From d61db1ad1dd79817562c5e516c7ff7c10078a221 Mon Sep 17 00:00:00 2001 From: Sandro Campos Date: Thu, 7 Mar 2024 11:50:37 -0500 Subject: [PATCH 1/6] Fix margin generation in from_dataframe --- .../dataframe/margin_catalog_generator.py | 104 ++++++++++++------ 1 file changed, 69 insertions(+), 35 deletions(-) diff --git a/src/lsdb/loaders/dataframe/margin_catalog_generator.py b/src/lsdb/loaders/dataframe/margin_catalog_generator.py index 7bf545ea..b039364d 100644 --- a/src/lsdb/loaders/dataframe/margin_catalog_generator.py +++ b/src/lsdb/loaders/dataframe/margin_catalog_generator.py @@ -4,11 +4,13 @@ import healpy as hp import hipscat as hc +import numpy as np import pandas as pd from hipscat import pixel_math from hipscat.catalog import CatalogType from hipscat.catalog.margin_cache import MarginCacheCatalogInfo from hipscat.pixel_math import HealpixPixel +from hipscat.pixel_math.healpix_pixel_function import get_pixel_argsort from lsdb import Catalog from lsdb.catalog.margin_catalog import MarginCatalog @@ -34,8 +36,8 @@ def __init__( margin_order (int): The order at which to generate the margin cache margin_threshold (float): The size of the margin cache boundary, in arcseconds """ - self.dataframe = catalog.compute().copy() - self.hc_structure = catalog.hc_structure + self.catalog = catalog + self.catalog_info = self.catalog.hc_structure.catalog_info self.margin_threshold = margin_threshold self.margin_order = self._set_margin_order(margin_order) @@ -43,8 +45,8 @@ def _set_margin_order(self, margin_order: int | None) -> int: """Set the order of the margin cache to be generated. If not provided, the margin will be of an order that is higher than that of the original catalog by 1""" - highest_order = self.hc_structure.partition_info.get_highest_order() - margin_pixel_k = highest_order + 1 + partition_info = self.catalog.hc_structure.partition_info + margin_pixel_k = partition_info.get_highest_order() + 1 if margin_order is None or margin_order == -1: margin_order = margin_pixel_k elif margin_order < margin_pixel_k: @@ -74,40 +76,72 @@ def _generate_dask_df_and_map(self): Tuple containing the Dask Dataframe, the mapping of HEALPix pixels to the respective Pandas Dataframes and the total number of rows. """ - # Find the margin pairs of pixels for the catalog - healpix_pixels = self.hc_structure.get_healpix_pixels() - negative_pixels = self.hc_structure.generate_negative_tree_pixels() + healpix_pixels = self.catalog.hc_structure.get_healpix_pixels() + negative_pixels = self.catalog.hc_structure.generate_negative_tree_pixels() combined_pixels = healpix_pixels + negative_pixels margin_pairs_df = self._find_margin_pixel_pairs(combined_pixels) - # Find in which pixels the data is located in the margin catalog - self.dataframe["margin_pixel"] = hp.ang2pix( - 2**self.margin_order, - self.dataframe[self.hc_structure.catalog_info.ra_column].values, - self.dataframe[self.hc_structure.catalog_info.dec_column].values, - lonlat=True, - nest=True, - ) - constrained_data = self.dataframe.reset_index().merge(margin_pairs_df, on="margin_pixel") + margin_shards = self._create_margins(healpix_pixels, margin_pairs_df) - pixel_dfs = [] - ddf_pixel_map = {} + pixel_list, final_df = list(margin_shards.keys()), list(margin_shards.values()) + ordered_pixels = np.array(pixel_list)[get_pixel_argsort(pixel_list)] + ddf_pixel_map = {pixel: margin_shards[pixel] for pixel in ordered_pixels} + ddf, total_rows = _generate_dask_dataframe(final_df, pixel_list) - # For each partition, filter the data according to the threshold - partition_dfs = constrained_data.groupby(["partition_order", "partition_pixel"]) + return ddf, ddf_pixel_map, total_rows - for i, (_, partition) in enumerate(partition_dfs): - order = partition["partition_order"].iloc[0] - pix = partition["partition_pixel"].iloc[0] - pixel = HealpixPixel(order, pix) - df = self._get_partition_data_in_margin(partition, pixel) - pixel_dfs.append(_format_margin_partition_dataframe(df)) - ddf_pixel_map[pixel] = i + def _create_margins(self, pixels: List[HealpixPixel], margin_pairs_df: pd.DataFrame) -> dict: + """Computes the margins for all the pixels in the catalog - # Generate Dask Dataframe with original schema - pixel_list = list(ddf_pixel_map.keys()) - ddf, total_rows = _generate_dask_dataframe(pixel_dfs, pixel_list) - return