Merge pull request #23 from asfadmin/feature-core-search

Feature core search

CHANGELOG.md

@@ -1,6 +1,6 @@
 # Changelog
 
-## [0.3.1](https://github.com/asfadmin/Discovery-asf_search/compare/v0.2.4...v0.3.1)
+## [0.3.2](https://github.com/asfadmin/Discovery-asf_search/compare/v0.2.4...v0.3.2)
 
 ### Added
 - Layed out framework for INSTRUMENT constants (needs to be populated)
@@ -14,6 +14,15 @@
 - ASFSearchResults now has a geojson() method which returns a data structure that matches the geojson specification
 - ASFProduct now has a geojson() method that produces a data structure matching a geojson feature snippet
 - ASFSearchResults and ASFProduct both have a __str__() methods that serializes the output of their geojson() methods
+- Added CodeFactor shield to readme
+- Now calculates temporal baselines when building a stack
+- New search options: 
+    - min/maxDoppler
+    - min/MaxFaradayRotation
+    - flightLine
+    - offNadirAngle
+    - season
+
 
 ### Changed
 - No longer uses range type for parameters that accept lists of values and/or ranges. Now expects a 2-value tuple.
@@ -24,12 +33,14 @@
 - Flatter structure for constants
 - baseline functionality moved into search group (file restructuring)
 - ASFProduct is no longer a subclass of dict. Instead, metadata has been moved to .properties and .geometry
-- ASFSearchResults is now a subclass of list, for list-like operations
+- ASFSearchResults is now a subclass of UserList, for list-type operations
+- Newly-built stacks are sorted by temporal baselines, ascending
 
 ### Fixed
 - Corrected handling of version number in user agent string
 - unused import cleanup
 - better type hinting on centroid() function
+- Cleaned up cruft from various refactors
 
 ## [0.2.4](https://github.com/asfadmin/Discovery-asf_search/compare/v0.0.0...v0.2.4)
 

README.md

@@ -2,11 +2,11 @@
 
 [![PyPI version](https://img.shields.io/pypi/v/asf_search.svg)](https://pypi.python.org/pypi/asf_search/)
 [![Conda version](https://img.shields.io/conda/vn/conda-forge/asf_search)](https://anaconda.org/conda-forge/asf_search)
-[![Conda platforms](https://img.shields.io/conda/pn/conda-forge/asf_search)](https://anaconda.org/conda-forge/asf_search)
 
 [![PyPI pyversions](https://img.shields.io/pypi/pyversions/asf_search.svg)](https://pypi.python.org/pypi/asf_search/)
 [![PyPI license](https://img.shields.io/pypi/l/asf_search.svg)](https://pypi.python.org/pypi/asf_search/)
 
+[![CodeFactor](https://www.codefactor.io/repository/github/asfadmin/discovery-asf_search/badge)](https://www.codefactor.io/repository/github/asfadmin/discovery-asf_search)
 [![Github workflow](https://github.com/asfadmin/asf_search/actions/workflows/run-pytest.yml/badge.svg)](https://github.com/asfadmin/Discovery-asf_search/actions/workflows/run-pytest.yml)
 
 Python wrapper for the ASF SearchAPI

asf_search/search/product.py → asf_search/ASFProduct.py

@@ -1,18 +1,20 @@
 from typing import Iterable
 import numpy as np
 import json
-from ..download import download_url
+from collections import UserList
+
+from asf_search.download import download_url
 
 
 class ASFProduct:
-    def __init__(self, args):
+    def __init__(self, args: dict):
         self.properties = args['properties']
         self.geometry = args['geometry']
 
     def __str__(self):
         return json.dumps(self.geojson(), indent=2, sort_keys=True)
 
-    def geojson(self):
+    def geojson(self) -> dict:
         return {
             'type': 'Feature',
             'geometry': self.geometry,
@@ -34,13 +36,13 @@ def download(self, dir: str, filename: str = None, token: str = None) -> None:
 
         download_url(url=self.properties['url'], dir=dir, filename=filename, token=token)
 
-    def stack(self) -> list:
+    def stack(self) -> UserList:
         """
         Builds a baseline stack from this product.
 
