From f64c7b76745ec71f18fd241a35f1de1f1332e96b Mon Sep 17 00:00:00 2001 From: Sandro Campos Date: Mon, 8 Jul 2024 15:51:07 -0400 Subject: [PATCH] Compute angular correlation with weights (#12) * Add acf with weights * Improve code coverage * Simplify arg construction * Remove nbins attribute * Add weight column as a parameter --- src/corrgi/correlation/angular_correlation.py | 22 +++++++--- src/corrgi/correlation/correlation.py | 2 + src/corrgi/corrgi.py | 8 +++- src/corrgi/dask.py | 11 ++++- tests/corrgi/conftest.py | 20 +++++++++ tests/corrgi/test_acf.py | 39 ++++++++++++++++++ .../expected_results/acf/dd_acf_weight.npy | Bin 0 -> 392 bytes .../expected_results/acf/rr_acf_weight.npy | Bin 0 -> 392 bytes tests/data/generate_data.ipynb | 12 +++++- .../Norder=0/Dir=0/Npix=1.parquet | Bin 0 -> 68531 bytes .../Norder=0/Dir=0/Npix=10.parquet | Bin 0 -> 5347 bytes .../Norder=0/Dir=0/Npix=2.parquet | Bin 0 -> 103799 bytes .../Norder=0/Dir=0/Npix=5.parquet | Bin 0 -> 7077 bytes .../Norder=0/Dir=0/Npix=6.parquet | Bin 0 -> 63956 bytes .../Norder=0/Dir=0/Npix=7.parquet | Bin 0 -> 14448 bytes .../hipscat/acf_gals_weight/_common_metadata | Bin 0 -> 3434 bytes tests/data/hipscat/acf_gals_weight/_metadata | Bin 0 -> 8351 bytes .../hipscat/acf_gals_weight/catalog_info.json | 8 ++++ .../acf_gals_weight/partition_info.csv | 7 ++++ .../acf_gals_weight/provenance_info.json | 25 +++++++++++ .../Norder=0/Dir=0/Npix=1.parquet | Bin 0 -> 215513 bytes .../Norder=0/Dir=0/Npix=10.parquet | Bin 0 -> 5663 bytes .../Norder=0/Dir=0/Npix=2.parquet | Bin 0 -> 244386 bytes .../Norder=0/Dir=0/Npix=5.parquet | Bin 0 -> 10296 bytes .../Norder=0/Dir=0/Npix=6.parquet | Bin 0 -> 181167 bytes .../Norder=0/Dir=0/Npix=7.parquet | Bin 0 -> 28055 bytes .../Norder=0/Dir=0/Npix=9.parquet | Bin 0 -> 5101 bytes .../hipscat/acf_rans_weight/_common_metadata | Bin 0 -> 3434 bytes tests/data/hipscat/acf_rans_weight/_metadata | Bin 0 -> 9162 bytes .../hipscat/acf_rans_weight/catalog_info.json | 8 ++++ .../acf_rans_weight/partition_info.csv | 8 ++++ .../acf_rans_weight/provenance_info.json | 25 +++++++++++ tests/data/raw/acf_gals_weight.fits | Bin 0 -> 135360 bytes tests/data/raw/acf_rans_weight.fits | Bin 0 -> 360000 bytes 34 files changed, 185 insertions(+), 10 deletions(-) create mode 100644 tests/data/expected_results/acf/dd_acf_weight.npy create mode 100644 tests/data/expected_results/acf/rr_acf_weight.npy create mode 100644 tests/data/hipscat/acf_gals_weight/Norder=0/Dir=0/Npix=1.parquet create mode 100644 tests/data/hipscat/acf_gals_weight/Norder=0/Dir=0/Npix=10.parquet create mode 100644 tests/data/hipscat/acf_gals_weight/Norder=0/Dir=0/Npix=2.parquet create mode 100644 tests/data/hipscat/acf_gals_weight/Norder=0/Dir=0/Npix=5.parquet create mode 100644 tests/data/hipscat/acf_gals_weight/Norder=0/Dir=0/Npix=6.parquet create mode 100644 tests/data/hipscat/acf_gals_weight/Norder=0/Dir=0/Npix=7.parquet create mode 100644 tests/data/hipscat/acf_gals_weight/_common_metadata create mode 100644 tests/data/hipscat/acf_gals_weight/_metadata create mode 100644 tests/data/hipscat/acf_gals_weight/catalog_info.json create mode 100644 tests/data/hipscat/acf_gals_weight/partition_info.csv create mode 100644 