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+ + +
+ +
+
+
+
    +
    • +
  • Overview: module code
    • +
  • +
    • +
+
+
+
+ +
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/harmony/cli.html b/0.10.0a1+113bd04/_modules/merger/harmony/cli.html new file mode 100644 index 00000000..b5c0ca4c --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/harmony/cli.html @@ -0,0 +1,131 @@ + + + + + + merger.harmony.cli — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +

Source code for merger.harmony.cli

+"""A Harmony CLI wrapper around Concise"""
+
+from argparse import ArgumentParser
+import harmony
+from podaac.merger.harmony.service import ConciseService
+
+
+

+[docs]
+def main(config=None):
+    """Main Harmony CLI entrypoint"""
+
+    parser = ArgumentParser()
+    harmony.setup_cli(parser)
+
+    args = parser.parse_args()
+    if harmony.is_harmony_cli(args):
+        harmony.run_cli(parser, args, ConciseService, cfg=config)
+    else:
+        parser.error("Only --harmony CLIs are supported")

+
+
+
+if __name__ == "__main__":
+    main()
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/harmony/download_worker.html b/0.10.0a1+113bd04/_modules/merger/harmony/download_worker.html new file mode 100644 index 00000000..c7c77aea --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/harmony/download_worker.html @@ -0,0 +1,217 @@ + + + + + + merger.harmony.download_worker — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Module code
    • +
  • merger.harmony.download_worker
    • +
  • +
    • +
+
+
+
+
+ +

Source code for merger.harmony.download_worker

+"""A utility for downloading multiple granules simultaneously"""
+
+from copy import deepcopy
+from multiprocessing import Manager, Process
+from os import cpu_count
+from pathlib import Path
+import queue
+import re
+from urllib.parse import urlparse
+
+from harmony.logging import build_logger
+from harmony.util import download
+
+
+

+[docs]
+def multi_core_download(urls, destination_dir, access_token, cfg, process_count=None):
+    """
+    A method which automagically scales downloads to the number of CPU
+    cores. For further explaination, see documentation on "multi-track
+    drifting"
+
+    Parameters
+    ----------
+    urls : list
+        list of urls to download
+    destination_dir : str
+        output path for downloaded files
+    access_token : str
+        access token as provided in Harmony input
+    cfg : dict
+        Harmony configuration information
+    process_count : int
+        Number of worker processes to run (expected >= 1)
+
+    Returns
+    -------
+    list
+        list of downloaded files as pathlib.Path objects
+    """
+
+    if process_count is None:
+        process_count = cpu_count()
+
+    with Manager() as manager:
+        url_queue = manager.Queue(len(urls))
+        path_list = manager.list()
+
+        for iurl, url in enumerate(urls):
+            url_queue.put((iurl, url))
+
+        # Spawn worker processes
+        processes = []
+        for _ in range(process_count):
+            download_process = Process(target=_download_worker, args=(url_queue, path_list, destination_dir, access_token, cfg))
+            processes.append(download_process)
+            download_process.start()
+
+        # Ensure worker processes exit successfully
+        for process in processes:
+            process.join()
+            if process.exitcode != 0:
+                raise RuntimeError(f'Download failed - exit code: {process.exitcode}')
+
+            process.close()
+
+        path_list = deepcopy(path_list)  # ensure GC can cleanup multiprocessing
+
+    return [Path(path) for ipath, path in sorted(path_list)]

+
+
+
+def _download_worker(url_queue, path_list, destination_dir, access_token, cfg):
+    """
+    A method to be executed in a separate process which processes the url_queue
+    and places paths to completed downloads into the path_list. Downloads are
+    handled by harmony.util.download
+
+    Parameters
+    ----------
+    url_queue : queue.Queue
+        URLs to process - should be filled from start and only decreases
+    path_list : list
+        paths to completed file downloads
+    destination_dir : str
+        output path for downloaded files
+    access_token : str
+        access token as provided in Harmony input
+    cfg : dict
+        Harmony configuration information
+    """
+
+    logger = build_logger(cfg)
+
+    while not url_queue.empty():
+        try:
+            iurl, url = url_queue.get_nowait()
+        except queue.Empty:
+            break
+
+        path = Path(download(url, destination_dir, logger=logger, access_token=access_token, cfg=cfg))
+        filename_match = re.match(r'.*\/(.+\..+)', urlparse(url).path)
+
+        if filename_match is not None:
+            filename = filename_match.group(1)
+            dest_path = path.parent.joinpath(filename)
+            path = path.rename(dest_path)
+        else:
+            logger.warning('Origin filename could not be assertained - %s', url)
+
+        path_list.append((iurl, str(path)))
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/harmony/service.html b/0.10.0a1+113bd04/_modules/merger/harmony/service.html new file mode 100644 index 00000000..655b2dc6 --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/harmony/service.html @@ -0,0 +1,263 @@ + + + + + + merger.harmony.service — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +

Source code for merger.harmony.service

+"""A Harmony service wrapper around the Concise module"""
+
+from datetime import datetime, timezone
+from pathlib import Path
+from tempfile import TemporaryDirectory
+from shutil import copyfile
+from urllib.parse import urlsplit
+from uuid import uuid4
+
+from harmony.adapter import BaseHarmonyAdapter
+from harmony.util import bbox_to_geometry, stage
+from pystac import Catalog, Item
+from pystac.item import Asset
+
+from podaac.merger.merge import merge_netcdf_files
+from podaac.merger.harmony.download_worker import multi_core_download
+from podaac.merger.harmony.util import get_bbox, get_datetime, get_granule_url
+
+
+NETCDF4_MIME = 'application/x-netcdf4'  # pylint: disable=invalid-name
+
+
+

+[docs]
+class ConciseService(BaseHarmonyAdapter):
+    """
+    A harmony-service-lib wrapper around the Concise module. This wrapper does
+    not support Harmony calls that do not have STAC catalogs as support for
+    this behavior is being depreciated in harmony-service-lib
+    """
+
+

+[docs]
+    def invoke(self):
+        """
+        Primary entrypoint into the service wrapper. Overrides BaseHarmonyAdapter.invoke
+        """
+        if not self.catalog:
+            # Message-only support is being depreciated in Harmony so we should expect to
+            # only see requests with catalogs when invoked with a newer Harmony instance
+            # https://github.com/nasa/harmony-service-lib-py/blob/21bcfbda17caf626fb14d2ac4f8673be9726b549/harmony/adapter.py#L71
+            raise RuntimeError('Invoking CONCISE without a STAC catalog is not supported')
+
+        return (self.message, self.process_catalog(self.catalog))

+
+
+

+[docs]
+    def process_catalog(self, catalog: Catalog):
+        """
+        Recursively process a catalog and all its children. Adapted from
+        BaseHarmonyAdapter._process_catalog_recursive to specfifically
+        support our particular use case for many-to-one
+
+        Parameters
+        ----------
+        catalog : pystac.Catalog or pystac.Collection
+            a catalog/collection to process for merging
+
+        Returns
+        -------
+        pystac.Catalog
+            A new catalog containing the results from the merge
+        """
+        result = catalog.clone()
+        result.id = str(uuid4())
+        result.clear_children()
+
+        # Get all the items from the catalog, including from child or linked catalogs
+        items = list(self.get_all_catalog_items(catalog))
+
+        # Quick return if catalog contains no items
+        if len(items) == 0:
+            return result
+
+        # -- Process metadata --
+        bbox = []
+        granule_urls = []
+        datetimes = [
+            datetime.max.replace(tzinfo=timezone.utc),  # start
+            datetime.min.replace(tzinfo=timezone.utc)   # end
+        ]
+
+        for item in items:
+            get_bbox(item, bbox)
+            get_granule_url(item, granule_urls)
+            get_datetime(item, datetimes)
+
+        # Items did not have a bbox; valid under spec
+        if len(bbox) == 0:
+            bbox = None
+
+        # -- Perform merging --
+        collection = self._get_item_source(items[0]).collection
+        filename = f'{collection}_merged.nc4'
+
+        with TemporaryDirectory() as temp_dir:
+            self.logger.info('Starting granule downloads')
+            input_files = multi_core_download(granule_urls, temp_dir, self.message.accessToken, self.config)
+            self.logger.info('Finished granule downloads')
+
+            output_path = Path(temp_dir).joinpath(filename).resolve()
+            merge_netcdf_files(input_files, output_path, granule_urls, logger=self.logger)
+            staged_url = self._stage(str(output_path), filename, NETCDF4_MIME)
+
+        # -- Output to STAC catalog --
+        result.clear_items()
+        properties = {
+            "start_datetime": datetimes[0].isoformat(),
+            "end_datetime": datetimes[1].isoformat()
+        }
+
+        item = Item(str(uuid4()), bbox_to_geometry(bbox), bbox, None, properties)
+        asset = Asset(staged_url, title=filename, media_type=NETCDF4_MIME, roles=['data'])
+        item.add_asset('data', asset)
+        result.add_item(item)
+
+        return result

+
+
+    def _stage(self, local_filename, remote_filename, mime):
+        """
+        Stages a local file to either to S3 (utilizing harmony.util.stage) or to
+        the local filesystem by performing a file copy. Staging location is
+        determined by message.stagingLocation or the --harmony-data-location
+        CLI argument override
+
+        Parameters
+        ----------
+        local_filename : string
+            A path and filename to the local file that should be staged
+        remote_filename : string
+            The basename to give to the remote file
+        mime : string
+            The mime type to apply to the staged file for use when it is served, e.g. "application/x-netcdf4"
+
+        Returns
+        -------
+        url : string
+            A URL to the staged file
+        """
+        url_components = urlsplit(self.message.stagingLocation)
+        scheme = url_components.scheme
+
+        if scheme == 'file':
+            dest_path = Path(url_components.path).joinpath(remote_filename)
+            self.logger.info('Staging to local filesystem: \'%s\'', str(dest_path))
+
+            copyfile(local_filename, dest_path)
+            return dest_path.as_uri()
+
+        return stage(local_filename, remote_filename, mime,
+                     logger=self.logger,
+                     location=self.message.stagingLocation,
+                     cfg=self.config
+                     )

+
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/harmony/util.html b/0.10.0a1+113bd04/_modules/merger/harmony/util.html new file mode 100644 index 00000000..4bb95f22 --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/harmony/util.html @@ -0,0 +1,226 @@ + + + + + + merger.harmony.util — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +

Source code for merger.harmony.util

+"""Misc utility functions"""
+
+
+

+[docs]
+def is_netcdf_asset(asset, strict):
+    """
+    Determine if an asset is netcdf4-python compatible. netcdf4-python currently supports
+    HDF5, NetCDF3, and NetCDF4. Determination is currently done through MIME if strict
+    mode is enabled. If strict mode is not enabled, determination is done through 'data'
+    role.
+
+    Parameters
+    ----------
+    asset : pystac.Asset
+        an asset to check
+
+    Returns
+    -------
+    bool
+        True if netcdf4-python compatible; False otherwise
+    """
+
+    if strict:
+        accepted_types = ['application/x-hdf5', 'application/x-netcdf', 'application/x-netcdf4']
+        return asset.media_type in accepted_types
+
+    return 'data' in asset.roles

+
+
+
+

+[docs]
+def get_granule_url(item, granule_urls, strict=True):
+    """
+    Processes an item to find a netcdf4-python compatible asset. If no asset is
+    found, a RuntimeException is thrown
+
+    Parameters
+    ----------
+    item : pystac.Item
+        an item to process
+    granule_urls : list
+        list to append the asset's url to
+    """
+
+    for asset in item.assets.values():
+        if is_netcdf_asset(asset, strict):
+            granule_urls.append(asset.href)
+            return
+
+    if not strict:
+        raise RuntimeError(f'A NetCDF4 asset was not found in this item: {item.id}')
+
+    get_granule_url(item, granule_urls, False)  # Rerun in lax-mode

+
+
+
+

+[docs]
+def get_bbox(item, current_bbox):
+    """
+    Accumulate bboxes from items to generate a bbox which encompasses all items
+
+    Parameters
+    ----------
+    item : pystac.Item
+        an item to process
+    current_bbox : list
+        the bbox to accumulate all items to
+    """
+
+    if len(current_bbox) == 0:
+        if item.bbox is not None:  # Spec allows for null geometry and bbox
+            current_bbox[:] = item.bbox
+    else:
+        # xmin
+        if item.bbox[0] < current_bbox[0]:
+            current_bbox[0] = item.bbox[0]
+        # ymin
+        if item.bbox[1] < current_bbox[1]:
+            current_bbox[1] = item.bbox[1]
+        # xmax
+        if item.bbox[2] > current_bbox[2]:
+            current_bbox[2] = item.bbox[2]
+        # ymax
+        if item.bbox[3] > current_bbox[3]:
+            current_bbox[3] = item.bbox[3]

+
+
+
+

+[docs]
+def get_datetime(item, datetimes):
+    """
+    Accumulate datetimes from items to generate a datetime pair that
+    encompasses all items
+
+    Parameters
+    ----------
+    item : pystac.Item
+        an item to process
+    datetimes : list
+        datetime pair to accumulate to; first element is start_datetime,
+        second is end_datetime
+    """
+
+    if item.datetime is None:
+        item_start_dt = item.common_metadata.start_datetime
+        item_end_dt = item.common_metadata.end_datetime
+    else:
+        item_start_dt = item.datetime
+        item_end_dt = item.datetime
+
+    if item_start_dt < datetimes[0]:
+        datetimes[0] = item_start_dt
+
+    if item_end_dt > datetimes[1]:
+        datetimes[1] = item_end_dt