ddf, ddf_pixel_map, total_rows + Args: + pixels (List[HealpixPixel]): The list of pixels in the catalog + margin_pairs_df (pd.DataFrame): A DataFrame containing all the combinations + of catalog pixels and respective margin pixels + + Returns: + A dictionary that maps each margin pixel to the respective DataFrame shards + that have points for each catalog partition + """ + margin_shards: dict[HealpixPixel, List[pd.DataFrame]] = {} + + for pixel in pixels: + partition = self.catalog.get_partition(pixel.order, pixel.pixel).compute() + partition["margin_pixel"] = hp.ang2pix( + 2**self.margin_order, + partition[self.catalog_info.ra_column].values, + partition[self.catalog_info.dec_column].values, + lonlat=True, + nest=True, + ) + constrained_data = partition.reset_index().merge(margin_pairs_df, on="margin_pixel") + if len(constrained_data): + constrained_data.groupby(["partition_order", "partition_pixel"]).apply( + self._to_margin_shard, margin_shards + ) + + return { + margin_pixel: pd.concat(shard_dfs, axis=0) for margin_pixel, shard_dfs in margin_shards.items() + } + + def _to_margin_shard(self, partition: pd.DataFrame, margin_shards: dict): + """Computes the data points for a margin pixel that are inside an + existing catalog partition + + Args: + partition (pd.DataFrame): Catalog partition DataFrame + margin_shards (dict): A dictionary that holds information about + each margin pixel and the respective DataFrame shards + """ + partition_order = partition["partition_order"].iloc[0] + partition_pixel = partition["partition_pixel"].iloc[0] + margin_pixel = HealpixPixel(partition_order, partition_pixel) + df = self._get_partition_data_in_margin(partition, margin_pixel) + if len(df): + df = _format_margin_partition_dataframe(df) + if margin_pixel in margin_shards: + margin_shards[margin_pixel].append(df) + else: + margin_shards[margin_pixel] = [df] def _find_margin_pixel_pairs(self, pixels: List[HealpixPixel]) -> pd.DataFrame: """Calculate the pairs of catalog pixels and their margin pixels @@ -153,8 +187,8 @@ def _get_partition_data_in_margin(self, partition_df: pd.DataFrame, pixel: Healp are within the specified margin. """ margin_mask = pixel_math.check_margin_bounds( - partition_df[self.hc_structure.catalog_info.ra_column].values, - partition_df[self.hc_structure.catalog_info.dec_column].values, + partition_df[self.catalog_info.ra_column].values, + partition_df[self.catalog_info.dec_column].values, pixel.order, pixel.pixel, self.margin_threshold, @@ -171,9 +205,9 @@ def _create_catalog_info(self, total_rows: int) -> MarginCacheCatalogInfo: The margin catalog info object """ return MarginCacheCatalogInfo( - catalog_name=f"{self.hc_structure.catalog_info.catalog_name}_margin", + catalog_name=f"{self.catalog_info.catalog_name}_margin", catalog_type=CatalogType.MARGIN, total_rows=total_rows, - primary_catalog=self.hc_structure.catalog_info.catalog_name, + primary_catalog=self.catalog_info.catalog_name, margin_threshold=self.margin_threshold, ) From c703841a6f21859af000bffb66a3bf075c0a4151 Mon Sep 17 00:00:00 2001 From: Sandro Campos Date: Thu, 7 Mar 2024 17:10:48 -0500 Subject: [PATCH 2/6] Revert to use the catalog dataframe for margins --- .../dataframe/margin_catalog_generator.py | 142 +++++++++--------- 1 file changed, 73 insertions(+), 69 deletions(-) diff --git a/src/lsdb/loaders/dataframe/margin_catalog_generator.py b/src/lsdb/loaders/dataframe/margin_catalog_generator.py index b039364d..807321a2 100644 --- a/src/lsdb/loaders/dataframe/margin_catalog_generator.py +++ b/src/lsdb/loaders/dataframe/margin_catalog_generator.py @@ -1,6 +1,6 @@ from __future__ import annotations -from typing import List +from typing import Dict, List import healpy as hp import hipscat as hc @@ -29,24 +29,32 @@ def __init__( margin_order: int | None = -1, margin_threshold: float = 5.0, ) -> None: - """Initializes a MarginCatalogGenerator + """Initialize a MarginCatalogGenerator Args: catalog (Catalog): The LSDB catalog to generate margins for margin_order (int): The order at which to generate the margin cache margin_threshold (float): The size of the margin cache boundary, in arcseconds """ - self.catalog = catalog - self.catalog_info = self.catalog.hc_structure.catalog_info + self.dataframe = catalog.compute().copy() + self.hc_structure = catalog.hc_structure