         :return: ASFSearchResults(list) of the stack, with the addition of baseline values (temporal, perpendicular) attached to each ASFProduct.
         """
-        from .baseline_search import stack_from_product
+        from .search.baseline_search import stack_from_product
 
         return stack_from_product(self)
 

asf_search/search/results.py → asf_search/ASFSearchResults.py

@@ -1,12 +1,10 @@
+from collections import UserList
 import json
-from .product import ASFProduct
 
-class ASFSearchResults(list):
-    def __init__(self, results: dict):
-        super(ASFSearchResults, self).__init__()
-        for product in results['features']:
-            self.append(ASFProduct(product))
+from asf_search.ASFProduct import ASFProduct
 
+
+class ASFSearchResults(UserList):
     def geojson(self):
         return {
             'type': 'FeatureCollection',

asf_search/__init__.py

@@ -1,5 +1,7 @@
 from importlib.metadata import PackageNotFoundError, version
 
+from .ASFProduct import ASFProduct
+from .ASFSearchResults import ASFSearchResults
 from .exceptions import *
 from .constants import *
 from .health import *

asf_search/download/download.py

@@ -2,7 +2,8 @@
 import urllib.parse
 import requests
 from importlib.metadata import PackageNotFoundError, version
-from ..exceptions import ASFDownloadError
+
+from asf_search.exceptions import ASFDownloadError
 
 
 def download_url(url: str, dir: str, filename: str = None, token: str = None) -> None:

asf_search/health/health.py

@@ -1,5 +1,6 @@
 import requests
 import json
+
 import asf_search.constants
 
 def health(host: str = None) -> dict:

asf_search/search/__init__.py

@@ -3,5 +3,3 @@
 from .product_search import product_search
 from .geo_search import geo_search
 from .baseline_search import stack_from_id
-from .product import ASFProduct
-from .results import ASFSearchResults

asf_search/search/baseline_search.py

@@ -1,11 +1,12 @@
-from typing import Iterable
-import numpy as np
-from .search import search
-from .results import ASFSearchResults
-from .product import ASFProduct
-from .product_search import product_search
-from ..constants import INTERNAL, PLATFORM
-from ..exceptions import ASFSearchError, ASFBaselineError
+from dateutil.parser import parse
+import pytz
+
+from asf_search.search import search
+from asf_search.ASFSearchResults import ASFSearchResults
+from asf_search.ASFProduct import ASFProduct
+from asf_search.search.product_search import product_search
+from asf_search.constants import INTERNAL, PLATFORM
+from asf_search.exceptions import ASFSearchError, ASFBaselineError
 
 
 precalc_platforms = [
@@ -35,14 +36,16 @@ def stack_from_product(
     """
 
     stack_params = get_stack_params(reference)
-    stack_results = search(**stack_params, host=host, cmr_token=cmr_token, cmr_provider=cmr_provider)
-    calc_temporal_baselines(reference, stack_results)
+    stack = search(**stack_params, host=host, cmr_token=cmr_token, cmr_provider=cmr_provider)
+    calc_temporal_baselines(reference, stack)
+    stack.sort(key=lambda product: product.properties['temporalBaseline'])
+
 
     #TODO: Calculate temporal baselines
     #TODO: Calculate perpendicular baselines
     #TODO: Add nearest neighbor finder
 
-    return stack_results
+    return stack
 
 
 def stack_from_id(
@@ -68,12 +71,9 @@ def stack_from_id(
         cmr_token=cmr_token,
         cmr_provider=cmr_provider)
 
-    try:
-        if len(reference_results) <= 0:
-            raise ASFSearchError(f'Reference product not found: {reference_id}')
-        reference = reference_results[0]
-    except KeyError as e:
+    if len(reference_results) <= 0:
         raise ASFSearchError(f'Reference product not found: {reference_id}')
+    reference = reference_results[0]
 
     return stack_from_product(reference, host=host, cmr_token=cmr_token, cmr_provider=cmr_provider)
 