+
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/merge.html b/0.10.0a1+113bd04/_modules/merger/merge.html new file mode 100644 index 00000000..5eaf9410 --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/merge.html @@ -0,0 +1,324 @@ + + + + + + merger.merge — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +

Source code for merger.merge

+"""Main module containing merge implementation"""
+from pathlib import Path
+from time import perf_counter
+from logging import getLogger
+from os import cpu_count
+import netCDF4 as nc
+import numpy as np
+
+from podaac.merger.merge_worker import run_merge
+from podaac.merger.path_utils import get_group_path, resolve_dim, resolve_group
+from podaac.merger.preprocess_worker import run_preprocess
+
+
+

+[docs]
+def is_file_empty(parent_group: nc.Dataset | nc.Group) -> bool:
+    """
+    Function to test if any variable size in a dataset is zero
+    """
+
+    for var in parent_group.variables.values():
+        if var.size != 0:
+            return False
+    for child_group in parent_group.groups.values():
+        return is_file_empty(child_group)
+    return True

+
+
+
+

+[docs]
+def merge_netcdf_files(original_input_files: list[Path],  # pylint: disable=too-many-locals
+                       output_file: str,
+                       granule_urls,
+                       logger=getLogger(__name__),
+                       perf_stats: dict = None,
+                       process_count: int = None):
+    """
+    Main entrypoint to merge implementation. Merges n >= 2 granules together as a single
+    granule. Named in reference to the original Java implementation.
+
+    Parameters
+    ----------
+    original_input_files: list
+        list of Paths to NetCDF4 files to merge
+    output_file: str
+        output path for merged product
+    granule_urls
+    logger: logger
+        logger object
+    perf_stats: dict
+        dictionary used to store performance stats
+    process_count: int
+        number of processes to run (expected >= 1)
+    """
+
+    if perf_stats is None:
+        perf_stats = {}
+
+    if process_count is None:
+        process_count = cpu_count()
+    elif process_count <= 0:
+        raise RuntimeError('process_count should be > 0')
+
+    # -- initial preprocessing --
+    logger.info('Preprocessing data...')
+    start = perf_counter()
+
+    input_files = []
+
+    # only concatinate files that are not empty
+    for file in original_input_files:
+        with nc.Dataset(file, 'r') as dataset:
+            is_empty = is_file_empty(dataset)
+            if is_empty is False:
+                input_files.append(file)
+
+    preprocess = run_preprocess(input_files, process_count, granule_urls)
+    group_list = preprocess['group_list']
+    max_dims = preprocess['max_dims']
+    var_info = preprocess['var_info']
+    var_metadata = preprocess['var_metadata']
+    group_metadata = preprocess['group_metadata']
+
+    perf_stats['preprocess'] = perf_counter() - start
+    logger.info('Preprocessing completed: %f', perf_stats['preprocess'])
+
+    merged_dataset = nc.Dataset(output_file, 'w', format='NETCDF4')
+    merged_dataset.set_auto_maskandscale(False)
+    init_dataset(merged_dataset, group_list, var_info, max_dims, input_files)
+
+    # -- merge datasets --
+    logger.info('Merging datasets...')
+    start = perf_counter()
+    run_merge(merged_dataset, input_files, var_info, max_dims, process_count, logger)
+
+    perf_stats['merge'] = perf_counter() - start
+    logger.info('Merging completed: %f', perf_stats['merge'])
+
+    # -- finalize metadata --
+    logger.info('Finalizing metadata...')
+    start = perf_counter()
+
+    for group_path in group_list:
+        group = merged_dataset if group_path == '/' else merged_dataset[group_path]
+
+        group_attrs = group_metadata[group_path]
+        clean_metadata(group_attrs)
+        group.setncatts(group_attrs)
+
+        for var in group.variables.values():
+            if var.name == 'subset_files' and group == merged_dataset:
+                continue  # Skip /subset_files for metadata finalization
+
+            var_path = get_group_path(group, var.name)
+            var_attrs = var_metadata[var_path]
+            clean_metadata(var_attrs)
+            var.setncatts(var_attrs)
+
+    perf_stats['metadata'] = perf_counter() - start
+    logger.info('Metadata completed: %f', perf_stats['metadata'])
+
+    merged_dataset.close()
+    logger.info('Done!')

+
+
+
+

+[docs]
+def clean_metadata(metadata: dict) -> None:
+    """
+    Prepares metadata dictionary for insertion by removing inconsistent entries
+    and performing escaping of attribute names
+
+    Parameters
+    ----------
+    metadata : dict
+        dictionary of attribute names and their associated data
+    """
+
+    for key in list(metadata):
+        val = metadata[key]
+
+        # delete inconsistent items
+        if not isinstance(val, np.ndarray) and isinstance(val, bool) and not val:
+            del metadata[key]
+        elif key == '_FillValue':
+            del metadata[key]
+
+        # escape '/' to '_'
+        # https://www.unidata.ucar.edu/mailing_lists/archives/netcdfgroup/2012/msg00098.html
+        if '/' in key:
+            new_key = key.replace('/', '_')
+            metadata[new_key] = val
+            del metadata[key]

+
+
+
+

+[docs]
+def init_dataset(merged_dataset: nc.Dataset,
+                 groups: list[str],
+                 var_info: dict,
+                 max_dims: dict,
+                 input_files: list[Path]) -> None:
+    """
+    Initialize the dataset using data gathered from preprocessing
+
+    Parameters
+    ----------
+    merged_dataset : nc.Dataset
+        the dataset to be initialized
+    groups : list
+        list of group names
+    var_info : dict
+        dictionary of variable names and VariableInfo objects
+    max_dims : dict
+        dictionary of dimension names (including path) and their sizes
+    input_files : list
+        list of file paths to be merged
+    """
+
+    # Create groups
+    for group in groups:
+        if group == '/':
+            continue  # Skip root
+
+        merged_dataset.createGroup(group)
+
+    # Create dims
+    merged_dataset.createDimension('subset_index', len(input_files))
+    for dim in max_dims.items():
+        group = resolve_group(merged_dataset, dim[0])
+        group[0].createDimension(group[1], dim[1])
+
+    # Generate filelist
+    subset_files = merged_dataset.createVariable('subset_files', np.str_, ['subset_index'])
+    subset_files.long_name = 'List of subsetted files used to create this merge product.'
+    for i, file in enumerate(input_files):
+        subset_files[i] = file.name
+
+    # Recreate variables
+    for var in var_info.items():
+        dims = ['subset_index'] + list(var[1].dim_order)
+        group = resolve_group(merged_dataset, var[0])
+
+        # Holdover from old merging code - not sure if needed, but kept for legacy
+        chunk_sizes = [1] + [resolve_dim(max_dims, group[0].path, key) for key in var[1].dim_order]
+
+        group[0].createVariable(
+            varname=var[1].name,
+            datatype=var[1].datatype,
+            dimensions=dims,
+            chunksizes=chunk_sizes,
+            fill_value=var[1].fill_value,
+            zlib=True
+        )

+
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/merge_cli.html b/0.10.0a1+113bd04/_modules/merger/merge_cli.html new file mode 100644 index 00000000..b2d5d01e --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/merge_cli.html @@ -0,0 +1,154 @@ + + + + + + merger.merge_cli — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +

Source code for merger.merge_cli

+"""A simple CLI wrapper around the main merge function"""
+
+from argparse import ArgumentParser
+import logging
+from pathlib import Path
+
+from podaac.merger.merge import merge_netcdf_files
+
+
+

+[docs]
+def main():
+    """Main CLI entrypoint"""
+
+    parser = ArgumentParser(
+        prog='merge',
+        description='Simple CLI wrapper around the granule merge module.')
+    parser.add_argument(
+        'data_dir',
+        help='The directory containing the files to be merged.')
+    parser.add_argument(
+        'output_path',
+        help='The output filename for the merged output.')
+    parser.add_argument(
+        '-v', '--verbose',
+        help='Enable verbose output to stdout; useful for debugging',
+        action='store_true'
+    )
+    parser.add_argument(
+        '-c', '--cores',
+        help='Override the number of cores to be utilized during multitreaded/multiprocess operations. Defaults to cpu_count',
+        type=int,
+        default=None
+    )
+
+    args = parser.parse_args()
+
+    if args.verbose:
+        logging.basicConfig(level=logging.DEBUG)
+
+    input_files = list(Path(args.data_dir).resolve().iterdir())
+    granule_urls = []
+    merge_netcdf_files(input_files, args.output_path, granule_urls, process_count=args.cores)

+
+
+
+if __name__ == '__main__':
+    main()
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/merge_worker.html b/0.10.0a1+113bd04/_modules/merger/merge_worker.html new file mode 100644 index 00000000..8fcd3a1b --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/merge_worker.html @@ -0,0 +1,459 @@ + + + + + + merger.merge_worker — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +

Source code for merger.merge_worker

+"""Preprocessing methods and the utilities to automagically run them in single-thread/multiprocess modes"""
+import logging
+import math
+import queue
+import time
+import os
+import shutil
+import multiprocessing
+from multiprocessing.shared_memory import SharedMemory
+from pathlib import Path
+import netCDF4 as nc
+import numpy as np
+
+from podaac.merger.path_utils import resolve_dim, resolve_group
+
+
+

+[docs]
+def shared_memory_size() -> int:
+    """
+    try to get the shared memory space size by reading the /dev/shm on linux machines
+    """
+    try:
+        stat = shutil.disk_usage("/dev/shm")
+        return stat.total
+    except FileNotFoundError:
+        # Get memory size via env or default to 60 MB
+        default_memory_size = os.getenv("SHARED_MEMORY_SIZE", "60000000")
+        return int(default_memory_size)

+
+
+
+

+[docs]
+def max_var_memory(file_list: list[Path], var_info: dict, max_dims) -> int:
+    """Function to get the maximum shared memory that will be used for variables
+
+    Parameters
+    ----------
+    file_list : list
+        List of file paths to be processed
+    var_info : dict
+        Dictionary of variable paths and associated VariableInfo
+    max_dims
+    """
+
+    max_var_mem = 0
+    for file in file_list:
+        with nc.Dataset(file, 'r') as origin_dataset:
+
+            for var_path, var_meta in var_info.items():
+                ds_group, var_name = resolve_group(origin_dataset, var_path)
+                ds_var = ds_group.variables.get(var_name)
+
+                if ds_var is None:
+                    target_shape = tuple(max_dims[f'/{dim}'] for dim in var_meta.dim_order)
+                    var_size = math.prod(target_shape) * var_meta.datatype.itemsize
+                    max_var_mem = max(var_size, max_var_mem)
+                else:
+                    var_size = math.prod(ds_var.shape) * var_meta.datatype.itemsize
+                    max_var_mem = max(var_size, max_var_mem)
+
+    return max_var_mem

+
+
+
+

+[docs]
+def run_merge(merged_dataset: nc.Dataset,
+              file_list: list[Path],
+              var_info: dict,
+              max_dims: dict,
+              process_count: int,
+              logger: logging.Logger):
+    """
+    Automagically run merging in an optimized mode determined by the environment
+
+    Parameters
+    ----------
+    merged_dataset : nc.Dataset
+        Destination dataset of the merge operation
+    file_list : list
+        List of file paths to be processed
+    var_info : dict
+        Dictionary of variable paths and associated VariableInfo
+    max_dims : dict
+        Dictionary of dimension paths and maximum dimensions found during preprocessing
+    process_count : int
+        Number of worker processes to run (expected >= 1)
+    logger
+    """
+
+    if process_count == 1:
+        _run_single_core(merged_dataset, file_list, var_info, max_dims, logger)
+    else:
+        # Merging is bottlenecked at the write process which is single threaded
+        # so spinning up more than 2 processes for read/write won't scale the
+        # optimization
+
+        max_var_mem = max_var_memory(file_list, var_info, max_dims)
+        max_memory_size = round(shared_memory_size() * .95)
+
+        if max_var_mem < max_memory_size:
+            _run_multi_core(merged_dataset, file_list, var_info, max_dims, 2, logger)
+        else:
+            _run_single_core(merged_dataset, file_list, var_info, max_dims, logger)