self.margin_threshold = margin_threshold self.margin_order = self._set_margin_order(margin_order) def _set_margin_order(self, margin_order: int | None) -> int: - """Set the order of the margin cache to be generated. - If not provided, the margin will be of an order that - is higher than that of the original catalog by 1""" - partition_info = self.catalog.hc_structure.partition_info - margin_pixel_k = partition_info.get_highest_order() + 1 + """Calculate the order of the margin cache to be generated. If not provided + the margin will be greater than that of the original catalog by 1. + + Args: + margin_order (int): The order to generate the margin cache with + + Returns: + The validated order of the margin catalog. + + Raises: + ValueError, if the provided margin order is lower than that of the catalog. + """ + margin_pixel_k = self.hc_structure.partition_info.get_highest_order() + 1 if margin_order is None or margin_order == -1: margin_order = margin_pixel_k elif margin_order < margin_pixel_k: @@ -70,90 +78,85 @@ def create_catalog(self) -> MarginCatalog: def _generate_dask_df_and_map(self): """Create the Dask Dataframe containing the data points in the margins for the catalog, as well as the mapping of those HEALPix pixels to - HEALPix Dataframes. + HEALPix Dataframes Returns: Tuple containing the Dask Dataframe, the mapping of HEALPix pixels to the respective Pandas Dataframes and the total number of rows. """ - healpix_pixels = self.catalog.hc_structure.get_healpix_pixels() - negative_pixels = self.catalog.hc_structure.generate_negative_tree_pixels() + healpix_pixels = self.hc_structure.get_healpix_pixels() + negative_pixels = self.hc_structure.generate_negative_tree_pixels() combined_pixels = healpix_pixels + negative_pixels margin_pairs_df = self._find_margin_pixel_pairs(combined_pixels) - - margin_shards = self._create_margins(healpix_pixels, margin_pairs_df) - - pixel_list, final_df = list(margin_shards.keys()), list(margin_shards.values()) - ordered_pixels = np.array(pixel_list)[get_pixel_argsort(pixel_list)] - ddf_pixel_map = {pixel: margin_shards[pixel] for pixel in ordered_pixels} - ddf, total_rows = _generate_dask_dataframe(final_df, pixel_list) - + # Compute points for each margin pixels + margins_pixel_df = self._create_margins(margin_pairs_df) + pixels, partitions = list(margins_pixel_df.keys()), list(margins_pixel_df.values()) + # Generate pixel map ordered by _hipscat_index + pixel_order = get_pixel_argsort(pixels) + ordered_pixels = np.asarray(pixels)[pixel_order] + ordered_partitions = [partitions[i] for i in pixel_order] + ddf_pixel_map = {pixel: index for index, pixel in enumerate(ordered_pixels)} + # Generate the dask dataframe with the pixels and partitions + ddf, total_rows = _generate_dask_dataframe(ordered_partitions, ordered_pixels) return ddf, ddf_pixel_map, total_rows - def _create_margins(self, pixels: List[HealpixPixel], margin_pairs_df: pd.DataFrame) -> dict: - """Computes the margins for all the pixels in the catalog + def _create_margins(self, margin_pairs_df: pd.DataFrame) -> Dict[HealpixPixel, pd.DataFrame]: + """Compute the margins for all the pixels in the catalog Args: - pixels (List[HealpixPixel]): The list of pixels in the catalog margin_pairs_df (pd.DataFrame): A DataFrame containing all the combinations of catalog pixels and respective margin pixels Returns: A dictionary that maps each margin pixel to the respective DataFrame shards - that have points for each catalog partition + that have points for each catalog partition. """ - margin_shards: dict[HealpixPixel, List[pd.DataFrame]] = {} - - for pixel in pixels: - partition = self.catalog.get_partition(pixel.order, pixel.pixel).compute() - partition["margin_pixel"] = hp.ang2pix( - 2**self.margin_order, - partition[self.catalog_info.ra_column].values, - partition[self.catalog_info.dec_column].values, - lonlat=True, - nest=True, + margin_shards: Dict[HealpixPixel, List[pd.DataFrame]] = {} + self.dataframe["margin_pixel"] = hp.ang2pix( + 2**self.margin_order, + self.dataframe[self.hc_structure.catalog_info.ra_column].values, + self.dataframe[self.hc_structure.catalog_info.dec_column].values, + lonlat=True, + nest=True, + ) + constrained_data = self.dataframe.reset_index().merge(margin_pairs_df, on="margin_pixel") + if