From 37c9eb57055afae85aab521f2ab8558a8e3f48dc Mon Sep 17 00:00:00 2001 From: Nelson Griffiths Date: Fri, 15 Nov 2024 15:17:16 -0700 Subject: [PATCH] working frac diff --- Cargo.lock | 1 + Cargo.toml | 1 + polars_trading/_testing/features.py | 29 ++- polars_trading/features/frac_diff.py | 31 +++ pyproject.toml | 2 +- src/frac_diff.rs | 45 ++++ tests/features/test_frac_diff.py | 58 +++++- tests/labels/test_dynamic_labels.py | 16 +- tests/labels/test_labels.py | 6 +- uv.lock | 299 ++++++++++++++------------- 10 files changed, 340 insertions(+), 148 deletions(-) diff --git a/Cargo.lock b/Cargo.lock index 93a1f91..632425f 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -2107,6 +2107,7 @@ version = "0.1.0" dependencies = [ "num", "polars", + "polars-arrow", "pyo3", "pyo3-polars", "serde", diff --git a/Cargo.toml b/Cargo.toml index 6e58226..e38ea86 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -13,3 +13,4 @@ pyo3-polars = { version = "*", features = ["derive", "dtype-struct"] } serde = { version = "1", features = ["derive"] } polars = { version = "*", features = ["dtype-struct"] } num = "0.4.3" +polars-arrow = "0.44.2" diff --git a/polars_trading/_testing/features.py b/polars_trading/_testing/features.py index 6c4cf6f..128240e 100644 --- a/polars_trading/_testing/features.py +++ b/polars_trading/_testing/features.py @@ -40,7 +40,7 @@ def frac_diff_ffd(series: pd.DataFrame, d: float, thresh: float = 1e-5) -> pd.Da width = len(w) - 1 df = {} for name in series.columns: - series_f = series[[name]].fillna(method="ffill").dropna() + series_f = series[[name]].ffill().dropna() df_ = pd.Series() for iloc1 in range(width, series_f.shape[0]): loc0 = series_f.index[iloc1 - width] @@ -48,3 +48,30 @@ def frac_diff_ffd(series: pd.DataFrame, d: float, thresh: float = 1e-5) -> pd.Da df_[loc1] = np.dot(w.T, series_f.loc[loc0:loc1])[0, 0] df[name] = df_.copy(deep=True) return pd.concat(df, axis=1) + + +if __name__ == "__main__": + import polars as pl + + from polars_trading._testing.data import generate_trade_data + from polars_trading.features.frac_diff import frac_diff + + pl.Config.set_verbose(True) + data = generate_trade_data(10_000, n_companies=3).sort("ts_event") + print( + data.with_columns( + frac_diff("price", 0.5, 1e-3).over("symbol").alias("frac_diff") + ).sort("symbol") + ) + + print( + pl.from_pandas( + data.to_pandas() + .set_index("ts_event") + .groupby("symbol")[["price"]] + .apply(frac_diff_ffd, 0.5, 1e-3), + include_index=True, + ).sort("symbol") + ) + + # print(frac_diff_ffd(data.to_pandas().set_index("ts_event")[["price"]], 0.5, 1e-3)) diff --git a/polars_trading/features/frac_diff.py b/polars_trading/features/frac_diff.py index e69de29..2f48445 100644 --- a/polars_trading/features/frac_diff.py +++ b/polars_trading/features/frac_diff.py @@ -0,0 +1,31 @@ +"""Module containing functions to generate fractionally differentiated features.""" + +import polars as pl +from polars.plugins import register_plugin_function + +from polars_trading._utils import LIB +from polars_trading.typing import IntoExpr + + +def frac_diff(expr: IntoExpr, d: float, threshold: float) -> pl.Expr: + """Generate expression to calculate the fractionally differentiated series. + + Args: + ---- + expr: IntoExpr - The expression to calculate the fractionally differentiated + series. + d: float - The