+
+
+
+def _run_single_core(merged_dataset: nc.Dataset,
+                     file_list: list[Path],
+                     var_info: dict,
+                     max_dims: dict,
+                     logger: logging.Logger):
+    """
+    Run the variable merge in the current thread/single-core mode
+
+    Parameters
+    ----------
+    merged_dataset : nc.Dataset
+        Destination dataset of the merge operation
+    file_list : list
+        List of file paths to be processed
+    var_info : dict
+        Dictionary of variable paths and associated VariableInfo
+    max_dims : dict
+        Dictionary of dimension paths and maximum dimensions found during preprocessing
+    logger
+    """
+
+    logger.info("Running single core ......")
+    for i, file in enumerate(file_list):
+        with nc.Dataset(file, 'r') as origin_dataset:
+            origin_dataset.set_auto_maskandscale(False)
+
+            for var_path, var_meta in var_info.items():
+                ds_group, var_name = resolve_group(origin_dataset, var_path)
+                merged_group = resolve_group(merged_dataset, var_path)
+                ds_var = ds_group.variables.get(var_name)
+
+                merged_var = merged_group[0].variables[var_name]
+
+                if ds_var is None:
+                    fill_value = var_meta.fill_value
+                    target_shape = tuple(max_dims[f'/{dim}'] for dim in var_meta.dim_order)
+                    merged_var[i] = np.full(target_shape, fill_value)
+                    continue
+
+                resized = resize_var(ds_var, var_meta, max_dims)
+                merged_var[i] = resized
+
+
+def _run_multi_core(merged_dataset: nc.Dataset,  # pylint: disable=too-many-locals
+                    file_list: list[Path],
+                    var_info: dict,
+                    max_dims: dict,
+                    process_count: int,
+                    logger: logging.Logger):
+    """
+    Run the variable merge in multi-core mode. This method creates (process_count - 1)
+    read processes which read data from an origin granule, resize it, then queue it
+    for the write process to write to disk. The write process is run in the current
+    thread
+
+    # of write processes (1) + # of read processes (process_count - 1) = process_count
+
+    Parameters
+    ----------
+    merged_dataset : nc.Dataset
+        Destination dataset of the merge operation
+    file_list : list
+        List of file paths to be processed
+    var_info : dict
+        Dictionary of variable paths and associated VariableInfo
+    max_dims : dict
+        Dictionary of dimension paths and maximum dimensions found during preprocessing
+    process_count : int
+        Number of worker processes to run (expected >= 2)
+    logger
+    """
+
+    logger.info("Running multicore ......")
+    total_variables = len(file_list) * len(var_info)
+    logger.info(f"total variables {total_variables}")
+
+    # Ensure SharedMemory doesn't get cleaned up before being processed
+    context = multiprocessing.get_context('forkserver')
+
+    with context.Manager() as manager:
+        in_queue = manager.Queue(len(file_list))
+        out_queue = manager.Queue((process_count - 1) * len(var_info))  # Store (process_count - 1) granules in buffer
+        memory_limit = manager.Value('i', 0)
+        lock = manager.Lock()
+
+        logger.info(file_list)
+        for i, file in enumerate(file_list):
+            in_queue.put((i, file))
+
+        processes = []
+
+        logger.info("creating read processes")
+        for _ in range(process_count - 1):
+            process = context.Process(target=_run_worker, args=(in_queue, out_queue, max_dims, var_info, memory_limit, lock))
+            processes.append(process)
+            process.start()
+
+        processed_variables = 0
+
+        logger.info("Start processing variables in main process")
+        while processed_variables < total_variables:
+            try:
+                i, var_path, shape, memory_name = out_queue.get_nowait()
+            except queue.Empty:
+                _check_exit(processes)
+                continue
+
+            merged_var = merged_dataset[var_path]
+            var_meta = var_info[var_path]
+            shared_memory = SharedMemory(name=memory_name, create=False)
+            resized_arr = np.ndarray(shape, var_meta.datatype, shared_memory.buf)
+
+            merged_var[i] = resized_arr  # The write operation itself
+            shared_memory.unlink()
+            shared_memory.close()
+            with lock:
+                memory_limit.value = memory_limit.value - resized_arr.nbytes
+            processed_variables = processed_variables + 1
+
+        for process in processes:
+            # Ensure that child processes properly exit before manager context
+            # gets GCed. Solves EOFError
+            process.join()
+
+
+def _run_worker(in_queue, out_queue, max_dims, var_info, memory_limit, lock):
+    """
+    A method to be executed in a separate process which reads variables from a
+    granule, performs resizing, and queues the processed data up for the writer
+    process.
+
+    Parameters
+    ----------
+    in_queue : Queue
+        Input queue of tuples of subset indexes and granule file paths respectively
+    out_queue : Queue
+        Output queue of tuples of subset indexes, variable path, variable shape, and shared memory name
+    max_dims : dict
+        Dictionary of dimension paths and maximum dimensions found during preprocessing
+    var_info : dict
+        Dictionary of variable paths and associated VariableInfo
+    """
+
+    # want to use max 95% of the memory size of disk
+    max_memory_size = round(shared_memory_size() * .95)
+
+    while not in_queue.empty():
+
+        try:
+            i, file = in_queue.get_nowait()
+        except queue.Empty:
+            break
+
+        with nc.Dataset(file, 'r') as origin_dataset:
+            origin_dataset.set_auto_maskandscale(False)
+
+            for var_path, var_meta in var_info.items():
+
+                ds_group, var_name = resolve_group(origin_dataset, var_path)
+                ds_var = ds_group.variables.get(var_name)
+
+                if ds_var is None:
+                    fill_value = var_meta.fill_value
+                    target_shape = tuple(max_dims[f'/{dim}'] for dim in var_meta.dim_order)
+                    resized_arr = np.full(target_shape, fill_value)
+                else:
+                    resized_arr = resize_var(ds_var, var_meta, max_dims)
+
+                if resized_arr.nbytes > max_memory_size:
+                    raise RuntimeError(f'Merging failed - MAX MEMORY REACHED: {resized_arr.nbytes}')
+
+                # Limit to how much memory we allocate to max memory size
+                while (memory_limit.value + resized_arr.nbytes) > max_memory_size > resized_arr.nbytes:
+                    time.sleep(.5)
+
+                # Copy resized array to shared memory
+                shared_mem = SharedMemory(create=True, size=resized_arr.nbytes)
+                shared_arr = np.ndarray(resized_arr.shape, resized_arr.dtype, buffer=shared_mem.buf)
+                np.copyto(shared_arr, resized_arr)
+                with lock:
+                    memory_limit.value = memory_limit.value + resized_arr.nbytes
+
+                out_queue.put((i, var_path, shared_arr.shape, shared_mem.name))
+                shared_mem.close()
+
+
+def _check_exit(processes: list):
+    """
+    Ensure that all processes have exited without error by checking their exitcode
+    if they're no longer running. Processes that have exited properly are removed
+    from the list
+
+    Parameters
+    ----------
+    processes : list
+        List of processes to check
+    """
+
+    for process in processes.copy():
+        if not process.is_alive():
+            if process.exitcode == 0:
+                processes.remove(process)
+            else:
+                raise RuntimeError(f'Merging failed - exit code: {process.exitcode}')
+
+
+

+[docs]
+def resize_var(var: nc.Variable, var_info, max_dims: dict) -> np.ndarray:
+    """
+    Resizes a variable's data to the maximum dimensions found in preprocessing.
+    This method will never downscale a variable and only performs bottom and
+    left padding as utilized in the original Java implementation
+
+    Parameters
+    ----------
+    var : nc.Variable
+        variable to be resized
+    var_info
+        contains a group path to this variable
+    max_dims : dict
+        dictionary of maximum dimensions found during preprocessing
+
+    Returns
+    -------
+    np.ndarray
+        An ndarray containing the resized data
+    """
+    # special case for 0d variables
+    if var.ndim == 0:
+        return var[:]
+
+    # generate an ordered array of new widths
+    dims = [resolve_dim(max_dims, var_info.group_path, dim.name) - dim.size for dim in var.get_dims()]
+    widths = [[0, dim] for dim in dims]
+
+    # Legacy merger doesn't explicitly define this behavior, but its resizer
+    # fills its resized arrays with 0s upon initialization. Sources:
+    # https://github.com/Unidata/netcdf-java/blob/87f37eb82b6f862f71e0d5767470500b27af5d1e/cdm-core/src/main/java/ucar/ma2/Array.java#L52
+    fill_value = 0 if var_info.fill_value is None else var_info.fill_value
+
+    resized = np.pad(var, widths, mode='constant', constant_values=fill_value)
+    return resized

+
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/path_utils.html b/0.10.0a1+113bd04/_modules/merger/path_utils.html new file mode 100644 index 00000000..8122ddb0 --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/path_utils.html @@ -0,0 +1,199 @@ + + + + + + merger.path_utils — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +

Source code for merger.path_utils

+"""
+Utilities used throughout the merging implementation to simplify group path resolution
+and generation
+"""
+import netCDF4 as nc
+
+
+

+[docs]
+def get_group_path(group: nc.Group, resource: str) -> str:
+    """
+    Generates a Unix-like path from a group and resource to be accessed
+
+    Parameters
+    ----------
+        group: nc.Group
+            NetCDF4 group that contains the resource
+        resource: str
+            name of the resource being accessed
+
+    Returns
+    -------
+        str
+            Unix-like path to the resource
+    """
+
+    if group.path == '/':
+        return '/' + resource
+
+    return group.path + '/' + resource

+
+
+
+

+[docs]
+def resolve_group(dataset: nc.Dataset, path: str):
+    """
+    Resolves a group path into two components: the group and the resource's name
+
+    Parameters
+    ----------
+        dataset: nc.Dataset
+            NetCDF4 Dataset used as the root for all groups
+        path: str
+            the path to the resource
+
+    Returns
+    -------
+        tuple
+            a tuple of the resolved group and the final path component str respectively
+    """
+
+    components = path.rsplit('/', 1)
+    group = dataset
+
+    if len(components[0]) > 0:
+        group = dataset[components[0]]
+
+    return group, components[1]

+
+
+
+

+[docs]
+def resolve_dim(dims: dict, group_path: str, dim_name: str):
+    """
+    Attempt to resolve dim name starting from top-most group going down to the root group
+
+    Parameters
+    ----------
+        dims: dict
+            Dictionary of dimensions to be traversed
+        group_path: str
+            the group path from which to start resolving the specific dimension
+        dim_name: str
+            the name of the dim to be resolved
+
+    Returns
+    -------
+        int
+            the size of the dimension requested
+    """
+    group_tree = group_path.split('/')
+
+    for i in range(len(group_tree), 0, -1):
+        path = '/'.join(group_tree[:i]) + '/' + dim_name
+
+        if path in dims:
+            return dims[path]
+
+    # Attempt to find dim in root node
+    return dims[dim_name]

+
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/preprocess_worker.html b/0.10.0a1+113bd04/_modules/merger/preprocess_worker.html new file mode 100644 index 00000000..55f05cb2 --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/preprocess_worker.html @@ -0,0 +1,584 @@ + + + + + + merger.preprocess_worker — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +

Source code for merger.preprocess_worker

+"""Preprocessing methods and the utilities to automagically run them in single-thread/multiprocess modes"""
+from pathlib import Path
+import json
+import queue
+from copy import deepcopy
+from datetime import datetime, timezone
+from multiprocessing import Manager, Process, Queue
+
+import importlib_metadata
+import netCDF4 as nc
+import numpy as np
+
+from podaac.merger.path_utils import get_group_path
+from podaac.merger.variable_info import VariableInfo
+
+
+

+[docs]
+def run_preprocess(file_list: list[Path], process_count: int, granule_urls: str) -> dict:
+    """
+    Automagically run preprocessing in an optimized mode determined by the environment
+
+    Parameters
+    ----------
+    file_list : list
+        List of file paths to be processed
+    process_count : int
+        Number of worker processes to run (expected >= 1)
+    granule_urls
+    """
+
+    if process_count == 1:
+        return _run_single_core(file_list, granule_urls)
+
+    return _run_multi_core(file_list, process_count, granule_urls)

+
+
+
+

+[docs]
+def merge_max_dims(merged_max_dims, subset_max_dims):
+    """
+    Perform aggregation of max_dims. Intended for use in multithreaded
+    mode only
+
+    Parameters
+    ----------
+    merged_max_dims : dict
+        Dictionary of the aggregated max_dims
+    subset_max_dims : dict
+        Dictionary of max_dims from one of the worker processes
+    """
+
+    for dim_name, subset_dim_size in subset_max_dims.items():
+        if dim_name not in merged_max_dims or subset_dim_size > merged_max_dims[dim_name]:
+            merged_max_dims[dim_name] = subset_dim_size

+
+
+
+

+[docs]
+def merge_metadata(merged_metadata: dict, subset_metadata: dict) -> None:
+    """
+    Perform aggregation of metadata. Intended for use in multithreaded
+    mode only
+
+    Parameters
+    ----------
+    merged_metadata : dict
+        Dictionary of the aggregated metadata
+    subset_max_dims : dict
+        Dictionary of metadata from one of the worker processes
+    """
+
+    for var_path, subset_attrs in subset_metadata.items():
+        if var_path not in merged_metadata:
+            merged_metadata[var_path] = {}
+
+        merged_attrs = merged_metadata[var_path]
+        for attr_name, subset_attr in subset_attrs.items():
+            if attr_name not in merged_attrs:
+                merged_attrs[attr_name] = subset_attr
+            elif not attr_eq(merged_attrs[attr_name], subset_attr):
+                merged_attrs[attr_name] = False  # mark as inconsistent

+
+
+
+

+[docs]
+def construct_history(input_files: list[Path], granule_urls: str) -> dict:
+    """
+    Construct history JSON entry for this concatenation operation
+    https://wiki.earthdata.nasa.gov/display/TRT/In-File+Provenance+Metadata+-+TRT-42
+
+    Parameters
+    ----------
+    input_files : list
+        List of input files
+    granule_urls : str
+
+    Returns
+    -------
+    dict
+        History JSON constructed for this concat operation
+    """
+
+    history_json = {
+        "date_time": datetime.now(tz=timezone.utc).isoformat(),
+        "derived_from": granule_urls,
+        "program": 'concise',
+        "version": importlib_metadata.distribution('podaac-concise').version,
+        "parameters": f'input_files={input_files}',
+        "program_ref": "https://cmr.earthdata.nasa.gov:443/search/concepts/S2153799015-POCLOUD",
+        "$schema": "https://harmony.earthdata.nasa.gov/schemas/history/0.1.0/history-v0.1.0.json"
+    }
+    return history_json