len(constrained_data): + constrained_data.groupby(["partition_order", "partition_pixel"]).apply( + self._to_margin_shard, margin_shards ) - constrained_data = partition.reset_index().merge(margin_pairs_df, on="margin_pixel") - if len(constrained_data): - constrained_data.groupby(["partition_order", "partition_pixel"]).apply( - self._to_margin_shard, margin_shards - ) - - return { - margin_pixel: pd.concat(shard_dfs, axis=0) for margin_pixel, shard_dfs in margin_shards.items() + reduced_margin_shards = { + pixel: pd.concat(shard_dfs, axis=0) for pixel, shard_dfs in margin_shards.items() } + return reduced_margin_shards - def _to_margin_shard(self, partition: pd.DataFrame, margin_shards: dict): - """Computes the data points for a margin pixel that are inside an - existing catalog partition + def _to_margin_shard( + self, partition: pd.DataFrame, margin_shards: Dict[HealpixPixel, List[pd.DataFrame]] + ): + """Get the points of a margin pixel which are inside a catalog partition Args: partition (pd.DataFrame): Catalog partition DataFrame - margin_shards (dict): A dictionary that holds information about - each margin pixel and the respective DataFrame shards + margin_shards (dict): A dictionary that maps each margin pixel and the + respective DataFrame shards """ partition_order = partition["partition_order"].iloc[0] partition_pixel = partition["partition_pixel"].iloc[0] margin_pixel = HealpixPixel(partition_order, partition_pixel) - df = self._get_partition_data_in_margin(partition, margin_pixel) + df = self._get_data_in_margin(partition, margin_pixel) if len(df): df = _format_margin_partition_dataframe(df) - if margin_pixel in margin_shards: - margin_shards[margin_pixel].append(df) - else: - margin_shards[margin_pixel] = [df] + margin_shards.setdefault(margin_pixel, []).append(df) def _find_margin_pixel_pairs(self, pixels: List[HealpixPixel]) -> pd.DataFrame: """Calculate the pairs of catalog pixels and their margin pixels Args: - pixels (List[HealpixPixel]): The list of HEALPix pixels to - compute margin pixels for. These include the catalog - pixels as well as the negative pixels. + pixels (List[HealpixPixel]): The HEALPix to compute margin pixels for. + These include the catalog pixels as well as the negative pixels. Returns: - A Pandas Dataframe with the many-to-many mapping between the - partitions and the respective margin pixels. + A Pandas Dataframe with the many-to-many mapping between the partitions + and the respective margin pixels. """ n_orders = [] part_pix = [] @@ -174,40 +177,41 @@ def _find_margin_pixel_pairs(self, pixels: List[HealpixPixel]) -> pd.DataFrame: columns=["partition_order", "partition_pixel", "margin_pixel"], ) - def _get_partition_data_in_margin(self, partition_df: pd.DataFrame, pixel: HealpixPixel) -> pd.DataFrame: + def _get_data_in_margin(self, partition_df: pd.DataFrame, pixel: HealpixPixel) -> pd.DataFrame: """Calculate the margin boundaries for the HEALPix and include the points - on the margins according to the specified threshold. + on the margins according to the specified threshold Args: partition_df (pd.DataFrame): The partition dataframe pixel (HealpixPixel): The HEALPix pixel to get the margin points for Returns: - A Pandas Dataframe with the points of the partition that - are within the specified margin. + A Pandas Dataframe with the points of the partition that are within + the specified margin. """ margin_mask = pixel_math.check_margin_bounds( - partition_df[self.catalog_info.ra_column].values, - partition_df[self.catalog_info.dec_column].values, + partition_df[self.hc_structure.catalog_info.ra_column].values, + partition_df[self.hc_structure.catalog_info.dec_column].values, pixel.order, pixel.pixel, self.margin_threshold, ) - return partition_df.loc[margin_mask] + return partition_df.iloc[margin_mask] def _create_catalog_info(self, total_rows: int) -> MarginCacheCatalogInfo: - """Creates the margin catalog info object + """Create the margin catalog info object Args: - total_rows: The number of elements in the margin catalog + total_rows (int): The number of elements in the margin catalog Returns: - The margin catalog info object + The margin catalog info object. """ + catalog_name = self.hc_structure.catalog_info.catalog_name return