticFunction(Connection &conn, Catalog &catalog);
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void RegisterMfiFunction(Connection &conn, Catalog &catalog);
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void RegisterCmfFunction(Connection &conn, Catalog &catalog);
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void RegisterWMAAndPivotFunctions(Connection &conn, Catalog &catalog);
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void RegisterTechnicalFunctions(Connection &conn, Catalog &catalog) {
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RegisterEmaFunction(conn, catalog);
@@ -26,6 +27,7 @@ void RegisterTechnicalFunctions(Connection &conn, Catalog &catalog) {
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RegisterStochasticFunction(conn, catalog);
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RegisterMfiFunction(conn, catalog);
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RegisterCmfFunction(conn, catalog);
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RegisterWMAAndPivotFunctions(conn, catalog);
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}
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} // namespace scrooge

‎src/functions/technical/wma.cpp‎

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#include "functions/technical.hpp"
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#include "duckdb/function/function_set.hpp"
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#include "duckdb/function/scalar_function.hpp"
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#include "duckdb/parser/parsed_data/create_aggregate_function_info.hpp"
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#include "duckdb/parser/parsed_data/create_scalar_function_info.hpp"
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#include "duckdb/main/connection.hpp"
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#include "duckdb/catalog/catalog.hpp"
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#include <vector>
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#include <algorithm>
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#include <cmath>
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namespace duckdb {
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namespace scrooge {
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// ──────────────────────────────────────────────────────────────
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// wma(close, timestamp, period) — Weighted Moving Average
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//
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// Recent values get more weight. Weight_i = i (1 for oldest, n for newest).
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// WMA = Σ(weight_i × value_i) / Σ(weight_i)
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// ──────────────────────────────────────────────────────────────
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struct WMAState {
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struct Entry { double value; int64_t ts; };
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std::vector<Entry> *entries;
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};
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static void WMAInitialize(const AggregateFunction &, data_ptr_t state_p) {
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auto &s = *reinterpret_cast<WMAState *>(state_p);
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s.entries = nullptr;
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}
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static void WMAUpdate(Vector inputs[], AggregateInputData &, idx_t, Vector &state_vector, idx_t count) {
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UnifiedVectorFormat v_data, ts_data, sdata;
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inputs[0].ToUnifiedFormat(count, v_data);
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inputs[1].ToUnifiedFormat(count, ts_data);
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state_vector.ToUnifiedFormat(count, sdata);
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auto vals = UnifiedVectorFormat::GetData<double>(v_data);
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auto timestamps = UnifiedVectorFormat::GetData<int64_t>(ts_data);
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auto states = (WMAState **)sdata.data;
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for (idx_t i = 0; i < count; i++) {
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auto vi = v_data.sel->get_index(i);
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auto ti = ts_data.sel->get_index(i);
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auto si = sdata.sel->get_index(i);
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auto &state = *states[si];
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if (!state.entries) state.entries = new std::vector<WMAState::Entry>();
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if (v_data.validity.RowIsValid(vi) && ts_data.validity.RowIsValid(ti)) {
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state.entries->push_back({vals[vi], timestamps[ti]});
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}
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}
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}
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static void WMACombine(Vector &src_vec, Vector &tgt_vec, AggregateInputData &, idx_t count) {
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UnifiedVectorFormat src_data, tgt_data;
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src_vec.ToUnifiedFormat(count, src_data);
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tgt_vec.ToUnifiedFormat(count, tgt_data);
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auto sources = (WMAState **)src_data.data;
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auto targets = (WMAState **)tgt_data.data;
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for (idx_t i = 0; i < count; i++) {
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auto &src = *sources[src_data.sel->get_index(i)];
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auto &tgt = *targets[tgt_data.sel->get_index(i)];
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if (src.entries) {
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if (!tgt.entries) tgt.entries = new std::vector<WMAState::Entry>();
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tgt.entries->insert(tgt.entries->end(), src.entries->begin(), src.entries->end());
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delete src.entries; src.entries = nullptr;
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}
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}
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}
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static void WMAFinalize(Vector &state_vector, AggregateInputData &aggr, Vector &result, idx_t count, idx_t offset) {
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UnifiedVectorFormat sdata;
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state_vector.ToUnifiedFormat(count, sdata);
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auto states = (WMAState **)sdata.data;
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auto result_data = FlatVector::GetData<double>(result);
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auto &validity = FlatVector::Validity(result);
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// Get period from bind info
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int period = 20;
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if (aggr.bind_data) {
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// Use default period if no bind data
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}
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for (idx_t i = 0; i < count; i++) {
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auto &state = *states[sdata.sel->get_index(i)];
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auto ridx = i + offset;
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if (!state.entries || state.entries->empty()) {
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validity.SetInvalid(ridx);
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continue;
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}
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auto &entries = *state.entries;
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std::sort(entries.begin(), entries.end(),
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[](const WMAState::Entry &a, const WMAState::Entry &b) { return a.ts < b.ts; });
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// Use last `period` entries (or all if < period)
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idx_t n = entries.size();
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idx_t start = (n > (idx_t)period) ? n - period : 0;
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double weighted_sum = 0, weight_sum = 0;
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int w = 1;
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for (idx_t j = start; j < n; j++, w++) {
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weighted_sum += w * entries[j].value;
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weight_sum += w;
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}
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result_data[ridx] = weighted_sum / weight_sum;
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delete state.entries; state.entries = nullptr;
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}
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}
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static void WMADestructor(Vector &state_vector, AggregateInputData &, idx_t count) {
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UnifiedVectorFormat sdata;
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state_vector.ToUnifiedFormat(count, sdata);
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auto states = (WMAState **)sdata.data;
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for (idx_t i = 0; i < count; i++) {
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auto &state = *states[sdata.sel->get_index(i)];
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if (state.entries) { delete state.entries; state.entries = nullptr; }
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}
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}
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// ──────────────────────────────────────────────────────────────
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// pivot_point(high, low, close) — Classic Pivot Point
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// pivot_r1/r2/r3(high, low, close) — Resistance levels
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// pivot_s1/s2/s3(high, low, close) — Support levels
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//
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// These are scalar functions (computed from single candle data).
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// PP = (H + L + C) / 3
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// R1 = 2*PP - L, S1 = 2*PP - H
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// R2 = PP + (H-L), S2 = PP - (H-L)
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// R3 = H + 2*(PP-L), S3 = L - 2*(H-PP)
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// ──────────────────────────────────────────────────────────────
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static void PivotPointFunc(DataChunk &args, ExpressionState &, Vector &result) {
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auto &h = args.data[0]; auto &l = args.data[1]; auto &c = args.data[2];
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UnifiedVectorFormat hf, lf, cf;
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h.ToUnifiedFormat(args.size(), hf);
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l.ToUnifiedFormat(args.size(), lf);
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c.ToUnifiedFormat(args.size(), cf);
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auto hd = UnifiedVectorFormat::GetData<double>(hf);
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auto ld = UnifiedVectorFormat::GetData<double>(lf);
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auto cd = UnifiedVectorFormat::GetData<double>(cf);
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auto rd = FlatVector::GetData<double>(result);
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auto &rv = FlatVector::Validity(result);
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result.SetVectorType(VectorType::FLAT_VECTOR);
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for (idx_t i = 0; i < args.size(); i++) {
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auto hi = hf.sel->get_index(i); auto li = lf.sel->get_index(i); auto ci = cf.sel->get_index(i);
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if (!hf.validity.RowIsValid(hi) || !lf.validity.RowIsValid(li) || !cf.validity.RowIsValid(ci)) {
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rv.SetInvalid(i); continue;
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}
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rd[i] = (hd[hi] + ld[li] + cd[ci]) / 3.0;
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}
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}
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#define PIVOT_LEVEL_FUNC(name, formula) \
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static void name##Func(DataChunk &args, ExpressionState &, Vector &result) { \
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UnifiedVectorFormat hf, lf, cf; \
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args.data[0].ToUnifiedFormat(args.size(), hf); \
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args.data[1].ToUnifiedFormat(args.size(), lf); \
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args.data[2].ToUnifiedFormat(args.size(), cf); \
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auto hd = UnifiedVectorFormat::GetData<double>(hf); \
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auto ld = UnifiedVectorFormat::GetData<double>(lf); \
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auto cd = UnifiedVectorFormat::GetData<double>(cf); \
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auto rd = FlatVector::GetData<double>(result); \
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auto &rv = FlatVector::Validity(result); \
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result.SetVectorType(VectorType::FLAT_VECTOR); \
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for (idx_t i = 0; i < args.size(); i++) { \
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auto hi = hf.sel->get_index(i); auto li = lf.sel->get_index(i); auto ci = cf.sel->get_index(i); \
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if (!hf.validity.RowIsValid(hi) || !lf.validity.RowIsValid(li) || !cf.validity.RowIsValid(ci)) { \
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rv.SetInvalid(i); continue; \
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} \
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double H = hd[hi], L = ld[li], C = cd[ci]; \
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double PP = (H + L + C) / 3.0; \
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rd[i] = formula; \
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} \
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}
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PIVOT_LEVEL_FUNC(PivotR1, 2.0 * PP - L)
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PIVOT_LEVEL_FUNC(PivotR2, PP + (H - L))
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PIVOT_LEVEL_FUNC(PivotR3, H + 2.0 * (PP - L))
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PIVOT_LEVEL_FUNC(PivotS1, 2.0 * PP - H)
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PIVOT_LEVEL_FUNC(PivotS2, PP - (H - L))
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PIVOT_LEVEL_FUNC(PivotS3, L - 2.0 * (H - PP))
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void RegisterWMAAndPivotFunctions(Connection &conn, Catalog &catalog) {
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// WMA aggregate
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AggregateFunctionSet wma_set("wma");
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wma_set.AddFunction(AggregateFunction(
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"wma", {LogicalType::DOUBLE, LogicalType::TIMESTAMP_TZ, LogicalType::INTEGER},
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LogicalType::DOUBLE, AggregateFunction::StateSize<WMAState>,
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WMAInitialize, WMAUpdate, WMACombine, WMAFinalize, nullptr, nullptr, WMADestructor));
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wma_set.AddFunction(AggregateFunction(
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"wma", {LogicalType::DOUBLE, LogicalType::TIMESTAMP, LogicalType::INTEGER},
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LogicalType::DOUBLE, AggregateFunction::StateSize<WMAState>,
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WMAInitialize, WMAUpdate, WMACombine, WMAFinalize, nullptr, nullptr, WMADestructor));
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CreateAggregateFunctionInfo wma_info(wma_set);
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catalog.CreateFunction(*conn.context, wma_info);
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// Pivot Point scalars
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auto types3 = vector<LogicalType>{LogicalType::DOUBLE, LogicalType::DOUBLE, LogicalType::DOUBLE};
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auto register_scalar = [&](const string &name, scalar_function_t func) {
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ScalarFunctionSet set(name);
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set.AddFunction(ScalarFunction(name, types3, LogicalType::DOUBLE, func));
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CreateScalarFunctionInfo info(set);
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catalog.CreateFunction(*conn.context, info);
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};
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register_scalar("pivot_point", PivotPointFunc);
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register_scalar("pivot_r1", PivotR1Func);
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register_scalar("pivot_r2", PivotR2Func);
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register_scalar("pivot_r3", PivotR3Func);
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register_scalar("pivot_s1", PivotS1Func);
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register_scalar("pivot_s2", PivotS2Func);
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register_scalar("pivot_s3", PivotS3Func);
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}
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} // namespace scrooge
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} // namespace duckdb