+
+
+
+

+[docs]
+def retrieve_history(dataset):
+    """
+    Retrieve history_json field from NetCDF dataset, if it exists
+
+    Parameters
+    ----------
+    dataset : netCDF4.Dataset
+        NetCDF Dataset representing a single granule
+
+    Returns
+    -------
+    dict
+        history_json field
+    """
+    if 'history_json' not in dataset.ncattrs():
+        return []
+    history_json = dataset.getncattr('history_json')
+    return json.loads(history_json)

+
+
+
+def _run_single_core(file_list: list[Path], granule_urls: str) -> dict:
+    """
+    Run the granule preprocessing in the current thread/single-core mode
+
+    Parameters
+    ----------
+    file_list : list
+        List of file paths to be processed
+    granule_urls
+
+    Returns
+    -------
+    dict
+        A dictionary containing the output from the preprocessing process
+    """
+    group_list = []
+    var_info = {}
+    max_dims = {}
+    var_metadata = {}
+    group_metadata = {}
+    history_json = []
+
+    for file in file_list:
+        with nc.Dataset(file, 'r') as dataset:
+            dataset.set_auto_maskandscale(False)
+            process_groups(dataset, group_list, max_dims, group_metadata, var_metadata, var_info)
+            history_json.extend(retrieve_history(dataset))
+
+    group_list.sort()  # Ensure insertion order doesn't matter between granules
+
+    history_json.append(construct_history(file_list, granule_urls))
+    group_metadata[group_list[0]]['history_json'] = json.dumps(
+        history_json,
+        default=str
+    )
+
+    return {
+        'group_list': group_list,
+        'max_dims': max_dims,
+        'var_info': var_info,
+        'var_metadata': var_metadata,
+        'group_metadata': group_metadata
+    }
+
+
+def _run_multi_core(file_list: list[Path],
+                    process_count: int,
+                    granule_urls: str) -> dict:
+    """
+    Run the granule preprocessing in multi-core mode. This method spins up
+    the number of processes defined by process_count which process granules
+    in the input queue until empty. When all processes are done, the method
+    merges all the preprocessing results together and returns the final
+    results
+
+    Parameters
+    ----------
+    file_list : list
+        List of file paths to be processed
+    process_count : int
+        Number of worker processes to run (expected >= 2)
+    granule_urls
+
+    Returns
+    -------
+    dict
+        A dictionary containing the output from the preprocessing process
+    """
+    with Manager() as manager:
+        in_queue = manager.Queue(len(file_list))
+        results = manager.list()
+
+        for file in file_list:
+            in_queue.put(file)
+
+        processes = []
+        for _ in range(process_count):
+            process = Process(target=_run_worker, args=(in_queue, results))
+            processes.append(process)
+            process.start()
+
+        # Explicitly check for all processes to successfully exit
+        # before attempting to merge results
+        for process in processes:
+            process.join()
+
+            if process.exitcode != 0:
+                raise RuntimeError(f'Preprocessing failed - exit code: {process.exitcode}')
+
+        results = deepcopy(results)  # ensure GC can cleanup multiprocessing
+
+    # -- Merge final results --
+    group_list = None
+    var_info = None
+    max_dims = {}
+    var_metadata = {}
+    group_metadata = {}
+    history_json = []
+
+    for result in results:
+        # The following data should be consistent between granules and
+        # require no special treatment to merge. Sanity checks added
+        # just for verification.
+        if group_list is None:
+            group_list = result['group_list']
+        elif group_list != result['group_list']:
+            raise RuntimeError('Groups are inconsistent between granules')
+
+        if var_info is None:
+            var_info = result['var_info']
+        elif var_info != result['var_info']:
+            intersecting_vars = set(var_info).intersection(result['var_info'])
+            if any(var_info[var] != result['var_info'][var] for var in intersecting_vars):
+                raise RuntimeError('Variable schemas are inconsistent between granules')
+            var_info.update(result['var_info'])
+
+        # The following data requires accumulation methods
+        merge_max_dims(max_dims, result['max_dims'])
+        merge_metadata(var_metadata, result['var_metadata'])
+        merge_metadata(group_metadata, result['group_metadata'])
+
+        # Merge history_json entries from input files
+        history_json.extend(result['history_json'])
+
+    history_json.append(construct_history(file_list, granule_urls))
+    group_metadata[group_list[0]]['history_json'] = json.dumps(
+        history_json,
+        default=str
+    )
+
+    return {
+        'group_list': group_list,
+        'max_dims': max_dims,
+        'var_info': var_info,
+        'var_metadata': var_metadata,
+        'group_metadata': group_metadata
+    }
+
+
+def _run_worker(in_queue: Queue, results: list[dict]) -> None:
+    """
+    A method to be executed in a separate process which runs preprocessing on granules
+    from the input queue and stores the results internally. When the queue is empty
+    (processing is complete), the local results are transferred to the external results
+    array to be merged by the main process. If the process never processed any granules
+    which is possible if the input queue is underfilled, the process just exits without
+    appending to the array
+
+    Parameters
+    ----------
+    in_queue : Queue
+        Input queue of tuples of subset indexes and granule file paths respectively
+    results : list
+        An array which stores the results of preprocessing from all workers
+    """
+    empty = True
+    group_list = []
+    max_dims = {}
+    var_info = {}
+    var_metadata = {}
+    group_metadata = {}
+    history_json = []
+
+    while not in_queue.empty():
+        try:
+            file = in_queue.get_nowait()
+        except queue.Empty:
+            break
+
+        empty = False
+        with nc.Dataset(file, 'r') as dataset:
+            dataset.set_auto_maskandscale(False)
+            process_groups(dataset, group_list, max_dims, group_metadata, var_metadata, var_info)
+            history_json.extend(retrieve_history(dataset))
+
+    group_list.sort()  # Ensure insertion order doesn't matter between granules
+
+    if not empty:
+        results.append({
+            'group_list': group_list,
+            'max_dims': max_dims,
+            'var_info': var_info,
+            'var_metadata': var_metadata,
+            'group_metadata': group_metadata,
+            'history_json': history_json
+        })
+
+
+

+[docs]
+def process_groups(parent_group: nc.Dataset | nc.Group,
+                   group_list: list,
+                   max_dims: dict,
+                   group_metadata: dict,
+                   var_metadata: dict,
+                   var_info: dict):
+    """
+    Perform preprocessing of a group and recursively process each child group
+
+    Parameters
+    ----------
+    parent_group: nc.Dataset, nc.Group
+        current group to be processed
+    group_list: list
+        list of group paths
+    max_dims: dict
+        dictionary which stores dimension paths and associated dimension sizes
+    group_metadata: dict
+        dictionary which stores group paths and their associated attributes
+    var_metadata: dict
+        dictionary of dictionaries which stores variable paths and their associated attributes
+    var_info: dict
+        dictionary of variable paths and associated VariableInfo data
+    """
+
+    if parent_group.path not in group_metadata:
+        group_metadata[parent_group.path] = {}
+
+    if parent_group.path not in group_list:
+        group_list.append(parent_group.path)
+
+    get_max_dims(parent_group, max_dims)
+    get_metadata(parent_group, group_metadata[parent_group.path])
+    get_variable_data(parent_group, var_info, var_metadata)
+
+    for child_group in parent_group.groups.values():
+        process_groups(child_group, group_list, max_dims, group_metadata, var_metadata, var_info)

+
+
+
+

+[docs]
+def get_max_dims(group: nc.Dataset | nc.Group, max_dims: dict) -> None:
+    """
+    Aggregates dimensions from each group and creates a dictionary
+    of the largest dimension sizes for each group
+
+    Parameters
+    ----------
+    group: nc.Dataset, nc.Group
+        group to process dimensions from
+    max_dims: dict
+        dictionary which stores dimension paths and associated dimension sizes
+    """
+
+    for dim in group.dimensions.values():
+        dim_path = get_group_path(group, dim.name)
+
+        if dim_path not in max_dims or max_dims[dim_path] < dim.size:
+            max_dims[dim_path] = dim.size

+
+
+
+

+[docs]
+def get_metadata(group: nc.Dataset | nc.Group | nc.Variable, metadata: dict) -> None:
+    """
+    Aggregates metadata from various NetCDF4 objects into a dictionary
+
+    Parameters
+    ----------
+    group : nc.Dataset, nc.Group, nc.Variable
+        the NetCDF4 object to aggregate metadata from
+    metadata : dict
+        a dictionary containing the object name and associated metadata
+    """
+
+    for attr_name in group.ncattrs():
+        attr = group.getncattr(attr_name)
+
+        if attr_name not in metadata:
+            metadata[attr_name] = attr
+        elif not attr_eq(metadata[attr_name], attr):
+            metadata[attr_name] = False  # mark as inconsistent

+
+
+
+

+[docs]
+def attr_eq(attr_1, attr_2) -> bool:
+    """
+    Helper function to check if one attribute value is equal to another
+    (no, a simple == was not working)
+
+    Parameters
+    ----------
+    attr_1 : obj
+        An attribute value
+    attr_2 : obj
+        An attribute value
+    """
+
+    if isinstance(attr_1, np.ndarray) or isinstance(attr_2, np.ndarray):
+        if not np.array_equal(attr_1, attr_2):
+            return False
+    elif type(attr_1) != type(attr_2) or attr_1 != attr_2:  # pylint: disable=unidiomatic-typecheck    # noqa: E721
+        return False
+
+    return True

+
+
+
+

+[docs]
+def get_variable_data(group: nc.Dataset | nc.Group, var_info: dict, var_metadata: dict) -> None:
+    """
+    Aggregate variable metadata and attributes. Primarily utilized in process_groups
+
+    Parameters
+    ----------
+    group : nc.Dataset, nc.Group
+        group associated with this variable
+    var_info : dict
+        dictionary of variable paths and associated VariableInfo
+    var_metadata : dict
+        dictionary of variable paths and associated attribute dictionary
+    """
+
+    for var in group.variables.values():
+
+        # Generate VariableInfo map
+        info = VariableInfo(var)
+        var_path = get_group_path(group, var.name)
+
+        if var_path not in var_info:
+            var_info[var_path] = info
+        elif var_info[var_path] != info:
+            # Check to ensure datasets are consistent
+            raise RuntimeError('Inconsistent variable schemas')
+
+        # Generate variable attribute map
+        if var_path not in var_metadata:
+            var_metadata[var_path] = {}
+
+        get_metadata(var, var_metadata[var_path])

+
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_modules/merger/variable_info.html b/0.10.0a1+113bd04/_modules/merger/variable_info.html new file mode 100644 index 00000000..183474bc --- /dev/null +++ b/0.10.0a1+113bd04/_modules/merger/variable_info.html @@ -0,0 +1,167 @@ + + + + + + merger.variable_info — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +

Source code for merger.variable_info

+"""Wrapper used to manage variable metadata"""
+import numpy as np
+
+
+

+[docs]
+class VariableInfo:
+    """
+    Lightweight wrapper class utilized in granule preprocessing to simply comparisons between
+    different variables from different granule sets
+
+    Attributes
+    ----------
+    name: str
+        name of the variable
+    dim_order: list
+        list of dimension names in order
+    datatype: numpy.dtype
+        the numpy datatype for the data held in the variable
+    group_path: str
+        Unix-like group path to the variable
+    fill_value: object
+        Value used to fill missing/empty values in variable's data
+    """
+
+    def __init__(self, var):
+        self.name = var.name
+        self.dim_order = var.dimensions
+        self.datatype = var.datatype
+        self.group_path = var.group().path
+
+        if hasattr(var, '_FillValue'):
+            self.fill_value = var._FillValue
+        elif hasattr(var, 'missing_value'):
+            self.fill_value = var.missing_value
+        else:
+            self.fill_value = None
+
+        self.init = True  # Finalize object values
+
+    def __setattr__(self, name, value):
+        if hasattr(self, 'init') and self.init:
+            raise AttributeError('VariableInfo is immutable')
+
+        self.__dict__[name] = value
+
+    def __str__(self):
+        return f"name:{self.name} dim_order:{self.dim_order} fill_value:{self.fill_value} datatype:{self.datatype} group_path:{self.group_path}"
+
+    def __eq__(self, other):
+        return (
+            self.dim_order == other.dim_order and
+            self.datatype == other.datatype and
+            self.name == other.name and
+            (
+                self.fill_value == other.fill_value or
+                np.array_equal(self.fill_value, other.fill_value, equal_nan=True)
+            ) and
+            self.group_path == other.group_path
+        )