tests/data/hipscat/acf_gals_weight/provenance_info.json create mode 100644 tests/data/hipscat/acf_rans_weight/Norder=0/Dir=0/Npix=1.parquet create mode 100644 tests/data/hipscat/acf_rans_weight/Norder=0/Dir=0/Npix=10.parquet create mode 100644 tests/data/hipscat/acf_rans_weight/Norder=0/Dir=0/Npix=2.parquet create mode 100644 tests/data/hipscat/acf_rans_weight/Norder=0/Dir=0/Npix=5.parquet create mode 100644 tests/data/hipscat/acf_rans_weight/Norder=0/Dir=0/Npix=6.parquet create mode 100644 tests/data/hipscat/acf_rans_weight/Norder=0/Dir=0/Npix=7.parquet create mode 100644 tests/data/hipscat/acf_rans_weight/Norder=0/Dir=0/Npix=9.parquet create mode 100644 tests/data/hipscat/acf_rans_weight/_common_metadata create mode 100644 tests/data/hipscat/acf_rans_weight/_metadata create mode 100644 tests/data/hipscat/acf_rans_weight/catalog_info.json create mode 100644 tests/data/hipscat/acf_rans_weight/partition_info.csv create mode 100644 tests/data/hipscat/acf_rans_weight/provenance_info.json create mode 100644 tests/data/raw/acf_gals_weight.fits create mode 100644 tests/data/raw/acf_rans_weight.fits diff --git a/src/corrgi/correlation/angular_correlation.py b/src/corrgi/correlation/angular_correlation.py index 70024fb..3a8319e 100644 --- a/src/corrgi/correlation/angular_correlation.py +++ b/src/corrgi/correlation/angular_correlation.py @@ -11,18 +11,21 @@ class AngularCorrelation(Correlation): """The angular correlation utilities.""" def _get_auto_method(self): - return cff.mod.th_A_wg if self.use_weights else cff.mod.th_A_naiveway + return cff.mod.th_A_wg_naiveway if self.use_weights else cff.mod.th_A_naiveway def _get_cross_method(self) -> Callable: - return cff.mod.th_C_wg if self.use_weights else cff.mod.th_C_naiveway + return cff.mod.th_C_wg_naiveway if self.use_weights else cff.mod.th_C_naiveway def _construct_auto_args(self, df: pd.DataFrame, catalog_info: CatalogInfo) -> list: - return [ - len(df), # number of particles + args = [ + len(df), *self.get_coords(df, catalog_info), # cartesian coordinates self.params.nsept, # number of angular separation bins self.bins, # bins in angular separation [deg] ] + if self.use_weights: + args = [args[0], df[self.weight_column].to_numpy(), *args[1:]] + return args def _construct_cross_args( self, @@ -31,7 +34,7 @@ def _construct_cross_args( left_catalog_info: CatalogInfo, right_catalog_info: CatalogInfo, ) -> list: - return [ + args = [ len(left_df), # number of particles of the left partition *self.get_coords(left_df, left_catalog_info), # X,Y,Z coordinates of particles len(right_df), # number of particles of the right partition @@ -39,3 +42,12 @@ def _construct_cross_args( self.params.nsept, # number of angular separation bins self.bins, # bins in angular separation [deg] ] + if self.use_weights: + args = [ + args[0], + left_df[self.weight_column].to_numpy(), + *args[1:5], + right_df[self.weight_column].to_numpy(), + *args[5:], + ] + return args diff --git a/src/corrgi/correlation/correlation.py b/src/corrgi/correlation/correlation.py index aba41fd..9e27e1c 100644 --- a/src/corrgi/correlation/correlation.py +++ b/src/corrgi/correlation/correlation.py @@ -18,10 +18,12 @@ def __init__( self, bins: np.ndarray, params: Munch, + weight_column: str = "wei", use_weights: bool = False, ): self.bins = bins self.params = params + self.weight_column = weight_column self.use_weights = use_weights def count_auto_pairs(self, df: pd.DataFrame, catalog_info: CatalogInfo) -> np.ndarray: diff --git a/src/corrgi/corrgi.py b/src/corrgi/corrgi.py index 2dc62bd..d8ad563 100644 --- a/src/corrgi/corrgi.py +++ b/src/corrgi/corrgi.py @@ -12,6 +12,8 @@ def compute_autocorrelation( catalog: Catalog, random: Catalog, params: Munch, + weight_column: str = "wei", + use_weights: bool = False, ) -> np.ndarray: """Calculates the auto-correlation for a catalog. @@ -21,13 +23,17 @@ def compute_autocorrelation( catalog (Catalog): The catalog. random (Catalog): A random samples catalog. params (Munch): The parameters dictionary to run gundam with. + weight_column (str): The weights column name. Defaults to "wei". + use_weights (bool): Whether to use weights or not. Defaults to False. Returns: A numpy array with the result of the auto-correlation, using the natural estimator. """ + if use_weights and weight_column not in catalog.columns: + raise ValueError(f"Weight column {weight_column} does not exist") num_galaxies = catalog.hc_structure.catalog_info.total_rows num_random = random.hc_structure.catalog_info.total_rows - counts_dd, counts_rr = compute_autocorrelation_counts(corr_type, catalog, random, params) + counts_dd, counts_rr = compute_autocorrelation_counts(corr_type, catalog, random, params, use_weights) return calculate_natural_estimate(counts_dd, counts_rr, num_galaxies, num_random) diff --git a/src/corrgi/dask.py b/src/corrgi/dask.py index bf87851..97a089a 100644 --- a/src/corrgi/dask.py +++ b/src/corrgi/dask.py @@ -15,7 +15,12 @@ def compute_autocorrelation_counts( - corr_type: type[Correlation], catalog: Catalog, random: Catalog, params: Munch + corr_type: type[Correlation], + catalog: Catalog, + random: Catalog, + params: Munch, + weight_column: str = "wei", + use_weights: bool = False, ) -> np.ndarray: """Computes the auto-correlation counts for a catalog. @@ -24,6 +29,8 @@ def compute_autocorrelation_counts( catalog (Catalog): The catalog with galaxy samples. random (Catalog): The catalog with random samples. params (dict): The gundam parameters for the Fortran subroutine. + weight_column (str): The weights column name. Defaults to "wei". + use_weights (bool): Whether to use weights or not. Defaults to False. Returns: The histogram counts to calculate the auto-correlation. @@ -31,7 +38,7 @@ def compute_autocorrelation_counts( # Calculate the angular separation bins bins, _ = gundam.makebins(params.nsept, params.septmin, params.dsept, params.logsept) # Create correlation with bins and params - correlation = corr_type(bins, params) + correlation = corr_type(bins, params, weight_column, use_weights) # Generate the histograms with counts for each catalog counts_dd = perform_auto_counts(catalog, correlation) counts_rr = perform_auto_counts(random, correlation) diff --git a/tests/corrgi/conftest.py b/tests/corrgi/conftest.py index 7df4758..6a1eca0 100644 --- a/tests/corrgi/conftest.py +++ b/tests/corrgi/conftest.py @@ -50,6 +50,16 @@ def rand_catalog_dir(hipscat_catalogs_dir): return hipscat_catalogs_dir / "RAND" +@pytest.fixture +def acf_gals_weight_dir(hipscat_catalogs_dir): + return hipscat_catalogs_dir / "acf_gals_weight" + + +@pytest.fixture +def acf_rans_weight_dir(hipscat_catalogs_dir): + return hipscat_catalogs_dir / "acf_rans_weight" + + @pytest.fixture def acf_bins_left_edges(acf_expected_results): return np.load(acf_expected_results / "l_binedges_acf.npy") @@ -70,6 +80,16 @@ def acf_rr_counts(acf_expected_results): return np.load(acf_expected_results / "rr_acf.npy") +@pytest.fixture +def acf_dd_counts_with_weights(acf_expected_results): + return np.load(acf_expected_results / "dd_acf_weight.npy") + + +@pytest.fixture +def acf_rr_counts_with_weights(acf_expected_results): + return np.load(acf_expected_results / "rr_acf_weight.npy") + + @pytest.fixture def acf_nat_estimate(acf_expected_results): return np.load(acf_expected_results / "w_acf_nat.npy") diff --git a/tests/corrgi/test_acf.py b/tests/corrgi/test_acf.py index 8f4249c..eee9a5a 100644 --- a/tests/corrgi/test_acf.py +++ b/tests/corrgi/test_acf.py @@ -2,6 +2,7 @@ import lsdb import numpy as np import numpy.testing as npt +import pytest from gundam import gundam from corrgi.correlation.angular_correlation import AngularCorrelation @@ -70,3 +71,41 @@ def test_acf_e2e( AngularCorrelation, galaxy_catalog, random_catalog, autocorr_params ) npt.assert_allclose(estimate, acf_nat_estimate, rtol=1e-7) + + +def test_acf_counts_with_weights_are_correct( + dask_client, + acf_gals_weight_dir, + acf_rans_weight_dir, + acf_dd_counts_with_weights, + acf_rr_counts_with_weights, + autocorr_params, +): + galaxy_catalog = lsdb.read_hipscat(acf_gals_weight_dir) + random_catalog = lsdb.read_hipscat(acf_rans_weight_dir) + assert isinstance(galaxy_catalog, lsdb.Catalog) + assert isinstance(random_catalog, lsdb.Catalog) + counts_dd, counts_rr = compute_autocorrelation_counts( + AngularCorrelation, + galaxy_catalog, + random_catalog, + autocorr_params, + use_weights=True, + ) + npt.assert_allclose(counts_dd, acf_dd_counts_with_weights, rtol=1e-3) + npt.assert_allclose(counts_rr, acf_rr_counts_with_weights, rtol=2e-3) + + +def test_acf_weights_not_provided(data_catalog_dir, rand_catalog_dir, autocorr_params): + galaxy_catalog = lsdb.read_hipscat(data_catalog_dir) + random_catalog = lsdb.read_hipscat(rand_catalog_dir) + assert isinstance(galaxy_catalog, lsdb.Catalog) + assert isinstance(random_catalog, lsdb.Catalog) + with pytest.raises(ValueError, match="does not exist"): + compute_autocorrelation( + AngularCorrelation, + galaxy_catalog, + random_catalog, + autocorr_params, + use_weights=True, + ) diff --git a/tests/data/expected_results/acf/dd_acf_weight.npy b/tests/data/expected_results/acf/dd_acf_weight.npy new file mode 100644 index 0000000000000000000000000000000000000000..60150377e7712973dcff4d69e65f479d77afffc1 GIT binary patch literal 392 zcmbR27wQ`j$;eQ~P_3SlTAW;@Zl$1ZlV+i=qoAIaUsO_*m=~X4l#&V(cT3DEP6dh= zXCxM+0{I%o#yXlh3bhL411<&zh7hiEzwCjuL+0NTAiA4(mZ$@e*5;NF0@2l$`jSAp zp+o7sI*5+G$F2*c4@~^=!xF^j)O4@~(h9kq-p)YULFKkj0FeH`-S;*ONKcSmu_gf| ze(|St8j#*_-J~fWNXOW#mXrZ$g-S>LMj&m|??15vNSodi)|v#Q1K+S8nB~CGaNBOC z&=Mfcktfcv-htsj$lpmzwgc%+diLChfHdQy^S@6!Fc`$0G}XT9z;GnG?HJDk2Zjyr 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