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+ +
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+ +
+
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+ +

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() +
+ +
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+ + + + \ 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 + + + + + + + + + + + + + + + + + +
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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))) +
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+ + + + \ 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 + )
+ +
+ +
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+ + + + \ 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
+ +
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+ + + + \ 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 + + + + + + + + + + + + + + + + + +
+ + +
+ +
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+
+ +
+
+
+
+ +

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 + )
+ +
+ +
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+ +
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+ + + + \ 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 + + + + + + + + + + + + + + + + + +
+ + +
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+ +
+
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+ +

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. 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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]$"); + if (re2.test(w)) + w = w + "e"; + else if (re3.test(w)) { + re = /.$/; + w = w.replace(re,""); + } + else if (re4.test(w)) + w = w + "e"; + } + } + + // Step 1c + re = /^(.+?)y$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + re = new RegExp(s_v); + if (re.test(stem)) + w = stem + "i"; + } + + // Step 2 + re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step2list[suffix]; + } + + // Step 3 + re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; + if (re.test(w)) { + var fp = re.exec(w); + stem = fp[1]; + suffix = fp[2]; + re = new RegExp(mgr0); + if (re.test(stem)) + w = stem + step3list[suffix]; + } + + // Step 4 + re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; + re2 = /^(.+?)(s|t)(ion)$/; + if (re.test(w)) { + var fp = re.exec(w); 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+ +/** + * Simple result scoring code. + */ +if (typeof Scorer === "undefined") { + var Scorer = { + // Implement the following function to further tweak the score for each result + // The function takes a result array [docname, title, anchor, descr, score, filename] + // and returns the new score. + /* + score: result => { + const [docname, title, anchor, descr, score, filename] = result + return score + }, + */ + + // query matches the full name of an object + objNameMatch: 11, + // or matches in the last dotted part of the object name + objPartialMatch: 6, + // Additive scores depending on the priority of the object + objPrio: { + 0: 15, // used to be importantResults + 1: 5, // used to be objectResults + 2: -5, // used to be unimportantResults + }, + // Used when the priority is not in the mapping. + objPrioDefault: 0, + + // query found in title + title: 15, + partialTitle: 7, + // query found in terms + term: 5, + partialTerm: 2, + }; +} + +const _removeChildren = (element) => { + while (element && element.lastChild) element.removeChild(element.lastChild); +}; + +/** + * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping + */ +const _escapeRegExp = (string) => + string.replace(/[.*+\-?^${}()|[\]\\]/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( + '" + ) + ); + }, + + /** + * 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

+ +
+ 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 + + + + + + + + + + + + + + + + + + + + + + + + \ 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

+ +
+ 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 + + + + + + + + + + + + + + + + + + + + +
+ + +
+ +
+
+
+
    +
  • + +
  • +
  • +
+
+
+
+
+ + + + +
+ +
+ +
+
+ +
+
+
+
+ + + + + + + + + \ 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, 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