+
+
+ +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/_sources/index.rst.txt b/0.10.0a1+113bd04/_sources/index.rst.txt new file mode 100644 index 00000000..835b8021 --- /dev/null +++ b/0.10.0a1+113bd04/_sources/index.rst.txt @@ -0,0 +1,40 @@ +Welcome to CONCISE (CONCatenatIon SErvice) +========================================== + +CONCISE is a Python package for merging dataset granules together. The package is a port of the +merging functionality from the l2ss-subset-worker Java project primarily utilizing the +netcdf4-python package and *a lot* of multi-core optimizations. The primary merging logic was +derrived from the :code:`gov.nasa.jpl.podaac.subsetter.netcdf.NetCDFSubsetter` class. The +package includes an integration with the Harmony service via :code:`harmony-service-lib`. + +The integration with upstream Harmony itself is currently incomplete. A fork of Harmony was +created to test the integration in the meanwhile. In order to workaround Harmony's current +lack of support for many-to-one services and OCG's Coverages API specification, a custom MIME +was defined as part of the :code:`output_formats` for the service in :code:`services.yml`. A +snippet of this workaround follows. + +.. code-block:: yaml + + capabilities: + output_formats: + - application/x-netcdf4.merge + +One possible route towards integrating CONCISE with Harmony and maintaining OCG API compliance +is to extend the NetCDF4 MIME with additional metadata. For example: +:code:`application/x-netcdf4;merged=true`. Metadata at the end of MIMEs is seen as a valid part +of the MIME specification according to +`RFC 6838 `_. + +.. toctree:: + :maxdepth: 3 + :titlesonly: + :caption: Contents: + + modules + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/0.10.0a1+113bd04/_sources/merger.harmony.rst.txt b/0.10.0a1+113bd04/_sources/merger.harmony.rst.txt new file mode 100644 index 00000000..95bb0442 --- /dev/null +++ b/0.10.0a1+113bd04/_sources/merger.harmony.rst.txt @@ -0,0 +1,45 @@ +merger.harmony package +====================== + +Submodules +---------- + +merger.harmony.cli module +------------------------- + +.. automodule:: merger.harmony.cli + :members: + :undoc-members: + :show-inheritance: + +merger.harmony.download\_worker module +-------------------------------------- + +.. automodule:: merger.harmony.download_worker + :members: + :undoc-members: + :show-inheritance: + +merger.harmony.service module +----------------------------- + +.. automodule:: merger.harmony.service + :members: + :undoc-members: + :show-inheritance: + +merger.harmony.util module +-------------------------- + +.. automodule:: merger.harmony.util + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: merger.harmony + :members: + :undoc-members: + :show-inheritance: diff --git a/0.10.0a1+113bd04/_sources/merger.rst.txt b/0.10.0a1+113bd04/_sources/merger.rst.txt new file mode 100644 index 00000000..f1d3b67c --- /dev/null +++ b/0.10.0a1+113bd04/_sources/merger.rst.txt @@ -0,0 +1,69 @@ +merger package +============== + +Subpackages +----------- + +.. toctree:: + :maxdepth: 4 + + merger.harmony + +Submodules +---------- + +merger.merge module +------------------- + +.. automodule:: merger.merge + :members: + :undoc-members: + :show-inheritance: + +merger.merge\_cli module +------------------------ + +.. automodule:: merger.merge_cli + :members: + :undoc-members: + :show-inheritance: + +merger.merge\_worker module +--------------------------- + +.. automodule:: merger.merge_worker + :members: + :undoc-members: + :show-inheritance: + +merger.path\_utils module +------------------------- + +.. automodule:: merger.path_utils + :members: + :undoc-members: + :show-inheritance: + +merger.preprocess\_worker module +-------------------------------- + +.. automodule:: merger.preprocess_worker + :members: + :undoc-members: + :show-inheritance: + +merger.variable\_info module +---------------------------- + +.. automodule:: merger.variable_info + :members: + :undoc-members: + :show-inheritance: + +Module contents +--------------- + +.. automodule:: merger + :members: + :undoc-members: + :show-inheritance: diff --git a/0.10.0a1+113bd04/_sources/modules.rst.txt b/0.10.0a1+113bd04/_sources/modules.rst.txt new file mode 100644 index 00000000..3d41d16a --- /dev/null +++ b/0.10.0a1+113bd04/_sources/modules.rst.txt @@ -0,0 +1,7 @@ +podaac +====== + +.. toctree:: + :maxdepth: 4 + + merger diff --git a/0.10.0a1+113bd04/_static/_sphinx_javascript_frameworks_compat.js b/0.10.0a1+113bd04/_static/_sphinx_javascript_frameworks_compat.js new file mode 100644 index 00000000..81415803 --- /dev/null +++ b/0.10.0a1+113bd04/_static/_sphinx_javascript_frameworks_compat.js @@ -0,0 +1,123 @@ +/* Compatability shim for jQuery and underscores.js. + * + * Copyright Sphinx contributors + * Released under the two clause BSD licence + */ + +/** + * small helper function to urldecode strings + * + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL + */ +jQuery.urldecode = function(x) { + if (!x) { + return x + } + return decodeURIComponent(x.replace(/\+/g, ' ')); +}; + +/** + * small helper function to urlencode strings + */ +jQuery.urlencode = encodeURIComponent; + +/** + * This function returns the parsed url parameters of the + * current request. Multiple values per key are supported, + * it will always return arrays of strings for the value parts. + */ +jQuery.getQueryParameters = function(s) { + if (typeof s === 'undefined') + s = document.location.search; + var parts = s.substr(s.indexOf('?') + 1).split('&'); + var result = {}; + for (var i = 0; i < parts.length; i++) { + var tmp = parts[i].split('=', 2); + var key = jQuery.urldecode(tmp[0]); + var value = jQuery.urldecode(tmp[1]); + if (key in result) + result[key].push(value); + else + result[key] = [value]; + } + return result; +}; + +/** + * highlight a given string on a jquery object by wrapping it in + * span elements with the given class name. + */ +jQuery.fn.highlightText = function(text, className) { + function highlight(node, addItems) { + if (node.nodeType === 3) { + var val = node.nodeValue; + var pos = val.toLowerCase().indexOf(text); + if (pos >= 0 && + !jQuery(node.parentNode).hasClass(className) && + !jQuery(node.parentNode).hasClass("nohighlight")) { + var span; + var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.className = className; + } + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + node.parentNode.insertBefore(span, node.parentNode.insertBefore( + document.createTextNode(val.substr(pos + text.length)), + node.nextSibling)); + node.nodeValue = val.substr(0, pos); + if (isInSVG) { + var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect"); + var bbox = node.parentElement.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute('class', className); + addItems.push({ + "parent": node.parentNode, + "target": rect}); + } + } + } + else if (!jQuery(node).is("button, select, textarea")) { + jQuery.each(node.childNodes, function() { + highlight(this, addItems); + }); + } + } + var addItems = []; + var result = this.each(function() { + highlight(this, addItems); + }); + for (var i = 0; i < addItems.length; ++i) { + jQuery(addItems[i].parent).before(addItems[i].target); + } + return result; +}; + +/* + * backward compatibility for jQuery.browser + * This will be supported until firefox bug is fixed. + */ +if (!jQuery.browser) { + jQuery.uaMatch = function(ua) { + ua = ua.toLowerCase(); + + var match = /(chrome)[ \/]([\w.]+)/.exec(ua) || + /(webkit)[ \/]([\w.]+)/.exec(ua) || + /(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) || + /(msie) ([\w.]+)/.exec(ua) || + ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) || + []; + + return { + browser: match[ 1 ] || "", + version: match[ 2 ] || "0" + }; + }; + jQuery.browser = {}; + jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true; +} diff --git a/0.10.0a1+113bd04/_static/basic.css 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---------------------------------------------------------------- */ + +table.docutils { + margin-top: 10px; + margin-bottom: 10px; + border: 0; + border-collapse: collapse; +} + +table.align-center { + margin-left: auto; + margin-right: auto; +} + +table.align-default { + margin-left: auto; + margin-right: auto; +} + +table caption span.caption-number { + font-style: italic; +} + +table caption span.caption-text { +} + +table.docutils td, table.docutils th { + padding: 1px 8px 1px 5px; + border-top: 0; + border-left: 0; + border-right: 0; + border-bottom: 1px solid #aaa; +} + +th { + text-align: left; + padding-right: 5px; +} + +table.citation { + border-left: solid 1px gray; + margin-left: 1px; +} + +table.citation td { + border-bottom: none; +} + +th > :first-child, +td > :first-child { + margin-top: 0px; +} + +th > :last-child, +td > :last-child { + margin-bottom: 0px; +} + +/* -- figures --------------------------------------------------------------- */ + +div.figure, figure { + 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// [C]VC[V] is m=1 + var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 + var s_v = "^(" + C + ")?" + v; // vowel in stem + + this.stemWord = function (w) { + var stem; + var suffix; + var firstch; + var origword = w; + + if (w.length < 3) + return w; + + var re; + var re2; + var re3; + var re4; + + firstch = w.substr(0,1); + if (firstch == "y") + w = firstch.toUpperCase() + w.substr(1); + + // Step 1a + re = /^(.+?)(ss|i)es$/; + re2 = /^(.+?)([^s])s$/; + + if (re.test(w)) + w = w.replace(re,"$1$2"); + else if (re2.test(w)) + w = w.replace(re2,"$1$2"); + + // Step 1b + re = /^(.+?)eed$/; + re2 = /^(.+?)(ed|ing)$/; + if (re.test(w)) { + var fp = re.exec(w); + re = new RegExp(mgr0); + if (re.test(fp[1])) { + re = /.$/; + w = w.replace(re,""); + } + } + else if (re2.test(w)) { + var fp = re2.exec(w); + stem = fp[1]; + re2 = new RegExp(s_v); + if (re2.test(stem)) { + w = stem; + re2 = /(at|bl|iz)$/; + re3 = new RegExp("([^aeiouylsz])\\1$"); + re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); 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+ +/** + * Simple result scoring code. + */ +if (typeof Scorer === "undefined") { + var Scorer = { + // Implement the following function to further tweak the score for each result + // The function takes a result array [docname, title, anchor, descr, score, filename] + // and returns the new score. + /* + score: result => { + const [docname, title, anchor, descr, score, filename] = result + return score + }, + */ + + // query matches the full name of an object + objNameMatch: 11, + // or matches in the last dotted part of the object name + objPartialMatch: 6, + // Additive scores depending on the priority of the object + objPrio: { + 0: 15, // used to be importantResults + 1: 5, // used to be objectResults + 2: -5, // used to be unimportantResults + }, + // Used when the priority is not in the mapping. + objPrioDefault: 0, + + // query found in title + title: 15, + partialTitle: 7, + // query found in terms + term: 5, + partialTerm: 2, + }; +} + +const _removeChildren = (element) => { + while (element && element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string + +const _displayItem = (item, searchTerms, highlightTerms) => { + const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; + const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; + const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; + const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + const contentRoot = document.documentElement.dataset.content_root; + + const [docName, title, anchor, descr, score, _filename] = item; + + let listItem = document.createElement("li"); + let requestUrl; + let linkUrl; + if (docBuilder === "dirhtml") { + // dirhtml builder + let dirname = docName + "/"; + if (dirname.match(/\/index\/$/)) + dirname = dirname.substring(0, dirname.length - 6); + else if (dirname === "index/") dirname = ""; + requestUrl = contentRoot + dirname; + linkUrl = requestUrl; + } else { + // normal html builders + requestUrl = contentRoot + docName + docFileSuffix; + linkUrl = docName + docLinkSuffix; + } + let linkEl = listItem.appendChild(document.createElement("a")); + linkEl.href = linkUrl + anchor; + linkEl.dataset.score = score; + linkEl.innerHTML = title; + if (descr) { + listItem.appendChild(document.createElement("span")).innerHTML = + " (" + descr + ")"; + // highlight search terms in the description + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + } + else if (showSearchSummary) + fetch(requestUrl) + .then((responseData) => responseData.text()) + .then((data) => { + if (data) + listItem.appendChild( + Search.makeSearchSummary(data, searchTerms, anchor) + ); + // highlight search terms in the summary + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + }); + Search.output.appendChild(listItem); +}; +const _finishSearch = (resultCount) => { + Search.stopPulse(); + Search.title.innerText = _("Search Results"); + if (!resultCount) + Search.status.innerText = Documentation.gettext( + "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." + ); + else + Search.status.innerText = _( + "Search finished, found ${resultCount} page(s) matching the search query." + ).replace('${resultCount}', resultCount); +}; +const _displayNextItem = ( + results, + resultCount, + searchTerms, + highlightTerms, +) => { + // results left, load the summary and display it + // this is intended to be dynamic (don't sub resultsCount) + if (results.length) { + _displayItem(results.pop(), searchTerms, highlightTerms); + setTimeout( + () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), + 5 + ); + } + // search finished, update title and status message + else _finishSearch(resultCount); +}; +// Helper function used by query() to order search results. +// Each input is an array of [docname, title, anchor, descr, score, filename]. +// Order the results by score (in opposite order of appearance, since the +// `_displayNextItem` function uses pop() to retrieve items) and then alphabetically. +const _orderResultsByScoreThenName = (a, b) => { + const leftScore = a[4]; + const rightScore = b[4]; + if (leftScore === rightScore) { + // same score: sort alphabetically + const leftTitle = a[1].toLowerCase(); + const rightTitle = b[1].toLowerCase(); + if (leftTitle === rightTitle) return 0; + return leftTitle > rightTitle ? -1 : 1; // inverted is intentional + } + return leftScore > rightScore ? 1 : -1; +}; + +/** + * Default splitQuery function. Can be overridden in ``sphinx.search`` with a + * custom function per language. + * + * The regular expression works by splitting the string on consecutive characters + * that are not Unicode letters, numbers, underscores, or emoji characters. + * This is the same as ``\W+`` in Python, preserving the surrogate pair area. + */ +if (typeof splitQuery === "undefined") { + var splitQuery = (query) => query + .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) + .filter(term => term) // remove remaining empty strings +} + +/** + * Search Module + */ +const Search = { + _index: null, + _queued_query: null, + _pulse_status: -1, + + htmlToText: (htmlString, anchor) => { + const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); + for (const removalQuery of [".headerlinks", "script", "style"]) { + htmlElement.querySelectorAll(removalQuery).forEach((el) => { el.remove() }); + } + if (anchor) { + const anchorContent = htmlElement.querySelector(`[role="main"] ${anchor}`); + if (anchorContent) return anchorContent.textContent; + + console.warn( + `Anchored content block not found. Sphinx search tries to obtain it via DOM query '[role=main] ${anchor}'. Check your theme or template.