MarginCacheCatalogInfo( - catalog_name=f"{self.catalog_info.catalog_name}_margin", + catalog_name=f"{catalog_name}_margin", catalog_type=CatalogType.MARGIN, total_rows=total_rows, - primary_catalog=self.catalog_info.catalog_name, + primary_catalog=catalog_name, margin_threshold=self.margin_threshold, ) From 4286ff9cba7c800a20d2491016201574d3caab07 Mon Sep 17 00:00:00 2001 From: Sandro Campos Date: Fri, 8 Mar 2024 10:55:10 -0500 Subject: [PATCH 3/6] Add margin test for small sky source of higher order --- tests/conftest.py | 6 ++ tests/data/generate_data.ipynb | 50 ++++++++++++++--- .../Norder=3/Dir=0/Npix=264.parquet | Bin 0 -> 11421 bytes .../Norder=3/Dir=0/Npix=707.parquet | Bin 0 -> 28346 bytes .../Norder=3/Dir=0/Npix=708.parquet | Bin 0 -> 21963 bytes .../Norder=3/Dir=0/Npix=709.parquet | Bin 0 -> 42432 bytes .../Norder=3/Dir=0/Npix=710.parquet | Bin 0 -> 25648 bytes .../Norder=3/Dir=0/Npix=711.parquet | Bin 0 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tests/data/small_sky_order3_source_margin/Norder=3/Dir=0/Npix=754.parquet create mode 100644 tests/data/small_sky_order3_source_margin/Norder=3/Dir=0/Npix=755.parquet create mode 100644 tests/data/small_sky_order3_source_margin/Norder=3/Dir=0/Npix=760.parquet create mode 100644 tests/data/small_sky_order3_source_margin/_common_metadata create mode 100644 tests/data/small_sky_order3_source_margin/_metadata create mode 100644 tests/data/small_sky_order3_source_margin/catalog_info.json create mode 100644 tests/data/small_sky_order3_source_margin/partition_info.csv create mode 100644 tests/data/small_sky_order3_source_margin/provenance_info.json diff --git a/tests/conftest.py b/tests/conftest.py index 7f3d978f..605a3711 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -12,6 +12,7 @@ SMALL_SKY_DIR_NAME = "small_sky" SMALL_SKY_LEFT_XMATCH_NAME = "small_sky_left_xmatch" SMALL_SKY_SOURCE_MARGIN_NAME = "small_sky_source_margin" +SMALL_SKY_ORDER3_SOURCE_MARGIN_NAME = "small_sky_order3_source_margin" SMALL_SKY_XMATCH_NAME = "small_sky_xmatch" SMALL_SKY_XMATCH_MARGIN_NAME = "small_sky_xmatch_margin" SMALL_SKY_TO_XMATCH_NAME = "small_sky_to_xmatch" @@ -181,6 +182,11 @@ def small_sky_source_margin_catalog(test_data_dir): return lsdb.read_hipscat(os.path.join(test_data_dir, SMALL_SKY_SOURCE_MARGIN_NAME)) +@pytest.fixture +def small_sky_order3_source_margin_catalog(test_data_dir): + return lsdb.read_hipscat(os.path.join(test_data_dir, SMALL_SKY_ORDER3_SOURCE_MARGIN_NAME)) + + @pytest.fixture def xmatch_expected_dir(test_data_dir): return os.path.join(test_data_dir, "raw", "xmatch_expected") diff --git a/tests/data/generate_data.ipynb b/tests/data/generate_data.ipynb index 0549b5ef..a803be91 100644 --- a/tests/data/generate_data.ipynb +++ b/tests/data/generate_data.ipynb @@ -224,6 +224,47 @@ "runner.pipeline_with_client(args, client)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### small_sky_order3_source_margin\n", + "\n", + "This one is similar to the previous margin catalogs but it is generated from a source catalog of order 3." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "args = ImportArguments(\n", + " input_file_list=[\"raw/small_sky_source/small_sky_source.csv\"],\n", + " output_path=\".\",\n", + " file_reader=\"csv\",\n", + " ra_column=\"source_ra\",\n", + " dec_column=\"source_dec\",\n", + " catalog_type=\"source\",\n", + " output_artifact_name=\"small_sky_order3_source\",\n", + " constant_healpix_order=3,\n", + " overwrite=True,\n", + " tmp_dir=tmp_dir,\n", + ")\n", + "runner.pipeline_with_client(args, client)\n", + "\n", + "args = MarginCacheArguments(\n", + " input_catalog_path=\"small_sky_order3_source\",\n", + " output_path=\".\",\n", + " output_artifact_name=\"small_sky_order3_source_margin\",\n", + " margin_threshold=300,\n", + " margin_order=7,\n", + " overwrite=True,\n", + " tmp_dir=tmp_dir,\n", + ")\n", + "runner.pipeline_with_client(args, client)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -434,13 +475,6 @@ "tmp_path.cleanup()\n", "client.close()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -459,7 +493,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.13" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/tests/data/small_sky_order3_source/Norder=3/Dir=0/Npix=264.parquet b/tests/data/small_sky_order3_source/Norder=3/Dir=0/Npix=264.parquet new file mode 100644 index 0000000000000000000000000000000000000000..e9e9ab5a035c3048c7b57784b1843fe169fa9917 GIT binary patch literal 11421 zcmcgS33yXg)-T;iOADotl9r0K(nx`}Sz4f&z&&VJ54_ug{@ zlgM%bCxr8A80W{}B94wj#1O>%;K*%pEP}-f5s=~RkhEB6{!a$YkvwQ_PJ||?ESya| z62%UgDF}}a*)R-1(iCV$7eb?