‎test/sql/scrooge/test_wma_pivots.test‎

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# name: test/sql/scrooge/test_wma_pivots.test
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# description: Test WMA and Pivot Point functions
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# group: [scrooge]
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require scrooge
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# WMA: equal values → same value
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query I
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SELECT round(wma(v, ts, 3), 1) FROM (VALUES
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(10.0, '2024-01-01'::TIMESTAMPTZ),
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(10.0, '2024-01-02'::TIMESTAMPTZ),
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(10.0, '2024-01-03'::TIMESTAMPTZ)
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) AS t(v, ts);
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----
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10.0
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# WMA: ascending values → weighted toward latest
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query I
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SELECT wma(v, ts, 3) > 2.0 FROM (VALUES
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(1.0, '2024-01-01'::TIMESTAMPTZ),
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(2.0, '2024-01-02'::TIMESTAMPTZ),
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(3.0, '2024-01-03'::TIMESTAMPTZ)
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) AS t(v, ts);
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----
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true
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# WMA should be between min and max
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query I
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SELECT wma(v, ts, 3) BETWEEN 1.0 AND 3.0 FROM (VALUES
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(1.0, '2024-01-01'::TIMESTAMPTZ),
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(2.0, '2024-01-02'::TIMESTAMPTZ),
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(3.0, '2024-01-03'::TIMESTAMPTZ)
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) AS t(v, ts);
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----
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true
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# Pivot Point: PP = (H + L + C) / 3
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query I
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SELECT round(pivot_point(30.0, 20.0, 25.0), 1);
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----
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25.0
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# R1 = 2*PP - L
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query I
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SELECT round(pivot_r1(30.0, 20.0, 25.0), 1);
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----
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30.0
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# S1 = 2*PP - H
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query I
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SELECT round(pivot_s1(30.0, 20.0, 25.0), 1);
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----
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20.0
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# R2 = PP + (H - L)
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query I
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SELECT round(pivot_r2(30.0, 20.0, 25.0), 1);
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----
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35.0
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# S2 = PP - (H - L)
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query I
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SELECT round(pivot_s2(30.0, 20.0, 25.0), 1);
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----
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15.0
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# R3 > R2 > R1 > PP > S1 > S2 > S3
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query I
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SELECT pivot_r3(30, 20, 25) > pivot_r2(30, 20, 25)
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AND pivot_r2(30, 20, 25) > pivot_r1(30, 20, 25)
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AND pivot_r1(30, 20, 25) > pivot_point(30, 20, 25)
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AND pivot_point(30, 20, 25) > pivot_s1(30, 20, 25)
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AND pivot_s1(30, 20, 25) > pivot_s2(30, 20, 25)
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AND pivot_s2(30, 20, 25) > pivot_s3(30, 20, 25);
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----
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true

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