From eb00339ad109704bc579ea09fd53091483b48bcf Mon Sep 17 00:00:00 2001 From: Scott Staniewicz Date: Mon, 21 Oct 2024 12:42:08 -0400 Subject: [PATCH] Replace CSVs with `chi2.ppf` for GLRT test (#456) * Replace CSVs with `chi2.ppf` for GLRT test * default 0.001 * test smaller alphas * specify log in temp dir --- src/dolphin/shp/_glrt.py | 63 +- src/dolphin/shp/glrt_cutoffs.csv | 3993 ----------------------- src/dolphin/workflows/config/_common.py | 8 +- tests/test_shp.py | 2 +- tests/test_workflows_displacement.py | 3 + 5 files changed, 19 insertions(+), 4050 deletions(-) delete mode 100644 src/dolphin/shp/glrt_cutoffs.csv diff --git a/src/dolphin/shp/_glrt.py b/src/dolphin/shp/_glrt.py index 13dc6d6f..fd003486 100644 --- a/src/dolphin/shp/_glrt.py +++ b/src/dolphin/shp/_glrt.py @@ -1,14 +1,12 @@ from __future__ import annotations -import csv -from functools import lru_cache from math import log -from pathlib import Path from typing import Optional import numba import numpy as np from numpy.typing import ArrayLike +from scipy import stats from dolphin._types import Strides from dolphin.utils import _get_slices, compute_out_shape @@ -78,7 +76,8 @@ def estimate_neighbors( half_row, half_col = halfwin_rowcol rows, cols = mean.shape - threshold = get_cutoff(alpha=alpha, N=nslc) + # 1 Degree of freedom, regardless of N + threshold = stats.chi2.ppf(1 - alpha, df=1) strides_rowcol = (strides["y"], strides["x"]) out_rows, out_cols = compute_out_shape((rows, cols), Strides(*strides_rowcol)) @@ -88,6 +87,7 @@ def estimate_neighbors( return _loop_over_pixels( mean, var, + nslc, halfwin_rowcol, strides_rowcol, threshold, @@ -96,47 +96,18 @@ def estimate_neighbors( ) -def get_cutoff(alpha: float, N: int) -> float: - r"""Compute the upper cutoff for the GLRT test statistic. - - Statistic is - - \[ - 2\log(\sigma_{pooled}) - \log(\sigma_{p}) -\log(\sigma_{q}) - \] - - Parameters - ---------- - alpha: float - Significance level (0 < alpha < 1). - N: int - Number of samples. - - Returns - ------- - float - Cutoff value for the GLRT test statistic. - - """ - n_alpha_to_cutoff = _read_cutoff_csv() - try: - return n_alpha_to_cutoff[(N, alpha)] - except KeyError as e: - msg = f"Not implemented for {N = }, {alpha = }" - raise NotImplementedError(msg) from e - - @numba.njit(nogil=True) -def _compute_glrt_test_stat(scale_1, scale_2): +def _compute_glrt_test_stat(scale_sq_1, scale_sq_2, N): """Compute the GLRT test statistic.""" - scale_pooled = (scale_1 + scale_2) / 2 - return 2 * log(scale_pooled) - log(scale_1) - log(scale_2) + scale_pooled = (scale_sq_1 + scale_sq_2) / 2 + return N * (2 * log(scale_pooled) - log(scale_sq_1) - log(scale_sq_2)) @numba.njit(nogil=True, parallel=True) def _loop_over_pixels( mean: ArrayLike, var: ArrayLike, + N: int, halfwin_rowcol: tuple[int, int], strides_rowcol: tuple[int, int], threshold: float, @@ -180,7 +151,7 @@ def _loop_over_pixels( continue scale_2 = scale_squared[in_r2, in_c2] - T = _compute_glrt_test_stat(scale_1, scale_2) + T = _compute_glrt_test_stat(scale_1, scale_2, N) is_shp[out_r, out_c, r_off, c_off] = threshold > T if prune_disconnected: @@ -188,19 +159,3 @@ def _loop_over_pixels( remove_unconnected(is_shp[out_r, out_c], inplace=True) return is_shp - - -@lru_cache -def _read_cutoff_csv(): - filename = Path(__file__).parent / "glrt_cutoffs.csv" - - result = {} - with open(filename) as file: - reader = csv.DictReader(file) - for row in reader: - n = int(row["N"]) - alpha = float(row["alpha"]) - cutoff = float(row["cutoff"]) - result[(n, alpha)] = cutoff - - return result diff --git a/src/dolphin/shp/glrt_cutoffs.csv b/src/dolphin/shp/glrt_cutoffs.csv deleted file mode 100644 index dd88033a..00000000 --- a/src/dolphin/shp/glrt_cutoffs.csv +++ /dev/null @@ -1,3993 +0,0 @@ -N,alpha,cutoff -1,0.001,6.314 -1,0.005,4.5737 -1,0.01,3.9102 -1,0.05,2.331 -2,0.001,2.9138 -2,0.005,2.1534 -2,0.01,1.8213 -2,0.05,1.0781 -3,0.001,1.966 -3,0.005,1.4326 -3,0.01,1.2206 -3,0.05,0.6986 -4,0.001,1.4093 -4,0.005,1.041 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-995,0.01,0.0033 -995,0.05,0.0019 -996,0.001,0.0052 -996,0.005,0.0039 -996,0.01,0.0033 -996,0.05,0.0019 -997,0.001,0.0053 -997,0.005,0.004 -997,0.01,0.0033 -997,0.05,0.002 -998,0.001,0.0054 -998,0.005,0.0039 -998,0.01,0.0033 -998,0.05,0.0019 diff --git a/src/dolphin/workflows/config/_common.py b/src/dolphin/workflows/config/_common.py index f83ff0c5..517344c5 100644 --- a/src/dolphin/workflows/config/_common.py +++ b/src/dolphin/workflows/config/_common.py @@ -108,8 +108,12 @@ class PhaseLinkingOptions(BaseModel, extra="forbid"): ) shp_method: ShpMethod = ShpMethod.GLRT shp_alpha: float = Field( - 0.005, - description="Significance level (probability of false alarm) for SHP tests.", + 0.001, + description=( + "Significance level (probability of false alarm) for SHP tests. Lower" + " numbers include more pixels within the multilook window during covariance" + " estimation." + ), gt=0.0, lt=1.0, ) diff --git a/tests/test_shp.py b/tests/test_shp.py index b3743459..56db285e 100644 --- a/tests/test_shp.py +++ b/tests/test_shp.py @@ -184,7 +184,7 @@ def test_shp_glrt_nodata_0(mean, var, strides): @pytest.mark.parametrize("method", ["glrt", "ks"]) -@pytest.mark.parametrize("alpha", [0.01, 0.05]) +@pytest.mark.parametrize("alpha", [0.001, 0.005]) @pytest.mark.parametrize("strides", [{"x": 1, "y": 1}, {"x": 2, "y": 2}]) def test_shp_statistics(method, alpha, strides): """Check that with repeated tries, the alpha is correct.""" diff --git a/tests/test_workflows_displacement.py b/tests/test_workflows_displacement.py index 3cff98c1..535c51db 100644 --- a/tests/test_workflows_displacement.py +++ b/tests/test_workflows_displacement.py @@ -197,6 +197,7 @@ def test_displacement_run_extra_reference_date( pytest.skip(reason="spurt unwrapper not installed") with tmpdir.as_cwd(): + log_file = Path() / "dolphin.log" cfg = config.DisplacementWorkflow( # start_date = 20220101 # shape = (4, 128, 128) @@ -208,6 +209,7 @@ def test_displacement_run_extra_reference_date( phase_linking={ "ministack_size": 4, }, + log_file=log_file, ) paths = displacement.run(cfg) @@ -245,3 +247,4 @@ def test_displacement_run_extra_reference_date( ] assert all(get_raster_units(p) == "radians" for p in paths.unwrapped_paths) + log_file.unlink()