&0?luup{cnKnnNOJwvK}4N-l6oqM}1Oh62~HVgT(Z zh2|9=z(0z5l}L%I2uUdl=Z27z0Zhk1qvk`iC<&U6IMB=;38bQ^7UKS>;UNtZ!ns6I 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Date: Fri, 8 Mar 2024 12:39:05 -0500 Subject: [PATCH 4/6] Fix documentation notebooks --- docs/notebooks/import_catalogs.ipynb | 6 +++--- docs/notebooks/ztf_bts-ngc.ipynb | 6 ++++-- src/lsdb/loaders/dataframe/from_dataframe_utils.py | 2 +- .../loaders/dataframe/margin_catalog_generator.py | 13 ++++++++----- 4 files changed, 16 insertions(+), 11 deletions(-) diff --git a/docs/notebooks/import_catalogs.ipynb b/docs/notebooks/import_catalogs.ipynb index c604205e..03708be7 100644 --- a/docs/notebooks/import_catalogs.ipynb +++ b/docs/notebooks/import_catalogs.ipynb @@ -293,14 +293,14 @@ "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" + "pygments_lexer": "ipython3", + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/notebooks/ztf_bts-ngc.ipynb b/docs/notebooks/ztf_bts-ngc.ipynb index 7bb0c585..b34891e8 100644 --- a/docs/notebooks/ztf_bts-ngc.ipynb +++ b/docs/notebooks/ztf_bts-ngc.ipynb @@ -173,7 +173,9 @@ " matched_df = matched.compute()\n", "\n", "# Let's output transient name, NGC name and angular distance between them\n", - "matched_df = matched_df[[\"IAUID_ztf\", \"Name_ngc\", \"_DIST\", \"RA_ztf\", \"Dec_ztf\"]].sort_values(by=[\"_DIST\"])\n", + "matched_df = matched_df[[\"IAUID_ztf\", \"Name_ngc\", \"_dist_arcsec\", \"RA_ztf\", \"Dec_ztf\"]].sort_values(\n", + " by=[\"_dist_arcsec\"]\n", + ")\n", "matched_df" ] }, @@ -288,7 +290,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.13" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/src/lsdb/loaders/dataframe/from_dataframe_utils.py b/src/lsdb/loaders/dataframe/from_dataframe_utils.py index b079e24f..b0135c5d 100644 --- a/src/lsdb/loaders/dataframe/from_dataframe_utils.py +++ b/src/lsdb/loaders/dataframe/from_dataframe_utils.py @@ -23,7 +23,7 @@ def _generate_dask_dataframe( Returns: The catalog's Dask Dataframe and its total number of rows. """ - schema = pixel_dfs[0].iloc[:0, :].copy() + schema = pixel_dfs[0].iloc[:0, :].copy() if len(pixels) > 0 else [] divisions = get_pixels_divisions(pixels) delayed_dfs = [delayed(df) for df in pixel_dfs] ddf = dd.from_delayed(delayed_dfs, meta=schema, divisions=divisions) diff --git a/src/lsdb/loaders/dataframe/margin_catalog_generator.py b/src/lsdb/loaders/dataframe/margin_catalog_generator.py index 807321a2..956fba40 100644 --- a/src/lsdb/loaders/dataframe/margin_catalog_generator.py +++ b/src/lsdb/loaders/dataframe/margin_catalog_generator.py @@ -1,7 +1,8 @@ from __future__ import annotations -from typing import Dict, List +from typing import Dict, List, Tuple +import dask.dataframe as dd import healpy as hp import hipscat as hc import numpy as np @@ -63,19 +64,21 @@ def _set_margin_order(self, margin_order: int | None) -> int: ) return margin_order - def create_catalog(self) -> MarginCatalog: + def create_catalog(self) -> MarginCatalog | None: """Create a margin catalog for another pre-computed catalog Returns: - Margin catalog object for the provided catalog + Margin catalog object, or None if the margin is empty. """ ddf, ddf_pixel_map, total_rows = self._generate_dask_df_and_map() - margin_catalog_info = self._create_catalog_info(total_rows) margin_pixels = list(ddf_pixel_map.keys()) + if len(margin_pixels) == 0: + return None + margin_catalog_info = self._create_catalog_info(total_rows) margin_structure = hc.catalog.MarginCatalog(margin_catalog_info, margin_pixels) return MarginCatalog(ddf, ddf_pixel_map, margin_structure) - def _generate_dask_df_and_map(self): + def _generate_dask_df_and_map(self) -> Tuple[dd.DataFrame, Dict[HealpixPixel, int], int]: """Create the Dask Dataframe containing the data points in the margins for the catalog, as well as the mapping of those HEALPix pixels to HEALPix Dataframes From a6e3e37d68646655ef365084778db7c788654bff Mon Sep 17 00:00:00 2001 From: Sandro Campos Date: Fri, 8 Mar 2024 12:53:59 -0500 Subject: [PATCH 5/6] Improve code coverage --- tests/lsdb/loaders/dataframe/test_from_dataframe.py | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/tests/lsdb/loaders/dataframe/test_from_dataframe.py