fractional difference. + threshold: float - The threshold. + + Returns: + ------- + pl.Expr: The expression to calculate the fractionally differentiated series. + + """ + return register_plugin_function( + plugin_path=LIB, + args=[expr], + kwargs={"d": d, "threshold": threshold}, + is_elementwise=False, + function_name="frac_diff", + ) diff --git a/pyproject.toml b/pyproject.toml index 2560a9f..6fd5460 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -85,7 +85,7 @@ dev-dependencies = [ "build>=1.2.1", "commitizen>=3.29.0", "marimo>=0.8.8", - "maturin>=1.7.1", + "maturin[patchelf]>=1.7.1", "mkdocs-gen-files>=0.5.0", "mkdocstrings[python]>=0.26.1", "pip>=24.2", diff --git a/src/frac_diff.rs b/src/frac_diff.rs index c8cf453..a98c3fa 100644 --- a/src/frac_diff.rs +++ b/src/frac_diff.rs @@ -1,3 +1,9 @@ +use polars::prelude::*; +use polars_arrow::bitmap::MutableBitmap; +use pyo3_polars::derive::polars_expr; + +use serde::Deserialize; + pub fn get_weights_ffd(d: f64, threshold: f64) -> Vec { let mut w = vec![1.]; let mut k = 1.0; @@ -12,3 +18,42 @@ pub fn get_weights_ffd(d: f64, threshold: f64) -> Vec { w.reverse(); w } + +fn dot_product(a: &[f64], b: &[f64]) -> f64 { + a.iter().zip(b.iter()).map(|(a, b)| a * b).sum() +} + +#[derive(Deserialize)] +struct FracDiffKwargs { + d: f64, + threshold: f64, +} + +#[polars_expr(output_type=Float64)] +fn frac_diff(inputs: &[Series], kwargs: FracDiffKwargs) -> PolarsResult { + let prices = inputs[0].f64().unwrap().to_vec_null_aware(); + let prices = if prices.is_left() { + prices.left().unwrap() + } else { + return Err(PolarsError::InvalidOperation("Null price found".into())); + }; + let weights = get_weights_ffd(kwargs.d, kwargs.threshold); + let n_weights = weights.len(); + let mut outputs: Vec = Vec::with_capacity(prices.len()); + let mut validity_mask = MutableBitmap::with_capacity(prices.len()); + validity_mask.extend_constant(prices.len(), true); + for i in 0..prices.len() { + if i < (n_weights - 1) { + outputs.push(0.0); + validity_mask.set(i, false); + } else { + let window = &prices[i + 1 - n_weights..i + 1]; + let output = dot_product(window, &weights); + outputs.push(output); + } + } + Ok( + Float64Chunked::from_vec_validity("frac_diff".into(), outputs, validity_mask.into()) + .into_series(), + ) +} diff --git a/tests/features/test_frac_diff.py b/tests/features/test_frac_diff.py index b1836ba..d6146f8 100644 --- a/tests/features/test_frac_diff.py +++ b/tests/features/test_frac_diff.py @@ -1,17 +1,73 @@ -from polars_trading._testing.features import get_weights_ffd +from polars_trading._testing.features import get_weights_ffd, frac_diff_ffd from polars_trading._internal import get_weights_ffd_py +from polars_trading.features.frac_diff import frac_diff import pytest +from polars.testing import assert_frame_equal +import pandas as pd +import polars as pl + + +def apply_pd_frac_diff(df: pd.DataFrame, d: float, threshold: float) -> pd.DataFrame: + return ( + df.set_index("ts_event") + .groupby("symbol")[["price"]] + .apply(frac_diff_ffd, 0.5, 1e-3) + .reset_index() + ) + def test__get_weights_ffd__matches_pandas(): out = get_weights_ffd(0.5, 1e-3).flatten().tolist() out2 = get_weights_ffd_py(0.5, 1e-3) assert out == out2 + @pytest.mark.benchmark(group="get_weights_ffd") def test__get_weights_ffd__benchmark_rs(benchmark): benchmark(get_weights_ffd_py, 