` + ); + } + + // if anchor not specified or not found, fall back to main content + const docContent = htmlElement.querySelector('[role="main"]'); + if (docContent) return docContent.textContent; + + console.warn( + "Content block not found. Sphinx search tries to obtain it via DOM query '[role=main]'. Check your theme or template." + ); + return ""; + }, + + init: () => { + const query = new URLSearchParams(window.location.search).get("q"); + document + .querySelectorAll('input[name="q"]') + .forEach((el) => (el.value = query)); + if (query) Search.performSearch(query); + }, + + loadIndex: (url) => + (document.body.appendChild(document.createElement("script")).src = url), + + setIndex: (index) => { + Search._index = index; + if (Search._queued_query !== null) { + const query = Search._queued_query; + Search._queued_query = null; + Search.query(query); + } + }, + + hasIndex: () => Search._index !== null, + + deferQuery: (query) => (Search._queued_query = query), + + stopPulse: () => (Search._pulse_status = -1), + + startPulse: () => { + if (Search._pulse_status >= 0) return; + + const pulse = () => { + Search._pulse_status = (Search._pulse_status + 1) % 4; + Search.dots.innerText = ".".repeat(Search._pulse_status); + if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); + }; + pulse(); + }, + + /** + * perform a search for something (or wait until index is loaded) + */ + performSearch: (query) => { + // create the required interface elements + const searchText = document.createElement("h2"); + searchText.textContent = _("Searching"); + const searchSummary = document.createElement("p"); + searchSummary.classList.add("search-summary"); + searchSummary.innerText = ""; + const searchList = document.createElement("ul"); + searchList.classList.add("search"); + + const out = document.getElementById("search-results"); + Search.title = out.appendChild(searchText); + Search.dots = Search.title.appendChild(document.createElement("span")); + Search.status = out.appendChild(searchSummary); + Search.output = out.appendChild(searchList); + + const searchProgress = document.getElementById("search-progress"); + // Some themes don't use the search progress node + if (searchProgress) { + searchProgress.innerText = _("Preparing search..."); + } + Search.startPulse(); + + // index already loaded, the browser was quick! + if (Search.hasIndex()) Search.query(query); + else Search.deferQuery(query); + }, + + _parseQuery: (query) => { + // stem the search terms and add them to the correct list + const stemmer = new Stemmer(); + const searchTerms = new Set(); + const excludedTerms = new Set(); + const highlightTerms = new Set(); + const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); + splitQuery(query.trim()).forEach((queryTerm) => { + const queryTermLower = queryTerm.toLowerCase(); + + // maybe skip this "word" + // stopwords array is from language_data.js + if ( + stopwords.indexOf(queryTermLower) !== -1 || + queryTerm.match(/^\d+$/) + ) + return; + + // stem the word + let word = stemmer.stemWord(queryTermLower); + // select the correct list + if (word[0] === "-") excludedTerms.add(word.substr(1)); + else { + searchTerms.add(word); + highlightTerms.add(queryTermLower); + } + }); + + if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js + localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) + } + + // console.debug("SEARCH: searching for:"); + // console.info("required: ", [...searchTerms]); + // console.info("excluded: ", [...excludedTerms]); + + return [query, searchTerms, excludedTerms, highlightTerms, objectTerms]; + }, + + /** + * execute search (requires search index to be loaded) + */ + _performSearch: (query, searchTerms, excludedTerms, highlightTerms, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + + // Collect multiple result groups to be sorted separately and then ordered. + // Each is an array of [docname, title, anchor, descr, score, filename]. + const normalResults = []; + const nonMainIndexResults = []; + + _removeChildren(document.getElementById("search-progress")); + + const queryLower = query.toLowerCase().trim(); + for (const [title, foundTitles] of Object.entries(allTitles)) { + if (title.toLowerCase().trim().includes(queryLower) && (queryLower.length >= title.length/2)) { + for (const [file, id] of foundTitles) { + let score = Math.round(100 * queryLower.length / title.length) + normalResults.push([ + docNames[file], + titles[file] !== title ? `${titles[file]} > ${title}` : title, + id !== null ? "#" + id : "", + null, + score, + filenames[file], + ]); + } + } + } + + // search for explicit entries in index directives + for (const [entry, foundEntries] of Object.entries(indexEntries)) { + if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { + for (const [file, id, isMain] of foundEntries) { + const score = Math.round(100 * queryLower.length / entry.length); + const result = [ + docNames[file], + titles[file], + id ? "#" + id : "", + null, + score, + filenames[file], + ]; + if (isMain) { + normalResults.push(result); + } else { + nonMainIndexResults.push(result); + } + } + } + } + + // lookup as object + objectTerms.forEach((term) => + normalResults.push(...Search.performObjectSearch(term, objectTerms)) + ); + + // lookup as search terms in fulltext + normalResults.push(...Search.performTermsSearch(searchTerms, excludedTerms)); + + // let the scorer override scores with a custom scoring function + if (Scorer.score) { + normalResults.forEach((item) => (item[4] = Scorer.score(item))); + nonMainIndexResults.forEach((item) => (item[4] = Scorer.score(item))); + } + + // Sort each group of results by score and then alphabetically by name. + normalResults.sort(_orderResultsByScoreThenName); + nonMainIndexResults.sort(_orderResultsByScoreThenName); + + // Combine the result groups in (reverse) order. + // Non-main index entries are typically arbitrary cross-references, + // so display them after other results. + let results = [...nonMainIndexResults, ...normalResults]; + + // remove duplicate search results + // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept + let seen = new Set(); + results = results.reverse().reduce((acc, result) => { + let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); + if (!seen.has(resultStr)) { + acc.push(result); + seen.add(resultStr); + } + return acc; + }, []); + + return results.reverse(); + }, + + query: (query) => { + const [searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms] = Search._parseQuery(query); + const results = Search._performSearch(searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms); + + // for debugging + //Search.lastresults = results.slice(); // a copy + // console.info("search results:", Search.lastresults); + + // print the results + _displayNextItem(results, results.length, searchTerms, highlightTerms); + }, + + /** + * search for object names + */ + performObjectSearch: (object, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const objects = Search._index.objects; + const objNames = Search._index.objnames; + const titles = Search._index.titles; + + const results = []; + + const objectSearchCallback = (prefix, match) => { + const name = match[4] + const fullname = (prefix ? prefix + "." : "") + name; + const fullnameLower = fullname.toLowerCase(); + if (fullnameLower.indexOf(object) < 0) return; + + let score = 0; + const parts = fullnameLower.split("."); + + // check for different match types: exact matches of full name or + // "last name" (i.e. last dotted part) + if (fullnameLower === object || parts.slice(-1)[0] === object) + score += Scorer.objNameMatch; + else if (parts.slice(-1)[0].indexOf(object) > -1) + score += Scorer.objPartialMatch; // matches in last name + + const objName = objNames[match[1]][2]; + const title = titles[match[0]]; + + // If more than one term searched for, we require other words to be + // found in the name/title/description + const otherTerms = new Set(objectTerms); + otherTerms.delete(object); + if (otherTerms.size > 0) { + const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); + if ( + [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) + ) + return; + } + + let anchor = match[3]; + if (anchor === "") anchor = fullname; + else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; + + const descr = objName + _(", in ") + title; + + // add custom score for some objects according to scorer + if (Scorer.objPrio.hasOwnProperty(match[2])) + score += Scorer.objPrio[match[2]]; + else score += Scorer.objPrioDefault; + + results.push([ + docNames[match[0]], + fullname, + "#" + anchor, + descr, + score, + filenames[match[0]], + ]); + }; + Object.keys(objects).forEach((prefix) => + objects[prefix].forEach((array) => + objectSearchCallback(prefix, array) + ) + ); + return results; + }, + + /** + * search for full-text terms in the index + */ + performTermsSearch: (searchTerms, excludedTerms) => { + // prepare search + const terms = Search._index.terms; + const titleTerms = Search._index.titleterms; + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + + const scoreMap = new Map(); + const fileMap = new Map(); + + // perform the search on the required terms + searchTerms.forEach((word) => { + const files = []; + const arr = [ + { files: terms[word], score: Scorer.term }, + { files: titleTerms[word], score: Scorer.title }, + ]; + // add support for partial matches + if (word.length > 2) { + const escapedWord = _escapeRegExp(word); + if (!terms.hasOwnProperty(word)) { + Object.keys(terms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: terms[term], score: Scorer.partialTerm }); + }); + } + if (!titleTerms.hasOwnProperty(word)) { + Object.keys(titleTerms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: titleTerms[term], score: Scorer.partialTitle }); + }); + } + } + + // no match but word was a required one + if (arr.every((record) => record.files === undefined)) return; + + // found search word in contents + arr.forEach((record) => { + if (record.files === undefined) return; + + let recordFiles = record.files; + if (recordFiles.length === undefined) recordFiles = [recordFiles]; + files.push(...recordFiles); + + // set score for the word in each file + recordFiles.forEach((file) => { + if (!scoreMap.has(file)) scoreMap.set(file, {}); + scoreMap.get(file)[word] = record.score; + }); + }); + + // create the mapping + files.forEach((file) => { + if (!fileMap.has(file)) fileMap.set(file, [word]); + else if (fileMap.get(file).indexOf(word) === -1) fileMap.get(file).push(word); + }); + }); + + // now check if the files don't contain excluded terms + const results = []; + for (const [file, wordList] of fileMap) { + // check if all requirements are matched + + // as search terms with length < 3 are discarded + const filteredTermCount = [...searchTerms].filter( + (term) => term.length > 2 + ).length; + if ( + wordList.length !== searchTerms.size && + wordList.length !== filteredTermCount + ) + continue; + + // ensure that none of the excluded terms is in the search result + if ( + [...excludedTerms].some( + (term) => + terms[term] === file || + titleTerms[term] === file || + (terms[term] || []).includes(file) || + (titleTerms[term] || []).includes(file) + ) + ) + break; + + // select one (max) score for the file. + const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); + // add result to the result list + results.push([ + docNames[file], + titles[file], + "", + null, + score, + filenames[file], + ]); + } + return results; + }, + + /** + * helper function to return a node containing the + * search summary for a given text. keywords is a list + * of stemmed words. + */ + makeSearchSummary: (htmlText, keywords, anchor) => { + const text = Search.htmlToText(htmlText, anchor); + if (text === "") return null; + + const textLower = text.toLowerCase(); + const actualStartPosition = [...keywords] + .map((k) => textLower.indexOf(k.toLowerCase())) + .filter((i) => i > -1) + .slice(-1)[0]; + const startWithContext = Math.max(actualStartPosition - 120, 0); + + const top = startWithContext === 0 ? "" : "..."; + const tail = startWithContext + 240 < text.length ? "..." : ""; + + let summary = document.createElement("p"); + summary.classList.add("context"); + summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; + + return summary; + }, +}; + +_ready(Search.init); diff --git a/0.10.0a1+113bd04/_static/sphinx_highlight.js b/0.10.0a1+113bd04/_static/sphinx_highlight.js new file mode 100644 index 00000000..8a96c69a --- /dev/null +++ b/0.10.0a1+113bd04/_static/sphinx_highlight.js @@ -0,0 +1,154 @@ +/* Highlighting utilities for Sphinx HTML documentation. */ +"use strict"; + +const SPHINX_HIGHLIGHT_ENABLED = true + +/** + * highlight a given string on a node by wrapping it in + * span elements with the given class name. + */ +const _highlight = (node, addItems, text, className) => { + if (node.nodeType === Node.TEXT_NODE) { + const val = node.nodeValue; + const parent = node.parentNode; + const pos = val.toLowerCase().indexOf(text); + if ( + pos >= 0 && + !parent.classList.contains(className) && + !parent.classList.contains("nohighlight") + ) { + let span; + + const closestNode = parent.closest("body, svg, foreignObject"); + const isInSVG = closestNode && closestNode.matches("svg"); + if (isInSVG) { + span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); + } else { + span = document.createElement("span"); + span.classList.add(className); + } + + span.appendChild(document.createTextNode(val.substr(pos, text.length))); + const rest = document.createTextNode(val.substr(pos + text.length)); + parent.insertBefore( + span, + parent.insertBefore( + rest, + node.nextSibling + ) + ); + node.nodeValue = val.substr(0, pos); + /* There may be more occurrences of search term in this node. So call this + * function recursively on the remaining fragment. + */ + _highlight(rest, addItems, text, className); + + if (isInSVG) { + const rect = document.createElementNS( + "http://www.w3.org/2000/svg", + "rect" + ); + const bbox = parent.getBBox(); + rect.x.baseVal.value = bbox.x; + rect.y.baseVal.value = bbox.y; + rect.width.baseVal.value = bbox.width; + rect.height.baseVal.value = bbox.height; + rect.setAttribute("class", className); + addItems.push({ parent: parent, target: rect }); + } + } + } else if (node.matches && !node.matches("button, select, textarea")) { + node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); + } +}; +const _highlightText = (thisNode, text, className) => { + let addItems = []; + _highlight(thisNode, addItems, text, className); + addItems.forEach((obj) => + obj.parent.insertAdjacentElement("beforebegin", obj.target) + ); +}; + +/** + * Small JavaScript module for the documentation. + */ +const SphinxHighlight = { + + /** + * highlight the search words provided in localstorage in the text + */ + highlightSearchWords: () => { + if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight + + // get and clear terms from localstorage + const url = new URL(window.location); + const highlight = + localStorage.getItem("sphinx_highlight_terms") + || url.searchParams.get("highlight") + || ""; + localStorage.removeItem("sphinx_highlight_terms") + url.searchParams.delete("highlight"); + window.history.replaceState({}, "", url); + + // get individual terms from highlight string + const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); + if (terms.length === 0) return; // nothing to do + + // There should never be more than one element matching "div.body" + const divBody = document.querySelectorAll("div.body"); + const body = divBody.length ? divBody[0] : document.querySelector("body"); + window.setTimeout(() => { + terms.forEach((term) => _highlightText(body, term, "highlighted")); + }, 10); + + const searchBox = document.getElementById("searchbox"); + if (searchBox === null) return; + searchBox.appendChild( + document + .createRange() + .createContextualFragment( + '