b/tests/lsdb/loaders/dataframe/test_from_dataframe.py index 7dcbdef0..cb34f4a8 100644 --- a/tests/lsdb/loaders/dataframe/test_from_dataframe.py +++ b/tests/lsdb/loaders/dataframe/test_from_dataframe.py @@ -231,3 +231,14 @@ def test_from_dataframe_invalid_margin_order(small_sky_source_df): lowest_order=2, margin_order=1, ) + + +def test_from_dataframe_margin_is_empty(small_sky_order1_df): + catalog = lsdb.from_dataframe( + small_sky_order1_df, + catalog_name="small_sky_order1", + catalog_type="object", + highest_order=5, + threshold=100, + ) + assert catalog.margin is None From bf34c8151ebcfc45394e4c20fc5beee9d42509bc Mon Sep 17 00:00:00 2001 From: Sandro Campos Date: Fri, 8 Mar 2024 18:03:33 -0500 Subject: [PATCH 6/6] Improve code readability --- .../dataframe/margin_catalog_generator.py | 119 +++++++++--------- 1 file changed, 59 insertions(+), 60 deletions(-) diff --git a/src/lsdb/loaders/dataframe/margin_catalog_generator.py b/src/lsdb/loaders/dataframe/margin_catalog_generator.py index 956fba40..06009bda 100644 --- a/src/lsdb/loaders/dataframe/margin_catalog_generator.py +++ b/src/lsdb/loaders/dataframe/margin_catalog_generator.py @@ -72,7 +72,7 @@ def create_catalog(self) -> MarginCatalog | None: """ ddf, ddf_pixel_map, total_rows = self._generate_dask_df_and_map() margin_pixels = list(ddf_pixel_map.keys()) - if len(margin_pixels) == 0: + if total_rows == 0: return None margin_catalog_info = self._create_catalog_info(total_rows) margin_structure = hc.catalog.MarginCatalog(margin_catalog_info, margin_pixels) @@ -80,29 +80,61 @@ def create_catalog(self) -> MarginCatalog | None: def _generate_dask_df_and_map(self) -> Tuple[dd.DataFrame, Dict[HealpixPixel, int], int]: """Create the Dask Dataframe containing the data points in the margins - for the catalog, as well as the mapping of those HEALPix pixels to - HEALPix Dataframes + for the catalog as well as the mapping of those HEALPix to Dataframes Returns: - Tuple containing the Dask Dataframe, the mapping of HEALPix pixels - to the respective Pandas Dataframes and the total number of rows. + Tuple containing the Dask Dataframe, the mapping of margin HEALPix + to the respective partitions and the total number of rows. """ healpix_pixels = self.hc_structure.get_healpix_pixels() negative_pixels = self.hc_structure.generate_negative_tree_pixels() combined_pixels = healpix_pixels + negative_pixels margin_pairs_df = self._find_margin_pixel_pairs(combined_pixels) + # Compute points for each margin pixels margins_pixel_df = self._create_margins(margin_pairs_df) pixels, partitions = list(margins_pixel_df.keys()), list(margins_pixel_df.values()) + # Generate pixel map ordered by _hipscat_index pixel_order = get_pixel_argsort(pixels) ordered_pixels = np.asarray(pixels)[pixel_order] ordered_partitions = [partitions[i] for i in pixel_order] ddf_pixel_map = {pixel: index for index, pixel in enumerate(ordered_pixels)} + # Generate the dask dataframe with the pixels and partitions ddf, total_rows = _generate_dask_dataframe(ordered_partitions, ordered_pixels) return ddf, ddf_pixel_map, total_rows + def _find_margin_pixel_pairs(self, pixels: List[HealpixPixel]) -> pd.DataFrame: + """Calculate the pairs of catalog pixels and their margin pixels + + Args: + pixels (List[HealpixPixel]): The list of HEALPix to compute margin pixels for. + These include the catalog pixels as well as the negative pixels. + + Returns: + A Pandas Dataframe with the many-to-many mapping between each catalog HEALPix + and the respective margin pixels. + """ + n_orders = [] + part_pix = [] + margin_pix = [] + + for pixel in pixels: + order = pixel.order + pix = pixel.pixel + d_order = self.margin_order - order + margins = pixel_math.get_margin(order, pix, d_order) + for m_p in margins: + n_orders.append(order) + part_pix.append(pix) + margin_pix.append(m_p) + + return pd.DataFrame( + zip(n_orders, part_pix, margin_pix), + columns=["partition_order", "partition_pixel", "margin_pixel"], + ) + def _create_margins(self, margin_pairs_df: pd.DataFrame) -> Dict[HealpixPixel, pd.DataFrame]: """Compute the margins for all the pixels in the catalog @@ -111,10 +143,9 @@ def _create_margins(self, margin_pairs_df: pd.DataFrame) -> Dict[HealpixPixel, p of catalog pixels and respective margin pixels Returns: - A dictionary that maps each margin pixel to the respective DataFrame shards - that have points for each catalog partition. + A dictionary mapping each margin pixel to the respective DataFrame. """ - margin_shards: Dict[HealpixPixel, List[pd.DataFrame]] = {} + margin_pixel_df_map: Dict[HealpixPixel, pd.DataFrame] = {} self.dataframe["margin_pixel"] = hp.ang2pix( 2**self.margin_order, self.dataframe[self.hc_structure.catalog_info.ra_column].values, @@ -125,78 +156,46 @@ def _create_margins(self, margin_pairs_df: pd.DataFrame) -> Dict[HealpixPixel, p constrained_data = self.dataframe.reset_index().merge(margin_pairs_df, on="margin_pixel") if len(constrained_data): constrained_data.groupby(["partition_order", "partition_pixel"]).apply( - self._to_margin_shard, margin_shards + self._append_margin_df, margin_pixel_df_map ) - reduced_margin_shards = { - pixel: pd.concat(shard_dfs, axis=0) for pixel, shard_dfs in margin_shards.items() - } - return reduced_margin_shards + return margin_pixel_df_map - def _to_margin_shard( - self, partition: pd.DataFrame, margin_shards: Dict[HealpixPixel, List[pd.DataFrame]] + def _append_margin_df( + self, partition_df: pd.DataFrame, margin_pixel_df_map: Dict[HealpixPixel, pd.DataFrame] ): - """Get the points of a margin pixel which are inside a catalog partition + """Filter margin data points and create the partition final Dataframe Args: - partition (pd.DataFrame): Catalog partition DataFrame - margin_shards (dict): A dictionary that maps each margin pixel and the - respective DataFrame shards + partition_df (pd.DataFrame): Catalog data points for the margin pixel + margin_pixel_df_map (Dict[HealpixPixel, pd.DataFrame]): A dictionary mapping + each margin pixel to the respective DataFrame. This dictionary is updated + on each call to this method. """ - partition_order = partition["partition_order"].iloc[0] - partition_pixel = partition["partition_pixel"].iloc[0] + partition_order = partition_df["partition_order"].iloc[0] + partition_pixel = partition_df["partition_pixel"].iloc[0] margin_pixel = HealpixPixel(partition_order, partition_pixel) - df = self._get_data_in_margin(partition, margin_pixel) + df = self._get_data_in_margin(partition_df, margin_pixel) if len(df): df = _format_margin_partition_dataframe(df) - margin_shards.setdefault(margin_pixel, []).append(df) - - def _find_margin_pixel_pairs(self, pixels: List[HealpixPixel]) -> pd.DataFrame: - """Calculate the pairs of catalog pixels and their margin pixels - - Args: - pixels (List[HealpixPixel]): The HEALPix to compute margin pixels for. - These include the catalog pixels as well as the negative pixels. - - Returns: - A Pandas Dataframe with the many-to-many mapping between the partitions - and the respective margin pixels. - """ - n_orders = [] - part_pix = [] - margin_pix = [] - - for pixel in pixels: - order = pixel.order - pix = pixel.pixel - d_order = self.margin_order - order - margins = pixel_math.get_margin(order, pix, d_order) - for m_p in margins: - n_orders.append(order) - part_pix.append(pix) - margin_pix.append(m_p) - - return pd.DataFrame( - zip(n_orders, part_pix, margin_pix), - columns=["partition_order", "partition_pixel", "margin_pixel"], - ) + margin_pixel_df_map[margin_pixel] = df - def _get_data_in_margin(self, partition_df: pd.DataFrame, pixel: HealpixPixel) -> pd.DataFrame: + def _get_data_in_margin(self, partition_df: pd.DataFrame, margin_pixel: HealpixPixel) -> pd.DataFrame: """Calculate the margin boundaries for the HEALPix and include the points - on the margins according to the specified threshold + on the margin according to the specified threshold Args: - partition_df (pd.DataFrame): The partition dataframe - pixel (HealpixPixel): The HEALPix pixel to get the margin points for + partition_df (pd.DataFrame): The margin pixel data + margin_pixel (HealpixPixel): The margin HEALPix Returns: A Pandas Dataframe with the points of the partition that are within - the specified margin. + the specified threshold in the margin. """ margin_mask = pixel_math.check_margin_bounds( partition_df[self.hc_structure.catalog_info.ra_column].values, partition_df[self.hc_structure.catalog_info.dec_column].values, - pixel.order, - pixel.pixel, + margin_pixel.order, + margin_pixel.pixel, self.margin_threshold, ) return partition_df.iloc[margin_mask]

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