@@ -116,6 +116,13 @@ def calc_temporal_baselines(reference: ASFProduct, stack: ASFSearchResults) -> N
     :param stack: The stack to operate on.
     :return: None, as the operation occurs in-place on the stack provided.
     """
-    pass
-
+    reference_time = parse(reference.properties['startTime'])
+    if reference_time.tzinfo is None:
+        reference_time = pytz.utc.localize(reference_time)
+
+    for secondary in stack:
+        secondary_time = parse(secondary.properties['startTime'])
+        if secondary_time.tzinfo is None:
+            secondary_time = pytz.utc.localize(secondary_time)
+        secondary.properties['temporalBaseline'] = (secondary_time - reference_time).days
 

asf_search/search/geo_search.py

@@ -1,8 +1,9 @@
 from typing import Union, Iterable
 import datetime
-from .search import search
-from .results import ASFSearchResults
-from ..constants import INTERNAL
+
+from asf_search.search import search
+from asf_search.ASFSearchResults import ASFSearchResults
+from asf_search.constants import INTERNAL
 
 
 def geo_search(

asf_search/search/granule_search.py

@@ -1,7 +1,8 @@
 from typing import Iterable
-from .search import search
-from .results import ASFSearchResults
-from ..constants import INTERNAL
+
+from asf_search.search import search
+from asf_search.ASFSearchResults import ASFSearchResults
+from asf_search.constants import INTERNAL
 
 
 def granule_search(

asf_search/search/product_search.py

@@ -1,7 +1,8 @@
 from typing import Iterable
-from .search import search
-from .results import ASFSearchResults
-from ..constants import INTERNAL
+
+from asf_search.search import search
+from asf_search.ASFSearchResults import ASFSearchResults
+from asf_search.constants import INTERNAL
 
 
 def product_search(

asf_search/search/search.py

@@ -3,32 +3,40 @@
 from requests.exceptions import HTTPError
 import datetime
 import math
-from .results import ASFSearchResults
-from ..exceptions import ASFSearch4xxError, ASFSearch5xxError, ASFServerError
-from ..constants import INTERNAL
 from importlib.metadata import PackageNotFoundError, version
 
+from asf_search.ASFSearchResults import ASFSearchResults, ASFProduct
+from asf_search.exceptions import ASFSearch4xxError, ASFSearch5xxError, ASFServerError
+from asf_search.constants import INTERNAL
+
 