' + + '' + + _("Hide Search Matches") + + "

" + ) + ); + }, + + /** + * helper function to hide the search marks again + */ + hideSearchWords: () => { + document + .querySelectorAll("#searchbox .highlight-link") + .forEach((el) => el.remove()); + document + .querySelectorAll("span.highlighted") + .forEach((el) => el.classList.remove("highlighted")); + localStorage.removeItem("sphinx_highlight_terms") + }, + + initEscapeListener: () => { + // only install a listener if it is really needed + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; + if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { + SphinxHighlight.hideSearchWords(); + event.preventDefault(); + } + }); + }, +}; + +_ready(() => { + /* Do not call highlightSearchWords() when we are on the search page. + * It will highlight words from the *previous* search query. + */ + if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); + SphinxHighlight.initEscapeListener(); +}); diff --git a/0.10.0a1+113bd04/genindex.html b/0.10.0a1+113bd04/genindex.html new file mode 100644 index 00000000..818f9815 --- /dev/null +++ b/0.10.0a1+113bd04/genindex.html @@ -0,0 +1,397 @@ + + + + + + Index — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Index
    • +
  • +
    • +
+
+
+
+
+ + +

Index

+ +
+ A + | C + | D + | F + | G + | I + | M + | N + | P + | R + | S + | V + +
+

A

+ + +
+ +

C

+ + + +
+ +

D

+ + + +
+ +

F

+ + +
+ +

G

+ + + +
+ +

I

+ + + +
+ +

M

+ + + +
+ +

N

+ + +
+ +

P

+ + + +
+ +

R

+ + + +
+ +

S

+ + +
+ +

V

+ + +
+ + + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/index.html b/0.10.0a1+113bd04/index.html new file mode 100644 index 00000000..f31e64da --- /dev/null +++ b/0.10.0a1+113bd04/index.html @@ -0,0 +1,152 @@ + + + + + + + Welcome to CONCISE (CONCatenatIon SErvice) — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

Welcome to CONCISE (CONCatenatIon SErvice)

+

CONCISE is a Python package for merging dataset granules together. The package is a port of the +merging functionality from the l2ss-subset-worker Java project primarily utilizing the +netcdf4-python package and a lot of multi-core optimizations. The primary merging logic was +derrived from the gov.nasa.jpl.podaac.subsetter.netcdf.NetCDFSubsetter class. The +package includes an integration with the Harmony service via harmony-service-lib.

+

The integration with upstream Harmony itself is currently incomplete. A fork of Harmony was +created to test the integration in the meanwhile. In order to workaround Harmony’s current +lack of support for many-to-one services and OCG’s Coverages API specification, a custom MIME +was defined as part of the output_formats for the service in services.yml. A +snippet of this workaround follows.

+
capabilities:
+  output_formats:
+    - application/x-netcdf4.merge
+
+
+

One possible route towards integrating CONCISE with Harmony and maintaining OCG API compliance +is to extend the NetCDF4 MIME with additional metadata. For example: +application/x-netcdf4;merged=true. Metadata at the end of MIMEs is seen as a valid part +of the MIME specification according to +RFC 6838.

+
+

Contents:

+ +
+
+
+

Indices and tables

+ +
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/merger.harmony.html b/0.10.0a1+113bd04/merger.harmony.html new file mode 100644 index 00000000..4ae9777b --- /dev/null +++ b/0.10.0a1+113bd04/merger.harmony.html @@ -0,0 +1,272 @@ + + + + + + + merger.harmony package — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

merger.harmony package

+
+

Submodules

+
+
+

merger.harmony.cli module

+

A Harmony CLI wrapper around Concise

+
+
+merger.harmony.cli.main(config=None)[source]
+

Main Harmony CLI entrypoint

+
+ +
+
+

merger.harmony.download_worker module

+

A utility for downloading multiple granules simultaneously

+
+
+merger.harmony.download_worker.multi_core_download(urls, destination_dir, access_token, cfg, process_count=None)[source]
+

A method which automagically scales downloads to the number of CPU +cores. For further explaination, see documentation on “multi-track +drifting”

+
+
Parameters:
+
    +

  • urls (list) – list of urls to download

    • +

  • destination_dir (str) – output path for downloaded files

    • +

  • access_token (str) – access token as provided in Harmony input

    • +

  • cfg (dict) – Harmony configuration information

    • +

  • process_count (int) – Number of worker processes to run (expected >= 1)

    • +
+
+
Returns:
+

list of downloaded files as pathlib.Path objects

+
+
Return type:
+

list

+
+
+
+ +
+
+

merger.harmony.service module

+

A Harmony service wrapper around the Concise module

+
+
+class merger.harmony.service.ConciseService(message, catalog=None, config=None)[source]
+

Bases: BaseHarmonyAdapter

+

A harmony-service-lib wrapper around the Concise module. This wrapper does +not support Harmony calls that do not have STAC catalogs as support for +this behavior is being depreciated in harmony-service-lib

+
+
+invoke()[source]
+

Primary entrypoint into the service wrapper. Overrides BaseHarmonyAdapter.invoke

+
+ +
+
+process_catalog(catalog: Catalog)[source]
+

Recursively process a catalog and all its children. Adapted from +BaseHarmonyAdapter._process_catalog_recursive to specfifically +support our particular use case for many-to-one

+
+
Parameters:
+

catalog (pystac.Catalog or pystac.Collection) – a catalog/collection to process for merging

+
+
Returns:
+

A new catalog containing the results from the merge

+
+
Return type:
+

pystac.Catalog

+
+
+
+ +
+ +
+
+

merger.harmony.util module

+

Misc utility functions

+
+
+merger.harmony.util.get_bbox(item, current_bbox)[source]
+

Accumulate bboxes from items to generate a bbox which encompasses all items

+
+
Parameters:
+
    +

  • item (pystac.Item) – an item to process

    • +

  • current_bbox (list) – the bbox to accumulate all items to

    • +
+
+
+
+ +
+
+merger.harmony.util.get_datetime(item, datetimes)[source]
+

Accumulate datetimes from items to generate a datetime pair that +encompasses all items

+
+
Parameters:
+
    +

  • item (pystac.Item) – an item to process

    • +

  • datetimes (list) – datetime pair to accumulate to; first element is start_datetime, +second is end_datetime

    • +
+
+
+
+ +
+
+merger.harmony.util.get_granule_url(item, granule_urls, strict=True)[source]
+

Processes an item to find a netcdf4-python compatible asset. If no asset is +found, a RuntimeException is thrown

+
+
Parameters:
+
    +

  • item (pystac.Item) – an item to process

    • +

  • granule_urls (list) – list to append the asset’s url to

    • +
+
+
+
+ +
+
+merger.harmony.util.is_netcdf_asset(asset, strict)[source]
+

Determine if an asset is netcdf4-python compatible. netcdf4-python currently supports +HDF5, NetCDF3, and NetCDF4. Determination is currently done through MIME if strict +mode is enabled. If strict mode is not enabled, determination is done through ‘data’ +role.

+
+
Parameters:
+

asset (pystac.Asset) – an asset to check

+
+
Returns:
+

True if netcdf4-python compatible; False otherwise

+
+
Return type:
+

bool

+
+
+
+ +
+
+

Module contents

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/merger.html b/0.10.0a1+113bd04/merger.html new file mode 100644 index 00000000..1c737b71 --- /dev/null +++ b/0.10.0a1+113bd04/merger.html @@ -0,0 +1,593 @@ + + + + + + + merger package — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

merger package

+
+

Subpackages

+
+ +
+
+
+

Submodules

+
+
+

merger.merge module

+

Main module containing merge implementation

+
+
+merger.merge.clean_metadata(metadata: dict) → None[source]
+

Prepares metadata dictionary for insertion by removing inconsistent entries +and performing escaping of attribute names

+
+
Parameters:
+

metadata (dict) – dictionary of attribute names and their associated data

+
+
+
+ +
+
+merger.merge.init_dataset(merged_dataset: Dataset, groups: list[str], var_info: dict, max_dims: dict, input_files: list[Path]) → None[source]
+

Initialize the dataset using data gathered from preprocessing

+
+
Parameters:
+
    +

  • merged_dataset (nc.Dataset) – the dataset to be initialized

    • +

  • groups (list) – list of group names

    • +

  • var_info (dict) – dictionary of variable names and VariableInfo objects

    • +

  • max_dims (dict) – dictionary of dimension names (including path) and their sizes

    • +

  • input_files (list) – list of file paths to be merged

    • +
+
+
+
+ +
+
+merger.merge.is_file_empty(parent_group: Dataset | Group) → bool[source]
+

Function to test if any variable size in a dataset is zero

+
+ +
+
+merger.merge.merge_netcdf_files(original_input_files: list[~pathlib.Path], output_file: str, granule_urls, logger=<Logger merger.merge (WARNING)>, perf_stats: dict | None = None, process_count: int | None = None)[source]
+

Main entrypoint to merge implementation. Merges n >= 2 granules together as a single +granule. Named in reference to the original Java implementation.

+
+
Parameters:
+
    +

  • original_input_files (list) – list of Paths to NetCDF4 files to merge

    • +

  • output_file (str) – output path for merged product

    • +

  • granule_urls

    • +

  • logger (logger) – logger object

    • +

  • perf_stats (dict) – dictionary used to store performance stats

    • +

  • process_count (int) – number of processes to run (expected >= 1)

    • +
+
+
+
+ +
+
+

merger.merge_cli module

+

A simple CLI wrapper around the main merge function

+
+
+merger.merge_cli.main()[source]
+

Main CLI entrypoint

+
+ +
+
+

merger.merge_worker module

+

Preprocessing methods and the utilities to automagically run them in single-thread/multiprocess modes

+
+
+merger.merge_worker.max_var_memory(file_list: list[Path], var_info: dict, max_dims) → int[source]
+

Function to get the maximum shared memory that will be used for variables

+
+
Parameters:
+
    +

  • file_list (list) – List of file paths to be processed

    • +

  • var_info (dict) – Dictionary of variable paths and associated VariableInfo

    • +

  • max_dims

    • +
+
+
+
+ +
+
+merger.merge_worker.resize_var(var: Variable, var_info, max_dims: dict) → ndarray[source]
+

Resizes a variable’s data to the maximum dimensions found in preprocessing. +This method will never downscale a variable and only performs bottom and +left padding as utilized in the original Java implementation

+
+
Parameters:
+
    +

  • var (nc.Variable) – variable to be resized

    • +

  • var_info – contains a group path to this variable

    • +

  • max_dims (dict) – dictionary of maximum dimensions found during preprocessing

    • +
+
+
Returns:
+

An ndarray containing the resized data

+
+
Return type:
+

np.ndarray

+
+
+
+ +
+
+merger.merge_worker.run_merge(merged_dataset: Dataset, file_list: list[Path], var_info: dict, max_dims: dict, process_count: int, logger: Logger)[source]
+

Automagically run merging in an optimized mode determined by the environment

+
+
Parameters:
+
    +

  • merged_dataset (nc.Dataset) – Destination dataset of the merge operation

    • +

  • file_list (list) – List of file paths to be processed

    • +

  • var_info (dict) – Dictionary of variable paths and associated VariableInfo

    • +

  • max_dims (dict) – Dictionary of dimension paths and maximum dimensions found during preprocessing

    • +

  • process_count (int) – Number of worker processes to run (expected >= 1)

    • +

  • logger

    • +
+
+
+
+ +
+
+merger.merge_worker.shared_memory_size() → int[source]
+

try to get the shared memory space size by reading the /dev/shm on linux machines

+
+ +
+
+

merger.path_utils module

+

Utilities used throughout the merging implementation to simplify group path resolution +and generation

+
+
+merger.path_utils.get_group_path(group: Group, resource: str) → str[source]
+

Generates a Unix-like path from a group and resource to be accessed

+
+
Parameters:
+
    +

  • group (nc.Group) – NetCDF4 group that contains the resource

    • +

  • resource (str) – name of the resource being accessed

    • +
+
+
Returns:
+

Unix-like path to the resource

+
+
Return type:
+

str

+
+
+
+ +
+
+merger.path_utils.resolve_dim(dims: dict, group_path: str, dim_name: str)[source]
+

Attempt to resolve dim name starting from top-most group going down to the root group

+
+
Parameters:
+
    +

  • dims (dict) – Dictionary of dimensions to be traversed

    • +

  • group_path (str) – the group path from which to start resolving the specific dimension

    • +

  • dim_name (str) – the name of the dim to be resolved

    • +
+
+
Returns:
+

the size of the dimension requested

+
+
Return type:
+

int

+
+
+
+ +
+
+merger.path_utils.resolve_group(dataset: Dataset, path: str)[source]
+

Resolves a group path into two components: the group and the resource’s name

+
+
Parameters:
+
    +

  • dataset (nc.Dataset) – NetCDF4 Dataset used as the root for all groups

    • +

  • path (str) – the path to the resource

    • +
+
+
Returns:
+

a tuple of the resolved group and the final path component str respectively

+
+
Return type:
+

tuple

+
+
+
+ +
+
+

merger.preprocess_worker module

+

Preprocessing methods and the utilities to automagically run them in single-thread/multiprocess modes

+
+
+merger.preprocess_worker.attr_eq(attr_1, attr_2) → bool[source]
+

Helper function to check if one attribute value is equal to another +(no, a simple == was not working)

+
+
Parameters:
+
    +

  • attr_1 (obj) – An attribute value

    • +

  • attr_2 (obj) – An attribute value

    • +
+
+
+
+ +
+
+merger.preprocess_worker.construct_history(input_files: list[Path], granule_urls: str) → dict[source]
+

Construct history JSON entry for this concatenation operation +https://wiki.earthdata.nasa.gov/display/TRT/In-File+Provenance+Metadata+-+TRT-42

+
+
Parameters:
+
    +

  • input_files (list) – List of input files

    • +

  • granule_urls (str)

    • +
+
+
Returns:
+

History JSON constructed for this concat operation

+
+
Return type:
+

dict

+
+
+
+ +
+
+merger.preprocess_worker.get_max_dims(group: Dataset | Group, max_dims: dict) → None[source]
+

Aggregates dimensions from each group and creates a dictionary +of the largest dimension sizes for each group

+
+
Parameters:
+
    +

  • group (nc.Dataset, nc.Group) – group to process dimensions from

    • +

  • max_dims (dict) – dictionary which stores dimension paths and associated dimension sizes

    • +
+
+
+
+ +
+
+merger.preprocess_worker.get_metadata(group: Dataset | Group | Variable, metadata: dict) → None[source]
+

Aggregates metadata from various NetCDF4 objects into a dictionary

+
+
Parameters:
+
    +

  • group (nc.Dataset, nc.Group, nc.Variable) – the NetCDF4 object to aggregate metadata from

    • +

  • metadata (dict) – a dictionary containing the object name and associated metadata

    • +
+
+
+
+ +
+
+merger.preprocess_worker.get_variable_data(group: Dataset | Group, var_info: dict, var_metadata: dict) → None[source]
+

Aggregate variable metadata and attributes. Primarily utilized in process_groups

+
+
Parameters:
+
    +

  • group (nc.Dataset, nc.Group) – group associated with this variable

    • +

  • var_info (dict) – dictionary of variable paths and associated VariableInfo

    • +

  • var_metadata (dict) – dictionary of variable paths and associated attribute dictionary

    • +
+
+
+
+ +
+
+merger.preprocess_worker.merge_max_dims(merged_max_dims, subset_max_dims)[source]
+

Perform aggregation of max_dims. Intended for use in multithreaded +mode only

+
+
Parameters:
+
    +

  • merged_max_dims (dict) – Dictionary of the aggregated max_dims

    • +

  • subset_max_dims (dict) – Dictionary of max_dims from one of the worker processes

    • +
+
+
+
+ +
+
+merger.preprocess_worker.merge_metadata(merged_metadata: dict, subset_metadata: dict) → None[source]
+

Perform aggregation of metadata. Intended for use in multithreaded +mode only

+
+
Parameters:
+
    +

  • merged_metadata (dict) – Dictionary of the aggregated metadata

    • +

  • subset_max_dims (dict) – Dictionary of metadata from one of the worker processes

    • +
+
+
+
+ +
+
+merger.preprocess_worker.process_groups(parent_group: Dataset | Group, group_list: list, max_dims: dict, group_metadata: dict, var_metadata: dict, var_info: dict)[source]
+

Perform preprocessing of a group and recursively process each child group

+
+
Parameters:
+
    +

  • parent_group (nc.Dataset, nc.Group) – current group to be processed

    • +

  • group_list (list) – list of group paths

    • +

  • max_dims (dict) – dictionary which stores dimension paths and associated dimension sizes

    • +

  • group_metadata (dict) – dictionary which stores group paths and their associated attributes

    • +

  • var_metadata (dict) – dictionary of dictionaries which stores variable paths and their associated attributes

    • +

  • var_info (dict) – dictionary of variable paths and associated VariableInfo data

    • +
+
+
+
+ +
+
+merger.preprocess_worker.retrieve_history(dataset)[source]
+

Retrieve history_json field from NetCDF dataset, if it exists

+
+
Parameters:
+

dataset (netCDF4.Dataset) – NetCDF Dataset representing a single granule

+
+
Returns:
+

history_json field

+
+
Return type:
+

dict

+
+
+
+ +
+
+merger.preprocess_worker.run_preprocess(file_list: list[Path], process_count: int, granule_urls: str) → dict[source]
+

Automagically run preprocessing in an optimized mode determined by the environment

+
+
Parameters:
+
    +

  • file_list (list) – List of file paths to be processed

    • +

  • process_count (int) – Number of worker processes to run (expected >= 1)

    • +

  • granule_urls

    • +
+
+
+
+ +
+
+

merger.variable_info module

+

Wrapper used to manage variable metadata

+
+
+class merger.variable_info.VariableInfo(var)[source]
+

Bases: object

+

Lightweight wrapper class utilized in granule preprocessing to simply comparisons between +different variables from different granule sets

+
+
+name
+

name of the variable

+
+
Type:
+

str

+
+
+
+ +
+
+dim_order
+

list of dimension names in order

+
+
Type:
+

list

+
+
+
+ +
+
+datatype
+

the numpy datatype for the data held in the variable

+
+
Type:
+

numpy.dtype

+
+
+
+ +
+
+group_path
+

Unix-like group path to the variable

+
+
Type:
+

str

+
+
+
+ +
+
+fill_value
+

Value used to fill missing/empty values in variable’s data

+
+
Type:
+

object

+
+
+
+ +
+ +
+
+

Module contents

+
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/modules.html b/0.10.0a1+113bd04/modules.html new file mode 100644 index 00000000..34367620 --- /dev/null +++ b/0.10.0a1+113bd04/modules.html @@ -0,0 +1,186 @@ + + + + + + + podaac — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+ +
+
+
+
+ +
+

podaac

+
+ +
+
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/objects.inv b/0.10.0a1+113bd04/objects.inv new file mode 100644 index 00000000..f4ca8521 Binary files /dev/null and b/0.10.0a1+113bd04/objects.inv differ diff --git a/0.10.0a1+113bd04/py-modindex.html b/0.10.0a1+113bd04/py-modindex.html new file mode 100644 index 00000000..5c67a7be --- /dev/null +++ b/0.10.0a1+113bd04/py-modindex.html @@ -0,0 +1,180 @@ + + + + + + Python Module Index — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
    • +
  • Python Module Index
    • +
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    • +
+
+
+
+
+ + +

Python Module Index

+ +
+ m +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
 
+ m
+ merger +
    + merger.harmony +
    + merger.harmony.cli +
    + merger.harmony.download_worker +
    + merger.harmony.service +
    + merger.harmony.util +
    + merger.merge +
    + merger.merge_cli +
    + merger.merge_worker +
    + merger.path_utils +
    + merger.preprocess_worker +
    + merger.variable_info +
+ + +
+
+ +
+
+
+
+ + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/search.html b/0.10.0a1+113bd04/search.html new file mode 100644 index 00000000..066d8ecb --- /dev/null +++ b/0.10.0a1+113bd04/search.html @@ -0,0 +1,125 @@ + + + + + + Search — podaac-concise 0.10.0a1+113bd04 documentation + + + + + + + + + + + + + + + + + + + + +
+ + +
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  • Search
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+ + + + + + + + + \ No newline at end of file diff --git a/0.10.0a1+113bd04/searchindex.js b/0.10.0a1+113bd04/searchindex.js new file mode 100644 index 00000000..3dec376c --- /dev/null +++ b/0.10.0a1+113bd04/searchindex.js @@ -0,0 +1 @@ +Search.setIndex({"alltitles": {"Contents:": [[0, null]], "Indices and tables": [[0, "indices-and-tables"]], "Module contents": [[1, "module-merger"], [2, "module-merger.harmony"]], "Submodules": [[1, "submodules"], [2, "submodules"]], "Subpackages": [[1, "subpackages"]], "Welcome to CONCISE (CONCatenatIon SErvice)": [[0, "welcome-to-concise-concatenation-service"]], "merger package": [[1, "merger-package"]], "merger.harmony package": [[2, "merger-harmony-package"]], "merger.harmony.cli module": [[2, "module-merger.harmony.cli"]], "merger.harmony.download_worker module": [[2, "module-merger.harmony.download_worker"]], "merger.harmony.service module": [[2, "module-merger.harmony.service"]], "merger.harmony.util module": [[2, "module-merger.harmony.util"]], "merger.merge module": [[1, "module-merger.merge"]], "merger.merge_cli module": [[1, "module-merger.merge_cli"]], "merger.merge_worker module": [[1, "module-merger.merge_worker"]], "merger.path_utils module": [[1, "module-merger.path_utils"]], "merger.preprocess_worker module": [[1, "module-merger.preprocess_worker"]], "merger.variable_info module": [[1, "module-merger.variable_info"]], "podaac": [[3, "podaac"]]}, "docnames": ["index", "merger", "merger.harmony", "modules"], "envversion": {"sphinx": 61, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.viewcode": 1}, "filenames": ["index.rst", "merger.rst", "merger.harmony.rst", "modules.rst"], "indexentries": {"attr_eq() (in module merger.preprocess_worker)": [[1, "merger.preprocess_worker.attr_eq", false]], "clean_metadata() (in module merger.merge)": [[1, "merger.merge.clean_metadata", false]], "conciseservice (class in merger.harmony.service)": [[2, "merger.harmony.service.ConciseService", false]], "construct_history() (in module merger.preprocess_worker)": [[1, "merger.preprocess_worker.construct_history", false]], "datatype (merger.variable_info.variableinfo attribute)": [[1, "merger.variable_info.VariableInfo.datatype", false]], "dim_order (merger.variable_info.variableinfo attribute)": [[1, "merger.variable_info.VariableInfo.dim_order", false]], "fill_value (merger.variable_info.variableinfo attribute)": [[1, "merger.variable_info.VariableInfo.fill_value", false]], "get_bbox() (in module merger.harmony.util)": [[2, "merger.harmony.util.get_bbox", false]], "get_datetime() (in module merger.harmony.util)": [[2, "merger.harmony.util.get_datetime", false]], "get_granule_url() (in module merger.harmony.util)": [[2, "merger.harmony.util.get_granule_url", false]], "get_group_path() (in module merger.path_utils)": [[1, "merger.path_utils.get_group_path", false]], "get_max_dims() (in module merger.preprocess_worker)": [[1, "merger.preprocess_worker.get_max_dims", false]], "get_metadata() (in module merger.preprocess_worker)": [[1, "merger.preprocess_worker.get_metadata", false]], "get_variable_data() (in module merger.preprocess_worker)": [[1, "merger.preprocess_worker.get_variable_data", false]], "group_path (merger.variable_info.variableinfo attribute)": [[1, "merger.variable_info.VariableInfo.group_path", false]], "init_dataset() (in module merger.merge)": [[1, "merger.merge.init_dataset", false]], "invoke() (merger.harmony.service.conciseservice method)": [[2, "merger.harmony.service.ConciseService.invoke", false]], "is_file_empty() (in module merger.merge)": [[1, "merger.merge.is_file_empty", false]], "is_netcdf_asset() (in module merger.harmony.util)": [[2, "merger.harmony.util.is_netcdf_asset", false]], "main() (in module merger.harmony.cli)": [[2, "merger.harmony.cli.main", false]], "main() (in module merger.merge_cli)": [[1, "merger.merge_cli.main", false]], "max_var_memory() (in module merger.merge_worker)": [[1, "merger.merge_worker.max_var_memory", false]], "merge_max_dims() (in module merger.preprocess_worker)": [[1, "merger.preprocess_worker.merge_max_dims", false]], "merge_metadata() (in module merger.preprocess_worker)": [[1, "merger.preprocess_worker.merge_metadata", false]], "merge_netcdf_files() (in module merger.merge)": [[1, "merger.merge.merge_netcdf_files", false]], "merger": [[1, "module-merger", false]], "merger.harmony": [[2, "module-merger.harmony", false]], "merger.harmony.cli": [[2, "module-merger.harmony.cli", false]], "merger.harmony.download_worker": [[2, "module-merger.harmony.download_worker", false]], "merger.harmony.service": [[2, "module-merger.harmony.service", false]], "merger.harmony.util": [[2, "module-merger.harmony.util", false]], "merger.merge": [[1, "module-merger.merge", false]], "merger.merge_cli": [[1, "module-merger.merge_cli", false]], "merger.merge_worker": [[1, "module-merger.merge_worker", false]], "merger.path_utils": [[1, "module-merger.path_utils", false]], "merger.preprocess_worker": [[1, "module-merger.preprocess_worker", false]], "merger.variable_info": [[1, "module-merger.variable_info", false]], "module": [[1, "module-merger", false], [1, "module-merger.merge", false], [1, "module-merger.merge_cli", false], [1, "module-merger.merge_worker", false], [1, "module-merger.path_utils", false], [1, "module-merger.preprocess_worker", false], [1, "module-merger.variable_info", false], [2, "module-merger.harmony", false], [2, "module-merger.harmony.cli", false], [2, "module-merger.harmony.download_worker", false], [2, "module-merger.harmony.service", false], [2, "module-merger.harmony.util", false]], "multi_core_download() (in module 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