0.5, 1e-5) + @pytest.mark.benchmark(group="get_weights_ffd") @pytest.mark.pandas def test__get_weights_ffd__benchmark_pandas(benchmark): benchmark(get_weights_ffd, 0.5, 1e-5) + + +@pytest.mark.parametrize( + "trade_data", [{"n_rows": 10_000, "n_companies": 3}], indirect=True +) +def test__frac_diff__matches_pandas(trade_data): + trade_data = trade_data.sort("ts_event") + out = trade_data.select( + "ts_event", "symbol", frac_diff("price", 0.5, 1e-3).alias("frac_diff") + ) + out2 = pl.DataFrame(apply_pd_frac_diff(trade_data.to_pandas(), 0.5, 1e-3)).rename( + {"level_1": "ts_event", "price": "frac_diff"} + ).cast(out.schema) + assert_frame_equal( + out.drop_nulls().sort("ts_event", "symbol"), + out2.sort("ts_event", "symbol"), + check_column_order=False, + ) + + +@pytest.mark.benchmark(group="frac_diff") +@pytest.mark.parametrize( + "trade_data", [{"n_rows": 10_000, "n_companies": 3}], indirect=True +) +def test__frac_diff__benchmark_polars(benchmark, trade_data): + trade_data = trade_data.lazy() + benchmark( + trade_data.select( + "ts_event", "symbol", frac_diff("price", 0.5, 1e-3).alias("frac_diff") + ).collect + ) + + +@pytest.mark.benchmark(group="frac_diff") +@pytest.mark.pandas +@pytest.mark.parametrize( + "trade_data", [{"n_rows": 10_000, "n_companies": 3}], indirect=True +) +def test__frac_diff__benchmark_pandas(benchmark, trade_data): + benchmark(apply_pd_frac_diff, trade_data.to_pandas(), 0.5, 1e-5) diff --git a/tests/labels/test_dynamic_labels.py b/tests/labels/test_dynamic_labels.py index cf582e4..3d07c1a 100644 --- a/tests/labels/test_dynamic_labels.py +++ b/tests/labels/test_dynamic_labels.py @@ -1,10 +1,14 @@ -from polars_trading.labels.dynamic_labels import daily_vol, get_vertical_barrier_by_timedelta +from polars_trading.labels.dynamic_labels import ( + daily_vol, + get_vertical_barrier_by_timedelta, +) import polars as pl from polars_trading._testing.labels import get_daily_vol import pytest from polars.testing import assert_frame_equal from datetime import datetime, timedelta + @pytest.mark.parametrize( "trade_data", [ @@ -30,8 +34,9 @@ def test__daily_vol__single_security(trade_data): ) def test__daily_vol__multi_security(trade_data): pl_result = ( - daily_vol(trade_data, "ts_event", "price", "symbol", 5) - .sort("ts_event", "symbol") + daily_vol(trade_data, "ts_event", "price", "symbol", 5).sort( + "ts_event", "symbol" + ) ).drop_nulls() pd_result = ( trade_data.to_pandas() @@ -163,6 +168,7 @@ def test__get_vertical_barrier_by_timedelta__simple(): result = get_vertical_barrier_by_timedelta(df.lazy(), "ts_event", "2h").collect() assert_frame_equal(result, expected) + def test__get_vertical_barrier_by_timedelta__skip_rows(): df = pl.DataFrame( { @@ -243,7 +249,9 @@ def test__get_vertical_barrier_by_timedelta__timedelta(): └─────────────────────┴─────────────────────┘ """) - result = get_vertical_barrier_by_timedelta(df.lazy(), "ts_event", timedelta(hours=2)).collect() + result = get_vertical_barrier_by_timedelta( + df.lazy(), "ts_event", timedelta(hours=2) + ).collect() assert_frame_equal(result, expected) diff --git a/tests/labels/test_labels.py b/tests/labels/test_labels.py index 4521d31..5344850 100644 --- a/tests/labels/test_labels.py +++ b/tests/labels/test_labels.py @@ -129,4 +129,8 @@ def 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