 def search(
         absoluteOrbit: Iterable[Union[int, Tuple[int, int]]] = None,
         asfFrame: Iterable[Union[int, Tuple[int, int]]] = None,
         beamMode: Iterable[str] = None,
         collectionName: Iterable[str] = None,
+        maxDoppler: float = None,
+        minDoppler: float = None,
         end: Union[datetime.datetime, str] = None,
-        flightDirection: Iterable[str] = None,
+        maxFaradayRotation: float = None,
+        minFaradayRotation: float = None,
+        flightDirection: str = None,
+        flightLine: str = None,
         frame: Iterable[Union[int, Tuple[int, int]]] = None,
         granule_list: Iterable[str] = None,
         groupID: Iterable[str] = None,
         insarStackId: str = None,
         instrument: Iterable[str] = None,
         intersectsWith: str = None,
         lookDirection: Iterable[str] = None,
+        offNadirAngle: Iterable[Union[float, Tuple[float, float]]] = None,
         platform: Iterable[str] = None,
         polarization: Iterable[str] = None,
         processingDate: Union[datetime.datetime, str] = None,
         processingLevel: Iterable[str] = None,
         product_list: Iterable[str] = None,
         relativeOrbit: Iterable[Union[int, Tuple[int, int]]] = None,
+        season: Tuple[int, int] = None,
         start: Union[datetime.datetime, str] = None,
         maxResults: int = None,
         host: str = INTERNAL.HOST,
@@ -42,21 +50,28 @@ def search(
     :param asfFrame: This is primarily an ASF / JAXA frame reference. However, some platforms use other conventions. See ‘frame’ for ESA-centric frame searches.
     :param beamMode: The beam mode used to acquire the data.
     :param collectionName: For UAVSAR and AIRSAR data collections only. Search by general location, site description, or data grouping as supplied by flight agency or project.
+    :param maxDoppler: Doppler provides an indication of how much the look direction deviates from the ideal perpendicular flight direction acquisition.
+    :param minDoppler: Doppler provides an indication of how much the look direction deviates from the ideal perpendicular flight direction acquisition.
     :param end: End date of data acquisition. Supports timestamps as well as natural language such as "3 weeks ago"
+    :param maxFaradayRotation: Rotation of the polarization plane of the radar signal impacts imagery, as HH and HV signals become mixed.
+    :param minFaradayRotation: Rotation of the polarization plane of the radar signal impacts imagery, as HH and HV signals become mixed.
     :param flightDirection: Satellite orbit direction during data acquisition
+    :param flightLine: Specify a flightline for UAVSAR or AIRSAR.
     :param frame: ESA-referenced frames are offered to give users a universal framing convention. Each ESA frame has a corresponding ASF frame assigned. See also: asfframe
     :param granule_list: List of specific granules. Search results may include several products per granule name.
     :param groupID: Identifier used to find products considered to be of the same scene but having different granule names
     :param insarStackId: Identifier used to find products of the same InSAR stack
     :param instrument: The instrument used to acquire the data. See also: platform
     :param intersectsWith: Search by polygon, linestring, or point defined in 2D Well-Known Text (WKT)
     :param lookDirection: Left or right look direction during data acquisition
+    :param offNadirAngle: Off-nadir angles for ALOS PALSAR
     :param platform: Remote sensing platform that acquired the data. Platforms that work together, such as Sentinel-1A/1B and ERS-1/2 have multi-platform aliases available. See also: instrument
     :param polarization: A property of SAR electromagnetic waves that can be used to extract meaningful information about surface properties of the earth.
     :param processingDate: Used to find data that has been processed at ASF since a given time and date. Supports timestamps as well as natural language such as "3 weeks ago"
     :param processingLevel: Level to which the data has been processed
     :param product_list: List of specific products. Guaranteed to be at most one product per product name.
     :param relativeOrbit: Path or track of satellite during data acquisition. For UAVSAR it is the Line ID.
+    :param season: Start and end day of year for desired seasonal range. This option is used in conjunction with start/end to specify a seasonal range within an overall date range.
     :param start: Start date of data acquisition. Supports timestamps as well as natural language such as "3 weeks ago"
     :param maxResults: The maximum number of results to be returned by the search
     :param host: SearchAPI host, defaults to Production SearchAPI. This option is intended for dev/test purposes.
@@ -65,6 +80,8 @@ def search(
 
     :return: ASFSearchResults(list) of search results
     """
+    #TODO: Add more params now that ranges are refigured
+    #TODO: Make sure Ziyi's search case is covered
 
     kwargs = locals()
     data = dict((k,v) for k,v in kwargs.items() if v is not None and v != '')
@@ -74,6 +91,7 @@ def search(
         'absoluteOrbit',
         'asfFrame',
         'frame',
+        'offNadirAngle',
         'relativeOrbit']
     for key in flatten_fields:
         if key in data:
@@ -112,9 +130,10 @@ def search(
             raise ASFSearch4xxError(f'HTTP {response.status_code}: {response.json()["error"]["report"]}')
         if 500 <= response.status_code <= 599:
             raise ASFSearch5xxError(f'HTTP {response.status_code}: {response.json()["error"]["report"]}')
-        raise ASFServerError
+        raise ASFServerError(f'HTTP {response.status_code}: {response.json()["error"]["report"]}')
 
-    return ASFSearchResults(response.json())
+    products = [ASFProduct(f) for f in response.json()['features']]
+    return ASFSearchResults(products)
 
 
 def flatten_list(items: Iterable[Union[float, Tuple[float, float]]]) -> str: